Scotland’s businesses, infrastructure, communities and natural environment face increasingly severe climate change impacts. Yet, the actions required to adapt to those changes – how they will evolve over time, what they will cost, and who should pay – remain poorly understood.  

This report provides the first estimate of Scotland’s climate adaptation investment needs through to 2040 across five sectors:  

  • agriculture;  
  • communities (focused on flooding);  
  • the natural environment (focusing on woodland creation, peatland, nature restoration); 
  • transport (focusing on trunk roads, motorways, railways); and  
  • water (focusing on public water and wastewater services).  

This work is intended to support the Scottish Government in building an evidence base ahead of the fourth Scottish National Adaptation Plan (SNAP4). 

Estimating future adaptation cost is inherently challenging. It requires assumptions about future warming, the level of climate risk that society are willing to tolerate, and the associated scale of adaptation and residual damages. Deep uncertainty in climate projections, socioeconomic change, asset vulnerability, and political priorities make precise modelling both challenging and resource intensive.  

As a result, the findings in this report should be treated as pragmatic, evidence-based approximations that indicate the order of magnitude of investment needs—not definitive targets

Estimated climate adaptation investment need  

Adaptation investment needs across the sectors and subsectors assessed in this study are estimated at £7.8–£14.2 billion between 2026 and 2040, or £566–£1,027 million per year.  

Previous estimates from the Climate Emergency Response Group, Paul Watkiss Associates, and the Office for Budget Responsibility suggested Scotland’s total adaptation costs would range from £196 million to £1,340 million per year from 2030 onwards. These are based on UK wide analyses and international benchmarks. Sector specific estimates in this study fall within that range. However, because this analysis covers fewer sectors than the Scottish National Adaptation Plan, the findings suggest that Scotland’s full adaptation investment needs may be higher than previously anticipated. 

The results in this report carry low confidence and should be viewed as indicative, not precise.  The sector-specific figures represent order of magnitude estimates designed to inform policy discussion and future research, rather than definitive costings. 

The macroeconomic effects of investing in climate adaptation  

This research also looks at macroeconomic modelling to estimate the wider economic effects of similar levels of adaptation spending.  

A full assessment of the macroeconomic costs and benefits of adaptation were beyond the scope of the study. However, the study did model the direct economic effects of adaptation spending across sectors. It also explored how different approaches to cost recovery affect economic activity, employment, and household incomes. 

The modelling consistently shows that adaptation spending generates a positive economic stimulus during the investment period, supporting jobs and output particularly in construction, engineering, and land-based supply chains. However, the way costs are recovered – whether through income-tax, charges or through public spending cuts – matters considerably. 

How will costs be borne by households, businesses, and the public sector? 

The researchers made additional analysis of how adaptation costs might be shared between the public and private sectors. 

The study investigated how adaptation is currently funded in each of the sectors. Climate adaptation in Scotland is currently funded predominantly by the public sector. However, households and businesses pay more than previously understood, through Council Tax and Non-domestic rates. Households and businesses also bear some costs directly, for example through property-level insurance and on-farm investments, but this remains modest in most sectors. 

This balance is unlikely to shift fundamentally. Most of the adaptation investment – including flood protection, transport resilience, and natural flood management – generates little or no direct financial return and is therefore structurally dependent on public funding. Analysis suggests that approximately three-quarters of adaptation investment needs will require public financing regardless of innovations in private finance mechanisms. 

Scope to boost private sector participation 

The study reviewed the innovative funding and financing models being used internationally and within Scotland. Analysis found that there is modest potential to increase private sector participation in adaptation funding and financing across all five sectors, and a range of innovative mechanisms are emerging. These include parametric insurance in agriculture, biodiversity credits and voluntary carbon markets in the natural environment, green and resilience bonds for flood and transport infrastructure, and catchment co-investment models in water.  

Recommendations 

The research report includes several recommendations for further research. These include developing adaptation targets and risk tolerance thresholds, strengthening the evidence base for the “triple dividend”, and creating frameworks for prioritising actions that account for rural vulnerability, social equity, and Just Transition principles. 

For additional recommendations and details of how the investment estimate where reached, please read the report.  

If you require the report in an alternative format, such as a Word document, please contact info@climatexchange.org.uk or 0131 651 4783.

Research completed: March 2026

DOI: https://doi.org/10.7488/era/7087

Executive summary

Background and purpose

Scotland’s businesses, infrastructure, communities and natural environment face increasingly severe climate change impacts. Yet, the required adaptation actions – how they will evolve over time, what they will cost, and who should pay – remain poorly understood.

This report provides the first estimate of Scotland’s climate adaptation investment needs through to 2040 across five sectors (and eight subsectors):

  • agriculture;
  • communities (flooding);
  • the natural environment (woodland creation, peatland, nature restoration);
  • transport (trunk roads, motorways, railways); and
  • water (public water and wastewater services).

It then presents two further discrete analyses: macroeconomic modelling to estimate the wider economic effects of similar levels of adaptation spending, The five sectors were chosen to reflect the diverse approaches required to assess indicative adaptation costs. We examine four aspects of climate adaptation investment: required investment, its macroeconomic impacts, public-private funding splits, and the potential to mobilise private capital. This work is intended to support the Scottish Government in building an evidence based ahead of the fourth Scottish National Adaptation Plan (SNAP4).

Estimating future adaptation cost is inherently challenging. It requires assumptions about future warming, the level of climate risk that society are willing to tolerate, and the associated scale of adaptation and residual damages. Deep uncertainty in climate projections, socioeconomic change, asset vulnerability, and political priorities make precise modelling both challenging and resource intensive. As a result, the findings in this report should be treated as pragmatic, evidence-based approximations that indicate the order of magnitude of investment needs—not definitive targets.

Why adaptation investment matters

Failing to invest in mitigation and adaptation carries significant economic costs. Estimates for this study suggest climate change could reduce GDP by 0.3-0.4% a year in the 2030s, rising to 1.2-1.6% by the 2050s and 1.6-3.3% by the 2070s. Other studies project higher impacts but these depend on the models and assumptions used. The Scottish Environment Protection Agency estimate that flooding alone already costs Scotland an estimated £500 million per year. Adaptation can reduce these damages, but it also requires upfront investment, is rarely fully effective, and involves trade‑offs between expenditure and residual risk. The key question is therefore not whether to invest in adaptation, but how much and who should pay.

Adaptation investment also delivers wider benefits, often described as the “triple dividend”: avoided losses, economic gains, and social and environmental co-benefits such as biodiversity improvements, carbon sequestration, and better mental health. These co-benefits further strengthen the economic case for adaptation.

Climate costs are projected to rise significantly beyond 2040. The research and strategic priorities below are therefore time-sensitive: early action on adaptation can reduce long-run costs and delivers benefits that delayed investment may not recover.

Estimated climate adaptation investment need for Scotland in five sectors

Adaptation investment needs across the five sectors and eight subsectors assessed in this study are estimated at £7.8–£14.2 billion between 2026 and 2040, or £566–£1,027 million per year. Sector and subsector level results are shown in Table 1.

Previous estimates from the Climate Emergency Response Group, Paul Watkiss Associates, and the Office for Budget Responsibility – based on UK wide analyses and international benchmarks – suggested Scotland’s total adaptation costs would range from £196 million to £1,340 million per year from 2030 onwards. The sector specific estimates in this study fall within that range. However, because this analysis covers fewer sectors than the Scottish National Adaptation Plan, the findings suggest that Scotland’s full adaptation investment needs may be higher than previously anticipated.

The study also compared the estimated annual adaptation investment needs to current allocations in the Scottish budget. It found that only the agriculture sector is likely meeting its adaptation needs. The communities (flooding), transport, and nature sectors will likely require additional investment to maintain current risk levels. We could not assess the water sector due to a lack of available information on existing adaptation spending.

The results in this report carry low confidence and should be viewed as indicative, not precise. Confidence levels vary by sector (Table 1) due to fragmented data, limited understanding of asset vulnerability, and the lack of clear adaptation targets to scale investment needs. Where Scottish specific data was unavailable, we crosschecked estimates with international comparisons, which also have limitations because of differing risks and institutional contexts. These figures therefore represent order of magnitude estimates designed to inform policy discussion and future research, rather than definitive costings.

Table 1: Climate adaptation investment estimates for 14 years 2026/27 to 2039/40 across five sectors and their key sub-sectors (2026/27 prices). Where available, current budget (or estimates) are presented alongside estimated investment need, with a RAG rating indicating whether current spend meets the estimated need (green), falls within 20% below it (amber), or is more than 20% below it (red). A confidence rating is assigned to each investment estimate, alongside the primary source from which the investment estimate was derived.

Sector

Sub-sector / approach

Investment estimate (£m)

Investment estimate (£m/yr)

2026/27 budget (£m/yr)

Confidence

Investment estimate source

Agriculture

 

£2,347m – £3,091m

£167.6m– £220.8m


£167.6m – £220.8m



Low


Scottish Government Budget

Communities

Capacity building

£102m

£7.3m


£6.9m


Medium

Scottish Government Budget

Property flood protection

£885m – £1,102m

£63.2m – £78.7m


£42m


Low

Scottish Government & DEFRA, HM Government

Property flood resilience

£10.5m – £52m

£0.8m – £3.7m

Unknown

Medium

JBA Risk Management2025

Natural environment

Woodland creation

£115m

£8.2m


£2.3m


Low – Medium

Scottish Government Draft Climate Change Plan

Peatland restoration

£236m

£16.8m


£5.6m


Low – Medium

Scottish Government Draft Climate Change Plan

Natural restoration

£73m

£5.2m


£5.2m


Low – Medium

NatureScot

Transport

Rail[1]

£1,582m – £4,734m

£113m- £338.1m


≈ £87.8m


Medium

Network Rail Scotland

Trunk roads and motorways

£1,418m – £2,213m

£101.3m – £158.1m


£82.3m


Very low

Scottish Government Budget

Water

Scottish Water[2]

£1,067m – £2,466m

£82.1m – £189.7m

Unknown

Medium

Scottish Water

Total

 

£7,835.5m – £14,182.8m

£565.5m – £1,026.6m

   

The macroeconomic effects of investing in climate adaptation

A full assessment of the macroeconomic costs and benefits of adaptation were beyond the scope of the study. However, the study did model the direct economic effects of adaptation spending across sectors. It also explored how different approaches to cost recovery affect economic activity, employment, and household incomes.

The modelling consistently shows that adaptation spending generates a positive economic stimulus during the investment period, supporting jobs and output particularly in construction, engineering, and land-based supply chains. However, the way costs are recovered matters considerably. Income-tax-based recovery is progressive but dampens household consumption and reduces activity in consumer-facing sectors. Charging-based approaches – such as higher food prices in agriculture or water bills in the water sector – tend to be regressive, falling disproportionately on lower-income households for whom essential goods represent a larger share of budgets. Recovery through public spending cuts generates the most widespread economic losses, particularly across service sectors. Funding design is therefore important to consider alongside investment scale.

These results should not be interpreted as a full cost-benefit assessment of adaptation. The modelling captures the demand-side effects of spending and cost recovery, but does not account for avoided climate damages, residual risks, or the broader triple dividend of adaptation.

How will costs be borne by households, businesses, and the public sector?

The study investigated how adaptation is currently funded in each of the sectors. Climate adaptation in Scotland is currently funded predominantly by the public sector. Central and local government fund and finance most adaptation-relevant expenditure across transport, flood management, water infrastructure, agriculture, and the natural environment. This is largely through existing budget lines that deliver multiple objectives alongside adaptation. However, households and businesses pay more than previously understood, through Council Tax and Non-domestic rates. Households and businesses also bear some costs directly, for example through property-level insurance and on-farm investments, but this remains modest in most sectors.

This balance is unlikely to shift fundamentally. Most of the adaptation investment – including flood protection, transport resilience, and natural flood management – generates little or no direct financial return and is therefore structurally dependent on public funding. Analysis suggests that approximately three-quarters of adaptation investment needs will require public financing regardless of innovations in private finance mechanisms.

Scope to boost private sector participation

The study reviewed the innovative funding and financing models being used internationally and within Scotland. Analysis found that there is modest potential to increase private sector participation in adaptation funding and financing across all five sectors, and a range of innovative mechanisms are emerging. These include parametric insurance in agriculture, biodiversity credits and voluntary carbon markets in the natural environment, green and resilience bonds for flood and transport infrastructure, and catchment co-investment models in water. However, several important caveats apply:

  • Scaling private investment will not happen through market forces alone. It will require concerted public policy action, enabling conditions, and in many cases public co-financing to de-risk private investment. The private sector’s role is best understood as complementary to, rather than a substitute for, public adaptation finance.
  • There is a critical distinction between private financing (where private capital provides upfront funding) and private funding (where costs are ultimately borne by the private sector rather than transferred back to government or consumers). Many instruments that appear to increase private participation in practice shift the funding burden, rather than share it. Policy ambitions to mobilise private capital should be assessed against this distinction.
  • High benefit-cost ratios in the adaptation literature typically reflect societal and environmental returns, including non-market values that generate no cash flow. Private investors assess financial returns, incremental revenues and recoverable costs, which are considerably lower. Treating strong societal co-benefit ratios as evidence of private investment attractiveness risks generating unrealistic expectations about the scale of private finance that can realistically be mobilised.

Recommendations

The report lays out the following key recommendations, in no particular order:

Table 2: Key recommendations for further research and strategic priorities.

Theme

Research priority

Strategic priority

Adaptation targets, objectives & risk tolerance

  • Develop quantified adaptation targets and sector specific risk tolerance thresholds. Use these to conduct gap analyses and support SNAP4.
  • Recognise that sectors are at different stages of the adaptation investment cycle and develop sector-differentiated investment strategies accordingly.

Asset level vulnerability & investment pipelines

  • Develop spatially referenced vulnerability inventories across all sectors to prioritise sites, assets, and interventions, integrating existing datasets such as SEPA flood risk assessments.
  • Build investment-ready pipelines capable of attracting both public and private finance at scale, moving from risk assessment towards costed, prioritised investment programmes.

Financial transparency & attribution

  • Develop methods to isolate adaptation specific spending in agriculture and assess funding adequacy.
  • Improve budget reporting so adaptation spending is clearly distinguished from mitigation and other objectives.
  • Embed adaptation objectives within existing spending programmes (e.g., infrastructure maintenance, housing retrofit) through improved budget tagging and apportionment guidance.

Triple dividend evidence base

  • Avoided losses: Strengthen evidence on avoided damages across sectors.
  • Economic stimulus: Quantify employment, supply chain, and distributional impacts.
  • Co-benefits: Assess wider social and environmental co-benefits.
  • Use fuller quantification of the triple dividend to build the economic case for public investment in adaptation.

Distributional impacts

  • Analyse how different financing mechanisms (tax, price, charges) affect different groups.
  • Identify compensatory policies to ensure fair and equitable funding.

Cross‑sector collaboration

  • Explore catchment‑scale approaches that deliver multiple co‑benefits.
  • Map how adaptation priorities can be embedded within civil contingencies, biodiversity governance, spatial planning, and infrastructure regulation.
  • Create mechanisms for sharing research and delivery across sectors, building on existing networks such as the CRIS Forum.

Prioritisation

 
  • Develop prioritisation frameworks that account for rural vulnerability, social equity, and Just Transition principles.

Private finance mobilisation

 
  • Develop a coherent national approach identifying appropriate mechanisms for each sector, the enabling conditions required, and how public co-financing can de-risk private investment.
  • Draw on international experience with blended finance, green bonds, and nature finance.

Monitoring and evaluation

 
  • Develop an adaptation investment monitoring and evaluation framework, aligned with SNAP3 but capturing financial flows and asset-level outcomes.

Glossary

Annual Average Loss (AAL)

The expected average financial loss from flood events in any given year, calculated across all possible flood scenarios weighted by their probability of occurrence.

Adaptation pathways

A planning approach that sequences adaptation actions over time, allowing for adjustments as climate change and its impacts become better understood.

Bottom-up costing

An approach to estimating adaptation investment needs that builds cost estimates from detailed, project-level information gathered from engineers, contractors and technical specialists, or from specific policy objectives where budget lines can be scaled up.

Computable General Equilibrium model (CGE model)

An economic modelling framework that simulates the interactions between different sectors of an economy to assess the broader macroeconomic impacts of policy changes or external shocks, such as climate change.

2026/27 Climate Taxonomy

A classification system, published alongside the Scottish Government budget, that identifies budget lines according to their impact on climate change mitigation and adaptation.

Community Benefit Funds (CBFs)

A community benefit fund is a voluntary, typically annual, financial contribution provided by developers to local communities hosting major projects, such as renewable energy sites.

Consumer Price Index (CPI)

Presents the percentage change in prices that consumers pay for goods and services.

Control Period (CP)

Network Rail’s fixed five-year funding and planning cycle that sets budgets and outputs for the railway (e.g. CP7: 1 April 2024 – 31 March 2029).

Expected Annual Damages (EAD)

The average annual financial cost of flood damage calculated across return periods, accounting for both the likelihood and severity of events.

Gross Value Added (GVA)

A measure of the value of goods and services produced in an area, industry or sector of an economy, used here as a proxy for scaling adaptation investment estimates across countries.

Major Capital Investment (MCI)

Large-scale, transformational infrastructure schemes where continued operations would otherwise become impossible as a result of a changing climate.

Natural Flood Management (NFM)

An approach to reducing flood risk that works with natural processes, for example through wetland creation, tree planting or river restoration, to slow the flow of water and reduce peak flood levels.

Organisation for Economic Co-operation and Development (OECD)

An international, intergovernmental forum of 38 developed market-based economies established in 1961 to stimulate economic progress and world trade. Headquartered in Paris, it provides data, policy analysis, and standards to promote prosperity, equality, and well-being.

Office for Budget Responsibility (OBR)

The Office for Budget Responsibility was created in 2010 to provide independent and authoritative analysis of the UK’s public finances.

Operations, Support, Maintenance and Renewals (OSMR)

The category of Network Rail Scotland investment covering day-to-day operational response to weather, preventative and reactive maintenance, and asset renewals.

Property Flood Resilience (PFR)

Measures applied at the individual property level to reduce the risk of flooding or minimise flood damage, such as flood doors, air brick covers, or non-return valves.

Potential Vulnerable Areas (PVAs)

Areas identified by SEPA as being at significant risk from flooding, which form the basis for Flood Risk Management Planning in Scotland.

Representative Concentration Pathway (RCP)

A greenhouse gas concentration trajectory used in climate modelling to represent different possible futures based on varying levels of emissions (e.g. RCP 4.5 is a moderate emissions scenario; RCP 8.5 is a high emissions scenario).

Residual damage

The climate-related losses or damages that remain even after adaptation measures have been implemented, reflecting the limits of adaptation effectiveness.

Scottish Environment Protection Agency (SEPA)

Scotland’s environmental regulator, responsible for flood risk assessment, flood warning, and producing Scotland’s Flood Risk Management Plans.

Scottish National Adaptation Plan 3 (SNAP3)

The third Scottish National Adaptation Plan, covering 2024–2029, setting out actions to achieve five national outcomes for climate resilience across society, the economy and the environment.

Scottish National Adaptation Plan 4 (SNAP4)

The fourth Scottish National Adaptation Plan will cover 2029 – 2034, setting out actions to better adapt Scotland to the changing climate.

Strategic Review 27 (SR27)

Scottish Water’s regulatory investment planning period covering 2027–2032, within which adaptation investment needs are assessed and costed.

Sustainable Urban Drainage Systems (SUDS)

Drainage infrastructure designed to manage surface water in a way that mimics natural drainage, reducing flood risk, improving water quality and enhancing the urban environment.

Top-down costing

An approach to estimating adaptation investment needs that uses economic models and sector-level damage assessments to derive aggregate cost estimates, typically without detailed project-level information.

Triple dividend

The three categories of benefit that adaptation investment can deliver: (1) avoided climate losses; (2) wider induced economic benefits such as infrastructure investment stimulus; and (3) social and environmental co-benefits such as biodiversity gains and improved mental health.

UK Climate Projections 2018 (UKCP18)

The most recent set of probabilistic climate projections for the UK, produced by the Met Office, used to inform climate risk assessments and adaptation planning across multiple sectors.

Value transfer

A method of estimating costs or benefits by applying findings from existing studies in comparable contexts (e.g. other countries or regions) to a new setting, adjusted for relevant differences such as economic scale or population.

Introduction

Overview, aim and scope

Tackling the climate emergency is a priority area for the Scottish Government – alongside eradicating child poverty and growing the economy and delivering high quality sustainable public services (Scottish Government, 2025a). As part of tackling the climate emergency, three questions have emerged associated with the need to better understand:

  • The costs of the Scottish Government climate change ambitions for adaptation and the residual damage of necessary trade-offs.
  • The macroeconomic effects of climate impacts and adaptation.
  • How these costs are being met today, and options for how these costs will be met by different groups, including public and private sectors.

This project provides an initial exploration of some of these issues. In doing so, it supports the Scottish Government in developing an evidence base on the potential costs of climate adaptation across a range of sectors. This is important information to assist in strategically planning and driving forward future adaptation action, in line with Scotland’s National Adaptation Plan.

The analysis focuses on three interconnected research objectives:

  1. Estimate adaptation investment needs for five sectors – agriculture, communities (focusing on flooding), natural environment (woodland creation, peatland restoration and nature restoration), transport (trunk roads and motorways and railways), and water (supply and treatment) – until 2040. This should be aligned with the with adaptation objectives defined in the Scottish National Adaptation Plan 3 (SNAP3) 2024–2029;
  2. Assess the likely investment split, over time, between the public sector, private sector businesses and individuals for each sector; and
  3. For each sector, identify the potential to support private sector participation in funding and financing adaptation, highlighting barriers to scale, and recommending policy instruments to mobilise private capital.

Context: climate risks in Scotland

Scotland’s businesses, infrastructure, communities and environment are becoming increasingly exposed to climate change. These impacts carry serious economic consequences.

The estimated impact of climate change on the UK’s economy differs depending on the climate scenarios used and wider socio-economic assumptions made within modelling. This study assessed the results for Scotland using results from a major EU project (Bosello et al., 2020). Across several climate scenarios, these suggests that from 2030 Scotland’s economy could be 0.3 – 0.5% smaller each year. By 2050, losses could rise to 1.2 – 1.6%, increasing further to 1.5 –3.3% by the 2070s. These are shown in Figure 1, and have been used as the basis for supporting subnational assessments of economic impacts in Scotland (e.g. Climate Ready Clyde, Highland Adapts, South East Scotland and Forth Valley).

Figure 1: Projected impact of climate change on GVA in Scotland for a range of future climate scenarios using Shared Socioeconomic Pathways 2 (SSP2). High Investment Mobility. SSP2 is also known as ‘middle of the road’ and assumes the world follows a path in which social, economic and technological trends to not shift markedly from historical patterns…

A second study, Rising et al. (2022), included additional risks, such as low-probability high-impact events, projecting that under current policies – and compared to a 2000 baseline – the total cost of climate change damages to the UK are projected to increase from 1.1% of GDP at present to 3.3% by 2050 and up to 7.4% by 2100 (Rising et al., 2022). Furthermore, the Office for Budget Responsibility (OBR) estimate that the cost of climate change could even reduce the UK level of GDP by 8% by 2070 if the world was to warm by 3oC by the end of the century (Office for Budget Responsibility, 2025).

While adaptation can significantly limit climate related damages, fully eliminating climate risk is neither technically feasible nor economically rationale (Rexer & Sharmer, 2024). This means that even robust adaptation actions will leave some residual risk, highlighting the need to target measures that deliver the greatest benefit relative to their cost.

The Climate Change (Scotland) Act 2009 requires a National Adaptation Plan to be published every five years, aligned with the latest UK Climate Change Risk Assessment (CCRA). The latest, SNAP3, covers 2024 – 2029. SNAP3 sets out outcomes, delivery objectives and policy actions. It the first UK Adaptation Plan to also be supported by a monitoring and evaluation framework to track progress. However, specific objectives around risk reduction, as well as associated costs or budgetary allocations remain undefined in Scotland and across the UK.

As the Scottish Government prepares to receive the upcoming fourth UK Climate Change Risk Assessment (CCRA4) and Well Adapted UK report, there is growing recognition of the need to be more specific about the assumptions underpinning adaptation planning, and the costs and benefits. The Climate Change Committee (CCC) recommends that the Scottish Government introduce quantified, timebound adaptation targets to better track progress and strengthen accountability, consistent with preparing for +2°C warming by 2050 while managing risks associated with up to +4°C by the end of the century (Scottish Government, 2025b). However, setting such targets requires clarity on the level of climate risk that government and society are willing to tolerate.

This raises the important question of the acceptable level of risk, and for whom. Different communities, sectors and social groups will be affected in different ways. Given these complexities, developing adaptation targets will likely require broader engagement, including opportunities for the public and stakeholders to contribute to discussions about acceptable levels of risk. It also involves considering who pays – raising questions of equity and risk ownership. As such, adaptation target setting can be closely linked to Just Transition principles.

Defining the level of climate risk that is acceptable is therefore closely associated with the question of how much adaptation investment is needed, and who should pay for it.

Yet current evidence on these questions for Scotland is limited. There are partial estimates of adaptation investment need within the literature, but no agreed sector-specific adaptation targets, no systematic estimates of the investment required to meet them, and no established framework for understanding how costs should be shared between the public sector, private sector, and individuals.

This gap matters: without a clearer picture of adaptation investment needs, it is difficult to plan strategically, allocate budgets effectively, or make the case to mobilise private capital alongside public expenditure. But it is also challenging due to the deep uncertainty of climate change – including our warming trajectories and socioeconomic change.

This report seeks to begin closing that gap. Drawing on a range of analytical methods and the best available evidence across five sectors – agriculture, communities (flooding), transport, water, and the natural environment – it provides indicative estimates of Scotland’s adaptation investment needs to 2040, an assessment of public-private investment splits, and an exploration of opportunities to increase private sector participation in financing Scotland’s adaptation.

This report is structured as follows:

  • Section 2 sets out a general account of the economics of adaptation. This sets out the conceptual framework for estimating investment needs, and approaches exploring the public-private investment split. It also positions the existing evidence base for Scotland.
  • Section 3 presents our approach and methods.
  • Section 4 provides sector-specific results for agriculture, communities (floods), the natural environment, transport, and water. It explores adaptation investment needs, macroeconomic effects and wider impacts, and funding and financing arrangements across all five sectors.
  • Section 5 presents a summary of our analysis
  • Section 6 outlines recommended research and strategic priorities.

The economics, costing and financing of adaptation

The economics of adaptation

In simple terms, adaptation costs and benefits can be estimated by first assessing the current and future impacts of climate change, then evaluating how much these impacts can be reduced and at what cost (Boyd and Hunt, 2004; UNFCCC, 2009). Adaptation measures can substantially reduce damages, but even well-designed strategies involve trade-offs: investing more in adaptation may deliver greater risk reduction but also increases cost. As a result, reducing risk to zero is neither technically feasible nor economically desirable, and some residual risk will always remain (Rexer & Sharma, 2024).

The scale of costs and benefits depends heavily on chosen objectives. For example, whether aiming for economic efficiency, reducing risks to acceptable levels, or maintaining today’s relative level of climate risk despite worsening conditions. In practice, estimating adaptation costs is highly complex because of deep uncertainty, with issues of socioeconomic change, future emissions, climate models, regional scenarios, impacts, adaptation responses, and political priorities combining to make modelling challenging (Wilby and Dessai, 2010; Taylor et al., 2025; Valverde et al., 2022). These uncertainties make it challenging to assess costs and benefits, creating the potential for over or underestimation of investment.

Despite this, there are some examples. These include national design standards for flood risk (e.g.to a 1-in-200-year event in Scotland, or up to 1-in-10,000-year in the Netherlands (Westerhof et al., 2023)), and emerging work on resilience in warming trajectories more broadly. The UK Government’s Long Term Investment Scenarios explore the optimum levels of investment under different climate scenarios and then use that to guide the spending envelope in the UK’s Flood and Coastal Erosion Risk Management (Environment Agency, 2021). And on reference scenarios, the Climate Change Committee has advised the UK Government to plan for 2 degrees of warming and prepare for 4, while in France the French Government has adopted a reference trajectory of four degrees.

Furthermore, adaptation investment can deliver multiple co-benefits, collectively known as the ‘triple dividend’ (Global Commission on Adaptation, 2019):

  • The first dividend relates to avoided losses from successful adaptation. For example, a home that doesn’t flood because flood defences were built.
  • The second relates to induced economic benefits such as the stimulus to the economy. For example, from capital investment in infrastructure development projects.
  • The third includes social and environmental benefits. For example, afforestation projects that slow water runoff to rivers provide flood mitigation but also deliver biodiversity gains, carbon sequestration, and mental health benefits through green space access.

Considering all three dividends has the potential to improve the economic rationale of investing in climate change adaptation (Figure 2). In this report, while our analyses partially explore triple dividend benefits, it is beyond the scope of work to comprehensively consider wider savings made on triple dividends (see Section 8 on next steps).

Figure 2: The economics of adaptation. The orange line shows projected climate change impacts on GDP (%) without adaptation; the teal line shows residual damages with adaptation. The gap between them represents the gross benefits of adaptation – subtracting the cost of adaptation yields the net benefits, comprising components such as avoided losses and economic, social and environmental co-benefits. Shaded areas indicate indicative uncertainty ranges only. The benefit breakdown is illustrative and not to scale. Adapted from Boyd and Hunt (2004), Global Commission on Adaptation (2019), and Watkiss et al. (2026a).

Apportioning adaptation costs

A key challenge in estimating adaptation investment needs is defining what constitutes ‘adaptation’ and how to attribute costs when activities serve multiple purposes. Climate adaptation rarely occurs in isolation – it is typically integrated into broader investment programmes, delivered alongside other policy objectives, or embedded within routine infrastructure maintenance and renewal. This raises practical questions for cost estimation: should we count the full cost of a project that includes adaptation as one of several objectives, or only the incremental cost of climate-proofing measures above a baseline investment?

To address this, the study adopted the adaptation cost taxonomy developed by the Multilateral Development Banks (MDBs), which has been widely applied internationally to track adaptation finance and compare investment needs across countries (MDB, 2022). This taxonomy categorises adaptation investments into three types based on the role adaptation plays in the overall investment (Figure 3):

Figure 3 Taxonomy of adaptation costs. Adapted from Watkiss et al. (2026a) based on Multilateral Development Banks (2023).

  • Building climate adaptation into proposed programmes and investments (climate proofing). For example, to include climate change in the design standards for new road investments. In this case, adaptation is not a major objective. Instead, assessments investigate the incremental costs of adaptation, over and above the core programme / investment costs.
  • Targeted/pure adaptation programmes and investments (targeted adaptation). In this case, the primary objective of the policy, programme or project is adaptation to climate change. For example, investing in coastal flood protection to address sea-level rise. In this case, the total costs of the investment are counted as adaptation.
  • Investments with multiple benefits that include adaptation (mixed objectives). Sitting between the two extremes above are a set of cases where adaptation is one of several objectives of the policy, programme or project (a secondary or significant objective). For example, investing in peatland restoration will lead to greater resilience of the peatland (to climate change) as well as off-site benefits (water management) but this investment is primarily associated with biodiversity and ecosystem services. In this case a proportion of the cost is attributed to adaptation, but this is often difficult to do accurately and involves more subjective decisions.

These distinctions are important for climate adaptation investment estimation and the economic rationale for investment. However, this categorisation can create potential for confusion in practice. Activities that might have been pursued primarily for economic development, environmental restoration, or other policy goals can be classified as ‘adaptation’ if they deliver climate resilience benefits – even when adaptation was not the original or primary driver. This raises important questions about additionality: would the investment have proceeded anyway without climate considerations?

Approaches to costing adaptation investment

International approaches

There is no single ‘correct’ method for costing climate adaptation. Instead, there are a variety of approaches, and the most appropriate approach depends on the context. Factors such as specific objectives, analysis level, measure types, and critically, the available data and resources all influence the choice (World Bank, 2024; Taylor et al., 2025).

Climate adaptation objectives can be framed in several ways – by setting targets based on future warming levels, engineering resilience standards, specific risk reduction goals, economic thresholds, or process-based requirements (World Bank, 2024). Each framing influences the scale of action, investment needs, and acceptable levels of residual risk. These choices shape how ambitious adaptation efforts must be, the types of projects prioritised, and the balance between public, private, and household responsibilities. Higher resilience standards typically require greater upfront investment, while economic optimal or process-based approaches may lower costs but leave more risk unaddressed (Taylor et al., 2025).

Costing methodologies exist on a spectrum: ‘top-down, science-first’ approaches use economic models and sector-level damage assessments to estimate aggregate costs, while ‘bottom-up, policy-first’ approaches build estimates from detailed project-level information gathered from contractors, engineers, and technical specialists, focused on answering specific near-term questions. There are also hybrid methods that blend top-down and bottom-up approaches. The World Bank identifies various tools and approaches for both sets of methods including top-down sector integrated assessment models (IAMs), computable general equilibrium (CGE) models, through to bottom-up sector-based costing, climate adaptation markups, and budget tagging approaches at the more granular level (World Bank, 2024).

The most accurate estimates for appraisal or project delivery come from bottom-up costing based on detailed contractor quotes. However, this approach requires substantial resources, data availability, time, and technical capacity to progress projects through to a level of maturity which can provide this, and this is not always available (Taylor et al., 2025).

European estimates

Multiple European countries have recently attempted to quantify their national adaptation investment needs, each developing similar, yet distinct, methodologies suited to their institutional context and data landscape. To inform the approach to Scotland, this study reviewed literature from these studies and drew key lessons from each, as follows:

Austria took a parallel approach (Knittel et al. 2017), adopting a top-down budget review using expert interviews to assign flexible apportionments of current spending to climate adaptation (such as 60% for flood infrastructure for example) and bottom-up costing of 67 National Adaptation Strategy measures grouped into cost bands. The two methods produced different results, €488m/yr versus €385m/yr respectively, revealing they measured fundamentally different things: current government activity versus strategic intent (Knittel et al., 2017).

France compiled existing estimates across 15 policy areas, gathering what stakeholders had already produced and providing unit-cost benchmarks from completed projects. It was openly acknowledged this represented ‘what exists’ in planning discussions rather than rigorous comprehensive costing (Dolques et al., 2025).

Spain aggregated funding from multiple sources, historical environmental spending, COVID recovery allocations, and department budgets, applying different percentages based on how directly measures addressed adaptation (100% for flood defences, 40% for ecosystem restoration, 10% for co-benefits). This reached €1.55bn for 2021-2025, though many costs remained undefined and excluded (MITECO, 2020).

Bulgaria grouped measures into Low/Medium/High-cost bands (up to €1m, €1-100m, over €100m) but using specific figures where detailed studies existed, such as €347.81m for irrigation from cost-benefit analysis (Dale & Zhekova, 2019).

Croatia took a strategic approach, developing a prioritised 20-year portfolio of adaptation investments (€3.6bn) through climate modelling and stakeholder workshops, then justifying the annual cost (€183m) by showing it was less than current average damages from extreme weather (€295m) (Croatian Parliament, 2020).

EU level analysis by Neumann et al. (2025) compiled national studies, adjusted them for different emission scenarios and hazards, then extrapolated to countries lacking data using sector economic output as a proxy. Transport estimates drew on seven national studies while agriculture relied on only three, highlighting persistent data gaps (Neumann et al., 2025). A separate EU level study (European Commission, 2026) conducted a bottom-up analysis, which reviewed member state risk assessments, identified and costed relevant measures and then scaled them to the EU. This suggests annual investment needs of €69bn/year to 2050, dominated by infrastructure and ecosystem investments.

There have also been estimates for the UK. These have focused on the costs of adaptation today by categorising actions in the National Adaptation Plan (NAP) in line with Multilateral Development Bank (MDB) taxonomies and estimating investment needs (Watkiss et al., 2026a), though there have been some estimates for future costs as part of the forthcoming Well Adapted UK report (e.g. in Watkiss et al, 2026b and others).

All these studies were transparent about the limitations of the methods used, acknowledging uncertainty rather than presenting false precision. They demonstrated that pragmatic, evidence-led approaches are essential given current data constraints, and framed estimates as ‘evolving documents’ requiring iterative refinement, not as definitive adaptation investment estimates.

Existing estimates for adaptation investment need

Globally, climate finance flows have grown significantly, with total flows reaching US$1.9 trillion in 2023 and private contributions exceeding US$1 trillion for the first time. However, the vast majority of this is directed towards mitigation, with Climate Policy Initiative (2025) estimating only 3.4% is going towards adaptation. The latest United Nations Environment Programme (UNEP) estimates show that developing countries will need at least US$320bn/yr – $400bn/yr for adaptation by 2035, which is roughly ten times higher than today’s international public adaptation finance flows (Watkiss and England, 2025).

To date, there has been limited research specific to Scotland on climate change adaptation investment need. Estimates are instead deduced from broader studies, ranging from £196–£1,340m per year:

  • A recent World Bank study suggests that near-term adaptation investment for the EU27 could amount to 0.1% – 0.4% of GDP annually by 2030 (World Bank, 2024). Scotland’s Climate Emergency Response Group (CERG) applied these values to Scotland, estimating £196 £784m per year by 2030 (CERG, 2024).
  • Indicative estimates for the UK suggest adaptation costs of around £5bn/yr to 2030 for a subset of priority risks, rising to £10bn/yr or more when all 61 CCRA3 risks and proactive adaptation measures are included (Watkiss, 2022). These figures are expected to increase significantly after 2030 as the number of high magnitude climate risks grows from 12 to 21 by the 2050s. Yet these estimates remain partial and indicative, with substantial gaps in sectoral coverage, inconsistent assumptions, and a bias toward engineering solutions rather than social or institutional adaptation (Watkiss, 2022). Using Watkiss (2022) values, and assuming Scotland accounts for 7.5% share of UK economic output as a proxy (Harari & Murray, 2024), implies adaptation costs of approximately £375 – £750m per year.
  • Analysis by the Office for Budget Responsibility (OBR) suggests adaptation costs of around 0.3% of GDP per degree of warming (OBR, 2021). The OBR also highlights that adaptation costs are likely to rise unevenly over time, with larger and more frequent economic shocks expected later in the century. Using 2024 prices, these costs are equivalent to £670 £1,340m per year for Scotland under 1 – 2°C of warming respectively.

Scotland’s specific vulnerabilities and policy landscape mean these broader UK estimates may not accurately reflect Scotland’s climate adaptation investment need. For example, Scotland faces a distinctive combination of climate hazards and geographic contexts. This includes a higher proportion of woodland and peatland, topographic challenges, and 93 inhabited islands, that may not be captured by downscaling UK-wide estimates based on Scotland’s share of GDP. The CCRA3 Scotland summary is also the only national summary to identify flooding as the most severe and costliest hazard to businesses, further highlighting the limitations of direct comparison to UK-level estimates.

Investment need will also vary within Scotland, with some regions more vulnerable to climate risks. Nascent estimates of the public sector adaptation gap in Glasgow City Region (Climate Ready Clyde, 2021) suggested a gap of £187m in 2018/19 alone for the region’s local authorities and the health board, equivalent to around 2% of combined local authority and NHS expenditure across the region’s eight councils and two health boards. No other regional estimates in Scotland have been published.

While national climate adaptation investment estimates are lacking, some public bodies, such as Scottish Water and Network Rail Scotland, have conducted bespoke asset climate vulnerability assessments and initial adaptation cost estimates to facilitate strategic business planning (e.g., Network Rail Scotland, 2024; Scottish Water, 2025). Others have more limited research on specific adaptation investment need. Therefore, while some sector specific information exists, it is fragmented.

As well as absence of Scotland-wide adaptation estimates, there is a lack of robust estimates of the wider returns from adaptation investment. These include avoided climate damages, economic benefits, and broader socio-environmental gains that comprise the ‘triple dividend’ of adaptation.

Who pays for adaptation?

Financing versus funding

A critical but often overlooked distinction in climate adaptation investment is the difference between financing and funding (Watkiss and England, 2025). Financing refers to where the upfront money comes from, whether public grants, government borrowing, sovereign green bonds, or private capital, and the financial instruments and terms involved. Funding, by contrast, refers to who ultimately pays for the adaptation over the lifetime of the investment, whether through public budgets, taxation, or user charges. This distinction matters because private sector involvement can help close the financing gap without necessarily closing the funding gap: costs may simply be transferred back to governments or households rather than genuinely shared.

This is illustrated in Figure 4, which shows options for delivery of a programme of coastal flood protection in a developing country context. Here, the delivery is provided by the private sector, who build the contract. The financing can be provided in many ways, including from public budget, tax rises, or private sector financing through the capital markets. These are important since there is much greater potential for private sector financing than for developing business. For example, it is possible to attract significant amounts of private sector financing to support public sector investment, but ultimately government repays with interest. Therefore, it is important to consider whether we are seeking to boost private sector funding (i.e. the proportion of companies and businesses that actually contribute to the costs of adaptation), or merely the financing.

Figure 4: A simple example of the financing, funding, and delivery of adaptation for coastal protection. Source: Watkiss and England. 2025.

The role of public and private sectors

In recent years, there have been substantial efforts to better understand the factors which can inform whether such activities should be funded by the private or public sectors. These include whether the costs and benefits of activities are public or private as well as the level of financial returns they offer. These can be none/limited (and are therefore typically public), below-market or market level returns (OECD, 2023). The level of market returns for many adaptation options have been classified in Table 3, and these have been reviewed and updated to be relevant to the sectors in scope of this study:

Table 3 – Adaptation activities and potential returns in developed countries for the sectors explored in the study. Updated from Watkiss and England, 2025 and OECD, 2023.

Sector and activity

Typical nature of investment

Typical level of return

Public

Below market

Market

Coastal, river and surface water flood

Protection (coastal and river floods)

Public

ü

  

Early warning services

Public

ü

  

Natural flood risk management / NbS

Public

ü

  

Property Level Flood Resilience and Resistance

Private

ü

ü

ü

Water

Integrated water resources management (IWRM)

Public

ü

  

Supply and distribution

Mixed

ü

ü

ü

Demand management, inc. efficiency measures

Mixed

ü

ü

ü

Agriculture

Research and Development

Mixed

ü

ü

ü

Extension services

Mixed

ü

ü

ü

Climate-smart agriculture

Mixed

ü

ü

ü

Irrigation

Mixed

ü

ü

ü

Trade and trade infrastructure

Mixed

ü

ü

ü

Infrastructure

Transport (road and rail)

Mixed

ü

ü

 

Biodiversity and Ecosystems

Protected areas

Public

ü

ü

 

Capacity building, institutional strengthening, awareness

Public

ü

ü

 

Forestry

Mixed

ü

ü

ü

Building on this approach, UNEP (2025) outline a useful typology (adapted into Figure 5) for understanding where public and private actors are best placed to act, based on the combination of level of returns and whether the costs and benefits are public, private or joint. These can be used to help classify a broad range of activities which are funded by either the public sector, private sector, or a mix of both.

Type A actions are public goods, such as major flood protection schemes, that generate little or no financial return and are therefore typically initiated and funded by government. Type B actions involve a mix of public and private costs and benefits, and where returns are typically below market. For example, supporting climate-smart agriculture. These typically involve blended finance arrangements. Type C actions sit within existing well-functioning markets and generate commercial returns, such as industrial cooling systems, and would be expected to be entirely privately financed and funded.

Figure 5: Simplified categorisation of adaptation types (A-C) and opportunities for private sector engagement. Adapted from UNEP (2025).

Barriers to adaptation finance

Private sector investment in climate adaptation remains persistently low, despite adaptation often delivering high economic returns for society (World Bank, 2024).

The core problem is that while the societal benefits of adaptation can be substantial, the financial returns that matter to private investors are much lower. Adaptation frequently reduces losses or damages and generates limited revenues, making it difficult to construct a viable business case for private finance. This is especially the case, given the opportunity cost of capital, and difficulties of modelling climate-related disruption in cashflows and returns (Watkiss and England, 2025). There are also issues of discounting, where costs arise today, but benefits occur far in the future and are therefore higher. The private sector also uses higher discount rates than the 3% in the public sector (HM Treasury, 2026), compounding this issue.

Many studies reporting high benefit-to-cost ratios for adaptation are measuring economic or societal returns, which include non-market benefits such as environmental value. Private investors, however, assess financial returns, incremental revenues and cash flows, which are considerably lower. This distinction is frequently misunderstood and leads to unrealistic expectations about the role private finance can play (Watkiss and England, 2025).

Watkiss and England (2025) identify five main categories of barrier to adaptation finance:

  1. Information barriers, including insufficient data on climate risks and limited investor understanding of adaptation as an asset class.
  2. Market failures, including public good characteristics and underdeveloped adaptation markets.
  3. Behavioural barriers, including low perceived urgency and limited willingness to pay for risk reduction.
  4. Policy and governance barriers, including weak or conflicting regulation and poor cross-sector coordination.
  5. Financial and bankability barriers, including long payback periods, small project sizes, high complexity, and limited replicability.

Scaling private investment into publicly identified adaptation priorities remains a significant challenge, particularly for smaller, fragmented projects involving many actors and beneficiaries.

Boosting private sector opportunities

Globally, current private sector contributions to climate adaptation are very small (approximately 3% of total needs). Even with substantial innovation and concerted effort, the private sector is expected to deliver only around 15% of required adaptation by 2035, with even less in least developed countries and small island developing states (Watkiss & England, 2025). However, this varies significantly based on country and sector structure. Recent analysis of the UK’s third National Adaptation Plan finds much higher numbers, suggesting around 45% of total adaptation costs are borne by private households and businesses (Watkiss et al., 2026a), in part driven by the privatised nature of the water sector in England. As Scottish Water is publicly owned, the equivalent figure for Scotland is likely to be lower, with a greater share of adaptation costs falling to the public sector.

As a result, climate adaptation is currently funded predominantly by the public sector, both globally and within the Scotland. Central and local government fund most adaptation-relevant expenditure across transport, flood management, water infrastructure, agriculture and the natural environment, largely through existing budget lines that deliver multiple objectives alongside adaptation, climate-proofing, or pure adaptation investment (e.g. for flood protection). Across all sectors, households and businesses also bear some adaptation costs directly. For example, through property level insurance or on-farm investments. However, this remains modest.

Crucially, scaling up private sector participation will not happen through market forces alone. It will require concerted public policy action, enabling conditions, and in many cases public co-financing to de-risk private investment. The private sector’s role is therefore best understood as being complementary to, rather than a substitute for, public adaptation finance (Watkiss and England, 2025).

Governments can adjust the financial characteristics of adaptation activities to increase private sector participation, either at the market level or at the level of individual investments. At the market level, this can include improving existing markets (e.g. through better provision of climate risk information), creating new markets (e.g. through water credits), or supporting public provision where markets fail (Greenhill et al., 2026). At the level of individual investments, policy and regulation or blended finance arrangements can be used to alter financial characteristics and improve commercial viability (World Bank, 2019; Watkiss and Ward, 2025). Where neither approach is sufficient, there remains scope to diversify the range of public financing sources and instruments. This is illustrated in the decision tree in Appendix A.

Climate justice considerations

Another significant consideration within the costs of adaptation are the distributional aspects, and the need for a “just resilience”. The CCC report to Scottish Government on climate adaptation and just transition in 2022 highlighted that fairness in adaptation is strongly linked to just transition concepts, and it is crucial to consider distributional effects to ensure effective and fair adaptation (CCC, 2022). Several characteristics that lead to increased vulnerability and reduced adaptive capacity to climate risk were identified, and include low-income groups, the very young and the elderly, and those in rural regions. The CCC recommended that policy to help address adverse distributional impacts should be routed in an understanding of the distributional effects of climate risks and opportunities.

While climate risks are unevenly distributed and demand equitable responses (European Environment Agency, 2025), they also involve costs. Such costs can be explored from several perspectives. A simplified set of approaches is shown in Table 4, ranging from most targeted to those most socialised, though in reality the approach may be context specific.

Table 4: Indicative approaches to guide who should pay for adaptation: Adapted from Paul Watkiss Associates.

Approach

Description and examples

Justification

Costs borne by those at risk

Those directly exposed to risks bear the costs of adaptation (e.g. PFR)

Beneficiaries should pay costs

Costs socialised amongst users

Investment in water / rail networks for adaptation through water bills and ticket sales

Efficiency, user pays

Maximise social welfare – prioritise dense population

Use of Cost-Benefit analysis to maximise (e.g. flood defences in England)

Social welfare, cost effectiveness

Costs socialised across society

Adaptation of nature and biodiversity, flood protection

Public goods, fairness or equity

Adaptation responsibility based on historic and current emissions

Highest emitters pay for adaptation (e.g. Green Climate Fund, Adaptation Fund)

Adaptation costs driven by historic emissions / most wealthy

The CCC recommended that policy to help address adverse distributional impacts should be rooted in an understanding of the distributional effects of climate risks and opportunities.

Early work underway globally is considering some of the principles behind the costs of adaptation. The Government of New Zealand (2025), set out some early principles in its National Adaptation Framework such as ensuring pre-and post-climate event costs are shared across society and over time, and that the public sector is used to incentivise private sector action, and to take market-based approaches that adjust over time. While beyond the scope of this report, it is noted that such considerations may have the potential to significantly vary relative distribution of costs.

Knowledge gaps and challenges

Evidence gaps in Scotland’s adaptation investment landscape

It is important to note here that adaptation investment, globally, is poorly understood, and many countries are, like Scotland, working to quantify their national adaptation investment needs. Scotland faces multiple knowledge gaps around climate adaptation investment. These include:

  • No clear understanding of the total investment required across sectors, including whether this will involve millions or billions of pounds, or how this spending will be distributed with time.
  • No detailed picture of what climate adaptation investment could deliver for different sectors.
  • No specific, measurable, achievable, relevant and time-bound (SMART) adaptation objectives under SNAP3.
  • No assessment of associated costs of not adapting, and/or expected residual damages.
  • No budget allocation for each SNAP3 objective.

These knowledge gaps make it difficult to determine whether a financing gap exists or how large that gap might be in Scotland.

Broader knowledge gaps in Scotland and beyond include:

  • Lack of robust estimates of the wider returns from adaptation investment, including avoided climate damages, economic benefits, and broader social and environmental gains that comprise the ‘triple dividend’ of adaptation.
  • Limited research exploring opportunities for blended public-private funding partnerships to support climate change adaptation spending.

Further research on these broader topics is key to ensuring and prioritising just and equitable climate adaptation solutions in Scotland.

Box 1: Challenges and limitations

Estimating Scotland’s climate adaptation investment need is inherently challenging. This work provides an initial method, approach, and set of assumptions to estimate climate adaptation spending across sectors. It is intended as a first step that will require further development. The figures presented should therefore be treated as indicative, order of magnitude estimates rather than precise calculations. Readers and peers are encouraged to build on this analysis by adding new assumptions, incorporating additional sub-sectors or hazards, or testing alternative scenarios and risk-tolerance thresholds.

The key data limitations and challenges underlying these estimates include:

Baseline spending: Incomplete information on current adaptation expenditure across Scotland makes it difficult to establish a reliable baseline from which to measure progress or scale up investment.

Asset vulnerability: Comprehensive inventories of climate-vulnerable assets are lacking in most sectors, and there is limited understanding of how vulnerability will evolve as the climate changes.

Climate and socio-economic uncertainty: Projections of how Scotland’s climate will change over the coming decades remain uncertain, as does the evolution of the broader socio-economic and political landscape.

Risk tolerance: Without clearly defined government risk tolerance thresholds or adaptation objectives for each sector, it is difficult to establish an ‘end goal’ against which investment needs can be scaled.

Scope limitations: The analysis focuses on selected sub-sectors and key hazards; many relevant adaptation actions and climate risks across Scotland’s wider economy are not included.

Methodological assumptions: Estimates rely on assumptions regarding appropriate adaptation objectives for 2040 and whether spending continues at current levels or scales up in line with growing climate risks.

Study methods

Our approach

Scotland faces similar challenges in estimating climate adaptation investment need to those across Europe, and the fragmented data landscape means no single method could be applied consistently across all sectors. The study therefore adopted a pragmatic, multi-stage and multi-method approach:

  1. estimating adaptation costs for each sector using the most appropriate costing method given available evidence;
  2. feeding these into a macroeconomic model to explore the economic impacts of different financing routes;
  3. mapping current governance arrangements to understand how adaptation is being paid for today; and,
  4. exploring the potential to increase private sector participation.

Due to resource and data limitations, the three analyses were conducted separately, with differing underlying assumptions. The cost estimates, macroeconomic modelling, and funding analysis are therefore not directly comparable with one another. Each is intended as a broad exploratory assessment, and further integrated analysis would be needed to draw firm conclusions across all three components.

Throughout, developing robust estimates also required identifying which SNAP3 targets and objectives are relevant to each sector and considering wider socio-economic context beyond climate risk alone. The detailed steps are shown below.

Step 1: Adaptation costing

Adaptation objective setting

We adopted 14 of the 23 objectives set out in SNAP3 (Scottish Government, 2024a). The selected objectives covered four of the five broader SNAP3 outcome areas identified by the Scottish Government: Public Services (PS), Economy, Business & Industry (B), Nature Connects (NC), and Communities (C) (Scottish Government, 2024a). Objectives relevant to the fifth SNAP3 outcome area, Connected and Engaged Society (CE), were not included in the scope of this analysis. The specific sectors, objectives and corresponding outcome explored within our analysis area are summarised in Table 5.

Table 5: Climate change adaptation outcome area and objectives from SNAP3 that align with the five sectors considered in our work were selected and, where relevant, amended. Sectors not explored – due to resource constraints – are crossed through in the objectives below.

Sector

SNAP3 outcome area and objectives

Agriculture

B2: Farming, forestry, fishing, and aquaculture businesses are supported to adapt production and operations in a way that benefits livelihoods, resilience, and the economy in a changing climate.

Communities

C1: Regional collaborations are driving inclusive, effective and place-based adaptation across all of Scotland.

C2: Communities and individuals are supported, informed, and able to take locally led adaptation action, supporting local priorities and resilient, healthy, and equitable places.

C3: Communities and individuals are able to prepare for, respond to and recover from emergencies in a way that builds future climate resilience, complements the work of emergency responders and protects those with vulnerabilities to multiple risks.

C4: New buildings are designed for a future climate, and opportunities for adaptation in existing buildings are taken during maintenance or retrofit.

C6: Coastal communities are preparing for and adapting to coastal erosion and sea level rise.

PS2: People can access the public services they need, and critical assets, systems and networks are resilient to the impacts of the changing climate. 

Natural environment

B2: Farming, forestry, fishing, and aquaculture businesses are supported to adapt production and operations in a way that benefits livelihoods, resilience, and the economy in a changing climate.

Nature-based solutions are protected and enhanced to enable healthier, cooler, water resilient and nature-rich places.

NC1: Landscape scale solutions are implemented for sustainable and collaborative land use including protecting and enhancing Scotland’s soils.

NC3: Development planning (including Local Development Plans and associated delivery programmes) takes current and future climate risks into account and is a key lever in enabling places to adapt.

NC4: Nature networks across every local authority area are improving ecological connectivity and climate resilience, alongside other transformative national actions to halt biodiversity loss by 2030.

NC6: Resilient natural carbon stores and sinks (such as peatland, forests and blue carbon) are supporting Scotland’s net zero pathway, alongside timber production, biodiversity gains, flood resilience and the priorities of local communities.

Transport

PS4: The transport system (trunk roads, rail, aviation, ferries, ports and canals) is prepared for current and future impacts of climate change and is safe for all users, reliable for everyday journeys and resilient to weather-related disruption.

PS2: People can access the public services they need, and critical assets, systems and networks are resilient to the impacts of the changing climate. 

Water

PS2: People can access the public services they need, and critical assets, systems and networks are resilient to the impacts of the changing climate. 

PS3: Partnerships for water resource planning and rainwater drainage networks are active in prioritised catchments to support climate resilient places and drought and flooding resilience.

 

The sectors and sub-sectors included in our study are defined as follows:

Table 6 Sectors and sub-sectors explored within this analysis

Sector

Sub-sector

Agriculture

  • N/A.

Communities

  • Flood protection schemes.
  • Property flood resilience.
  • Wider capacity building.

Natural environment

  • Woodland creation.
  • Peatland restoration.
  • Nature restoration.

Transport

  • Trunk roads and motorways.
  • Rail network.

Water

  • Scottish Water – water and wastewater services

Note that, due to resource constraints, a range of other key sectors – for example, energy, telecommunications, and health – have not been explored in this report. Furthermore, even within the sectors we have examined, we have not conducted full sectoral analyses. For example, within transport, adapting ferries, aviation, and canals was not included in the analysis due to resource constraints. Consequently, the results should be interpreted accordingly.

Context setting

To estimate the uplift or scaling factors for adaptation investment needs to 2040, we considered how wider socio‑economic conditions, such as population change, economic growth and sectoral investment trends, might evolve over time. These factors can be important. For example, estimating future flood defence needs can require assumptions about future population distribution, while economic growth and inflation trajectories influence both the cost of adaptation measures and the scale of potential economic losses.

In practice, this broader socioeconomic context was only relevant to a limited part of our analysis. Most estimates relied on sector specific data and updated risk information – such as SEPA’s revised flood risk mapping or current housing stock – rather than the national socioeconomic scenarios developed for CCRA3. As a result, although we originally intended to use the central CCRA3 socioeconomic scenarios to inform investment scaling, these were largely not required in the final workflow.

If needed for future updates, this contextual information can be revisited, but for the purposes of this assessment it played only a minor supporting role.

Apportioning adaptation spend

Following the MDB taxonomy introduced in Section 2.2, this study applied different cost attribution approaches across the five sectors depending on the type of adaptation investment and available evidence. The specific methods used for each sector are detailed below and further elaborated in the sector-specific analyses (Section 4).

Climate-Proofing (Incremental Costs)

For infrastructure investments where adaptation is integrated into planned programmes but not the primary objective, we estimated incremental costs above baseline investment, for example:

  • Transport (trunk roads and motorways): We applied relevant climate-proofing uplifts from the literature to Scottish Government 2026/27 budget lines for road maintenance and renewal. These uplifts reflect the additional investment required to design infrastructure for future climate conditions rather than historical baselines. For example, upgraded drainage capacity to handle more intense rainfall, enhanced slope stabilisation for increased landslide risk, or heat-resistant surfacing materials. The baseline represents the investment that would proceed regardless of climate change; the uplift captures the incremental adaptation cost.

Mixed Objectives (Apportioned Costs)

For investments delivering multiple benefits including adaptation, we apportioned costs based on expert judgment in consultation with Paul Watkiss Associates, who have extensive experience applying the MDB taxonomy internationally. For example:

  • Woodland creation: Forestry investment delivers multiple benefits including timber production, carbon sequestration (mitigation), biodiversity, recreation, and climate adaptation (ecosystem resilience, water regulation, reducing downstream flood risk). We reviewed stated objectives in Scottish Government forestry programmes and applied expert judgment from Paul Watkiss Associates, aligned with on-going UK level adaptation investment need research, to determine what proportion of woodland creation costs should be attributed to adaptation.
  • Peatland restoration: Peatland restoration similarly delivers carbon sequestration, biodiversity recovery, water quality improvements, and adaptation benefits (enhanced water storage and flow regulation reducing flood peaks, maintaining ecosystem function under climate stress). We assessed the relative emphasis on these objectives in Scotland’s peatland restoration programmes and apportioned costs, accordingly. These apportionments were cross-checked through expert review with Paul Watkiss Associates.
  • Nature restoration: We applied similar logic to wider nature restoration funding, examining whether investments prioritise climate resilience objectives (e.g., creating ecological corridors to enable species migration under climate change, restoring coastal habitats for natural flood defence) or primarily target biodiversity and ecosystem health goals, and attributed costs proportionally.

Different analysts might reasonably apply different attribution percentages to the same mixed-objective investments, as there is no objectively correct answer to how investment should be apportioned across multiple objectives, including the distinction between climate adaptation and mitigation. The percentages applied in this study are therefore documented transparently in the sector-specific analyses (Section 4) and supplementary data.

Targeted adaptation (pure adaptation)

For dedicated adaptation investments where climate risk reduction is the primary or sole objective, we counted total programme costs:

  • Flood protection schemes: We examined historic budget allocations from Scottish Government expenditure data and uplifted these to current construction prices using appropriate indices. Estimates drew on SEPA’s updated flood risk mapping and UK-wide research on flood defence costs, scaled to Scotland’s exposure and asset base.
  • Property-level flood resilience (PFR): We scaled recent UK research on PFR costs and uptake rates in proportion to Scotland’s residential and non-residential building stock at flood risk, using SEPA flood risk data to estimate the exposed population.
  • Capacity building (communities): We engaged with Scottish Government policy teams to identify planned and potential future investment in community-level adaptation capacity, resilience planning, and climate literacy programmes where adaptation is the primary objective.

Sector-specific considerations

A pragmatic, multi method strategy was adopted that used the most appropriate costing approach for each sector, determined by data availability and evidence maturity. The core approaches drawn upon were:

  • Drawing on existing sectoral analysis of initial adaptation investment estimates for specific plausible future scenarios (e.g., water and rail).
  • Applying relevant climate proofing uplifts from the literature to relevant Scottish Government 2026/27 budget lines (Scottish Government 2026b), reflecting changing climate risks (e.g., trunk roads and motorways).
  • For each plan or budget line, including the Scottish Government Draft Climate Change Plan (CCP) (2025) and the Scottish Government 2026/27 budget (Scottish Government, 2026b), the multiple objectives were examined to identify the proportion of investment directly related to adaptation (e.g., agriculture, woodland creation, peatland restoration, and nature restoration).
  • Examining and uplifting historic budget allocations to current construction index prices (e.g., flood protection schemes).
  • Drawing on wider UK research and scaling estimates in proportion to Scotland’s building stock or relevant assets (e.g., flood-protection schemes and property level flood resilience).
  • Engaging with Scottish Government policy teams to discuss likely investment changes for spending with adaptation relevance (capacity building within communities).
  • Applying value transfer methods by exploring how adaptation cost estimates compare when scaled to the Scottish context, drawing on Neumann et al. (2025) as an international benchmark for agriculture and transport infrastructure, and on UK Government (2025) analysis for flood protection schemes.
  • Undertaking expert review to cross-check estimates against parallel analysis being undertaken for the Climate Change Committee’s Well Adapted UK report, due for publication in Spring 2026.

For further detail on methodological approach used, please see the sector-specific analyses, the appendices B and C (for additional information on Network Rail Scotland and Scottish Water’s analysis respectively), and supplementary data.

Step 2: Estimating macro-economic effects of spending

Macro-economic effects

Fully modelling the costs and benefits of adaptation, including all potential avoided damages, productivity improvements, health gains, and environmental co-benefits, is extremely resource intensive and was beyond the scope of this project. Instead, the Centre for Energy Policy at the University of Strathclyde used a Computable General Equilibrium (CGE) model of the Scottish economy to explore one deliberately narrow but important question: what are the direct economic effects of additional climate adaptation investment in Scotland, and what economic activity does this spending stimulate?

CGE models are widely used by governments and research institutions, including HM Treasury and the Scottish Government, to understand how changes in one part of the economy ripple through the rest. For this study, a model was used that represents the Scottish economy across 30 broad sectors and is built on Scottish Government Input-Output tables from 2019, chosen to reflect the structure of the economy before the disruptions of Covid-19 and the war in Ukraine. The model traces how adaptation spending affects prices, production, employment, and incomes across sectors, and how these effects in turn influence government revenues and public finances. It also accounts for how wages and employment interact. It allows for migration in and out of Scotland depending on relative economic conditions. Finally, it divides households into five income groups to understand how different parts of society might be affected.

For this research, we assumed that climate change adaptation is a form of capital spending that does not create additional production capital for production sectors. Instead, it allows them to maintain the same production capacity, which would be at risk in the face of climate change.

Understanding the modelling approach: spending and cost recovery

To make the modelling approach clearer, it is helpful to think of adaptation in two phases:

Phase 1: Sectoral spending for climate adaptation measures
In Phase 1 the scope of the work is to model how the spending flows through the Scottish supply chains. We model how the sector makes additional purchases of goods and services to deliver adaptation measures (for example, construction materials, engineering services, flood defences, or restoration work). This spending initially flows through Scottish supply chains, creating economic activity in the sectors that deliver the work and in households that benefit from the associated wages and employment.

Phase 2: Cost recovery
Over time, the sectors and/or government need to recover the costs of adaptation. Each sector may have a different cost recovery approach, depending on its business models and economic structure. We modelled three stylised approaches to illustrate the broad channels through which different funding choices affect the economy:

(1) “Government pays, funded through income tax” (used for Communities, Rail and Trunk roads) may have the following implications:

  • Income tax rates rise to cover adaptation costs.
  • Household disposable incomes fall, especially for higher earners.
  • Consumer spending is dampened across society.
  • This approach is typically progressive, as those earning more pay a larger share.
  • Government spending in other areas (health, education, etc.) is preserved.

(2) “Government pays, funded through government spending cuts” (used for Natural environment) may have the following implications:

  • Public spending declines towards all sectors to cover adaptation costs.
  • Public administration/defence, education, and tertiary sectors suffer most.
  • This approach tends to be mixed.

(3) “Industry pays, funded through higher prices” (used for Agriculture and Water) may have the following implications:

  • The adapting sector faces a cost they have to cover, which firms pass on to consumers through higher prices.
  • Higher prices reduce export competitiveness (assuming similar price increases are not also happening abroad), which reduces demand for Scottish goods.
  • This approach tends to be regressive, as lower-income households spend a relatively larger share of their budgets on essential goods and services.

Important caveats
All approaches are highly stylised and are used to illustrate the broad economic channels and trade-offs that different funding choices create. In reality, adaptation funding is likely to involve a blend of government and industry contributions, as well as other mechanisms such as borrowing, grants, or targeted levies. The scenarios presented here should be treated as illustrative, helping to understand the direction and scale of potential impacts rather than precise forecasts.

More detail on the methodological approach and more detailed analysis of selected sectors can be found in Appendix D.

Note: The macroeconomic modelling cannot be taken as an assessment of the costs and benefits of adaptation. While the modelling captures the direct economic stimulus of adaptation spending and the effects of cost recovery, it does not model residual damages. Neither does it quantify the full range of avoided climate damages, increased resilience, reduced disruption to businesses and households, improved business continuity, health gains, long-term productivity benefits, or environmental co-benefits that underpin the wider “triple dividend” of adaptation. The results should therefore be interpreted as a conservative and partial estimate, representing only one dimension of the economic effects – the demand-side impacts of the spending and its financing – rather than the full spectrum of costs and benefits of adaptation.

Steps 3 and 4: Estimating current and future private sector contributions

In each of the sectors represented in the report, there are existing models which are being used to cover the costs of adaptation today. To explore the current and future potential splits, the project documented the broad governance models of each sector today. We then carried out a qualitative evaluation of the potential use of blended finance, regulation and policy and innovative models. We note that these vary significantly based on the broad structure of the sector, and appetite for change.

Our focus has been on the theoretical potential to increase private sector contributions (noting that this may not be ultimately desirable). This is based on the need to prioritise public sector expenditure on those areas which cannot be met by private sector or households directly. The range of models explored includes:

  • Innovative models using private finance to provide upfront capital
  • Models which increase private sector funding for adaptation
  • Provision of adaptation goods and services (which ultimately reduce costs for public and private sector activities

To identify potential innovations, we drew on the Paul Watkiss Associate database of innovative accelerators (England et al., 2023; United Nations Environment Programme, 2024), as well as recent wider work exploring financing options (Watkiss and England, 2025). Further supplemental models were identified through desk-based searches during this project. We undertook a rapid review and used expert judgement to extract innovative approaches that they felt were potentially relevant in a Scottish context.

Due to the limited resources available for the project, the review has inevitably been ‘light touch’ but serves as the basis for further exploration and discussion to inform the development of SNAP4, as well as the future business models of public bodies such as Scottish Water or Network Rail.

Prices

All prices in the report are presented in 2026/27 prices. For the period 2025/26 to 2026/27, a nominal growth rate of 2% per annum has been applied, consistent with the Bank of England’s long-run inflation target. See the supplementary data for further detail.

Sector-specific analysis

The results derived are detailed below. For each sector – agriculture, communities (flooding), transport, water and natural environment – we highlight (1) key risks and adaptation opportunities, (2) information regarding current investment in climate adaptation, (3) the estimates of adaptation investment need, (4) the wider (co)-benefits of such spend, (5) the current governance, and (6) funding and financing arrangements.

Agriculture

Key climate risks and adaptation opportunities

Agriculture in Scotland faces a complex and intensifying range of climate-driven pressures. More frequent extreme rainfall events are already causing excess waterlogging, which has been shown to be a greater current risk to wheat yields than heat or water stress (risk N6 in CCRA3). Hotter, drier summers are reducing the suitability of high-quality arable land due to drought risk. The 2018 drought illustrated how quickly these pressures cascade through supply chains, with reduced malt barley yields and distilleries halting production due to low river flows. Fluvial flooding on major river catchments such as the Tay and Tweed continue to damage agricultural land, and projections suggest the area of Scotland’s best-quality farmland at risk from flooding could rise by over 30% by the 2080s under a +2°C scenario. Warmer conditions are also driving increases in pests, pathogens and invasive species (CCRA3 risk N7), from potato blight and cyst nematodes to Bluetongue virus, posing escalating threats to crops, livestock and soil health (Sniffer, 2021). Together, these pressures are expected to push agricultural climate risk, as stated in the CCRA3, from medium to high in the coming decades (Sniffer, 2021).

Addressing these risks requires an integrated, forward-looking approach to land-use planning and farm management. Key priorities identified by CCRA3 (2021) include updated land capability assessments using UKCP18 data to guide decisions on where agricultural systems remain viable, alongside improved skills and knowledge exchange, crop diversification, and better soil and water management. Expanded pest and disease monitoring, stronger biosecurity, and wider uptake of integrated pest management are also highlighted, as is the need to align adaptation with net zero strategies to avoid introducing new vulnerabilities. Stronger research, improved coordination between government and land managers, and a more strategic cross-sector approach will be essential to safeguard Scotland’s long-term agricultural productivity as climate pressures intensify (Sniffer, 2021).

Current spending and context

It is not possible to outline how much capital the Scottish Government currently allocates specifically toward climate adaptation of agriculture. This is because climate adaptation investment is currently folded into budget lines with multiple other objectives such as emissions reductions, increased biodiversity and wider farm support. However, the Scottish Government 2026/27 Climate Taxonomy highlights that £221m worth of allocated budget within agriculture have a positive impact on adaptation. Similarly, to our knowledge, there is no available evidence on private sector investment for adaptation of agriculture within Scotland.

Adaptation investment need

Budget lines from the Scottish Government’s 2026/27 Climate Taxonomy with a positive impact on adaptation were used as the primary basis for estimating mixed-objective investment need for agriculture (Table 7). Spending was assumed to continue in nominal terms to 2040, with no uplift applied for increasing climate risk over the period. It should also be noted that some budget lines with positive adaptation impacts may not have been captured, for example, the Farm Advisory Service and Knowledge Transfer and Innovation Service sits under ‘Business Development’ in the Scottish Budget and has not been included, despite likely supporting adaptation through improved uptake of resilient practices.

It is important to note that these budget lines deliver multiple benefits alongside adaptation, including climate mitigation, soil health improvements, biodiversity gains, and wider farm business productivity. Disentangling the proportion of each line attributable specifically to adaptation is particularly challenging in agriculture, where weather and climate resilience – and therefore adaptation – are integral to sectoral success. For this reason, no specific proportion of any budget line was allocated to adaptation in isolation; instead, the whole budget line was included. Estimated costs should therefore be understood as representing a bundle of co-benefits of which adaptation is one component.

Table 7: Budget lines from the Scottish Government Climate Taxonomy 2026/27 that were included in adaptation investment need analysis for agriculture, and associated adaptation rating (Positive – High or Positive – Low) which represents the likely impact (and extent of impact) of the budget line on adaptation, e.g. ‘Positive – High’ is a positive impact that is likely to be highly beneficial.

Budget lines included in analysis

2026/27 budget (£m)

Adaptation rating

Pillar 1 – Greening Payments

£142m

Positive – High

Agricultural Modernisation Fund

£26m

Positive – Low

Scottish Rural Network

£0.87m

Positive – Low

Agri Environmental Measures Resources

£21m

Positive – High

Agri Environmental Measures Capital

£4.7m

Positive – High

Public Good Advice

£2m

Positive – Low

Veterinary Grants

£0.8m

Positive – Low

Animal Diseases

£23.5m

Positive – Low

Table 8 outlines our estimate of mixed objective investment need – including adaptation – for agriculture. This estimate ranges from £168m/yr for budget lines associated with a high positive impact on adaptation to £221m/yr where budget lines with a low positive impact on adaptation are also included.

We cannot give an estimate of adaptation investment need for agriculture in isolation. However, if the current level of spend is maintained out to 2040, total investment in budget lines associated with a positive impact on adaptation in agriculture would amount to between £2,347m – £3,091m, or equivalent to £167.6m – £221m per year over the period 2026–2040 (Table 8).

Table 8: Lower and upper estimates of the mixed-objective investment need (including climate adaptation) for agriculture, based on budget lines in the Climate Taxonomy 2026/27 with a positive impact on adaptation. Values are in 2026/27 prices.

Lower estimate

Upper estimate

Cost p.a. (£m/yr)

Total up to 2039/40 (£m)

Cost p.a. (£m/yr)

Total up to 2039/40 (£m)

£167.6m/yr

£2,347m

£221m/yr

£3,091m

These estimates were triangulated by scaling adaptation cost estimates from Neumann et al. (2025) to the Scottish context as an international benchmark. Neumann et al. (2025) estimated EU agricultural adaptation costs at approximately 0.04% – 0.06% of GDP per year under moderate to high emissions scenarios. Applying this range to Scotland’s GDP yields an indicative figure of £90m – 142m/yr (2026/27 prices). Scotland’s agricultural GVA (approximately £2.2bn, around 1% of GDP) is broadly comparable to the EU average (approximately 1.2% of EU GDP), supporting the plausibility of this transfer as a cross-check (Scottish Government, 2025c; Eurostat, 2026). However, this comparison should be treated with caution: the nature and projected intensification of climate hazards vary considerably across EU member states and diverges from Scotland’s risk profile in important respects. These figures were therefore used as an indicative benchmark to assess how our estimates compare at an international level, and are not included in our reported adaptation investment need figures.

We also conducted separate exploratory research to highlight the challenges and opportunities of using bottom-up analysis to cost climate change adaptation investment need for specific agriculture actions (see Case study 1).

Case study 1: Exploratory bottom-up analysis of agricultural adaptation actions

While budget tagging reveals how much is being spent, it does not indicate what this delivers for climate resilience or whether current levels are sufficient. As an exploratory supplement to the primary budget-line estimates, indicative cost estimates were developed for 33 adaptation actions identified in a Scottish Government RESAS report, to showcase how investment need estimates could iteratively improve to become asset- and action-based going forward. This analysis should be regarded as a proof-of-concept; further data collection and expert elicitation would be needed to improve future estimates and develop associated adaptation pathways.

Costs were sourced from academic and grey literature, with confidence ratings assigned to each source, and scaled to Scotland’s agricultural land area using land-use archetypes from the CCC’s Rural Land Use Types report (Thomson et al., 2025). Complete scaled cost estimates were produced for 19 of the 33 actions. Where data permitted, an exploratory cost-benefit analysis was undertaken for selected actions, including diversified crop rotations, examining potential impacts on yields, soil erosion, and fertiliser use.

The exploratory CBA for diversified crop rotations suggests potential monetised benefits totalling £856m–1.1bn between 2026 and 2040 for reduced soil erosion, increased crop yields and reduced fertiliser usage. Relative to an estimated total action cost of £3.5bn, this represents 25–31% of the potential investment directly benefiting agricultural productivity. Furthermore, other public good benefits not explored from diversified crop rotations could include other benefits such as increased biodiversity and improved water retention that were not explored here.

These figures assume each action is applied across all eligible land, which is an over estimation. Further information on the results, assumptions made, confidence ratings, and recommended further research steps are provided in Appendix E and the supplementary data.

Macroeconomic effects and wider impacts

Macro-economic impacts

We assumed the agriculture sector requires approximately £2.3bn of adaptation investment between 2026 and 2040, around £150m/yr (based on rounding down the analysis in Section 4.1.3). This spending is distributed across construction, the agriculture sector itself, all other manufacturing, and wholesale/retail (vehicles).

Without cost recovery (a modelling device to isolate the spending effect): The programme generates GDP and employment gains during the spending period, with around 80% concentrated in the sectors directly delivering the works – construction, all other manufacturing, wholesale/retail (vehicles), and agriculture itself. Positive spillovers reach consumer services as household incomes rise. Employment and GDP impacts track each other closely because the agriculture adaptation supply chain involves relatively capital-intensive activities such as specialised equipment and infrastructure. As with other sectors, these benefits fade after spending concludes.

With “industry pays” cost recovery (a stylised scenario): When farmers bear adaptation costs and pass them to consumers via higher food prices, the effects are regressive. By 2040, the lowest-income households face price increases of 0.09%, compared with 0.07% for the highest-income households, because food represents a much larger share of poor households’ budgets. Higher food prices erode real incomes and household consumption across all income groups, while reduced export competitiveness further dampens GDP and employment. Because agriculture is one of Scotland’s most labour-intensive sectors – employing 8.5 workers per £1m of output, well above the economy-wide average of 6.6 – the concentrated negative impacts trigger significant job losses that spill across the wider economy. Scotland’s labour mobility means workers leave rather than accept wage cuts, prolonging the employment losses.

Policy implications: An “industry pays” approach financed through higher food prices risks regressive impacts on low-income households and substantial employment losses. While adaptation spending itself stimulates construction and manufacturing, the method of cost recovery determines whether these gains are preserved or eroded, and which parts of society bear the burden.

Current governance, funding and financing arrangements

Agriculture is a market sector but is heavily supported by the public sector (Figure 6). See Appendix F for further information on how this support is planned to change.

A key challenge in the agriculture sector is disentangling the adaptation costs from the other objectives, as the sector involves a mix of activities. There are some dedicated adaptation activities, but other agri-environment objectives include actions to improve productivity, with private costs and benefits, but supported by public activities. Furthermore, it is also challenging to differentiate adaptation actions from wider activities to boost yields or achieve other objectives.

Therefore, rather than looking at activities, the study took an alternative approach which explored the relative income sources for farms. Scottish Government produces estimates on the annual income from farms, including their makeup (Scottish Government, 2025d) shown in Appendix F. These show that agricultural activity in Scotland is typically lossmaking, except for dairy and general cropping, and that agricultural support payments make up a significant share of all farm income. The survey excludes sectors which do not receive support, such as pigs, poultry and horticulture.

The results suggest that loss-making farms may struggle to invest in adaptation measures and that the majority of the ability to invest in adaptation is likely to come through support payment income. We assume that adaptation action is mainstreamed into general agricultural support.

To derive estimates of private sector contribution we started by assuming that for farm types where agriculture is not profitable, all agricultural adaptation is paid for by the public sector. For those sectors where agricultural income is profitable, we assume 50% co-investment, assuming farmers can contribute to those areas which support adaptation. For those sectors excluded for support payments, we assume adaptation costs are 100% private. These assumptions were then applied to output of holdings by farm type from the 2025 Scottish Agricultural Survey. The results suggests that 33% of investment in adaptation is likely to be from the private sector. However, given the overlap with many other objectives and activities (including flood management), the uncertainty on the types of interventions and how they vary by farm type, as well as the fact that many of the grant schemes require co-investment from farmers. the confidence in such apportionment is low.

Figure 6 Financing, funding, and delivery arrangements for adaptation in agriculture.

Innovation that could boost private sector participation

Agriculture is one of the sectors where there is the greatest amount of innovation. There are a range of opportunities to leverage private finance for agriculture adaptation – especially as part of the wider agricultural reform programme. In general, blended finance offers a significant opportunity to incentivise further opportunities for investment in adaptation. For example, it can mainstream adaptation into loan requirements for agricultural investment, or support investment in dedicated adaptation activities. In Scotland, elements of nature restoration on farmland could be financed through biodiversity credits. Blended public-private models such as the Scottish Government £1m Agritourism Investment Scheme – offering grants of up to £50,000 covering 40% of eligible capital costs – can support farm diversification and rural resilience (Savills, 2026).

These can also be complemented by other models which support investment, including from suppliers interested in value chain resilience, or using offtaker agreements.

There are also specific models for investment that target particular activities or parts of the supply chain. For example, use of Public Private Partnership (PPPs) for climate resilient seeds, or the use of digital platforms to provide weather and advisory services) to support farm activities. In addition, parametric insurance offers faster, more transparent cover for systemic risks including drought, flooding, frost and yield shortfalls. It pays out automatically when pre-agreed environmental thresholds are met, rather than requiring loss assessment (Descartes, 2026). Parameters must be carefully designed to avoid leaving farmers exposed to events that fall outside agreed trigger conditions.

Shared rural infrastructure offers a further avenue for cost-effective private investment. Co-operative models – for example, shared grain stores and drying equipment – spread capital costs across multiple businesses while building collective resilience to weather-related yield losses. Similarly, investment in commercial deer carcass processing infrastructure, including improved Approved Game Handling Establishments (AGHEs), could support the economic viability of deer management, which delivers biodiversity, habitat restoration, and natural flood risk management benefits alongside commercial returns. Where shared infrastructure generates both adaptation outcomes and commercial revenues across multiple beneficiaries, blended public-private financing is well suited and could be supported through existing rural development funding mechanisms (World Bank, 2019).

Finally, there are newer and more experimental models being developed, such as the use of Resilience Credits; summarised in Table 9. While conceptually similar to carbon credits, they are more challenging to operationalise due to the conceptual challenges of adaptation, such as avoided future losses and the local place-based context of adaptation and resilience.

Table 9: Examples of innovative models for private participation in agriculture, with cost recovery model. Source: Updated from Watkiss and England (2025).

Model

Examples

Cost recovery model

Blended finance

Many examples of public and private investment, e.g. World Bank (2019), Scottish Government Agri-Environment schemes

User pays but can generate value addition through financial return (adaptation goods and services)

Concessional Credit Lines (e.g. SNIB)

Many examples of below-market loans and guarantees

Offtaker agreements / Supply chain finance

AMRU Rice (McNally et al., 2024)

Ex-post proof sharing

Warehouse receipt financing

Value chain integration

International Finance Corporation’s (IFC’s) Global Warehouse Finance Program (IFC, n.d.)

Digital platforms (weather and advisory

GeoKrishi (GeoKrishi, n.d.)

Resilience credits (reward investment in adaptation)

IFAD (Puri and Chowdhury, 2023)

Seed value chain

Tolerant seed multiplication (IFC, 2019)

PPPs for seed companies

FAO public–private blended finance facility for climate-resilient rice landscapes (Damon, 2023)

Communities

Key climate risks and adaptation opportunities

Flooding is the largest climate-driven threats to communities and the built environment in Scotland, with exposure increasing across riverine, coastal and surface water systems (SEPA, 2025). Surface water flooding is the most widespread form of flooding as more frequent extreme rainfall events are overwhelming drainage networks and intensifying surface water flooding. Approximately 400,000 properties are currently at risk from a 1-in-200-year flood event (SEPA, 2025). Flooding already costs Scotland an estimated £500m every year – and that figure will likely grow (SEPA, 2025). Beyond physical damage, flood events trigger persistent mental health impacts, particularly where households face prolonged displacement or repeated flooding. In addition, the burden falls disproportionately on socially vulnerable coastal, urban and rural communities (Sayers et al., 2018; Song et al., 2025). As climate change and population growth converge, exposure is projected to extend into areas with no historical flooding experience.

Addressing these risks requires a coordinated, forward-looking approach to spatial planning, infrastructure design and community-level adaptation. Key priorities identified by CCRA3 (2021) include stricter controls on development in flood-exposed areas, greater enforcement of Sustainable Drainage Systems (SuDS), wider uptake of Property Flood Resilience (PFR) measures, and better integration of natural flood management alongside traditional defences. CCRA3 (2021) also highlight improved flood forecasting, public warning systems and more targeted investment in vulnerable communities, alongside updated planning policies that embed climate-ready design principles. As surface water flooding is projected to increase under all climate scenarios, a strategic approach combining planning, infrastructure, social policy and community engagement will be critical to safeguarding people and places (Sniffer, 2021).

Current spending and context

Flood protection schemes

The Scottish Government has maintained a long-term baseline of £42m/yr for flood protection schemes since at least 2015/16, supplemented by a one-off top-up of £150m. Together this totals £570m invested in flood resilience over 2016–2026 (Scottish Government, 2024a; Scottish Government, 2025e). Local authorities also contribute to the cost of building major flood schemes. In the national ‘cycle 1’ scheme, it is estimated that the Scottish Government pays for 80% of the costs and local authorities pay for the remaining 20% of the costs. If costs increase after a specific point in the process, local authorities must pay for those increases. Local authorities also pay for ongoing maintenance once the flood schemes have been built (Audit Scotland, 2025).

Of the 40 flood protection schemes in ‘cycle 1’ (2016–2021) originally deemed eligible for funding, eight were subsequently abandoned and one was separated into a dedicated taskforce, leaving 31 viable schemes. As of early 2026, 21 of these have been completed. One is currently under construction, and a further six schemes are expected to have main construction contracts in place by March 2026. Three remain eligible for funding. However, projected costs across the programme have escalated significantly. For example, the Hawick scheme rose from £37.4m to £78.6m, Musselburgh from £8.9m to £106m, and Dumfries Whitesands from £18.9m to £68.6m (Internal Scottish Government Data – collected from local authorities in November 2024).

On average this investment has protected approximately 600 additional homes per year from flooding between 2016–2026 (Scottish Government, 2025e). However, climate change is exposing an estimated additional 3,000 properties to flood risk each year (SEPA, 2025), meaning that even if the flood protection scheme cycle was fully delivered, it would struggle to keep pace with the scale of need.

Property flood resilience

Property flood resilience (PFR) measures are an important complement to wider flood protection schemes, with particular suitability for managing surface water flooding (Pettit et al., 2020). PFR measures include resistance measures that prevent water entry and resilience measures that reduce damage and speed recovery. Currently, only a small share of Scotland’s flood protection budget is directed towards PFR, despite its potential to provide cost-effective protection for properties exposed to frequent flooding. JBA Risk Management (2025) identifies 4,679 PFR-eligible properties in Scotland with a payback period of 3–5 years, drawn from a wider total of 116,073 properties considering Great Britain, England, Wales and Scotland. However, this represents only a fraction of the likely need – at least 81,000 homes have been identified as suitable for PFR more broadly (Petitt et al., 2020). This figure predates SEPA’s updated flood risk assessment and may therefore underestimate current exposure. This suggests that the near-term investment requirement for properties where PFR is highly cost-effective is relatively modest and well-defined. However, the investment need across the broader pool of suitable properties is considerably less certain, requiring further research.

Capacity building

Climate Action Hubs, Adaptation Scotland, and Climate Ready Regions are the three main Scottish Government programmes delivering systemic capacity building for adaptation beyond infrastructure interventions. These programmes are intended to support communities, businesses, and public bodies to understand and respond to a wide range of climate hazards including flooding, heat, drought, sea level rise, and storms. The Adaptation Scotland Programme works across a broad range of sectors beyond communities. A proportion of Climate Action Hubs activity relates to mitigation rather than adaptation. In both cases, full budget allocations have been retained as spending cannot be reliably disaggregated between adaptation, mitigation, and other functions.

Drainage partnership funding – representing important capacity building at the catchment level – is included within adaptation cost estimates for the water sector and is not included here to avoid double-counting.

Adaptation investment need

This analysis focuses on flood risk management to assess climate adaptation investment needs for communities, covering flood protection schemes, property flood resilience (PFR), natural flood risk management, and wider capacity building. Some flood adaptation measures, such as improved hydrological modelling and early warning systems, have not been costed here and would add to the overall investment need. Other hazards affecting communities – including coastal erosion, drought, heatwaves and wind – fall outside the scope of this analysis and could be explored in further work.

Flood risk management entails a wide range of activities. Our research sought to cover expenditure across four main spending lines: (a) flood protection schemes, (b) property flood resilience (PFR), (c) natural flood risk management (implicitly included in the natural environment budget), and (d) wider capacity building.

This was challenging for two reasons: firstly, it was difficult to establish how Scotland’s current budget is allocated across these spending lines. Secondly, there was an absence of quantified targets or risk-tolerance levels against which investment needs could be scaled. For example, if the Scottish Government were to commit to protecting all high flood risk social housing, it would be possible to identify the number of eligible properties and estimate protection costs accordingly, but without such targets, scaling investment needs requires assumptions that introduce additional uncertainty. As a result, multiple complementary methods were used to assess investment need, with the caveat that there may be a small degree of double-counting between individual estimates. Estimating potential avoided losses from flood risk investment was also particularly challenging in this sector.

Flood protection schemes

To estimate future investment requirements for flood protection schemes, we take two approaches:

  • We uplift the historic baseline funding of £42m/yr, in place from at least 2015/16 (Audit Scotland, 2025), using the ONS construction price index. This yields an estimated £63m/yr and a total projected requirement of £882m for the period 2026 to 2040 (Table 5).
  • We take DEFRA flood protection commitments of £7.9bn for England between 2025 and 2035 (UK Government, 2025) and scale to Scotland based on dwelling stock. This yields an equivalent figure of £79m/yr, or £1,102m over 2026–2040. This value-transfer approach rests on assumptions of comparable housing stock, property type, and flood risk exposure with the wider UK and should be treated with appropriate caution.

Both figures are presented in Table 10 to reflect the inherent uncertainty in projecting long-term flood protection expenditure. Together, these approaches indicate an adaptation investment need for communities via flood protection schemes of £885m – £1,102m over the period 20262040.

Table 10: Property flood protection scheme climate adaptation estimates 2026–2040, assuming uplift of Scotland’s historic £42m/yr guaranteed spend for the historic Scottish budget scaled, and 10% of wider UK pledge to be proportionate to Scottish dwellings.

Flood protection schemes

Historic Scottish budget scaled

DEFRA pledge (Scotland equivalent)

Cost p.a. (£m/yr)

Total up to 2039/40 (£m)

Cost p.a. (£m/yr)

Total up to 2039/40 (£m)

£63.2m/yr

£885m

£78.7m/yr

£1,102m

This estimate is likely conservative, as it captures only Scottish Government central funding. Local authorities also contribute toward flood protection investment. For example, within ‘cycle 1’ local authorities contributed an estimated 20% of the investment need and the cost of maintenance (Audit Scotland, 2025).

Property flood resilience

Investment need for property flood resilience (PFR) was estimated by applying unit costs from JBA Risk Management (2025) to the 4,679 PFR-eligible properties in Scotland identified as having a payback period of approximately 3–5 years. This focus on properties with the strongest return on investment reduces the risk of double-counting with the wider flood protection budget, while reflecting the economic case for targeted intervention. Unit costs of approximately £2,250 per property for limited PFR measures (e.g., temporary flood barriers for doors, air brick covers, toilet bungs) and £11,000 for standard measures (e.g., permanent flood doors, extensive waterproofing / re-pointing of external walls) were applied accordingly.

By multiplying the average cost per property for limited measures (£2,250) and for standard measures (£11,000) by properties eligible with a short payback period (4,679 properties), calculations indicate an adaptation investment need for communities via property flood resilience measures of £10.5m £51.5m over the period 20262040, equivalent to £0.75m/yr £3.68m/yr (Table 11).

Table 11: Property flood resilience climate adaptation investment need where payback time is likely approximately 5 years, using JBA Risk Management (2025) data

Property flood resilience

Limited measures

Standard measures

Cost p.a. (£m/yr)

Total up to 2039/40 (£m)

Cost p.a. (£m/yr)

Total up to 2039/40 (£m)

£0.75m/yr

£10.5m

£3.68m/yr

£51.5m

The economic case for investment is reinforced by JBA Risk Management (2025) analysis of Annual Average Losses (AAL), which indicates that delivering standard PFR measures across all 4,679 eligible properties could reduce AAL from £22.8m to £11.1m – a saving of £11.7m per year, suggesting the full cost of standard intervention would be recovered through avoided flood damages within approximately five years.

Capacity building activities

Capacity building investment need was estimated by reviewing expected funding pathways for three programmes, in consultation with Scottish Government policy teams. Climate Action Hubs are estimated at £6m/yr (£84m to 2039/40); Adaptation Scotland at £0.4m/yr (£6m to 2039/40); and Climate Ready Regions at £0.55m/yr rising to £0.9m/yr between 2026 and 2029, remaining at £0.9m/yr through to 2039/40 (£12m to 2039/40). Case study 2 highlights one of the Climate Ready regions funded initiatives. Furthermore, it should be noted that capacity building investment need spans risks beyond flooding – including storms, drought, wildfires, and heatwaves – and encompasses some capacity building for climate mitigation that could not be disentangled from adaptation spend. Together, our calculations indicate adaptation investment need for communities via capacity building amount to £102m between 2026–2040 (Table 12).

Table 12: Estimated climate adaptation investment need for capacity building activities within the communities’ sector between 2026–2040. Costs in 2026/27 prices.

Capacity building activities

 

Standard measures

Action

Cost p.a. (£m/yr)

Total up to 2039/40 (£m)

Climate action hubs

£6m/yr

£84m

Adaptation Scotland

£0.4m/yr

£6m

Climate ready regions

£0.55m – £0.9m/yr

£12m

 

Total:

£102m

These figures assume current spending levels, increasing nominally, are sufficient to meet future adaptation capacity building needs – an assumption that may warrant revisiting as Scotland’s adaptation requirements become better understood.

Case Study 2: University of Strathclyde Raingarden Parklet Case Study

The Raingarden Parklet, led by Hope in Place CIC and supported by Civic, is an innovative piece of green urban infrastructure designed, created, and built in Glasgow. It represents a new approach to sustainable urban drainage systems (SuDs). It aims to reduce peak run off during intense rainfall. while simultaneously creating social value through education, training, and pathways into green jobs.

The modular unit measures 4.5m × 1.5m × 1.2m and costs approximately £10,000 to design and manufacture. The University of Strathclyde secured £15,000 through Climate Ready Regions funding via Climate Ready Clyde, covering the parklet and a proportion of the £15,000 – £20,000 installation costs.

The final location outside the Andersonian Library was selected through stakeholder consultation against criteria including flood risk, footfall, and connection to local drainage infrastructure. It demonstrates what can be achieved in a single car parking space and offering a visible symbol of Glasgow’s shift towards greener, healthier streets.

Beyond flood resilience, the pilot delivers co-benefits across public realm enhancement, green skills and employment, and justice system reform. The parklet was constructed in HMP Barlinnie using recycled materials, with profits funding a training pathway towards a ‘Green Skills Factory’ at the new HMP Glasgow and the project fostering broader community-university collaboration. This has the potential to act as a catalyst for further investment in modular, scalable adaptation solutions that deliver integrated benefits for society, the environment, and the economy.

Example of a raingarden parklet. Image credit: Ben Raw.

Total adaptation investment need for communities through flood measures.

In total, the adaptation investment need estimate for communities – focusing predominantly on flood management – is £997.5m – £1,256m between 2026–2040, equivalent to £71.2m/yr – £89.7m/yr (Table 13).

Table 13: Estimated climate adaptation investment need for flood protection schemes, property flood resilience and capacity building between 2026 – 2040. 2026/27 prices.

Sub-sector

Cost p.a. (£m/yr)

Total up to 2039/40 (£m)

Flood protection schemes

£63.2 – £78.7m/yr

£885 – £1,102m

Property flood resilience

£0.75 – £3.68m/yr

£10.5 – £52m

Capacity building

Approx. £7.29m/yr

£102m

Total

£71.2 – £89.7m/yr

£997.5 – £1,256m

Macroeconomic effects and wider impacts

Macroeconomic impacts

The communities sector adaptation package, covering regional hubs, property flood resilience and flood protection schemes, amounts to around £978m between 2026 and 2040, approximately £65m/yr. This is slightly lower than the figures quoted in section 4.2.3.4 because of rounding and the pricing being in different years.

Without cost recovery (a modelling device to isolate the spending effect): By 2040, Construction records an output gain of £38m and roughly 575 jobs, while architectural services and “all other services” add £9m in output and 120 jobs. Modest positive impacts appear in wholesale and retail trade, fabricated metals, manufacturing and primary sectors, reflecting supply-chain linkages. The overall effect is a modest but broadly positive local economic boost centred on construction, professional services and local services.

With “government pays” cost recovery (a stylised scenario): When the Scottish Government recovers costs through higher income tax, construction retains most of its gains, recording £35m in output and around 530 jobs. Architectural services and supply-chain activities such as fabricated metals and steel also remain positive. However, consumer-facing sectors reverse direction. Retail (excluding vehicles) shifts from a £1.7m gain and 36 jobs in the no-recovery case to a £2.8m loss and 59 fewer jobs once taxes rise. Similarly, “all other services” flips from an £8.6m gain and 114 jobs to a £15m loss and 187 fewer jobs. Financial services, travel, transport, manufacturing and energy sectors also turn negative as squeezed household incomes reduce demand. In simple terms, higher income taxes reduce disposable incomes, which reduces consumer spending, putting pressure on retail, hospitality and service jobs.

Policy implications: Even relatively modest adaptation programmes provide meaningful local benefits in construction and professional services. However, income-tax recovery dampens broader gains: it is more progressive than raising prices for essential goods, but it still reduces household budgets and activity in consumer-facing sectors. Policymakers need to weigh these short-term sectoral effects against the long-term flood protection and community resilience benefits.

Wider impacts

The economic case for adaptation investment in flood resilience for communities is strong. Defra estimates that every £1 spent on flood defences prevents around £8 in economic damage (UK Government, 2025). Furthermore, the expected annual cost of flooding impacts in Scotland is now approximately £260m/yr (Scottish Government, 2025e), with multi-hazard events, such as the associated flooding from 11 named storms between November 2015 and March 2016, negatively impacting the UK economy by 0.08% of GDP (Office for Budget Responsibility, 2024). Consequently, the potential avoided losses from sustained investment in flood protection schemes remain substantial. Note, further research is required to develop a full understanding of the wider co-benefits associated with investing in flood protection schemes, PFR and wider capacity building.

Current governance, funding and financing arrangements

Flood risk management is currently predominantly funded by the public sector as illustrated in Figure 7. This includes direct funding from Scottish government for schemes. Responsibilities are set out under the Flood Risk Management (Scotland) Act 2009. Most flood investment is provided by Scottish Government, who provide £42m/yr. However, this is provided at an intervention rate of 80%, with an additional 20% from local authorities from general ringfenced funding. Assuming this is spent, an additional £8.4m a year is provided by local authorities. Allocating the same percentage of private sector contribution (37%) as for transport, suggests that around £3.1m (37% of £8.4m) a year is contributed by households and businesses.

Some levels of PFR are funded by households, both domestically and through Flood Re’s Build Back Better scheme (a joint initiative between the UK insurance industry, see Innovation section, below), but this is relatively low. Details of the number of properties ceded to flood Re, or properties provided with PFR, are not publicly available. The Flood Re market study assumes around 500 – 550 residential properties a year going through (Borio and Kassian, 2023). This suggests around £540,000 a year in contributions, though both the Borio and Kassian (2023) study and Pettit et al. (2020) highlight most of these schemes are publicly funded or subsidised. Therefore, for the purposes of the study, we assume the total contribution to floods indirectly via Council Tax and Non-Domestic Rates to be roughly 7%.

Figure 7: Financing, funding, and delivery arrangements for adaptation in flood protection schemes and property flood resilience.

Innovation that could boost private sector participation

Opportunities to leverage private investment in adapting to changing flood risk in Scotland could include:

Scotland Bond Issuance programme: Scottish Government is in the process of putting in place the mechanisms to facilitate the issuance of bonds, having obtained a credit rating and appointing banks and legal advisors (Scottish Government, 2026a). This has been used in the UK to provide upfront financing for Flood and Coastal Erosion Risk Management, with UK Government reporting on use of proceeds. Similar mechanisms could be used to provide a significant boost to available capital investment.

The FloodRe ‘build back better’ scheme: For communities impacted by flooding, it is likely their properties will be eligible for the FloodRe ‘build back better’ scheme, a joint initiative between the UK insurance industry and the UK Government, which offers householders the chance to install property flood resilience measures up to the value of £10,000 when repairing their properties after a flood (FloodRe, 2023). No data is currently published on use, but uptake is thought to be low.

Scotland’s current resilience organisations: These span Regional and Local Resilience Partnerships, Community Resilience Committees, and Category 1 and 2 responders (Brett et al., 2026). They represent a cost-effective foundation for building adaptation capacity without requiring entirely new delivery structures. Embedding adaptation within local authority contingency planners, local resilience partnerships, and community councils offers a pragmatic route to scaling capacity building across Scotland’s communities and institutions. Private sector organisations, particularly utility and transport operators operating as Category 2 responders, are well positioned to potentially contribute co-funding and expertise to this capacity building as part of their existing statutory obligations and business continuity responsibilities.

There are multiple opportunities to increase both private sector funding and financing. Financing opportunities relate to the use of a range of debt financing instruments, such as green bonds, to support adaptation. There have also been examples where development banks have provided commercial funds to help local authorities address fiscal space constraints. In addition, there have been some examples in England where the use of PPPs has been used to unlock private sector financing for flood defences. In a similar vein, Land Value Capture and Tax Increment Financing provides an option to unlock future revenue streams through increases in land value or development through investment in flood defences. Parametric insurance has also been used to provide upfront protection for coral reefs which serve as flood defences as well as payouts for recovery.

There are also schemes which encourage private sector funding (summarised in Table 14), such as direct contributions to flood risk management schemes. Evidence from the National Audit Office suggests that around 9% of total contributions to flood defences in England came from businesses (National Audit Office, 2023) – but also from more local schemes, such as the use of climate resilience districts or water funds. There is also the potential for the use of tourism taxes and levies, as well as dedicated levies for climate resilience, such as those in Greece or Italy (Venice). There are also models which leverage revenue streams from co-investment such as in the Netherlands where revenues from wind turbines have been used to partially fund dikes.

Table 14: Examples of innovative models for private participation in flood protection, with cost recovery model. Source: Authors, updated from Watkiss and England, 2025.

Model

Examples

Cost recovery model

Green bonds / resilience bonds

UK green bonds (gilts) include coastal projects (UK Debt Management Office, n.d.) European Bank for Reconstruction and Development climate resilience bonds (Bennett, 2019)

Government pays

Public Private Partnership (PPPs)

UK Broadlands (Jacobs, n.d.) / US Fargo

Mixed

Parametric insurance

Quintana Roo (Green Finance Institute, 2024a)

User pays (public and private sources)

Local water use charges or taxes

Copenhagen Cloudburst (City of Copenhagen, 2012)

User pays (local public and private)

Land Value Capture / Tax Increment Financing

Mission Rock Bhutan Phuentsholing Township Development (ADB, 2018)

User pays

Mitigation co-benefits

RWE wind turbines on dikes, Netherlands (Windpowernl, 2022)

Co-benefit streams – energy sales

Private co-funding of flood defences

UK Flood and Coastal Erosion Risk Management Strategy

Business pays

Increased private contribution to PFR

UK assessment (Wood Environment & Infrastructure Solutions UK Limited, 2019)

User pays (private) (Possible insurance benefit).

Climate resilience districts

US (California, Connetticut),

Businesses pay

Tourist taxes / Levies

Hawaii (Jacobo, 2025), Venice, Greece

User pays

Concessional Finance

National Wealth Fund, Wales

Government pays

Natural environment

Key climate risks and adaptation opportunities

Peatland

Scotland’s peatlands face serious and accelerating degradation from multiple climate pressures. Heavier rainfall increases erosion and carbon-rich sediment loss, while warmer, drier summers accelerate oxidation and peat loss – with degraded lowland peatlands already losing 1–2 cm of soil depth annually. Heightened wildfire risk adds further pressure, and many peatlands remain inadequately monitored, meaning the true extent of degradation may be underestimated. Climate risk is projected to rise from medium to high, with the potential for irreversible loss of peatland functions including carbon storage, biodiversity support and water regulation (Sniffer, 2021).

Reversing this degradation requires more comprehensive monitoring of peat condition, integrated land-use policies prioritising protection and restoration, and targeted guidance for land managers on re-wetting, water management and erosion prevention. Peatland adaptation must also align closely with mitigation strategies. For example, directing woodland expansion onto mineral soils rather than peat, and stress-testing net zero measures against future climate risks. Better research on climate impacts to carbon stores, more systematic soil carbon monitoring, and strategic cross-sector land-use planning across agriculture, forestry and coastal zones will be essential to safeguard water quality, flood regulation and the reliability of Scotland’s greenhouse gas projections as the climate shifts (Sniffer, 2021).

Forestry

Scotland’s forestry sector faces serious and interconnected climate threats (risks N6, N8 and N9 in CCRA3). Rising temperatures and increasing drought, particularly in central and eastern regions, are reducing growth rates, affecting timber quality and shifting species viability. Commercially important species such as Sitka spruce are losing ground to more drought-tolerant alternatives. Broadleaved species face severe stress from more frequent extreme weather. Warmer conditions are also accelerating the arrival and spread of pests, pathogens and invasive species, including Phytophthora ramorum, Dothistroma needle blight and bark beetles, compounded by increasing deer damage. Overall risk is projected to rise from medium to high under future warming, while potential opportunities from longer growing seasons and expanded species suitability remain largely unrealised due to adaptation barriers (Sniffer, 2021).

Building forestry resilience requires integrated action across several fronts. Strategic land-use planning must embed both adaptation and mitigation objectives, with clearer decisions about which forest types and locations remain viable as conditions change. Improved surveillance and biosecurity at ports of entry, better soil and water management, strengthened wildfire preparedness, and diversified woodland species and structures will all help spread risk and improve long-term productivity. Warmer temperatures do create opportunities for previously unsuitable species such as Douglas fir and fast-growing bioenergy trees, but realising these benefits requires deliberate research and field trials. Enhanced cross-sector coordination, better knowledge exchange with land managers, and targeted research into future-adapted management systems will be essential to maintain carbon storage, support Net Zero transitions, and preserve the ecological and economic value of Scotland’s woodlands as the climate shifts (Sniffer, 2021).

Nature restoration

There are also multiple adaptation opportunities within the nature restoration that align with wider biodiversity and carbon mitigation targets. Case study 3 outlines on-going research NatureScot is conducting to explore catchment scale nature restoration cost estimates.

Case study 3: Catchment scale nature restoration, NatureScot

Context

  • NatureScot is working with SEPA, Scottish Water, FLS and Scottish Forestry to review and prioritise landscape / catchment scale nature restoration projects across Scotland (Scottish Biodiversity Strategy Action 2.1) and align this with SNAP3 objective NC2 on landscape scale approaches to climate adaptation and river basin management planning.

Preliminary cost estimates

NatureScot have started to estimate the costs of restoring catchments across Scotland and work is underway to refine these. Early in financial year 2026/27 they hope to have indicative costs for catchment scale restoration across Scotland, likely to be in the region of £5bn. Through 2026/27 they will develop a costed pipeline of projects out to 2045, refining the cost estimates at project scale to inform an Investment Plan for delivery.

Current methods use GIS analysis and cost assumptions based on existing projects. During 2026/27, the projects themselves will estimate costs to inform a more accurate cost estimate.

Key challenges and opportunities for climate adaptation at a catchment scale:

  • Lack of evidence on the costs of natural flood management
  • Lack of evidence to support quantification of benefits and to inform a business case
  • Lack of long-term commitments to the funding streams that currently pay for restoration and insufficient funding for the scale of the challenge
  • Immature nature finance market which is not yet delivering private investment at the scale required. 

Current spending and context

Current Scottish Government spending includes specific investment in nature based climate solutions. For 2026/27, the Scottish Budget allocates £28m for peatland restoration, supporting the restoration of over 10,000 hectares of degraded peatland. A further £37m is committed to woodland creation, aimed at delivering more than 12,000 hectares of new woodland (Scottish Government, 2026b). In addition, £26m is allocated through the Climate Taxonomy for nature restoration activities, supporting wider ecological recovery and contributing to long-term climate adaptation and resilience objectives (Scottish Government, 2026c).

Adaptation investment need

Cost estimates for the natural environment draw on the Scottish Government’s draft Climate Change Plan (CCP) and Scottish Budget Climate Taxonomy (2026/27), with expert-elicited proportions assigned to reflect the share of costs attributable to adaptation. These proportions, 25% for peatland restoration, 6.25% for woodland creation, and 20% for wider nature restoration, were derived by examining the mixed objectives of each budget line and assigning a share to adaptation relative to co-benefits such as carbon mitigation, biodiversity gain, and flood alleviation. For peatland restoration, for example, carbon mitigation is the primary objective of the CCP spend, with flood reduction and biodiversity functioning as secondary objectives; the adaptation proportion reflects this hierarchy. These proportions were cross-checked through expert review with Paul Watkiss Associates, drawing on comparable apportionment approaches used in parallel Climate Change Committee analysis for England (Watkiss et al., 2026a). No uplift for increasing climate risk was applied to these estimates up to 2040. It should be noted that other relevant actions – including wildfire management and enhanced monitoring of peatland and woodland restoration – have not been costed here and would add to the overall investment need.

Peatland

Scotland’s draft CCP projects peatland restoration ramping up from approximately 15,400 ha/yr in 2026 to just over 22,500 ha/yr from 2030 onwards, totalling 319,489 ha by 2040, contributing toward the wider Scottish Government target of 400,000 ha of peatland restoration by 2040. Total peatland restoration costs were estimated using the draft CCP central estimate of £2,894/ha (capital and resource combined), assuming a mix of peat types restored across 2026 – 2040, with capital costs derived from Glenk et al. (2025) using 2022 grant data uplifted to current prices using ONS GDP deflators. Applied to the CCP’s restoration target, this yields a total cost of £925m (£66m/yr) in 2025/26 prices for 2026–2040. A 25% adaptation apportionment was applied on the basis that, while the off-site adaptation benefits of peatland restoration represent a relatively modest share of overall benefits, there are also meaningful on-site benefits to the peatlands themselves. The UK National Adaptation Plan similarly cites climate resilience as one of four core benefits of restoration (Watkiss et al., 2026a).

We estimate climate adaptation investment need for peatland restoration at £236m to 2040, equivalent to £16.8m/yr. It is important to note that peatland restoration costs are subject to considerable uncertainty, varying significantly by peat type, depth, location, site accessibility, and contracting arrangements. Okumah et al. (2019) report a median restoration cost of £1,009/ha, with a range of £3,707 between minimum and maximum estimates. Glenk et al. (2025) report costs ranging from £191/ha at the 5th percentile to £4,483/ha at the 95th percentile. This wide cost distribution means peatland restoration estimates should be treated with particular caution. Further research to better constrain unit costs would meaningfully improve the robustness of future investment needs assessments.

Woodland creation

Scotland’s draft CCP projects woodland creation ramping up from 12000 ha/yr in 2026 to 18,000 ha/yr from 2029 onwards, totalling 258,000 ha between 2026–2040. For woodland the study used the central estimates of total costs provided by the Scottish Government. These estimates include the total capital, maintenance and administration costs between Scottish Government and businesses at a total of £1,799m to 2040.

Apportioning a share of this expenditure to climate adaptation is not straightforward. The primary objective of woodland creation is carbon mitigation, and woodlands can in some cases increase certain climate risks. For example, this can be through disease spread, fallen trees from storms, and increased vegetation growth affecting critical infrastructure (e.g., Bebber et al., 2025; Network Rail Scotland, 2024). Identifying the adaptation-specific component therefore required an evidence-based approach.

To apportion a share of expenditure, we drew on the Economic and Natural Capital Assessment (ENCA) database to compare the economic value of flood control benefits delivered by woodland creation and peatland restoration, expressed in £/ha/yr. Flood control was the only comparable adaptation benefit available to us in consistent monetary terms across both habitat types. The evidence indicates that flood control benefits from woodland creation are approximately four times lower than those from peatland restoration per hectare (Broadmeadow et al., 2023; Morris and Camino, 2011). Having assigned a 25% adaptation apportionment to peatland restoration on this basis, we therefore applied a proportionally scaled figure of 6.25% to woodland creation. This apportionment was cross-checked through expert review with Paul Watkiss Associates.

We recognise that this approach captures only one dimension of adaptation value – flood control – and that other potential adaptation benefits of woodland creation, such as shade provision, slope stabilisation, and reduced surface runoff, are not reflected in the apportionment. This figure should therefore be treated as a conservative estimate and is identified as a priority area for further research and methodological development.

We estimate climate adaptation investment need for woodland creation at £8.2m per year or £115m between 2026–2040.

Nature restoration

Finally, there is an additional budget line in the Scottish Budget 2026/27 (Scottish Government, 2026b) relating to nature restoration. The Climate Taxonomy identifies a nature restoration budget line of £26m/year, relating to policy development and implementation to manage and restore Scotland’s biodiversity and landscapes. This also includes provision of the Nature Restoration Fund and continued commitment to the Central Scotland Green Network (Scottish Government, 2026c), at a consistent level of funding. By assessing the multiple objectives of nature restoration, we assume 20% of these benefits are related to adaptation. We estimate climate adaptation investment need for nature restoration at £5.2m/yr for a total of £73m between 2026–2040.

Total adaptation investment need for natural environment

We estimate climate adaptation investment need for peatland restoration, woodland creation and nature restoration at £16.8m/yr, £8.2m/yr and £5.3m/yr respectively, totalling £30.2m/yr, or approximately £423.8m between 2026–2040 (Table 15).

Table 15: Estimated climate adaptation investment need for peatland restoration, woodland creation and nature restoration between 2026–2040. These costs represent a proportion of the total spend from the Climate Change Plan or the Scottish Budget that is related to adaptation for woodland creation (6.25%), peatland restoration (25%) and nature restoration (20%) accordingly. In 2026/27 prices.

Sector

% Apportionment

Cost p.a. (£m/yr)

Total up to 2039/40 (£m)

Peatland restoration

25%

£16.8m/yr

£236m

Woodland creation

6.25%

£8.2m/yr

£114.7m

Nature restoration

20%

£5.2m/yr

£73.1m

Total

 

£30.2m/yr

£423.8m

Macroeconomic effects and wider impacts

Macroeconomic impacts

For natural environment, we’ve modelled the total spending outlined in the Climate Change Plan and nature restoration budget (as opposed to the adaptation portion of £423.8m – see Section 4.3.3.4). This totals just over £3bn between 2026–2040, around £200m/yr.

Without cost recovery (a modelling device to isolate the spending effect): The programme generates substantial gains in “other primary” activities – forestry and land-use sectors – where output rises by around £92m and employment by roughly 1,050 jobs by 2040. Agriculture adds £1m in output and 14 jobs. Construction gains £11m in output and 170 jobs, while “all other services” contributes around £29m and 380 jobs. The overall effect is a broad-based but especially land-focused expansion, reflecting the labour-intensive and locally embedded nature of restoration activities.

With “government pays” via expenditure cuts in all areas (a stylised scenario): When costs are recovered through public spending cuts, widespread reversals occur, particularly in service sectors. “All other services” shifts from a gain of £29m and nearly 380 jobs to a loss of roughly £102m and around 1,300 jobs. Education moves from a gain of £2.8m and 60 jobs to a loss of nearly £25m and over 520 jobs. Public administration records a decline of about £43m and nearly 480 jobs. Retail, financial services and transport flip from modest gains to losses. Even the core land-use sectors are affected: “Other primary” moves from a gain of around £92m to a small loss, and construction swings from a gain of £11m and 170 jobs to a loss of around £14m and 200 jobs. Manufacturing gains are largely erased. The aggregate effect under income-tax funding is contractionary by 2040, meaning that while restoration work still channels activity into land-use sectors, the broader economic impact turns negative once cost recovery is factored in.

Policy implications: Land-based adaptation can boost rural employment and supply chains significantly, but spending-cut recovery creates widespread service-sector losses that outweigh the direct stimulus. This highlights an acute trade-off between using spending cut and preserving activity in consumption-dependent and public-service sectors. The results exclude long-term ecosystem, carbon sequestration, flood risk reduction and recreation benefits, which are particularly important for Scotland’s climate and biodiversity goals.

Wider impacts

Woodland creation and peatland restoration generate multiple co-benefits beyond direct climate adaptation. These include carbon storage, biodiversity gain, water quality improvement, air quality, temperature regulation, flood regulation, recreation, and physical health. Resource constraints prevented a comprehensive review of all co-benefits; however, we have estimated the value of a selected range, assuming that the peatland restoration and woodland creation targets for 2026 –2040 set out in the draft CCP (see section 4.3.3) are successfully completed, to current climate resilience standards, and established by 2050.

Should the 319,488 ha of peatland targeted under the draft CCP be successfully restored between 2026 and 2040, this could generate approximately £267m/yr in flood control and storm buffering benefits, £191m/yr in water quality benefits, and £199m/yr in biodiversity benefits (Table 16).

Should the 258,000 ha of woodland targeted for creation between 2026 and 2040 be successfully established to climate-resilient standards, a range of co-benefits could be realised by 2050, once the woodland has had time to develop. These include flood storage (£29m/yr–£54m/yr), recreation and health benefits (£383m/yr), biodiversity benefits (£46m/yr), and avoided mental health costs (£48m/yr) (Table 16).

These figures carry considerable uncertainty, reflecting both the pace of establishment and the assumptions underpinning each co-benefit category. They nonetheless demonstrate that the economic case for woodland creation as a climate adaptation investment strengthens substantially when co-benefits are considered. It also demonstrates that the investment need estimates presented above likely understate the full economic value of this expenditure.

Table 16 Estimated value of a range of co-benefits (£m/yr) for 258,000ha of established woodland, and 319,488ha of established peatland restoration in 2026/27 prices.

Sub-sector

Co-benefit

Total benefits (£m/yr)

Source

Woodland creation

Flood storage

£29m/yr – £54m/yr

Broadmeadow et al. 2023

Additional recreation and health

£391m/yr

Scarpa, 2003

Biodiversity

£46m/yr

Willis et al., 2003

Avoided mental health costs

£50m/yr

Shanahan et al., 2016

Peatland restoration

Flood control and storm buffering

£267m/yr

Morris and Camino, 2011

Water quality

£191m/yr

Morris and Camino, 2011

Biodiversity

£199m/yr

Morris and Camino, 2011

Current governance, funding and financing arrangements

Peatland restoration

To deliver the Scottish Government targets for peatland restoration, Scottish Government funds five delivery partners to undertake peatland restoration to meet these targets: NatureScot, Loch Lomond and Trossachs National Park Authority, Cairngorms National Park Authority, Forestry and Land Scotland and Scottish Water seen in Figure 8 (Scottish Government 2023a). There have been some elements to crowd fund in private sector finance but for now this investment is presumed to be purely public. Beyond public funding, there has been minimal investment in peatland restoration from private sources to date, including through voluntary carbon markets (Scottish Government, 2023a).

Figure 8: Financing, funding, and delivery arrangements for adaptation in peatland restoration. Adapted from Paul Watkiss Associates.

Woodland creation

The governance landscape for woodland creation is complicated, summarised in Figure 9. It is overseen and delivered by two executive agencies – Scottish Forestry and Forest and Land Scotland. Scottish Forestry is the government agency responsible for forestry policy, regulation and grant schemes. Forestry and Land Scotland are the operational land-management agency for the forest estate. However, much planting occurs on private land and for commercial purposes. Investment in new woodland creation is supported by grants through the Forestry Grant Scheme. This supports the creation of new woodland, as well as management of existing woodlands and investments in forest infrastructure such as protection.

An evaluation of the previous phase of the Forestry Grant Scheme for Scotland highlighted that the grants are unlikely to cover the total cost of the investment (Scottish Forestry, 2025). This means there will be residual costs associated with long term management and felling that will need to be met by the private sector. However, there is no data on the proportion of this investment. Given this, we have not been able to generate reliable investments in the split of public and private sector investment in adaptation. The governance arrangements for nature restoration more broadly have not been mapped in detail due to the limited resources for the study.

Figure 9: Financing, funding, and delivery arrangements for adaptation in woodland creation.

Innovation that could boost private sector participation

While nature and ecosystems have broadly public characteristics, there are a range of mechanisms (see Table 17) that can support private sector involvement in adaptation and provision of ecosystem services.

The first cluster relate to the benefits derived from ecosystems. These include dedicated payment for ecosystem services schemes, but also carbon and biodiversity credits, or for loss reduction, noting that these are co-benefits and that the locations of planting need to coincide with those needed for risk reduction, and that in such schemes the revenues are too small and benefits arise (Watkiss and Hunt, 2024; England et al., 2025). The Scottish Government, NatureScot and SEPA are supporting CreditNature, selected through the CivTech innovation accelerator, to develop a voluntary biodiversity credit market for Scotland. This will be guided by the British Standards Institute’s Nature Investment Standards programme and the Scottish Government’s Natural Capital Markets Framework (Scottish Government, 2023b; Scottish Government, 2024b; NatureScot, 2026). Similarly, in England, the introduction of Biodiversity net gain is also supporting the development of a market and is beginning to unlock new investment in ecosystem restoration (e.g. Avon Needs Trees).

There are some examples of private and corporate investment. Philanthropic investment has included around £50m over three years for rewilding across privately managed Scottish estates (BBC, 2019). Diageo has committed up to £5m over five years to restore up to 3,000 hectares of degraded peatland by 2030 – illustrating how businesses with supply chain dependencies on healthy ecosystems can become adaptation co-funders (Diageo, 2026). However, these are likely to be relatively modest and opportunistic.

A second cluster relates to investment based on sustainability outcomes, whereby the terms of financing are preferential based on the impact. This includes payment for ecosystem services, sustainability linked loans, as well as direct investments in nature-positive businesses and redeemable equity. There have been efforts by the Scottish National Investment Bank to provide concessional credit lines to support. For example, the SNIB recently provided a £50m cornerstone investment to the Gresham House Forestry Fund, 60% of which will be invested in Scotland, and which includes commitment to climate resilience (Scottish National Investment Bank, 2026).

Finally, there are also a cluster of insurance-based innovations. For example, in Colombia, the City of Bogota has extended previous work by The Nature Conservancy (TNC) on Water Funds. This provides a proactive fund where beneficiaries pay into funds which support proactive risk reduction as well as offering parametric insurance for response and recovery. In Mexico, the Quintana Roo coral reef scheme sees local businesses and tourists paying in alongside government to support reef protection and receive parametric insurance. In addition, the NATURANCE and PIISA Horizon Europe projects examining how disaster risk financing can be combined with nature-based solutions to develop scalable insurance products (Climate-ADAPT, 2026).

Table 17: Examples of innovative models for private participation in natural environment, with cost recovery model. Source: Authors, updated from Watkiss and England, 2025.

Model

Examples

Cost recovery model

Anticipatory parametric insurance for damage reduction

Paramos Wildfire Facility, Colombia

User pays

Blockchain carbon credits for ecosystem services

AirEco (Indonesia) (SEED, n.d.)

User pays

Online platform with blockchain tokens, and enhanced Monitoring, Reporting, and Verification

Global Mangrove Trust (Thailand) (SEED, 2018)

User pays

Voluntary carbon markets (with NbS projects)

REDD+ examples, such as Mai Ndombe REDD+ project (Democratic Republic of Congo) and Lariba REDD+ project (Zimbabwe) Reforestation/afforestation projects such as CommuniTree Carbon Program (Nicaragua) Regenerative agriculture projects such as Nature Carbon (Cerrado Biome) (Brazil)

Private sector pays

Biodiversity credits/offsets

Ambatovy Minerals Project (Madagascar) (World Bank Group, 2016) Lom Pangar Hydropower Project (Cameroon) Savimbo (Colombia, Colombian Amazon) (Dasgupta, 2024) WWF Pilot Projects (Tanzania) (WWF, n.d.)

Private sector pays but can generate value addition through financial return

Payment for Loss Reduction

Restoration Insurance Service Company (RISCO) (Philippines, Mexico, Brazil, Malaysia) – mangroves (CPI, n.d.)

User pays

Sustainability premium and traceability app

Monsoon Tea Company (Thailand) (GSMA, 2024)

User pays

Investment fund for nature-positive businesses

Tropical Resilience Fund (Africa, Latin America, East/Southeast Asia) (Global Innovation Lab for Climate Finance, n.d., a)

Private sector pays

Payment for ecosystem services

The Nature Conservancy (TNC) Water Funds Portfolio (TNC, 2024) BIOFIN – capacity building in identifying and implementing relevant ecosystem services payments (BIOFIN, 2024a) Forest Resilience Bond (California, US) (Green Finance Institute, 2024b) UN-REDD Programme Initiatives

User pays

Sustainability Linked Loans

ING’s Nature Framework and SLLs (Europe) (ING, 2025)

User pays

Direct investment in NbS-generating businesses/ projects (equity-based)

Cacao Oro de Nicaragua (sustainable agroforestry for cacao production) (GIZ, 2023) African Conservation and Communities Tourism (ACCT) Fund (eco-tourism supporting conservation) (GIZ, 2023)

User pays

Impact bonds (e.g. conservation impact bonds)

Deshkan Ziibi Conservation Impact Bond (DZCIB) (Canada) (Arjaliès, 2024)

Government or philanthropic organization pays

Blended Finance for NbS

SNIB FORESTRY

Amazon Biodiversity Fund (Brazil) (Ivory, 2025) Tropical Forest Forever Facility (Brazil/World Bank) (weADAPT 2025)

Consumer/end user pays and gets access to better services, cost savings, or enhanced ecosystem benefits.

Redeemable equity

Regenera Ventures Fund (Mexico) (Brasil-Leigh et al., 2024)

User pays

Certification and Standardization

Certification of NbS portfolios (Morocco, Senegal) (GEF, 2021)

Government and businesses pay

Insurance and risk-transfer mechanisms

Quintana Roo Coral Reef Insurance (Mexico) (GIZ, 2023)

Consumers pay via tourism, and taxpayers via government, while benefiting from public goods – tourism assets, reduced disaster risk, and ecosystem health.

Platform / ecosystem development

SCALE (global)

Government pays

Transport

Key climate risks and adaptation opportunities

Road networks

Scotland’s road network faces a complex and intensifying set of climate-driven pressures threatening long-term reliability, safety and connectivity. More intense rainfall is accelerating surface water flooding, overwhelming drainage systems and causing recurring closures on trunk and local roads alike. In upland and rural areas, where single-access routes are common, even short-lived disruptions can isolate communities and disrupt supply chains. Saturated soils and steep topography are heightening landslide risk, most visible along routes such as the A83 at the Rest and Be Thankful, where repeated slope failures have led to long detours and escalating maintenance costs. Extreme temperatures add further stress, damaging pavements and bridges in summer while winter storms bring wind hazards, fallen debris and ice-related disruption (Sniffer, 2021).

Strengthening resilience will require a more strategic, forward-looking approach to maintenance, planning and design. Key priorities include identifying road corridors most vulnerable to flooding and slope failure, scaling up green-blue infrastructure and Sustainable Drainage Systems, improving drainage capacity, and applying soft-engineering approaches such as vegetation management to stabilise slopes. Better condition monitoring, data sharing and early-warning systems for rainfall, wind and landslide risk can support more proactive hazard management. For new infrastructure, mainstreaming climate adaptation into design standards will be essential to avoid costly retrofits, while stronger resilience indicators and more consistent climate risk assessment across local road authorities will be critical to closing Scotland’s current adaptation gap (Sniffer, 2021).

Rail networks

Scotland’s rail network, spanning over 1,700 miles and 360 stations across diverse and challenging terrain, is already experiencing the impacts of a changing climate, with risks projected to intensify over the coming decades (Network Rail Scotland, 2024). Observed changes include warmer average temperatures, altered rainfall patterns, and an increase in the frequency and severity of extreme weather events.

More intense and prolonged rainfall increases the likelihood of surface water and river flooding, as well as saturated ground conditions, contributing to earthwork instability. Embankments and cuttings, many of which are Victorian era assets, are becoming increasingly vulnerable to failure, leading to disruption, safety risk and higher maintenance demand. Storms and high winds continue to cause disruption through fallen trees, debris and damage to exposed assets, while coastal routes face longer term risks from erosion, sea level rise and increased wave action (Network Rail Scotland, 2024).

Higher temperatures are an emerging and growing risk, with hotter and more frequent heat events increasing the incidence of rail buckling, overhead line sag and emergency speed restrictions, affecting network performance and reliability (Network Rail Scotland, 2024).

Wind, flooding and snow are consistently the most disruptive and costly weather hazards on the Scottish network, with weather related disruption incurring significant Schedule 8 compensation costs (payments made to train operators following unplanned disruption) over the past decade (Network Rail, 2024). Around 90% of Network Rail assets are as they were when installed before the year 2000 and were not designed to contend with the more aggressive weather conditions now being experienced or forecast for the future under climate change (Network Rail, 2024).

Network Rail Scotland’s key adaptation priorities include delivering revised climate change risk assessments to identify future vulnerable locations, developing a long-term adaptation strategy using an adaptation pathways approach, and enhancing monitoring and assurance of resilience actions across the network (Network Rail Scotland, 2024).

In addition to spending on infrastructure, there may be some spending being undertaken on rolling stock companies (ROSCOs), but this is not available and therefore excluded from estimates of adaptation investment need.

Current spending and context

Specific information on the cost of climate proofing trunk roads and motorways within Scotland is currently not available. However, the Scottish Budget 2026/27 allocates approximately £82m to adaptation and resilience for trunk roads and motorways (Scottish Government, 2026c). This budget line covers trunk road adaptation schemes to improve network resilience to climate change and severe weather, casualty reduction measures, and Traffic Scotland operational commitments.

Furthermore, Network Rail Scotland has already spent £103.1m of primary resilience interventions to date in control period 7 2024–2029 (CP7). The largest shares have been directed at earthworks (£59.8m) and drainage (£27.7m), reflecting the priority placed on managing slope instability and flood risk across the network.

Adaptation investment need

Transport adaptation investment need was assessed across two sub-sectors: trunk roads and motorways, and rail. Other transport modes, including ferries, canals, aviation, and active travel, have not been included in this analysis and would add to the overall investment need.

Road networks

There is limited information regarding future investment need for climate adaptation on the road network. Strategic Transport Projects Review 2 (STPR2) estimates indicate a capital cost banding of £1bn – £2.5bn over the life of the review from 2022–2042 (Jacobs & AECOM, 2022), reflecting the anticipated scale of investment required to adapt the trunk road and motorway network to climate change. However, this figure was explicitly indicative rather than a precise cost estimate, based primarily on adaptation to flooding at highly exposed locations and not accounting for the full range of relevant climate hazards, including landslides, high winds, scour, and high temperatures. Transport Scotland anticipated that a dedicated Trunk Roads Climate Change Adaptation Plan would establish more robust costs in due course and does not consider the STPR2 figures sufficiently reliable for planning purposes.

To estimate adaptation investment need for trunk roads and motorways, we explored current Scottish Government budget lines with a neutral or positive adaptation influence were identified from the Scottish Budget 2026/27 and associated Climate Taxonomy (Scottish Government, 2026b; 2026c). The Transport Portfolio contains 15 budget lines associated with the Trunk Road Network, of which four, relating to network depreciation and PPP payments, were excluded as not relevant to climate adaptation, leaving 11 budget lines for analysis (Table 18).

Table 18: Budget lines from the Scottish Government Climate Taxonomy 2026/27 that we included in adaptation investment need analysis via exploring the additional ‘climate proofing’ spend or the whole budget.

Budget lines included in analysis

2026/27 budget (£m)

Climate proofing / whole budget

Capital Land and works

£223.26m

Climate proofing

Tay Road Bridge Capital Grant

£3.09m

Climate proofing

Tay Road Bridge Resource Grant

£2.2m

Climate proofing

Adaptation and resilience

£82.32m

Whole budget

Bridge Strengthening and Repairs

£149m

Climate proofing

Woodside Viaduct

£23.7m

Climate proofing

Trunk Roads Structural Repairs

£142m

Climate proofing

Routine and Winter Maintenance

£172.34m

Climate proofing

Safety Camera

£8.2m

Climate proofing

Other Trunk Road Expenditure

£14.28m

Climate proofing

Road Safety

£19.36m

Climate proofing

Two approaches were applied to these budget lines. For ten of the eleven lines, a climate-proofing uplift was applied to estimate the additional investment required to maintain network resilience under a changing climate. Uplift factors of 2.5% and 10%, representing the lower and upper bounds of the additional cost of climate-proofing infrastructure, were drawn from scaling factors in the Asian Development Bank (2014) and World Bank (2019). Crucially, the uplift itself – that is, the difference between the original and uplifted budget – represents the estimated additional spend attributable to climate-proofing, rather than the total uplifted budget. For the adaptation and resilience budget line, the full budget allocation was retained, as this line is wholly directed at adaptation activity.

Applying the climate proofing approach and budget lines outlined in Table 17, the estimated adaptation investment needed for trunk roads and motorways is between £101.2m–£158.06m/yr, amounting to approximately £1,417.52m–£2,212.82m over the period 2026–2040 (Table 19).

Table 19: Climate change adaptation investment need for trunk roads and motorways between 2026-2040. Presented in 2026/27 prices.

Transport (road)

Period

Lower estimate (2.5% uplift) (£m)

Upper estimate (10% uplift) (£m)

Total (2026– 2040) (£m)

£1,417.52m

£2,212.82m

Total (2026–2040 p.a.) (£m/yr)

£101.25m

£158.06m

Local road networks, maintained by local authorities rather than Transport Scotland, are not captured in this analysis. These represent an additional and likely material cost that is expected to grow as climate risk intensifies but fell beyond the scope of the present study. Several methodological limitations are also worth noting. Some budget line descriptions overlap, introducing a degree of potential double-counting (see supplementary data for more detail). The 2.5% and 10% uplift range is derived from international infrastructure literature and may not fully capture the specific risk profile of Scotland’s trunk road network. Applying a larger uplift – as some international studies have suggested may be appropriate for higher emissions scenarios – would yield considerably higher estimates, suggesting the figures presented here may be conservative.

These estimates were triangulated by scaling adaptation cost estimates from Neumann et al. (2025) to the Scottish context as an international benchmark. Neumann et al. (2025) estimated EU transport adaptation costs at approximately 0.04%–0.06% of GDP per year under moderate to high emissions scenarios. Applying this range to Scotland’s GDP yields an indicative figure of £90m – £142m/yr (2026/27 prices), which is broadly consistent with the trunk roads and motorways estimate presented above. However, this comparison should be treated with caution: the nature and projected intensification of climate hazards vary considerably across EU member states and diverges from Scotland’s risk profile in important respects. Furthermore, Neumann et al. (2025) does not provide a breakdown between road and rail spending, limiting the precision of this transfer. These figures were therefore used as an indicative benchmark to assess how our estimates compare at an international level, and are not included in our reported adaptation investment need figures.

Transport Scotland is also actively working to better understand the scale of investment needed for adapting trunk roads to be resilient to climate change. For example, they are developing the Vulnerable Locations Operational Group (VLOG) prioritisation tool to identify climate-vulnerable locations across the trunk road network and better constrain the costs of necessary upgrades and renewals (see case study 4). Consequently, the indicative adaptation investment estimates outlined in this report are expected to be further refined as this ongoing analysis matures.

Case Study 4: Vulnerable Locations Operational Group (VLOG) prioritisation tool

The Vulnerable Locations Operational Group (VLOG) prioritisation tool, developed by Transport Scotland, identifies which parts of Scotland’s trunk road network are most vulnerable to climate change and where investment is most needed. By bringing together asset information to assess exposure, sensitivity, and adaptive capacity, the tool provides a consistent, evidence-based approach to understanding climate risks and prioritising funding across the wide range of geotechnical and geometric challenges throughout Scotland’s network.

The tool uses a scoring and ranking system that evaluates locations against a range of factors including whole-life asset costs, effectiveness of risk reduction, environmental benefits, social impacts, and economic consequences of route disruption. This allows different locations and interventions to be compared fairly and transparently, with quality checks, peer review, and alignment with existing appraisal and business case processes built in to ensure decisions can be reviewed and approved through established governance structures.

Over time, the VLOG tool will help Transport Scotland baseline and monitor how climate-related risks evolve as projects progress and conditions change. For adaptation planning specifically, understanding which locations are most vulnerable and what interventions deliver the greatest risk reduction is essential for ensuring investment is targeted where it will have most impact – moving beyond reactive maintenance towards proactive, planned adaptation. Critically, the tool will enable more asset-based adaptation investment need estimates, moving beyond the indicative budget-line approach used in this report towards a robust, location-specific evidence base for future climate resilience planning across Scotland’s trunk road network.

Image: Example of VLOG prioritisation tool dashboard outlining climate-vulnerable sites.

Rail networks

Interpretation of Network Rail Scotland Investment estimates

The rail investment figures presented here represent indicative, scenario‑based estimates developed by Network Rail Scotland to explore the potential scale of climate adaptation investment required to maintain current levels of service and safety under future climate conditions.

The upper end of the range reflects a plausible future pathway that includes what are currently hypothetical transformational capital interventions at particularly vulnerable locations, which may or may not be required depending on how climate risks evolve over time, and how Network Rail chooses to sequence interventions that are required based on its adaptation pathways programme.

As with other sectors, the absence of agreed levels of service and climate risk‑tolerance targets means these figures are best understood as order‑of‑magnitude planning assumptions, intended to inform strategic discussion rather than define investment requirements.

Investment need estimates

Investment need estimates for the Scottish rail network were drawn directly from high-level analysis Network Rail Scotland’s internal climate adaptation assessment. This draws on climate-based modelling, expert judgement, and current spending patterns to project costs across two categories of spend: (a) operations, support, maintenance and renewals (OSMR), which covers the ongoing costs of maintaining a climate-resilient network; and (b) major capital interventions (MCI), which covers larger-scale infrastructure investment at vulnerable locations. Full details of the underlying methods, assumptions, and calculations are provided in Appendix B.

Total potential adaptation investment requirements for the Scottish rail network are estimated at between £113m–£338.1m/yr, amounting to £1,581.8m–£4,733.6m when operations, support, maintenance and renewals (OSMR) and major capital interventions (MCI) are included over the period 2026–2040 (all figures in 2026/27 prices) (Table 20). This spend would cover increased operational and maintenance activity in response to more frequent severe weather. Such activity includes additional seasonal treatment trains, emergency speed restrictions, and reactive repairs following weather-induced failures, targeted renewals to address accelerated asset degradation across drainage, earthworks, and track. At the upper end, it includes hypothetical transformational capital schemes at locations where incremental intervention alone cannot sustain current service levels, such as infrastructure re-alignment in response to coastal erosion.

The wide range between lower and upper bounds, particularly for MCI, reflects the inherent difficulty of projecting major capital requirements over long time horizons. Network Rail Scotland note that ongoing work under their Adaptation Pathways Programme is expected to narrow these ranges as vulnerable locations become better characterised. These figures represent one plausible investment scenario focused on continued service delivery; alternative investment scenarios could reasonably be explored.

Table 20: Estimated climate change adaptation investment need for Network Rail Scotland, 2026–2040, based on CP7 remaining spend, CP8 and CP9 allocations under a continued service scenario, and pro-rated 2039/40 spend. All figures uplifted to 2026/27 prices (assuming 2% nominal growth per annum) from 2023/24 base prices provided by Network Rail Scotland.

Transport (rail)

 

Operations, support, maintenance and renewals (OSMR)

Operations, support, maintenance and renewals (OSMR) + major capital interventions (MCI)

Period

Lower estimate (£m)

Upper estimate (£m)

Lower estimate (£m)

Upper estimate (£m)

Total (£m)

£998.2m

£1,815.3m

£1,581.8m

£4,733.6m

Total (£m/yr)

£71.3m/yr

£129.7m/yr

£113m/yr

£338.1m/yr

Case Study 5: Extreme rainfall and landslides at the Falls of Cruachan

The Oban branch of the West Highland Line plays a vital role connecting rural communities around Oban with the rest of Scotland, running alongside the A85 trunk road through mountainous terrain with limited diversionary routes when disruption occurs. The Northwest Highlands are the wettest area of Great Britain. Parts of the railway line – particularly near the Falls of Cruachan – are highly susceptible to landslides due to prolonged heavy rainfall, steep topography, and proximity to unstable slopes. In December 2022, approximately 100 tonnes of material moved down Ben Cruachan’s slopes onto the railway and A85, caused by a blocked culvert overtopped during adverse weather.

Temporary repairs to reopen the railway, including slope stabilisation, signalling repairs, and new track, cost approximately £0.5m. A more permanent fix is now underway at a cost of £3m, encompassing drainage renewal, soil nailing, erosion protection, and lightweight catch fences. Control period 7* plans also include approximately £5m for ongoing vegetation removal and maintenance of the line’s stone signals, which date to 1882 and are approaching life expiry.

Further investment will be required in later years to provide a longer-term solution as increasing frequency of adverse weather events heightens landslide risk. Network Rail Scotland’s current view is that resilience work will combine low-to-medium capacity catch fences with modern instrumented barrier technology along the four-mile length. This is at an estimated cost of circa. £5m in CP8, alongside continued improvement of drainage asset maintenance to better manage water movement during heavy rainfall events. Longer-term options under consideration through Network Rail Scotland’s climate change adaptation pathways programme include a combination of nature-based solutions, such as enhanced vegetation management to stabilise slopes, alongside engineered interventions, reflecting a broader shift towards integrated, pathway-based approaches to managing climate risk on vulnerable parts of the network.

*A control period is Network Rail’s fixed five-year funding and planning cycle that sets budgets and outputs for the railway (e.g., CP7 1 April 2024 – 31 Mar 2029).

Image: Landslide over railway at Falls of Cruachan.

Macroeconomic effects and wider impacts

Macro-economic impacts

Trunk roads and motorways

For macroeconomic modelling we assume trunk roads and motorways require the adaptation investment between 2026–2040 of approximately £90m/yr. These have differing pricing years compared to section 4.4.3.1. This spending flows primarily to construction and wholesale/retail (vehicles), with significant additional activity in public administration, architectural services and a wide range of supply-chain sectors.

Without cost recovery (a modelling device to isolate the spending effect): By 2040, construction gains £12.7m in output and 191 jobs, while wholesale/retail (vehicles) adds £29m in output and 516 jobs. Supply-chain effects spread to fabricated metals, manufacturing, energy and primary sectors, and household consumption spillovers boost retail, financial and travel services. No major sector is worse off during the construction period; the programme delivers broad-based increases in output and employment across the economy.

With “government pays” cost recovery (a stylised scenario): When costs are recovered through higher income tax, the core delivery sectors retain net gains. Construction still adds £3.6m in output and 43 jobs, wholesale/retail (vehicles) retains £26.6m in output and 472 jobs, and public administration adds £5.5m and 55 jobs – because they remain central to the works. However, many consumer-facing sectors flip to losses. Retail (excluding vehicles) loses £3.7m in output and 88 jobs, while “all other services” records a loss of £24.3m and 385 jobs. Manufacturing and primary sectors similarly shift from gains to losses as higher income tax squeezes household spending and raises labour costs, reducing demand and competitiveness.

Policy implications: Without cost recovery, roads adaptation delivers a strong temporary stimulus across the economy. With income-tax funding, construction and vehicle-related sectors still gain, but many consumer and trade-exposed sectors lose activity and jobs. Policymakers must balance fiscal sustainability against these short-term economic effects and against the long-term resilience benefits of climate-ready road infrastructure.

Rail Network

Using the lower estimate for investment in operations, support, maintenance and renewals (OSMR) and major capital interventions (MCI), rail network climate adaptation requires approximately £100m/yr of investment from 2026–2040. The spending flows primarily to wholesale/retail (vehicles) for rolling stock maintenance and replacement, construction for network reinforcement, and public administration for programme management.

Without cost recovery (a modelling device to isolate the spending effect): The programme creates a demand stimulus that peaks at 0.5% GDP growth (around £100m) and 1,500 FTE jobs by 2040. The sectors delivering the works experience the largest gains, with positive spillovers to consumer services as higher household incomes boost spending. Prices rise only modestly as workers migrate to Scotland to meet labour demand, easing wage pressures. All sectors benefit or remain unaffected during the investment period, though these impacts fade roughly 15 years after spending ends.

With “government pays” cost recovery (a stylised scenario): When the Scottish Government recovers costs through higher income tax, the GDP and employment gains are largely eroded and turn temporarily negative in many sectors. Higher income tax reduces household disposable incomes, particularly for higher earners, dampening the consumption that drove much of the initial stimulus. At the same time, employers partly absorb the tax rise through wage bargaining, raising their production costs and pushing prices higher for longer, which weakens Scotland’s export competitiveness. The core delivery sectors – wholesale/retail (vehicles), construction, and public administration – retain smaller gains because they remain central to the works, but consumer-facing services such as “all other services” experience significant job and output losses.

Policy implications: Income-tax funding can protect long-term rail resilience, but it imposes short- to medium-term costs in terms of growth, employment and real incomes, particularly for higher-income households. Policymakers need to weigh these costs against the avoided disruption and economic losses from climate-damaged rail infrastructure.

Current governance, funding and financing arrangements

Road networks

Delivery arrangements for road infrastructure investment are shown in Figure 10, the majority of which is funded through the public sector. Transport Scotland pays for investment on the trunk road network and contracts a range of companies to ensure Scottish trunk roads are safe, efficient and well management (Transport Scotland n.d). This includes both maintenance contracts (provided by Amey and Bear Scotland), but also a range of Design, Build, Finance and Operations (DBFO) contracts. Local roads are managed by local authorities, who pay for investment in the local road network. Scottish Government (including Transport Scotland) spent £3bn on transport in 2023/24. Local Authorities spent £1.17bn in 2023/24 (Transport Scotland, 2025).

While all adaptation costs for the trunk road network are met from government, local costs are met by local government from a mix of sources. Local Government spent £27bn in 2024/25 from four sources of income. Excluding service income (which is ringfenced for uses such as early learning and childcare but not transport) the remaining £16bn came from Scottish Government grant (63%), council tax (18%) and non-domestic rates (19%) (Scottish Government, 2026d). Assuming that adaptation costs are evenly apportioned across funding sources, applying these shares to the relative share of the total investment, we estimate that private sector contributes around 10% of the costs of adaptation, split evenly between households and businesses.

Figure 10: Financing, funding, and delivery arrangements for adaptation in road networks.

Rail networks

The rail sector is a complicated set of governance arrangements (summarised in Figure 11), since rail infrastructure, services and rolling stock are managed by separate organisations. Network Rail manages railway infrastructure. It generates a range of income from access charges, commercial income and an electricity for traction programme. The majority of rail services in Scotland are publicly provided by ScotRail through Scottish Rail Holdings Ltd (SRH Limited), an arm’s length company owned and controlled by Scottish Government (Transport Scotland, n.d), though other franchise operators (e.g. Avanti) run services serving the wider UK.

Whilst the study has not generated estimates of required adaptation spend for rolling stock, this is also important. Rolling stock is privately owned and leased from Rolling Stock Operating Companies (ROSCOs), who have invested over £20bn in rolling stock since 1995 (Mather, 2025). Payments are made from the train operating companies to ROSCOs for the lease of the stock – in 2024/25 these totalled about £2.7bn in the UK (Office of Road and Rail, 2025). Scotland intends to also continue securing financing for the stock, and a lease model (Scotrail, 2026).

Figure 11: Financing, funding, and delivery arrangements for adaptation in the Scottish rail sector.

There are already significant efforts ongoing to consolidate the sector. The UK Government is bringing franchises into public ownership as contracts expire, it is consolidating track management and rail services under Great British Rail to provide overall coordination of track and timetable franchising under one guiding arm. All franchises are expected to be due back in public ownership by the end of 2027. Under this model, Scottish ministers will set a rail strategy for Scotland and fund GBR to provide Infrastructure in Scotland (Department for Transport, 2025), while ScotRail will continue to deliver services. The government expects the leasing of rolling stock from ROSCOs to continue where such investments offer value for money (Mather, K., 2025). Figure 11 represents the funding arrangements following this transition.

To provide an initial view on the split of funding for adaptation, the study used the aggregate income and expenditure for the UK Rail Sector for Scotland (ORR, 2025). This breaks down the relative total income from different sources for the overall sector, and the expenditure, excluding internal money flows. This shows that in 2024/25, government funding made up 66% of all rail sector income, with the remainder coming from passenger income (29.6%) and the remainder coming from industry (1.8%) and freight industry (2.8%). However, looking over time, there has been significant variation in this split, with 50% of income at one point coming from private income. At present, it is assumed Network Rail does not apportion or ringfence income, meaning that adaptation costs are assumed to be split between public and private sector in the same proportions.

Innovation that could boost private sector participation

For transport, road user charging, including city centre congestion charging and expanded parking zones, could generate revenues to help fund climate-resilient infrastructure upgrades. Toll financing on major road networks or adaptation projects offers a further avenue, with potential for private operators to contribute to or co-finance expensive resilience interventions in exchange for revenue streams from infrastructure users. Similarly, there is the potential to mainstream adaptation costs into rail ticket prices. This could be to fund maintenance but can also be blended into PPPs to provide support to capital investment.

There is also the potential to leverage wider infrastructure investment. SSEN Transmission’s commitment of over £200m to Highland roads and bridges demonstrates how major private infrastructure developers can contribute meaningfully to transport resilience as a condition of their wider operations (SSE, 2026).

Finally, there are a typical spread of debt financing models which could be used, such as the use of green bonds or sustainability linked loans. There also more innovative investment approaches such as Collective Investment Vehicles (CIVs), which enable diversification of risk and attract private capital for adaptation investments. One prominent example is the Urban Resilience Fund. Managed by Meridiam and supported by the Rockefeller Foundation, this is a €500m investment fund, split between Africa and OECD countries, and includes a €20m catalytic capital fund for project preparation. Other examples are given in Table 21.

Table 21: Examples of innovative models for private participation in Transport, with cost recovery model. Source: Authors, updated from Watkiss and England, 2025.

Model

Examples

Cost recovery model

Collective Investment Vehicles

Urban Resilience Fund, Meridam

Government pays

Climate-smart PPPs for Roads

Kuala Lumpur Smart Tunnel, Malaysia

Government pays

Tolls

World Bank PPP guidance

User pays

Hypothecated taxes (e.g. Congestion charging, road user charging)

London

User pays

Climate Insurance-linked Infrastructure Financing

Climate Insurance-Linked Resilient Infrastructure Financing (CILRIF)

User pays

Sustainability-linked bonds / debt finance

Song and Medda, 2021

Government pays

Climate resilience districts / Business Improvement districts

US (California and Connetticut)

Local businesses and households pay

Water

Key climate risks and adaptation opportunities

Scotland’s water supply systems face increasing climate-driven pressures. Rising temperatures, shifting rainfall patterns and growing demand are placing new stresses on water resources (Sniffer, 2021). Projections indicate that under +2°C and +4°C scenarios, several regions could experience supply-demand deficits by mid-century (Scottish Water, 2024). Reservoirs in Scotland are increasingly vulnerable to extreme rainfall, high inflows and warmer temperatures, which can erode embankment integrity and reduce water quality. While current adaptation measures keep public water supply risk in the low category, more than half of Scotland’s population could be at risk of water scarcity by 2050 during very dry periods (Scottish Government, 2023c). River flooding currently affects 279 Scottish Water assets during frequent storm conditions, with a further 11 Scottish Water assets projected to face increased fluvial exposure beyond 2050. Surface water flood risk is also set to grow, with 8 Scottish Water assets at increased risk by 2050, rising to 171 by 2080 (Scottish Water, 2024).

The wastewater system faces similar pressures, with more intense rainfall driving sewer overflows, inundating treatment works and raising pollution risk (Sniffer, 2021). River flooding already affects 720 of Scottish Water’s wastewater assets during frequent storm conditions, with a further 194 projected to face increased fluvial exposure beyond 2050 (Scottish Water, 2024). Surface water flood risk is set to escalate further, from 65 wastewater assets at increased risk by 2050 to 463 by 2080 (Scottish Water, 2024).

Reducing these risks requires maintaining and strengthening Scotland’s proactive approach to water management through long-term, evidence-based investment. Future resilience will depend on integrating climate projections into reservoir inspection regimes, infrastructure planning and risk assessments, ensuring systems are designed for higher peak flows and more volatile conditions. Demand-side measures, including leakage control, metering and behavioural change, will be increasingly critical, as CCRA3 shows that only scenarios incorporating additional adaptation result in sustained supply-demand surpluses. For wastewater, targeted investment in flood-exposed sites, expansion of green-blue infrastructure, and upgrades integrating SUDs and nature-based solutions will be essential. A more systematic approach aligning water resource planning with climate risk modelling, alongside strategic catchment-wide thinking, will be critical to ensuring Scotland’s water systems remain robust and secure as climate pressures intensify (Sniffer, 2021).

Private water supplies (Lawson and Davies, 2025) serve approximately 3.5% of Scotland’s population, mostly in more remote rural areas. Risk to private supplies is less well understood, but they are likely to be particularly vulnerable to water scarcity events (DWQR, 2024). Requirements and effective measures to support climate resilient private water supplies are far less understood than public water systems, even though private water supplies are more vulnerable. At a supply-level, private water supply owners are responsible for investment to upgrade the system – and they are responsible for reporting issues such as water availability to their local authority. Private water supply owners may be eligible for a Scottish Government grant of up to £800 to improve their existing private water supply (mygov.scot, 2025), though this initiative is not focused on climate resilience. For example, a switch from surface to bore supply is considered to offer climate resilience (Rivington et al., 2020).

Climate adaptation in the water sector can also overlap with initiatives in the natural environment, particularly nature-based solutions aiming to slow run-off and increase water quality like the Loch Katrine programme (see case study 6).

Case Study 6: Loch Katrine Catchment Management, Scottish Water

Loch Katrine, located within the Loch Lomond and Trossachs National Park, is the primary source of drinking water for Glasgow. Climate modelling of key water quality parameters, under 2050 and 2080 scenarios, projects a deterioration in raw water quality beyond the treatment capacity of existing works, driven by the warmer, drier summers and more intense rainfall events associated with climate change. Without intervention, this trajectory would necessitate significant capital upgrades to Glasgow’s water treatment infrastructure.

Scottish Water, in partnership with long-term tenant Forestry and Land Scotland (FLS), has developed a 10-year Land Management Plan (LMP) for the 9,500-hectare Loch Katrine catchment, approved by Scottish Forestry in 2024 (Forestry and Land Scotland, 2023). Scottish Water will invest £11m across multiple investment periods in two core programmes: (1) 4,600 hectares of native woodland creation, largely through rewilding and natural regeneration, expanding woodland from the loch shores into higher elevations; (2) up to 2,000 hectares of peatland restoration and management – through rewetting, reprofiling, and encouraging sphagnum moss to restore the peatland’s capacity to retain water and slow surface runoff.

Peatland restoration receives co-funding through Peatland ACTION, the Scottish Government’s national programme backed by a £250m commitment to restore 250,000 hectares of peatland by 2030.

Image: Loch Katrine. Taken from Scottish Water: Loch Katrine Woodland Creation and Peatland Restoration – Scottish Water.

By stabilising soils and locking carbon into the landscape rather than allowing it to run off into the water environment, the catchment management measures aim to halt the modelled deterioration in raw water quality. Healthy woodland and functioning peatland slow surface runoff, reduce the volume of organic matter reaching the loch, and improve the resilience of the catchment to both drought and extreme rainfall. In doing so, the LMP is expected to offset the need for significant capital investment in treatment process upgrades that would otherwise be required, making it a proactive, nature-based alternative to reactive infrastructure expenditure. Beyond the water quality rationale, the LMP is projected to deliver over 700,000 tonnes of CO₂e sequestered over 60 years and a 40% improvement in biodiversity across the site (Scottish Water, 2026d).

Loch Katrine illustrates how proactive catchment management can function as a cost-effective climate adaptation strategy, deferring capital infrastructure costs while delivering carbon, biodiversity, and water quality co-benefits.

Current spending and context

We do not have specific information on Scottish Water’s current climate adaptation investment. However, several ongoing programmes demonstrate adaptation relevant investment. For example, Scottish Water is developing a major demand reduction programme in response to projected summer water shortages, including an estimated 260Ml/d deficit by 2050 under a 1-in-150-year drought scenario. A £1.8m domestic smart monitoring trial launched in Dundee in 2025 (2,300 monitors) is testing whether providing households with real time usage data can reduce consumption, with results expected in 2028 (Scottish Water, 2026b). This builds on a successful pilot with 3,000 business users in Inverness and Orkney and underpins a planned £60m national rollout of smart meters for 130,000 business customers (Scottish Water, 2026a). The rollout aims to achieve an 80Ml/d reduction by 2039 through reduced customer side leakage, improved network leakage detection, and behaviour change. These initiatives help reduce pressure on water resources during hotter, drier summers and strengthen overall system resilience.

Adaptation investment need

Investment need estimates were drawn from Scottish Water’s Strategic Review (SR)27 of Charges Business Plan (2027/28–2032/33) and associated technical appendix, combined with their longer-term indicative adaptation investment estimate of £2 – 5bn to 2050 (Scottish Water, 2026a; Scottish Water, 2026c). The portion of the longer-term estimate falling within the 2033–2040 research window was incorporated alongside the SR27 allocation. Note that 2026/27 is not included as these data were not available. Full details of these underlying methods, assumptions, and calculations can be found in Appendix C.

Total climate change adaptation investment requirements for Scottish Water over 2027– 2040 are estimated at between £82.1m – £189.7m per year, equivalent to £1,067.3m –£2,465.9m in 2026/27 prices (Table 22). We do not include 2026/27 as this information is not available. For SR27 (2027/28 – 2032/33), the lower estimate is £357.9m and upper estimate is £471.3m. This SR27 investment spans operational resilience (including standby generators at 52 sites to guard against storm-related power outages); asset resilience measures to address drought pressure on water supply and sewer flood risk from increasingly extreme rainfall; and catchment-scale transformation through pioneer catchment pilots and drainage partnerships. The upper estimate for SR27 also includes retained risks such as water quality and the water environment (Scottish Water, 2026a). Scottish Water has developed a long-term indicative adaptation investment estimate of £2 – 5bn to 2050. Deducting the SR27 allocation, the remaining estimate of required investment is distributed equally across annual periods from 2033/34 to 2049/50, with the portion falling within the research window (2033/34–2039/40) incorporated here.

The widening range between lower and upper adaptation estimates in later periods reflects the inherent uncertainty in projecting long-term adaptation investment need as climate risks intensify. It should also be noted that there is potential for some double counting with peatland-related climate adaptation grants for Scottish Water catchments possibly also included elsewhere in this analysis.

Table 22: Climate change adaptation investment need estimate for Scottish Water 2027– 2040 using the information from the draft SR27 business plan (including the technical annex on adaptation). All figures uplifted to 2026/27 prices (assuming 2% nominal growth per annum) from 2024/25 base prices provided by Scottish Water.

Period

Lower estimate (£m)

Upper estimate (£m)

2026/27

Not included in analysis

Not included in analysis

2027/28 – 2032/33

£357.9m

£471.3m

2033/34 – 2039/40

£709.4m

£1,994.6m

Total (£m)

£1,067.3m

£2,465.9m

Total (£m/yr)

£82.1m/yr

£189.7m/yr

Macroeconomic effects and wider impacts

Macro-economic stimulus

For macroeconomic modelling, we assumed there is £1bn adaptation investment between 2026 and 2040, approximately £67m/yr. The spending flows primarily to construction for infrastructure upgrades, with additional demand for engineering services, fabricated materials manufacturing and equipment suppliers. Note, this modelling was developed by Centre for Energy Policy at the University of Strathclyde, Scottish Water have not provided these figures.

Without cost recovery (a modelling device to isolate the spending effect): By 2040, construction gains £36m in output and 536 jobs, while architectural services add £1.8m and 27 jobs. Fabricated metals, manufacturing and wholesale/retail (vehicles) see modest supply-chain gains. The water/sewerage sector itself records a small direct gain of £1.1m and 5 jobs, and “all other services” benefits from household income spillovers, adding £10.5m and 140 jobs. The overall effect is a modest but broadly positive stimulus centred on construction and engineering supply chains.

With “industry pays” cost recovery (a stylised scenario): When Scottish Water recovers costs through higher water charges, the water/sewerage sector experiences the largest proportional loss across all scenarios examined. It shifts from a gain of £1.1m and 5 jobs to a loss of £37.5m and 156 jobs. Construction retains a reduced gain of £22m and 332 jobs because it remains central to delivering the infrastructure works, but most other sectors flip to negative impacts. “All other services” loses £24m and 345 jobs, while retail (excluding vehicles), financial services, education, manufacturing and electricity all record output and employment losses. In the CGE model, higher water charges raise business costs economy-wide, reducing competitiveness, while also acting as a regressive consumption tax on households since water is an essential service that low-income households cannot avoid.

Policy implications: An “industry pays” approach via water charges concentrates severe impacts on the water/sewerage sector itself and raises costs across all businesses and households, with regressive effects. Alternative or blended funding approaches merit serious consideration to avoid undermining both the sector and the broader economy, while recognising that these results exclude the substantial avoided benefits in terms of water security, public health and climate resilience.

Wider impacts

The economic case for adaptation investment in the water sector is strong. Evidence reviewed as part of the third UK Climate Change Risk Assessment (CCRA3) finds high benefit-to-cost ratios (BCRs) across a range of water sector measures (Watkiss, 2022). Water efficiency measures deliver the highest returns, with an average BCR of just over 10:1. So every £1 invested in water efficiency measures returns over £10 in net economic benefits. Upland peatland restoration shows similarly high but more variable returns, reflecting the site-specific nature of these investments. This is directly relevant to catchment management approaches such as the Loch Katrine Land Management Plan outlined in Case Study 6. Furthermore, flood preparedness and protection average a BCR of around 5:1, while making new infrastructure resilient averages 4:1 (Watkiss, 2022). Beyond these direct economic returns, adaptation investments frequently generate important co benefits. As well as reducing potential losses from climate change, they often deliver direct economic gains and social or environmental benefits. It is important to note that these BCRs are indicative. Actual returns are highly site and context specific, and uncertainty around the future scale of climate change means quantification of benefits remains challenging.

Current governance, funding and financing arrangements

Water provision in Scotland is in public ownership, Scottish Water is a public corporation providing potable water to 97% of households and businesses in Scotland and wastewater services to 93% (Scottish Government, 2026e). The Scottish Water business plan indicates that around 90% of all the cost of providing water and wastewater services is met by customer charges, with the remainder (£170m a year) met by Scottish Government (Scottish Water, 2025a).

Scottish Water’s regulated business supplies water and wastewater services to households and is also the wholesaler to the water retail market for businesses in Scotland. For the financial year 2024/25, around 73% of the total income was from households, with the remainder from wholesale businesses (Scottish Water, 2025b). See Table 23 for recent regulated business revenue.

Table 23: Scottish Water regulated business revenue. Decreases shown in brackets. Source: Scottish Water (2025b)

 

FY25 (£m)

FY24 (£m)

Increase/(decrease) (£m)

Household

£1,154m

£1,050m

£104m

Wholesale

£410m

£382m

£28m

Other

£15m

£17m

£(2)m

Total revenue

£1,579m

£1,449m

£130m

Beyond its core regulated business, Business Stream, Scottish Water’s retail subsidiary, competes as a licensed provider in both the Scottish and English markets, holding around a 20% share of the English market. It operates under a Governance Code agreed with the Water Industry Commission for Scotland and has its own independent board and management team. Non-regulated commercial activities, including renewable energy and innovative water technologies, are undertaken separately through Scottish Water Horizons (Scottish Water, 2025b).

The organisation has previously used Private Finance Initiative (PFI) models to finance infrastructure investment. However, these have run their course and over the next SR period, all but one of the PFI contracts will return to public ownership. The intention in the business plan is to keep all lending the same, and for additional investments in the network to be covered by user charges.

For the purposes of this study, we assume that the majority of the costs of adaptation are paid through Scottish Households and businesses, since the relative surplus from the other activities are relatively low (Business stream group had an £18m surplus before tax). The arrangements are set out Figure 12.

Going forward, Scottish Water expects the nominal borrowing from Scottish Government to stay the same, and the increased expenditure to be funded through households and businesses. The current business plan projects the proportion of expenditure to rise from 90% to 94% (Scottish Water, 2026c).

Figure 12: Financing, funding, and delivery arrangements for water and wastewater adaptation investment in Scotland.

Innovation that could boost private sector participation

In the water sector, options to boost private sector participation are more constrained given that Scottish Water operates as a publicly owned utility and the majority of investment is already funded through consumer bills.

There are also a spectrum of options relating to private financing (Table 24). The first is a basket of financing arrangements (Sustainability linked finance, Collective Investment Vehicles) that can be used but require long-term commitments to repayment or creation of revenue streams. However, in reality, their potential is likely to be limited since borrowing terms from Scottish Government are likely to be highly attractive, and future investment may also be linked to the plans for a new Scottish government bond. Full privatisation, while theoretically a financing option, is not considered a realistic or desirable pathway in the Scottish context.

There are also models which support private financing of specific assets, such as Public private partnerships (PPPs). However, while PPPs have previously been used to finance investment in Scottish Water infrastructure, the current direction of travel, bringing such infrastructure into public use, suggests limited appetite in practice.

Finally, there are alternatives which enhance contributions from businesses and consumers due to water-related benefits. In relation to billing, there are also alternative options for enhancing cost recovery through water tariffs. Many households in Scotland do not have water meters and are charged for installation, so such a programme could incentivise use and more accurately reflect usage. There is also the potential to enhance contributions from large businesses and landowners. For example, in Scotland, Diageo are already investing in upstream peatland restoration for flood management at their distillery. These may be able to be extended to cover akin to water funds which co-invest to improve efficiency and costs. It also noted that the hydrogen and digital sectors are also likely to increase water demand, and so may offer further potential. Developing clearer frameworks for how such investments are valued and attributed across multiple beneficiaries would help unlock this potential at greater scale.

Table 24: Examples of innovative models for private participation in water with cost recovery model. Source: authors, updated from Watkiss and England (2025).

Model

Examples

Cost recovery model

PFI/ PPP

Kigali Bulk Water Project (Rwanda) (Blended Finance Taskforce and Systemiq, n.d.)

User pays and government pays

Water Funds

Norfolk Water Fund TNC

User pays

Collective Investment Vehicles

Water Equity Global Access Fund IV (Heading For Change, n.d.)

User pays

Sustainability-linked finance

Pennon Group Green Finance Framework (UK) (Pennon, 2024)

User pays

Syndicated Loans

Enhancing Water and Sanitation Resilience with IDB Invest and partners (Brazil) (IDB Invest, 2025

User pays

Securitization, Guarantees and Credit Enhancement

Water Finance Facility (Kenya) Pooled Water Fund (Blended Finance Taskforce and Systemiq, n.d.)

User pays

Project aggregation

Climate Adaptation Notes

User pays

Micro finance

Water Credit Initiative (Water.org, n.d.)

User pays

Supply chain finance

Sanivation (Africa) (Sanivation, n.d.)

Government pays and private sector pays / new revenue model

Metering

CityTaps (Kenya) (The Global Innovation Fun, n.d.)

User pays through more accurate charging

Summary of findings

The evidence base on the cost of climate adaption in Scotland -and how this will change with time – is limited.

This study aimed to develop and test a preliminary approach that could be used to inform the potential indicative costs of climate adaptation across a range of sectors in Scotland.

We use a multi method approach to explore four dimensions: investment needs, the macroeconomic effects of such needs, public-private funding splits, and scope to mobilise private capital. Here, we present the key findings from the work which focussed on areas within five sectors: agriculture, communities (flooding), natural environment (woodland creation, peatland restoration and nature restoration), transport (trunk roads and motorways and railways), and water (public water and wastewater services).

Investigating climate change adaptation investment need

Investment needs were estimated using a pragmatic, multi-method approach tailored to the data availability and evidence maturity of each sector. Methods included drawing on existing sectoral analyses, applying climate-proofing uplifts to Scottish Government budget lines, scaling from UK-wide research, and using expert judgement to apportion investment with mixed objectives directly to adaptation.

We find that climate adaptation investment need for the five analysed sectors totals £7.8–£14.2 billion for 2026–2040, or £566–£1,027 million per year (Table 25).

Table 25: Summary of estimated climate change adaptation investment need for areas within the five sectors included in our study, for the period 2026 – 2040 (2026/27 prices). Where available, current budget (or estimates) are presented alongside estimated investment need, with a RAG rating indicating whether current spend meets the estimated need (green), falls within 20% below it (amber), or is more than 20% below it (red). An expert-elicited investment need estimate confidence rating is assigned to each sector/sub-sector estimate, alongside the primary source from which it was derived. *Note Scottish Water estimates are for 13 years from 2027– 2040.

Sector

Sub-sector / approach

Investment estimate (£m)

Investment estimate (£m/yr)

2026/27 budget (£m/yr)

Investment estimate confidence

Investment Estimate Source

Agriculture

 

£2,347m – £3,091m

£167.6m/yr – £220.8m/yr

£167.6m/yr – £220.8m/yr

Low

Scottish Government Budget

Communities

Capacity building

£102m

£7.3m

£6.9m

Medium

Scottish Government Budget

Property flood protection

£885m – £1,102m

£63.2m – £78.7m

£42m

Low

Scottish Government & DEFRA, HM Government

Property flood resilience

£10.5m –£52m

£0.8m- £3.7m

Unknown

Medium

JBA Risk Management 2025

Natural environment

Woodland creation

£115m

£8.2m

£2.3m

Low – Medium

Scottish Government Draft Climate Change Plan

Peatland restoration

£236m

£16.8m

£5.6m

Low – Medium

Scottish Government Draft Climate Change Plan

Natural restoration

£73m

£5.2m

£5.2m

Low – Medium

NatureScot

Transport

Rail[3]

£1,582m –£4,734m

£113m –£338.1m

≈ £87.8m

Medium

Network Rail Scotland

 

Trunk roads and motorways

£1,418m –£2,213m

£101.3m – £158.1m

£82.32m

Very low

Scottish Government Budget

Water*

Scottish Water[4]

£1,067m –£2,466m

£82.1m – £189.7m

Unknown

Medium

Scottish Water

Total

 

£7,835.5m £14,182.8m

£565.5m £1,026.6m

   

The macroeconomic effects of investing in climate adaptation

While a full assessment of the macroeconomic costs and benefits of adaptation was beyond the scope of this report, the study used a Computable General Equilibrium (CGE) model of the Scottish economy to explore the direct economic effects of adaptation spending across sectors and consider how different approaches to cost recovery affect economic activity, employment, and household incomes.

The modelling shows that adaptation spending can generate a positive economic stimulus during the investment period across all sectors studied. However, the way costs are recovered matters considerably, with effects varying by sector and recovery mechanism:

  • Agriculture: Adaptation spending would stimulate construction, manufacturing, and agricultural supply chains. However, recovering costs through higher food prices would disproportionately affect lower-income households and risk significant job losses given agriculture’s labour-intensive nature.
  • Communities: Flood adaptation would generate meaningful local gains in construction and professional services. If costs were recovered through income tax, broader consumer spending would be dampened, with retail and service sectors potentially flipping from gains to losses.
  • Natural environment: Land-based restoration would generate substantial rural employment gains, particularly in forestry and land-use sectors. Recovery through public spending cuts could produce widespread losses across service, education, and public administration sectors that outweigh the direct stimulus.
  • Transport (roads and rail): Adaptation spending would deliver broad-based construction and supply-chain gains. Income-tax recovery could erode much of this stimulus, particularly affecting consumer-facing sectors and export competitiveness.
  • Water: Recovering costs through higher water charges would concentrate severe impacts on the water sector itself and could act as a regressive tax on households and businesses for whom water is an unavoidable essential service.

These results should not be interpreted as a full cost-benefit assessment of adaptation. The modelling captures the demand-side effects of spending and cost recovery, but does not account for avoided climate damages, residual risks, or the broader triple dividend of adaptation.

Current funding and financing arrangements

For each of the areas within the five sectors included in our study, we calculated indicative estimates of the current and future contributions from the private sector towards adaptation investment. These are highly speculative and represent a first pass attempt at quantifying the current and potential contributions of the private sector to adaptation costs.

We find that currently investment is predominantly public across most sectors and sub-sectors. Private contributions range from negligible (peatland restoration) to around a third (agriculture). Water represents a notable exception where approximately 90% of costs are met through household and business customer charges. These are shown below, alongside the typical levels of financial returns for the activities (Table 26).

Table 26: Current and future maximum potential of private sector contributions to adaptation. Private sector contributions include households, businesses and financial institutions. Source: Updated from Watkiss and England, 2025.

Sector

Nature of Investment in baseline (Scotland)

Typical level of financial returns without innovation

Private sector contributions (funding and finance)

Public

Below-market

Commercial Returns

Current

Future (Potential)

Agriculture

Mixed

X

X

X

33%

35%

Communities – Flood protection.

Mixed (Public for protection, early warning and NBS, private for household measures)

X

  

7%

15%

Natural environment – Peatland

Public

X

  

0%

5 10%

Natural environment – Forestry

Mixed

X

X

x

Not quantified

Not quantified

Natural environment – Nature restoration

Public

X

  

0%

10%

Transport – Rail

Mixed

X

X

 

40%

45%

Transport – Road

Mixed

X

X

 

10%

15%

Water

Private

 

X

X

90%

100%

Innovations that could boost private sector participation

Opportunities to increase private sector contributions vary considerably by sector (Table 25). They include blended finance and parametric insurance in agriculture; green bonds, land value capture, and property-level flood resilience schemes for flooding; biodiversity and carbon credits alongside payment for ecosystem services in the natural environment; road user charging, tolls, and collective investment vehicles in transport; and water funds and sustainability-linked finance in the water sector, though options here are more constrained given Scottish Water’s public ownership model.

It was not possible to apply these estimates to the total figures for adaptation spend due to methodological differences in scope. However, the results suggest that for the five sectors explored, there is modest potential to boost private sector participation in adaptation funding and financing. While the numbers are modest in percentage terms, this nonetheless highlights real opportunity to increase private contributions, which will become increasingly important as costs are projected to rise significantly. Scottish Government and associated non-departmental public bodies should therefore consider this as part of the development of SNAP4.

Who pays for adaptation?

A clear structural tension running through all five sectors is the question of who pays for adaptation. Private finance can help meet upfront costs but rarely reduces the underlying funding burden. Costs are frequently transferred back to government or consumers, meaning private sector participation should be understood as complementary to, rather than a substitute for, public funding. This is reinforced by the nature of Scotland’s adaptation priorities. The majority of these fall within Type A and B categories (see Section 2.2 and Figure 3), implying that approximately three-quarters of investment needs must be publicly funded. Scaling private participation will therefore require active policy intervention, enabling conditions, and public co-financing to de-risk investment – it will not emerge through market forces alone.

How adaptation costs are ultimately recovered also has significant distributional consequences: income-tax funding spreads cost progressively but suppresses household consumption, while price-based approaches risk being regressive in essential sectors such as agriculture. Funding design is therefore as consequential as investment scale.

Across all sectors, the co-benefits of adaptation investment – avoided losses, economic stimulus, and socio-environmental gains – can substantially strengthen the economic rationale for action, particularly from a public sector perspective. However, these benefits are rarely fully monetised, meaning investment cases are systematically understated. Crucially, while co-benefits reinforce the public sector case for sustained funding, they do not necessarily translate into financial returns for private investors. This distinction helps explain the persistent gap between headline benefit-cost ratios and the limited appetite of private capital for adaptation investment.

Uncertainties and challenges

Our findings are a first attempt to quantify Scotland’s climate adaptation investment need across five sectors and should be interpreted accordingly. Significant uncertainties and methodological limitations attach to each dimension of the analysis.

Adaptation investment need estimates

Costing approaches vary considerably, from detailed sector/subsector assessments (rail, water), to climate-proofing uplifts on budget lines (roads), to apportionment of mixed-objective spend (natural environment), to value transfer approaches (communities – flood protection schemes). The breadth of approaches limits comparability across sectors and introduces varying degrees of uncertainty, as reflected in the confidence ratings in Table 23. The investment estimates presented in this report are indicative and order-of-magnitude in nature.

Key challenges and wider sources of uncertainty include:

Undefined risk tolerance thresholds

  • Without agreed adaptation objectives or acceptable risk levels for each sector, investment need cannot be scaled against a definitive end-goal. The figures we present reflect assumptions about continued or modestly scaled-up spending rather than what might be required to meet specific resilience outcomes.

Partial sectoral coverage

  • Many sectors such as energy, telecommunications, and health were not included in our analysis due to resource constraints. Furthermore, the sectors included in our analysis are only partially covered. For example, for transport, we included only rail infrastructure and motorway and trunk roads, we did not include local road networks, ferries, aviation, canals, and active travel. The communities sectoral analysis focused on flood risk management only. Adaptation investment needs for storm, drought, coastal erosion, heat risks and other factors that will affect communities were not considered.

Deep uncertainty in underlying drivers

  • Future climate trajectories, socio-economic and geopolitical change all remain uncertain.

Mixed objective apportionment

  • Apportionment fractions, (for example, the adaptation share attached to peatland restoration, woodland creation, and agricultural support) carry considerable uncertainty. They were derived through exploring the listed multiple objectives of each investment area and then using expert elicitation to attach an estimate apportionment, rather than empirical evidence.

Risk of double-counting

  • In some areas, the same expenditure may be captured under more than one sector. For example, peatland grants administered through Scottish Water catchment programmes may overlap with peatland restoration budgets counted within the natural environment sector.

Public-private investment split

The estimates of current and potential private sector contributions to adaptation funding are highly speculative and should be treated as illustrative rather than definitive. This relates to the following challenges:

Limited baseline data

  • Private sector adaptation expenditure is largely unrecorded across all five sectors. In agriculture, it is folded into support payment income streams; in transport, it is estimated from aggregate local government finance data; in water, it reflects consumer billing structures rather than genuine private risk-bearing. These limitations make cross-sector comparisons unreliable.

Definitional ambiguity between financing and funding

  • Instruments such as green bonds, sustainability-linked loans, or PPP arrangements can mobilise upfront private capital, but costs are typically repaid through public budgets, regulated consumer charges, or government guarantees. Private participation therefore tends to alter the timing and vehicle of finance without necessarily reducing the public funding burden.

Rapidly shifting governance landscape

  • The consolidation of rail services under Great British Rail, development of Scottish Government bond issuance mechanisms, and evolving frameworks for biodiversity and carbon credits could all materially alter funding arrangements over the period to 2040, making future contribution estimates uncertain.

Structural limits on private participation

  • Most of Scotland’s adaptation priorities fall within Type A or B categories (public goods or mixed-benefit activities with below-market returns). This means the majority of climate adaptation investment needs are likely to require public funding regardless of innovation in finance mechanisms.

Capturing wider co-benefits

The economic case for adaptation investment is substantially strengthened when the full triple dividend is considered. However, this report’s treatment of co-benefits is partial:

Limited co-benefits quantification in several sectors

  • Across all sectors, we have not explored the avoided losses of adaptation due to resource constraints.
  • Excluding economic stimulus, we have provided minimal evidence for the wider social, economic and environmental co-benefits of adaptation.
  • Where estimates are provided, notably for peatland restoration and woodland creation, these draw on literature values that carry their own uncertainty ranges and depend heavily on the pace and scale of successful delivery. More research is needed to capture the co-benefits of adaptation investment across Scotland.

Attribution challenges

  • Where adaptation investment delivers multiple outcomes, assigning economic value to the adaptation-specific component requires further subjective apportionment. The same hectare of restored peatland contributes to carbon sequestration, biodiversity gain, flood management, and water quality improvement simultaneously, making clean attribution inherently imprecise.

Conflation of societal and financial returns

  • High benefit-cost ratios in the literature typically reflect economic and environmental returns measured at a societal level, including non-market values that generate no cash flow. Private investors assess financial returns, incremental revenues and recoverable costs, which are considerably lower. Consequently, treating strong societal co-benefit ratios as evidence of private investment attractiveness risks overstating the potential for private finance mobilisation.

Recommended priorities

Recommended research priorities

While this project provides a first estimate of Scotland’s adaptation investment needs, it has identified significant gaps that require further data, research and analysis.

  • Adaptation objectives and risk tolerance
    • Develop specific, quantified adaptation targets and sector-specific risk tolerance thresholds aligned with climate scenarios and socioeconomic assumptions.
    • Use these objectives to enable meaningful gap analysis between current spending and investment need, and to support the development of SNAP4.
  • Asset-level vulnerability and investment pipelines
    • Develop comprehensive, spatially referenced vulnerability inventories across all five sectors included in this analysis.
    • Move from broad climate vulnerability assessments to spatially specific prioritisation of sites, assets, and interventions, building on existing work such as the Transport Scotland VLOG prioritisation tool and the Network Rail Scotland Adaptation Pathways Programme.
    • Integrate existing data sources, including Coastal Climate Adaptation Plans, SEPA flood risk assessments, and emerging sectoral tools, into the development of future adaptation investment plans.
  • Financial transparency and attribution
    • Improve the granularity in public budget reporting, including clearer disaggregation of adaptation spend from mitigation, and other objectives.
    • Undertake dedicated methodological work in agriculture to isolate the adaptation-specific component of spending and assess whether current budgets levels are appropriate for changing climate risks.
  • Triple dividend
    • Avoided losses: build the evidence base on avoided losses associated with adaptation investment across all sectors in Scotland, drawing on top-down modelling approaches and/or sector-specific data sources where available.
    • Economic stimulus: quantify the economic stimulus effects of adaptation investment, including employment, supply chain, and distributional impacts. CGE modelling offers a promising approach for capturing these macroeconomic and regional effects.
    • Social and environmental co-benefits: assess the wider social and environmental co-benefits of adaptation investment across sectors. This research could include a combination of reviewing existing literature and associated data, wider stakeholder engagement and/or practical field-based research for sectors such as natural environment and agriculture.
  • Distributional impacts
    • Conduct targeted research on the distributional consequences of different financing approaches – income-tax, price-based, and charge-based – and on compensating policy measures to support more equitable funding design.
  • Cross-sector collaboration
    • Develop mechanisms and spaces to share adaptation research and delivery across sectors, building on existing forums such as the Climate Ready Infrastructure Scotland (CRIS) Forum.
    • Further explore efficiency gains from catchment-scale management approaches, where investment simultaneously delivers water quality, biodiversity, flood management, and carbon sequestration benefits.
    • Map how adaptation priorities can be embedded within existing cross-cutting frameworks spanning civil contingencies, biodiversity governance, spatial planning, and infrastructure regulation, with Local Resilience Partnerships and the Scottish Wildfire Forum as existing entry points.

Prioritisation

A further challenge that cuts across all sectors is how to prioritise adaptation investment when resources are constrained. Standard cost-benefit frameworks tend to favour investment in areas of dense population, maximising the number of beneficiaries per pound spent, for example directing flood protection spending towards urban centres. However, several of the sectors and sub-sectors assessed in this report are most acutely exposed to climate risk in rural and remote areas. This includes transport routes, agricultural land, peatland, and water supplies serving dispersed communities. This creates a structural tension between economic efficiency and equity and raises important questions about who adaptation investment is designed to protect. Future work should explore how prioritisation frameworks can be developed that explicitly account for rural vulnerability, social equity, and Just Transition principles alongside conventional cost-benefit criteria ensuring that investment decisions do not systematically disadvantage the people and environment that face the greatest climate exposure.

Recommended strategic priorities for adaptation investment

A national strategy for adaptation investment must begin by recognising that different sectors are at different stages of the adaptation investment cycle. For example, in communities, the priority is shifting from capacity building towards delivery, mobilising resources for property flood resilience and scaling flood protection schemes at pace. In transport, the immediate need is moving from risk assessment and vulnerability mapping towards robust costing and prioritised investment programmes. In the natural environment, the strategic focus could be to further develop the private finance ecosystem, accelerating the maturity of biodiversity credit and voluntary carbon markets to draw in private capital at scale.

Across all sectors, there is value in ensuring that adaptation objectives are embedded within existing spending programmes. For example, infrastructure maintenance, rural development funding, housing retrofit, and land management schemes. This requires improved budget tagging, clearer apportionment guidance, and stronger policy levers to ensure that co-funded programmes deliver credible adaptation outcomes alongside their primary objectives.

Private finance mobilisation also requires a more coherent national approach. While opportunities exist across all five sectors, they are currently fragmented, small-scale, and unevenly distributed. A clearer national strategy should identify which mechanisms are most appropriate for each sector, what enabling conditions are required, and how public co-financing can be used most effectively to de-risk private investment. This could include drawing on international experience with blended finance, green bonds, and nature finance markets, while remaining realistic about the fundamental limits of private capital in funding what are, in most cases, public goods. Underpinning all of this is the need for an improved monitoring and evaluation framework for adaptation investment specifically. As adaptation investment programmes scale up, a consistent and transparent approach to tracking expenditure, outputs, and outcomes across sectors will be essential for accountability, learning, and iterative improvement, aligned with the SNAP3 requirements but going further to capture financial flows and asset-level progress.

A summary of the recommended strategic priorities for adaptation investment is provided in Box 2 below.

Box 2: Summary of strategic priorities for adaptation investment

  • The development of quantified adaptation targets and asset-level vulnerability inventories are the most important near-term research priorities, providing the foundations for robust investment need estimates and long-term adaptation pathways.
  • The improvement of financial attribution through improved budget tagging, clearer disaggregation of adaptation from co-objectives, and fuller quantification of the triple dividend, is important for making a credible and comprehensive economic case for sustained public investment.
  • Cross-sector collaboration, both in sharing research and delivery costs and in embedding adaptation within existing governance networks, offers significant efficiency gains that are currently underexploited.
  • Investment strategies must be sector-differentiated, reflecting where each sector sits in the adaptation cycle, and focused on building investment-ready pipelines capable of attracting both public and private finance at scale.
  • A shared monitoring and evaluation framework, specifically focused on adaptation investment, aligned with SNAP3, but capturing financial flows and asset-level outcomes, is a precondition for accountability and iterative improvement as the Scottish adaptation programme expands.

Acknowledgements

We would firstly like to thank the Scottish Government and ClimateXChange for their continued support with this project.

We would also like to thank the organisations and individuals that contributed information and/or case studies to this report, including: Scottish Water, Network Rail Scotland, Transport Scotland, FloodRe, University of Strathclyde, Hope in Place CIC and NatureScot.

Additionally, we would like to thank the individuals that contributed to preparing this report and analysis, including David Sturgess and Adam Hughes-Buchanan (both University of Strathclyde) and Andrew Moxey and Paul Watkiss (both Paul Watkiss Associates).

Finally, we would like to acknowledge the support from ATTENUATE project for their contributions on the conceptual framing, costing and financing (funded by UK Research & Innovation; grant number UKRI282). ATTENUATE is a collaborative project focused on unlocking private sector funding for climate adaptation, building the case for greater public sector investment, and addressing governance barriers to investment and is supported by the UKRI-Defra ‘Maximising UK Adaptation to Climate Change’ programme. For more information, see www.lse.ac.uk/granthaminstitute/projects/attenuate.

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Scottish Water (2026c) Final Business Plan 2027–2033: Investing in Scotland’s Future. Available at: https://www.scottishwater.co.uk/-/media/scottishwater/document-hub/key-publications/delivery-and-business-plans/business-plan-sr27/260226scottishwaterfinalbusinessplan2027to033.pdf (Accessed: 23/03/2026).

Scottish Water (2026d) Loch Katrine Woodland Creation and Peatland Restoration. Available at: https://www.scottishwater.co.uk/In-Your-Area/Investments-in-Your-Area/070125-Loch-Katrine-woodland-creation (Accessed 31/03/2026).

Shanahan, D., Bush, R., Gaston, K. et al. (2016) Health Benefits from Nature Experiences Depend on Dose. Sci Rep 6, 28551. Available at: https://doi.org/10.1038/srep28551.

Sniffer (2021). Evidence for the third UK Climate Change Risk Assessment (CCRA3) – Summary for Scotland. Available at: CCRA-Evidence-Report-Scotland-Summary-Final-1.pdf

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Taylor, R., England, K. and Eggert, A. L. (2025) Developing an Adaptation Investment Plan. Guidance for facilitators. Deliverable 3.1 of the CLIMATEFIT project.

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Appendices

 

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Decision tree for assessing private sector potential in adaptation. Image source: ADB, 2026.

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Detailed methods: Network Rail Scotland

Network Rail Scotland calculated future adaptation investment needs using UKCP18 climate projections under two scenarios: RCP 6.0 (medium emissions, ~2°C warming by c.2055) and RCP 8.5 (high emissions, ~2°C by c.2045, ~4°C by c.2080). The analysis assumed maintaining current service levels and asset condition at Control Period 7 (CP7) * exit levels, aligned with CCC guidance from October 2025. However, it is important to note that this represents just one potential ‘investment future’. Ultimately there are multiple other plausible futures (including changes to service provision targets, transport modal shift, prioritisation of investment in rail, changes to safety tolerance levels, or other external factors) that would all likely have different adaptation investment needs associated with them.

Currently, Network Rail Scotland uses two complementary approaches to track weather and climate resilience investment for CP7. The top-down approach assesses standardised intervention types and applies nationally agreed percentages to reflect their contribution to resilience (e.g., 100% of cost attributed to drainage renewals would count towards ‘resilience’, recognising that this type of intervention is fundamentally about the management of water on their infrastructure. Whereas only 50% of the cost associated with overhead line renewals would contribute to resilience, recognising that the driver of renewal is likely condition of asset, but that the renewed asset is inherently more resilient to hot weather). A bottom-up approach uses expert-led qualitative engineering assessment to identify specific schemes contributing to network resilience. Together, the two approaches established a CP7 baseline of £400m total in asset interventions that deliver a weather and/or climate resilience benefit (2024/25–2028/29).

Network Rail Scotland’s future potential adaptation investment calculations are structured across multiple cost categories: operations and support (operational response to extreme weather, seasonal treatment trains, emergency speed restrictions); maintenance (preventative and reactive maintenance, inspections, monitoring); network resilience renewals catch-up (addressing current renewal backlog); network resilience renewals additional (business-as-usual renewals responding to enhanced asset degradation from climate change); and location-specific renewals (targeted interventions at sites with specific weather and climate challenges). Furthermore, estimates for major capital interventions – large-scale transformational schemes where continued operations would otherwise be impossible as a result of changing climate – are also calculated, though with a large uncertainty range.

For each category, subject matter experts developed cost ranges based on considerations such as historical data, operational experience, climate projections, asset models maintained by Network Rail Technical Authority, and anticipated increases in weather event frequency and severity. Estimates were produced for both operations, support, maintenance, and renewals (OSMR), as well as OSMR combined with the additional inclusion of major capital interventions. The estimates produced represent additional investment required in each of CP8 (2029/30–2033/34) and CP9 (2034/35–2038/39) above CP7 baseline levels.

For our research period 2026/27–2039/40, we assumed the following: CP7 remaining spend from 2026/27 onwards; full CP8 investment estimates; full CP9 investment estimates; and, a pro-rated single year for 2039/40 (one-fifth of CP9 costs). All figures from Network Rail Scotland were quoted in 2023/24 prices and uplifted to 2026/27 prices. These figures assume maintaining a broadly similar service level and asset condition to that of CP7 and should be interpreted as one plausible investment future only.

Network Rail Scotland are undertaking active work to refine and improve these cost estimates. As part of their Adaptation Pathways Programme, they are working at pace to understand what potentially vulnerable locations may require future adaptation investment – the outputs of this work will allow them to narrow the indicative investment cost ranges included in this study. 

* A Control Period is Network Rail’s fixed five‑year funding and planning cycle that sets budgets and outputs for the railway (e.g., CP7: 1 Apr 2024 – 31 Mar 2029).

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Detailed methods: Scottish Water

Scottish Water uses a wide range of climate and operational models to understand how future weather will affect its services in the Strategic Review (SR) SR27. This includes UKCP18 climate projections, water-resource models to assess drought impacts, catchment-deterioration models to understand future water-quality risks, rainfall-uplift and flood-modelling tools developed with UKWIR, Newcastle University and the Met Office, and mapping of flood and coastal-erosion exposure using SEPA flood maps and Dynamic Coast. Together, these tools allow Scottish Water to test resilience under both +2°C and +4°C global-warming scenarios.

Using these models, Scottish Water assessed 126 climate-related risks. Each risk was evaluated for both likelihood and impact, covering potential effects on customers, compliance, finances, health and the environment. This structured assessment helps the organisation prioritise where adaptation is most urgent and where investment will deliver the greatest resilience benefits.

Scottish Water’s adaptation actions fall into three categories: operational resilience, asset resilience, and service transformation. Most adaptation is embedded within core investment programmes, for example upgrading water-supply systems, wastewater networks and treatment works to cope with future rainfall and drought conditions. Some actions are key-driver investments where climate change is the primary reason for action, while others are retained risks where climate impacts are recognised but investment is not yet justified. A smaller set of actions are transformational, such as blue-green infrastructure, catchment-scale nature-based solutions and customer behaviour-change programmes.

For long-term planning, Scottish Water planning experts and technical consultants used early qualitative risk assessments to develop an indicative £2–5bn investment estimate for climate adaptation up to 2050. For the research period 2027/28–2039/40, SR27 spend (2027/28–2032/33) is taken directly from Scottish Water’s draft SR27 business plan. For the period 2033/34 onwards, the remaining budget — calculated by deducting the SR27 allocation from the lower and upper bounds of the £2–5bn long-term estimate — is distributed equally across annual periods from 2033/34 to 2049/50, with only the portion falling within the research window (2033/34–2039/40) included in the totals presented here. All figures provided by Scottish Water in 2024/25 prices have been uplifted to 2026/27 prices assuming 2% nominal growth per annum.

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Detailed methods and analysis: Modelling the economy-wide impacts of climate change adaptation spending.

Methodology:

For this work we have used the AMOSENVI, computable general equilibrium (CGE) model of the Scottish economy. The model captures all the sectors of the Scottish economy, aggregated into 30 broader sectors to allow us to trace the interactions between sectors and identify the drivers behind the results we observe. This is one of the key strengths of CGE modelling; it allows us to capture how the spending of different sectors to adapt to climate change affect prices and through that the wider Scottish economy.

Our model uses the 2019 edition of the Scottish Input-Output (IO) tables, published annually by the Scottish Government. This version is the latest currently available, where the Scottish economy is not affected by the Covid-19 pandemic or the Russian invasion of Ukraine and the impact it had on international energy prices. This way, 2019 data allow us to study how climate change adaptation spending might impact a version of the Scottish economy unaffected by major international incidents.

In our model, we assume that Scottish workers have the power to bargain for their wages, which is inversely related to the unemployment rate in the Scottish economy. This way, when unemployment is low, workers have the ability to bargain for higher wages and vice versa. However, we also assume that Scotland is an open economy, meaning that workers can freely migrate in and out of Scotland. When Scottish unemployment is lower and real wages are higher compared to the rest of UK (RUK) and the rest of the world (ROW), workers migrate to Scotland, increasing the labour supply. The opposite is true when Scotland experiences high unemployment and low real wages.

Wages are mostly important for the consumption of households. In this version of AMOSENVI, households are disaggregated to quintiles based on their gross income, with HG1 including 20% of the lowest income households and HG5 including 20% of the highest income households. Not all households are affected in the same way from changes in the economy, such as the climate adaptation spending, so this disaggregation allows us to capture the distributional impacts across the different household income groups. Households consume based on their disposable income, which is affected, apart from the wage and employment levels, from taxation such as income tax.

Income tax is a key, but not the only, source of revenue for the Scottish Government, which our model also includes. The income tax rate is normally fixed, but we also include scenarios where the income tax rate is adjusted to cover the cost of climate change adaptations in different sectors. Apart from raising revenue, the government also purchases goods and services from Scotland, RUK and abroad. Typically, government spending is fixed in real terms. However, for this work we use the government spending as a mechanism to model the adaptation spending.

Modelling adaptation spending

For the purpose of this work, we assume that climate change adaptation is a form of capital spending that does not create additional production capital for production sectors. Instead, it allows them to maintain the same production capacity, which would be at risk in the face of climate change.

This assumption has two main implications:

  • The breakdown of each sector’s spending matches where they would spend their investments to create new capital or to maintain their existing capital.
  • Climate change adaptation is a one-off spending. Once it is concluded and the associated cost is recovered, there is not further impact to the Scottish economy, which is gradually returning to its pre-spending level.

The latter assumption can be altered to assume the need for recurring spendings to address the challenges of climate change on an ongoing basis. However, to model the ongoing spending, more information is necessary to estimate how the adaptation cost might change over time and as climate change intensifies. Hence, we have opted to model a one-off spending based on the information currently available to us.

In terms of the spending, we model it as additional government purchases by the Scottish Government. Subsequently, we model the cost recovery in two main ways, depending on the sector that is adapting to climate change. We model a ‘government pays’ approach, where government covers the adaptation cost and raises the income tax to raise the necessary funds. Alternatively, we model an ‘industry pays’ approach, where the government still makes the necessary purchases of goods and services and then increases the indirect business tax rate of the adapting sectors so that they cover the adaptation cost.

Table D1: Climate adaptation spending in different parts of the Scottish economy (in 2025 prices).

Sector

Sub-sector

Investment estimate 2026-2040 (£m)

Investment estimate 2026-2040 (£m/yr)

Agriculture

£2,269m

£151m/yr

Communities

Regional hubs​

£98m​

£6.6m/yr​

Property flood resilience​

£867m

£58m/yr

Flood protection schemes​

£578m​

£39m/yr​

Natural environment c

Woodland creation​

£1,769m

£118m/yr

Peatland restoration​

£909m

£61m

Nature restoration​

£358m

£24m/yr

Transport

Rail​

£1,538m

£103m/yr

Trunk roads and motorways​

£8,170m

£545m/yr

Water

Scottish Water​

£1,009m

£67m/yr

We model the adaptation cost for 5 production sectors, as well as some more generic adaptation spending that is not linked to any specific production sector. The sectors, as well as the cost and who pays for it are reflected on Table D1. Please note that our original information included estimates in different price years. To improve the comparability between the different results, we adjust all the values in Table 1 and the values reported in our results to 2025 prices, using the UK GDP deflators.

Adaptation of Rail transportation

Constantly exposed to the elements, transportation services and their necessary equipment are facing the implications of climate change more than other sectors in the Scottish economy. Updates in different parts of the network and the trains themselves will be necessary to ensure that disruptions and safety concerns are kept to a minimum. Figure D1 presents how the adaptation spending of ‘Rail transportation’ is distributed across different Scottish sectors.

A pie chart showing the breakdown of 'Rail transportation' adaptation spending across industry sectors. The largest segment is Wholesale and Retail (vehicles) at 45.89%, followed by Construction at 17.51%, Public administration and defence at 14.77%, and All other services at 9.46%. Smaller segments include All other manufacturing at 3.70%, Wholesale excluding vehicles at 2.66%, Education at 2.30%, Architectural services etc at 1.91%, Fabricated metal at 1.29%, Agriculture at 0.29%, Coal, lignite and Mining Support at 0.21%, and Coke, petroleum and petrochemicals at 0.02%. Figure D1. Breakdown of ‘Rail transportation’ adaptation spending

As we can see in Figure D1, ‘Rail transportation’ needs to spend a significant amount on construction services, to maintain and reinforce the rail network to cope with the effects of climate change. The most significant share of the spending though is directed to ‘Wholesale & Retail – vehicles’. This sector is most focused on the sales, maintenance and repair of vehicles, including trains and carriages, which is obviously crucially important for the expansion of the and maintenance of the trains. It is reasonable to expect then that similarly large spendings will be required in adapting to climate change. Besides those two sectors, some spending on engineering and relevant specialised services is expected, currently included in ‘All other services’.

The impacts in the absence of cost recovery

Climate adaptation spending introduces a demand shock to the Scottish economy that leads to gross domestic product (GDP) and employment gains. The gains are originally observed in the sectors delivering the rail adaptation activity. Shortly after, the additional employment required to deliver the adaptation and the wage gains that this employment requirements drive, trigger an increase in household consumption that fuels further GDP and employment gains. See Figure D2.

Figure D2. Scottish GDP, employment and CPI impacts from climate change adaptation spending in Rail Transportation

The GDP gains peak at the end of the spending period in 2040[5], as are the employment gains. By 2040, the Scottish GDP grows by 0.54% (£99m in 2025 prices) along with the creation of 1,490 full-time equivalent (FTE) jobs (0.063% employment gains). Interestingly, the economy-wide prices, reflected by the consumer price index (CPI) are peaking in the first year of the adaptation spending, when we observe the Scottish CPI increasing by 0.026%. This price increase is fuelled by the demand for workers, which pushes the cost of workers upwards. Subsequently, more workers migrate to Scotland to benefit from the increased employment opportunities and the higher wages. The expansion of the labour force eases the pressures on wages, so we observe smaller price increases despite the increased employment and household consumption.

The gross value added (GVA) and employment impacts are not distributed uniformly across all the sectors. As shown in Figure D3 for 2040, most GVA is generated in sectors heavily involved in delivering the climate adaptation of ‘Rail transportation’. Further gains are achieved in sectors where households spend their additional income, such as ‘All other services’. In all other sectors the gains are negligible.

Figure D3. 2040 gross value-added impacts per sector due to climate adaptation spending in Rail Transportation

We observe a similar picture in relation to employment (see Figure D4). Some small differences are present, depending on the labour intensity of each sector, but broadly the picture resembles what we see for GVA. An important thing to point out is that in the absence of cost recovery considerations, all Scottish sectors benefit, or at least are unaffected, by the climate adaptation spending for ‘Rail transportation’.

However, all these impacts are temporary. Figure D2 indicates that shortly after the end of the climate adaptation spending, the gains are eroded with the economy returning to the original levels[6]. Approximately 15 years after the end of the spending period, almost none of the benefits from the adaptation spending can be observed.

Figure D4. 2040 employment impacts per sector due to climate adaptation spending in Rail Transportation

The effect of cost recovery via the income tax

The results change both qualitatively and quantitatively if we also consider how the costs will be recovered. For ‘Rail transportation’, because of the nature of the infrastructure that will need to be adjusted, we assume that it will be the government paying for the adaptation and therefore recovering the cost. We have considered the adjustment of the income tax rate as a mechanism to raise the funds required to deliver climate change adaptation in ‘Rail transportation’.

Figure D2 demonstrates that when the adaptation costs are recovered via increases in the income tax, the GDP and employment gains are reversed and the Scottish economy is, temporarily, negatively affected. Income tax increases affect the economy in two main ways. First, a higher income tax restricts the disposable income of households. The lowest income quintile, HG1, is largely unaffected by the income tax increase, while the highest income households of HG5 are observing the highest, in both percentage and absolute terms, real income losses. This reduction in households’ real disposable income, erodes any potential gains emerging from increased household consumption.

Second, the income tax increase is to some extent internalised by the employers as part of the wage bargaining process. Therefore, even though the real take home wage of employees decreases due to increased unemployment, the labour cost to businesses increases, pushing their production cost upwards. This is reflected in the higher, and longer-lasting, CPI impacts when the costs are recovered via the income tax. The higher economy-wide prices further erode household consumption, while also reducing the competitiveness, and by extension the exports, of Scottish sectors, further contributing to the negative economy-wide outcomes.

Of course, similarly to the ‘no recovery’ case, the impacts are not distributed evenly across all the sectors (see Figure D3 and Figure D4). The heavy involvement of ‘Wholesale/Retail – vehicles’, ‘Construction’ and ‘Public admin/defence’ in delivering the adaptation spending, somewhat insulates them against the effects of the income tax increases and allows them to still achieve, smaller scale, GVA and employment gains. Other sectors like ‘All other services’ experience a radical reversal of their GVA and employment impacts, reflecting the combined effects of higher labour costs and lower household consumption.

Adaptation of the Agriculture sector

Undoubtedly, one of the sectors that are most likely to be affected by climate change, and therefore requiring significant spending to adapt to the potential changes, is agriculture. However, it is an umbrella sector encompassing a wide range of products, farming techniques and technologies. Hence, the range sectors involved in adapting agriculture production to the challenges of climate change is expected to be broad. Figure D5 demonstrates this wide range of sectors.

Figure D5. Breakdown of ‘Agriculture’ adaptation spending

The breakdown for ‘Agriculture’ adaptation spending is quite different to the spending for ‘Rail transportation’. Here, ‘Construction’ is expected to play a more significant role, which is to be expected as new infrastructure will be required to ensure the ongoing agricultural production. Other large spendings are expected in part of the ‘Agriculture’ sector itself, as well as on ‘All other manufacturing’ and ‘Wholesale/Retail – vehicles’.

Agriculture adaptation without cost recovery

In may ways, the climate adaptation spending for ‘Agriculture’ leads, qualitatively, to the same impacts as in the ‘Rail transportation’ case, in the absence of cost recovery. Quantitatively though the impacts are different, driven in part by the large spending required for the adaptation of ‘Agriculture’ and the different composition of sectors involved. The qualitative similarities of the two adaptation cases can be visually confirmed by comparing Figure D6 to Figure D2.

Figure D6. Scottish GDP, employment and CPI impacts from climate change adaptation spending in Agriculture

One notable difference between the two cases is that employment more closely tracks the GDP impacts, both time-wise and as a percentage change. The smaller gap between the employment and GDP impacts in the ‘Agriculture’ case suggests that the sectors involved in the adaptation spending of this sector are more capital- and less labour-intensive compared to the sectors involved in the adaptation of ‘Rail transportation’.

Furthermore, the distribution of the GVA and employment gains across the different sectors is also different to the ‘Rail transportation’ case (see Figure D7 and Figure D8), as is greatly influenced by the breakdown of the sectors that deliver the ‘Agriculture’ adaptation (shown in Figure D5). Despite the differences in the distribution, some qualitative characteristics remain the same, in that a small number of sectors contribute around 80% of the total GDP gains and that again 80% of the employment gains are concentrated in the same small number of sectors.

Figure D7. 2040 gross value-added impacts per sector due to climate adaptation spending in Agriculture

Figure D8. 2040 employment impacts per sector due to climate adaptation spending in Agriculture

Accounting for ‘who pays’ for the ‘Agriculture’ adaptation

In the ‘Rail transportation’ case we assumed that the sector itself, and the infrastructure developments that may be required, meant that the government was likely to pay the adaptation cost and recover it via fiscal instruments, such as changes in the income tax rate.

‘Agriculture’ though is different, with many small producers contributing to the sector rather than consisting of a handful of firms. This being the case, it is very likely that the farmers themselves will have to cover the adaptation cost and subsequently pass it to the consumers via the price of their farming goods. This ‘industry pays’ approach leads to different impacts across the wider economy. A key difference is that an ‘industry pays’ approach is regressive in nature. Indeed, looking at the CPI for each household group we can see that, by 2040, the lowest income households in HG1 experience broader price increases of 0.088%, while the highest income households in HG5 experience price increases of 0.073%. The difference is driven in part by the spending in agricultural produce, which is a larger share of the total consumption of low-income households; hence, any price increases in agriculture products leads to greater CPI pressures to this specific income quintile.

Generally, agriculture products are an important component of the consumption of all households and a price increase to recover the adaptation spending can trigger the significant economy-wide CPI pressures observed in Figure D6. These economy-wide price increases erode the purchasing power of all households and lead to reduced household consumption, reduced GDP and employment. Coupled with the export losses that increased prices trigger, lead to the negative picture presented in dashes in Figure D6.

A further important implication of the ‘industry pays’ approach here is that it affects one of the most labour-intensive sectors in the Scottish economy, employing 8.5 FTE workers per £m of output. With concentrated impacts on the sector, we see in Figure D8 that significant employment losses are triggered, contributing to the larger net employment losses across the Scottish economy.

In an economy where movement of labour in and out of the economy is challenging, the unemployment increase associated with job losses would trigger labour cost reduction processes that would help cushion the negative impacts to the economy. However, we assume that workers can move freely in and out of Scotland. Increased unemployment and reductions in the real wage, fuelled by the CPI increase, incentivise workers to leave Scotland, ultimately easing the changes in the unemployment rate. But this prevents the cushioning labour cost reductions from materialising, leading to reduced employment, reduced purchasing power per worker, but also higher labour costs for the businesses. The combination of all these effects leads to the significant economy-wide losses, throughout the cost recovery period.

 

  1.  

Agriculture: Climate adaptation exploratory analysis

This case study presents an exploratory analysis of the costs associated with climate adaptation actions for Scottish agriculture. It draws on thirty-three actions identified as suitable for the Scottish context in a report published for the Scottish Government’s Rural and Environment Science and Analytical Services (RESAS). Available evidence, targets, and contextual information – see supplementary data – were used to estimate the potential deployment of each action across Scotland. Costs were scaled using land use archetypes from the Climate Change Committee’s Rural Land Use Types report (Thomson et al., 2025). The resulting estimates should be regarded as first-pass figures requiring further expert elicitation to be refined. Where the scope of the analysis permitted, an exploratory cost-benefit analysis was undertaken for selected actions, examining potential impacts on yields, soil erosion, disease risk, productivity, and biodiversity.

Action Identification

The thirty-three adaptation actions drawn from the RESAS report span arable, pastoral, and universal categories, and carry ratings for both impact and complexity across three levels: low, medium, and high. Prior to costing, two actions were excluded on the grounds that they are implicitly captured within the overarching action ‘diversifying Ccrop rotations’: namely, ‘crop introductions and diversification’ and ‘use of more resistant crop varieties’.

Cost information

Cost information was sourced from academic and grey literature, with a confidence rating (low, medium, or high) assigned to each source. Of the thirty-three actions, cost estimates were successfully obtained for twenty-one. The remaining twelve could not be costed due to an absence of relevant literature with associated expenditure data. In addition, two further actions identified during the literature review process — biocontrol and organic conversion — were incorporated into the analysis on the basis that sufficient cost data were available. Both were considered of material relevance to Scottish agriculture. All costs were adjusted to 2026/27 prices and converted to pound sterling where necessary. Further detail regarding the specific assumptions underpinning individual cost estimates is provided in the supplementary data.

Scaling costs

To scale unit adaptation costs (typically expressed in £/ha) to the applicable Scottish agricultural land area, the Climate Change Committee’s Rural Land Use Types report was employed (Thomson et al., 2025). This report disaggregates Scotland’s total agricultural land stock into ten archetypes, of which the six largest were selected for this analysis, together accounting for 97.9% of Scottish agricultural land: highly degraded lowland organic soils (117,300 ha); degraded upland grazing land and forest on organic soils (619,900 ha); hilly farmland on improved and semi-natural grassland on non-organic soils (106,400 ha); open pasture on the upland fringe (814,300 ha); acid grasslands on hilly uplands (767,400 ha); and arable on sandy soils (511,900 ha).

The report further disaggregates each archetype by land cover, as illustrated in Figure E1, across categories including arable and horticulture, acidic grassland, and coniferous woodland. These breakdowns were used to delineate the proportion of each archetype applicable to the scaling of adaptation action categories: arable, livestock, grassland, and universal.

Where data on the current extent of action deployment were available, this was deducted from the target area prior to scaling, ensuring that cost estimates reflect remaining deployment requirements rather than total potential coverage. The general scaling methodology proceeded as follows: the per-hectare cost of each action was multiplied by the applicable target area and, where actions were costed on an annual basis, further multiplied by the fourteen-year adaptation period to produce a total cost estimate covering 2026/27 to 2039/40. In certain cases, e.g., the application of green pesticides, the number of applications per year was incorporated into the calculation before extrapolation across the full period. Full details of the assumptions and methodologies applied to individual actions are provided in the supplementary data.

Figure E1: Land Cover Map categories in 2021 by archetype. The percentage of the archetype covered by organic soil is given above each bar – fig.4 from Thomson et al. (2025) – used to assist adaptation action cost scaling.

Complete scaled exploratory cost estimates for the fourteen-year period were produced for nineteen adaptation actions in total, presented in full in Supplementary Table X with associated confidence ratings and contextual information. A subset of six illustrative actions is excerpted in Table E1.

Table E1: Six example adaptation actions with associated scaled costs.

RESAS action

RESAS category

Action cost estimate

Target area (ha)

Scaled cost (2026-40)

Diversified crop rotations – Impact: HIGH, complexity: LOW

Arable

£254/ha implementation and £495/ha/yr running [7]£254/ha implementation and £495/ha/yr running [1]

482035

£3,462,939,440

Alterative tillage techniques – Impact: HIGH, complexity: MEDIUM

Arable

£814/ha implementation and £42/ha/yr running 3

431272

£604,643,344

Adjusting or reducing stocking rates – Impact: HIGH, complexity: LOW

Livestock

£69.46/ha/yr [8]£69.46/ha/yr [2]

1755415

£1,707,035,763

Virtual fencing technology – Impact: MEDIUM, Complexity: MEDIUM

Livestock

£3791 set up + £57 per collar [9]£3791 set up + £57 per collar [3]

N/A

£531,990,570

Enhanced production on marginal land – Impact: LOW, complexity: HIGH

Grassland

Government budget for LFA is £65.5M for 2026/27 [10]

LFA is 86%[11] of total agricultural land (5.16M ha[12]) = 4.44M ha

Government budget for LFA is £65.5M for 2026/27 [4]

LFA is 86%[5] of total agricultural land (5.16M ha[6]) = 4.44M ha

Cost per hectare of LFA: £14.76/ha/yr

1419739.6

£293,374,991

Agrivoltaics – Impacts: MEDIUM, Complexity: HIGH

Universal

Capital expenditure £7950/ha AND operational expenditure: £4300.96/ha/yr

3237

£220,645,055

[1] https://ieep.eu/wp-content/uploads/2024/07/The-costs-and-benefits-of-transitioning-to-sustainable-agriculture-IEEP-2024.pdf

[2] https://www.gov.wales/sites/default/files/publications/2023-12/atisn19234doc1.pdf

[3] https://doi.org/10.33988/auvfd.837485

[4] https://www.gov.scot/binaries/content/documents/govscot/publications/corporate-report/2026/01/scottish-budget-2026-2027/documents/scottish-budget-2026-2027/scottish-budget-2026-2027/govscot%3Adocument/scottish-budget-2026-2027.pdf

[5]https://www.gov.scot/publications/scottish-rural-development-programme-2014-2020-ex-post-evaluation-annex-scheme-summary-report/pages/11

[6] https://www.gov.scot/publications/results-from-the-scottish-agricultural-census-june-2024/pages/most-of-scotlands-area-is-used-for-agriculture/

Exploratory cost-benefit analysis

Exploratory cost-benefit analysis (CBA) was undertaken for the adaptation action ‘diversified crop rotations’, examining potential monetary benefits resulting from this action. These included increased crop yields of between 10% and 25%; reduced losses from soil erosion of up to 90%; and fertililser usage savings of 30%.  

The result, shown in Table E2,outlines the potential monetised benefits between 2026 and 2040 of £1.1bn- £856M. This means that 24.7% to 31.4% of the total could be returned by increased crop yields, reduced losses and reduced fertiliser cost.

This is not an exhaustive CBA but indicative of the potential of these actions relative to a do-nothing scenario.

Table E2: Exploratory cost benefit analysis for diversified crop rotation

Cost benefit description​

+25% yield value

+10% yield value

Crop yield increase of 10-25% [13]

1.53B total crop output (2024) [14]

Crop yield increase of 10-25% [1]

1.53B total crop output (2024) [2]

 

 

£382,500,000.00​

£153,000,000.00​

Reduced losses of up to 90% in yield value from soil erosion

(calculated using +10% and +25% yield value)​)

Approx 19.2% of Scottish arable land at risk of soil erosion[15]

 

Approx 19.2% of Scottish arable land at risk of soil erosion[3]

Assume therefore, that 19.2% of crop output value (1.53B) at risk consequently

Soil erosion causes losses in crop productivity of 0.43% [16]Soil erosion causes losses in crop productivity of 0.43% [4]

£19,894,896.00​

£17,507,508.48​

30% fertilizer cost saving relative to cost of fertilizers currently widely in use.

Total UK spend on fertilizer 2023 = £1.36 Billion

Scotland share of UK agricultural land = ~12%

 

£685,440,000.00

£685,440,000.00

Total monetised benefits

£1,087,834,896.00

£855,947,508.48

Diversified crop rotations scaled cost (base)

£3,462,939,440.00

NET COST of diversified crop rotations after accounting for savings in fertilizer usage, reduced losses from soil erosion and increased yield value, all as a direct result of this action​ (= Base cost – Total monetised benefits)

£2,375,104,544.00

£2,606,991,931.52

Several important limitations should be noted when interpreting these results:

  • Cost estimates assume that each action is applied across all land eligible for that measure, which is likely to overestimate real-world uptake; results should therefore be interpreted as upper-bound estimates.
  • In practice, interventions would be carefully selected and targeted, and not all actions would necessarily be deployed across the full eligible area.
  • Limited data on the current extent of adaptation adoption makes it difficult to accurately determine the remaining deployment gap for individual actions.
  • Cost data were unavailable for several actions that are nonetheless considered significant for Scottish agricultural adaptation; these would benefit from dedicated expert costing exercises.
  • The analysis does not account for the potential impact of increasing climate risk on the cost or effectiveness of adaptation actions over the period.

Scaling was not feasible for certain actions due to data limitations. Costing shelterbelts, for example, would require data on the total perimeter of agricultural land. Costing enhanced livestock housing design would require detailed information on existing infrastructure and the degree of upgrade required. In the latter case, the only cost data identified were sourced from European literature, providing a range of €5,000 to €100,000 per unit — figures that may not be directly transferable to the Scottish context.

  1.  

Wider policy and economic context for agriculture:

Policy context

The Agricultural and Rural Communities (Scotland) Act 2024 set out the legal framework for transforming Scotland’s farm support system, replacing former Common Agricultural Policy (CAP) schemes with a four‑tier framework by 2027. The reforms aim to shift agricultural support toward delivering environmental and climate outcomes while still underpinning food production and rural livelihoods. Central to this shift is the Whole Farm Plan, which requires farmers to baseline their environmental performance and adopt practices that reduce emissions, restore nature, and improve efficiency. Implementation will be gradual: initial changes begin in 2025, consolidation of payments and “Enhanced Greening” follow in 2026, and by 2027-28 the full framework, alongside new agri‑environment, forestry, and capital support measures, will be in place.

Overall, the new system moves from unconditional payments to support linked to specific outcomes across Tiers 1–4, balancing farm productivity with climate adaptation, mitigation, and biodiversity goals. Tier 1 provides core direct income support, evolving from the Basic Payment Scheme but tied to meeting baseline environmental and regulatory standards. Tier 2 rewards enhanced environmental delivery, including greening measures and likely future integration of the Less Favourable Area Support Scheme (LFASS). Tier 3 offers elective, targeted support for specific environmental or land‑management actions, replacing schemes like AECS and FGS. Tier 4 delivers complementary capital grants, skills development, and advisory services to help businesses adopt new practices. While the approach builds on what many farms already do, Tier 2 and Tier 3 are expected to drive the greatest climate‑adaptation impacts – though separating adaptation from mitigation remains a challenge in practice. The subsidy landscape is likely to continue evolving as budgets and schemes consolidate under the new structure. More information available at: 0624 Future Support Briefing.pdf

Economic context

Figure F1: Breakdown of contributions to farm income by farm type, 2023-24. Source: Scottish Government, 2025d.

How to cite this publication:

Brett, L., White, C.J., England, K., Calvillo Munoz, C., Roberts, J.J. (2026) ‘Investigating climate change adaptation investment need across five sectors in Scotland (2026 – 2040)’, ClimateXChange. DOI: https://doi.org/10.7488/era/7087

© The University of Edinburgh, 2026
Prepared by the University of Strathclyde on behalf of ClimateXChange, The University of Edinburgh. All rights reserved.

While every effort is made to ensure the information in this report is accurate as at the date of the report, no legal responsibility is accepted for any errors, omissions or misleading statements. The views expressed represent those of the author(s), and do not necessarily represent those of the host institutions or funders.

This work was supported by the Rural and Environment Science and Analytical Services Division of the Scottish Government (CoE – CXC).

ClimateXChange

Edinburgh Climate Change Institute

High School Yards

Edinburgh EH1 1LZ

+44 (0) 131 651 4783

info@climatexchange.org.uk

www.climatexchange.org.uk


  1. The figures represent one scenario-based estimate of potential adaptation-related spend required to maintain current service levels under future climate conditions – there are many potential future scenarios, each returning different potential investment requirements.



  2. Note Scottish Water estimates are for 13 years from 2027/28 – 2039/40.



  3. The figures represent one scenario-based estimate of potential adaptation-related spend required to maintain current service levels under future climate conditions – there are many potential future scenarios, each returning different potential investment requirements.



  4. Note Scottish Water estimates are for 13 years from 2027/28 – 2039/40.



  5. We have modelled the impacts based on the available estimates on adaptation spending over the next 15 years, until 2040. If further adaptation spending is required then the economy-wide impacts will continue. In that case more analyses will be needed to explore the implications of extended adaptation spending.



  6. The modelled shock to the economy has completed, so in the absence of a shock the economy returns back to the baseline.



  7. https://ieep.eu/wp-content/uploads/2024/07/The-costs-and-benefits-of-transitioning-to-sustainable-agriculture-IEEP-2024.pdf



  8. https://www.gov.wales/sites/default/files/publications/2023-12/atisn19234doc1.pdf



  9. https://doi.org/10.33988/auvfd.837485



  10. https://www.gov.scot/binaries/content/documents/govscot/publications/corporate-report/2026/01/scottish-budget-2026-2027/documents/scottish-budget-2026-2027/scottish-budget-2026-2027/govscot%3Adocument/scottish-budget-2026-2027.pdf



  11. https://www.gov.scot/publications/scottish-rural-development-programme-2014-2020-ex-post-evaluation-annex-scheme-summary-report/pages/11



  12. https://www.gov.scot/publications/results-from-the-scottish-agricultural-census-june-2024/pages/most-of-scotlands-area-is-used-for-agriculture/



  13. https://www.researchgate.net/publication/390161885_Benefits_of_Crop_Rotation_UK_Scenario_25032025



  14. https://www.gov.scot/publications/total-income-from-farming-estimates-2018-2024/pages/value-of-output-remains-stable/)



  15. https://www.gov.scot/publications/developing-method-estimate-costs-soil-erosion-high-risk-scottish-catchments/pages/8/



  16. https://onlinelibrary.wiley.com/doi/full/10.1002/ldr.2879


The Scottish Government has made successive commitments to delivering a just transition to a net zero and climate resilient Scotland. The Scottish Government and others have made progress in developing monitoring and evaluation (M&E) frameworks to consider the fairness of transition processes and outcomes. However policymakers have found that these were not ready to be implemented in practice. 

On behalf of the Scottish Government, ClimateXChange commissioned a research fellow, embedded in the government’s Climate Change Analysis team, to develop a just transition M&E framework that prioritises rigour and practical use.  

This research is independent and should not be considered Scottish Government policy. 

The framework  

The proposed framework is made up of four outcomes, each with a set of indicators – Communities and Places, People and Equity, Jobs, Skills and Economic Opportunities, Environment and Biodiversity. 

There are 50 outcome indicators in total. 15 of these are identified as summary indicators intended to provide a high-level overview of progress that can be more easily communicated than the full indicator set. 

In addition to outcome indicators, this research includes 23 indicators focused on key locations, or hotspots, where the transition to a net zero and climate resilient Scotland is likely to have significant impact.  

Hotspots are defined as places either experiencing significant industrial change, for example Aberdeen and Grangemouth, or hosting major net zero developments, such as Shetland and Dumfries and Galloway. 

This project also examines possible anticipatory approaches for early warning identification and monitoring of hotspots, transition risks and opportunities. 

The proposed framework emphasises the essential role of regular stakeholder engagement to inform all dimensions of M&E.  It can be used as a tool for qualitative data collection, an approach for monitoring and indicator interpretation, a real-time tool for risk mitigation and a method for the anticipation of potential transitions. 

Recommendations 

The research report includes a number of recommendations to further develop the framework and just transition monitoring and evaluation. These include testing and refining through data collection, developing qualitative engagement tools, filling critical data gaps and using communications tools such as data visualisation tools to engage with external stakeholders on just transition progress.  

For detailed recommendations and next steps and to learn about the development of the proposed framework, please read the report.  

If you require the report in an alternative format, such as a Word document, please contact info@climatexchange.org.uk or 0131 651 4783. 

Research completed March 2026

DOI: https://doi.org/10.7488/era/7089

Executive summary

Background and aims

The Scottish Government has made successive commitments to delivering a just transition to a net zero and climate resilient Scotland. As part of this, it is important to understand, as far as is practicable, the extent to which transition processes and outcomes are just. Recent years have seen proactive efforts by the Scottish Government and others to develop monitoring and evaluation (M&E) frameworks for a just transition in Scotland. These made progress but the Scottish Government found they were not yet ready to be implemented in practice.

ClimateXChange commissioned this research on behalf of the Scottish Government to deliver a proposal for a just transition M&E framework that prioritises rigour and practical applicability. The project was led by the University of Edinburgh and delivered by a ClimateXChange Research Fellow embedded in the Scottish Government.

This report is independent: it is not Scottish Government policy, nor does it reflect Scottish Government policy positions.

Results – The framework

This project developed an M&E framework for a just transition to a net zero and climate resilient Scotland, informed by a Theory of Change approach. The proposed framework is made up of four outcomes, each with a set of indicators (number of indicators in parentheses):

  • Communities and Places (12),
  • People and Equity (13),
  • Jobs, Skills and Economic Opportunities (17),
  • Environment and Biodiversity (8).

There are 50 outcome indicators in total. The framework also identifies 15 summary indicators which are selected from the 50 outcome indicators. These are intended to provide a high-level overview of progress that can be more easily communicated than the full indicator set.

Figure 1 provides an overview of outcome indicators in the M&E framework. These are categorised by outcome, target population, summary indicators and data availability. Some of the proposed indicators cannot be monitored with existing data.

In addition to outcome indicators, this framework proposes a set of 23 indicators for monitoring key sites of transition, or ‘hotspots’. Hotspots are defined as places directly impacted by industrial change or by net zero developments. This project also examines possible anticipatory approaches for early warning identification and monitoring of hotspots, transition risks and opportunities.

Stakeholder engagement is identified as fundamental for just transition M&E. It is presented as a tool for qualitative data collection, an approach for monitoring and indicator interpretation, a real-time tool for risk mitigation and a method for the anticipation of potential transitions.

Framework limitations

  • Data availability, timeliness and scale: There are data gaps for some key just transition concerns. Data availability, quality and coverage also vary at local, regional and national scale. In addition, they do not always match the scale of concern (e.g., local authority data does not represent the sub-local authority Grangemouth and Falkirk towns). Most indicators are published with a time delay and will not reflect transition impacts in real time.
  • Framework structure, design and development: This project provides a detailed approach to monitoring a just transition in Scotland and to interpreting outcome indicators. Further work is needed to support evaluation of why a just transition is / is not being achieved.
  • The proposed M&E framework emphasises the essential role of regular stakeholder engagement to inform all dimensions of M&E. Effective stakeholder engagement in resource constrained contexts can be challenging and may limit implementation.

Recommendations for just transition M&E

  • Start now: test and refine the proposed approach through data collection and indicator interpretation across outcome and hotspot indicators. This will enable an assessment of the practical applicability of the framework and its ability to capture just transition concerns in the Scottish context.
  • Identify the conditions necessary for just transition delivery and develop approaches to evaluation. This will include attention to issues of governance, responsibility and policy responsiveness to just transition M&E.
  • Develop qualitative engagement tools and analytical approaches as part of just transition M&E, to support the identification of transition risks, indicator interpretation and evaluation.
  • Implement more integrated approaches to data collation and sharing across Scottish Government and with external stakeholders.
  • Fill critical data gaps, including but not limited to (i) workforce transitions in high emitting sectors, (ii) business vulnerability and adaptation to climate change and net zero, (iii) household vulnerability and resilience to climate change and (iv) land use change implications for a just transition.
  • Test and refine anticipatory uses of just transition M&E to identify and monitor sites of transition before transitions are underway. This can support the anticipation of risks and opportunities and inform responsive policymaking.
  • Use M&E to improve communication with external stakeholders about transition efforts towards net zero and climate resilience, including successes and challenges. Consider the use of data management and visualisation tools such as dashboards, websites and reports for data management, communication and reporting.

Figure 1. Outcome indicators in the just transition M&E framework. Categorised by outcome, target population, summary indicators and data availability.

Glossary

Just Transition

“For the Scottish Government a just transition means becoming a net zero, climate resilient economy in a fair way that seeks to tackle inequality and injustice. Just transition is about both the outcome – a fairer, greener future for all – and the way we get there in partnership with those most likely to be impacted by the change.” (Scottish Government, 2026a, p.32)

Net zero

“A situation in which any greenhouse gas emissions put into the atmosphere are balanced out by the greenhouse gases removed from the atmosphere, so that the “net” effect is zero emissions. Scotland has committed to ‘net zero’ emissions by 2045.” (Scottish Government, 2026a, p.33)

Climate resilience

In this report, climate resilience refers to the results of adapting to a changing climate. “Adaptation to climate change involves the deliberate and systematic adjustment of systems and processes to effectively address both anticipated and actual climate change impacts.” (Scottish Government, 2026a p.32)

Hotspots

Sites of transition identified on the following basis:

  • Places reliant on a high-emitting industry and undergoing industrial change
  • Places hosting net zero developments (renewable energy infrastructure and land use change) and their aggregated impacts

Monitoring and evaluation

A practice by which responsible actors can track, measure and assess progress towards identified goals, while analysing the degree to which implemented actions supported the delivery of said goals.

Indicator

An indicator is a specific, measurable variable which can be monitored over time, often to show trends. An indicator should support assessment of progress towards achieving overall aims. Indicators can be qualitative or quantitative and may be tracked at different timeframes (e.g. annually, biannually, every 5 years).

Abbreviations

CCC

Climate Change Committee

CCP

Climate Change Plan

EU

European Union

JT

Just Transition

JTC

Just Transition Commission

M&E

Monitoring and Evaluation

NSTA

North Sea Transition Authority

SEPA

Scottish Environmental Protection Agency

SIMD

Scottish Index of Multiple Deprivation

STUC

Scottish Trade Union Congress

SNAP3

Scottish National Adaptation Plan 3

SPRI

Scottish Pollutant Release Inventory

ToC

Theory of Change

UK

United Kingdom

List of figures and tables

Figure 1. Structure and parts of the full Just Transition M&E framework. 12

Figure 2. Visualisation of the four outcomes of a JT to a net zero and climate resilient Scotland. 14

Figure 3. Outcome indicators in the JT M&E framework. Categorised by outcome, target population, summary indicators and data availability. 15

Table 1: Methods used in the development of the JT M&E framework. 7

Table 2. Outcomes, M&E framework for a JT to a net zero and climate resilient Scotland. 13

Table 3: Summary indicators for the JT M&E framework. 18

Table 4: Communities and Places outcome for the JT M&E framework. 21

Table 5: People and Equity outcome for the JT M&E framework. 23

Table 6: Jobs, Skills and Economic Opportunities outcome for the JT M&E framework. 25

Table 7: Environment and Biodiversity outcome for the JT M&E framework. 27

Table 8: Hotspot indicators, by hotspot ‘type’ and data source. 36

Introduction

The Scottish Government has made successive commitments to integrating Just Transition (JT) into its policymaking processes and outcomes. JT principles were integrated into the Climate Change Act (Scottish Parliament, 2019) and the Just Transition Commission (JTC) was established with an independent scrutiny role. The Government also published a National JT Planning Framework (2021); draft sectoral JT plans for energy (Scottish Government, 2023), transport (Scottish Government, 2025a) and agriculture and land use (Scottish Government, 2025b); and the Grangemouth Industrial JT Plan (Scottish Government, 2025c). Most recently, JT indicators were included in the Climate Change Plan (CCP) published in March 2026 (Scottish Government, 2026b). The Government also committed support for a JT through the Just Transition Funds for Grangemouth and for the North East and Moray (Scottish Government, 2025c; Scottish Government, 2026c).

JT monitoring and evaluation (M&E) approaches remain in their infancy for various reasons. Defining what is captured within the scope of JT is challenging. In addition, there are difficulties in developing national-level frameworks which also reflect the experiences and needs across people and geographies. There are challenges around the temporal nature of the transition, including the ways in which responsibilities, costs and benefits are spread across generations. The transition to net zero and climate resilience also faces uncertain impacts and unintended consequences, including from unpredictable economic, geopolitical and climatic shocks. From a practical perspective, there are clear data weaknesses and gaps for JT monitoring in Scotland (e.g., Drabble et al. 2024). Finally, there are limited examples of applied frameworks for JT M&E worldwide.

Scotland is embarking on the transition to net zero and climate resilience from a baseline of inequality and existing, legacy injustices (Drabble et al. 2024). The cumulative impacts of climate change, climate adaptation and decarbonisation risk entrenching injustices and creating new ones. At the same time, the systems-wide net zero transition is also an opportunity to correct historical injustices while improving equity, wellbeing and justice in Scotland; goals aligned with the Scottish Government’s JT outcomes in the National JT Planning Framework (2021). It is essential that the Scottish Government can understand, as far as is practicable, how the transition is unfolding, and whether the associated processes and outcomes are just.

Recent years have seen proactive efforts to develop JT M&E approaches in Scotland. Research by the Just Transition Lab in Aberdeen and Aberdeenshire advanced understandings of place-based JT monitoring grounded in local priorities (Shapovalova et al. 2023). The second JTC published various place-based reports (e.g., in Shetland (Voar, 2024), Dumfries and Galloway (2025a) and Aberdeen and the North East (2025b)), showcasing the unique characteristics of net zero transitions in different parts of Scotland. The JTC also published a national JT Theory of Change (ToC) and M&E framework (Drabble et al. 2024). The latter was subsequently translated into the Grangemouth local context (Jenkins et al. 2025). While these works took JT M&E further and provided a broad overview of JT and M&E concerns, the Scottish Government found they were not yet ready to be implemented in practice.

This project was commissioned by ClimateXChange on behalf of the Scottish Government. The aim was to develop a rigorous and pragmatic JT M&E framework that could be made operational by the Scottish Government. As such, it builds on existing work and departs from it, informed by additional empirical stakeholder engagement and a review of the most recent evidence.

The project was led by the University of Edinburgh and delivered by an independent ClimateXChange Research Fellow embedded in the Scottish Government. This report sets out a proposed JT M&E framework and recommendations for JT M&E implementation for the Scottish Government. The report is independent: it not Scottish Government policy, nor does it reflect Scottish Government policy positions.

Conceptualising JT ‘Monitoring and Evaluation’

The term ‘Monitoring and Evaluation’ (M&E) encompasses a range of practices for tracking, measuring and assessing progress towards identified goals. M&E also analyses the degree to which implemented actions supported the delivery of those goals (HM Treasury, 2026; HM Treasury, 2020; Adindu, 2010; Estrella and Gaventa, 1998). The use of M&E frameworks is widespread, often to assess the impact of specific delivery programmes or interventions (e.g., Adindu, 2010).

A ‘JT’ is often not contained to a single policy or project and for some, is an overarching societal goal. Responsibilities and influence over a JT are spread across a variety of stakeholders and its achievement is often conditioned by a broader, shifting context. In this way, it can be comparable to the Sustainable Development Goals (United Nations, n.d.) or aspirational visions of national wellbeing, as reflected in Scotland’s National Performance Framework (currently archived and under revision) (Scottish Government, n.d.).

In Scotland, both Scottish Government policy (e.g., Scottish Government, 2021a) and JTC published reports (e.g., Just Transition Commission, 2024, 2025a, 2025b; Voar, 2024; Drabble et al. 2024; Jenkins et al. 2025) define the JT in expansive terms. This includes a spread of intersecting concerns including employment; community participation and empowerment; the distribution of benefits; industrial change and existing socio-economic inequalities, across scales and sectors. Further increasing complexity, the JT is characterised both as a “process” and “outcome” (Scottish Government, 2021a, p.5; e.g., Jenkins et al. 2025, p.27). So, a JT is as much about the just-ness of how the transition develops, as about the impacts it creates.

In the context of specific delivery programmes, policies or interventions, ‘monitoring’ is the “process of continuously tracking the progress and performance of an intervention, to provide data on whether it is being delivered as intended” (HM Treasury, 2026, p.72). It involves tracking specific data points over time that relate to the overall goal. The cross-cutting, multi-dimensional and multi-stakeholder nature of JT makes such an approach challenging. In the Scottish Government, many policy areas relate to, impact and condition JT delivery, from economic development through to poverty, agriculture, planning or technological development (e.g., Scottish Government, 2021a). Although there is a central JT Unit within the Scottish Government, there is no single, neatly bounded programme for JT delivery.

In a policy context, evaluation can be defined as: “a systematic assessment of the design, implementation and outcomes of an intervention. It involves understanding how an intervention is being, or has been, implemented and what effects it has, for whom and why” (HM Treasury, 2020, p.5). Evaluation is also broader, however, referring to “the process of judging or calculating the quality, importance, amount, or value of something” (Cambridge dictionary, n.d.). It is possible to evaluate what happened, how it happened and/or why it happened. These three types of evaluation are different, require different approaches and all apply in the context of assessing progress towards a JT.

This project understands ‘monitoring’ and ‘evaluation’ as interdependent practices necessary to comprehend the just-ness of the transition to net zero and climate resilience in Scotland. This interdependent approach underpins the conceptualisation and structure of the proposed JT M&E framework. Indicators were selected based on key, monitorable areas related to JT outcomes. Indicator selection was also underpinned by the framework’s evaluation objectives, based on a dual understanding of evaluation as assessing what is happening, and why. Said another way, the framework was designed to enable both an assessment of the just-ness of the transition, and an assessment of why particular impacts have come about.

The framework takes inspiration from ‘Theory of Change’ (ToC). In simple terms, ToC can be defined as “the hypothesis about the way that a program brings about its effects” (Dhillon and Vaca, 2018, p.65). ToC has been identified as a useful tool to design transformational social interventions (Simeone et al. 2023) and has been used by the Scottish Government to inform M&E frameworks for complex, multi-dimensional phenomena. Examples include the third Scottish National Adaptation Plan (SNAP3) M&E framework (Scottish Government, 2024a), and the Grangemouth Industrial JT Plan (Scottish Government, 2025c). Drabble et al. (2024) also used a ToC approach to inform their development of a JT M&E framework for Scotland.

ToC informed M&E frameworks often contain two key dimensions: outcomes and mechanisms. Outcomes are medium term goals, or ‘what success looks like’; while the mechanisms or enablers are the ‘conditions for success’ (Drabble et al. 2024, p. 42). Because mechanisms focus on the conditions for successful delivery of the outcomes, they can support evaluation of why progress is being made.

Drawing on ToC and the JT M&E framework developed by Drabble et al. (2024), the proposed M&E framework is designed to include both outcomes and mechanisms. Within this structure, this project has prioritised (a) outcome identification and refinement and (b) indicator development for monitoring. As currently developed, the framework therefore enables JT monitoring and supports evaluation of what is happening in relation to JT outcomes, but not how or why. The framework’s design enables the future integration of mechanisms to support evaluation of why JT progress is underway. This responds to the project specification to develop:

  1. High-level quantitative metrics for JT M&E in Scotland,
  2. Qualitative evaluation proposals to support indicator monitoring, including attention to place-based activity and the experiences of the most vulnerable to negative transition impacts, and
  3. A proposal for an integrated and practical approach to JT M&E that combines quantitative and qualitative approaches in a coherent theoretical framework.

Project methods and report structure

Methods

The methods used to inform the proposed M&E framework and related recommendations are summarised in Table 1.

Method

Detail

Purpose

Policy review

Including:

  • Scottish Government policy, prioritising JT policy and related policy areas
  • M&E frameworks in JT and related policy areas in Scottish Government
  • Examples of JT M&E approaches across governments worldwide
  • To increase familiarity with the Scottish Government JT policy landscape and policy M&E approaches and expertise.
  • To learn from and build on available existing JT M&E, approaches as relevant to the Scottish context.
  • To inform the shape and language of the final framework, including through the identification of gaps, inconsistencies, and underdeveloped opportunities.

Literature review

Including:

  • JT M&E approaches by non-government stakeholders for Scotland and further afield
  • Identified JT M&E academic literature
  • To provide insight into existing JT M&E work, alongside methods for JT M&E.
  • To learn from and build on available approaches as relevant in the Scottish context.

Semi-structured and unstructured interviews, exchanges

With external stakeholders and public agencies (Appendix A):

  • On existing M&E practices and frameworks
  • On JT priorities and indicators

Total: 16

  • To gain practical insight into available methods, frameworks and practices to understand, analyse and evaluate impact.
  • To refine the focus of outcomes and indicators and identify available data sources.

Iterative engagement across Scottish Government areas

Continuous, routine and ad hoc meetings and follow up discussions with team members across government areas.

To support indicator development, data identification and recommendations drawing on cross-government expertise.

Workshop

In-person workshop with purposefully selected stakeholders and Scottish Government team members (held on the 17 November 2025).

To support indicator identification and refinement across outcomes and attention to affected and vulnerable groups in the transition and climate change context.

Internal sessions

Internal sessions with Scottish Government team members responsible for the future direction and implementation of JT M&E (organised in February 2026).

To increase JT M&E framework familiarisation within Scottish Government and inform reflections and recommendations on implementation in a policy context.

Table 1: Methods used in the development of the JT M&E framework.

The Research Fellow was embedded within the Scottish Government Climate Change Analysis Team in close collaboration with members of the JT Unit. This enabled engagement across government teams, attendance at relevant internal webinars and workshops and direct involvement in discussions on a variety of relevant JT topics. It also informed the methods detailed in Table 1, including through access to support on policy and data identification, workshop design and facilitation, or iterative discussions on M&E framework development. A full list of interviewees, workshop attendees and areas engaged across the Scottish Government is included in Appendix A.

Report structure

Section 2 outlines the evidence reviewed, focusing on Scottish Government policy and JT M&E proposals across policy and academia worldwide. Section 3 presents the key findings from this research. Sections 3.1 and 3.2 detail the core of the proposed M&E framework including JT outcomes, indicator and data selection methods, and outcome indicators. Section 3.3 presents a ‘hotspot’ monitoring approach and indicators, integrating place-based JT M&E within a national M&E framework. It also proposes anticipatory approaches to monitoring as part of JT M&E. Section 3.4 includes detail on interpreting framework indicators. Section 4 sets out framework limitations and reflections on JT M&E. Section 5 presents a set of recommendations and concludes this report.

Evidence review

The Scottish Government published a National JT Planning Framework in 2021 (Scottish Government, 2021a). This included eight JT outcomes focused on empowering communities; skills development and fair work; addressing existing socio-economic inequality; supporting a strong and productive economy; supporting climate adaptation; protecting the environment; ensuring decarbonisation, and furthering human rights while avoiding the creation of new injustice (Scottish Government, 2021a, p.31). The Government also committed to developing sector-specific JT plans for four ‘net zero sectors’: energy (2023), transport (2025a), agriculture and land use (2025b) and buildings and construction (not yet published). In tandem, the Grangemouth Industrial JT Plan was published in 2025.

The National JT Planning Framework, draft sectoral JT plans and the Grangemouth Industrial JT Plan are structured differently and vary in detail and level of indicator development. The sectoral plans and Grangemouth industrial plan all refer to four themes which cluster JT concerns in Scotland: Communities and Places; People and Equity; Jobs Skills and Economic Opportunities, and Environment, Biodiversity and Adaptation[1][2].

In parallel, the second JTC has focused on JT M&E, including through recommendations in their Annual Report (2024) and in their final report in 2026 (Just Transition Commission, 2024, 2026a). They have published numerous JT M&E reports, including by Drabble et al. (2024) who developed a ToC for a JT in Scotland and a national JT M&E framework. The authors detailed JT priorities in the Scottish context, articulating both outcomes (what success looks like) and mechanisms (how to get there). They developed indicators, identified data sources and data gaps and provided a baseline assessment of indicator progress on a traffic light scale (improving – maintaining – declining).

The national JT M&E framework by Drabble et al. (2024) was translated into the Grangemouth local context by Jenkins et al. (2025). This reiterates the importance of place-specific transitions and accordingly, contextualised M&E. Shapovalova et al.’s (2023) work on monitoring a JT in Aberdeen and Aberdeenshire also focused on place-based transitions. Through stakeholder engagement, the authors identified four JT themes and an accompanying suite of indicators, which were analysed in relation to the local context.

The Scottish Government has also commissioned ClimateXChange projects to review and learn from the evolving JT M&E landscape and inform sectoral JT plans. These include a summary of existing approaches to JT M&E (Bergseng, 2023) and three reports by SYSTRA (2023a, 2023b, 2023c). The SYSTRA reports provide JT perspectives into sectoral areas of energy, transport and the built environment and construction.

Drawing boundaries around what is/ is not JT policy is an ongoing challenge. Climate change impacts and actions relating to the transition are cross-cutting issues, as are considerations of justice. Beyond explicit JT policy, there are various Scottish Government policy areas directly relevant to issues of JT. Illustrative examples of strategies and monitoring frameworks which overlap with JT considerations include: the National Performance Framework, the CCP (2026), the SNAP3 M&E framework (2024), the Public Engagement Strategy for Climate Change (Scottish Government, 2021b), the draft Environment Strategy (Scottish Government, 2025e), the Biodiversity Strategy M&E framework (Scottish Government, 2024b), the National Transport Strategy 2 (2020) and related M&E frameworks (Transport Scotland, 2021, 2022, 2024), the National Strategy for Economic Transformation (2022) and the Green Industrial Strategy (Scottish Government, 2024c).

Across Scottish Government JT policies, reports and related policy arenas, there is some convergence around ToC informed approaches to M&E. Most clearly, the Grangemouth Industrial JT Plan includes JT outcomes and ‘transition levers’ (the mechanisms), which capture ‘how the Just Transition will be delivered’ (Scottish Government, 2025c, p.11). In the space of climate adaptation, SNAP3’s M&E framework uses a ToC informed approach with outcomes, objectives and indicators, including a monitored annual baseline and identified climate adaptation ‘enablers’. The ToC has also been mobilised in JT M&E efforts beyond Scotland.

Beyond Scotland

Efforts to monitor and evaluate progress towards a JT are emerging worldwide. The diverse models reflect varying interpretations of the JT both conceptually and in a policy context. In the European Union (EU) context, for instance, JT M&E is proposed in relation to environmental policy (Heyen et al. 2021). The authors present a suite of output, result and impact indicators including measures linked to EU social domains and environmental impacts. More broadly, the EU defines ‘JT regions’ as carbon intensive regions currently supported by the Just Transition Fund (EU, 2024). This contrasts with the more expansive understanding of JT by the Scottish Government.

Kelly et al. (2025) developed a JT M&E approach for the Irish government based on JT ‘domains’. These are broadly sector-oriented (electricity; agriculture and land use; buildings; transport and connectivity, and environment) along with two cross-sectoral domains: skills and employment, and participation and community engagement. The sectoral approach echoes sectoral JT plans under development in Scotland. In Kelly et al. (2025), these are integrated into the core structure for a nation-wide JT monitoring framework for Ireland. The framework is funded by the Environment Protection Agency and sits in relation to environmental policy, as per the EU.

The Spanish Government’s understanding of JT is primarily focused on economic and employment aspects of the transition, alongside additional social concerns (Spanish Government, 2020). In addition, Spain takes an ‘at-risk area first’ approach to JT, which prioritises attention to declining coal and emissions-intensive dependent regions through the implementation of place-based ‘Just Transition Agreements’ (Spanish Government, 2020). From an M&E angle, Spain has been reporting on JT progress for circa five years. Their monitoring and reporting approach is output oriented and focuses primarily on whether policy commitments have been delivered (yes/no), and on data such as the amount of funds invested into different projects (Spanish Government, n.d.). There is lesser attention to Spain’s progress towards a JT overall from an outcome-oriented perspective. Their reports provide detailed, qualitative case studies about place-based ‘Just Transition Agreements’ implementation and delivery (Spanish Government, 2023).

Although not specifically a JT framework, the National Wellbeing Framework for Wales provides an applied example of monitoring multi-dimensional, complex phenomena on an outcome basis, as it has been reported against since 2017[3]. This framework is made up of seven high-level goals (or outcomes) and identifies a suite of 50 indicators which map across the different goals. In this framework, a single indicator may be used to monitor progress across various goals. From these 50 indicators, 16 are selected as milestone indicators to provide a high-level overview of how Wales is doing in relation to wellbeing goals (Welsh Government, 2022a, 2022b). The cross-cutting approach to indicator relevance, along with framework visualisations and reporting experience make this a useful example for JT M&E framework development.

The Taranaki region in New Zealand used a ToC approach to identify JT outcomes for a vision of Taranaki in 2050 (Venture Taranaki, 2020). This framework includes monitoring, causality analysis, policy tracking and evaluation. It is conceptualised in detail but appears at an early stage of implementation, with limited indicator development. Tarfa et al.’s (2024) Monitoring, Reporting and Verification framework for a Just and Gender Inclusive Transition in Nigeria also used a ToC approach. The authors present an overarching JT goal, a vision and eight high-level outcomes, the latter of which are broken down into actions, intermediate outcomes and ultimate outcomes. Indicators cover environmental dimensions like emissions or chemical spillage and pollution, and social dimensions ranging from positive community impacts, reducing social inequalities or the redistribution of oil and gas revenues to social projects.

The Monitoring, Evaluation and Learning framework for tracking a JT in South Africa (ICAT, 2024) is also grounded in a ToC. The authors include restorative justice, procedural justice and distributive justice as underpinning their understanding of JT. This framework incorporates enabling conditions, outputs, milestones and outcomes through which to reach overall JT impact. It identifies 54 priority indicators across these categories. Outcome indicators are focused on fossil fuel consumption, emissions reductions, training and employment creation, and participation measures, at times reporting at smaller geographical levels or by demographic groups.

Research by Oliver et al. (2025) into JT M&E in the Welsh context offers a different approach to ToC and outcome-based frameworks. Drawing on concepts of resilience and vulnerability, the authors identify what would affect a person’s ability to prepare for, respond to, benefit from, and recover from different climate change policies and scenarios. On this basis, they conceptualise a composite, weighted vulnerability index focused on vulnerability to climate change mitigation and rank Welsh local authorities accordingly.

JT M&E has also been explored in academia, often in collaboration with policy or industry. Examples include Htitich et al.’s (2024) methodology for developing a Just Transition Score tool in collaboration with the Social Progress Index, or Kelly et al.’s (2020) composite indicator to identify households at risk of energy poverty. From a policy development and evaluation perspective, Bird et al. (2024) developed a tool to assess ‘Just Energy Transition Plans’, while Kaljonen et al. (2024) set out an approach to combine policy mixes to support JT delivery. McCauley et al. (2023) suggested a JT ranking method through a suite of indicators which they related to theoretical justice tenets. Live, industry-based examples of JT monitoring include the World Wildlife Fund’s tool and scorecard to rank national JT plans (World Wildlife Fund, n.d.); the World Benchmarking Alliance’s JT Methodology (2025) which uses a ‘scoring and weighting’ approach that provides a very high-level numerical score on JT; or the Transition Plan Taskforce’s (2024) review of 13 existing disclosure frameworks that are relevant to transition planning and disclosures.

Summary

The evidence reviewed illustrates a variety of approaches, models and frameworks for JT M&E. These emphasise the use of overarching goals/aims/outcomes, and the different types of monitoring approaches available. Monitoring may be focused on outcome/impact, policy delivery or output tracking. Justice theory (e.g. Heyen et al. 2021; Kelly et al. 2025) and conceptual structures like the ToC explicitly and implicitly underpin several of the reviewed examples. Others, like Oliver et al. (2025), take a composite index approach instead.

Various sources highlight the importance of quality data gathering and indicator development (e.g. Kelly et al. 2025; Tarfa et al. 2024) along with attention to demographic data breakdowns and to the distributional implications of the transition (e.g. Hayen et al. 2021; Oliver et al. 2025; Kelly et al. 2025). The evidence also emphasises the value of M&E and reporting for communication with stakeholders (e.g., ICAT, 2024). In this vein, Kelly et al. (2025, p.25) also recommend the development of a dashboard as a ‘suitable destination framework for communicating and presenting indicators and trends’.

Various reports also refer to the dynamic nature of climate change and the transition. They emphasise the importance of reviewing JT M&E frameworks alongside broader contextual trends over time (e.g., ICAT, 2024). Reports also stress the importance of harnessing an M&E framework and tools for prospective analysis (Oliver et al. 2025), equipping JT M&E and policy with foresight – or anticipatory – capacity (Kelly et al. 2025). This includes anticipatory attention to key ‘at risk’ areas (e.g. Hayen et al. 2021; Spain, 2024; Lázaro Touza et al. 2025).

The Framework

The full structure of the proposed M&E framework (‘the framework’) is illustrated in Figure 1. The objectives of the framework, informed by the evidence, Scottish Government and stakeholder input are to:

  • Monitor impacts of the transition across Scotland and provide a stocktake of how Scotland is doing from the perspective of justice,
  • Support policy tracing and causality evaluation across mechanisms and policies, in relation to JT outcomes,
  • Support anticipation of risks and opportunities of the transition before they happen, including in ‘hotspot’ areas,
  • Through the three objectives detailed above, inform policy development,
  • Communicate progress in relation to a JT, to (i) hold the government to account and (ii) improve communication of the impacts of the transition.

Figure 1. Structure and parts of the full Just Transition M&E framework.

As illustrated in Figure 1, the framework structure is informed by a ToC approach and includes both outcomes and mechanisms, as well as hotspots. Hotspots are defined as places directly impacted by industrial change or by net zero developments, further detailed in section 3.3.

The remainder of this section focuses on outcomes, hotspots and their indicators, as outlined in section 1.1. Section 3.1 details outcome development, followed by outcome indicators in 3.2. Section 3.3 presents the hotspots approach, anticipatory methodologies for hotspot identification and hotspot indicators, followed by recommendations for indicator interpretation in Section 3.4.

Outcomes

This project understands outcomes as ‘what success looks like’ or what characterises a JT in the Scottish context. Within JT policy in Scotland, the definitions and language surrounding JT (and JT M&E) have iteratively evolved since the publication of the National JT Framework in 2021. There have been varying definitions of what outcomes embody a JT in Scotland and for the Scottish Government, and there are arguably inconsistencies. The Scottish Government’s draft sectoral JT plans, for instance, do not refer to the eight outcomes in the National JT Framework (2021)[4]; and neither does the JT section within the CCP (2026). Draft sectoral JT plans, the Grangemouth Industrial JT Plan and the Draft CCP (2025) all refer to four themes: Communities and Places; People and Equity; Jobs, Skills and Economic Opportunities and Environment, Biodiversity and Adaptation. These themes are described as relating to, or grouping JT outcomes (e.g., Scottish Government, 2023; Scottish Government, 2025a)[5].

This project reviewed and mapped references to outcomes, outcome clusters, proxy outcomes, objectives, themes and priority areas (whichever way defined) within existing JT publications by the Scottish Government and in Drabble et al. (2024). Appendix B summarises the terminology and categorisations used in the documents reviewed. This highlighted clear convergence in JT policy and Drabble et al. (2024) around the four themes outlined above. On this basis, this project developed a refined set of four overarching outcomes characterising a JT to a net zero and climate resilient Scotland. These are named according to the four themes and are introduced in Table 2.

The four outcomes below synthesise the key JT areas of concern in Scotland. They were identified and refined based on the evidence review, stakeholder feedback and internal engagement with Scottish Government teams.

Outcomes

Communities and Places: The transition to net zero and climate resilience increases agency, social cohesion and community wealth across Scotland through collaboration, empowerment and socio-economic benefit.

People and Equity: The transition to net zero and climate resilience addresses existing inequalities across Scotland and avoids creating new ones, supporting a more equal society overall.

Jobs, Skills and Economic Opportunities: Scotland ensures a managed transition away from high-emissions industries and practices and delivers a diversified, prosperous and climate resilient economy grounded in worker participation, fair work, skills development and thriving business.

Environment and Biodiversity: Through the transition to net zero and climate resilience, Scotland acts within planetary boundaries and restores the natural environment for current and future generations of people and planet.

Table 2. Outcomes, M&E framework for a JT to a net zero and climate resilient Scotland.

There is inevitable overlap across outcomes. In this framework they are positioned in relation to each other and with no hierarchy (Figure 2). At the same time, each outcome signifies a distinct focus area which enables the thematic grouping of certain indicators per outcome (for a similar approach, see Shapovalova et al. (2023)).

Figure 2. Visualisation of the four outcomes of a JT to a net zero and climate resilient Scotland.

Outcome indicators

Figure 3 provides a visual overview of proposed outcome indicators grouped by outcome, including their target populations for data monitoring. It also signposts the summary indicators (intended to provide a high-level overview of the transition), and identifies the indicators with no data currently available. The remainder of this section presents the indicator development approach followed by an overview of summary indicators and outcome indicators. Additional information on indicators including their desired trend, data timeframes and a quality assessment can be found in Appendix C.

Figure 3. Outcome indicators in the JT M&E framework. Categorised by outcome, target population, summary indicators and data availability.

Indicator development and data selection

Indicator selection was guided by the following priorities: conceptual rigour, relevance and representativeness of a JT in Scotland, data availability, timeliness and responsiveness to the project specification.

Drawing on the evidence review, outcomes were defined first. This established high level JT priorities in the Scottish context. A long list of indicators was developed from policy, reports and academic literature, with attention to their relevance across the four outcomes. This list was complemented with stakeholder input. The workshop and semi-structured interviews were specifically designed to focus on indicator development. To support discussions during these engagements, the four outcomes were sub-divided into descriptive focus areas (available in Appendix D). Informal conversations and meetings with external stakeholders and the Scottish Government further informed indicator development and data identification. The indicator long list was queried and refined to merge, move and remove indicators based on relevance and data availability[6]. Full indicator details and a quality assessment can be found in Appendix C. Further detail on the indicator selection process is available upon request.

The final list of indicators was also informed by data availability. The search for available data involved desk-based research and stakeholder engagement across government teams and with external stakeholders. Tables 1, 2 and 3 in Appendix A summarise the stakeholders and different government areas engaged throughout. Drawing on Taranaki Venture (2020) and SNAP3 (Scottish Government, 2024a), criteria influencing indicator development and data selection included:

  • Relevance to the outcomes to be measured,
  • Timeliness,
  • Sample sizes for Scotland (when data is collected at UK scale),
  • Possible breakdowns by socio-economic and geographic scales (where relevant),
  • Data availability and accessibility.

Reporting for most indicators is recommended at a ‘Scotland-wide’ target population level. Additional target populations are included for some indicators based on an understanding of their relevance for specific geographies or groups. Target populations for data monitoring (relevant across all outcomes and indicator tables) include:

  • Scotland-wide: Data for Scotland as a whole,
  • Demographic groups: Age, sex, gender, ethnicity, disability, income (as relevant/ available per data source),
  • Scottish Index of Multiple Deprivation (SIMD): By SIMD percentile (e.g., locations identified as the 20% most deprived areas of Scotland) (SIMD, 2020),
  • 6-fold urban-rural classification and islands: Geographical data breakdown according to the Scottish Government’s Urban Rural Classification. This distinguishes between large urban areas, other urban areas, accessible small towns, remote small towns, accessible rural and remote rural areas (Scottish Government, 2024d). Alongside the rural-urban classification, this target population group includes monitoring islands separately,
  • Local Authorities as relevant to the indicator.

Data identification and indicator refinement were undertaken simultaneously. Efforts focused on identifying indicators where data was readily available, to ensure the feasible implementation of the framework and avoid further delays to JT monitoring. The framework also includes some indicators for which data is currently not available, yet which cover key JT areas of concern. Possibilities for indicator refinement and data collection were also explored for these indicators, the details of which can be found in Appendix E.

Finally, indicators within the framework both draw on and at times, depart from existing Scottish Government JT M&E publications. Appendix F details the parallels and differences between this framework and in particular, JT indicators in the CCP (2026).

Summary indicators

The proposed 15 summary indicators provide a high-level overview of the just-ness of Scotland’s transition across the four JT outcomes. As a small set of indicators, they offer cross-cutting insight into the JT. This may also be useful at reporting stage and for JT communication with internal and external stakeholders.

Summary indicators are selected from across the four outcomes and should be reported on at a Scotland-wide level. Additional reporting by demographic groups is also recommended for three indicators in the list: those about policy influence, opportunities for young people in Scotland and about individuals’ ability to adapt to climate change. These three indicators are selected as proxies for issues of participation, recognition and distribution of impacts and opportunities across groups in Scotland, today and in the future. Table 3 sets out the proposed 15 summary indicators.

Outcome

Summary Indicator

(all reported on at Scotland-wide level)

Target population

Communities and Places:

The transition to net zero and climate resilience increases agency, social cohesion and community wealth across Scotland through collaboration, empowerment and socio-economic benefit.

Proportion of people in Scotland reporting satisfaction with opportunities to influence (i) the Scottish Government’s approach to delivering net zero, and (ii) local policy and planning decisions relating to net zero

Demographic groups

Number of community groups involved in climate action/sustainability activities, as recorded by the Climate Action Hubs (and case studies).

 

Operational capacity of community and locally owned energy installations in Scotland. Include breakdown (i) by type of ownership (ii) by location and (iii) as a proportion of total renewable energy installed (that year/ overall).

 

People and Equity:

The transition to net zero and climate resilience addresses existing inequalities across Scotland and avoids creating new ones, supporting a more equal society overall.

Percentage of dwellings in Fuel Poverty

 

Percentage of people reporting that they can afford their individual transport costs

 

Proportion of people who agree that the transition to net zero and climate resilience will support a more positive future for young people and future generations in Scotland

Demographic groups

Level of adaptation action being taken by people in Scotland

Demographic groups

Premature deaths due to exposure to fine particulate matter (PM2.5)

Demographic groups

Jobs Skills and Economic Opportunities:

Scotland ensures a managed transition away from high-emissions industries and practices and delivers a diversified, prosperous and climate resilient economy grounded in worker participation, fair work, skills development and thriving business.

Employment (full-time equivalent) in the low carbon and renewable energy economy (LCREE) in Scotland 

 

Low Carbon and Renewable Energy Economy (LCREE) estimated direct and indirect turnover

 

High emitting industry worker participation in decisions affecting them

 

Sense of uncertainty/ confidence in the transition amongst workers in high emitting industries

 

Proportion (%) of employees earning less than the Real Living Wage

 

Environment and Biodiversity:

Through the transition to net zero and climate resilience, Scotland acts within planetary boundaries and restores the natural environment for current and future generations of people and planet.

Emissions of the eight priority Air Quality pollutants (ammonia, carbon monoxide, nitrogen oxides, non-methane volatile organic compounds, particulate matter, sulphur dioxide and lead) for Scotland

 

Scotland’s carbon footprint expressed in million tonnes of carbon dioxide equivalent per year

 

Table 3: Summary indicators for the JT M&E framework.

Communities and Places

Table 4 provides an overview of proposed indicators to monitor progress towards the Communities and Places (CP) outcome. This table includes indicator number, indicator, target population (which may include more than one population, indicated as ‘population #2, population #3’) and the data source. Indicators with no currently available data are clustered at the end of the table (CP 9-12). Summary indicators are marked with an asterisk in the CP column (e.g., CP1*). The same approach is used for all outcome tables presented in Sections 3.2.3 – 3.2.6.

Communities and Places (CP)

CP

Indicator

Population

Population #2

Data source

CP1*

Proportion of people in Scotland reporting satisfaction with opportunities to influence (i) the Scottish Government’s approach to delivering net zero, and (ii) local policy and planning decisions relating to net zero

Scotland-wide

[Demographic group breakdown in P&E]

Scottish Climate Survey (proposed addition from Autumn 2026)

CP2

Proportion of people in Scotland reporting satisfaction with opportunities to influence net zero and climate adaptation developments happening in their local area

Scotland-wide

[Demographic group breakdown in P&E]

Scottish Climate Survey (proposed addition from Autumn 2026)

Ad hoc qualitative – with stakeholders

CP3*

Number of community groups involved in climate action/sustainability activities, as recorded by the Climate Action Hubs (and case studies)

Scotland-wide

Local Authorities (qualitative)

Climate Action Hubs quarterly reporting to Scottish Government

Qualitative – with community action stakeholders

CP4

Geographical coverage of regional adaptation collaborations [once full coverage, updates on implementation]

Scotland-wide

Local Authorities not involved in adaptation partnerships

Adaptation Scotland reporting to Scottish Government

CP5

The proportion of people reporting that changes to their local place due to net zero infrastructure and/or land use change[7] have maintained or improved the quality of their local area

Scotland-wide

 

Scottish Climate Survey (proposed addition from Autumn 2026)

CP6

Area of community assets (in hectares)

Scotland-wide

 

Community Ownership in Scotland 2024 – gov.scot

CP7*

Operational capacity of community and locally owned energy installations in Scotland. Include breakdown (i) by type of ownership (ii) by location and (iii) as a proportion of total renewable energy installed (that year/ overall)

Scotland-wide

 

Energy Saving Trust

CP8

Average value of community benefits committed from renewable energy projects commissioned in the last 36 months, where a community or developer form is attached to a project

Scotland-wide

 

Local Energy Scotland community benefits register 

 

Indicators with no currently available data

Population

Population #2

Suggested method/ data source for collection

CP9

Engagement experiences of the fishing sector with offshore energy developments

Scotland-wide

 

Qualitative engagement with key stakeholder groups e.g., Regional Inshore Fisheries Group and existing forums.

CP10

Distribution of marine space across activities, including % available for fishing

Scotland-wide

 

Marine Directorate – NMPi

CP11

Number of woodland creation projects registered with the Woodland Carbon Code (WCC) and peatland restoration projects registered with the Peatland Code (PC) owned by community groups and small landholdings; and as a % of total registered projects

Scotland-wide

 

UK Woodland Carbon Code registry

UK Peatland Code registry

Case studies – qualitative engagement with stakeholders e.g., Scottish Forestry, Peatland Action, Community Land Scotland.

CP12

Socio-economic benefits from woodland creation and peatland restoration

Scotland-wide

 

Qualitative engagement with key stakeholder groups e.g., Community Land Scotland, Scottish Forestry, Peatland Action, Scottish Land Commission, and with projects under development. The WCC has a benefits self-reporting tool from which data may also be available for the Scottish Government.

Table 4: Communities and Places outcome for the JT M&E framework.

People and Equity

Table 5 provides an overview of proposed indicators to monitor progress towards the People and Equity (PE) outcome. Earlier versions of the framework included absolute poverty, relative poverty and the GINI coefficient as indicators within this outcome (in keeping with Drabble et al. (2024) and the JTC’s Annual Report (2024)). Following discussions with Scottish Government analysts, these were removed from any one outcome. Instead, they are identified as high level, contextual trends against which to analyse JT progress across all four outcomes. Further detail on the value of using poverty and inequality data as contextual trends for indicator interpretation is provided in Section 3.4.2.

People and Equity

PE

Indicator

Population

Population #2

Population #3

Data source

PE1*

Proportion of people in Scotland reporting satisfaction with opportunities to influence (i) the Scottish Government’s approach to delivering net zero, and (ii) local policy and planning decisions relating to net zero

Demographic groups

 

 

Scottish Climate Survey (proposed addition from Autumn 2026)

PE2

Proportion of people in Scotland reporting satisfaction with opportunities to influence net zero and climate adaptation developments happening in their local area. Include breakdown by (a) ocean and (b) land projects

Demographic groups

 

 

Scottish Climate Survey (proposed addition from Autumn 2026)

Ad hoc qualitative engagement with sectoral stakeholders

PE3*

Percentage of dwellings in Fuel Poverty

Scotland-wide

(ii) 6-fold rural/urban

(iii) Island local authorities

 

Scottish House Condition Survey

PE4

Housing with EPC C or above across housing/tenure types

Scotland-wide

(ii) 6-fold rural/urban
(iii) Island local authorities

 

Scottish House Condition Survey

PE5*

Percentage of people reporting that they can afford their individual transport costs 

Scotland-wide

(ii) 6-fold rural/urban
(iii) Island local authorities

Income

Scottish Household Survey

PE6

Number of people reporting they do not use public transport (buses) due to connectivity issues

Scotland-wide

(ii) 6-fold rural/urban classification groups
(iii) Island local authorities

 

Scottish Household Survey

PE7

  1. Proportion of adults within 5-minute walk of greenspace
  2. Extent of green-blue land cover in urban areas

Scotland-wide

Demographic groups

 SIMD percentile (if data is available)

Scottish Household Survey

Ordnance Survey

PE8*

Proportion of people who agree that the transition to net zero and climate resilience will support a more positive future for young people and future generations in Scotland

Scotland-wide

 

 

Scottish Climate Survey (proposed addition from Autumn 2026)

PE9*

Level of adaptation action being taken by people in Scotland

Scotland-wide

Demographic groups

 SIMD percentile

Scottish Climate Survey

PE10

Hospitalisations by heat

Scotland-wide

Demographic groups (available by age and sex)

SIMD percentile

Public Health Scotland

PE11

Proportion of householders with prior flood claims who can receive quotes from 5 or more insurers

Scotland-wide

  

Flood-Re

PE12

Proportion of people living in a flood risk area who report an inability to implement flood risk measures

Scotland-wide

  

Scottish Climate Survey (proposed addition from Autumn 2026)

 

Indicators with no currently available data

Population

Population #2

Population #3

Suggested method/ data source for collection

PE13*

Premature deaths due to exposure to fine particulate matter (PM2.5) (number of premature deaths)

Scotland-wide

Demographic groups

SIMD percentile

Public Health Scotland

Table 5: People and Equity outcome for the JT M&E framework.

Jobs, Skills and Economic Opportunities

Table 6 provides an overview of proposed indicators to monitor progress towards the Jobs, Skills and Economic Opportunities (JSEO) outcome. Indicators dependent on UK Sectoral Industrial Classification (SIC) codes may be subject to change and refinement following the revision of UK SIC codes currently underway (Office for National Statistics, 2026). This may result in new sectoral categorisations and sub-categories by activities directly related to ‘net zero’ (e.g., renewable energy) which could support targeted sectoral breakdowns for indicators such as JSEO8, “proportion [%] of employees earning less than the Real Living Wage”.

Jobs, Skills and Economic Opportunities

JSEO

Indicator

Population

Population #2

Data source

JSEO1*

Employment (full-time equivalent) in the Low Carbon and Renewable Energy Economy (LCREE) in Scotland 

Scotland-wide

 

ONS – LCREE statistics

JSEO2

Total employment in Energy (including renewables)

Scotland-wide

 

Growth sector statistics – gov.scot (www.gov.scot)

JSEO3

Employment in forestry and marginal employment changes from woodland creation

Scotland-wide

 

Scottish Forestry reporting to Scottish Government

JSEO4*

Low Carbon and Renewable Energy Economy (LCREE) estimated direct and indirect turnover

Scotland-wide

 

ONS – LCREE statistics

JSEO5

Businesses with 10+ employees with (i) a climate strategy (ii) biodiversity strategy (iii) publishing an annual sustainability report

Scotland-wide

 

Business Insights and Conditions Survey (Environment Wave)

JSEO6

Number of people in Modern Apprenticeships reporting that their apprenticeship is in a ‘net zero or green sector’ (i) 3-month and (ii) 15-month after finishing

Scotland-wide

Demographic groups

Skills Development Scotland – Apprentice Voice

JSEO7

Trade union membership density in Scotland

Scotland-wide

 

Department for Business and Trade – UK Government

JSEO8*

Proportion (%) of employees earning less than the Real Living Wage

Scotland-wide

 

Annual Survey of hours and earnings

JSEO9

The difference between male and female full-time hourly earnings in the transport sector[8]. [SIC H: Transportation and storage]

Scotland-wide

 

Annual Survey of hours and earnings

JSEO10

The difference between male and female full-time hourly earnings in the energy sector. [SIC B: Mining and Quarrying; SIC D: Electricity, Gas, steam and air conditioning supply]

Scotland-wide

 

Annual Survey of hours and earnings

JSEO11

The difference between male and female full-time hourly earnings in the construction sector. [SIC F: Construction]

Scotland-wide

 

Annual Survey of hours and earnings

JSEO12

The difference between male and female full-time hourly earnings in the agriculture sector. [SIC A: Agriculture, forestry and fishing]

Scotland-wide

 

Annual Survey of hours and earnings

 

Indicators with no currently available data

Population

Population #2

Suggested method/ data source for collection

JSEO13

Number of renewable energy supply chain businesses in Scotland

Interim proxy: £ value of ScotWind projects committed to Scottish-based suppliers

Scotland-wide

 

Selected industry statistics for business based on pre-identified SIC code sectors.

Proxy: Supply Chain Development Statements (accessed via Crown Estate Scotland)

JSEO14

Business resilience and ability to adapt to climate change and the transition

Interim proxy (in CCP 2026): Proportion of small businesses in Scotland reporting the level of energy prices as an obstacle

Scotland-wide

 

N/A

Proxy: Scotland Small Business Survey

JSEO15

Number of workers experiencing redundancy in high emitting industries in Scotland receiving support/ reporting that their employers are implementing transition plans for workers

Scotland-wide

 

Survey and qualitative engagement with key stakeholders.

JSEO16*

High emitting industry worker participation in decisions affecting them

Scotland-wide

 

Survey and qualitative engagement with key stakeholders.

JSEO17*

Sense of uncertainty/ confidence in the transition amongst workers in high emitting industries

Scotland-wide

 

Survey and qualitative engagement with key stakeholders.

Table 6: Jobs, Skills and Economic Opportunities outcome for the JT M&E framework.

Environment and Biodiversity

Table 7 provides an overview of proposed indicators to monitor progress towards the Environment and Biodiversity (EB) outcome.

Environment and Biodiversity

EB

Indicator

Population

Data source

EB1*

Emissions of the eight priority Air Quality pollutants (ammonia, carbon monoxide, nitrogen oxides, non-methane volatile organic compounds, particulate matter, sulphur dioxide and lead) for Scotland and by industrial sector

Scotland-wide

National Atmospheric Emissions Inventory

EB2

Improvements to water quality across types in Scotland

Scotland-wide

SEPA – Aquatic classification and water classification hub

EB3*

Scotland’s carbon footprint expressed in million tonnes of carbon dioxide equivalent per year

Scotland-wide

Scottish Government – Chief Economist Directorate

EB4

Global biodiversity impact (Measures the effect of Scotland’s resource use on biodiversity domestically and abroad)

Scotland-wide

Material Flow Accounts

EB5

Soil sealing

Scotland-wide

NatureScot

EB6

Regeneration of vacant / derelict urban land (% of which is regenerated through environmental restoration, for climate adaptation and by net zero initiatives)

Scotland-wide

Scottish Land Commission/SEPA, qualitative engagement with energy developers.

EB7

Number of hectares of newly protected land and marine features across Scotland

Scotland-wide

NatureScot

 

Indicators with no currently available data

Population

Suggested method/ data source for collection

EB8

Carbon and social footprint of materials used for net zero developments in Scotland

Interim proxy: Carbon Intensity of Materials (Circular Economy Strategy (2026) (Scottish Government, 2026d): indicates whether a nation is consuming more sustainable alternatives, independent of trends in overall GHG impact.

Scotland-wide

Data not available. Developers increasingly conduct project lifecycle assessments during the planning process. This may be a starting point for data collection.

Proxy: Material Flow Accounts

Table 7: Environment and Biodiversity outcome for the JT M&E framework.

Monitoring local transitions: hotspot indicators and anticipating risk

In parallel to monitoring indicators for the four, high-level JT outcomes for Scotland, the proposed framework includes a focus on key locations identified as ‘sites of transition’, or transition ‘hotspots’. This is grounded in the inherently spatial nature of (in)justice (Bouzarovski and Simcock, 2017) and the recognised importance of contextualised, placed-based approaches to transitions (e.g., Jenkins et al. 2025; Shapovalova et al. 2023). The hotspots approach integrates attention to specific places experiencing change because of or influenced by[9] the net zero transition.

The definition of ‘hotspots’ as used throughout this report is as follows:

  • Places reliant on a high-emitting industry and undergoing industrial change
  • Places hosting net zero developments and their aggregated impacts

Some hotspots are already known, while others will need to be identified and may become hotspots over time. Examples of identified hotspots include Aberdeen City, Aberdeenshire and Grangemouth in Falkirk from the perspective of industrial change. Shetland, Dumfries and Galloway or Caithness in the Highland Council are examples of hotspots hosting significant net zero developments (e.g. Voar, 2024; Equitable Energy, 2025; Mountain, 2024; Just Transition Commission, 2025). Two additional hotspot criteria have been identified but remain underdeveloped in this report: (i) places of legacy unjust transitions and aggregated effects and (ii) places facing high levels of climate change risk.

Alongside the importance of place-based transition monitoring, there is growing attention to the need for future-facing, anticipatory approaches to justice (e.g. Santos Ayllón et al. 2025; Trueworthy et al. 2024; Rodhouse et al. 2024). This was also mentioned by stakeholders during the workshop, with reference, for instance, to the known closure of Petroineos oil refinery operations at Grangemouth and a perceived failure to act in a timely fashion. The need for anticipatory, or “early warning” indicators and approaches to JT has also been emphasised in letters and consultation responses to the Draft CCP (2025) (e.g., Just Transition Commission, 2026b).

It is intended that anticipatory approaches to hotspot identification and monitoring as part of JT M&E can help mitigate risks of injustice – and pursue opportunities for more just outcomes – before transitions are locked in (Santos Ayllón et al. 2025).

The hotspot approach developed for this framework draws on existing work on place-based JT M&E. It presents an approach to monitoring place-specific sites of transition and proposes methodologies to anticipate potential transitions. In this vein, sections 3.3.1 and 3.3.2 set out approaches for hotspot identification, not monitoring. These approaches are exploratory and untested in practice and require further analytical development and pilot application. They were informed by support from Scottish Government analysts and by insight from stakeholders such as the Scottish Trade Union Congress (STUC).

Section 3.3.3 details the hotspot monitoring approach and a set of indicators. These indicators are proposed to monitor readily identified hotspots or known sites of transition. The development of the hotspots approach and hotspot indicators integrates place-based JT M&E within the proposed national JT M&E framework for Scotland.

Throughout these sections, this report reiterates the value of formalised and regular stakeholder engagement. Direct engagement with project developers, employers, planning authorities, local councils and sector-specific institutions will be invaluable to understand ongoing transition plans and decisions. This may be one of the most fruitful methods for anticipating potential transitions overall.

Identifying potential hotspots of industrial change

Locating potential industrial transition hotspots will involve identifying places hosting the types of industries which the low carbon economy is expected to move away from. These may include specific sectoral activities (e.g., oil and gas production or domestic vehicle combustion engine construction) and high emitting industrial sites which can be expected to undergo some form of decarbonisation over time.

To identify potential areas of industrial change using available data, the Scottish Government could pre-select a group of high-emitting sectors (e.g., heavy industry, manufacturing, energy, construction, or transport) using UK SIC code classifications. Although SIC code classifications do not precisely match distinctions between emitting and low-carbon activity, industry statistics by SIC code can be broken down to granular sector levels and small-scale geographies across Scotland.

A variety of statistical approaches could be then used to identify potential hotspots in relation to pre-identified sectors. ‘Location quotients’, for example, show the proportion of total employment in a place from a particular industry, compared to the national share. This can show sectors of dependency (or strength) for different local authority areas and at smaller scales. Location quotient data shows Aberdeen City as having a high location quotient in ‘mining and quarrying’ (SIC sector B) of 12.7, and Aberdeenshire of 3.2. This means that the proportion of jobs in ‘mining and quarrying’ in Aberdeen City and Aberdeenshire are 12.7- and 3.2-times the Scotland-wide share respectively (where 0.98% of Scottish jobs are in ‘mining and quarrying’)[10]. The data is sourced from the Business Register and Employment Survey and is available via NOMIS, and used by the Scottish Government, for example, in the Industry Statistics Database. 

The Scottish Government could also identify key locations of industrial activity in identified sectors (determined according to SIC codes) based on the following indicators: (i) number of employees and (ii) proportion of employment in the local area dependent on these industries. Data for these measures is available in the Scottish Government’s industry statistics (Scottish Government, n.d.). This proposal takes a slightly different approach to location quotients by recognising the relative importance of industries in places, regardless of their proportional comparison to the rest of Scotland. If a given location is particularly dependent on an industry relative to its local employment levels and economic scale, then a change in this industry could have a significant impact locally (even if the facility is relatively small compared to the Scotland-wide sectoral workforce). Possible geographical scale for these analyses (as advised by analysts in the industry statistics area in government) include, for example, ‘travel to work’ areas, which are based on commuting patterns. Some of these are larger than local authorities, while others are smaller and based around specific towns. The Scottish Government could also use data on ‘anchor firms’ as the largest place-based employers across Scotland to further support hotspot identification.

A sector-based approach could also support the identification of potential net zero ‘growth’ areas, again, using tools such as location quotients or proportion of employment in a local area. The pre-selection of opportunity net zero sectors could be based on existing government strategies and analysis (e.g., the National Strategy for Economic Transformation (2022) and the Green Industrial Strategy (2024)). This will also be conditioned to some extent by available SIC code breakdowns. The current review of SIC code classifications (UK Government, 2026) may enable improved analyses of net zero sectors in the future. There could be overlap between industrial change hotspots and growth areas.

In parallel to sector-based analyses, the Scottish Government could use data sources like the Scottish Environment Protection Agency’s (SEPA) Scottish Pollutant Release Inventory (SPRI), to identify the most emitting industrial sites across Scotland (SEPA, n.d.). This dataset is annually updated and includes an extensive list of pollutants, including key greenhouse gases such as carbon dioxide and methane. As an example, journalist investigations have previously used this data to identify what authors labelled “Scotland’s top 20 climate polluters” with a focus on carbon dioxide emissions (Edwards and Dobson, 2022). The authors identified the single most polluting sites (e.g., SSE’s gas-fired plant at Peterhead) and the most polluting companies (e.g., Ineos). A cement works plant, waste incinerators, a glass manufacturing plant and a whisky distillery were also in the ‘top 20’, highlighting potential transition sites outside of the known industrial transition sectors. This proposal is inspired by similar analyses shared by STUC.

There may also be value in using the regularly updated data and maps from the North Sea Transition Authority (NSTA). NSTA datasets include regularly updated, long term decommissioning plans by well (North Sea Transition Authority, n.d.). Alongside these, the Scottish Government’s Marine Directorate produces spatially mapped data of onshore and offshore oil and gas infrastructure (e.g., MarineScotland, 2020). A spatial, infrastructure-based approach hyper-localises the identification of potential sites of transition and may also support identification of key employers and operators across sites and wells. Additional analysis of the Marine Directorate and NSTA data to identify field names, operators and their employee base could provide further insight into oil and gas transitions more broadly. This project has identified this as a critical area requiring new data collection for JT monitoring.

Identifying potential net zero development hotspots

Scholarships focused on energy, justice and JT have demonstrated the potential negative implications of net zero developments in the places where they are deployed (e.g., Mejía-Montero, 2025; Kalt et al. 2023; Healy et al. 2019). As such, the Scottish Government should also anticipate potential sites of net zero development. This includes both the deployment of renewable energy and related infrastructure (e.g., transmission lines, subsea cables, power stations, and green hydrogen production plants). It also includes sites of land use change like woodland creation and peatland restoration (e.g., for carbon offsetting purposes).

In the case of renewable energy and adjacent energy infrastructure developments, the most comprehensive data source identified is the UK Renewable Energy Planning Database. This is updated multiple times a year (UK Government, n.d.). It tracks the progress of UK renewable electricity projects over 150kW (onshore and offshore) through the planning system across technology types[11]. This data is available in spreadsheet format and as an interactive map, and projects can be filtered by development stages (UK Government, n.d.). The Scottish Government could filter by projects at inception and planning stages as a starting point for anticipatory JT analysis of potential developments.

There is extensive research regarding the justice implications of energy. Data collection associated with renewable energy benefits and ownership distribution is already underway by the Scottish Government. In contrast, this project identifies natural capital projects resulting in land use change for net zero as an important and underexplored area from a JT perspective. The Scottish Crofting Federation, for example, voiced a clear concern regarding land purchase and accumulation through natural capital development opportunities. Conversations across natural capital and Woodland Carbon Code (WCC) areas of government recognised existing concerns about land ownership concentration and the establishment of ‘green lairds’ (McMorran et al. 2022) yet also suggested that ownership concentration is not happening to date. This contrast in stakeholder perspectives demonstrates the relevance of this arena for further research, data collection and anticipatory hotspot attention.

Stakeholder engagement during this project shed light on the limited data available in relation to natural capital projects and their impacts from a JT perspective. Existing data includes publicly available lists of projects registered with WCC and Peatland Code (PC) (Woodland Carbon Code, n.d., Peatland Code, n.d.). In addition, Peatland Action hold and map data regarding completed and in-progress peatland restoration across Scotland (NatureScot, n.d.). Their map includes data on conducted ‘feasibility studies’ which can show sites of future restoration (however, these areas will not necessarily see the development of peatland restoration projects). A similar map was not identified for woodland creation projects. Like energy developments, land use change projects need to obtain consent (e.g., Scottish Forestry, 2025). The Scottish Government could explore avenues to access planning applications for woodland creation and peatland restoration as a step towards understanding planned landscape change for net zero and climate resilience.

Net zero developments are happening at a fast pace and across all of Scotland. This project proposes that the Scottish Government visually map and regularly update related data to enable a more comprehensive understanding of (i) the degree of change across different areas in Scotland and (ii) aggregated effects in a single place. Additional criteria to inform identification of potential hotspots facing net zero developments are (i) considerations of project scale and expected impact and (iii) the local context. This is applicable to both energy and land use change hotspots.

Hotspot indicators

The following section sets out the list of 23 indicators recommended for monitoring hotspots. Various indicators for hotspot JT M&E were selected from the four outcomes in the full M&E framework. Alongside these, additional indicators were identified which provide relevant information regarding transition processes in specific contexts. The selection of indicators was also informed directly by the dual hotspot definition above.

There are known and predicted similarities in the concerns created by specific transition impacts. In the case of industrial change, for example, concerns include worker participation in decision-making processes, unemployment and worker mobility, reskilling, socio-economic wellbeing of the local community, local identity and cohesion and levels of deprivation (e.g., Mayer, 2018; International Labour Organisation, 2015; Walsh et al. 2016; Santos Ayllón and Jenkins, 2023; Shapovalova et al. 2023; Jenkins et al. 2025). For places hosting net zero developments, concerns include transparency and participation in decision-making, stakeholder recognition and decision-making power hierarchies, impacts on identity and place attachment, the distribution of socio-economic impacts and risks of extractivism (Jenkins et al. 2016; Shejale et al. 2025; Raymond et al. 2023; Kalt et al. 2023; Healy et al. 2019; Morrissey, 2023).

Known and predicted concerns informed both the definition of hotspots and the selection of hotspot indicators. As an example, industrial change hotspot indicators include workforce experiences and local economy fluctuations. They also include indicators monitoring alcohol and drug use hospitalisations. While not directly connected to net zero activity, the latter serve as early warning measures of deprivation. Their inclusion draws on Shapovalova et al. (2023) and on the SIMD. Given the SIMD is produced every four to five years, they provide advanced insight into deprivation (SIMD, 2020).

The selection of indicators is further informed by the fact that hotspots directly experiencing industrial or net zero transition impacts (e.g., from the closure of an industrial plant or the deployment of transmission lines), are also impacted by broader transition dynamics captured across the four JT outcomes. In this way, place-specific transitions are layered upon broader JT issues, such as fuel costs, transport accessibility, fair work or participatory capacity in net zero policy-making processes.

Hotspot indicators are proposed as a useful starting point and guide for monitoring hotspot areas. They are not a blanket approach that will apply equally in every site of transition or consistently through time. While hotspots may share characteristics regarding the types of transition underway (e.g. industrial change or decline), each will be unique. Indicators may illustrate similar trends for different hotspots, but this will not necessarily demonstrate that the same transitions are occurring, nor similarities in their just-ness.

Attention should be given to unique, place-based realities including through complementary analytical tools such as the SIMD, existing climate change risk maps and data (e.g., SEPA, 2025; Climate Just, n.d.) and qualitative engagement with stakeholders. This follows recommendations in Jenkins et al. (2025) regarding the importance of bespoke approaches and indicators grounded in the most relevant concerns per place. For the purposes of national-level implementation and taking a national perspective, this report provides a set of indicators as a starting point for hotspot JT monitoring. Table 8 provides an overview of hotspot indicators and their data source. Appendix G provides further detail on hotspot indicators including their desired trend and rationale.

H

Indicator (monitored by selected Local Authority)

Industrial change

Net Zero developments

Data source

H1

Employment rate for people aged 16-64 across Scotland

X

X

ONS

H2

Unemployment rate for people aged 16-64 across Scotland

X

 

ONS

H3

Number of people Not in Employment and Education or Training (16-19)

X

 

Skills Development Scotland

H4

Number of people in Modern Apprenticeships reporting that (i) their apprenticeship is in ‘green skills’/for the net zero economy’ during, 3-month and 15 months after finishing their apprenticeship and of these, (ii) number of people staying to work in their same Local authority

X

X

Skills Development Scotland – Apprentice Voice

H5

Population change (with attention to in-out migration)

X

X

Council area profiles – National Records of Scotland (NRS)

H6

Business activity/ survivability: Business birth and death rates

X

 

Scottish Government – Sub-Scotland Economic Statistics Database

H7

Sectoral economic dependence/diversification:

  1. Sectoral share of GVA (those increasing and in decline)
  2. Employment Share by Sector (Regional Sector Share) (to monitor changing employment across sectors in the local economy; those increasing and in decline).
  3. Location quotients (importance of a sector to a region relative to the national average)

Contextualised within broader economic trends per local authority

X

X

Business and innovation statistics – gov.scot

H8

Proportion of households reporting that they are managing well financially

X

 

Scottish Household Survey

H9

Median house price by Local Authority

 

X

Registers of Scotland

H10

People reporting they can afford their individual transport costs

X

X

Scottish Household Survey

H11

Proportion of adults within 5-minute walk of greenspace

 

X

Scottish Household Survey

H12

Operational capacity of community and locally owned energy installations in Scotland. Include a breakdown (i) by type of ownership (ii) by location and (iii) as a proportion of total renewable energy installed in local area

X

X

Energy Saving Trust

H13

Area of community assets (in hectares)

X

X

Community Ownership in Scotland 2024 – gov.scot

H14

Community benefits from energy (and for natural capital projects, once available)

if/as relevant

X

Local Energy Scotland community benefits register 

H15

Number of hospitalisations due to alcohol use

X

 

ScotPHO profiles

H16

Number of drug use hospitalisations

X

 

ScotPHO profiles

H17

Worker participation in industrial change processes

X

 

Data not currently available

H18

Premature deaths due to exposure to fine particulate matter (PM2.5)

X

X

Data not currently available

H19

Fuel poverty

x

(Every 3 yrs)

x

(Every 3 yrs)

Scottish House and Condition Survey

H20

Proportion of people who agree that the transition to net zero and climate resilience will support a more positive future for young people and future generations in Scotland

x

(Every 3 yrs)

x

(Every 3 yrs)

Scottish Climate Survey (proposed addition from Autumn 2026)

H21

Proportion of people in Scotland reporting satisfaction with opportunities to influence (i) the Scottish Government’s approach to delivering net zero, and (ii) local policy and planning decisions relating to net zero

 

x

(Every 3 yrs)

Scottish Climate Survey (proposed addition from Autumn 2026)

H22

Proportion of people in Scotland reporting satisfaction with opportunities to influence net zero and climate adaptation developments happening in their local area

x

(Every 3 yrs)

x

(Every 3 yrs)

 Scottish Climate Survey (proposed addition from Autumn 2026)

H23

The proportion of people reporting that changes to their local place due to net zero infrastructure and/or land use change have maintained or improved the quality of their local area

 

x

(Every 3 yrs)

 Scottish Climate Survey (proposed addition from Autumn 2026)

Table 8: Hotspot indicators, by hotspot ‘type’ and data source.

All hotspot indicators share two characteristics: they are all available at local authority level and data is updated on an annual basis (except for the Scottish Climate Survey and fuel poverty data, for which local authority data is available every 3 years). The local authority level is the smallest area for which data is available across all identified indicators. This allows comparability. This scale is also recognised as a limitation to the hotspots approach, given transition impacts may be contained to smaller local areas within local authorities. Highland Council data will not necessarily reflect realities of wind farm and transmission line installations in Caithness, for example, and centralised Orkney Islands level data may be insufficient to understand the just-ness of transitions underway on individual islands within the archipelago.

Annual data collection for most indicators is common and is the most frequent data update period (with some exceptions e.g., labour market trends, which are updated monthly). Given that hotspots are already undergoing transformational change, regular, timely monitoring is critical to understand the implications of the transition. Annual indicators could also serve as early warning indicators for hotspot locations over time. At the same time, this annual updating cycle is recognised as a limitation, given that data will never be available in real time. The limitations of the hotspots approach are returned to in Section 4.

Hotspot indicator monitoring should incorporate regular stakeholder engagement. This will be necessary to better understand both (i) where impacts are localised within each local authority and (ii) to obtain regular, near real time updates while indicator data is unavailable. Regular engagement will also triangulate monitoring with qualitative lived-experience data. The role of stakeholder engagement in JT M&E is expanded on in Section 3.5. A key recommendation for Scottish Government is the further development of effective approaches to engagement as a qualitative monitoring tool.

Interpreting indicators

The sections above have presented a set of proposed indicators across four JT outcomes, a selection of ‘summary indicators’ for these, and an additional set of hotspot indicators. Together, these indicators make up the core for monitoring a JT at a Scotland-wide level and for specific sites of transition in Scotland. The indicators are selected based on their relevance and representativeness of the outcomes and hotspots they relate to, alongside data availability.

The identified indicators are partial. Together, they support an understanding of progress towards JT outcomes, yet they are unable to capture every dimension, nuance and implication of the transition from a JT perspective. The transition itself is underway within a broader landscape of social, economic and planetary change, at local, national and international scales. For improved understanding of the just-ness of the transition, the indicators should be interpreted (i) as interrelated features of a JT within the framework, and (ii) in relation to broader contextual trends. This section addresses each of these points in turn.

Interpreting outcome and hotspots indicators

A JT to net zero and climate resilience is a dynamic, multi-layered process. As an example, an individual may face issues of transport affordability due to the shift towards electric vehicles, gain health benefits from reduced air pollution and be employed in peatland restoration while feeling disenfranchised from decisions about the installation of wind turbines near their home. This understanding of the JT was foundational to the conceptualisation of the proposed JT M&E framework.

A multi-layered and dynamic M&E framework was deemed too unwieldy for feasible implementation. As such, the core of the proposed framework is structured according to a linear logic in which high-level outcomes are monitored by a set of indicators, each with an individual desirable trend. If every indicator in the Communities and Places outcome is progressing in the desired direction, then the Scottish Government could interpret this as progress towards this JT outcome.

A review of individual indicator trends alone, however, is insufficient to assess the just-ness of the transition and may obscure experiences of injustice. As an example, an increasing trend in community energy ownership may not show differences in access to community energy ownership opportunities. These considerations also apply to interactions across indicators, and across outcomes too. Increasing community land ownership, for example, is deemed positive from the perspective of community empowerment and access to net zero opportunities. Yet changes in land ownership could also have negative distributional impacts on people previously employed on the land. The increase in marine protected areas is deemed desirable from the perspective of the Environment and Biodiversity outcome yet may also create additional pressures on fishers and coastal communities in relation to the Communities and Places outcome. Critical inquiry into the indicators, what they do not show and how they relate to each other will improve assessment of JT progress. This critical attention draws from methods developed by the field of responsible research and innovation (e.g., Stilgoe et al. 2013) and has also been proposed in anticipatory justice approaches (e.g., Santos Ayllón et al. 2025). It should be complemented with qualitative, stakeholder engagement, returned to in Section 3.5.

The hotspots approach is designed to capture the multi-layered, cross-cutting nature of the JT more effectively. This is made possible by the narrower scope offered by the hotspots approach. Thus, while hotspot indicators have an indicative desired trend (see Appendix G), they should be interpreted in their local context and, to the extent possible, in relation to each other.

Interpreting indicators against contextual trends

Indicator trends can provide the Scottish Government with an overview of progress towards (or away from) a set of desired outcomes. However, these indicators should be interpreted (i) in the context of climate change mitigation and adaptation actions and (ii) as part of a wider socio-economic landscape. The importance of interpreting indicators within context was emphasised by NatureScot team members, alongside Scottish Government analysts in the industry statistics area. The importance of context to understand quantitative indicators is also clear in Shapovalova et al.’s (2023) narrative interpretation of indicators for a JT in Aberdeen and Aberdeenshire. Contextual interpretation recognises the unpredictability of climate impacts and responses to these, and the ways in which wider trends can impact the ongoing transition (e.g., ICAT, 2024).

This report proposes an initial set of trends which can support the interpretation of monitored indicators. The first two relate to climate change mitigation and adaptation, followed by broader socio-economic trends:

  1. Greenhouse gas emissions in Scotland: To assess a JT in the context of progress towards climate change mitigation. Greenhouse gas emissions are reported on annually in the CCP (2026) with a time lag of circa two years.
  2. Climate risk (and adaptation) in Scotland: To assess a JT in the context of changing climate risk. A comprehensive assessment of climate change risk for Scotland is conducted every 5 years by the Climate Change Committee (CCC). Climate adaptation research and policy team members have used the CCC assessment to inform their M&E framework for SNAP3. The CCC presents a set of risks and evaluates these on a scale of high-medium-low. The recommendation is to use this (the number and type of risks per category) as a baseline for climate risk and adaptation (e.g., Climate Change Committee, 2021).
  3. Land ownership concentration in Scotland: To assess a JT to net zero and climate resilience in the context of evolving land ownership trends in Scotland. Changes in land ownership and land use could have a variety of impacts including potential job losses, landscape change and new distributions of benefits and harms. Land ownership was recognised by stakeholders as key to accessing opportunities from net zero and climate resilience. While data is currently unavailable to monitor land concentration trends, the annual Rural Land Market insights report by the Scottish Land Commission can provide a high-level overview of trends (Scottish Land Commission, 2025). This can be supplemented with insight from relevant Scottish Government teams and stakeholders like Community Land Scotland and the Scottish Land Commission.
  4. Economic trends in Scotland: To assess a JT to net zero and climate resilience in the context of the health and resilience of the Scottish economy at any given point in time. This can include particular attention to sectoral composition by % of GVA, to support high-level analyses of the direction of the economic transition. Economic statistics are updated annually across Scottish Government. Business and industry surveys are regularly conducted with the least regular surveys taking place on an annual basis.
  5. Poverty and inequality trends in Scotland: To assess a JT to net zero and climate resilience in the context of structural vulnerabilities and inequity. Relative and absolute poverty statistics, along with GINI coefficient and Palma ratio analyses of inequality are updated annually by Scottish Government.
  6. Global events: To assess a JT to net zero and climate resilience in the context of global affairs, including geopolitical shocks, economic crises, pandemics or accelerating commitments to climate action. Scotland is part of an interconnected economic, institutional and ecological global landscape. Developments in this landscape will undoubtedly impact on – and could be impacted by – Scotland’s progress towards a JT.

These trends are relevant for JT indicator interpretation across the four outcomes and hotspots[12]. Falling fuel poverty and increasing transport affordability indicate positive advances to address fuel and transport inequities. However, in a context of increasing greenhouse gas emissions these would not necessarily be associated with a net zero transition. A continued increase in poverty levels in a context of falling greenhouse gas emissions and increasing low carbon jobs and economic activity (JSEO1, JSEO4) may signal failings in securing JT objectives. Geopolitical shocks (such as the coronavirus pandemic, Russia’s invasion of Ukraine in 2022, or USA and Israel strikes on Iran in 2026) can impact fuel prices and the cost of living, change government policy priorities and affect public concerns. Analysis of indicators in relation to global affairs can thus support improved interpretation of indicator trends and any sudden shifts these may present.

Stakeholder engagement

The proposed framework is grounded in an underpinning commitment to formalised, regular stakeholder engagement. This is seen as fundamental to supporting JT monitoring. Workshop participants emphasised the value of stakeholder engagement and stakeholder participation both for JT delivery, and specifically to support JT M&E. They explained that building trusted and regular networks with key stakeholders could support data collection, fill data gaps, and improve communication about the transition. This focus on engagement also echoes Mechanism 3 in Drabble et al. (2024, p.47), which identified ‘stakeholder participation in Just Transition decision making’ as one of the conditions for JT success.

Stakeholder engagement is envisaged to enable qualitative data collection for relevant indicators and as a supplement to quantitative data. It is also deemed crucial for indicator interpretation, both to triangulate and contextualise indicators with experience on the ground. Importantly, stakeholder engagement can also provide insight into transition impacts before indicator data is available. Finally, engaging with key stakeholders is also suggested as an anticipatory tool for the Scottish Government to identify potential future hotspots.

Stakeholder engagement can provide granularity, nuance and qualitative case studies grounded in lived experiences of the transition. This can improve understanding of what is and is not captured by indicators, and therefore the multiple implications of the transition. As examples, a Poverty Alliance team member referred to instances in which heat pump installations in social housing had resulted in inhabitants falling into energy debt. During the workshop, a representative from CEMVO explained the difficulties often faced by ethnic minorities in accessing opportunities such as the Community and Renewable Energy Scheme (CARES) funding. Fuel poverty and community energy ownership indicators in the framework (PE3 and CP7) do not reflect these risks and inequalities relating to heat pumps and renewable energy. While indicator data does not capture these experiences, qualitative feedback can.

Some indicators in the framework suggest a combination of quantitative and qualitative data, the latter collected as ad hoc stakeholder insight or case studies. Examples include CP3 on community groups involved in climate and sustainability related activities. Climate Action Hub teams can provide qualitative insight into where community-led action is particularly strong. Conversely, this engagement can also show where it is struggling to take off and offer reasons why. Organisations like the Scottish Community Development Centre and the Scottish Communities Climate Action Network can provide further insight into community-led climate action. Recommendations for stakeholder engagement in indicator JSEO16 (on workforce participation) was informed by a discussion with STUC. This shed light on the legal and practical barriers to worker-involved transitions in high emitting industries.

Some indicators in the framework are fully qualitative. One example is CP9, which monitors engagement experiences of the fishing sector with offshore energy developments. Fishing was discussed not only as an economic activity but a way of life, with strong impact on coastal and island local economies and identities (as explained by the Regional Inshore Fisheries Group and Scottish Government team members). The Regional Inshore Fisheries Group reflected on power and resource hierarchies between offshore energy developers and the fishing sector, and on the different types of fishing and potential diverse impacts. Questions of sectoral coexistence, decline and change in the offshore economy are too complex to be captured in a single data point. Engagement with key stakeholder groups directly involved is therefore key.

The Scottish Government can explore different forms of engagement for JT M&E. These may range from individual meetings to establishing a regular stakeholder forum. There may be opportunities for the Scottish Government to complement these efforts with JTC support, which is to be renewed in 2026 (Scottish Government, 2025f). From the perspective of national JT M&E, the Scottish Government already has extensive knowledge and networks with stakeholder groups and organisations across many JT areas of concern. Internal and external stakeholders engaged with throughout this project are also deemed valuable contact points.

Alongside sector-specific stakeholders, and for national JT monitoring, the Scottish Government can engage with Scottish Government teams working on related Scotland-wide monitoring (e.g., the National Performance Framework or the Wellbeing Economy Monitor) to support contextualisation of indicators into Scotland-wide trends. In addition, the Scottish Government could explore existing connections to local authorities to contrast national-level JT monitoring with local concerns. Stakeholders such as the Convention of Scottish Local Authorities (COSLA) and the Scottish Climate Intelligence Service offer potential to connect nationwide JT monitoring to more local priorities. Local authorities could provide qualitative input to complement indicator monitoring, for example, and could report back on which indicators reflect local priorities at a given point in time.

In the case of hotspots monitoring, the Government could establish regular communication and feedback loops with a bespoke set of stakeholders on the ground. This may include local authority representatives, developers, employers, trade unions and local third sector organisations. Such arrangements could also be used as an anticipatory tool to identify future hotspots facing industrial and net zero change. In addition, existing partnerships and stakeholder networks including the eight Regional Economic Partnerships, for example, or the Sub-Scotland Economic Statistics Group, may be useful to support hotspot indicator interpretation.

While this section has focused on engagement with institutional stakeholders, this does not preclude engagement with individuals directly exposed to and experiencing transition impacts. In some cases, this could be the most direct way to access, listen to and integrate lived experience (e.g., Jenkins et al. 2025). Research into justice in energy transitions has explored the role of intermediaries in translating lived experiences such as of fuel poverty, including both their value and potential risks (e.g., Lacey-Barnacle and Bird, 2018; Santos Ayllón and Jenkins, 2023). This section recommends engagement with institutional stakeholders first for reasons of feasibility, and to ease potential burdens on directly affected groups.

Engagement with individuals experiencing transitions may in some cases be necessary to better understand and evaluate transition impacts. Where needed, the Scottish Government should build in opportunities for ad hoc qualitative research and engagement. The Scottish Government may also explore possible avenues for more formalised engagement approaches to reach lived experience, including through participatory citizens assemblies or ‘experts by experience’ panels (e.g., Elstub et al. 2022; Poverty and Inequality Commission, 2023).

Limitations and reflections

The proposed JT M&E framework has several limitations. Some of these relate to the practicalities of framework implementation, and others to the specific constraints affecting this project. Some limitations reflect the complexity of monitoring a JT itself.

Data availability, temporality and scale

Data availability has played an important role in the final shape of the proposed M&E framework. Broadly speaking, core areas of JT concern are included in the framework across outcomes and hotspot indicator lists. However, for many of these indicators, the data available is partial. For example, ‘adults within 5-minute walking distance of greenspace’ does not provide information on the quality or accessibility of this space. In addition, data for all indicators in the framework is retrospective. While many indicators in the framework are available on an annual basis, others are only available every two or three years. The current lack of real time data is arguably a limitation of any M&E framework aiming to monitor and assess a JT in Scotland.

More broadly, data limitations relate to their collection and categorisation parameters. Two clear examples are industrial classifications by SIC codes or the geographies of data collection, which do not necessarily match geographies of transition. This is particularly key in the case of hotspots. Although data is available at local authority levels, sites of transition often sit within local authorities. Transition dynamics may not necessarily be captured by local authority level data. As discussed in Section 3.5, close engagement with relevant stakeholders will be essential to better understand localised transitions. Engagement will provide as close to real-time data as possible and can triangulate and nuance indicator data. It may also be one of the most effective tools to anticipate future hotspots before transitions begin.

Finally, important data gaps remain. While the framework was developed with feasibility of implementation in mind, it also includes critical areas of JT concern for which both understanding and data is lacking. These gaps suggest areas for further research and data collection. These areas are summarised below:

  • Geographic and demographic breakdowns of low carbon and renewable energy jobs (often referred to as ‘green jobs’),
  • Education, training and skills development for the economy of the future (in ‘green’ jobs and more broadly),
  • Regular data collection on individuals’ sense of influence at smaller geographical scales (Scottish Climate Survey data is only available by local authority every 3 years),
  • Worker transitions, including the processes, distributional impacts and lived experience of workers in high-emitting sectors and on retraining pathways,
  • Exposure to climate change risk and the ability to access and adopt climate adaptation measures across people and places,
  • Climate change and net zero transition impacts on business, with attention to vulnerability, resilience and opportunities for different business types and scales. This includes direct attention to sole traders, who make up 71.9% of businesses in Scotland (Scottish Government, 2025g),
  • Implications, benefits and harms of land use change for natural capital projects,
  • Opportunities and risks relating to land ownership, access and distribution, with attention to stakeholders such as crofters, farmers and gamekeepers,
  • Land and coastal place-based identities and the implications of safeguarding or losing generational occupations and skills (e.g. crofting and fishing),
  • The spatial and demographic distribution of environmental degradation, pollution and hazardous sites across Scotland.

The list above relates to all indicators in the framework, including those with available data. For example, although there is an indicator focused on net zero skills development through apprenticeships, this is insufficient to capture the array of skilling and reskilling processes relating to net zero.

Alongside identified data gaps, stakeholder input spotlighted four key areas for further attention. These are not currently captured in the framework because they cut across various outcomes and are affected by extensive data gaps. The Scottish Government could explore (i) how these issues relate to JT delivery in Scotland and (ii) how they may be monitored and evaluated over time:

  • Distribution of responsibility, overconsumption and polluter pays considerations: Policy narratives often focus on distributing the benefits of the transition fairly and reducing the burden on disadvantaged households. However, less attention is given to responsibility, overconsumption and polluter pay considerations (at individual, business or industry levels). Participants in the workshop voiced concerns about how ‘climate policy is regressive’. Drabble et al. (2024, p.17) also briefly reflected on these considerations in their reference to ‘assessment of disproportionate benefits’. Most stakeholders engaged in this project and the evidence reviewed did not focus explicitly on issues of historical, international, intergenerational and intragenerational responsibility, often captured by the term ‘climate justice’ (e.g., Roser and Seidel, 2016). Overall, issues of distribution and responsibility are underexplored within a policy context in relation to JT and invite closer attention.
  • Intersections between food production systems, stakeholder power, food security, ecosystem and human health, and land use change: Interviews with NatureScot and the Scottish Crofting Federation pointed to the intersections between food production systems, power hierarchies and land use change in the transition to net zero. Concerns were also related to issues of food security, resilience and health. These insights invite further attention into how net zero and climate adaptation actions interact, if at all, with food production, food security and land use, and the risks and opportunities from the perspective of ensuring a JT.
  • Intersections between land prices, housing prices and availability and land use change in rural areas: The relevance of land ownership has been highlighted throughout, particularly in relation to distributional justice and access to net zero opportunities. The Scottish Crofting Federation also highlighted issues of land prices, housing prices and the ways in which land use change can affect these, particularly in rural and island areas. This may be directly affected by net zero and climate adaptation developments. In other cases, this may be adjacent to the transition underway and part of broader trends. Improved understanding of how land and house prices interact with the transition will support improved assessment of a JT.
  • Implications of human/nature relationships for the planetary crises and JT: There is growing attention to human-and-nature relationships from the perspective of justice, climate change, the energy transition and JT (e.g., Tafon et al. 2023; van Vugt et al. 2025; Tschakert et al. 2020; Stanley et al. 2025). This relates to beliefs, values and ethical systems, similarly to issues of justice (e.g., van Uffelen et al. 2024; Roser and Seidel, 2016). NatureScot interviewees emphasised the importance of assessing the JT within the current, exploitative relationship with nature (in industrial contexts) and its underlying causes. Disconnection from and domination over nature has also been recognised by the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) as an underlying cause of biodiversity loss and nature’s decline (IPBES, 2025, p. 28 Figure SPM.1). In the workshop, indicator discussions for the ‘Environment and Biodiversity’ outcome highlighted diverse perspectives on the role of ‘nature’ within a JT. This included questions about the ways in which the climate and biodiversity crises (also known as the twin-crises) are interlinked; and the implications of this for a JT in Scotland. Overall, the space for nature within understandings of a JT and within JT policy in Scotland is unclear and would benefit from further attention.

Framework structure, design and development

The proposed framework is broadly structured according to a linear logic: outcomes inform the development of indicators which in turn, serve to assess progress towards the outcome. This enables targeted consideration of key areas of concern, along with an opportunity to monitor a suite of indicators providing detail into specific outcomes. At the same time, a linear approach clusters and to some extent, siloes areas and indicators. Indicators captured under ‘People and Equity’ or ‘Environment and Biodiversity’ may also be relevant to monitor progress towards ‘Communities and Places’, for example, but are not easily interconnected in the framework. In contrast to outcomes, a cross-outcome use of indicators is proposed for hotspot monitoring. An example of a cross-cutting indicator approach to M&E is the National Wellbeing Framework for Wales, in which each indicator is relevant to more than one outcome (Welsh Government, 2022b).

Secondly, this framework is designed with in-built stakeholder engagement and qualitative analysis as two fundamental tools for its effective use and delivery. Qualitative approaches are often deemed resource intensive and challenging to implement in practice. Their effectiveness also depends on diverse stakeholders with their own interests and agendas. Emphasis on the role of qualitative approaches also partially moves away from many M&E frameworks that focus predominantly on monitoring quantitative indicator trends over time. Innovation into policy tools and approaches to engage in this feasibly and effectively is a recommendation for the Scottish Government going forward.

Constrained resources for this project resulted in the prioritisation of conceptualisation, outcome and indicator development for monitoring, with less attention to mechanism identification and evaluation proposals. The mechanisms are a key dimension of a full ToC and are important to support evaluation of why a JT is happening, and what actions have driven change (e.g., Drabble et al. 2024, p.42). They allow for “a deeper understanding of what is necessary, and what must be avoided for a ToC to successfully achieve its impact” (Dhillon and Vaca, 2018, p.70). It is recommended that the Scottish Government elaborate on the mechanisms presented by Drabble et al. (2024) to subsequently explore effective and feasible ways for mechanism monitoring. This will also enable more comprehensive evaluations of JT progress.

Finally, the framework has not been ‘tested’ in practice. While indicators have been researched, identified and in some cases, developed, a baseline of data collection has not been undertaken. This report recommends that the Scottish Government collate data across outcome indicators alongside example hotspots such as Aberdeen City or the Shetland Islands. In doing so, it is anticipated that some indicators may evolve, others may be removed and new ones added. This will enable refining of the outcomes and hotspots approach.

Reflections on the temporal nature of (just) transitions

The net zero and climate adaptation transitions, alongside climate change impacts themselves, are by nature fluid, uncertain, and spread over time. Plans such as SNAP3 (2024) and the CCP (2026) set out long term goals to 2045, in keeping with Scotland’s target to reach net zero emissions. This is also reflected in Drabble et al.’s (2024) conceptualisation of a JT ToC for Scotland.

The groups and locations vulnerable to climate change impacts and affected by transition risks and opportunities will change over time. In the case of hotspots, new locations will become focal sites of transition over the next 20 years. The long-term, live and uncertain nature of the transition has implications for any effort towards JT M&E. This requires that the framework be kept live as new issues emerge and new data becomes available. In addition, identifying and defining when sites of transition become hotspots and when their transitions ‘start’ and ‘end’, will be an important consideration for the effective implementation of this framework.

It is recommended that places identified as ‘hotspots’ with known imminent transitions (such as the closure of the Mossmorran chemical plant in Fife (e.g., BBC, 2026)) or those with transitions already underway are monitored as early on as possible. In the case of anticipated hotspots, this becomes a more challenging question relating to pre-empting transitions and the implications of doing so, given that there is no clear cut, pre-determined list of sites of decline or opportunity. Further research into anticipatory policymaking, risk mitigation and future-facing M&E could inform decision-making in this arena.

Reflections on defining the scope of JT

It is also worth reflecting on learnings from this project’s efforts to develop an M&E framework for a JT. Understandings of a JT vary widely. For the development of this M&E framework, this project has understood a JT to be the just-ness of the process and outcomes of the transition in response to climate change through ‘net zero’ and ‘climate adaptation’ in Scotland. Even within these boundaries, issues of JT concern are wide-ranging and incredibly complex. They are also not always comfortably attributable to climate change impacts nor transition actions alone. Instead, they are interwoven with broader local, national and global political, economic and ecological networks, changes and shocks.

The value of tools such as M&E frameworks for a JT should be understood in the messy context of delimiting the scope of JT. Although M&E frameworks will struggle to capture every single aspect and lived experience relating to a JT, they can inform policymaker and societal understanding. They can provide insight into the ways in which the net zero transition and climate adaptation are unfolding and their just-ness. They can also inform interventions and importantly, hold actors in roles of influence and responsibility to account, including the Scottish Government.

Conclusion and recommendations

This project has developed an M&E framework for a JT to a net zero and climate resilient Scotland. The proposed framework supports monitoring of a JT for Scotland as a whole, while integrating attention to specific regions, places and to vulnerable and affected groups. The body of this framework is made up of quantitative indicators alongside recommendations for the development of qualitative indicators. It also integrates qualitative engagement, analysis and interpretation as necessary tools for effective JT M&E.

The proposed framework also builds in a place-based, hotspots monitoring approach. This recognises that specific places will be directly and significantly affected by processes of industrial change and net zero developments. Through the development of the hotspots approach, this framework also presents the future-facing potential of M&E in a JT context, to anticipate and inform transitions towards more just outcomes while mitigating risks (e.g., Santos Ayllón et al. 2025).

This framework is developed within severe constraints on data availability. It offers a step forward towards what is pragmatically possible now. The Scottish Government should keep the framework live and adaptable as the transition unfolds.

The next step is to test the proposed approach through data collection across outcome and hotspot indicators. This will assess how well the framework can be used in practice and its ability to capture JT concerns. In parallel, this report recommends that the Scottish Government develop a set of mechanisms and their monitoring along with approaches to JT evaluation. The identification and development of qualitative engagement tools and analytical approaches for risk mitigation, indicator interpretation and JT evaluation is also encouraged.

Based on stakeholder input and learnings throughout this project, the report closes with a set of key recommendations to Scottish Government for effective M&E of a JT in Scotland:

  • Start now: The urgency of understanding transition impacts is clearly felt by stakeholders and within government. The inclusion of JT indicators within the CCP (2026) recognises the centrality of a JT to climate action. In this vein, the Scottish Government should begin to systematically monitor, evaluate and report on progress towards a JT. Implementation of existing (albeit imperfect) frameworks and iterative learning is the next step.
  • Data collation and sharing avenues within and beyond government: Data collection and collation in databases, dashboards and reports is underway across teams and directorates in Scottish Government. There is an opportunity to develop cross-team mechanisms to collect and collate this data. There is also an opportunity to put the necessary infrastructure in place for data sharing by non-governmental actors (and to require this, where relevant) with the Scottish Government, to begin to fill data gaps.
  • Fill key data gaps with new data collection: Arguably, one of the most pressing data gaps relates to experiences and outcomes of the transitioning workforce in high-emitting sectors. Additional data gaps which require further research from a JT perspective include (i) land use change from natural capital projects, (ii) business vulnerability to climate change and net zero transitions, and (iii) vulnerability to climate impacts and access to adaptation solutions.
  • Governance, responsibilities and policy responsiveness: M&E frameworks in other areas of government (such as for SNAP3 (2024) or the Biodiversity Strategy (2024)) have developed governance structures for M&E delivery. It is recommended that the Scottish Government explore questions of JT governance and responsibility, including for JT M&E. This may increase attention and accountability of JT delivery. Relatedly, attention to what bounds JT interventions from a Scottish policy perspective can also support efforts towards governance and attribution analyses, alongside mechanism identification.
  • Trial anticipatory approaches to JT M&E: The Scottish Government can use M&E to support proactive JT planning in ways which mitigate risks and pursue opportunities for more just outcomes, particularly in place-specific contexts. The Scottish Government should also identify available tools for policy responsiveness to insights from anticipatory analyses and JT M&E across outcomes and hotspots more broadly.
  • Investigate qualitative tools and approaches for M&E: Despite the widespread use of quantitative data for M&E, this project has highlighted the key role of regular stakeholder input, qualitative data and analyses for effective JT M&E. Further development of qualitative engagement tools and analytical approaches is a key recommendation both for indicator monitoring, interpretation and JT evaluation. The implementation of a qualitative-strong JT M&E approach will also require the development and use of strategic analysis capabilities to interpret and evaluate progress towards a JT.
  • Use M&E to communicate about the JT and about the transition more broadly: There is value in using JT M&E as a tool for improved communication about climate change, climate action and the impacts of net zero and adaptation. This gains relevance in a political context that is shifting towards anti-climate change and net zero narratives. Monitoring JT indicators and communicating these in relation to net zero and climate adaptation (through dashboards, reports or other tools) is identified as a key avenue for dissemination.
  • Identify tools for data management and communication: The breadth and multi-dimensional nature of JT invite the development of digital visualisation tools. These might include websites or dashboards for ease of monitoring, reporting and broader communication purposes. It is also possible to use programmes like Excel to organise data and begin monitoring. This will enable framework implementation in the short-term with readily available tools. It is recommended that transparent internal and external reporting is prioritised.

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Appendices

  1. Methods – Stakeholder engagement

The following tables detail (1) engagement with external (non-core Scottish Government) stakeholders through semi-structured and unstructured interviews and informal exchanges; (2) a list of workshop participants and (3) a descriptive list of areas across government that have engaged with and supported this work. Varying levels of detail on stakeholders reflect participant consents.

External stakeholders and public bodies

Method

NatureScot

Semi-structured interview

Poverty Alliance

Semi-structured interview

Scottish Trade Union Congress (STUC)

Semi-structured interview

Scottish Crofting Federation

Semi-structured interview

Community Land Scotland (shared project with Scottish Land Commission)

Unstructured interview

Just Transition Commission Secretariat

Unstructured interview

PhD researcher – qualitative framework development

Unstructured interview

Regional Inshore Fisheries Group

Unstructured interview

Sustainability impact consultant

Unstructured interview

Sustainability impact consultant

Unstructured interview

Scottish Climate Intelligence Service

Meeting and email exchange

Skills Development Scotland

Meeting and email exchange

Public Health Scotland

Meetings and written feedback

Academia – Just Transition M&E researchers

Meeting

IUCN UK Peatland Programme

Email exchanges

Scottish Environmental Protection Agency

Email exchanges

Table 1 (Appendix A): External stakeholder engagement list (by method and in alphabetical order)

Role

Organisation (in alphabetical order)

Environmental Projects Coordinator

CEMVO Scotland

ClimateXChange project lead

ClimateXChange

Culture/SHIFT programme manager

Culture for Climate Scotland

Director of Curriculum for STEM and Construction

Forth Valley College

Researcher

Heriot-Watt University

Just Transition Commissioner, Scotland Director for Business in the Community

Just Transition Commission

Secretary

Just Transition Partnership

Just Transition Communities Project Manager (Project & Practice Lead)

NESCAN – Just Transition Communities Project

Information Consultant, Climate Analyst Team

Public Health Scotland

Principal Information Analyst, Climate Analyst Team

Public Health Scotland

Strategy Lead, Just Transition Unit

Scottish Government

Head of Net Zero Economy and Carbon Markets

Scottish Government

Senior Manager, Sustainability, SSEN Transmission; and member, Climate Emergency Response Group

SSEN Transmission; Climate Emergency Response Group

Coordinator, Aberdeen Just Transitions Lab

University of Aberdeen

Operations Coordinator

2050 Climate Group

Organisation

Workshop facilitator

University of Edinburgh

Research Fellow (Lara Santos Ayllón)

University of Edinburgh

Academic Project Lead (Kirsten Jenkins)

Scottish Government (Climate Change Analysis Unit)

Project representative (Emily Creamer)

Scottish Government (Just Transition Unit)

Project representative (Abi Whitefield-Stevens)

Table 2 (Appendix A): Workshop participants (17 November 2025)

Scottish government focus areas

Agricultural reform research, monitoring and evaluation

City and Region Growth Deals

Climate adaptation policy

Climate adaptation research

Community climate action

Energy transition

Fair Work Convention Secretariat

Flood resistance policy

Geospatial Analysis

Heat research and analysis

Industry Statistics

Inshore fisheries

Just Transition Unit

Land use strategy

Marine climate change and biodiversity policy

National Performance Framework

Natural capital markets policy

Offshore wind policy – fisheries coexistence

Peatland restoration delivery

Poverty and deprivation

Regional Partnerships

Rural and Environment Science and Analytical Services (RESAS) – Environmental Analysis Unit

Rural and Environment Science and Analytical Services (RESAS) – Rural communities research

Scottish Forestry – woodland creation

Transport Statistics

Table 3 (Appendix A): Scottish Government areas (in alphabetical order)

  1. Evidence review: JT M&E terminology

The following table provides an overview of key Scottish Government JT policies and JT M&E publications by the JTC. It illustrates areas of overlap and difference in the use of M&E terminology and categorisation.

Key JT policy/ reports

Owner

Four themes

Additional terminology/ categorisation used

National Just Transition Planning Framework

Scottish Government (2021)

N/A

Themes, outcomes

Draft Energy Strategy and Just Transition Plan

Scottish Government (2023)

X

Guiding principles, outcomes

Draft Transport Just Transition Plan

Scottish Government (2025)

X

Outcomes, bespoke stakeholder groups, action timeframes

Draft Land Use and Agriculture Just Transition Plan

Scottish Government (2025)

X

Outcomes, themes, objectives

Grangemouth Industrial Just Transition Plan

Scottish Government (2025)

X

Pillars, outcomes, levers

Measuring and Evaluating Success in the Scottish Just Transition

Drabble et al. (2024) (JTC)

X

Outcome clusters, proxy outcomes, ultimate aims, mechanisms, original outcomes

Assessing the low carbon transition at Grangemouth: A case study for measuring fairness

Jenkins et al. (2025) (JTC)

X

Outcome clusters, proxy outcomes, ultimate aims, mechanisms

Table 1 (Appendix B): Overview of key JT policies and M&E framework terminology and categorisation approaches

  1. Outcome Indicators – Quality assessment

This appendix provides a summary of each indicator, including target population, desired trend, data source and timeframe. It also provides a data quality assessment based on three key criteria: relevance, representativeness and data availability. These criteria were selected from SNAP3 (Scottish Government, 2024a) as the most relevant for this project. Each is categorised according to assessed indicator quality. They are colour coded red for low quality, amber for moderate quality and green for high quality. This is aligned with the approach in used in the SNAP3 M&E framework (2024a, p.35) and in the CCP (2026) (Scottish Government, 2026e). Table 1 below describes each quality assessment criterion and its rating. The table is amended from the CCP (2026).

Criterion

Description

Low

Moderate

High

Relevance

The indicator should relate clearly to the emissions source, climate resilience or just transition outcome it is designed to monitor

Minimal or indirect relationship to emissions reductions, climate adaptation or just transition

Some relationship to emissions reduction, climate adaptation or just transition but indirect or partial

Clear and direct relationship to the emissions pathway, climate adaptation or just transition outcome

Representativeness

The indicator should be directly relevant to key dimensions of the just transition outcome it is designed to monitor

The indicator doesn’t capture the key drivers of the expected emissions reduction, climate adaptation or just transition outcome

Represents some important drivers but not the full picture

Represents the key drivers of just transition, emissions change or climate adaptation

Data availability

Data should be regularly published, accessible and sufficiently robust

Data unavailable, restricted, irregular or highly uncertain

Data available but with limitations (lag, infrequent updates, quality caveats)

Data regularly published, accessible, and statistically robust

Table 1 (Appendix C): Criteria used to evaluate indicators (amended from the CCP (2026) (Scottish Government, 2026e).

Communities and Places 

CP1: Proportion of people in Scotland reporting satisfaction with opportunities to influence (i) the Scottish Government’s approach to delivering net zero, and (ii) local policy and planning decisions relating to net zero

Indicator information:

  • Target population(s): (i) Scotland-wide and (ii) by demographic groups in People and Equity (the same assessment applies)
  • Data source: Scottish Climate Survey (proposed addition from autumn 2026)
  • Desired trend: Increasing
  • Timeframe: Annual

CP1: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given it focuses directly on participation and policymaking in relation to net zero, which is key to a JT.

Representativeness

Moderate

This indicator is rated moderate for representativeness given its direct relevance to JT concerns through a focus on participation and influence over net zero policymaking at national and local scales. Breakdown by demographic groups also reflects considerations of recognition and existing socio-economic inequities in relation to participation opportunities. It does not provide insight into the felt experiences of participation opportunities, and interpretations and experiences of influencing policy may vary across survey respondents.

Data availability

Moderate

This indicator is rated moderate for data availability given that it depends on the annual commissioning of the Scottish Climate Survey.

CP2: Proportion of people in Scotland reporting satisfaction with opportunities to influence net zero and climate adaptation developments happening in their local area.

Indicator information:

  • Target population(s): (i) Scotland-wide and (ii) by demographic groups in People and Equity (the same assessment applies)
  • Data source: Scottish Climate Survey (proposed addition from autumn 2026)
  • Desired trend: Increasing
  • Timeframe: Annual

CP2: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given its direct focus on engagement and influence over net zero and climate adaptation developments.

Representativeness

Moderate

This indicator is rated moderate for representativeness of JT concerns given its direct attention to issues of participation and influence over net zero and climate adaptation projects at local scales. Breakdown by demographic groups also reflects considerations of recognition and existing socio-economic inequities in relation to participation opportunities. It does not provide insight into the felt experiences of project engagement processes (e.g., consultations) and could underrepresent harder to reach populations, who are also often underrepresented in formal engagement processes.

Data availability

Moderate

This indicator is rated moderate for data availability given that it depends on the annual commissioning of the Scottish Climate Survey.

CP3: Number of community groups involved in climate action/sustainability activities, as recorded by the Climate Action Hubs (and case studies)

Indicator information:

  • Target population(s): (i) Scotland-wide and (ii) including qualitative attention to groups across Local Authorities
  • Data source: Climate Action Hubs; qualitative – with community action stakeholders
  • Desired trend: Increasing
  • Timeframe: Annual

CP3: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

High

This indicator is rated high for relevance due to its focus on community-led climate action and sustainability initiatives, which related directly to JT outcomes.

Representativeness

Moderate

This indicator is rated moderate for representativeness of JT concerns. Community-led and grassroots climate action more broadly are strongly associated to community empowerment and participation in the transition, both key dimensions of JT. Climate Action Hubs data is not representative of all community-led climate action across Scotland and may also include sustainability initiatives not directly related to net zero or climate adaptation. Engagement with the Climate Action Hub team can provide additional qualitative nuance, including insight into where community-led action is/ is not taking place and why, capturing considerations of spatial justice. Engagement with broader sectoral stakeholders can complement this indicator to provide a broader view of activity in Scotland.

Data availability

High

This indicator is rated high for data availability given that membership data is already collected by the Climate Action Hubs.

CP4: Geographical coverage of regional adaptation collaborations [once full coverage, updates on implementation]

Indicator information:

  • Target population(s): (i) Scotland-wide and (ii) by Local Authorities not covered by adaptation partnerships
  • Data source: Adaptation Scotland
  • Desired trend: Increasing
  • Timeframe: Annual

CP4: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

High

This indicator is rated high for relevance due to its direct focus on climate adaptation and on partnership working for climate action.

Representativeness

Moderate

This indicator is rated moderate for representativeness of JT concerns. Cross-institutional and cross-stakeholder partnership working has been identified as a key feature of JT. From an adaptation perspective, it captures a range of collaborations and their regional coverage. However, the data records Adaptation Scotland partnerships and may not capture all adaptation activity and collaborations within a region.

Data availability

Moderate

This indicator is rated moderate for data availability given that data is collected directly from Adaptation Scotland. The data will not reflect all adaptation collaborations in Scotland.

CP5: The proportion of people reporting that changes to their local place due to net zero infrastructure and/or land use change have maintained or improved the quality of their local area.

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: Scottish Climate Survey (proposed addition from autumn 2026)
  • Desired trend: Increasing
  • Timeframe: Annual

CP5: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

High

This indicator is rated high for relevance due to its direct focus on the impacts of net zero infrastructure and land use change.

Representativeness

Moderate

This indicator is rated moderate for representativeness of JT concerns. It puts the focus on the local perceptions and implications of net zero developments to capture distributional issues of benefit and harm from net zero developments. The focus on ‘quality of their local area’ may be interpreted differently by respondents. It may also obscure issues relating to the processes by which developments happened.

Data availability

Moderate

This indicator is rated moderate for data availability given that it depends on the annual commissioning of the Scottish Climate Survey.

CP6: Area of community owned assets (in hectares)

Indicator information:

CP6: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

Moderate

This indicator is rated moderate for relevance given that land ownership directly affects community participation in the transition. However, it does not directly focus on community ownership of assets relating to net zero or climate resilience.

Representativeness

Moderate

This indicator is rated moderate for representativeness of JT concerns. Ownership and control over land enables direct access for communities to net zero opportunities, decision-making and benefits distribution. However, this indicator does not reflect the uses of community owned land nor the related impacts on stakeholders dependent on the land.

Data availability

High

This indicator is rated high for data availability given that it is regularly collected by Scottish Government.

CP7: Operational capacity of community and locally owned energy installations in Scotland. Include breakdown (i) by type of ownership (ii) by location and (iii) as a proportion of total renewable energy installed (that year/ overall).

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: Energy Saving Trust
  • Desired trend: Increasing
  • Timeframe: Annual

CP7: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given that the monetary and non-monetary benefits of community owned energy are well known and directly relate to JT outcomes and net zero.

Representativeness

Moderate

This indicator is rated moderate for representativeness because it captures the megawatts of installed capacity but does not provide evidence of the benefit of this to communities. It does not reflect differences in who can and cannot become involved in community ownership initiatives and thus is not representative of socio-economic inequalities. Data breakdowns by type of ownership, by location and as a proportion of total renewable energy installed can provide a more nuanced understanding in this direction. Stakeholder engagement with representative organisations could provide qualitative insight in relation to involved groups and complement this data.

Data availability

Moderate

Data are published on an annual basis as part of Energy Saving Trust ‘Community and Locally Owned Energy in Scotland’ report. The register is not compulsory so may not capture all projects.

CP8: Average value of community benefits committed from renewable energy projects commissioned in the last 36 months, where a community or developer form is attached to a project.

Indicator information:

CP8: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given the focus on community benefits from renewable energy as a net zero development.

Representativeness

Moderate

This indicator is rated moderate for representativeness of JT concerns. Community benefits payments are a recognised vehicle to distribute benefit locally and increase community wealth in response to implications of renewable energy developments (including, for example, landscape change, noise and economic opportunities). The indicator does not show the distribution of these benefits across Scotland nor within communities, nor how the funds are used.

Data availability

Moderate

This indicator is rated moderate for data availability given that data is regularly collected by Local Energy Scotland. It is provided by developers, project owners and fund administrators on a voluntary basis, so the data may be incomplete.

CP9: Engagement experiences of the fishing sector with offshore energy developments

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: Data not available. Recommended data collection: qualitative engagement with key stakeholder groups e.g., Regional Inshore Fisheries Group and existing forums.
  • Desired trend: Monitor, improving
  • Timeframe: Annual

CP9: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given the expected impact of planned offshore energy developments (wind, tidal, wave) as part of the net zero transition.

Representativeness

Moderate

This indicator is rated moderate for representativeness of JT concerns. Offshore energy developments create a recognised net zero pressure on the distribution of marine space. The fishing sector is facing cumulative pressures in part, because of the net zero transition. This indicator recommends qualitative engagement with sectoral stakeholders to understand transition dynamics between the offshore energy and fishing sector. This data will not be representative of experiences with every development underway in Scotland and may be highly variable.

Data availability

Low

This indicator is rated low for data availability as this data is not currently collected. Stakeholder networks involving the Scottish Government through which to begin to collect this data are available.

CP10: Distribution of marine space across activities, including % available for fishing

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: Data not available in monitorable format. Data available and regularly updated in map format by the Marine Directorate (NMPi)
  • Desired trend: Monitor, qualitative
  • Timeframe: Annual

CP10: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given the scale of potential offshore energy developments (wind, tidal, wave) as part of the net zero transition.

Representativeness

High

This indicator is rated high for representativeness of JT concerns. Offshore energy developments are a clear net zero pressure on the use of marine space. The fishing sector is facing cumulative pressures, in part because of the net zero transition. Monitoring available marine space for fishing over time (and where possible, in relation to developing offshore energy projects and related installations e.g., subsea cables) can support distributional justice analyses across energy and fishing stakeholders and provide insight into transition dynamics.

Data availability

Low

This indicator is rated low for data availability as this data is not currently collected in a monitorable format. The data exists and is regularly updated in an online map format by the Scottish Government Marine Directorate.

CP11: Number of woodland creation projects registered with the Woodland Carbon Code (WCC) and peatland restoration projects registered with the Peatland Code (PC) owned by community groups and small landholdings; and as a % of total registered projects.

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: Data not currently available. Projects registered with the WCC and PC are visible on their public registers (WCC registry, PCC registry), including details of ownership. Additional analysis may enable identification of community and small landholdings projects. Can collect case study data through qualitative engagement with (e.g., Scottish Forestry, Peatland Action, Community Land Scotland).
  • Desired trend: Monitor, increasing
  • Timeframe: Annual

CP11: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given the direct focus on natural capital projects developed for carbon offsetting for net zero.

Representativeness

Moderate

This indicator is rated moderate for representativeness of JT concerns. Community and small landholding involvement in carbon offsetting projects reflects opportunities for smaller scale participation in carbon offsetting projects as a net zero opportunity. Delimiting ‘natural capital’ and carbon offsetting projects is challenging, and not all projects such projects will be registered with the WCC and PC. This indicator does not capture the impacts of these projects.

Data availability

Low

This indicator is rated low for data availability as this data is not currently collected. Data exists on public WCC and PC registries. Specific community and small landholding data may be accessible through further analysis.

CP12: Socio-economic benefits from woodland creation and peatland restoration

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: Qualitative engagement with key stakeholder groups e.g., Community Land Scotland, Scottish Forestry, Peatland Action, Scottish Land Commission, and with projects under development. The WCC has a benefits self-reporting tool from which data may also be available for the Scottish Government.
  • Desired trend: Increasing
  • Timeframe: Annual

CP12: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given the direct focus on the type and distribution of benefits from woodland creation and peatland restoration, both of which support net zero and climate resilience.

Representativeness

Moderate

This indicator is rated moderate for representativeness of JT concerns. Woodland creation and peatland restoration will create diverse socio-economic benefits and their localised impacts across communities in Scotland directly affects distributional and procedural JT considerations. Defining and quantifying socio-economic benefits from natural capital projects (which are often not monetary benefits) is challenging. Qualitative data collection will support increasing understanding of these projects, their development processes and impacts.

Data availability

Low

This indicator is rated low for data availability as this data is not currently collected. Potential stakeholders for qualitative data collection have been identified and have existing networks with the Scottish Government.

People and Equity

Indicators PE1 and PE2 are covered by the quality assessment in Communities and Places and are not repeated below.

PE3: Percentage of dwellings in Fuel Poverty

Indicator information:

  • Target population(s): (i) Scotland-wide, (ii) 6-fold rural/urban classification and (iii) Island local authorities
  • Data source: Scottish House Condition Survey (in Scottish Household Survey)
  • Desired trend: Towards the attainment of statutory targets
  • Timeframe: Annual (Local authority data availably every 3 years)

PE3: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given that fuel poverty is an existing, systemic injustice related to access and affordability of energy, a key sector in the transition to net zero.

Representativeness

Moderate

This indicator is rated moderate for representativeness given the strong spatial dimension of fuel poverty in Scotland, where it is strongly characterised by its geographical distribution. Data by local authorities is only available every three years, however; and the indicator does not distinguish between fuel poverty and extreme fuel poverty, nor reflects the lived experiences of different households.

Data availability

High

This indicator is rated high for data availability given that data is published annually as accredited official statistics.

PE4: Housing with EPC C or above across housing/tenure types

Indicator information:

  • Target population(s): (i) Scotland-wide, (ii) 6-fold rural/urban classification and (iii) Island local authorities
  • Data source: Scottish House Condition Survey
  • Desired trend: Increasing
  • Timeframe: Annual

PE4: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given that increasing energy efficiency is a key vehicle for net zero, climate resilience, and addressing fuel poverty.

Representativeness

High

This indicator is rated high for representativeness given that access to energy efficiency and retrofit solutions is often costly, challenging and is a key avenue to decrease poverty alongside emissions reductions. Inequalities of access to retrofit and efficiency solutions are spread across housing and tenure types, which will also be captured by this indicator. In Scotland, energy efficiency inequalities are also spatially distributed across geographies.

Data availability

High

This indicator is rated high for data availability given this data is collected annually in the Scottish House Condition Survey.

PE5: Percentage of people reporting that they can afford their individual transport costs

Indicator information:

  • Target population(s): (i) Scotland-wide, (ii) 6-fold rural/urban classification, (iii) island local authorities and (iv) people with different levels of household income.
  • Data source: Scottish Household Survey (SHS)
  • Desired trend: Increasing
  • Timeframe: Annual

PE5: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given that transport affordability is a key concern relating to the transition to net zero.

Representativeness

Moderate

This indicator is rated moderate for representativeness given that it directly asks about issues of affordability and can monitor these across Scotland’s geographies (in which transport needs vary) and with attention to low levels of income. The indicator is based on a reported sense of affordability and could be impacted by various factors other than the net zero transition. Over time, however, as the transition to net zero unfolds, transport should not become unaffordable.

Data availability

High

This indicator is rated high for data availability given this data is collected annually through the Scottish Household Survey.

PE6: Number of people reporting they do not use public transport (buses) due to connectivity issues

Indicator information:

  • Target population(s): (i) Scotland-wide, (ii) 6-fold rural/urban classification, and (iii) island local authorities
  • Data source: Scottish Household Survey (SHS)
  • Desired trend: Decreasing
  • Timeframe: Every two years

PE6: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given that transport connectivity is a key dimension of transport poverty which could be impacted by the net zero transition. Public transport is a key avenue for transport emissions reductions and is broadly more affordable transport, in particular by bus.

Representativeness

Moderate

This indicator is rated moderate for representativeness given that it focuses directly on issues of connectivity. Connectivity is a challenging issue to capture due to its overlap with other considerations. This indicator is based on a combined analysis of data to the question of why respondents do not use public transport (SHS). The suggested analysis includes attention to the following responses: lack of service, too infrequent, takes too long, inconvenient, no direct route, unreliable. In addition, analysis should also include the response ‘use my own car’ overlayed with these issues. Geographical breakdowns reflect different transport needs across regions in Scotland.

Data availability

High

This indicator is rated high for data availability given this data is collected annually in the Scottish Household Survey.

PE7: (i) Proportion of adults within 5-minute walk of greenspace

(ii) Extent of green-blue land cover in urban areas

Indicator information:

  • Target population(s): (i) Scotland-wide, (ii) demographic groups, (iii) SIMD 20% most deprived (if data is available)
  • Data source: (i) Scottish Household Survey (ii) Ordnance Survey
  • Desired trend: Increasing over time
  • Timeframe: Annual

PE: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

Moderate

This indicator is rated moderate for relevance given the role of greenspace in emissions reductions and increasing climate resilience, alongside the benefits from greenspace access for individuals. It is also important to monitor whether new net zero developments are reducing greenspace access.

Representativeness

Moderate

This indicator is rated moderate for representativeness given that it does not reflect the quality, safety nor accessibility of greenspace. Increases in greenspace may not be reflected in responses based on the ‘5-minute walking distance’ perimeter. Greenspace access inequities would support JT analyses, but this is subject to data availability e.g., by SIMD percentile.

Data availability

High

This indicator is rated high for data availability given this data is collected annually in the Scottish Household Survey and the Ordnance survey. The two data sources are used in SNAP3 for annual reporting.

PE8: Proportion of people who agree that the transition to net zero and climate resilience will support a more positive future for young people and future generations in Scotland.

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: Scottish Climate Survey (proposed addition from autumn 2026)
  • Desired trend: Increasing over time
  • Timeframe: Annual

PE8: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given that an expansive JT has a strong component of intergenerational justice, that is, protecting the planet today for younger people and the generations of the future. This is an underlying driver of the transition to net zero and climate resilience.

Representativeness

Moderate

This indicator is rated moderate for representativeness given that respondents could have varying understandings of what the transition means, or what a ‘more positive future’ entails.

Data availability

Moderate

This indicator is rated moderate for data availability given that it depends on the annual commissioning of the Scottish Climate Survey.

PE9: Level of adaptation action being taken by people in Scotland

Indicator information:

  • Target population(s): (i) Scotland-wide, (ii) demographic groups, (iii) SIMD 20% most deprived (if data is available)
  • Data source: Scottish Climate Survey
  • Desired trend: Increasing
  • Timeframe: Annual

PE9: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given it directly focuses on ability to engage in climate change adaptation.

Representativeness

Moderate

This indicator is rated moderate for representativeness. The ability to adapt to a changing climate will be impacted by a range of factors, from systemic inequalities through to perceived risk and information and knowledge access. While this indicator captures self-reported data at an individual household level, it does not reflect institutional action to support climate resilience, for example, at local authority level.

Data availability

Moderate

This indicator is rated moderate for data availability given that it depends on the annual commissioning of the Scottish Climate Survey.

PE10: Hospitalisations by heat

Indicator information:

  • Target population(s): (i) Scotland-wide, (ii) demographic groups (age and sex), (iii) SIMD 20% most deprived (if data is available)
  • Data source: Public Health Scotland
  • Desired trend: Decreasing
  • Timeframe: Annual

PE10: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given it directly focuses on the distribution of impacts from climate change.

Representativeness

Moderate

This indicator is rated moderate for representativeness given that it captures a health concern relating to climate change impacts and by attention to affected populations such as older adults. The data is modelled and will not necessarily reflect the increasing adoption of adaptation measures.

Data availability

High

This indicator is rated high for data availability given that the dataset is developed by Public Health Scotland with plans for annual publication and further development.

PE11: Proportion of householders with prior flood claims who can receive quotes from 5 or more insurers

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: Flood-Re
  • Desired trend: Maintaining/increasing
  • Timeframe: Annual

PE11: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given it directly focuses on issues of accessing solutions for climate change resilience and adaptation.

Representativeness

Moderate

This indicator is rated moderate for representativeness given that it reflects availability of flood insurance for readily impacted households, which has already been monitored at 100%. As flooding becomes more frequent in a changing climate, availability of flood insurance could be at risk of decreasing. The indicator does not reflect the affordability of this insurance, who can/cannot access it nor whether it is taken up.

Data availability

High

This indicator is rated high for data availability for the data is collected annually from Flood-Re for SNAP3 M&E.

PE12: Proportion of people living in a flood risk area who report an inability to implement flood risk measures

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: Scottish Climate Survey (proposed addition from autumn 2026)
  • Desired trend: Increasing
  • Timeframe: Annual

PE12: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given it directly focuses on issues of accessing solutions for climate change resilience and adaptation.

Representativeness

Moderate

This indicator is rated moderate for representativeness given that it focuses directly on affected populations by flood risk, and on adaptation capabilities. The implementation of flood resilience at a household level is challenging and very costly. This indicator only focuses on flood risk and does not capture broader risks of climate change and adaptation.

Data availability

Moderate

This indicator is rated moderate for data availability given that it depends on the annual commissioning of the Scottish Climate Survey.

PE13: Premature deaths due to exposure to fine particulate matter (PM2.5) (number of premature deaths)

Indicator information:

  • Target population(s): (i) Scotland-wide, (ii) by SIMD percentile and (iii) by demographic groups
  • Data source: Data not available in indicator format. Discussions with Public Health Scotland suggests feasibility of indicator development.
  • Desired trend: Decreasing
  • Timeframe: Annual

PE13: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given the expected positive implications of net zero for reductions in air pollution and the distributed impacts of current pollution across Scotland.

Representativeness

Moderate

This indicator is rated moderate for representativeness of JT concerns. Reductions in harmful pollutants is a benefit across Scotland. Suggested geographical and demographic breakdowns draw attention to potential inequities in exposure to polluted environments and subsequent health impacts, which should improve in the transition to net zero. The extent to which this is an issue in Scotland is to be determined once data is collected.

Data availability

Low

This indicator is rated low for data availability as this indicator does not currently exist. Advice from Public Health Scotland suggests feasibility of development.

Jobs, Skills and Economic Opportunities

JSEO1: Employment (full-time equivalent) in the Low Carbon and Renewable Energy Economy (LCREE) in Scotland

Indicator information:

JSEO1: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given it is specifically focused on job creation in the net zero, low carbon economy.

Representativeness

Moderate

This indicator is rated moderate for representativeness. The dataset cannot be broken down by geographies, demographic groups nor specific sectors. Capturing who can and cannot access low carbon jobs is thus an important gap in this indicator. The indicator also does not reflect the quality of these jobs. The LCREE data are survey-based estimates based on a sample, and results from sample surveys are always estimates and not precise figures.

Data availability

High

This indicator is rated high for data availability given that it is annually published as official statistics by the Office for National Statistics (ONS).

JSEO2: Total employment in Energy (including in renewables)

Indicator information:

JSEO2: Indicator quality assessment

Criterion

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given the role of the energy sector in Scotland’s economy, and the significance of the energy sector in the move towards net zero.

Representativeness

Moderate

This indicator is rated moderate for representativeness. Monitoring energy employment throughout the transition matters in the Scottish context given expected job losses in fossil fuel energy sectors alongside expected job creation in renewable energy. As a major sector driving activity in the net zero transition in Scotland, this justifies directed attention. If energy employment declines over time, there is reasonable scope to infer that the fossil fuel energy industry employment is not being replaced by growing renewable energy jobs. This indicator does not distinguish between types of energy sectors, occupation nor quality of jobs. It focuses solely on energy and hence on just one part of the net zero economy.

Data availability

High

This indicator is rated high for data availability for the data is annually collected as official statistics by the Scottish Government.

JSEO3: Employment in forestry and marginal employment changes from woodland creation

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: Scottish Forestry
  • Desired trend: Increasing (qualitative, contextualised)
  • Timeframe: Annual

JSEO3: Indicator quality assessment

Criteria

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given the role of land use change activities in net zero and climate resilience.

Representativeness

Moderate

This indicator is rated moderate for representativeness. As the transition unfolds, woodland creation is an economic and emissions reductions opportunity. This indicator captures changes in woodland creation employment, but this is only one of many forms of ‘natural capital’ employment. Not all woodland creation will be for the purposes of net zero or climate adaptation (but all woodland creation will impact emissions).

Data availability

High

This indicator is rated high for data availability given that marginal employment changes are calculated annually by Scottish Forestry. In addition, Scottish Forestry also conduct ad hoc research providing further detail into employment impacts.

JSEO4: Low Carbon and Renewable Energy Economy (LCREE) estimated direct and indirect turnover

Indicator information:

JSEO4: Indicator quality assessment

Criteria

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given its attention to economic turnover in the net zero, low carbon economy.

Representativeness

Moderate

This indicator is rated moderate for representativeness given that it is based on businesses self-reporting activity across a bespoke set of 17 sectors defined by the Office for National Statistics (ONS). LCREE estimates are survey-based and gather information from a sample of businesses rather than the whole population, so are subject to measurable sampling uncertainty.

Data availability

High

This indicator is rated high for data availability given that it is annually published as official statistics by the Office for National Statistics (ONS).

JSEO5: Businesses with 10+ employees with (i) a climate strategy (ii) biodiversity strategy (iii) publishing an annual sustainability report

Indicator information:

JSEO5: Indicator quality assessment

Criteria

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given it provides information about business knowledge, planning and action towards climate change and climate adaptation in a transitioning economy.

Representativeness

Low

This indicator is rated low for representativeness. It reflects self-reported commitments towards actions on climate change and biodiversity by businesses, which implies a level of awareness, responsiveness and adaptation by businesses to a changing climate and economy. The Business Insights and Conditions Survey does not include every sector and reports on businesses of 10+ employees. This excludes smaller businesses including sole traders, who make up the majority of businesses in the Scottish economy (in Businesses in Scotland, Scottish Government, 2025g). The data is self-reported and does not reflect actual adaptation or decarbonisation actions.

Data availability

High

This indicator is rated high for data availability given that it is annually available through the Business Insights and Conditions Survey.

JSEO6: Number of people in Modern Apprenticeships reporting that their apprenticeship is in a ‘net zero or green sector’ (i) 3 months and (ii) 15 months after finishing

Indicator information:

JSEO6: Indicator quality assessment

Criteria

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given the direct focus on net zero or ‘green’ sectors in relation to skills development through apprenticeship training underway.

Representativeness

Low

This indicator is rated low for representativeness. The indicator focus is directly relevant to JT concerns in the transition to net zero. However, apprenticeships are only one of many training and education pathways. The sample size will be too small for the Scottish Government to gain insight into skills development, training and retraining underway in Scotland as a whole. Still, a steady increasing trend of apprenticeships in green sectors, alongside monitoring decreasing inequalities across demographic groups, can be considered a positive trend overall.

Data availability

High

This indicator is rated high for data availability because the data is collected on a rolling basis by Skills Development Scotland.

JSEO7: Trade union membership density in Scotland

Indicator information:

JSEO7: Indicator quality assessment

Criteria

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given the importance of worker representation and participation in decision-making throughout the transition to net zero and climate resilience. Trade union representation and access are core characteristics of the fair work economy, in line with Scottish Government commitments.

Representativeness

Low

This indicator is rated low for representativeness given it focuses on trade union membership density in Scotland as a whole, and not in specific sectors relating to the net zero and climate resilience transition. In addition, trade union membership does not ensure worker participation in transition decision-making. Attention to trade union access would support a more nuanced view.

Data availability

High

This indicator is rated high for data availability as this is annually collected as official statistics by the UK Government.

JSEO8: Proportion (%) of employees earning less than the Real Living Wage

Indicator information:

JSEO8: Indicator quality assessment

Criteria

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given the importance of quality and fair work jobs in the low carbon economy in Scotland. The real living wage is a key characteristic of a fair work economy, in line with Scottish Government commitments.

Representativeness

Moderate

This indicator is rated moderate for representativeness given that it is not broken down by sectors and specifically, net zero and climate adaptation employment. However, it remains representative of a JT given the economy-wide implications of the transition in Scotland, across sectors.

Data availability

High

This indicator is rated high for data availability given it is annually collected by the Office for National Statistics (ONS).

JSEO9: The difference between male and female full-time hourly earnings in the transport sector (SIC H: Transportation and storage)

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: Annual Survey of hours and earnings
  • Desired trend: Gap decreasing
  • Timeframe: Annual

JSEO9: Indicator quality assessment

Criteria

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given the opportunity for increased pay equity in net zero and climate adaptation related sectors (as a key dimension of fair work), including transport. This indicator was identified in the Draft Transport JT Plan (2025).

Representativeness

Moderate

This indicator is rated moderate for representativeness. It does not capture sub-sectoral categories of high emissions and low emissions transport, yet trends should highlight changes in the gender pay gap in transport overall. These can be contextualised within progress towards emissions reductions across sectors.

Data availability

High

This indicator is rated high on data availability for it is annually collected by the Office for National Statistics (ONS).

JSEO10: The difference between male and female full-time hourly earnings in the energy sector (SIC B: Mining and Quarrying; SIC D: Electricity, Gas, steam and air conditioning supply).

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: Annual Survey of hours and earnings
  • Desired trend: Gap decreasing
  • Timeframe: Annual

JSEO10: Indicator quality assessment

Criteria

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given the opportunity for increased pay equity in net zero and climate adaptation related sectors (a key dimension of fair work), including energy.

Representativeness

Moderate

This indicator is rated moderate for representativeness given that current SIC code sectoral breakdowns for energy do not capture the full set of changing and new energy activities as a result of net zero.

Data availability

High

This indicator is rated high for data availability for it is annually collected by the Office for National Statistics (ONS).

JSEO11: The difference between male and female full-time hourly earnings in the construction sector. [SIC F: Construction]

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: Annual Survey of hours and earnings
  • Desired trend: Gap decreasing
  • Timeframe: Annual

JSEO11: Indicator quality assessment

Criteria

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given the opportunity for increased pay equity in net zero and climate adaptation related sectors (a key dimension of fair work), including construction.

Representativeness

High

This indicator is rated high for representativeness given the expected activity in relation to buildings and construction as part of the transition to net zero and climate resilience.

Data availability

High

This indicator is rated high for data availability given that it is annually collected by the Office for National Statistics (ONS).

JSEO12: The difference between male and female full-time hourly earnings in the agriculture sector (SIC A: Agriculture, forestry and fishing)

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: Annual Survey of hours and earnings
  • Desired trend: Gap decreasing
  • Timeframe: Annual

JSEO12: Indicator quality assessment

Criteria

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given the opportunity for increased pay equity in net zero and climate adaptation related sectors (a key dimension of fair work), including in agriculture and land use.

Representativeness

Moderate

This indicator is rated moderate for representativeness given that current Sectoral Industrial Classification (SIC) breakdown does not capture sub-sectoral categories of land use change relating to net zero and climate resilience activities.

Data availability

High

This indicator is rated high on data availability for it is annually collected by the Office for National Statistics (ONS).

JSEO13: (i) Number of renewable energy supply chain businesses in Scotland.

(ii) Proxy: £ value of ScotWind projects committed to Scottish-based suppliers

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: (i) Data not available, (ii) Crown Estate Scotland
  • Desired trend: Increasing
  • Timeframe: Annual

JSEO13: Indicator quality assessment

Criteria

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given that the creation of renewable energy supply chain businesses in Scotland is a key opportunity for distributed benefit from the net zero transition.

Representativeness

Low

This indicator is not currently available. The recommended proxy is rated low for representativeness. ScotWind offshore wind project supply chain commitments do not cover all supply chain activity in Scotland, do not represent all renewable energy activity Scotland, nor do they provide detail on business creation and growth. However, as an important energy development with recognised implications in Scotland, it serves as an interim proxy on whether economic opportunities from renewable energy are distributed across the Scottish economy.

Data availability (proxy)

Moderate

The proxy indicator is rated moderate for data availability given that it is collected by Crown Estate Scotland through developer supply chain commitments.

JSEO14: (i) Business resilience and ability to adapt to climate change and the transition

(ii) Proxy (in the CCP, 2026): Proportion of small businesses in Scotland reporting the level of energy prices as an obstacle.

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: (i) Data not available, (ii) Scotland Small Business Survey
  • Desired trend: Increasing
  • Timeframe: Annual

JSEO14: Indicator quality assessment

Criteria

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given the need to understand to what extent businesses in Scotland are resilient to climate change, and whether they are benefiting from or being negatively impacted by net zero.

Representativeness

Low

This indicator is not available. The proxy indicator focused on small businesses reporting energy costs as an obstacle to their business is rated low for representativeness. A wide range of factors could be affecting energy prices and business success at different points in time, which makes it challenging to trace this back to the net zero transition itself. The potential impact on energy prices is just one of many ways in which small businesses may be affected by the net zero transition.

Data availability (proxy)

High

The proxy indicator is rated high for data availability given that the data is annually collected in the Scotland Small Business Survey.

JSEO15: Number of workers experiencing redundancy in high emitting industries in Scotland receiving support/ reporting that their employers are implementing transition plans for workers

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: Data not available – survey recommended
  • Desired trend: Increasing (and qualitative engagement)
  • Timeframe: Annual

JSEO15: Indicator quality assessment

Criteria

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given the implications of the transition to net zero for high emitting industries and their workforce.

Representativeness

High

This indicator is rated high for representativeness, Managed, supported transitions for workers in high emitting industries is a core pillar of a JT, and the recommended survey should cover workers across high emitting sectors and in a range of occupations.

Data availability

Low

This indicator is rated low for data availability because data is currently non-existent.

JSEO16: High emitting industry worker participation in decisions affecting them

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: Data not available – survey recommended
  • Desired trend: Increasing (and qualitative engagement)
  • Timeframe: Annual

JSEO16: Indicator quality assessment

Criteria

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given the implications of the transition to net zero for high emitting industries and their workforce.

Representativeness

High

This indicator is rated high for representativeness given that managed, supported and negotiated worker transitions driven by participatory processes are key to delivering a JT. The recommended survey should cover workers across high emitting sectors and in a range of occupations.

Data availability

Low

This indicator is rated low for data availability because data is currently non-existent.

JSEO17: Sense of uncertainty/ confidence in the transition amongst workers in high emitting industries

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: Data not available – survey recommended
  • Desired trend: Increasing (and qualitative engagement)
  • Timeframe: Annual

JSEO17: Indicator quality assessment

Criteria

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given the implications of the transition to net zero for high emitting industries and their workforce.

Representativeness

Moderate

This indicator is rated moderate for representativeness. In a context of industrial change, including at times, site closure and redundancies, the sense of uncertainty and confidence in the transition should to some extent, reflect ongoing experiences with the transition and whether assurances and support are in place.

Data availability

Low

This indicator is rated low for data availability because data is currently non-existent.

Environment and Biodiversity

EB1: Emissions of the eight priority Air Quality pollutants (ammonia, carbon monoxide, nitrogen oxides, non-methane volatile organic compounds, particulate matter, sulphur dioxide and lead) for Scotland and by industrial sector

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: National Atmospheric Emissions Inventory
  • Desired trend: Decreasing
  • Timeframe: Annual

EB1: Indicator quality assessment

Dimension

Rating

Explanation

Relevance

Moderate

This indicator is rated moderate for relevance given the expected impact of net zero actions on air pollutants and the implications this has for the future health of people and planet.

Representativeness

Moderate

This indicator is rated moderate for representativeness given that air pollution has direct impacts on health across the population. The breakdown by industrial sector enables a degree of attention to where emissions are falling and which ones remain. However, the indicator does not show disproportionate impacts of air pollution on different groups or places, nor the distribution of responsibility for these emissions. Air quality in the UK is not just affected by emissions included in the National Atmospheric Emissions Inventory but also by secondary formation of air pollutants, emissions originating from outside the UK and geographical and meteorological factors. 

Data availability

High

This indicator is rated high for data availability given it is annually collected by the National Atmospheric Emissions Inventory.

EB2: Improvements to water quality across types in Scotland

Indicator information:

EB2: Indicator quality assessment

Dimension

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given that the transition to net zero should directly see decreases in water quality pollution from across industries (like fossil fuels and agriculture) but could also create risks to water sources (e.g., through wind farm installation). Annex 2 in the Draft CCP (Scottish Government, 2025i) also identified increased flood risk as posing risks to water quality.

Representativeness

Moderate

This indicator is rated moderate for representativeness given that water quality in Scotland is key for healthy populations and ecosystems. However, the indicator does not capture where or by whom the risks and benefits of decreasing/increasing water quality are being felt because of net zero or climate adaptation interventions.

Data availability

High

This indicator is rated high for data availability given it is annually collected by SEPA.

EB3: Scotland’s carbon footprint expressed in million tonnes of carbon dioxide equivalent per year

Indicator information:

EB3: Indicator quality assessment

Dimension

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given the role of embodied emissions in the move towards net zero and the focus of carbon footprint measurements on consumption emissions. Consumption emissions are those associated with the spending of Scottish residents on goods and services, wherever in the world these emissions arise, alongside emissions directly generated by Scottish households through private heating and motoring (Scottish Government, 2025j). This is different to reporting on the greenhouse gas emissions produced within a country’s territory (UK Government, 2026).

Representativeness

Moderate

This indicator is rated moderate for representativeness given the implications of consumption, resource use and embodied emissions for a JT in relation to planetary boundaries. The indicator does not monitor the distribution of harm nor responsibility for Scotland’s carbon footprint. It also cannot reflect why the footprint is increasing/ falling.

Data availability

High

This indicator is rated high for data availability given it is annually collected by the Scottish Government and trend data is available since 1998.

EB4: Global biodiversity impact (Measures the effect of Scotland’s resource use on biodiversity domestically and abroad)

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: Material Flow Accounts
  • Desired trend: Decreasing negative impacts
  • Timeframe: Annual

EB4: Indicator quality assessment

Dimension

Rating

Explanation

Relevance

Moderate

This indicator is rated moderate for relevance given that the net zero transition will have indirect impacts on resource use. The biodiversity crisis is a key planetary boundary with implications for climate resilience more broadly.

 

Representativeness

Moderate

This indicator is rated moderate for representativeness given that the dynamics of resource use, emissions reductions and net zero are uncertain.

Data availability

Low

This indicator is rated low for data availability. The indicator is taken from the Circular Economy Strategy (Scottish Government, 2026d). The Material Flow Accounts data is collected by Zero Waste Scotland, but data for this indicator currently unavailable. Frequency of data collection is currently unknown.

EB5: Soil sealing

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: NatureScot
  • Desired trend: Monitor, qualitative
  • Timeframe: Annual

EB5: Indicator quality assessment

Dimension

Rating

Explanation

Relevance

Moderate

This indicator is rated moderate for relevance given that the negative impacts of soil sealing on soil health can limit the potential benefits of healthy soils relating to water filtration and flood risk mitigation. Net zero developments like wind farms can have direct impacts on levels of soil sealing.

Representativeness

Moderate

This indicator is rated moderate for representativeness given that the indicator does not show where or why soil is being sealed. The trade-offs between impacts on soil health for climate resilience versus the installation of a wind farm, for example, are uncertain. This indicator can be regarded alongside indicator EB6 on regeneration of vacant/derelict urban land.

Data availability

Moderate

This indicator is rated moderate for data availability as data is collected by NatureScot from analysis of Ordnance Survey Mastermap data and NatureScot records of windfarm sites. There is historical data from 2009 to 2020, which was published in 2023.

EB6: Regeneration of vacant / derelict urban land (% of which is regenerated through environmental restoration, for climate adaptation and by net zero initiatives)

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: Scottish Land Commission/SEPA, qualitative engagement with energy developers.
  • Desired trend: Increasing
  • Timeframe: Annual (TBC)

EB6: Indicator quality assessment

Dimension

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given that environmental restoration of vacant and derelict land directly supports JT outcomes and has implications for climate resilience.

 

Representativeness

Moderate

This indicator is rated moderate for representativeness given that the currently available data maps known sites of derelict urban land alongside action being taken. Further analysis is needed to understand what type of site regeneration is underway (e.g., environmental) and whether this is supported by net zero projects. Qualitative case studies and engagement with energy developers on regeneration initiatives may be a useful source of detail on activity underway.

Data availability

Low

This indicator is rated low for data availability. Although data is published by the Scottish Land Commission it is unclear whether it can be accessed and analysed to monitor this indicator.

EB7: Number of hectares of newly protected land and marine features across Scotland

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: NatureScot
  • Desired trend: Increasing
  • Timeframe: Annual

EB7: Indicator quality assessment

Dimension

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given the importance of environmental restoration for JT. Better protected land and marine areas will be more resilient to climate change impacts.

Representativeness

Moderate

This indicator is rated moderate for representativeness given that measures of protection and restoration not covered by this dataset will not be reflected in the indicator.

Data availability

Moderate

This indicator is rated moderate for data availability given that frequency of data updates is still to be decided (as assessed in the SNAP3 M&E framework, (Scottish Government, 2024a, p. 40).

EB8: Carbon and social footprint of materials used for net zero developments in Scotland

Interim proxy: Carbon Intensity of Materials: indicates whether a nation is consuming more sustainable alternatives, independent of trends in overall greenhouse gas impact.

Indicator information:

  • Target population(s): Scotland-wide
  • Data source: Data not available. Developers increasingly conduct project lifecycle assessments for the planning process. This may be a starting point for data collection. Proxy data: Material Flow Accounts
  • Desired trend: Monitor, qualitative
  • Timeframe: Annual

EB8: Indicator quality assessment

Dimension

Rating

Explanation

Relevance

High

This indicator is rated high for relevance given that net zero developments like renewable energy projects will have embodied, social and environmental impacts and emissions. These span from material extraction for technological and project development through to waste once projects are decommissioned.

 

Representativeness

Low

This indicator in unavailable. The proxy indicator is rated low for representativeness given that while it provides an overall picture of trends in the carbon footprint of materials used in Scotland, it cannot distinguish by sectors.

Data availability (proxy)

Low

The proxy indicator is rated low for data availability. The indicator is taken from the Circular Economy Strategy (2026). The Material Flow Accounts data is collected by Zero Waste Scotland, but data for this indicator currently unavailable. Frequency of data collection is currently unknown.

  1. Outcome ‘focus areas’ for indicator development

The following table illustrates the breakdown of the four outcomes into more granular focus areas. These were used as prompts during the workshop held on the 17 November 2025 and in semi-structured interviews, to stimulate discussion about possible indicators.

Theme and Outcome

Potential focus areas for indicators, as directly relates to the process and outcome of net zero and climate adaptation:

Communities and Places

  • Community empowerment, participation and involvement
  • Sense of belonging, identity and place
  • Localised socio-economic benefit

Locally and in relation to Scotland as a whole.

People and Equity

  • Socio-economic inequalities
  • Quality of life (mental and physical health, housing, fuel and transport poverty)
  • Participation inequalities

With particular attention to affected and disadvantaged households and places, from a financial and a spatial lens.

Jobs, Skills and Economic Opportunities

  • Diversified and prosperous economy, including business health
  • Worker transitions and availability and accessibility of fair work jobs
  • Skills and training opportunities
  • Worker participation in transition processes

With particular attention to affected sectors and groups, alongside risks and opportunities for businesses and economic health more broadly.

Environment and biodiversity

  • Nature-positive Scotland
  • Environmental health across land, sea and species

Table 1 (Appendix D): Four JT outcomes and focus areas, prompts for discussion.

  1. ‘No data’ outcome indicators: rationale and recommendations

The four outcomes include indicators for which data is currently not available. These indicators represent key areas of JT concern. Stakeholder engagement and desk-based research have helped to identify possible avenues for further refinement and data collection. These indicators, their relevance for a JT in Scotland and possible avenues for data collection are expanded on below, categorised by outcome.

Communities and Places (indicators CP9-CP12)

CP9: Engagement experiences of the fishing sector with offshore energy developments

The fishing sector is experiencing cumulative pressures in part, because of the energy transition. This includes from marine surveying, subsea cable developments and the installation of offshore wind farms. Fishers face high levels of uncertainty regarding the cumulative impact of developments, both due to varying timelines for different projects and uncertainties around the long-term impacts of offshore energy production on the marine environment. The fishing sector is small in capacity and resource in comparison to large scale offshore wind developers, creating hierarchies of power and influence over decision-making. Often, the just-ness of engagement and decision-making processes depend on each individual developer’s approach. This project has not found quantitative data able to communicate this complexity. The recommendation is for the Scottish Government to monitor a qualitative indicator informed by iterative stakeholder engagement with key fisheries representatives (e.g. Regional Inshore Fisheries Group and others). Various forums involving marine stakeholders and the Scottish Government readily exist and could be a possible avenue for qualitative data collection.

CP10: Distribution of marine space across activities, including % available for fishing

Fishing stakeholders often refer to the experienced ‘spatial squeeze’ by the sector. This refers to the accumulating pressures of new blue economy activities, environmental protection and others and the overlap with – and shrinking of – traditional fishing grounds. Stakeholder insights suggested that potentially relevant indicators like ‘employment in fishing’ will be influenced by too many variables beyond the transition to net zero to be useful for JT M&E. However, monitoring available marine space for fishing over time should be able to increase understandings of ongoing spatial trade-offs in the marine environment, including in direct relation to fishing. The Scottish Government’s Marine Directorate publish an interactive website illustrating the distribution of marine space in Scotland. These visual maps are informed by backend data which could support trend analysis regarding % change in marine space available for fishing over time.

CP11-12: Land use change for net zero and climate resilience: ‘natural capital’ engagement processes, participation and distributed benefits

Research on the types of land use change activities and their implications as part of the transition to net zero and climate resilience illustrated the challenges of defining and monitoring these from a JT perspective. Stakeholders explained the difficulties in setting boundaries around the term ‘natural capital’ and what interventions do/ do not fall into the scope of net zero and climate adaptation efforts. Woodlands may be created for carbon offsetting purposes, for example, for social uses or for other economic productive uses like timber production or tourism; all of which could be considered ‘natural capital’. In addition, many of the benefits from natural capital are considered public goods. In this context, indicators CP11 and CP12 focus on issues of ownership and socio-economic benefits, based on insight from stakeholder discussions and identified avenues to trial data collection. Project ownership will largely be conditioned by land ownership. The benefits and costs of owning woodland creation or peatland restoration as a community will likely differ from those of community owned energy. This suggests the need for continued research in this area. Engagement key stakeholders such as Community Land Scotland and their Natural Capital Community Partnerships project will be important to better understand the implications of these projects from a JT perspective. This can enable qualitative data collection for monitoring alongside refinement of land use change JT indicators.

People and Equity (indicator PE13)

PE13: Premature deaths due to exposure to fine particulate matter (PM2.5)

This indicator draws attention to improved air quality and the health implications of existing pollution levels for Scotland, across different groups and in the most deprived areas. This indicator is available in England (Department of Health and Social Care, n.d.). It reflects distributional justice concerns associated with the unequal distribution of negative impacts from environmental pollution in the current, high carbon economy. This unequal distribution should be addressed throughout the transition to a low carbon one (Farrell, 2012; Shen et al. 2020; Sun et al. 2024). This includes attention both to the geographical distribution of premature deaths by air pollution, to different demographic groups and by levels of deprivation across Scotland. Drabble et al. (2024) included various indicators focused on the spatial distribution of pollution exposure (see p.26, p.28, p.42, p.46). Although this data is not published in this form at present, engagement with Public Health Scotland advised that the development of this indicator would be feasible.

Jobs, Skills and Economic Opportunities (indicators JSEO13 – JSEO17)

JSEO13: Number of renewable energy supply chain businesses in Scotland.

The development of a domestic renewable energy industry has been identified by the Scottish Government as a key economic opportunity from net zero for Scotland (e.g., in the Green Industrial Strategy, Scottish Government, 2024c). The growth of existing supply chain businesses in Scotland and development of new ones as renewable energy is installed would reflect a level of distributed benefit, in contrast with the UK experience with onshore wind in the 20th century (Smith, 2011; Brunt and Spooner, 1998). This indicator is not currently developed. Using UK SIC codes, the Scottish Government could first, identify sectors under which renewable energy supply chain activity would be categorised. It could then monitor business growth and business startups in these sectors, to assess whether there is a developing renewable energy supply chain.

Proxy: £ value of ScotWind projects committed to Scottish-based suppliers

The proxy indicator was identified with support from Scottish Government analysts. It is focused solely on ScotWind, the offshore wind leasing rounds led by Crown Estate Scotland. While offshore wind is not representative of the full renewable energy supply chain, the scale and breadth of expected offshore wind projects justify its use as a proxy (Crown Estate Scotland, n.d.). Developers bidding in ScotWind leasing rounds are required to detail their supply chain spend plans in Scotland. This is a suggested avenue for data collection.

JSEO14: Business resilience and ability to adapt to climate change and the transition

Businesses across Scotland will be affected by climate change and will need to adapt to these changes. They will also be affected by the transition to net zero and may benefit from or be harmed by related impacts. The evidence review alongside stakeholder engagement has highlighted an evidence gap regarding the vulnerabilities, risks and opportunities faced by different business types and scales in Scotland, in the context of climate change and the net zero transition. There are a variety of available, regularly updated data sources about businesses in Scotland (including: the Scottish Annual Business Statistics, Small Business Survey Scotland and Business Insights and Conditions in Scotland, amongst others). While some of these surveys ask businesses about climate change impacts or adaptation measures, this data is currently insufficient to convey business transition, vulnerability, risk and opportunity pathways from a JT perspective.

Proxy: Proportion of small businesses in Scotland reporting the level of energy prices as an obstacle

It is important for the Scottish Government to understand the ways in which energy prices are affecting business success. The proposed framework includes the JT indicator which was included in the CCP (2026) as a proxy. However, business energy costs may be affected by many variables, and is only one of a suite of dimensions reflecting business vulnerability and resilience to climate change and the transition. In addition, engagement with Scottish Government industry analysts suggested there are limited surveys for data collection on sole traders. Sole traders make up over 70% of Scottish businesses (in Businesses in Scotland, Scottish Government, 2025g). This suggests a clear opportunity for targeted data collection on the impacts and experiences of climate change and the transition across business types and scales.

JSEO15-17: Indicators relating to worker transitions

Evidence collected throughout this project has spotlighted the lack of data available/ accessible to understand ongoing industrial transitions and the processes, impacts and experiences of the workforce. Employment and skills development indicators included by Drabble et al. (2024) in their framework already highlighted this data gap, given that data could not be categorised e.g., by specific sectors. The framework proposed by this project includes indicators focused on support and participation experiences alongside a broader sense of uncertainty amongst high emitting industry workers. It recommends the development of a targeted survey alongside qualitative methods to understand what is happening in transitioning industrial sites on the ground. Stakeholders such as STUC recognised the challenges of reaching many workers, particularly those working offshore. Suggested methods include in person surveying in key sites of mobility, such as, for instance, Aberdeen Airport. All three indicators (JSEO15-17) can be supported with qualitative case study and experience data from key stakeholders such as STUC, who are involved in day-to-day experiences on the ground. This new data collection could be complemented with case study data from (i) workers accessing the Oil and Gas Transition Training Fund, (ii) workers experiencing redundancy in Grangemouth accessing skill support, and (iii) any other initiatives by Scottish Government to support managed transitions away from high emitting industries.

Environment and Biodiversity (indicator EB8)

EB8: Carbon and social footprint of materials used for net zero developments in Scotland

This indicator recognises that infrastructure developed for the purposes of net zero will also have social and environmental impacts. These impacts are spread throughout renewable energy technology and projects’ supply chains and lifecycles, from material extraction through to decommissioning and waste. This indicator targets responsible renewable energy developments and addresses procedural risks of greenwashing renewable energy production. Developers are increasingly conducting social and environmental lifecycle assessments as part of their project planning applications. The Scottish Government could explore the extent to which this data is accessible and collatable as a starting point for indicator data collection and monitoring. This data would allow for better understanding of net zero developments in Scotland at local and global scales, including the risks of offshored injustice (e.g., Healy et al. 2019).

  1. JT indicators in Scottish Government policy

This appendix details how this framework relates to existing JT indicators in the CCP (2026), the Grangemouth Industrial JT Plan and draft sectoral JT plans. Detailed attention is awarded to the JT indicators in the CCP (2026) given that it is the first Scottish Government publication to include a set of JT indicators for Scotland within statutory annual reporting.

Climate Change Plan (2026)

The CCP (2026) includes 12 JT indicators. This project developed in parallel to proposals for JT indicators in the Draft CCP (2025). However, this framework’s development process was separate. The proposed framework has parallels with, and at times departs from the JT indicators published in the CCP (2026). Table 1 below presents indicators in the CCP (2026) (Scottish Government, 2026e, p. 14) which are not included in the outcome indicator list in the proposed framework and provides a brief explanation as to why.

JT indicator in CCP

Explanation

Employment rate for people aged 16-64 in five local authorities with high socioeconomic dependence on oil and gas industries: (i) Aberdeen City; (ii) Aberdeenshire; (iii) Falkirk; (iv) Shetland Islands; and (v) Orkney Islands

This is not in the full outcomes list in the JT M&E framework because it is part of the proposed hotspots approach.

Proportion of households reporting that they are managing well financially in three local authorities with a high proportion of employment in oil and gas industries: (i) Aberdeen City, (ii) Aberdeenshire, and (iii) Falkirk

This is not in the full outcomes list in the JT M&E framework because it is part of the proposed hotspots approach.

Number of recipients of the Oil and Gas Transition Training Fund joint Scottish Government and UK Government initiative

This indicator is removed from the proposed M&E framework. It is deemed too specific for a national JT M&E framework. It is more clearly policy-oriented than outcome focused. This indicator could support improved, case specific understanding of the transition in the northeast of Scotland, where the Transition Training Fund is being implemented. It could also support causal evaluations of place-based change alongside the articulation of mechanisms (not included in this report).

Table 1 (Appendix E): JT indicators in the CCP (2026) not amongst the outcome indicators of this JT M&E framework.

Draft sectoral JT plans and the Grangemouth Industrial JT Plan

This project has delivered an M&E framework at a Scotland level and is thus less focused on granular assessment of the JT in the four net zero sectors identified by Scottish Government (energy, transport, agriculture and land use, buildings and construction). Similarly, the indicators in the Grangemouth Industrial JT Plan are directly relevant to the place and site-specific transition underway in the Grangemouth industrial cluster and will not apply to all transitions underway in Scotland as a whole.

The Jobs, Skills and Economic Opportunities outcome in the proposed framework includes fair work indicators. These focus on gender pay gap for energy, agriculture and land use, transport and buildings and construction. This selection was informed by indicators in the Draft Transport JT Plan (2025) and insight from the Fair Work Convention Secretariat. Additional sectoral breakdowns for other indicators in the Jobs, Skills and Economic Opportunities outcome (such as for trade union density/ access, or green jobs) are not possible with currently available data.

Some JT indicators relevant in the Grangemouth industrial cluster context (such as access to greenspace, attention to derelict sites or satisfaction with opportunities to influence decisions) are also reflected in indicators across the four outcomes in the proposed M&E framework. More broadly, draft sectoral JT plans, the Grangemouth Industrial JT Plan and their indicators were reviewed as evidence to inform this framework.

  1. Hotspot indicator list – rationale

H

Indicator (reported on per selected local authority)

Desired trend (contextualised per hotspot)

Data source

Rationale

H1

Employment rate for people aged 16-64 across Scotland

Increasing

ONS

Employment trends in hotspots are a key indicator of the workforce’s activity and mobility, both in places of industrial change/decline and in locations hosting large-scale net zero developments.

H2

Unemployment rate for people aged 16-64 across Scotland

Decreasing

ONS

Unemployment trends provide nuanced insight into changing employment patterns, often reflecting mobility challenges. Combined attention to employment and unemployment is inspired by Shapovalova et al. (2023).

H3

Number of people Not in Employment and Education or Training (16-19)

Decreasing

Skills Development Scotland

This indicator reflects a lack of engagement with available opportunities, by younger generations in sites of transition. An increasing trend draws attention to whether opportunities are available at all. It can highlight concerning transition dynamics in sites of industrial change and in contrast to pre-transition levels.

H4

Number of people in Modern Apprenticeships reporting that (i) their apprenticeship is in ‘green skills’/for the net zero economy’ during, 3-month and 15 months after finishing their apprenticeship and of these, (ii) number of people staying to work in their same Local authority.

Increasing

Skills Development Scotland – Apprentice Voice

Although modern apprenticeships are just one of many education pathways, this indicator will reflect levels of training/retraining opportunities in ‘green skills’ in hotspot locations.

H5

Population change (with attention to in-out migration)

Monitor

Council area profiles – National Records of Scotland (NRS)

Population changes capture multi-dimensional distributional burdens and opportunities in sites of transition over time. For example, this may include: depopulating areas due to industrial closure or large-scale industrialisation for energy production, or inward-migration due to employment creation as a result of transition interventions.

H6

Business activity/ survivability: Business birth and death rates

Monitor, increasing survivability

Scottish Government – Sub-Scotland Economic Statistics Database

Levels of business birth and death are one way to monitor economic activity in a particular area. These data points can serve as an early signal of changing opportunities in a local economy, including highlighting risks of economic decline.

H7

Sectoral economic dependence/diversification:

  1. Sectoral share of GVA (those increasing and in decline)
  2. Employment Share by Sector (Regional Sector Share) (to monitor changing employment across sectors in the local economy; those increasing and in decline).
  3. Location quotients (importance of a sector to a region relative to the national average)

Contextualised within broader economic trends per local authority.

Monitor

Business and innovation statistics – gov.scot

Economic diversification was identified as an objective in the Scottish Government’s National Strategy for Economic Transformation (2022) and was identified by the JTC as a key strategic dimension of a JT (Just Transition Commission, 2024, p. 14).

Sectoral clustering creates innovation and productivity benefits but also increases potential exposure to sector-specific shocks. This indicator supports monitoring of changing economic patterns in hotspots. However, ‘Economic diversification’ does not necessarily demonstrate either resilience or a JT. The Scottish Government should contextualise this indicator within broader economic trends per local area, and the insight from relevant teams and stakeholders.

H8

Proportion of households reporting that they are managing well financially

Increasing

Scottish Household Survey

This indicator provides annual data on felt financial wellbeing by households. It will be particularly relevant to monitor a sense of financial wellbeing on an annual basis in places experiencing industrial change.

H9

Median house price by Local Authority

Monitor

Registers of Scotland

This indicator captures potential knock-on effects on house prices from changing land use in sites of transition. This may include the installation of energy infrastructure or natural capital projects.

H10

People reporting that they can afford their individual transport costs

Increasing

Scottish Household Survey

Through annual data, this indicator provides a frequent update on felt transport costs across households in sites of transition. In the case of net zero developments these are often rural and island areas with complex transport realities.

H11

Proportion of adults within 5-minute walk of greenspace

Increasing

Scottish Household Survey

This indicator monitors greenspace levels in places that will host net zero developments. This includes qualitative attention to reduced greenspace access from these developments (e.g., the Energy Transition Zone using part of St. Fitticks Park in Aberdeen. St Fitticks Park is in Torry, one of the more deprived areas of Aberdeen according to SIMD).

H12

Operational capacity of community and locally owned energy installations in Scotland. Include breakdown (i) by type of ownership (ii) by location and (iii) as a proportion of total renewable energy installed in local area.

Increasing

Energy Saving Trust

This indicator captures the multi-dimensional features of transitions given that sites of industrial change may also see community ownership developments. Hotspots of net zero transitions may see projects developing owned by a variety of different stakeholders. While community owned energy is identified as desirable from a JT perspective in Scotland, monitoring this in a hotspot context also enables qualitative attention to the benefits and potential harms of this type of ownership as well.

H13

Area of community- owned assets (in hectares)

Increasing

Community Ownership in Scotland 2024 – gov.scot

This indicator captures the multi-dimensional features of transitions given that sites of industrial change may also see community ownership developments. Community ownership of assets beyond energy also signals to opportunities to access transition opportunities beyond energy, alongside community wealth building and empowerment more broadly.

H14

Community benefits from energy (and for natural capital projects, once available)

Increasing

Local Energy Scotland community benefits register 

This indicator captures the multi-dimensional features of transitions. Sites of industrial change may also be hosting renewable energy developments making community benefit payments. In net zero development contexts this should increase alongside increasing renewable energy projects. This indicator will not, however, tell the Scottish Government the impact nor local acceptance of these benefits. Engagement with local stakeholders will provide nuanced insight through a JT lens.

H15

Number of hospitalisations due to alcohol use

Decreasing

ScotPHO profiles

This indicator is included as an early warning sign of deprivation in contexts of industrial change. It is taken directly from Shapovalova et al. (2023).

H16

Number of drug use hospitalisations

Decreasing

ScotPHO profiles

This indicator is included as an early warning sign of deprivation in contexts of industrial change. It is taken directly from Shapovalova et al. (2023).

H17

Worker participation in industrial change processes

Increasing

N/A

Worker participation in industrial change processes is core to a JT, and hence directly relevant to hotspots of industrial change. Data is currently unavailable. Data collection through surveys and engagement with stakeholders like STUC is recommended.

H18

Number of premature deaths by particulate matter (PM2.5)

Decreasing

N/A

This indicator is included for both sites of industrial change and net zero developments. Decreasing emissions should decrease pollution in industrial sites, and inhabitants in these places may have also had higher historical exposure to pollutants. Increasing premature deaths by PM2.5 particulate matter in hotspots of net zero developments would be a clear warning sign of unexpected transition developments/ stagnant transitions.

H19

Fuel poverty

Decreasing

Scottish House and Condition Survey

By Local Authority – every 3 years

This indicator monitors fuel poverty, which captures energy inequities affected by a complex array of factors. Fuel poverty could increase in areas experiencing industrial change while exacerbating felt injustices in locations hosting renewable energy production. Its inclusion also reflects the multi-dimensional aspect of transitions given that places potentially seeing negative consequences may simultaneously see e.g., falling levels of fuel poverty.

H20

Proportion of people who agree that the transition to net zero and climate resilience will support a more positive future for young people and future generations in Scotland

Increasing

Scottish Climate Survey (proposed addition from Autumn 2026)

By Local Authority – Every 3 years

This indicator provides high level overview of perceptions of the transition by and for younger people in places directly witnessing transition impacts. This indicator is only available at local authority level every three years.

H21

Proportion of people in Scotland reporting satisfaction with opportunities to influence (i) the Scottish Government’s approach to delivering net zero, and (ii) local policy and planning decisions relating to net zero

Increasing

Scottish Climate Survey (proposed addition from Autumn 2026)

By Local Authority – Every 3 years

This indicator captures the sense of influence over national and local policy relating to the transition. This is a key dimension of the JT for Scotland and directly relevant in places seeing targeted interventions and experiencing change. This indicator is only available at local authority level every three years.

H22

Proportion of people in Scotland reporting satisfaction with opportunities to influence net zero and climate adaptation developments happening in their local area

Increasing

Scottish Climate Survey (proposed addition from Autumn 2026)

By Local Authority – Every 3 years

This indicator captures the sense of influence over net zero and climate adaptation projects in hotspots. This is a key dimension of the JT for Scotland and directly relevant in places seeing targeted interventions and experiencing change. It is directly relevant for net zero development hotspots and may also be relevant in hotspots of industrial change. This indicator is only available at local authority level every three years.

H23

The proportion of people reporting that changes to their local place due to net zero infrastructure and/or land use change have maintained or improved the quality of their local area

Increasing

Scottish Climate Survey (proposed addition from Autumn 2026)

By Local Authority – Every 3 years

This indicator monitors mid-term experiences of change in sites of transition. It is directly relevant to net zero hotspots and may be relevant in industrial hotspots. It does not reflect the reasons for improved quality nor a breakdown by respondents. This indicator is only available at local authority level every three years.

How to cite this publication:

Santos Ayllón, L. M., Jenkins, K. E. H., (2026) ‘Monitoring a Just Transition to a net zero and climate resilient Scotland’, ClimateXChange. DOI:

© The University of Edinburgh, 2026
Prepared by The University of Edinburgh on behalf of ClimateXChange, The University of Edinburgh. All rights reserved.

While every effort is made to ensure the information in this report is accurate as at the date of the report, no legal responsibility is accepted for any errors, omissions or misleading statements. The views expressed represent those of the author(s), and do not necessarily represent those of the host institutions or funders.

This work was supported by the Rural and Environment Science and Analytical Services Division of the Scottish Government (CoE – CXC).C

ClimateXChange

Edinburgh Climate Change Institute

High School Yards

Edinburgh EH1 1LZ

+44 (0) 131 651 4783

info@climatexchange.org.uk

www.climatexchange.org.uk


  1. These themes were also referred to in the Draft CCP (2025), though they do not feature in the final CCP (2026).



  2. These four ‘themes’, now widely used across Scottish Government JT policy, are different in focus and definition to four ‘themes’ in the National JT Planning Framework (2021). The latter have not been returned to since.



  3. The National Performance Framework for Scotland is currently archived and under review.



  4. The draft Energy Strategy and JT Plan (2023) refers to the eight national JT outcomes in its Annex F to translate them into energy sector outcomes.



  5. The four themes are not referred to in the final CCP (2026).



  6. Some indicators such as ‘employment’, for example, were removed from the full outcome indicator list and integrated into the hotspots monitoring approach instead.



  7. With ‘net zero infrastructure and/or land use change’ this report refers to the installation of renewable energy production and related infrastructure (power stations, transmission lines), alongside projects of woodland creation and peatland restoration for net zero and adaptation purposes.



  8. JSEO indicators 9-12 focus on the gendered dimension of fair work in the four net zero sectors identified by the Scottish Government, following advice from the Fair Work Convention Secretariat and indicators in the Draft Transport JT Plan (2025). This framework prioritises gender pay gap as a measure of structural inequity.



  9. This caveat recognises that while the net zero transition will impact industries such as oil and gas, their declining activity in Scotland is also a result of various factors other than the response to climate change. These have been affecting these industries for some time (e.g., Shapovalova et al. 2023).



  10. Location quotient calculations were provided by the industry statistics area in Scottish Government, January 2026.



  11. The minimum threshold for installed capacity was 1MW until 2021, at which point it was lowered to 150kW. This means that projects below 1MW that were going through the planning system before 2021 may not be represented.



  12. For hotspots, trend three ‘economic trends in Scotland’ should also be complemented with economic trend data in the specific local authority monitored.


Reducing emissions from Scotland’s tourism sector is a crucial part of reaching the Scottish Government’s target of net zero greenhouse gas (GHG) emissions by 2045.

Emissions from tourism cut across passenger transport, accommodation, food and drink, culture, retail and outdoor recreation, so reliable data is required. Current data, however, only reports over broad categories such as ‘transport’ or ‘buildings’ and does not isolate the contribution from visitor activity.

In this report, researchers explore how they can measure GHG emissions from Scotland’s tourism sector in a way that is credible, repeatable, and trackable over time. The primary aims of this research were:

  • To identify a practical methodology for a reliable, national-level estimate of tourism-related GHG emissions.
  • To examine the potential for separating results by factors such as geography, visitor or accommodation type to support place-based policy
  • To ensure the chosen approach aligns with established GHG measurement practices and can be maintained through routine updates while balancing coverage, granularity, cost, and capacity.

Findings

  • Scotland’s tourism sector has distinctive characteristics, including geography, rural tourism, transport emissions, seasonal workforce, and post-COVID behavioural changes.
  • There is broad consensus on definitions of “tourism” across the literature, with studies organising indicators according to the United Nations World Tourism Organisation’s (UNWTO) Measuring the Sustainability of Tourism (MST) framework.
  • Tourism Satellite Accounts (TSAs) – data sets providing economic analysis of a country’s tourism industry – are critical for defining the economic boundary of tourism, separating visitor-driven activity from resident activity, and enabling reporting.
  • Four major methodology types for assessing GHG emissions in tourism are identified:
    • Environmentally‑Extended Input-Output (EEIO) analysis is suitable for establishing a robust, repeatable national baseline.
    • Life Cycle Assessments (LCA) provide detailed insights for operational decision-making.
    • Hybrid models can combine the strengths of both approaches.
    • Survey-based methods are useful for capturing regional behaviour and supplementing other models.

Recommendations

The report’s headline recommendation is to take a proportionate, staged pathway that matches effort to ambition. It suggests: 

  • Conducting a comprehensive audit of Scotland’s available data, including Input-Output tables, environmental accounts, and surveys such as the International Passenger Survey (IPS) and the Great Britain Tourism Survey (GBTS).
  • Establishing an EEIO baseline as the analytical backbone, updated regularly using repeated survey data.
  • Developing a Scotland-specific Tourism Satellite Account to enable greater precision, sector splits, and geographical disaggregation.
  • Running LCA pilots for selected assets or services to provide operational insight and validate baseline assumptions.

Over time, these elements could be integrated into a hybrid framework under formal governance and quality assurance, reporting both production- and consumption-based perspectives. A staged, proportionate approach provides a clear, low-risk path to a credible baseline and repeatable evidence base, supporting policy and industry efforts to track and reduce tourism-related emissions.

Further recommendations

The report also outlines steps that should be taken in development of the methodlogy, regardless of the final methodology chosen:

  • Adopt the IRTS definition of tourism and structure the GHG account within the UNWTO MST framework.
  • Main active links with those that are further advanced, such as Denmark, to learn best practice.
  • Build the methodology around a mix of data sources and keep data management central to project governance.
  • The approach should be designed for regular repetition, and to secure the resources needed for scheduled updates.

For further information, please read the report.

If you require the report in an alternative format, such as a Word document, please contact info@climatexchange.org.uk or 0131 651 4783.

Community benefits are additional benefits offered by renewable energy developers to support communities. Examples include community benefit funds and in-kind benefits provided by developers such as investment in local infrastructure improvements or funding for education programmes. Community benefits currently operate on a voluntary basis in Scotland.

The Scottish Government has published Good Practice Principles for onshore and offshore energy in Scotland, which are currently under review. Within the context of that overarching review, the primary aims of this research were: 

  • To help identify any necessary adjustments to Scotland’s current voluntary community benefits approach for onshore and offshore to better support communities and industry as part of a just transition.
  • To understand how different renewable energy technologies affect the provision of community benefits. 
  • To understand how mandating community benefits could work in practice for onshore renewable energy technologies.

The research incorporated an evidence review, qualitative interviews and the design and testing of a socio-economic analysis framework.

Findings

  • No obvious adjustments need to be made to Scotland’s current community benefit approach.
  • Financial aspects of a renewable energy project (costs, revenue and financial viability) are key factors impacting community benefit levels. Projects with higher amounts of revenue, and more robust and predictable financial returns are better positioned to offer significant community benefits.
  • It is easier to offer community benefits for projects involving more established technologies like onshore wind, compared to newer technologies like hydrogen.
  • The literature reviewed did not allow for a satisfactory comparative analysis of the in-practice impacts of mandatory versus voluntary approaches.
  • Further development and more complete data is required to make a functional framework that could inform policy decisions on the appropriate levels of community benefit for different renewable energy technologies.

For further information, please read the report.

If you require the report in an alternative format, such as a Word document, please contact info@climatexchange.org.uk or 0131 651 4783. 

Research completed: July 2025

DOI: http://dx.doi.org/10.7488/era/6396

Executive summary

Research background and aims

Community benefits are additional benefits offered by renewable energy developers to support communities. Examples include community benefit funds and in-kind benefits provided by developers such as investment in local infrastructure improvements or funding for education programmes. Community benefits currently operate on a voluntary basis in Scotland. The Scottish Government has published Good Practice Principles for onshore and offshore energy in Scotland, which are currently under review.

Within the context of that overarching review, the primary aims of this research were:

  • To understand how different renewable energy technologies affect the provision of community benefits. This included developing and testing a socio-economic analysis framework to understand the factors that influence the nature and level of community benefits associated with different renewable energy technologies.
  • To understand how mandating community benefits could work in practice for onshore renewable energy technologies.
  • To help identify any necessary adjustments to Scotland’s current voluntary community benefits approach for onshore and offshore to better support communities and industry as part of a just transition.

The study methodology incorporated an evidence review, qualitative interviews, and the design and testing of a socio-economic analysis framework. This research focused on the factors influencing how different renewable energy technologies affect developers’ provision of community benefits, rather than on the experiences and perspectives of recipient communities. Interviews were therefore conducted with renewable energy developers.

The Scottish Government is gathering other non-industry perspectives on community benefits, including the views of community members, through a public consultation on the Good Practice Principles.

Understanding the ability of different technologies to offer community benefits

One of the ways this research explored how renewable energy technologies affected developers’ ability to offer community benefits was to develop and test a socio-economic analysis framework. This framework set out the parameters assumed to influence the level and nature of community benefits. An initial set of seven draft parameters were developed by the Scottish Government and the research team. Following an assessment of the feasibility of measurement and feedback from renewable energy developers, four parameters were recommended for further consideration (and which are subsequently referred to as “the framework”). These were:

  • Technology maturity (i.e. more mature technologies, with well-established supply chains and business models, may better allow developers to build community benefit provision into their project plans compared to newer technologies).
  • Market maturity (i.e. maturity may influence investor confidence, competition between developers, and certainty in supply chains which may in turn determine predictability of financial plans and therefore ability to deliver community benefits).
  • Deployment and operating costs (i.e. the costs associated with developing and operating different renewable energy technologies may impact the financial capacity to provide community benefits).
  • Revenue and profit (i.e. a project’s revenue and profit will impact on its overall financial viability which may impact on its ability to delivery community benefits).

This study identified significant challenges in developing a single framework to assess how different technologies affect developers’ provision of community benefit. For such a framework to work as a practical, decision-making tool, quantitative data on the economics of different renewable energy technology projects would be required. However, existing public data is sparse and of inadequate quality and many developers were unable or unwilling to share commercially sensitive data about their projects. A further limitation was that existing data (e.g. on the value of community benefits from individual renewable energy projects) is based on actual provision rather than an assessment of potential. Additionally, data available is largely historical and therefore challenging to use when anticipating new technologies and emerging economic and regulatory models.

However, it was clear from interviews with developers that the financial aspects of a renewable energy project (costs, revenue and financial viability) were key factors impacting community benefit levels. They noted that projects with higher amounts of revenue, and more robust and predictable financial returns are better positioned to offer significant community benefits. Conversely, if the financial viability of a development is low, then it is unlikely it can offer monetary community benefits without the project becoming non-viable. Developers noted that both technology maturity and market maturity can have an impact on a project’s financial viability and are therefore, indirectly, also linked to a project’s ability to deliver community benefits. However, this was based on qualitative interviews and was not possible to measure using quantitative data.

Developers also reported that it is easier to offer community benefits for projects involving more established technologies like onshore wind, compared to newer technologies, due to the latter’s comparatively lower profit margins. Less mature technologies (e.g., floating offshore wind, hydrogen) can have higher risks, higher delivery costs, less predictability in cost and performance, and lower investor confidence which can impact on their ability to offer benefits.

Although not necessarily directly impacting the level of benefit offered, developers identified community engagement as key factor for effective delivery. Developers emphasised the importance of levels of community engagement and capacity to effectively manage and deliver benefit funds. Interviewees highlighted the importance of community engagement, consultation and feedback in moulding community benefit initiatives, ensuring more meaningful and tailored contributions. This is difficult to quantify and would therefore be challenging to include in a socio-economic analysis framework.

How mandating community benefits could work in practice (for onshore renewable technologies)

The available literature does not enable a comparison of the real-world impacts of mandatory, as opposed to voluntary, provision of community benefits. Mandatory community benefits as part of renewable energy infrastructure development exist in Denmark and Ireland, specifically for wind projects. However, the literature reviewed does not allow for a satisfactory comparative analysis of the in-practice impacts of mandatory versus voluntary approaches.

Existing onshore developers felt that the following factors should be considered:

  • clear guidance on what the financial expectation attached to mandating is to avoid any potential for confusion;
  • allowing for the differences between individual onshore technologies to be taken into account;
  • retaining a degree of flexibility, particularly in terms of allowing for community benefits to be designed around the needs of communities;
  • avoiding overly burdensome processes. For example, in relation to restrictions on how communities should spend the money.

The power to mandate community benefits is reserved to the UK Government. In May 2025, the UK Government published a working paper seeking views on a mandatory community benefits scheme for low carbon energy and mechanisms for shared ownership of onshore renewables[1]. This includes the option to utilise existing powers to mandate offering shared ownership.

Any necessary adjustments to Scotland’s current voluntary community benefits approach for onshore and offshore

This research has not identified any obvious adjustments that need to be made to Scotland’s current community benefit approach.

The literature highlights that the Scottish Government is leading the way across the UK in highlighting the role of communities in the development of renewable projects. While there are examples in the literature of other approaches to community benefit provision outside of Scotland (e.g. in Ireland and Denmark), there is limited evidence directly comparing how different approaches have impacted the level of community benefits delivered. Therefore, there are no clear lessons from these international approaches suggesting a need to change the current approach in Scotland.

Guidance from the Scottish Government, in the form of Good Practice Principles and a recommended community benefit contribution of £5,000 per installed MW per year for onshore projects, was highlighted in interviews with developers as being a strength of the current process. They felt it provided a degree of predictability while also allowing for flexibility in application. However, for projects of emerging and/or non-generative technologies, developers noted that more targeted guidelines would be beneficial, noting that there is no established industry standard approach.

Conclusion and recommendations

The intention was that the framework examined in this study could inform policy decisions on the appropriate levels of community benefit for different renewable energy technologies. However, further development and more complete data is needed to be functional for this purpose. Collating the required data would need considerable resources and rely on information that developers perceive to be commercially sensitive. Considering data gaps, collection challenges, the difficulty in sourcing data specifically focused on future ability to offer benefits (rather than actual performance), further research and/or alternative approaches would be required. For these reasons, the approach explored here does not provide a robust enough evidence base to underpin a framework for use as a decision-making tool.

The report highlights existing measurement tools and guidance that can be used to understand where a project sits in relation to certain parameters, such as technology and market maturity. Further data collection work would be needed to make the most of these tools for robust socio-economic analysis. This would involve collecting relevant data for a large number of projects across metrics with established measurement tools. This would require a significant time and resource commitment and may not be a practical option.

To better understand how different renewable energy technologies affect developers’ provision of community benefits further research, beyond the financial indicators highlighted, would be needed. Considering the challenge of sourcing quantitative data on project economics, further qualitative research may be the most feasible option. Ideally this would be with a larger selection of developers across the full technology spectrum (including those that had not been able to deliver community benefits), direct engagement with communities, and wider stakeholder engagement (e.g. project investors, funders and other partners that have assisted in project development). This type of engagement would add to and build on the insights from developers gathered in this study.

Introduction

This report presents findings from research exploring opportunities for providing community benefits from renewable energy projects using different technologies in way that is fair and consistent. The research was carried out by Ipsos on behalf of ClimateXChange and the Scottish Government.

Background to the project

The Scottish Government has set ambitious targets for achieving net zero emissions by 2045, emphasising the importance of renewable energy technologies in this transition. The Climate Change Plan update (2020)[2] sets out Scotland’s ambition of a transformed energy system, which supports sustainable economic growth across all regions of Scotland.

Communities are at the heart of the energy transition in Scotland. Community benefits are additional benefits offered by renewable energy developers to support communities, offering them an opportunity to work with renewable energy businesses to secure long-term benefits. They provide an opportunity to share in the benefits of the energy resource and can have lasting social and economic impacts[3].

The Scottish Government published Good Practice Principles for the onshore[4] and offshore[5] energy sectors to outline how they can achieve a positive legacy for local communities. The approach and nature of community benefits operates on a voluntary basis in Scotland, with the guidelines allowing for flexibility in benefits arrangements offered by industry. Decisions on mandating community benefits are reserved to the UK Government. In May 2025, the UK Government published a Working Paper on community benefits and shared ownership for low carbon energy infrastructure, seeking views on whether mandating is the right approach and if so, to inform the design of future policy proposals.

Good Practice Principles have been widely adopted, but the approach to community benefits has not been wholly consistent across developments. In recognition of this, and of the rapidly changing sectoral and policy landscape, the Scottish Government is undertaking a review of the Good Practice Principles to ensure that guidance continues to help communities and developers get the best from community benefits.

This research sits within that overarching review. It was designed to help the Scottish Government understand more about different approaches to providing community benefits and to explore the opportunities for providing community benefits in future in a way that is fair and consistent for industry and communities. The findings from this research will help to inform a refresh of the Good Practice Principles.

Aims and objectives

The primary aims of this research were:

  • To understand how different renewable energy technologies affect developers’ provision of community benefits. This included developing and testing a socio-economic analysis framework to understand the factors that influence the nature and level of community benefits associated with different renewable energy technologies.
  • To understand how mandating community benefits could work in practice for onshore renewable energy technologies.
  • To help identify any necessary adjustments to the Scottish Government’s current voluntary community benefits approach for onshore and offshore to better support communities and industry as part of a just transition.

The findings aimed to support policy development and further refinement of guidelines and frameworks to help ensure that community benefits are effectively and fairly integrated into Scotland’s net zero energy system and strategy.

Methodology

The research involved a mix of desk research, qualitative interviews with developers and data analysis, as outlined below (detailed methodology is in Appendix A):

  • A desk-based evidence review that explored examples of community benefits from onshore and offshore renewable energy technologies in the UK and other countries. Literature sources reviewed included 12 peer reviewed academic papers, 20 reports, 2 guidance documents from grey literature (e.g., renewable energy developers, private consultancies) and 1 policy document. These were all published between 2011 and 2024, with 22 documents from the last 5 years.
  • Initial scoping interviews with four industry representative bodies to understand their views on current community benefit approaches and to explore options for sourcing data that could support socio-economic analysis on community benefits.
  • Design of a socio-economic analysis framework to help understand the factors which are likely to affect the level and nature of community benefits.
  • In-depth interviews with 21 industry developers from a range of renewable energy technologies (see Appendix A). As the focus was on how different renewable energy technologies affect provision of community benefits, qualitative research with developers was carried out to help understand the views of those with direct experience of working with projects and benefits. Interviews helped to understand industry perceptions towards community benefits arrangements, collect feedback on the proposed analytical framework, and to understand availability of relevant data for socio-economic analysis.
  • Assessment of the suitability of a framework to act as a tool for the Scottish Government to understand what type and level of community benefit may be suitable for different renewable energy technologies, based on data availability and feedback from interviews.

Definitions

Community benefits are defined in this research in line with the Scottish Government’s Good Practice Principles:

Community benefits are additional benefits, that are currently voluntary, which developers provide to the community. The Scottish Government does not currently have the power to legislate for community benefits, which lies with the UK Government. A community benefit fund is considered to be a fundamental component of a community benefit package, though other measures may be considered such as in-kind works, direct funding of projects, or any other voluntary site-specific benefits. Community benefits are not compensation for impacts on communities or other interests, including commercial interests, arising from renewable installations and they are not taken into account in a decision over whether a consent for a development is granted.

Community benefit in Scotland is distinct from shared ownership. Shared ownership provides community groups or members of a community the opportunity to make an investment in a commercially owned renewable energy project. This includes any structure which involves a community group as a financial partner benefitting over the lifetime of a renewable energy project. As shared ownership is not considered a form of community benefit in Scotland, it has not been included within this research.

In this report renewable energy technologies have been interpreted as the range of technologies outlined in the Scottish Government’s draft Energy Strategy and Just Transition Plan[6]. This includes onshore wind, offshore wind (both floating and fixed), solar, hydro, pumped hydro storage, battery energy storage system (BESS), hydrogen, and carbon capture, utilisation and storage (CCUS).

Limitations

This study was limited by data availability. Existing public data (for example on community benefit values, project costs and revenue) is sparse and of inadequate quality to effectively measure the parameters within a socio-economic analysis framework. Many developers were unable or unwilling to share commercially sensitive data about their projects. A further limitation was that existing data (e.g. on the value of community benefits from individual renewable energy projects) is based on actual provision rather than an assessment of project’s potential capability. Additionally, existing data are largely historical and therefore challenging to use when anticipating new technologies and emerging economic and regulatory models. Consequently, data gaps mean it was not possible to develop a fully functioning socio-economic analysis framework as part of this study.

A further limitation is that this research draws on the views of a relatively small sample of developers. These represent one group of perspectives on community benefits, albeit from different organisations, working with different technologies. Non-industry perspectives, including those of community members themselves, were not included in the remit of this study and would not be expected to fill the data gaps highlighted above.

Current community benefit arrangements

This chapter details the current arrangements for delivering community benefits, based on findings from the literature and from the qualitative interviews with renewable energy technology developers. At various points, examples of community benefit projects identified in the literature are shown to help illustrate the findings.

Key findings

  • The literature highlights that the Scottish Government is leading the way across the UK in highlighting the role of communities in the development of renewable projects and in providing good practice guidelines.
  • Community benefits from renewable energy projects in the UK mainly involve community benefit funds[7], but there are also examples of in-kind benefits such as investment in education and infrastructure programmes. Community benefit funds are not as extensively adopted outside of the UK.
  • Onshore wind has more established community benefit practices than other onshore and offshore technologies. However, a key similarity is that all projects, regardless of technology, tended to adopt both community benefits funds and in-kind contributions.
  • There is limited evidence directly comparing how different approaches in the UK and in other countries have impacted the level of community benefits delivered.

Guidelines for community benefits

According to the reviewed literature, the Scottish Government is leading the way across the UK in highlighting the role of communities in the development of renewable projects. The Good Practice Principles for Community Benefits from Onshore Renewable Energy Developments (updated in 2019) and the draft Good Practice Principles for Community Benefits from Offshore Renewable Energy Developments (2018) outline how the energy sector can achieve a positive, lasting legacy for local communities, and a range of successful community benefit projects have been implemented to date.[8] These guidelines have been widely adopted across the renewables industry, providing best practice for the sector.[9]

The voluntary guidelines suggest practices like conducting impact studies to identify affected communities, engaging in consultations, and tailoring benefits to local context and needs. These principles aim to ensure benefits are well-targeted and meet community expectations, which could be seen as markers of a well-designed scheme.[10]

Example 1.

Beatrice Offshore Windfarm’s Community Benefits Fund used the Scottish Government’s Good Practice Principles to guide the development of the fund. The Beatrice Community Benefits Fund also undertook innovative analysis of the potential wider impacts of the community benefits funding, using a Social Return on Investment methodology.[11] This illustrates the ability of the Good Practice Principles to be applied alongside other models and approaches.

In Scotland, the Scottish Government also established the Community Benefits Register,[12] managed by Local Energy Scotland. It can be viewed online and offers a form of third-party reporting and public recognition.[13] Best practice guidance also exists in England, Ireland, the Netherlands and Germany (see Table 2 in Appendix B).

Approaches used in the UK and elsewhere

The literature provided examples of different approaches to designing and implementing community benefits schemes. However, most examples are from onshore wind farms, with some examples given from offshore wind technologies. There is very little to no reference to other renewable technologies such as hydrogen, hydro, solar, wave, thermal, or BESS.

Community benefit mechanisms referred to in the literature included[14]:

  • Financial contributions to a community benefit fund, to be used as directed by the community to invest in local initiatives[15];
  • In-kind contributions to local infrastructure, facilities, or services[16];
  • Grants, scholarships, or donations to support community initiatives[17];
  • Electricity discounts or subsidies for local residents[18];
  • Provision of environmental or recreational amenities.[19]

While these approaches share many similarities, there are some notable differences and ambiguities. These include varying interpretations of what constitutes the “local community” (especially for offshore projects)[20] and differing emphasis on the rationale for providing benefits (e.g., impact mitigation).

This section describes the different approaches to community benefits in more detail. Differences between the UK and other countries are noted, where available.

Community benefit funds

Community benefits from renewable energy projects in the UK are primarily delivered through community benefit funds. The UK onshore wind industry, in particular, has well established approaches for this.[21] Through this mechanism, developers voluntarily contribute a certain amount of funding to local communities. In some cases, the level of funding is linked to the amount of installed capacity of the project or the amount of energy produced. For example, in Scotland, it is the industry norm for onshore wind projects to typically deliver £5,000 per megawatt (MW) of installed capacity per year in alignment with the Good Practice Principles for Onshore Renewable Energy Developments.[22] However, the per MW model is not the only approach used and the total amount provided is based on the agreement between the developers and the community.

Example 2.

Crossdykes Wind Farm near Lockerbie, Scotland (developed by Muirhall Energy) offered an industry-leading £7,000 per MW per year for a community benefit fund, well above the industry standard of £5,000 per MW per year. The project provided an Initial Investment Fund of £100,000 to support community projects during the wind farm’s construction phase, showing a proactive effort to deliver early benefits.

Example 3.

Brechfa Forest West Wind Farm in Wales (owned by RWE Renewables), is an example of a community-administered community benefit fund which is expected to provide £11 million in community benefit funding, administered by the local enterprise agency and a volunteer panel of residents.[23]

Regarding offshore wind, the concept of community benefits in the UK is relatively newer and more flexible than for onshore, reflecting the evolving nature of the industry.[24] Some, predominantly near-shore English and Welsh wind farms (e.g. North Hoyle and Rhyll Flats off the North Wales coast) have followed the pattern of the onshore wind farms, with benefits pro rata to MW size, although at a much lower rate.[25] However, in many cases, and for some of the large North Sea distant offshore wind farms, the benefits packages have been more ad hoc and much smaller (pro rata) than for onshore projects.[26] Several challenges have been identified with providing community benefits funds for offshore wind projects, including defining the relevant community to be targeted.[27]

Example 4.

The Hornsea/Race Bank East Coast Community Fund, off the Norfolk coast, is managed independently by a specialist grant-making charity, GrantScape, on behalf of the developer Orsted. This enables an arms-length, transparent allocation process.[28]

According to a number of the literature sources, allocation and spending of community benefit funds are usually determined by developers, in collaboration with the local communities, often through local trusts or organisations. Developers often strive to tailor the benefits based on local priorities identified through community engagement.[29] Community benefit funds can take different forms, ranging from local funds – investments in communities nearest to developments to enhance services, assets and activities of residents – to regional funds – investment in transformational projects to provide socio-economic growth for wider communities.[30]

The evidence reviewed suggests that community benefit funds are not as extensively adopted outside of the UK. There are some instances of community benefit funds in Europe. Notably, in Denmark, from 2008-2018, the state-run “Green Scheme” mandated payments per kilowatt per hour of production to host communities. As of 2020, Danish developers must pay fixed amounts per MW installed into green funds for affected municipalities under the “Green Pool” scheme and make annual payments to neighbouring residents under the “VE-Bonus” scheme, with amounts determined by the Danish Energy Agency.[31] In Ireland, renewable energy auctions require developers to contribute €2 per MW hour to a community benefit fund, with defined spending allocations.[32]

Among the developers interviewed for this research, flexible community benefit funds were the most common approach being taken to community benefits in Scotland. The exact sum delivered through these funds varies project-by-project. Onshore wind developers said that they follow, and often exceed, the Good Practice Principles guidelines of £5,000 per MW per year. For other technologies, which developers said often have greater financial uncertainty and/or smaller margins than onshore wind, the levels of community benefit are less predictable. Developers said that the level of benefit is often closely linked to the project’s costs and financial returns, which varies.

“We typically work backwards from what we think the returns in the scheme are going to look like. And that’s very site specific, dependent on abnormal costs, grid costs, land rights costs…Depending on what that looks like, we’ll then generate a number to determine what we can reasonably offer local communities.” – BESS developer

In a number of cases, these funds are administered by Foundation Scotland, a charitable organisation that helps to support communities to set up, manage and distribute their funding. This has particularly been the case where local communities may lack the capacity to manage significant financial resources independently. Some projects also have established their own governance arrangements, involving boards constituted of local community members to determine the allocation of these funds.

Other community benefit mechanisms

Other examples of community benefits mechanisms that appeared in the literature include tax revenues or fiscal contributions from wind farm developers, which go directly into funding local infrastructure and community services. From the documents reviewed, this is common practice in Germany, Poland, Croatia, France and Italy. [33]

Example 5.

The Block Island offshore wind farm development in Rhode Island, USA, is an example of fiscal contributions being made to support local infrastructure. In this case, a formal Community Benefit Agreement was developed in which the wind farm company pays for improvements to town infrastructure where the cable comes ashore. This project was also highlighted in the literature as an example of community engagement resulting in locally appropriate community benefits and high levels of support for the development from the local community. As part of the public consultation on the project proposals, the developer, Deepwater Wind, collaborated with the town council to invite stakeholders and hired consultants from the local community to represent local interests. This helped establish trust and perceptions of fairness in the process.[34]

The literature also identified Australian examples of neighbourhood benefit programmes.[35] These programmes aim to address concerns around fairness that can arise when local residents receive no direct benefits from a renewable energy project which affects their experience of their place and community.[36] Examples of the types of benefits provided via these neighbourhood benefit programmes include support towards home energy efficiency measures, the installation of residential solar PV, and contributions to electricity bills for neighbours or neighbourhood community facilities (e.g. local hall, local fire-fighting facilities).

The reviewed literature suggests that the involvement of local authorities in the delivery of community benefits varies by country. In some European countries (including Denmark, Germany, France, Italy and Spain), the local municipality plays a significant role and often decides funding priorities of community benefits. In the UK and Ireland, local authorities generally decline involvement to avoid conflicts of interest in the planning process. However, Highland Council recently set out plans for a different approach to community benefit decision making and fund distribution and Shetland Council approved a new set of principles around community benefit.

Developers interviewed also described the types of in-kind benefits they offer communities. Examples included:

  • Employment and education programmes. This includes providing funding towards training in green technologies, especially in areas that are reliant on traditional energy industries rather than renewable energy.
  • Electricity discount schemes, with money coming off local residents’ bills.
  • Investment in environmental and net zero initiatives, including activities designed to reduce carbon footprint and support biodiversity in communities, along with awareness-raising around these issues.
  • Infrastructure improvements such as broadband access, roads and pathways, and community recreational facilities.

Impact of different approaches on the level of community benefits delivered

Based on the literature reviewed, there is limited evidence directly comparing how the different approaches in the UK and in other countries have impacted the level of community benefits delivered.

Among the documents reviewed, the only source that explicitly offers comparative analysis between approaches in the UK and European countries was the Department of Trade and Industry report conducted by the Centre for Sustainable Energy, which involved detailed case studies of major wind farms in the UK, Germany, Denmark, Ireland and Spain. The following points are drawn exclusively from this report:

  • The overall levels of benefits accruing to communities from wind projects in Denmark, Spain and Germany tend to be higher than in the UK. However, it is important to note that in such countries, community benefits are mostly associated with shared ownership practices, and therefore economic and financial benefits are linked to those practices. Shared ownership is not included in the Scottish Government definition of community benefits and it is also worth noting that developments outside of the UK will have different policy contexts and market conditions to those in the UK, making it difficult to directly compare.
  • While the authors do not find robust evidence that higher benefits directly lead to higher levels of support for developments, they suggest that they are likely an important factor in sustaining long-term acceptance of projects.

Lessons from community benefits projects

Common themes emerged from the literature and interviews around what constitutes good practice in community benefit:

  • Early community engagement. Establishing trust, building relationships with local residents and identifying concerns and priorities early on can lead to smoother running of the project and help dispel fears of community members early on. [37]
  • Ensuring community representation in the co-design and administration of community benefits[38] as this can help establish trust and lead to higher levels of sustained support for the project.[39]
  • Providing broad and flexible community benefit. Literature and interviews highlighted the value of funds being used to support a wide range of community priorities like infrastructure, schools, housing, elderly care, environment, etc. that improve quality of life for residents. [40]
  • Community capacity was noted by developers as a factor that can impact on their ability to deliver community benefits. Not all communities were seen to have the resources or expertise needed to administer funds efficiently. They noted that the existence of strong community councils or Community Development Officers to help generate ideas have helped contribute to successful community benefit funds.
  • Ensuring transparency of communication and providing full information to communities through trusted messengers is seen in the literature as a crucial step in securing support from communities.[41]
  • The reviewed literature also suggests that formalising benefit commitments and monitoring progress can promote accountability and sustainability over the long-term. It helps ensure developers deliver on promises made to communities.[42]
  • There is also evidence that partnering and aligning with local government, NGOs and other companies allows projects to leverage additional resources and maximise the scale and impact of their community investments.[43]

Understanding how different renewable energy technologies affect the ability to offer community benefits

One of the ways this research explored how renewable energy technologies affect the level of community benefits offered by developers was to develop and test a socio-economic analysis framework. This framework set out the parameters assumed to influence the level and nature of community benefits provided. This chapter outlines the steps taken to develop and test a framework and the extent to which this tool could help to understand how different renewable energy technologies affect the level community benefits provided by developers.

Key findings

  • Within the scope of this study, the available evidence did not support a single framework to robustly determine how different technologies affect the provision of community benefits. For such a framework to work as a practical, decision-making tool, quantitative data on the economics of different renewable energy technology projects would be required. However, existing public data is insufficient to effectively measure the parameters in the framework, and it was not possible within this study to gather the level of quantitative data that would be needed for robust socio-economic analysis.
  • However, it was clear from the interviews with developers that the financial aspects of a renewable energy project (costs, revenue and financial viability) were key factors impacting community benefit levels.
  • Developers’ feedback also highlighted that it is easier to offer community benefits for projects involving more established technologies like onshore wind, compared to other technologies (e.g. offshore wind, solar and battery storage) due to the latter’s comparatively low profit margins.

Original framework parameters

The initial parameters identified at the scoping phase of the project are outlined in Table 1. The following section sets out the feedback received from developers in response to this framework, and the extent to which these parameters are measurable within a framework.

Table 1 Initial list of identified parameters affecting provision of community benefits

Parameter

Justification for inclusion

Technology maturity

More mature technologies like onshore wind and solar PV have well-established supply chains and business models, allowing for community benefit provision to be built in to project plans. The more mature technologies are also more reliable in terms of return on investment (ROI), than less mature technologies. Emerging technologies have less predictability in costs and revenues, affecting community benefit schemes and their provision.

Market maturity

The level of market maturity can determine the provision of community benefits by influencing investor confidence, increased competition between developers, robust supply chains and solidified regulatory frameworks. These all determine predictable project economics and financial plans, increasing the likelihood and scale of community benefits being provided.

Project size/energy yield

The energy yield of a project is a critical factor that can influence the revenue and, consequently, the level of community benefits provided. Smaller projects may have small absolute margins and so may be less able to provide the same level of community benefits as larger projects.

Deployment and operating costs

The costs associated with developing and operating different renewable energy technologies can impact the financial capacity to provide community benefits. If one technology has higher upfront costs or operating expenses, this might reduce the scope of benefits a developer can offer, as well as the timing of delivering these benefits.

Revenue and profit

The amount of revenue generated by a project, or the profits it generates, could also have an impact on a project’s ability to deliver community benefit and on the level and nature of community benefits that can be delivered.

Land use, visual, environmental and social impacts

Wind farms, especially onshore ones, can have a significant visual impact and may occupy large areas of land which can influence the local community’s perception, and the level of benefits expected. This may differ for offshore wind. It may also influence the type of community benefit provided (environmental, social, economic). In contrast, solar PV installations typically are less sensitive to visual impacts than wind turbines but could be associated with higher land use impacts.

Wider economic impact of the project and its distribution

The economic returns from projects may also influence the level of benefits provided through community benefit schemes. Projects which require a large workforce for ongoing maintenance and operation will provide economic benefits to the local area through jobs and investment which is multiplied through other sectors and amenities required by residents. It can be theorised that a developer’s contribution to the wider economy may reduce their overall willingness to community benefit commitments, though it is unlikely that this contribution would affect their ability to provide monetary commitments.

Community benefit value

There is a lack of data on the level of community benefits offered by renewable energy projects. The Local Energy Scotland Community Benefits Register is currently the most comprehensive data source for capturing the community benefits monetary measures. However, this is not exhaustive and does not cover the full range of renewable energy technologies.

Further steps were therefore taken to identify additional and more up-to-date data for this research. Firstly, data was requested from developers taking part in interviews, but not all were willing or able to share this (either because they could not access the data, or due to commercial sensitivities). Secondly, online searching for publicly available information on monetary values of community benefits was carried out. While data for some projects is available publicly, this requires a significant time commitment to source since it is not held in a central source nor in a consistent format. Therefore, data gaps remained after taking these steps. For the framework to be robust, a more complete set of data on community benefit value is required.

Technology maturity

Technological maturity is a widely used metric for gauging a technology’s development and readiness for deployment.

Developers generally felt that this could have an impact on the viability of a project, and as a result affect the level of community benefits. Some agreed that, compared to mature technologies (e.g., onshore wind), technologies such as floating offshore wind, BESS and hydrogen can have higher risks, higher delivery costs, less predictability in cost and performance and lower investor confidence. However, some onshore wind developers argued that more mature technologies do not always have more secure financial models because recent cost increases in their supply chains have made viability harder to predict.

Technology maturity is suitable for quantitative measurement using the NASA Technology Readiness Level (TRL) scale (see Appendix E for details). To accurately assess a technology’s TRL, it is recommended that individual projects are approached directly for scoring, as they may employ different versions of the technology. If direct assessment is not possible, it would be possible to utilise the International Energy Agency’s ETP Clean Energy Technology Guide, which evaluates and provides comprehensive information on each technology’s current development stage across the energy system.

This parameter could be included in a socio-economic analysis framework, provided there was sufficient data available or one of the existing guides outlined above could be used.

Market maturity

Factors influencing market maturity include established supply chains, business models and supporting physical and regulatory infrastructure (ports for deployment of offshore wind, standards for solar farms, etc.).

Developers felt that emerging technologies and immature markets face difficulties determining an appropriate level of community benefits because of uncertainty around securing investment and finances. However, some onshore wind developers also noted that their more mature market can still experience challenges with supply chains, especially in relation to costs of deployment (e.g. turbine costs have increased).

Market maturity could be measured using existing tools. The Adoption Readiness Level (ARL) framework, developed by the U.S. Department of Energy, is a tool for assessing the commercialisation risks of new technologies. It helps identify potential roadblocks to market adoption, such as cost-competitiveness, regulatory landscape, public perception and infrastructure availability. It also helps evaluate market demand by identifying the target market, understanding customer needs, and assessing the competitive landscape.

The ideal approach to understanding this parameter would involve project-level assessments via direct engagement with project owners, using the scoring framework available online[44]. However, given the large number of projects, this endeavour would be challenging. The decision to pursue this should weigh the uncertainties about the parameter’s significance in determining community benefits, with the time commitment needed to collect this information.

This parameter would be suitable to include in a socio-economic analysis framework, but the ability to source the level of data required is challenging.

Project size or energy yield

This measure is quantifiable, based on the level of energy capacity installed for each project expressed in MW. This data is available on the Local Energy Scotland’s Community Benefit Register and the Renewable Energy Planning Database (REPD). To enable a comparison between different technologies, it is important to convert installed capacity to expected energy yield as each technology has different levels of efficiency.

Capacity and energy yield are both inputs in the estimation of gross revenue. Therefore, inclusion of these metrics as stand-alone parameters in the framework would be duplicative and would correlate very highly with any revenue estimations. For this reason, these metrics would not need to act as stand-alone parameters in an analysis framework but could be used as inputs to the revenue estimation.

Deployment and operating costs

The total costs of developing and operating a renewable energy project captures an important financial aspect assumed to influence the level of community benefit commitment.

Developers noted that the developmental and operating costs impact the financial capacity for a project to provide community benefit. As with revenue, obtaining precise cost figures would involve direct input from project owners. Again, due to commercial sensitivities and challenges in accessing this data, estimating total cost of production might need to rely on publicly available sources. This can be done for a selection of technologies using the Department for Energy Security and Net Zero’s Levelised Cost of Electricity (LCOE) estimates.[45] It is worth noting that not all REPD project technologies are included in this resource, and hence, some projects will require mapping to the closest matching technology category. Despite this challenge, a basic methodology for estimating LCOE from generation technologies is outlined in Appendix D.

When looking at non-generation projects, i.e. storage projects, it is important to reflect the differences to generation projects in the calculation of costs. An analogous version of the LCOE is the Levelised Cost of Storage (LCOS), which uses charging cost as fuel cost and uses the discharged electricity instead of generated electricity. Given the lack of access to the necessary data it is not possible to accurately estimate LCOS for storage projects.

Given that project costs provide a direct link to the financial aspects that are assumed to influence community benefits, it is recommended to include this parameter in a socio-economic analysis framework.

Revenue and profit

Developers agreed that the amount of revenue generated by a project has an impact on their ability to deliver community benefits and the level of community benefits that can be offered.

Ideally, obtaining precise revenue figures would involve direct input from project owners. However, due to commercial sensitivities and challenges in accessing data, estimating revenue might need to rely on publicly available sources. It is important to note that this approach is based on significant assumptions that might not hold true over time. Estimating future revenues is particularly challenging because it depends on projected electricity prices, which are notoriously difficult to predict with accuracy or extend into the future. Despite these challenges, a basic methodology for estimating revenues from generation technologies is outlined in Appendix D.

When it comes to non-generation projects, revenue estimation becomes even more complex and uncertain. These types of projects may involve diverse sources of income and variables, requiring a more nuanced approach to estimation. Battery storage projects generate revenue through a variety of mechanisms, often stacked together to maximise returns. Key revenue streams include arbitrage (buying electricity when prices are low and selling it back to the grid when prices are high), grid services (e.g. frequency regulation, voltage support), capacity market participation and ancillary services (e.g. black start capability). The lack of publicly available data for each of these revenue streams make it challenging to estimate revenue for non-generation projects.

Given that revenue estimation provides a direct link to the financial aspects that are assumed to influence community benefits, it is recommended that consideration is given to including this parameter in a socio-economic analysis framework.

Land use, visual and environmental impacts

There are several challenges associated with quantitatively measuring land use, visual, environmental and social impacts:

  • Quantifying land use involves assessing the physical footprint of a project, which can vary significantly based on the type and scale of the renewable technology employed. Further challenges arise in comparing land use impacts across different technologies, such as wind farms versus solar arrays, as each may occupy land differently (e.g., spacing between wind turbines versus solar panel coverage). These differences between technologies were also noted by developers.
  • Visual impact assessments are inherently subjective and can vary depending on individual perspectives and local landscape characteristics. Moreover, accurately quantifying visual impacts requires sophisticated modelling tools and surveys that consider factors like visibility range, landscape context, and viewer sensitivity.
  • Comprehensive environmental impacts involve a multitude of factors, including potential effects on local wildlife, ecosystems, water resources, and biodiversity. Data collection for environmental impacts may be inconsistent and require long-term monitoring to capture seasonal or cumulative effects accurately.
  • Social impacts can include effects on local communities, employment opportunities, and cultural shifts, which are difficult to measure quantitatively and may require qualitative research approaches. In addition, assessing social impacts often involves engaging with communities and stakeholders, which can introduce variability and complexity in data collection and interpretation.
  • Each of these aspects often interacts with others, making it challenging to isolate and assess impacts individually without considering cumulative or synergistic effects. Variability in methodologies and data availability can also lead to inconsistent measurements and comparisons.

For these reasons, this parameter is not suitable for a socio-economic analysis framework.

Wider economic impact of the project and its distribution

Renewable energy projects, especially large-scale ones, often generate significant economic benefits. For example, they may create high-value jobs through operation and maintenance, enhance the local supply chain and attract inward investments. These contributions can lead to substantial regional development and improved economic resilience.

However, there are notable challenges in confining these benefits strictly to the local communities most directly impacted by the projects. Economic effects often extend beyond the immediate vicinity. Moreover, quantifying these impacts presents difficulties, often necessitating self-reported data from projects. Such data can be subject to bias and may not fully capture the comprehensive economic changes occurring in the region. These challenges were reflected in interviews with developers. They noted that projects can add a lot of value to an area through high-value jobs, contribution to the supply chain and driving inward investment. However, they noted that it would be difficult to define this parameter, since the economic impacts may not be contained to the specific community in question. Projects can also incur wider costs, such as seabed option fees and rental fees for offshore wind renewable energy developments and these funds can have a wider economic impact.

Additionally, this metric’s applicability varies with different project types. For instance, projects involving CCUS often repurpose existing infrastructure, without necessitating a new workforce. As a result, the direct local economic impacts of such projects might be limited, underscoring the need for careful consideration when using this metric to assess community benefit commitments.

Wider economic impact provides a valuable lens for understanding potential benefits. However, the challenges and variability associated with measuring and applying this parameter across project types should be carefully evaluated to ensure fair, accurate and consistent community benefit determinations. For these reasons, this parameter is not suitable for a socio-economic analysis framework.

Community involvement and capacity

During interviews, developers suggested that community involvement and capacity influence the ability to provide community benefits and should be considered as part of a framework. This parameter focuses on the role of communities in both shaping and managing the benefits derived from renewable energy projects. Interviewees highlighted that placing community needs at the core is essential for ensuring that the type and level of benefits align with local priorities. They emphasised the importance of community engagement, consultation, and feedback in moulding these initiatives, arguing that this involvement leads to more meaningful and tailored contributions.

Additionally, while not directly impacting a developer’s ability to offer community benefit, the capacity of communities to effectively manage and deliver agreed benefits was seen as important. Interviewees pointed out that variations in the size and organisation of community councils or other community groups can significantly impact their ability to administer benefits. Hence, recognising these differences allows developers to support and enhance the local capacity, fostering increased participation and benefit realisation from the projects.

However, there are several challenges to quantitatively measuring these aspects. Quantifying community engagement and feedback is subjective, as perceptions of effective engagement vary among stakeholders. Communities often have diverse and evolving needs, making standardisation difficult. Additionally, while the number of consultations can be counted, assessing their quality requires qualitative data, which is harder to quantify. Asking the community to accurately capture and record this data would put significant burden on individuals who quite often are volunteers in the community. Moreover, community needs can change over time, necessitating ongoing updates and flexible metrics.

Due to these challenges, it is not recommended to include this parameter as a stand-alone element in a socio-economic analysis framework.

Conclusion

Following the assessment outlined above, four parameters were deemed suitable to be considered in a socio-economic analysis framework. These were:

  • Technology maturity
  • Market maturity
  • Deployment and operating costs
  • Revenue and profit.

To demonstrate how a framework could be used in future, socio-economic analysis has been carried out based on a sample of data on renewable energy projects (see Appendix C). The parameters in scope of this analysis are restricted to those which have been deemed feasible to measure and for which a suitable method to measure them has been identified. This analysis is based on data available from the Community Benefits Register Database, supplemented with additional data sourced through desk research. Due to the data sources available, it only includes onshore wind, offshore wind and hydro technologies.

Key findings from that analysis are:

  • Industry alignment and policy influence: While many onshore wind and hydro projects in Scotland are clustering around the recommended annual £5,000 per MW capacity for community benefits for onshore technologies, more than half of the onshore wind and hydro projects analysed in the available data set commit less than the recommended amount.
  • Revenue-benefit correlation: A positive correlation exists between gross project revenue and total community benefit commitments, with larger projects providing bigger packages. However, this relationship weakens for high-revenue projects, suggesting a potential plateau effect.
  • Costs and benefit packages: There is a positive correlation between total cost of production and total community benefit packages across all project sizes, suggesting that as total costs increase, so does the size of the overall commitment to community benefits. While this may appear contrary to the views of developers shown earlier (i.e. those who said that high costs can impact on financial viability and therefore their ability to offer community benefits) it should be noted that this data analysis is based only on projects already providing monetary benefits. It excludes those that had not yet provided any community benefits. It can therefore be assumed that the dataset excludes those projects that were deemed not financially viable enough to enable community benefit provision.

In interpreting these findings and considering next steps it is important to acknowledge the distinction between the willingness of projects (measured by actual provision) to provide community benefits and their ability to provide community benefits. The analysis above is based on actual provision of community benefits. It could be assumed that these commitments are indicative of both willingness and some inferred level of ability, but the data does not allow for an assessment of the capability of projects (and different technologies) to offer these benefits. The UK Government’s Contracts for Difference (CfD) scheme is the main support mechanism for renewable energy projects. It is important to acknowledge that although community benefit funds are not recognised costs in the CfD framework, they are often treated as part of a project’s overall cost base and priced in to CfD bids.

Robust analysis of the capability to provide community benefits would require detailed project-level data. To collate the data needed will require considerable resources and will also require renewable energy technology developers to share data they perceive as commercially sensitive, which may be unrealistic. This work has highlighted considerable data gaps, challenges collecting data in the future and difficulty in sourcing data specifically focused on future ability to offer community benefits rather than actual performance. Therefore, the approach explored here does not provide a robust enough evidence base to underpin a framework for use as a decision-making tool.

To better understand the capacity for projects to provide community benefits, it is suggested that further research and / or alternative approaches may be needed. This could take the form of qualitative research with a larger selection of projects across the full technology spectrum, to understand perceived barriers or enablers of moving from willingness to ability. This should offer insights into the practical challenges faced by projects. Longitudinal case studies may prove beneficial to understand how changes in policy, economic conditions or market incentives could have influenced both the willingness and perceived capacity to make these commitments.

Exploring mandatory community benefit arrangements

This chapter looks at current approaches to mandating found in the evidence review and the views of the industry on how mandating community benefits for onshore technologies could work in practice, based on qualitative research with developers.

Key findings

  • Mandatory community benefits approaches exist in Denmark and Ireland, as part of renewable energy infrastructure development for wind projects. However, the literature reviewed does not allow for a satisfactory comparative analysis of the in-practice impacts of mandatory versus voluntary approaches.
  • Existing onshore developers felt that the following factors would need to be considered for mandating to work in practice:
  • clear guidance on the financial expectation attached to mandating
  • accounting for differences between individual onshore technologies
  • retaining a degree of flexibility, particularly in terms of the ability for community benefits to be designed around the needs of communities
  • avoiding overly burdensome processes.

Current approaches to mandating community benefits

Mandatory community benefits as part of net zero energy infrastructure development exist in Denmark and Ireland, specifically for onshore and offshore wind projects. Other countries have mandated approaches for shared ownership, special taxes, energy subsidies, or monetary compensations, but not community benefits as defined here. This includes Germany, France, Taiwan, and the Philippines [46].

Denmark has a history of various mandates relating to community benefits. For example, until 2018, the “Green Scheme” required the Danish state to pay hosting communities a fixed amount per kWh of production from new turbines. This applied to offshore wind farms built outside the tender process and within 8km of shore.[47] More recently, as of June 2020, regulations require offshore wind developers to pay fixed amounts per MW installed into green funds for affected municipalities. The payment is DKK 115,000 per MW (around €15,500).[48] Additionally, in Ireland, renewable energy auctions mandate that developers contribute €2/MWh to a community benefit fund, with defined criteria for how the funds must be spent.[49]

Other mandated approaches similar to community benefits include special taxes imposed on developers, that are distributed to local authorities, and electricity subsidies for “host communities”. The former approach has been implemented in France and Germany. The French Maritime Wind Turbine Tax is imposed on offshore wind farms, and is allocated to local authorities to finance local projects, per a defined formula. Germany requires that tax revenue generated from offshore wind farms in the Exclusive Economic Zone is distributed to coastal states. Energy subsidies for host communities have been implemented in the Philippines and Taiwan. Since 2008, the Philippines has required that 80% of money generated from royalties, or government shares in renewable projects, must be used to subsidise the electricity costs of communities affected by these projects.[50] In Taiwan, the Electricity Assistance Fund (EAF) is distributed to communities affected by power plant projects (including, but not limited to renewable energy) according to a pre-defined formula. For example, in the case of offshore wind, 30% of EAF funds are provided to “local project fund pools” for the benefit of residents, community groups, and civil society organisations, and 70% is provided for councils and fishery associations.[51]

Although shared ownership is seen distinct from community benefits in Scotland, some other countries have mandated shared ownership or compensation payments. For example, in Denmark, the 2008 Renewable Energy Act mandated developers to offer at least 20% of shares in wind projects for sale to local households within 4.5km of a turbine.[52] Similarly, in Germany, several states have required that between 10% and 25% of wind farm shares be offered to local residents and municipalities. Mandated compensation payments to nearby residents and community funds have been implemented in Denmark and Ireland. Since 2020, Irish legislation obliges wind farm developments to provide an annual contribution to nearby households and communities.

While some of the literature reviewed implies that mandated approaches are more robust,[53] no clear evidence is provided of their outcomes and impact compared to voluntary approaches. The literature does not allow for a satisfactory comparative analysis of the in-practice impacts of mandatory versus voluntary approaches.

Developers’ perspectives on how mandating community benefits could work in practice

Industry stakeholders shared their views on the potential for mandating community benefits for onshore technologies. Mandating was explored in both the scoping interviews with representative bodies and in the main interviews with developers. Developers highlighted some key considerations that they felt should be borne in mind for how mandating could work in practice.

For mandatory community benefits to work in practice, developers felt that there would need to be clear guidelines on what the financial expectation is to avoid any potential for confusion. It was suggested that the community benefit value attached to any mandated approach should be realistic and determined in collaboration with industry to help clarify what the expectations are for developers and for communities.

To work in practice, it was felt that mandatory community benefits would need to take into account the differences between different technologies. For example, by having different levels of benefits that technologies are expected to contribute. Specifically, some interviewees highlighted the different operating contexts and economies (e.g. different capital costs) between some technologies. Further, it was suggested that hydrogen and CCUS should be treated differently because they are designed to complement renewable technologies by operating only when needed. Therefore, it was argued that it is difficult to tie community benefits to specific metrics for these.

“[If] it would be used to set an X amount per megawatt, [then] that would need to be split into different technologies because it’s not a clear cut case for all technologies. It has to show this is what it is for BESS, what is for wind, what is for solar. Because if you get that number wrong, you can make the scheme unviable or unattractive and therefore it will not come forward.” – BESS stakeholder

It was also felt that for mandating to be practical, the approach to community benefits should retain some degree of flexibility and the ability to be designed around the needs of individual communities. For example, one onshore and offshore wind developer said if mandating were to happen it should be around the amount of funding that should be provided and not how communities spend the money. This view echoes findings of a report by BiGGAR Economics (2023) that states that the current voluntary system has allowed communities and developers to be flexible in their arrangements, and has enabled the “formation of mature, collaborative relationships” between parties. [54]

Related to the point above, some developers felt that, in practice, mandates could mean a more bureaucratic process which could slow things down, in turn impacting developers’ ability to deliver benefits. Stakeholders made contrasts with the current system, which was perceived as “fairly simple” and “flexible”. Therefore, it was suggested that approaches to mandates should avoid overly burdensome processes and bureaucracy. For example, it was suggested that it should avoid having too many restrictions around timescales or conditions on how communities should spend the funding.

Another view from developers was mandating might impact on the existing relationships between developers and communities, as it could move away from a collaborative process to one where there is a firmer expectation around what developers are required to give. Therefore, the approach would need to consider the relationships between developers and communities. Developers particularly felt it important to avoid community benefits appearing like compensation. For example, it was felt that creating a mandated system through which a certain amount is paid made directly to homeowners could lead to the system feeling like a form of compensation.

“If it’s mandated, it absolutely can’t be attributed as compensation to the community. If money had to be paid to compensate people for the effects of a wind farm, then the wind farm shouldn’t be being built.” – Multi-technology stakeholder

Aside from practicalities, a key concern raised was that mandating community benefit provision could risk investor confidence. Some developers felt that mandatory community benefits would have an impact on financial viability of projects, which could make investors less confident to invest. It was suggested that they may choose to invest in projects in other countries that do not have a community benefit mandate or in which they feel the approach is more straightforward.

“The danger with [mandating] is that it creates investor concerns. There’s a lot of competing geographies around the world that want money for renewable energy projects…If one country becomes difficult or the risks are harder to understand, they’ll move that investment to another country where they understand it. And the UK, and especially Scotland, runs a real risk of upsetting investor confidence, which is already very delicate because of the situations with the grid at the moment.” – Solar PV stakeholder

As the scope of this research was focused on understanding how different renewable technologies influence the level of community benefits offered by developers, interviews were conducted with a sample of renewable energy developers. A wide range of other stakeholders will have views.

Adjustments needed to Scotland’s current voluntary community benefits approach

This chapter sets out the extent to which any adjustments are required to the current voluntary community benefits approach based on findings from the literature review, interviews with developers and the design and testing of a socio-economic analysis framework.

Key findings

  • This research has not identified any obvious adjustments that need to be made to Scotland’s current community benefit approach. Developers felt that the current system could better acknowledge the different realities of different technologies, but they were not specific about what the best future approach should be.
  • Developers felt that guidance from the Scottish Government, in the form of Good Practice Principles and a recommended level of community benefit for onshore projects was a strength of the current process. However, for projects of emerging and/or non-generative technologies, developers noted that more targeted guidelines would be beneficial, noting that there is no established industry standard approach.
  • The intention was that the framework in this study could be used by Scottish Government to determine an appropriate expectation of the level and types of community benefit required for different renewable energy technologies. This work identified significant data gaps, challenges collecting data in the future, and the difficulty in sourcing data specifically focused on future ability to offer community benefits rather than actual performance. For these reasons, the framework explored here is not robust enough to use as a decision-making tool.

Lessons from literature and developers’ views

Based on the literature reviewed, there is limited evidence directly comparing how the different community benefit approaches in the UK and in other countries have impacted the level of community benefits delivered. Similarly, there is limited evidence to compare the impacts of mandated and voluntary approaches. International examples do not therefore provide any obvious lessons for the current approach in Scotland.

Onshore wind developers interviewed as part of this study were largely satisfied with the current arrangements. They felt that having a recommended standard (of £5,000 per MW per year for onshore) works well, helping them to predict what the cost associated with each project will be. Since it is a recommended, rather than compulsory standard, they also felt that it also allows for a degree of flexibility, meaning that the community benefit contribution can be responsive to both project and local community needs.

“That financial outlay [£5,000 per MW per year] is much more predictable in our models that we bake in during development…we actually really try to make sure that we can deliver it and protect it.” – Multi-technology developer

Developers of some less well-established technologies (e.g. hydrogen and pumped hydro storage) expressed a desire for clearer guidance from government on the appropriate levels of community benefit for these technologies. They suggested that new guidelines around levels of community benefit should take into consideration the differences in scale and impact between projects like pumped storage and hydrogen generation, which can be more expensive and less visible than wind projects. Those from non-generative technologies (e.g. BESS) felt that it is more difficult to determine the amount of community benefits (funds) that can be delivered from these projects because they have lower level of return (they do not yield energy) and serve a different function in the energy market than generation projects.

Developers also suggested that further structure and support for communities could help them to manage funds more effectively. They felt that community-led decision-making was vital for ensuring the funds meet local needs, but that this should be balanced with adequate administrative support to prevent the misuse or underutilisation of funds.

“There is also a misconception that communities are underspending this funding. Our analysis shows that if we invest and empower communities, then they are very capable of delivering impactful projects.” – Multi-technology developer

Lessons from testing a framework approach

As noted earlier, to effectively measure parameters identified in the proposed framework, project-level data would be required on costs, revenue, technology readiness levels and market maturity. Data on these metrics is not currently available and collecting this data would be a significant task.

Developers felt that certain parameters (see chapter 4) were considered suitable for a socio-economic analysis framework. However, their limited testing means that the framework would need more comprehensive data to fully model these parameters’ effects on community benefits. This is especially true for community benefit commitment data (£/MW/yr) which currently is only reported in the Community Benefits Register Database for onshore wind and hydro projects.

When discussing the idea of such a framework, developers noted that community benefits should not have a one-size-fits-all approach and should be reflective of specific circumstances of each technology and each project. Concerns were raised by some interviewees that a framework might lead to overly prescriptive approaches which could risk stifling development and deterring investment.

“Each [parameter] is relevant and I can see why they have been captured as things that would influence the value and viability of community benefits […] It all depends on an individual project basis, depends on what else is happening in terms of landscape and development.” – Multi-technology developer

Interviewees also questioned whether sufficient data would be available to support the framework and there was some concern about using historic data to understand future community benefit levels. A few interviewees also highlighted concerns about data sensitivity and need for any information to be carefully handled.

Considering the data gaps, challenges collecting data in the future, and the difficulty in sourcing data specifically focused on future ability to offer community benefits rather than actual performance, a single framework may not be the most appropriate approach.

Conclusions

This research looked at current and future approaches to community benefits to help inform decisions around future provision of community benefits in a way that is fair and consistent. This chapter draws conclusions around the three broad research aims:

  • To understand how different renewable energy technologies affect the capacity of developers to provide community benefits, including developing and testing a socio-economic analysis framework.
  • To understand how mandating community benefits could work in practice for onshore renewable energy technologies.
  • To help identify any necessary adjustments to the Scottish Government’s current voluntary community benefits approach for onshore and offshore to better support communities and industry as part of a just transition.

Understanding how different renewable energy technologies affect community benefits

Within the scope of this study, the available evidence did not support a single framework to robustly determine how different technologies affect community benefits. For such a framework to work as a practical, decision-making tool, quantitative data on the economics of different renewable energy technology projects would be required. However, existing public data is sparse and of inadequate quality to effectively measure the parameters within a framework and many developers were unable or unwilling to share commercially sensitive data about their projects. A further limitation was that existing data (e.g. on the value of community benefits from individual renewable energy projects) is based on actual provision rather than an assessment of project’s potential ability. Additionally, data available is largely historical and challenging to use when anticipating new technologies and emerging economic and regulatory models.

However, from data that was available, it was clear that the financial aspects of a renewable energy project (costs, revenue and financial viability) were key factors impacting the developers’ offer of community benefits. Projects with higher amounts of revenue and more robust and predictable financial returns are better positioned to offer significant community benefits. Conversely, if the financial viability of a development is low, then it is unlikely developers can offer community benefits without the project becoming non-viable. Developers noted that both technology maturity and market maturity can have an impact on a project’s financial viability and are therefore, indirectly, also linked to a project’s suitability to deliver community benefits. As discussed above, while there are existing tools for measuring technology and market maturity, data gathering is challenging.

Developers’ feedback also highlighted that it is easier to offer community benefits for more established technologies like onshore wind, compared to other technologies (e.g. solar and battery storage) due to the latter’s comparatively low profit margins. Less mature technologies (e.g., floating offshore wind, hydrogen) can have higher risks, higher delivery costs, less predictability in cost and performance, and lower investor confidence which can impact on their ability to offer benefits.

While not directly impacting on the level of community benefits offered, developers noted the importance of community engagement and capacity to effectively manage and deliver benefit funds. Interviewees highlighted the importance of community engagement, consultation and feedback in moulding community benefit initiatives, ensuring more meaningful and tailored contributions. However, this is difficult to quantify and would therefore be challenging to include in a socio-economic analysis framework.

How mandating community benefits could work in practice (for onshore renewable technologies)

The literature reviewed does not allow for a satisfactory comparative analysis of the in-practice impacts of mandatory versus voluntary approaches. Mandatory community benefits approaches exist in Denmark and Ireland, as part of net zero energy infrastructure development for wind projects. While the literature provides examples of where this was happening outside of the UK, it was less clear on the extent to which mandating had an impact on the level and nature of community benefits when compared with voluntary approaches.

Developers felt that for mandating to work in practice, a number of factors would need to be taken into consideration. It was felt that any future mandating approach should allow for the differences between technologies to be accounted for by setting, for example, different recommended levels of community benefit fund value. For mandating to work in practice, it was also felt that flexibility was key, particularly in terms of how communities could make use of the funding provided. Practicalities aside, there was some concern that mandating could potentially pose a risk to projects, by placing a financial burden on some projects (particularly those with smaller financial returns such as solar and BESS technologies) which could pose a risk to investors.  

Any necessary adjustments to Scotland’s current voluntary community benefits framework for onshore and offshore

This research has not identified any obvious adjustments that need to be made to Scotland’s current community benefit approach.

Guidance from the Scottish Government, in the form of best practice principles and a recommended level of community benefit for onshore projects was highlighted in interviews with developers as being a strength of the current process. However, developers’ feedback suggests the current system needs to better acknowledge the different realities of different technologies. Developers of emerging and non-generative technologies suggested that more targeted guidelines for these newer technologies would be beneficial, noting that there is no established industry standard approach. However, while they suggested some areas for consideration, they were not specific about what the best future approach should be.

The intention was that the framework in this study could be used by the Scottish Government to determine an appropriate expectation of the level and types of community benefit required for different renewable energy technologies. The parameters that were considered suitable for the framework could provide a useful understanding of the factors that influence ability to offer community benefits. However, this would be dependent on data gaps being addressed. Ideally, it would have up-to-date data on community benefit value covering the full range of renewable energy technologies, with at least 50 projects for each technology.

This study has identified data gaps, challenges collecting data in the future and the difficulty in sourcing data specifically focused on future ability to offer community benefits rather than actual performance. The approach explored here does not provide a robust enough evidence base to underpin a framework for use as a decision-making tool.

Recommendations and next steps

The report highlights existing measurement tools and guidance that can be used to understand where a project sits in relation to certain parameters, such as technology and market maturity. To make the most of these tools, further data collection work would be needed before they could be used for robust socio-economic analysis. This would involve collecting relevant data for a representative sample of projects across the metrics that have already established measurement tools. This would require a significant time and resource commitment and may not, therefore, be a practical option.

To better understand the factors influencing the level of community benefit, beyond the financial indicators highlighted in this study, further research would be needed. Considering the challenge of sourcing quantitative data on project economics, further qualitative research may be the most feasible option. Ideally this would be with a larger selection of developers across the full technology spectrum (including those that had not been able to deliver community benefits), direct engagement with communities, and wider stakeholder engagement (e.g. project investors, funders and other partners that have assisted in project development). This type of engagement would add to and build on the insights gathered from developers in this study.

Glossary / abbreviations table

Acronym/Abbreviation

Definition

ARL

Adoption Readiness Level

BESS

Battery energy storage system

BWE

German Wind Energy Association

CCUS

Carbon capture utilisation and storage

EAF

Electricity Assistance Fund

ESG

Environmental, Social, and Governance

GW

Gigawatt

IEA ETP guide

International Energy Agency’s Energy Technology Perspectives guide

LCLO

Local Community Liaison Officer

LCOE

Levelised Cost of Electricity

LCOS

Levelised Cost of Storage

MW

Megawatt

NASA

National Aeronautics and Space Administration of the United States

REPD

Renewable Energy Project Database

SROI

Social Return on Investment

TRL

Technology Readiness Level

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Appendices

Appendix A – Methodology

Evidence review

Aims and objectives

The aims of the evidence review were to:

  • Explore best practice on community benefits in the UK and internationally in relation to renewable energy technologies.
  • Explore how community benefit schemes operate and examine their funding arrangements in the UK and internationally.
  • Provide examples of where community benefits have been mandated and what impact this has had on industry, communities and the delivery of renewable energy technologies.
  • Inform the socio-economic analysis in terms of identifying key parameters and contexts that impact the propensity to supply community benefits at varying scales.
  • Identify data sources for the socio-economic analysis.

Defining the research questions

To ensure the evidence review is useful in summarising best practises and informing the socio-economic analysis the following research questions were defined:

  • Research Question 1 – What is the best practice on community benefits from onshore and offshore renewable energy technologies internationally?
  • Research Question 2 – How does the UK differ from international counterparts on the processes on the provision of community benefits? How does this impact the level of community benefits?
  • Research Question 3 – Which (if any) countries mandate community benefits as part of net zero energy infrastructure construction? What impact has this had on the provision of community benefits? What impact has this had on communities and the delivery of net zero energy policies?
  • Additional Scoping – What data is available on the levels of community benefits, and their corresponding technologies/market maturities/technology maturity and other hypothesised parameters which influence the provision of community benefits?

Scope of the literature search

The literature search included the identification of relevant sources from:

  • Existing research into/evaluations of community benefit schemes
  • Academic literature
  • Grey literature
  • Policy documents
  • Media publications

The search for literature was primarily done through using Google and Google Scholar but also used sources such as JSTOR, Scopus, and organisational websites where necessary. Whilst we did not take a strict view on the geographical scope of our search, we favoured countries which are contextually similar to the UK (European countries, US, Australia) as it is likely these findings will be more relevant to the UK.

We explored literature relevant to onshore and offshore renewable energy technologies. This included, but was not limited to, wind, solar, hydro, wave, thermal, pumped hydro storage, bioenergy, battery storage, hydrogen, Negative Emission Technologies (NETs) and transmission infrastructure. The ability to look at these internationally was dependent on the context and energy mix of the countries in question. It was decided that it would also be useful to assess levels of community benefits for technologies which may be emerging in the UK but are more established elsewhere, bringing in the Three Horizons approach featured in the proposal.

Search Terms

Some initial search terms for covering the aforementioned specifications and research questions were developed and are presented in the table below:

Search Term (Google/Google Scholar)

Relevance/comments

“[insert technology] community benefits best practice [international/UK/insert country]”

All technologies and internationally. This will support answering RQ1 and part of RQ2 by allowing for a comparison between countries.

“[insert technology] community benefits monitoring [international/UK/insert country]”

All technologies and internationally. This will support answering RQ1 and part of RQ2 by allowing for a comparison between countries.

“[insert technology] community benefits evaluation [international/UK/insert country]”

All technologies and internationally. This will support answering RQ1 and part of RQ2 by allowing for a comparison between countries.

“[insert technology] community benefits lessons [international/UK/insert country]”

All technologies and internationally. This will support answering RQ1 and part of RQ2 by allowing for a comparison between countries.

“[insert technology] community benefits impacts [international/UK/insert country]”

All technologies and internationally. This will support answering RQ1 and part of RQ2 by allowing for a comparison between countries.

“[insert technology] community benefits funding arrangements [international/UK/insert country]”

All technologies and internationally. This will allow us to understand the structure of community benefit funds, supporting RQ1 and RQ2

“[insert technology] community benefits management arrangements [international/UK/insert country]”

All technologies and internationally. This will allow us to understand the structure of community benefit funds, supporting RQ1 and RQ2

“[insert technology] mandate/mandated/mandating community benefits [international/UK/insert country]””

All technologies and internationally. This will provide an answer to RQ3, where we can begin to assess the impact of mandating community benefits and what this looks like in practise

“[insert technology] community benefits press release”

This search supports the scoping of what is feasible for the socio-economic analysis. At this stage, a high-level search will be conducted, with more in depth web scraping for data (if possible) to be completed as part of the socio-economic analysis.

Prioritisation approach

A long list of 86 sources were initially identified which were then prioritised using the prioritisation criteria set out below:

  • Based on existing evidence: Does the document focus on existing practice/examples of renewable projects/developments?
  • Focus on community benefits: Is the main focus of the document around the provision of community benefits (as opposed to for e.g. broader discussions of social acceptability of renewable energy developments OR community engagement)?
  • Policy guidance: Does the document include policy recommendations/best practice guidance/reflections on lessons learned?
  • Geographical scope: Does the geographical scope of the document include Europe, the UK or US?
  • Peer reviewed / grey literature: Peer reviewed sources were prioritised over grey literature sources.

Additional considerations:

  • Ensuring the inclusion of evidence on a wide spread of renewable technologies.
  • Ensuring the inclusion of evidence from both voluntary and mandatory community benefits schemes.
  • Ensuring the inclusion of evidence from a wide spread of types of community benefits.

Additional sources were added to the short-list of literature as suggested by Scottish Government and stakeholders in the scoping interviews. A total of 35 sources were reviewed in-depth. The final list of literature sources reviewed included 12 peer reviewed academic papers, 20 reports, 2 guidance documents from grey literature (e.g., renewable energy developers, private consultancies) and 1 policy document. The publication years of the reviewed documents ranges from 2011 to 2024, with 22 documents from the last 5 years.

Evidence extraction

The prioritised literature sources were then reviewed and findings relevant to the research questions were extracted into an excel sheet. Ipsos Facto, a Large Language Model, was used to assist with identifying and summarising relevant data.

Scoping interviews

In parallel to the evidence, we conducted four in-depth scoping interviews with industry bodies, trade associations, and members of developer groups to enhance the findings from the evidence review.

The aim of these interviews was twofold:

  • to understand their views on different types of community benefits and their perceptions of current / best practice arrangements related to community benefits;
  • to explore options for sourcing data from the industry, including the types of information they think businesses will / will not be prepared to share with us.

Learnings from the scoping interviews were used specifically to inform the design of the subsequent stakeholder engagement and framework development.

Developer interviews

In-depth interviews were conducted with 21 industry developers. Interviewees covered a range of technologies including onshore wind (7), offshore wind (7), solar PV (5), battery storage (6), grid stability (1), hydro (3), pumped hydro storage (3), hydrogen (6 including 2 green hydrogen) and carbon capture, utilisation and storage (2). Among interviewees, 11 were mostly multi-technologies developers and 10 were single-technology developers.

The objectives of the interviews were threefold:

  1. To gather qualitative data on the types of community benefits they have delivered/plan to deliver, views on current arrangement for community benefits and potential different approaches (including mandating for onshore), and what factors have contributed to the provision/ success of their community benefits (i.e. to help inform what parameters are most important in informing potential future community benefits). This will help contextualise the socio-economic analysis and the findings in the report.
  2. To gather quantitative data that we will then use in our analysis, using the parameters set out in the framework (these will be developed further based on CXC/SG feedback). This will include information such as the cost of developing the project(s), value of community benefits, proportion of those values in comparison with turnover/profit, employment impacts etc.
  3. To help reframe/revise the socio-economic analysis framework as required, based on their views on what parameters/variables are important
  4. Ahead of the interview, stakeholders were also requested to complete a ‘Data request sheet’ that aimed to gather data for the socio-economic analysis (see below).

Framework development

The development of the framework to assess the influence of various parameters on community benefits involved a systematic approach following stakeholder interviews. Each initial parameter underwent a comprehensive evaluation to determine the feasibility of its measurement and potential impact on community benefit commitments.

  • Assessment of measurement challenges. Initially, each parameter was scrutinised to identify any inherent challenges or limitations in its measurement. This involved examining the complexity, availability of data, and any factors that could hinder accurate quantification.
  • Identification of pre-existing measures. For parameters where it was determined that measurement challenges were minimal or non-existent, existing methodologies and measures were sought. This step involved a thorough review of established metrics and tools already in use.
  • Development of proxy measures. In cases where no established measures were applicable, proxy measures were devised. This involved identifying the closest available data that could serve as a stand-in to approximate the parameter’s influence on community benefits. These proxies were selected based on their relevance and potential to offer meaningful insights.

Throughout this process, each parameter’s potential to influence community benefits was evaluated. This iterative methodology ensured a robust and nuanced framework, capable of effectively guiding future assessments and decisions concerning community benefit commitments.

Socio-economic analysis

To illustrate the application of the framework, a socio-economic analysis was conducted using a sample dataset of renewable energy projects. This analysis examined the relationship between the parameters detailed in Section 5 and the levels of community benefits, employing the methodologies outlined in the framework.

The analysis focuses on parameters deemed feasible to measure with available methods, specifically revenue and costs, along with technology type. Technology type was used as a proxy for technology maturity, given the current uniformity of maturity levels within each technology. The analysis relied on data from the Community Benefits Register Database, supplemented by additional information obtained through desk research.

For this analysis, the scope included onshore wind, offshore wind, and hydro technologies. These were chosen based on their data availability and relevance to the parameters evaluated.

Appendix B Examples of community benefit-sharing initiatives

Table 2 Examples of community benefit-sharing initiatives and related guidance for renewable technologies in selected European countries (from O San Martin et al. (2022)

Country

Guidance document

Scope of initiative

Scotland

Scottish Government: Onshore Wind Policy Statement (2017); Scottish Government: Good Practice Principles for Community Benefits from Onshore Renewable Energy Developments (2019 Update); and Good Practice Principles for Community Benefits from Offshore Renewable Energy Developments (2018)

Wind farm operators currently utilise both community funding options and shared ownership, both are seen as good practices and responsive to the local community’s specific wishes.

England

Community Benefits from Onshore Wind Developments: Best Practice Guidance for England (2021)

Both a community benefit fund and community shared ownership are recommended. Noted that many developers are providing funds significantly below the recommended amount.

Ireland

Code of Practice for Wind Energy Development in Ireland Guidelines for Community Engagement; and Best Practice Guidelines for the Irish Wind Energy Industry (2012)

ORESS 1 Community Benefit Fund – Rulebook for Generators and Fund Administrators (2023)

Irish wind farm operators currently offer both community funding options and shared ownership; both are seen as good practices.

Netherlands

Dutch Wind Energy Association (NWEA): Code of Conduct for Acceptance & Participation of Onshore Wind Energy (2016)

Both a community benefit fund and community shared ownership are acceptable, but shared ownership is generally preferred and expected by local communities.

Germany

German Wind Energy Association (BWE):

“Collectively Winning – Local Wind Energy”: Framework Paper for the topics added value, public participation, and acceptance (2018);

“Citizen-owned Wind Energy” – Energy from the region for the region (2013)

Best practice in Germany heavily tends towards community stakes/shared ownership in wind farms as the main model of how communities benefit. In contrast, the community funding model is less well-received in Germany.

Appendix C Socio-economic analysis results

To demonstrate how the framework could be used in future, socio-economic analysis was carried out based on a sample of data from net zero energy projects. This analysis explores the relationship between the parameters outlined in chapter 4 and the levels of community benefits, using the methods outlined in the framework.

The parameters in scope of this analysis are restricted to those which have been deemed feasible to measure and for which a suitable method to measure them has been identified These include revenue and costs, as well as technology type (which serves as a proxy for technology maturity, as maturity levels do not vary within technologies currently). It should be noted that this analysis is based on data available from the Community Benefits Register Database, supplemented with additional data sourced through desk research. Due to the data sources available, it only includes onshore wind, offshore wind and hydro technologies.

The subsequent analysis in this chapter presents the relationships between the measurable parameters for which data is available and the level of community benefits.

Key findings

  • Industry alignment and policy influence. Many onshore wind and hydro projects in Scotland are clustering around the recommended annual £5,000 per MW capacity for community benefits for onshore technologies. However, a significant number of onshore wind and hydro projects (more than half of those analysed in the available dataset) commit less than the recommended amount.
  • Revenue-benefit correlation. A positive correlation exists between gross project revenue and total community benefit commitments, with larger projects providing bigger packages. However, this relationship weakens for high-revenue projects, suggesting a potential plateau effect.
  • Costs and benefit packages. There is a positive correlation between total costs and total community benefit packages. For projects costing less than £25 million, when comparing onshore wind and hydropower projects of the same energy capacity and with equivalent community benefit budgets (£5,000 per MW annually), onshore wind offers greater community benefits per pound spent on energy production.

Analysis of community benefit commitments

Many onshore wind and hydro projects in Scotland are aligning with the recommended community benefits package of £5,000 per MW capacity. The clustering of commitments around the recommended amount suggests that policy guidelines are influencing industry behaviour, but full compliance among onshore projects has not yet been achieved. This is observed in Figure 1 by the number of projects committing less than the recommended amount. Of the 282 onshore wind and hydro projects analysed, 177 were committing less than the recommend amount.

There exists a small but notable group of projects that have committed to providing community benefits from onshore renewable energy developments above the recommended £5,000 per MW capacity. These projects may be setting new benchmarks for corporate social responsibility. The strong concentration around the £5,000 figure could indicate an opportunity for standardising community benefit packages across the industry, potentially simplifying expectations for both developers and communities.

Figure 1 Distribution of Annual Community Benefit Commitments per MW – Onshore Projects

Source: Community Benefits Register Database

Figure 2 below illustrates where most of the data points are concentrated and the variation in the data. There are distinct patterns in community benefit commitments across the two different onshore renewable technologies shown. Figure 2 shows that hydro projects commitments range between £456 and £5,000 per MW per year, while onshore wind commitments range between £60-£20,000 (the upper end of this range is not visible in Figure 2 below as this distorted the shape and scales of the figure).

There is a concentration of commitments around the £5,000 figure for both hydro and onshore wind which aligns with the recommended amount (as demonstrated by the width of the violin plot), indicating a level of industry-wide acceptance of this guideline for land-based projects.

Figure 2 Distribution of Annual Community Benefit Commitments per MW by Onshore Technology

Source: Community Benefits Register Database

Figure 3 below shows the distribution of community benefit commitments among offshore projects. It should be noted that there was very low coverage of offshore wind projects captured in the register, and hence efforts were made to manually collect benefits data through desk-based research. This may have resulted in some discrepancies in actual provision versus what projects would have reported through the register. Figure 3 shows offshore wind projects notably committing lower amounts compared to onshore wind and hydro projects, with a range between c.£20-£2,000 per MW per year. It is acknowledged here that this analysis is based on 21 projects out of a possible 47 operational offshore wind projects in the UK[55] and therefore figures should be treated with caution.

Figure 3 Distribution of Annual Community Benefit Commitments per MW – Offshore Projects

Source: desk research

There are several reasons why offshore wind projects might be committing lower amounts than their onshore counterparts. Most importantly, onshore renewable energy projects in Scotland are encouraged to offer community benefits, typically around £5,000 per megawatt of installed capacity annually. This is a voluntary guideline, not a requirement, specifically for onshore projects, and does not apply to offshore projects. Beyond this, offshore wind farms, being located further from communities, might be perceived as having less direct impact on local populations, potentially justifying lower community benefit packages. The offshore wind sector in Scotland is also at an earlier stage of development compared to onshore technologies, with community benefit standards still being defined. This technological and market immaturity means standards for community benefits are still evolving within this sector. In contrast, onshore wind technologies are more established and benefit from years of development and market experience. The advanced state of onshore wind technology may allow for greater efficiency and cost reduction, enabling more substantial community support relative to their offshore counterparts. Moreover, the scale of offshore wind projects may mean that while there are lower per-MW commitments, the overall total community benefits package may still be substantial.

Analysis of community benefit parameters and their impact

Revenue and profit

Figure 4 below illustrates the relationship between estimated gross revenue and total community benefit commitments over the project lifetime. The relationship is split and visualised by revenue levels due to the variation in the strength of the relationship as revenue changes. Blue dots represent projects that have committed £5,000 per MW per year, while red dots represent any figure other than the recommended £5,000 per MW. There is a clear positive correlation between gross project revenue and total community benefit commitments across all renewable energy projects in Scotland. This suggests that as projects become more financially substantial, they tend to provide larger community benefit packages. As project size increases in revenue terms, there is a widening range of community benefit amounts. This indicates that larger projects have more diverse approaches to community support. The relationship between gross revenue and community benefits appears to weaken for larger revenue projects. This suggests a potential plateau effect where community benefit increases do not keep pace proportionally with revenue growth beyond a certain point.

Small (under £35m gross revenue) and medium-sized (£25-250m gross revenue) projects frequently demonstrate commitment to the recommended £5,000 per MW amount, suggesting strong guideline adherence among projects of these scales. Across these sized projects, there are few instances of commitments exceeding the recommended amount relative to their revenue, suggesting a general reluctance to exceed standard guidelines.

 

Figure 4 Community Benefits Package by Gross Revenue Bucket (Under £25M, £25M-£250M and £250M+ Gross Revenue)

Source: See appendix F (Recommended data sources)

Deployment and Operating Costs

Figure 5 below shows the relationship between estimated total cost of production, expressed as the average cost of producing one unit of energy (LCOE – £/MWh) multiplied by total expected production over the project lifetime, and total community benefit commitments over the project lifetime. As above, the relationship is split and visualised by total cost of production levels due to the variation in the strength of the relationship as total cost changes. There is a positive correlation between total cost of production and total community benefit packages across all project sizes, suggesting that as total costs increase, as does the size of the overall commitment to community benefits. The correlation between total cost and total community benefit are relatively strong (Pearson correlation coefficient[56] = 0.56) at lower total cost levels (under £25M total cost). This increases to 0.62 for mid-sized projects (£25-250M total cost). However above £250M total costs, there is no correlation (Pearson correlation coefficient=-0.002), indicating that total cost plays less of a role in determining community benefits at large cost levels.

While this may appear contrary to the views of developers shown earlier (i.e. those who said that high costs can impact on financial viability and therefore their ability to offer community benefits) it should be noted that this data analysis is based only on projects that were already providing monetary community benefits. It excludes those that had not provided any benefits. It can therefore be assumed that the dataset excludes those projects that were deemed not financially viable enough to enable community benefit provision.

This analysis goes further to explore whether there are any differences by technology class within onshore projects only (offshore projects have been removed at this stage as the recommended £5,000/MW applies only to onshore technologies). In order to do so, it is important to control for project size (as measured by MW capacity), so as not to produce spurious results. Figure 6 illustrates how many pounds (£) are allocated to community benefits for every pound (£) spent producing energy, categorised by the project’s size in capacity (MW). Blue dots represent projects that have committed less than the recommended £5,000 per MW per year, while green dots represent projects that have committed more than the recommended amount and red dots represent project that have committed the recommended £5,000 per MW. For projects with total production costs under £25 million, when comparing hydro and onshore wind projects of the same capacity that both allocate £5,000 per MW annually to community benefits, onshore wind projects are actually providing more community benefits per pound (£) spent on energy production than hydro projects.

Figure 5 Community Benefits Package by Total Cost of Production Bucket (Under £25M, £25M-£250M and £250M+ Total Cost)

Source: See appendix F (Recommended data sources)

Figure 6 Community Benefits Package by Total Cost of Production Bucket (Under £25M, £25M-£250M and £250M+ Total Cost)

Source: See appendix F (Recommended data sources)

Appendix D Methodologies for estimating revenue and costs

Project Revenue

Simplified Annual Revenue Estimation – Generation Projects

The fundamental formula for estimating annual revenue is as follows:

Estimated Revenue = Expected Generation (MWh) * Electricity Price (£/MWh), where

Expected Generation (MWh) = Capacity (MW) * Capacity Factor* Hours in a year

Breaking down these components:

  • Installed Capacity (MW): This represents the maximum power output of the project under ideal conditions. This data is readily available from the Renewable Energy Planning Database (REPD).
  • Capacity Factor: This represents the actual output of a project as a percentage of its maximum potential output over a specific period. Historical capacity factors for certain technologies (onshore wind, offshore wind, hydro, landfill gas, and sewage sludge digestion) in Scotland can be found in the Energy Trends: UK Renewables publications[57].
    • Addressing Missing Capacity Factors: For technologies where Scotland-specific capacity factors are unavailable (e.g., solar PV, tidal, wave, biomass), several approaches can be used:
      • UK-wide Proxies: Use UK average capacity factors as a starting point, acknowledging this as a limitation and potential source of error.
      • Technology-Specific Adjustments: Adjust UK proxies based on technology and location characteristics. For example, solar PV capacity factors are influenced by latitude and solar irradiance. Tools like PVGIS can provide location-specific solar irradiance data to refine estimates (this approach is out of scope for the analysis in this study).
  • Average Annual Electricity Price (£/MWh): This represents the average price received for each MWh of electricity generated over a year. Given the difficulty of obtaining project-specific PPA data, the wholesale market price serves as a practical proxy.
    • Wholesale Price Data Sources: While real-time wholesale price data requires plugging into Elexon’s BMRS API, a simplified approach for this framework should entail using Ofgem’s published weekly wholesale day-ahead price data[58] to calculate annual averages. These are GB-wide averages, and hence regional variations should be recognised as a limitation.
    • Simplified CfD Approach (for CfD-supported projects): For projects under a Contract for Difference (CfD) the strike price is a guaranteed price. This figure is a conservative estimate of returns, as actual revenue could be higher if market prices exceed the strike price. CfD data is available from the Low Carbon Contracts Company (LCCC).

Estimating Future Revenue (also applicable for projects not yet operational) – Generation Projects

For revenue in future years, or for projects under development or construction, estimating future revenue requires additional considerations:

  • Project Lifetime Assumption: Specify a reasonable assumed operational lifetime for the technology (e.g., 25 years for offshore wind, 20-25 years for solar PV). This assumption directly impacts total revenue calculations.
  • Future Capacity Factor Estimation: Project future capacity factors based on recent trends and technological advancements. If historical capacity factor data for the specific technology in Scotland (or a similar region) is available, this trend should be analysed over the past years.[59] This trend should be extrapolated outward to estimate future capacity factors. For less established technologies with limited historical data, the technology’s maturity should be considered. Rapidly evolving technologies may see more significant performance improvements expected while more mature technologies might expect to see more stable future performance anticipated. For example, floating offshore wind might be expected to see larger capacity factor gains in the coming years compared to a more established technology like onshore wind.
  • Future Electricity Price Estimation: Given the volatility of electricity markets, projecting future prices is challenging. For projects supported by a Contract for Difference (CfD), the strike price offers a guaranteed future revenue stream and can be used as a conservative estimate. For non-CfD projects, where future revenue is directly exposed to market price fluctuations, a simplified approach involves using the average annual CfD strike price for the corresponding technology in each future year. However, it’s essential to acknowledge that:
    • CfD strike prices are influenced by auction dynamics and may not perfectly represent the market value of electricity from non-CfD projects.
    • Not all technologies are represented in CfD auctions.
    • Using CfD strike prices as proxies across all non-CfD projects might result in a somewhat conservative revenue estimate, as market prices could exceed the strike price in some years.

Prices beyond the latest future year reported in the CfD auction reports are set at the price in the latest year for the respective technology. For example, if CfD auction strike prices are set for the year 2027, the strike price in all future years will be set at the prices in 2027 for that technology. It is acknowledged these prices are unrealistic, however, they serve as the most appropriate benchmark against which to extrapolate.

  • Discounting Future Cash Flows: To compare projects and scenarios, discount future revenue streams to their present value using an appropriate discount rate that reflects project risk. We propose using the technology-specific discount rate of 10% used by DESNZ in their Levelised Cost of Electricity (LCOE) methodology documents.

Total Cost of Production Calculation

Total Cost of Production Calculation – Generation Projects

Estimating the total lifetime cost of production across the range of projects in scope requires a consistent and transparent method to apply cost assumptions across different generation technologies. To support this, we use benchmark Levelised Cost of Electricity (LCOE) estimates published by DESNZ.

DESNZ’s LCOE values represent the average lifetime cost (£/MWh) of generating electricity for each technology type. These figures include all relevant capital, operational, fuel, and decommissioning costs, spread over the expected lifetime electricity output of a project. As such, LCOE is a useful and well-recognised benchmark for comparing the cost-effectiveness of electricity generation technologies in the UK.

Importantly, we are not re-estimating or recalculating LCOE. Instead, we are using DESNZ’s published LCOE values as input parameters in our framework to estimate total cost of production across different project configurations. Specifically, we apply the LCOE estimates to the expected energy output of each project to calculate a total cost figure. This calculation can be expressed as:

Total Cost of Production (£) = LCOE (£/MWh) x (Installed Capacity (MW) x Load Factor x Annual Operating Hours x Project Lifetime (years))

This approach allows us to derive a consistent estimate of total production cost, using technology-specific LCOE values as cost rates, scaled by the expected energy output of each project over its lifetime.

The process for estimating total cost of production is as follows:

  • Technology categorisation: Categorise REPD projects to align with the technology categories used in the UK Government’s LCOE estimates file. This may involve mapping project types to the closest matching category in the government data.
  • Energy Output Calculation: Estimate the annual energy output (MWh) for each project based on its capacity and typical capacity factors for the relevant technology.
  • Total calculation: Using the scaled cost components and estimated energy output, we will calculate the total cost for each project using the formula. It’s important to note that the UK Government’s LCOE estimates are provided for projects with commissioning dates in 2025, 2030, 2035, and 2040. Therefore, our total cost calculations will need to be based on the estimate that most closely matches each project’s expected commissioning date. We will assign each project to the nearest available estimate year based on its planned commissioning date.
  • Inflation-adjustment: Furthermore, all costs in the UK Government’s estimates are reported in 2021 prices. To ensure consistency and accurate comparisons across projects with varying commissioning dates, we adjust these figures to a common base year using HM Treasury GDP deflators. These temporal adjustments will help ensure that our total cost calculations accurately reflect the economic conditions and technological advancements expected at the time of each project’s commissioning, within the constraints of the available data.

Appendix E Socio-economic scoring mechanisms

Table 3 NASA Technology Readiness Levels

TRL

TRL Summary

1

Basic principles have been observed and/or formulated: Lowest level of technology readiness. Scientific research begins to be translated into applied research and development (R&D). Examples might include paper studies of a technology’s basic properties.

2

Developing hypothesis and experimental designs: Invention begins. Once basic principles are observed, practical applications can be invented. Applications are speculative, and there may be no proof or detailed analysis to support the assumptions. Examples are limited to analytic studies.

3

Specifying and developing an experimental Proof of Concept (PoC): Active R&D is initiated. This includes analytical studies and laboratory studies to physically validate the analytical predictions of separate elements of the technology. Examples include components that are not yet integrated or representative.

4

PoC demonstrated in test site/initial evaluation of costs and efficiency produced: Basic technological components are integrated to establish that they will work together. This is relatively “low fidelity” compared with the eventual system. Examples include integration of “ad hoc” hardware in the laboratory.

5

Technology/process validated in relevant environment: Fidelity of breadboard technology increases significantly. The basic technological components are integrated with reasonably realistic supporting elements so they can be tested in a simulated environment. Examples include “high-fidelity” laboratory integration of components.

6

Technology/process validated in operational environment: Representative model or prototype system, which is well beyond that of TRL 5, is tested in a relevant environment. Represents a major step up in a technology’s demonstrated readiness. Examples include testing a prototype in a high-fidelity laboratory environment or in a simulated operational environment.

7

System complete and qualified: Prototype near or at planned operational system. Represents a major step up from TRL 6 by requiring demonstration of an actual system prototype in an operational environment (e.g., in an aircraft, in a vehicle, or in space).

8

Product/technology in manufacture/process being implemented: Technology has been proven to work in its final form and under expected conditions. In almost all cases, this TRL represents the end of true system development. Examples include developmental test and evaluation (DT&E) of the system in its intended weapon system to determine if it meets design specifications.

9

Product/service on commercial release/process deployed: Actual application of the technology in its final form and under mission conditions, such as those encountered in operational test and evaluation (OT&E). Examples include using the system under operational mission conditions.

10

Dead end and reached.

Table 4 IEA Technology Guide Technology Maturity Scale

Technology Readiness Level

Description

11

Proof of stability reached

10

Integration needed at scale

9

Commercial operation in relevant environment

8

First of a kind commercial

7

Pre-commercial demonstration

6

Full prototype at scale

5

Large prototype

4

Early prototype

3

Concept needs validation

2

Application formulated

1

Initial idea

Table 5 Market Maturity Scale

Score

Reasoning

5

Fully Mature Market: A fully mature market is characterized by high levels of competition, well-established regulatory and policy frameworks, and a global supply chain. The technology is fully integrated into the energy system, and investment is based on market forces rather than policy incentives. The market operates efficiently with clear pricing signals. Hydropower, especially conventional dam-based installations, has a fully mature market with a global presence and long history of integration into energy systems.

4

Established Market: Established markets have a stable and supportive regulatory environment, a robust and competitive supply chain, and a broad base of stakeholders. Investment is seen as lower risk, and financing models are well understood. There is strong competition, and the technology is a significant part of the energy mix. Onshore wind and solar PV have both reached this level of market maturity, with widespread adoption and a solid market presence.

3

Growing Market: At this stage, markets are experiencing noticeable growth in demand and investment. The regulatory environment is becoming more supportive, with clearer policies and standards. The supply chain is expanding, and costs start to decrease as economies of scale are realized. There is a healthy level of competition with several established players. Fixed-bottom offshore wind is at this stage, with a growing number of projects and increasing investor confidence.

2

Emerging Market: Markets at this stage have begun to establish some regulatory frameworks and attract early adopters. The supply chain is forming but may not be fully reliable or cost-effective. There is a growing interest from investors, but financing often depends on policy incentives. Competition is limited, but there are signs of market growth. Floating offshore wind, which is beginning to see commercial interest and investment, but lacks the extensive market presence of fixed-bottom offshore wind, would fall into this category.

1

Nascent Market: The market at this stage is in its infancy. There are few, if any, regulatory standards or guidelines, and the supply chain is undeveloped. Investment is highly speculative, and there are very few players in the market. The technology may still be reliant on grants or government support with no established commercial financing models.

Appendix F Recommended data sources

The following below provides a summary of the key data sources currently available to measure framework parameters. However, these are not complete and additional work is required to fill gaps.

Parameter

Measurement item

Recommended data source

Community Benefit

Community benefits monetary value (£)

Community Benefit Register Database. Since the database does not cover all technologies, this would need to be supplement with data from individual developers, either through requesting this directly or sourcing it from company reports (where available).

Technical maturity

Technology maturity scoring

NASA TRL Scale

IEA ETP Clean Energy Technology Guide. While the database is comprehensive in its technology classification, there is likely to be some mis-classification of REPD projects to specific IEA ETP technologies. Ideally, project TRLs should be sourced directly from project owners.

Project revenue

Installed capacity

Community Benefit Register Database and REPD

Capacity factor

Energy Trends: UK Renewables publications. Historical capacity factors are only available for certain technologies. Newer technologies are therefore not captured and will need to be sourced directly from projects.

Electricity price

Elexon

Ofgem wholesale day-ahead price

CfD strike price

Low Carbon Contracts Company

Capital and operating costs

Technology categorisation

UK Government’s LCOE estimates. This data source captures LCOE for a selection of common technologies. More niche/newer technologies are not captured within this data source and therefore should be collected directly through projects.

 

Energy output

REPD

Energy Trends: UK Renewables publications

How to cite this publication:

Mulholland, C., Jones, R., Tapie, N. and Stow, C. ‘Renewable energy technologies and community benefits’, ClimateXChange. http://dx.doi.org/10.7488/era/6396 

© The University of Edinburgh, 2025
Prepared by Ipsos on behalf of ClimateXChange, The University of Edinburgh. All rights reserved.

While every effort is made to ensure the information in this report is accurate as at the date of the report, no legal responsibility is accepted for any errors, omissions or misleading statements. The views expressed represent those of the author(s), and do not necessarily represent those of the host institutions or funders.

This work was supported by the Rural and Environment Science and Analytical Services Division of the Scottish Government (CoE – CXC).

ClimateXChange

Edinburgh Climate Change Institute

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+44 (0) 131 651 4783

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www.climatexchange.org.uk

If you require the report in an alternative format such as a Word document, please contact info@climatexchange.org.uk or 0131 651 4783.


  1. See Community benefits and shared ownership for low carbon energy infrastructure: working paper (accessible webpage) – GOV.UK



  2. Scottish Government (2020)



  3. Scottish Government (2024)



  4. Scottish Government (2019)



  5. Scottish Government (2018)



  6. Scottish Government (2023)



  7. Community benefit funds typically mean that developers will voluntarily contribute a certain amount of funding to local communities. In some cases, the level of funding is linked to the amount of installed capacity of the project or the amount of energy produced.



  8. Kerr et al (2017), Anchustegui (2021), Kerr & Weir (2018), O San Martin et al (2022), Scottish Government (2022), Scottish Government (2019), Scottish Government (2018)



  9. O San Martin et al (2022)



  10. Anchustegui (2021)



  11. Glasson (2020)



  12. https://localenergy.scot/community-benefits-register/



  13. Kerr et al (2017)



  14. In the reviewed literature, shared ownership was a common practice in countries outside the UK, notably in Germany and Denmark. However, this is not outlined here as shared ownership is not part of the Scottish Government’s definition of community benefits.



  15. le Maitre, 2024; Toledano, et al., 2023; O San Martin, et al., 2022;



  16. Anchustegui, 2021



  17. Lansbury Hall, 2020; Regen, 2022; Lane, et al., 2019;



  18. Energy UK, 2024



  19. Centre for Sustainable Energy (CSE), 2005; Walker, 2023; Glasson, 2020; Chen, 2024



  20. Regen, 2022



  21. van den Berg & Tempels (2022); Glasson (2020)



  22. Kerr & Weir (2018), Scottish Government (2022)



  23. le Maitre (2024)



  24. Glasson (2020)



  25. Rudolph et al. (2014)



  26. Rudolph et al. (2014)



  27. Glasson (2020)



  28. Glasson (2020)



  29. Glasson (2020)



  30. SSE Renewables (2024)



  31. Regen (2022)



  32. Le Maitre et al. (2024)



  33. Wind Europe (n.d.); San Martin (2022); Arsenova et al. (2024); Anchustegui (2021)



  34. Klain et al. (2017)



  35. Lane & Hicks (2019)



  36. Lane & Hicks (2019)



  37. Chen et al. (2024); Klain et al. (2017); Rudolph et al. (2014)



  38. Glasson (2020), Manitius (2023), Arsenova & Wlokas (2019), BiGGAR Economics (2024a), BiGGAR Economics (2024b), Toledano et al. (2023)



  39. Klain et al. (2017)



  40. Wind Europe (n.d.)



  41. Chen et al. (2024), Klain et al. (2017)



  42. Arsenova & Wlokas (2019)



  43. Arsenova & Wlokas (2019)



  44. US Department of Energy (2024)



  45. Department for Energy Security and Net Zero (2023)



  46. Anchustegui, 2021; Kerr, 2017; le Maitre, 2024; Rudolph, et al., 2014; Toledano, et al., 2023; Arsenova,et al., 2019



  47. Herrera (2021)



  48. Herrera (2021)



  49. le Maitre (2024)



  50. Toledano, et al.



  51. Arsenova, et al., 2024



  52. Kerr et al (2017); le Maitre (2024)



  53. le Maitre (2024)



  54. BiGGAR Economics (2023)



  55. Four operational offshore wind projects were in Scotland, two in Wales and fifteen in England.



  56. The Pearson correlation coefficient measures how strongly two variables are linearly related, ranging from -1 (perfect negative correlation) to 1 (perfect positive correlation), with 0 indicating no linear relationship.



  57. https://www.gov.uk/government/statistics/energy-trends-section-6-renewables



  58. https://www.ofgem.gov.uk/energy-data-and-research/data-portal/wholesale-market-indicators Wholesale market indicators | Ofgem



  59. It is recommended to aim for a minimum of 5 years of historical data. This provides a reasonable basis for identifying trends and patterns, while also smoothing out short-term fluctuations or anomalies.


As part of its commitment to achieving net zero by 2045, the Scottish Government has ambitions for Scotland to become a major exporter of low-carbon hydrogen and hydrogen derivatives and products (HDPs).

Hydrogen can be produced using electrolysis, a process which involves splitting water into hydrogen and oxygen. When this process is performed using only renewable sources of electricity, the hydrogen produced is known as green hydrogen.

This study explores Scotland’s capabilities of producing green hydrogen and developing the HDP sector, identifying opportunities and barriers it may face in scaling it up. It also aims to understand the role different regions of Scotland can play in enabling the growth of these sectors.

Findings

Scotland’s abundant access to renewable energy, geographic proximity to the EU, skilled workforce and a favourable external policy landscape are major strengths that can enable growth in the hydrogen and HDP sectors. However, there are potential weaknesses and barriers too. Producing renewable electricity, a major cost source for producing green hydrogen, is currently relatively expensive in Scotland, with prices around 70% higher than the average of EU and G7 countries.

Supply chain capabilities and addressable market demand

Following a systematic comparison of the supply chain capabilities of 14 potential hydrogen hubs identified by the Scottish Government, Aberdeen ranked the highest in many metrics, followed by Cromarty and Ayrshire.

The report also assessed the addressable market demand for HDPs. Roughly 97% of all HDP demand comes from the aviation and maritime sectors and Grangemouth was estimated to have the biggest market demand for both.

Co-locating demand and supply will enable the early scaling of Scotland’s hydrogen and HDP sectors as national network infrastructure is developed. Analysis of both supply and demand found that with the presence of a large chemicals industry and a major airport, Grangemouth outperforms all other hubs. Despite relative strengths in supply chain capability, Aberdeen is not the optimal region for co-locating supply with demand opportunities.

Policy gaps

Analysis of the policy landscape in the UK, the EU and Scotland suggests a number of potential approaches to help develop the hydrogen and HDP sectors. Scotland’s abundant access to renewable energy, strong workforce capabilities and demand potential can facilitate vibrant hydrogen and HDP sectors. However, Scotland will need to address issues such as:

  • the high cost of electricity generation;
  • a more sophisticated planning regime that considers both site demand and supply in order to optimise co-location strategies.

Working with the UK and foreign governments to capitalise on export opportunities will allow Scotland to expand its potential market size.

Cross-hub development

Although Aberdeen and Grangemouth stand out as having relative strengths in relation to supply chain capabilities and market demand, there are strengths and capabilities across the other potential hubs. Cromarty and Ayrshire offer strong supply chain capabilities. Glasgow and Fife present significant demand opportunities. The Western Isles and Argyll and Islands may require targeted support to enhance their supply chain capabilities, while the Scottish Borders may need support in developing greater regulatory experience.

This diversity points to the importance of a cross-hub approach, in addition to co-locating demand with supply. By balancing cross-hub collaboration with localised development, Scotland can maximise the potential of its hydrogen economy, driving the sector’s long-term growth and resilience.

For further information, please read the report.

If you require the report in an alternative format, such as a Word document, please contact info@climatexchange.org.uk or 0131 651 4783. 

Research completed: April 2025

DOI: http://dx.doi.org/10.7488/era/6397

Executive summary

Aims

The Scottish Government is committed to achieving net zero emissions by 2045, five years ahead of the UK’s target. Scotland also aims to become a major exporter of low carbon hydrogen derivatives and products (HDPs) and has access to the abundant renewable energy necessary for their production. Hydrogen derivatives are chemicals produced from hydrogen that can more easily be stored and transported and then converted back to hydrogen for later use. Examples include ammonia and methanol. Hydrogen products, such as sustainable aviation fuels (SAFs), do not need a further conversion process and are used for a range of applications.

Hydrogen can be produced using electrolysis, a process which involves splitting water into hydrogen and oxygen. When this process is performed using only renewable sources of electricity, the hydrogen produced can be deemed as green hydrogen.

As green hydrogen supply is crucial for the development of HDP production, this study explores Scotland’s strengths and weaknesses in developing both the green hydrogen and HDP sectors. Throughout this study, the term “hydrogen and HDP sector” is used to include green hydrogen and HDPs produced using that green hydrogen.

This study analyses Scotland’s supply chain capabilities in producing HDPs and identifies opportunities and barriers it may face in scaling up the hydrogen and HDP sectors. It also aims to understand the role different regions of Scotland can play in enabling the growth of these sectors.

Findings

Scotland’s abundant access to renewable energy, geographic proximity to the EU, skilled workforce and a favourable external policy landscape are major strengths that can enable growth in the hydrogen and HDP sectors. However, there are potential weaknesses and barriers too. Producing renewable electricity, a major cost source for producing green hydrogen, is currently relatively expensive in Scotland, with prices around 70% higher than the average of EU and G7 countries.

Supply chain capabilities

The Scottish Government’s Hydrogen Action Plan identified 14 hydrogen hubs. This report systematically compared the supply chain capabilities of each for producing HDPs. Hubs were assessed on:

  • Availability of feedstock (i.e., production source material)
  • Economic factors from co-located industries
  • Workforce and skills
  • Infrastructure,
  • Local policy and planning support, and
  • Co-location with innovation institutions

For comparison, the Duisburg region of Germany was assessed against the same metrics, as a potential competitor to Scottish hubs.

Aberdeen ranked the highest in many metrics, followed by Cromarty and Ayrshire. The Duisburg hub also scored highly on several metrics. The aim was not to find a single best hub. Aberdeen’s high score suggests that it is currently relatively well-developed against the supply chain metrics, it does not suggest that this is the sole hub suitable for developing Scotland’s hydrogen and HDP sectors.

Addressable market demand

The report estimated the addressable market demand for HDPs in each hub. The HDPs considered were ammonia and e-methanol for the maritime sector, ammonia-based fertiliser for the agriculture sector, e-methanol feedstock for the chemical sector, and SAF for aviation.

The addressable demand for all HDPs in all the sectors is around 35 TWh. Roughly 97% of this comes from just the aviation and maritime sectors. Grangemouth is estimated to have the biggest market for HDPs in both sectors.

Co-locating demand and supply

Co-locating demand and supply will enable the early scaling of Scotland’s hydrogen and HDP sectors as national network infrastructure is developed. Aberdeen and Grangemouth both stand out as key hubs for the development of Scotland’s HDP economy. Analysis of supply and demand found that with the presence of a large chemicals industry and a major airport, Grangemouth outperforms all other hubs.

Despite relative strengths in supply chain capability, Aberdeen is not the optimal region for co-locating supply with demand opportunities because the maximum demand potential is higher in Grangemouth.

There are significant hazards associated with HDPs bringing associated regulatory requirements. Analysis of current Control of Major Accidents and Hazards (COMAH) site locations provides insight into the infrastructure and the expertise needed to handle HDPs safely. Fife, Glasgow, Moray and Grangemouth hubs have the most COMAH sites, bringing relatively strong experience in this regulatory environment.

Policy gaps

Analysis of the policy landscape in the UK, the EU and Scotland suggests a number of potential approaches to help develop the hydrogen and HDP sectors. Scotland’s abundant access to renewable energy, strong workforce capabilities and demand potential can facilitate a vibrant hydrogen and HDP sectors. However, Scotland will need to address issues such as:

  • the high cost of electricity generation;
  • a more sophisticated planning regime that considers both site demand and supply in order to optimise co-location strategies.

Working with the UK and foreign governments to capitalise on export opportunities will allow Scotland to expand its potential market size.

Conclusions

Hub development requires both a cross-hub approach and strategic co-location of regional supply and demand. Individual hubs should not be considered in isolation. Particular hubs score relatively highly but this does not preclude a very significant role for other hubs within the overall hydrogen and HDP sectors.

Aberdeen and Grangemouth stand out as having relative strengths in relation to co-location of supply chain capabilities with demand. Cromarty and Ayrshire offer strong supply chain capabilities. Glasgow and Fife present significant demand opportunities. The Western Isles and Argyll and Islands may require targeted support to enhance their supply chain capabilities. The Scottish Borders may need support in developing greater regulatory experience.

By balancing cross-hub collaboration with localised development, Scotland can maximise the potential of its hydrogen economy, driving the sector’s long-term growth and resilience.

Glossary / Abbreviations

Abbreviations

COMAH

Control of Major Accident Hazards

FEED

Front-End Engineering Design

FTE

Full-Time Equivalent

GHS

Globally Harmonized System of Classification and Labelling of Chemicals

GSMR

Gas Safety (Management) Regulations 1996

GVA

Gross Value Added

HPBM

Hydrogen Production Business Model

HSBM

Hydrogen Storage Business Model

HSE

Health and Safety Executive

HTBM

Hydrogen Transport Business Model

IMO

International Maritime Organization

IPCEI

Important Projects of Common European Interest

IRENA

International Renewable Energy Agency

LOHC

Liquid Organic Hydrogen Carrier

MCH

Methylcyclohexane

MoU

Memorandum of Understanding

NSIP

Nationally Significant Infrastructure Project

NSTA

North Sea Transition Authority

NZHF

Net Zero Hydrogen Fund

REPD

Renewable Energy Planning Database

RFNBO

Renewable fuels of non-biological origin

SAF

Sustainable Aviation Fuel

SEPA

Scottish Environment Protection Agency

SIC

Standard Industrial Classification

Glossary of units

gCO₂e/MJ

Grams of CO₂ equivalent per megajoule

J

Joule

kg CO₂-eq/kg

Kilograms of CO₂ equivalent per kilogram

Wh

Watt-hour

m

Metre

%

Percentage

t

Tonne

W

Watt

Introduction

Scotland has set an ambitious target to reach net zero by 2045. To be able to achieve its targets, Scotland will have to rapidly decarbonise its economy. The Scottish Government is exploring options to use hydrogen to decarbonise certain sectors and to develop current HDP capabilities in support of climate goals. Scotland ultimately aims to produce 5 GW of low-carbon hydrogen by 2030 and 25 GW by 2045. In addition to reaching its net zero goals, the Scottish Government also aims to utilise these resources to capitalise on export and other economic opportunities. Green hydrogen is expected to be the dominant low carbon production method in Scotland. This study focuses solely on HDPs produced from green hydrogen, which are referred to as “HDPs” throughout this report.

In this study we aim to explore Scotland’s supply chain capabilities. To situate the need for this research, we conducted a review of existing literature (see Appendix A: Current state of play). Our review of the literature analyses the strengths that Scotland possesses to scale up its hydrogen and HDP sectors. It also details some of the biggest barriers that Scotland is likely to face. The review then focusses briefly on specific HDPs and their potential role in enabling Scotland’s transition to net zero.

We also analyse Scotland’s strengths and weaknesses in developing its capabilities. We focus on assessing the opportunities and challenges associated with exporting HDPs to the rest of the UK and the EU. Moreover, we aim to understand the role that different regions of Scotland can play in enabling the development of HDP production. We have identified 14 regional hydrogen hubs in Scotland from the Scottish Government’s Hydrogen Action Plan (2022), shown in Table 1. In addition to the Scottish hubs, the study also considers the Ruhr region of Germany as an alternative hub. Scotland is expected to export a significant amount of its green hydrogen produce to the EU. Therefore, the Ruhr region of Germany was considered as a potential alternative source of green hydrogen for the EU.

For each metric, we rank the hubs to analyse their relative strengths, before combining these rankings into a final capability score for each hub in Section 3.8. In this manner, we provide a balanced and quantitative assessment of the relative supply chain capabilities of Scotland’s hydrogen hubs. It is important to note that the purpose of this analysis is not to find the absolute “best” hydrogen hub in Scotland. By ranking the hubs in each metric, we have assessed their relative strengths and weaknesses.

In an international market, Scotland’s hubs will be competing with various other green hydrogen and HDP production areas. As Scotland aims to export to Europe, in particular Germany, it will have to compete with local European production (Scottish Government, 2024). Germany’s Ruhr region aspires to be the first model hydrogen region to accelerate the hydrogen sector in Europe (Hydrogen Metropole Ruhr, 2023). Hydrogen is already playing a role in developing HDP production in the region (Metropole Ruhr Business, 2025). One example is the Greenlyte’s project in Marl which is producing e-methanol from CO2 and green hydrogen. In August 2025, this project secured a 7-figure e-methanol offtake agreement with Germany-based MB Energy, indicating substantial market interest for HDPs produced in the Ruhr region (Greenlyte, 2025). Given Ruhr’s strong ambitions, to evaluate Scotland’s competitiveness at the international level, we will compare the Scottish hubs with the hydrogen hub of Duisburg, situated in the Ruhr region.

In subsequent chapters, we analyse the supply chain capabilities of each hub in Scotland, addressable demand for various HDPs in different sectors, and the regulatory environment related to safety. The final chapter focusses on the wider policy landscape, analysing gaps and providing recommendations to policymakers.

Table 1: List of Scottish hubs and their corresponding local authorities.

Hub

Corresponding local authorities

Aberdeen

Aberdeenshire and Aberdeen City

Argyll and Islands

Argyll and Bute

Ayrshire

East Ayrshire, North Ayrshire, and South Ayrshire

Cromarty

Highlands

Moray

Moray

Dumfries and Galloway

Dumfries and Galloway

Dundee

Dundee and Angus

Fife

Fife

Glasgow

East Dunbartonshire, East Renfrewshire, Glasgow City, North Lanarkshire, Renfrewshire, South Lanarkshire and West Dunbartonshire

Grangemouth

Clackmannanshire, Falkirk and Stirling

Orkney

Orkney Islands

Scottish Borders

Scottish Borders

Shetland

Shetland Islands

Western Isles

Western Isles

Supply chain capabilities of Scotland’s hydrogen hubs

In this chapter, we investigate the relative supply chain capabilities of Scotland’s hydrogen hubs to produce HDPs. We have selected six capability groups for evaluation (shown in Table 2). These groups are broadly based on the six key advantages for hydrogen production identified in the Scottish Government’s Hydrogen Action Plan (2024). Certain capability groups, such as pipeline infrastructure, are highly dependent on future developments at a national and international level. The results from analysing all these capability groups will allow us to assess each hub’s intrinsic and long-term supply chain strengths that will enable the fast growth of the hydrogen and HDP sectors.

We have then broken down these groups further into assessment metrics in order to accurately evaluate the capability groups against available data. This analysis produces detailed hub differentiation to support actionable conclusions for policymakers. Table 2 shows each capability group and their associated metrics. Further information on metric methodology, sources and data is found in Appendix B.

Table 2: Capability groups and assessment metrics for evaluating the supply chain capabilities.

Capability group

Assessment metric

Feedstock and inputs

Maximum potential renewable power generation

Water availability

Economic output from relevant co-located industries

Gross Value Added of the energy sector

Workforce and skills

Full time equivalent workers in energy and engineering

Future workforce requirements

Infrastructure

Large-scale storage capacity

Pipeline network infrastructure

Ports

Local policy and planning support

Processing time for industrial planning applications

Success rate of industrial planning applications

Co-location with innovation institutions

Innovation institutions with facilities for pilot-scale testing

Feedstock and inputs

Renewable electricity and water are the two fundamental feedstocks for green hydrogen production. The availability of both can be seen to vary, by region. This is in contrast to the supply of nitrogen for e-ammonia or carbon dioxide for e-methanol, where both feedstocks are derived from air, via direct air capture and can therefore be assumed to be equally available to all hubs.

Maximum potential renewable power generation

Scotland’s abundant renewable energy resources are key to its net zero transition. In particular, the Scottish Government has identified Scotland’s extensive offshore wind resource as a considerable opportunity for green hydrogen production (Scottish Government, 2020). Under a business-as-usual scenario, installed offshore wind capacity is expected to rise from 3.4 GW in 2025 to 27 GW in 2045 (Scottish Government, 2020). Green Hydrogen production can support this growth by helping to overcome Scotland’s grid constraints.

The co-location of renewable energy generation and HDP production takes advantage of existing infrastructure, reduced electricity transmission costs and improved project economics. An example of co-location is Scottish Power’s planned 20 MW Whitelee Green Hydrogen Project near Glasgow (Scottish Power, 2024). The facility will be co-located with a 70 MW combined Solar and Battery Energy Storage Scheme. Adjacent is the 539 MW Whitelee Windfarm and substation.

We have analysed the maximum potential renewable power generation for each hub, based on the total current, planned and announced installed capacity of solar and wind power projects (DESNEZ, 2024; Offshore Wind Scotland, 2024). We scaled the resulting capacities by the appropriate load factor to determine the maximum potential renewable power generation (see Appendix B for load factors). For offshore wind, we assigned each project to the hub associated with its current or forecasted onshore landing point.

Figure 1: Maximum potential renewable power generation split by current and future (planned and announced) projects.

The order of hubs by maximum potential renewable power generation is shown in Figure 1. As shown from left to right, Aberdeen is ranked first and Duisburg, Germany is ranked last.

We can take several key insights from Figure 1:

  • Access to future wind projects, particularly offshore wind, broadly determines which hubs have the most renewable power capability. Aberdeen, ranked first, accounts for around 50% of planned and announced offshore wind capacity among the Scottish hubs.
  • Hubs with large future offshore wind projects – such as the announced ScotWind projects – lead the rankings (Offshore Wind Scotland, 2024). These hubs include Aberdeen, Cromarty and Moray.
  • Grangemouth, with no current or future offshore wind capacity, ranks lowest among the Scottish hubs.
  • As a densely populated hub, with no offshore wind, Duisburg ranks lowest overall.

Water availability

Sustainable water management is vital to balancing our water demand with environmental and ecological needs. Therefore, it is important to identify the water supply for hydrogen production early in the development process to ensure sufficient availability.

The electrolysis process requires large volumes of treated water, which is split to form hydrogen and oxygen. Reviewing the commercial electrolyser technologies, an estimated 10 litres of water is required per kilogram of green hydrogen produced (Ramboll, 2022). Water for green hydrogen production can be obtained from several sources, shown in Table 3:

Table 3: Sources of water for green hydrogen production (Ramboll, 2022).

Type of water

Definition for the purpose of this study

Effluent

Treated effluent from Scottish Water’s Wastewater Treatment Works

Surface water

Freshwater abstracted from rivers, lochs and reservoirs

Groundwater

Freshwater abstracted from bedrock

Potable water

Drinking water

Sea water

Saltwater which is abstracted and desalinated

Where possible a local water supply should be used for green hydrogen production, due to the cost of transporting water over long distances (Ramboll, 2022). Ramboll proposes that effluent should be the first water source considered as it does not compete with other sectors such as agriculture. Surface water, groundwater and potable water may be sourced from the mains water supply dependant on capacity and infrastructure availability. However, the use of potable water should be avoided where possible (Ramboll, 2022). While desalination has not been established for water supply in Scotland, the use of seawater may be an interesting option for the future hub development, particularly for island hubs which have less connectivity to mains infrastructure. However, for this analysis, we have focused on Scotland’s current water infrastructure capabilities from mains water supply and regional Scottish Water Wastewater Treatment Works.

In 2022, Ramboll, on behalf of SGN, investigated the water availability for green hydrogen production across Scotland (Ramboll, 2022). Drawing on Ramboll’s work, Table 4 shows the maximum green hydrogen production potential, based on water availability and the forecasted installed green hydrogen production capacity in 2045. We used these figures to assess water availability for the forecasted installed capacity in 2045. For Duisburg, we applied the same assumptions used for the Scottish hubs (Ramboll, 2022, pp. 26-27).

Table 4: Water availability ranking by hub

Hub

Forecasted installed green hydrogen capacity in 2045 (GW)

Maximum potential installed green hydrogen production based on water availability (GW)

Water availability ranking

Glasgow

2.50

239.2

1

Grangemouth

2.00

145.9

2

Dundee

0.25

73.0

3

Fife

0.25

67.8

4

Cromarty

5.00

61.2

5

Ayrshire

0.50

47.5

6

Aberdeen

0.50

44.5

7

Dumfries and Galloway

0.50

26.7

8

Moray

2.00

26.6

9

Scottish Borders

0.00

22.9

10

Duisburg

1.00

14.0

11

Argyll and Islands

0.13

11.4

12

Western Isles

0.12

9.1

13

Orkney

0.05

1.5

14

Shetland

6.30

2.0

15

The relative water availability for hubs is shown in Table 4, from which we can take several key insights:

  • Overall, water availability is unlikely to limit the deployment of forecasted green hydrogen installed capacity. However, future water abstraction may be limited by regulatory changes, land use restrictions, and competing demand.
  • Shetland is ranked in last place as it is the only hub where forecasted green hydrogen production requires more water than is currently deliverable. This issue could be mitigated if desalination infrastructure is made available.
  • Populous areas are more favourable for expanding green hydrogen production capacity based on water availability. These areas have greater effluent wastewater availability, which does not compete directly with other use cases. For example, Glasgow could potentially produce up to 203 GW of green hydrogen from effluent water. Orkney, in comparison, could only produce up to 0.03 GW.
  • The island hubs (Western Isles, Orkney and Shetland) rank lowest. This is due to their limited freshwater supply and small population.

Economic output from relevant co-located industries

Gross Value Added of the energy sector

To evaluate the economic output from relevant co-located industries, we have compared the gross value added (GVA) of the energy sector in each hub. A high GVA signals that a region has a strong existing industrial base, infrastructure and workforce for the energy sector. This makes GVA a useful indicator of the investment attractiveness of establishing local hydrogen and HDP sectors.

Using the Scottish Government’s Industry Statistics, we have calculated the approximate gross value added of the energy industry for each hub in 2022 (Scottish Government, 2024). The definition of energy sector is based on Standard Industrial Classification (SIC) Codes 2007 and is outlined further in Appendix B. Generally, these SIC codes cover the following industries:

  • Fossil fuel extraction and mining
  • Manufacturing of petroleum products and other organic chemicals
  • Energy supply e.g. electricity
  • Water processing and supply
  • Waste treatment and disposal
  • Engineering and environmental consultancy

Figure 2: Estimated balanced GVA of the energy sector (2022).

The order of hubs by energy sector GVA is shown in Figure 2 from left to right. Aberdeen’s energy sector has the highest GVA at £25.9 billion in 2022; the Western Isles has the lowest, with a GVA of £16.8 million. Aberdeen, as the primary base of operations for the UK’s offshore oil and gas industry, is by far the major contributor to Scotland’s energy sector GVA (Port of Aberdeen, 2025).

For Duisburg, we conducted a separate analysis to allow comparison on a like-for-like basis using available data. Considering the Production Sector, as defined by SIC Codes 2007, Duisburg is ranked second after Aberdeen with a GVA of £4.15 billion (Länder, 2024; Office for National Statistics, 2024).

Workforce and skills

For this capability group, we have assessed the current workforce and the future workforce metrics for each hub. The expanding hydrogen and HDP sectors will demand a skilled and educated workforce. Scotland’s existing energy and engineering professionals are best positioned to make this transition, although not all will do so. To account for this unknown, we have evaluated future workforce requirements as well as the current transferable workforce.

Full time equivalent workers in energy and engineering

We have analysed the number of full-time equivalent (FTE) workers in these sectors (Skills Development Scotland, 2024). This will provide us with an indication of the relative workforce availability between the hubs.

Figure 3: Number of FTE workers in the energy and engineering sectors by hub

Figure 3 shows that Aberdeen has the most workers in energy and engineering with 71,100 FTEs; the Western Isles ranks lowest with only 400 FTEs. We can take several key insights from Figure 3:

  • Aberdeen and Glasgow are the hubs with the largest transferable workforce. Among all the hubs, Aberdeen and Glasgow contain 70% of all FTE workers in energy and engineering.
  • Skilled workforce availability may be a challenge for island hubs. There are only 1600 FTEs in energy and engineering across Shetland, Orkney and the Western Isles combined.

Future workforce requirements

We evaluated the hubs in terms of their future workforce requirements, analysing estimated demand for Scottish workers in the energy and engineering sectors. Labour forecasts can be divided into two categories: replacement demand and expansion demand. For this study, we have only considered expansion demand[1].

Positive expansion demand represents increasing labour demand due to sector growth. Negative expansion demand suggests shrinking sectors, demanding less labour. The time period considered for this analysis was 2027-2034.

Hubs with higher expansion demand will see more competitive labour market conditions. Growing hydrogen and HDP sectors in such hubs can be expected to increase labour competition further. Hubs with negative expansion demand are expected to have less competitive labour market conditions in the future. Growing the HDP sector in such hubs will not exacerbate competition for skilled workers, as the number of jobs is likely to exceed the number of available workers.

Figure 4: Estimated expansion labour demand in energy and engineering sectors.

Figure 4 shows Aberdeen with the lowest expansion demand of -4,600 people. This means the engineering and energy sectors in Aberdeen will require 4,600 fewer workers in the period 2027-2034 compared to today. Glasgow, Fife, Ayrshire and Grangemouth follow with expansion demands between around -1,500 (Glasgow) and -700 (Grangemouth). These hubs are likely to have the least competitive labour market conditions in the future, implying less competition for workers in the growing hydrogen and HDP sectors. As Figure 4 shows, none of the hubs is forecast to have positive expansion demand: more additional workers are not expected to be needed in any hub. The labour market environment for engineering and energy jobs, within each of the hubs, appears to be favourable for growing Scotland’s hydrogen and HDP sectors.

It is worth reiterating that replacement demand has not been considered in this analysis. Therefore, it is important to understand that this analysis does not provide a full image of the future labour market for the hubs in these two sectors.

Infrastructure

Regional infrastructure is key for facilitating the storage, distribution and trade of green hydrogen to supply HDP production. In A Trading Nation – Realising Scotland’s Hydrogen Potential – A Plan for Exports, the Scottish Government identified ports, pipelines and large-scale storage as the three connectivity pillars required to enable the hydrogen and HDP sector’s growth (2024). Here, we investigate each hub’s relative strengths.

Large-scale storage capacity

Large-scale storage will be required to scale up hydrogen production and balance supply and demand. This scale of storage will likely be provided by underground geological storage, rather than aboveground storage which is constrained by land availability. There are several types of geological storage, which are described in Table 5.

Table 5: Types of geological storage for hydrogen and their technology readiness levels (ClimateXChange, 2023).

Geological storage technology

Description

Technology readiness level (1 = lowest, 9 = highest)

Salt caverns

Most mature hydrogen storage technology, formed of an underground cavity in a rock salt layer.

9

Saline aquifers

Deep, porous rock formations filled with salty water. Previously used for commercial town gas (50% hydrogen) storage.

2-3

Depleted oil and gas fields

Former fields can be repurposed for storage. This technology already provides the majority of global gas storage capacity.

3-4

There are currently no projects to develop commercial geological hydrogen storage in Scotland. Moreover, apart from salt caverns, these technologies are still immature. So, we have assessed the technical geological storage capacity for each hub. For this, we have used available estimates from scientific literature. We assigned storage capacities to each hub based on their location or, if offshore, their likely terminal. The locations and total technical capacity for each storage technology is shown in Table 6.

Table 6: Technical capacity and locations for geological storage types in Scotland.

Type of storage

Locations in Scotland

Technical capacity in Scotland (TWh)

Onshore salt caverns

  • There are no onshore salt caverns in Scotland.

0 TWh (ClimateXChange, 2023)

Offshore salt caverns

  • There are high prospectivity offshore salt caverns in the Central North Sea and North Channel (Edlmann, et al., 2024).
  • These are mapped in the UK Hydrogen Storage Database (Edlmann, et al., 2024).

Unknown

Saline aquifers

  • Offshore aquifers would likely be in the Aberdeen (1849 TWh), Moray (118 TWh) and Shetland (82 TWh) hubs (Safidi, et al., 2021).
  • Onshore aquifer storage capacity is unknown.

2048 TWh of offshore storage capacity (Safidi, et al., 2021).

Depleted oil and gas fields

  • North Sea fields mostly terminate in the Aberdeen hub at St Fergus (1082 TWh).
  • Some capacity in Shetland (32 TWh).

1115 TWh maximum potential capacity including producing fields (Peecock, et al., 2022)

We scored the hubs based on their total geological storage capacity for hydrogen. We then adjusted these scores to account for the possibility of developing offshore salt caverns and planned pipeline connections to English salt caverns.

Figure 5: Large-scale storage capacity by hub.

Figure 5 shows the relative strength of hubs in terms of geological storage capacity. As shown from left to right, Aberdeen is ranked highest, and the Western Isles is ranked lowest. We can take several key insights from our analysis and the rankings in Figure 5:

  • The most attractive hubs – Aberdeen, Moray, Shetland – are those with terminals for potential offshore geological storage infrastructure.
  • There is a vast opportunity, particularly in Aberdeen, for repurposing depleted oil and gas fields as production tails off. This would extend the fields’ economic value and build on Scotland’s oil and gas expertise.
  • With the construction of a national hydrogen pipeline infrastructure, connected hubs with a lack of geological storage may be able to pipe hydrogen to other storage facilities.
  • Duisburg is advantaged by the fact that nearby hydrogen storage projects are under development (e.g. the RWE Gas Storage West project in Epe) (Hornby, 2023). These projects will be connected to Duisburg by the approved German core hydrogen network.

Pipeline network infrastructure

Scotland is actively pursuing several large-scale hydrogen pipeline projects to maximise the potential of our hydrogen and HDP sector (Scottish Government, 2024). Several key projects include the National Gas Project Union and an offshore pipeline from Scotland to Germany:

  • National Gas Project Union will repurpose sections of the UK National Transmission System to carry 100% hydrogen (National Gas, 2025). These transmission pipelines will stretch from St Fergus in Aberdeenshire, down Scotland’s east coast and throughout the UK.
  • The H2 Caledonia project plans to construct new hydrogen transmission pipeline to support the creation of Scotland’s hydrogen ecosystem (SGN, 2023). This project combines pre-FEED projects in Scotland’s Central Belt, Fife’s East coast and the Aberdeen Vision study.
  • The Scottish Government is in Phase 2 of a project which is considering the development of an offshore pipeline from northeast Scotland to Germany. This would connect Scotland to the European Hydrogen Backbone pipelines (2024).

To score each hub’s potential pipeline infrastructure, we used the following scale from 1-6:

  • There is no pipeline infrastructure suitable for hydrogen and no proposed or planned new hydrogen pipelines.
  • There are existing gas pipelines which can be repurposed. There are no planned new hydrogen pipelines but there may be some projects proposed.
  • There is a small-scale (e.g. distribution/spur pipelines) hydrogen pipeline project at any phase of development.
  • There is a large-scale (e.g. trunkline pipelines) hydrogen pipeline project at any phase of development.
  • The hub is a potential international export or import site for hydrogen and HDPs. However, the planned pipeline infrastructure is insufficient and/or the site is not well-established for international trade.
  • The hub is a potential international export or import site for hydrogen and HDPs. There is sufficient planned pipeline infrastructure, and the site is well-established for international trade.

Figure 6: Hydrogen pipeline network infrastructure by hub.

Figure 6 shows the final hub scores for hydrogen pipeline infrastructure. As shown from left to right, Aberdeen is ranked highest, and the Argyll and Islands is ranked lowest.

We can take several key insights from our analysis and the hub rankings in Figure 6:

  • In Scotland, Aberdeen, Cromarty, Orkney and Shetland are all hubs which could support export activity. They are all being considered as export locations for the Scotland to Germany pipeline project (Net Zero Technology Centre, 2023).
  • Aberdeen and Duisburg rank highest with a score of 6/6.
  • In the Aberdeen hub, St Fergus Gas Terminal is recognised as a well-established export route. St Fergus will be connected to the rest of the UK by the Project Union Hydrogen backbone pipeline project.
  • With the largest inland container port in the world, Duisburg is planning to be a major import hub for hydrogen and HDPs (Gasunie, 2023). The approved 9,040 km German hydrogen core network should connect Duisburg sufficiently (Bundesnetzagentur, 2024).
  • Hubs on the east coast of Scotland will benefit most from national and international trading opportunities. This is due to their relative proximity to mainland Europe and their planned connection to the Project Union and H2 Caledonia pipelines.

Ports

Access to ports is crucial for hydrogen hubs for several reasons:

  • To engage in the trading and export of hydrogen (as a liquid, gas or LOHC) and HDPs by ship.
  • To capitalise on the growing demand for HDPs to be used as shipping fuels, such as ammonia and e-methanol.

We have investigated which hubs are most suitable for meeting maritime shipping fuel demand and for trading hydrogen and HDPs by ship. To evaluate the scale of each hub’s maritime industry, we first scored the hubs based on the total freight traffic through their ports. This analysis was based on the Department for Transport’s Port Freight Statistics Publication (Maritime Statistics, 2024). We adjusted these initial scores based on several criteria, including:

  • Does the hub have a port with existing or planned infrastructure for the storage, production or maritime fuelling of hydrogen/HDPs?
  • Does the hub have a port with dimensions suitable for a typical small carrier vessel for transporting gas or ammonia? The Scottish Government defines these dimensions as a 100m length, 25m beam and a 12m draft (2020, p. 63).
  • Does the hub have a port which is suitable for hydrogen/HDP exports to mainland Europe, as considered by the Scottish Government? Or, for Duisburg, is the hub a key port for hydrogen imports into Europe?

Figure 7: Port suitability for the hydrogen sector (higher score = more suitable).

Figure 7 shows the final hub scores and ranking for ports. As shown from left to right, Duisburg is ranked highest, and the Scottish Borders is ranked lowest. Several key insights can be made based on our analysis:

  • Duisburg ranks highest with regards to port suitability for the hydrogen and HDP sector. As the largest inland container port in the world, Duisburg has by far the largest potential maritime fuel demand (Duisburger Hafen HG, 2025).
  • Considering all of Scotland’s ports, Forth Ports in Grangemouth and Fife have the most freight traffic at around 19 million tonnes in 2023. Although, this figure only represents around half of Duisburg’s total freight traffic.
  • The Scottish Government considers that the Aberdeen, Fife, Grangemouth, Shetland, Cromarty and Orkney hubs are most attractive for exports to Europe (2020). These hubs also have existing or planned port infrastructure for hydrogen.
  • Without port redevelopment, most hubs do not have ports with suitable dimensions for the trade of ammonia by a typical carrier vessel. Those that do include Cromarty, Shetland, Aberdeen and Orkney.
  • The Scottish Borders ranks lowest as it has no major or minor freight traffic in the region, and it scored negatively for all additional criteria.

Local policy and planning support

In Scotland, most industrial planning applications must be approved at the local council level. Local policy and planning support are crucial in sanctioning the construction of hydrogen hubs in Scotland. Streamlined planning processes and supportive local policy will help expedite the development of a robust infrastructure network. To investigate this capability group, we evaluated the industrial planning process duration and success rate for each hub. Hubs with shorter processing times and higher success rates for planning applications indicate that they are more supportive of industry and can support new infrastructure more efficiently.

Processing time for industrial planning applications

To assess hub processing time for industrial planning applications, we have taken an average of the relevant council areas. For Duisburg, the average processing time for construction permits in Germany is used (World Bank, 2024).

Figure 8: Average industrial planning process duration

Figure 8 shows the average number of weeks taken to process an industrial planning application in each hub. Ayrshire and Aberdeen are ranked highest with an average of 6.7 weeks of processing time, while Duisburg has an average 18-week processing time. Several insights can be taken from this analysis:

  • Among the Scottish hubs, the range in average processing time is 10.9 weeks. The range of number of weeks taken is from 6.7 weeks to 18 weeks. This indicates disparity in local planning efficiency.
  • On average, Scottish hubs process planning applications seven weeks faster than German industrial planning applications.

Success rate of industrial planning applications

To calculate the hub success rate for industrial planning applications, we have taken an average of the relevant council areas (Planning Application Statistics, 2024). No data was found for Duisburg, Argyll and Islands, Dumfries and Galloway, Moray, Orkney, Shetland or the Western Isles.

Figure 9: Hubs by average success rate of industrial planning applications.

Figure 9 shows the average success rate of industrial planning applications in each hub. The Scottish Borders is ranked highest with an average of 88%, while Ayrshire ranks lowest with an average of 50%.

When considering the average success rate and processing times for industrial planning applications together, Aberdeen is the most favourable hub for local planning and policy support. However, these two metrics do not always go hand-in-hand. While Ayrshire has the shortest processing duration for planning applications, these applications are also the least successful on average.

Co-location with innovation institutions

Innovation institutions with facilities for pilot-scale testing

Formed by Scottish Enterprise, the Scottish Hydrogen Innovation Network (SHINe) aims to support Scotland’s hydrogen and HDP sectors and accelerate innovation. SHINe innovation institutes can streamline access to the necessary infrastructure and expertise required to develop a successful hydrogen and HDP sectors. To assess this metric, we ranked the hubs by the number of SHINe institutions present. Innovation institutions include a range of projects like pilot-scale manufacturing capabilities of hydrogen related components, green hydrogen production, research centres, etc (Table 7). For Duisburg, we have assessed the number of comparable innovation institutions in the area (Scottish Enterprise, 2025).

Table 7: Innovation institutions and their capability for pilot-scale manufacturing by hub. Hub ranking is shown descending from the top (highest) to bottom (lowest) of the table.

Rank

Hub

Innovation institutions

Pilot-scale manufacturing

1

Duisburg

NH3toH2

Yes

H2BF

Yes

ELECKTRA II

Yes

1

Aberdeen

Energy Transition Zero

Yes

HyOne

Yes

Net Zero Technology Centre

Yes

2

Glasgow

Glasgow Hydrogen Innovation Centre

Yes

Energy Technology Partnership

Yes

Power Networks Demonstration Centre

No

3

Dundee

Michelin Scotland Innovation Parc

Yes

3

Orkney

European Marine Energy Centre

Yes

4

Cromarty

Powerhouse

No

5

All other hubs

There are no SHINe innovation institutions.

No

From Table 7, we can take away several key insights:

  • Aberdeen and Duisburg have the highest number of innovation institutions with pilot-scale manufacturing capabilities.
  • SHINe innovation institutions are mostly concentrated in Scotland’s major cities – Aberdeen, Glasgow, Dundee and Edinburgh. One exception, with pilot-scale manufacturing capabilities, is the European Marine Energy Centre in Orkney.
  • The majority of hubs have no local SHINe innovation institutions.

Financial aspects

While not included in the scope of this project, we recognise that financial aspects can impact hydrogen hub supply chain development. According to the UK Government, the UK’s industrial electricity prices were 25.85 pence per kWh in 2023 including taxes (Energy Prices Statistics Team, 2024). This price is 70% higher than the average of the EU and G7 countries. As electricity costs account for some 70% of the total cost of green hydrogen, these high prices could hamper grid-connected project economics (Renewable UK & Hydrogen UK, 2025). Regional hubs with higher electricity prices could be impacted more. Notably, North Scotland has some of the highest electricity distribution costs in the UK (Gallizzi, 2025). Additionally, rural hubs may experience greater transportation costs to procure goods, services, and labour. For island-based hubs, reliance on a rotational workforce from the mainland could further impact their competitiveness by driving up labour costs.

Overall supply chain capabilities

To assess overall supply chain capabilities, we have calculated a total score for each hub from the metrics discussed above. Each metric has been assigned a specific weight, based on their importance to producing HDPs and the confidence in the quality of available data. Table 8 shows the final weightings we applied to each metric. For each hub, we scaled each metric by the relevant weighting. We then summed the resulting metric scores to give a final score out of 100. The overall hub ranking for supply chain capability is shown in Figure 10.

It is important to note that the purpose of this analysis is not to find the absolute “best” hydrogen hub in Scotland. By ranking the hubs in each metric, we have assessed their relative strengths and weaknesses. This detailed analysis provides the nuance required to understand each hub’s overall supply chain capabilities. The metric weightings selected provide an expert-based view on the supply chain capabilities of each hub. However, as shown by sensitivity analysis (detailed in Appendix B), hub rankings can vary when metric weightings are altered. The conclusions drawn from the final hub scores detailed below should be viewed in this context.

Table 8: Metric weightings for final hub scoring.

Priority ranking

Group weighting

Capability group

Metric

Metric weighting

1

25%

Feedstock and inputs

Maximum potential renewable power generation

15%

Water scarcity

10%

2

23%

Workforce and skills

Full time equivalent workers in energy and engineering

13%

Future workforce requirements

10%

3

22%

Infrastructure

Large-scale storage capacity

3%

Pipeline network infrastructure

7%

Ports

12%

4

15%

Local policy and planning support

Processing time for industrial planning applications

12%

Success rate of industrial planning applications

3%

5

10%

Economic productivity of the energy sector

Gross Value Added of the energy sector

10%

6

5%

Co-location with innovation

Innovation institutions with facilities for pilot-scale testing

5%

Figure 10: Final scores for hub supply chain capability.

From Figure 10, our analysis suggests that the Aberdeen hub has the greatest relative supply chain capability (90/100), while Argyll and Islands has the lowest (27/100). There are several conclusions that we can take from these final scores:

  • Aberdeen stands out as being particularly capable to support the hydrogen and HDP sector. The hub ranked highest for 7 metrics out of 11, including:
  • Maximum renewable power generation
  • GVA of the energy industry
  • Full-time equivalent workers in energy and engineering
  • Large-scale storage capacity
  • Pipeline network infrastructure
  • Processing time for industrial planning applications
  • Innovation institutions with facilities for pilot-scale testing
  • Cromarty and Glasgow are also identified as attractive hubs.
  • The Cromarty hub benefits from excellent access to offshore wind developments, a strong current workforce and major port infrastructure at Cromarty Firth with identified export opportunities.
  • The Glasgow hub benefits from a particularly strong workforce capability and plentiful access to effluent water as well as support from innovation institutions and major port infrastructure from the Clydeport network.
  • While specific strengths vary between hubs, the majority of Scotland’s hydrogen hubs can be broadly grouped by overall supply chain capability.
  • Cromarty, Glasgow, Fife, Grangemouth and Ayrshire fall into an “upper category” with scores ranging only three points (58-61).
  • Dundee, Moray, Dumfries and Galloway, Shetland Orkney and the Scottish Borders broadly fall into the “lower category” with scores ranging from 40-47.
  • The Aberdeen hydrogen hub offers a promising opportunity to compete with local Duisburg supply in the Ruhr region. However, considering their similarly high scores, any of the Scottish hubs in the “upper category” may also be considered to be well placed. As the Ruhr area aims to be a model hydrogen region, this result indicates Scotland’s potential competitiveness in the European market.
  • On the other hand, Western Isles and Argyll & Islands have promising renewable power generation potential. Development of green hydrogen production may therefore help address grid curtailment issues and address local, isolated demand. However, their supply chain capabilities are hindered by a lower workforce capability and fewer connections to suitable ports, large-scale storage and pipelines.

Overall, Scotland’s hydrogen hubs are relatively well balanced in their supply chain capabilities and have the potential to contribute significantly to both the national and international hydrogen market. The Aberdeen and Cromarty hubs particularly excel, while the Western Isles and Argyll and Islands may face resource limitations. By enhancing the strengths of higher-scoring hubs while addressing others’ limitations, Scotland will ultimately improve its competitive position in the global market.

HDP demand in Scotland’s hydrogen hubs

The Scottish Government’s Hydrogen Action Plan identifies that low-cost green hydrogen production is key to the net-zero transition (2022). To minimise the additional cost of transportation and other supporting infrastructure, the Scottish Government plans to encourage the “aggregation of cross-sectoral demand and co-location of the whole hydrogen value chain”. Thus, the efficiency of co-locating supply with high local demand will support the rapid scaling of Scotland’s hydrogen and HDP sectors. This rationale underpins the hydrogen hub model.

In this chapter, we analyse and estimate the addressable market or demand for each HDP in each hub. This analysis will initially provide a view on which hubs are most suited to supporting the development of local HDP demand in Scotland (Section 4.1.5). In Chapter 5, we bring together our supply chain capability and demand analysis to identify co-location opportunities for HDPs.

We assess the hubs based on current demand opportunities, which will initially support rapid market scaling. Therefore, we define HDP demand as the addressable market that HDPs could supply in a complete fuel-switching scenario. This enables us to differentiate hubs and provide a relative view on HDP demand opportunities. We assess four key sectors which could support the aggregation of cross-sectoral HDP demand within Scotland’s hydrogen hubs:

  • Ammonia and e-methanol fuel for the maritime sector.
  • Ammonia-based fertilisers for the agriculture sector.
  • E-methanol feedstock for the chemical sector.
  • SAF for the aviation sector.

To differentiate HDP demand by end use, our analysis considers HDPs used for direct consumption, excluding HDPs used as a hydrogen carrier (e.g. LOHCs).

Please refer to Appendix C for further information on this section’s methodology, sources and raw data.

HDP fuel for maritime shipping

In 2021, UK shipping used over seven million tonnes of fossil marine fuel oils, accounting for 18% of UK transport emissions (Transport & Environment, 2023). As the global regulatory body for shipping, the International Maritime Organisation (IMO) has set a 2050 net zero target for international shipping (IMO, 2023). In conjunction with Scotland’s net zero target, this means that the Scottish maritime industry will seek to replace fossil-based shipping fuels. The UK shipping industry can be decarbonised with HDPs, such as ammonia and e-methanol.

To evaluate the addressable market for these HDPs, we have analysed the current shipping fuel demand for each hub. There are uncertainties on which HDP shipping fuel – ammonia or e-methanol – will predominately address the market. Therefore, we have based our calculation on total energy demand in TWh.

Based on the UK’s 2021 marine fuel consumption, we calculated the annual energy demand for shipping. We then assigned this demand proportionally to each hub according to its total shipping traffic (Maritime Statistics, 2024).

Figure 11: Ranking of hubs by HDP shipping fuel demand.

Figure 11 shows the addressable market for HDP shipping fuel in each hub. Fife and Grangemouth rank highest with 3.5 TWh of demand, while the Scottish Borders ranks lowest with no current demand. From Figure 11 and our analysis, there are several key insights to address:

  • Forth ports in Fife and Grangemouth is likely to be the largest addressable market for HDP maritime fuels, followed by the Clydeport network in Glasgow and Ayrshire.
  • Forth ports and the Inverness and Cromarty Firth port network are Green Freeports (Inverness & Cromarty Firth Green Freeport, 2025; Forth Ports, 2025). These ports have varied tax and custom rules which could incentivise the development of HDPs for maritime fuel.
  • While we have covered shipping demand, there may be other smaller sources of maritime demand for HDP fuels that were out of scope for this project. These sources include fishing vessels, ferries, service vessels and tugs.

Ammonia-based fertilisers for agriculture

The International Energy Agency estimates that around 70% of ammonia produced is used to make nitrogen-based fertilisers (2021). Ammonia production, by the Haber-Bosch process, is fossil-fuel based and highly energy intensive. The process accounts for 2% of the world’s total final energy consumption and 1.3% of carbon dioxide emissions from the energy system (International Energy Agency, 2021). As a sustainable alternative, green ammonia is gaining attention to decarbonise fertiliser production.

We have estimated green ammonia’s addressable market for fertilisers in each hub. First, we estimated total nitrogen-based fertiliser demand in Scotland for cropland and grassland. For this, we used average fertiliser application rates from UK Government data (UK Government, 2023). We also assumed that the nitrogen-based fertilisers were urea and ammonium nitrate, applied in equal proportions. From this assumption, we estimated the ammonia required to produce these fertilisers. Finally, we allocated this ammonia demand across the hubs based on their share of agricultural GVA in Scotland.

It is important to note here that we have only considered nitrogen-based fertiliser in our analysis, and not any other type of fertilisers. Therefore, our demand analysis only represents a subset of demand for fertilisers and not the total demand for fertilisers in Scotland.

Figure 12: Ranking of hubs by demand for green ammonia fertilisers. The ranking is shown from left (highest rank) to right (lowest rank).

Figure 12 shows green ammonia’s addressable market for fertilisers in each hub. Aberdeen ranks highest with 0.14 TWh of demand – around 31% of Scotland’s total demand. Moray and the island hubs rank lowest. Green ammonia’s addressable market will likely be greater on Scotland’s east coast where there is more agriculture.

E-methanol feedstock for chemical production

The International Renewable Energy Agency (IRENA) estimates that around 98 million tonnes of methanol is produced globally each year (IRENA and Methanol Institute, 2021). It is mostly used as a feedstock – a starting material – to produce formaldehyde, acetic acid and plastics. Currently, we produce most methanol from fossil fuels – such as synthetic gas (syngas). Methanol emissions represent around 10% of the chemical sector’s carbon dioxide emissions, and addressing these will be key for decarbonising the sector. E-methanol, produced with green hydrogen and captured carbon dioxide, could address methanol’s current market.

In Scotland, we assume that Grangemouth Chemical Science Park is the only large-scale user of methanol as a chemical feedstock. It is one of only four major chemical parks in the UK, and the only one in Scotland (Scottish Development International, 2023). With the closure of the refinery, Grangemouth’s industrial future is uncertain. However, INEOS’s Olefins and Polymers business will continue running as usual (INEOS, 2024). Their two onsite ethane cracker plants have the capacity to produce 1 million tonnes of ethylene per year (Endeavor Business Media, 2016). Fossil-based hydrogen and methane are produced as a by-product from an ethane cracker and can be used as syngas (Brooks, 2013).

To evaluate the maximum potential addressable market, we assume that this syngas is used to produce methanol. From this, we estimate that e-methanol could address a maximum demand of 100,000 tonnes per year (0.56 TWh).

SAF for aviation

The UK SAF mandate determines the share of SAF in total UK jet fuel demand (UK Government, 2024). It sets key SAF targets of 2% by 2025, 10% by 2030 and 22% by 2040. In securing demand, this mandate incentivises SAF production and supply across the UK.

To evaluate the addressable market for SAF, we analysed the current aviation fuel demand for each hub. To achieve this, we assigned the UK’s aviation fuel consumption in 2022 proportionally to each hub according to its total aircraft movement. To capture Edinburgh airport’s fuel demand, we have assigned it to the nearby Grangemouth hub.

Figure 13: Ranking of hubs by aviation fuel demand.

Figure 13 shows the addressable market for SAF in each hub. The airports in each island hub are shown combined: Shetland includes Lerwick (Tingwall), Scatsta and Sumburgh; Orkney includes Kirkwall and Wick John O’Groats; Western Isles includes Barra, Benbecula and Stornoway; Argyll and Bute includes Cambeltown, Islay and Tiree.

Grangemouth ranks highest with 5 TWh of demand, while hubs with no airports rank lowest. Regionally, about a third of SAF demand would arise from Edinburgh Airport and around a quarter from Glasgow Airport and Glasgow Prestwick. From Figure 13, we can see that locating SAF production around Scotland’s major airports would maximise co-location synergies. Progress has already begun in this area:

  • In 2021, Edinburgh Airport signed a Memorandum of Understanding with Ørsted (Edinburgh Airport, 2021). The partnership recognises the importance of HDPs to accelerate the shift to sustainable air travel.
  • In 2022, AGS Airports which own and operate Aberdeen and Glasgow airports, signed an agreement with ZeroAvia (Glasgow Airport, 2022). This partnership is exploring the development of hydrogen fuel infrastructure for zero-emission flights.
  • In 2024, the Glasgow Airport Hydrogen Innovation Hub consortium delivered a feasibility study for a hydrogen hub at the airport (Glasgow Airport, 2024).

Overall HDP demand opportunities

The maritime and aviation sectors will be the main sources of HDP demand as Scotland scales its hydrogen and HDP sectors. These sectors account for 97% of the roughly 35 TWh addressable market analysed in this report. Due to this scale, our analysis suggests that hubs with major ports and airports would be best suited to develop HDP demand opportunities. In this regard, the hubs that stand out are Grangemouth (with 9.1 TWh of demand opportunity), Glasgow (with 6.1 TWh) and Aberdeen (with 4.4 TWh). Grangemouth’s advantage arises from several factors:

  • An established and experienced chemical industry.
  • Developed port infrastructure within the major Forth Ports network.
  • Proximity to major airports, like Edinburgh Airport.

The Scottish Borders notably have the lowest demand opportunity overall. It is disadvantaged by the lack of shipping, aircraft traffic and chemical industry as well as a relatively small agricultural sector.

The potential demand opportunity for HDPs is greatest for SAF with a total addressable market of approximately 18 TWh. In comparison, e-methanol and green ammonia have a combined total of around 17 TWh.

Overall, our demand analysis has identified that focus should be placed on developing major offtake opportunities from the maritime and aviation sectors. This focus would best facilitate the large-scale and rapid scaling of the Scotland’s domestic HDP market. As the Scottish Government identified in the Hydrogen Action Plan, aggregating multiple end-use applications for production streams would improve the economic benefit of Scotland’s hydrogen hubs. Therefore, while SAF does have the greatest demand opportunity, it is worth noting that green ammonia and e-methanol have more diverse end uses and so would be better suited for demand aggregation. As such, each HDP has a distinct potential role in accelerating Scotland’s hydrogen and HDP sectors.

Co-location of HDP supply chain capabilities and demand opportunities

The Scottish Government recognises that co-location of supply and demand will help develop a sustainable domestic hydrogen and HDP sectors (2022). This development is required to establish Scotland in the wider global market (2022). In this chapter, we bring together our insights from the supply chain capabilities in Chapter 0 and the demand analysis in Chapter 4. This enables us to identify co-location opportunities for HDPs within Scotland’s hydrogen hubs.

Figure 14 summarises the co-location opportunity in each hub. The x-axis shows the overall supply chain capability score; the y-axis and bubble size show the aggregated demand opportunity. The top right quadrant broadly indicates which hubs may be best suited for co-location.

Figure 14: Overall co-location analysis showing the relative supply chain capability on the x-axis and the demand opportunity on the y-axis and as the relative bubble size.

From Figure 14, it is interesting to note that the top hydrogen hub for supply chain capability is not the one with the greatest demand opportunity. Aberdeen has the greatest supply chain capability score (93/100) while, with Edinburgh Airport and Forth Ports, Grangemouth has the greatest HDP demand opportunity (9.1 TWh). This supports the idea that these analyses should not be looked at in isolation. Rather, differing hub strengths can favour the development of different sections of the HDP economy.

Looking at the top right quadrant, we note that Aberdeen, Glasgow and Grangemouth are most aligned to facilitate the development of a regional, co-located HDP economy. In general, the hubs identified as strongest in supply chain capability – including Grangemouth, Aberdeen, Glasgow, Fife and Cromarty – are also those with greater demand opportunity.

We identify the Western Isles and Argyll and Islands as hubs which may need further support to develop their supply chain capabilities. On the other hand, the Scottish Borders and Moray may need to identify other, smaller offtake sectors to capitalise on co-location efficiencies.

The balancing of supply and demand opportunities will require careful consideration, particularly in the early stages of Scotland’s hydrogen and HDP sector development. Favouring supply opportunities could increase the cost and logistical complexity of transportation and storage to address more distant demand. Conversely, locating supply based on demand opportunities could limit the capacity and the economics of supply.

Overall, the diversity of Scotland’s hydrogen hub strengths points to the importance of a cross-hub approach, in addition to co-locating demand with supply. Hubs with greater connectivity to pipeline and port infrastructure, such as Aberdeen, will be more able to take advantage of this approach. As suitable pipeline and port infrastructure develops, supply and demand opportunities will be unlocked that are not possible by co-location. For example, piped green hydrogen from Fife could support HDP production in the adjacent Grangemouth hubs. For hubs with lower connectivity, such as the Western Isles, further development of suitable infrastructure is required to access cross-hub opportunities. Overall, the growth of HDP production will require both cross-hub and co-located approaches. Balancing these will help maximise each hub’s potential and, ultimately, that of the hydrogen sector itself.

Regulatory considerations for the HDP sector

Each HDP has different health, safety and planning requirements due to differing chemical properties. These requirements are stipulated by UK regulations. Higher hazard HDPs may face more severe limitations in how, where, and in what quantities they can be handled, for example for production or storage. This section explores the UK regulatory environment and its potential impact on the development of the HDP economy in Scotland.

Hazards associated with HDPs

Table 9 shows the physical, health and environmental hazards of hydrogen and HDPs. These hazards were identified from the standardised safety data sheet for each substance. The LOHC that we analysed was methylcyclohexane (MCH), the most common LOHC. The rating from 1-4 indicates the highest hazard severity category for each hazard type. According to the Globally Harmonised System classifications, a Category 1 hazard is the most severe while a Category 4 hazard is the least severe (United Nations, 2019).

Table 9: Hazards of hydrogen and HDPs from 1 (most severe) to 4 (least severe).

Substance

Physical hazard

Health hazard

Environmental hazard

Hydrogen

1

4

4

Ammonia

2

1

1

E-methanol

2

1

4

LOHC (MCH)

2

1

2

SAF

3

1

2

From Table 9, we can see that ammonia is the most hazardous substance overall. Handlers must monitor it closely to mitigate its Category 1 health hazard and environmental hazards. LOHCs, E-methanol and SAF are less hazardous overall, although all also have Category 1 health hazards. This means that handling these HDPs is generally less inhibitive than for ammonia. As a feedstock, hydrogen’s severe flammability and explosion hazards should also be considered carefully for any HDP production development.

Review of key UK regulations affecting HDP handling

Due to these physical, health and environmental hazards, HDP production is strictly controlled by UK regulations and regulatory authorities. With the exception of LOHCs, HDPs like ammonia, methanol and aviation fuel are already produced and handled on a large-scale globally. Therefore, there are relatively few new regulatory issues concerning these HDPs. We have reviewed several key regulations that site handling HDPs must adhere to. These are detailed in Table 10.

Table 10: Key regulations and regulatory bodies and their implications for HDP production.

Regulation/Regulatory Body

Implications for a HDP production site

The Control of Major Accident Hazards (COMAH) Regulations

  • Operators should submit an environmental risk assessment. All measures necessary must be taken to prevent major accidents.
  • The site must register as a COMAH site based on the quantity of hazardous substances stored or processed. There are two tiers of sites: Lower and Upper.
  • Operators should identify sensitive environmental receptors within 10 km.

UK registration, evaluation, authorisation and restriction (UK REACH) of chemicals

  • The development is subject to UK REACH regardless of company size.
  • If manufacturing or importing one tonne per year or more of any substance, the company must register the substance with the Health and Safety Executive.
  • The development must comply with both UK REACH and EU REACH regulations where necessary.

Town and Country Planning (Environmental Impact Assessment) (Scotland) Regulations 2017

  • The development must obtain planning permission from the relevant planning authority.
  • Hazardous Substances Consent is required if more than two tonnes of hydrogen are onsite or if hydrogen is present with other chemicals.
  • An Environmental Impact Assessment is required for certain developments.

Health and Safety Executive (HSE) and Scottish Environment Protection Agency (SEPA)

  • These regulatory bodies enforce the compliance of COMAH, as well as other environmental and safety regulations.
  • They are consulted for many planning applications.

It is important to note that, under COMAH, each HDP is subject to different regulatory requirements based on their hazards, classified by the Globally Harmonized System (GHS). Based on the COMAH Lower Tier threshold quantity for each HDP, we have broadly ranked the HDPs by the regulatory stringency required to manage its hazards.

Table 11: Rank of HDPs by their COMAH Lower Tier threshold. The associated energy content of LOHC assumes the theoretical hydrogen storage content of MCH (6.22 wt%). Energy content of the HDPs was sourced from (Ozkan, et al., 2024).

HDP

Lower Tier threshold (tonnes)

Energy content (MJ/kg)

Associated energy content (TJ)

Rank (1 = most stringent, 4 = least stringent)

LOHC (MCH)

50

120 (for H2)

0.4

1

Ammonia

50

18.8

0.9

2

E-Methanol

500

19.9

10.0

3

SAF

2500

45.7

114.3

4

From Table 11, we can see that LOHC and ammonia are the most stringently regulated by COMAH with the same Lower Tier threshold of 50 tonnes. However, as an energy carrier of hydrogen, LOHC handling is more limited by the threshold. The associated energy content of LOHC is 0.5×1012 J lower than that of ammonia. In comparison, e-methanol and SAF are less stringently regulated by COMAH. By energy content, a Lower Tier COMAH site would be able to handle 25x more e-methanol or over 250x more SAF than LOHC. Therefore, based on the stringency of COMAH regulations, the simplest HDP to handle is SAF, followed by e-methanol, ammonia and LOHC.

Hub-level regulatory capabilities

Considering the hazards associated with hydrogen and HDPs, hubs with more regulatory experience are likely to be better suited to handling these substances safely. For HDP production, existing COMAH sites may be expanded or new COMAH sites developed. As a broad measure of current and relative regulatory experience at a hub level, we will evaluate the number and tier level of COMAH sites present in each hub. The presence of COMAH sites, with their existing infrastructure and workforce, indicates that a hub may be more capable at handling hazardous HDPs safely according to regulation. Identifying these sites can also provide insights into potential offtakers as well as production, storage and distribution sites for HDPs.

Figure 15: Number of Upper Tier COMAH sites present in each hub.

We have assessed the number of registered COMAH sites in each hub as of June 2023 (Health and Safety Executive, 2023). There are two tiers of COMAH site: a Lower Tier and an Upper Tier. Upper Tier sites are more stringently regulated since they handle greater quantities of hazardous substances. Figure 15 shows the number of Upper Tier COMAH sites in each hub. Grangemouth has the most (16), including the Grangemouth Terminal and INEOS chemical sites. This indicates that the Grangemouth hub, and its associated workforce, may have the most regulatory experience for the large-scale handling of hazardous chemicals. The terminal, for instance, already facilitates the supply of Scotland’s aviation fuel (Forth Ports , 2025).

Key COMAH Upper Tier sites include:

  • The St. Fergus Gas Terminal in the Aberdeen hub. This site receives, processes and compresses North Sea gas for the National Transmission System as well as stores and distributes other chemicals and fuels (North Sea Midstream Partners, 2025).
  • The Clydebank Terminal operated by Exolum in the Glasgow hub. This site has a storage capacity of 56,257 m3 and a jetty to receive and storage liquid products, including fuels (Exolum, 2025).
  • Moray’s sites are predominately distilleries which are engaged offtakers for the hydrogen sector. In March 2025, Storegga submitted a planning application to Moray Council to construct a 25 tonne per day green hydrogen facility to decarbonise local distilleries (Storegga, 2025). The UK Government has also found LOHCs to be a viable option for supplying hydrogen to distilleries, and could be explored further for the decarbonisation of Scotland’s distilleries (BEIS, 2021).

These hubs are likely to have a lower safety risk for handling HDPs. This is due to their existing regulatory experience and infrastructure. These insights are supported by the fact that the number of COMAH sites in each hub generally aligns with its overall supply chain capability score: the “upper” and “lower” hub groupings are broadly preserved. In comparison, the Scottish Borders has only one Lower Tier COMAH site, a fuel storage and distribution site operated by Flogas Britain. This relatively limited experience could indicate that there is greater need for local workforce training, community engagement and risk communication and investment into infrastructure to support the safe development of a local HDP sector.

Overall, this broad hub-level analysis has provided an indication of hubs’ regulatory capabilities. While out of scope for this project, individual assessment of existing and potential COMAH sites would add value to the analysis. This would provide greater detail into the specific capabilities of each hub to handle, produce and distribute HDPs safely, in accordance with regulations.

Policy gap analysis

In the previous chapters, we identified the strengths and barriers for Scotland to scale up its HDP market. To maximise opportunities a favourable and clear policy landscape is needed. This landscape must consider policy at a devolved, national and regional level. This will ensure that Scotland’s HDP related policies work with UK and EU specific policies in a harmonious manner.

To that end, we analysed relevant policies in the UK, Scotland or the EU. We considered policies in the following categories:

  • Subsidies and obligations
  • Supply chain/infrastructure development
  • Technical and safety regulations
  • Licensing
  • Planning and consenting

Scottish policy gaps

Here we describe the main policy gaps, and the resultant risks, faced by the Scottish HDP industry. The Scottish Government has already taken some positive steps. However, plugging some gaps will significantly improve the standing of the industry.

Supply chain incentives/development for HDPs

The Scottish Government recently published plans to realise export opportunities for green hydrogen (International Trade and Investment Directorate, 2024). Although this a very important step in furthering the interest of Scottish exports to nearby regions, there are still some gaps remaining. The government’s plan identifies the various investment opportunities and barriers. However, there is a need for more clarity on how the Scottish Government will collaborate with the UK Government or build relationships with international export partners. Timely publication of such plans will provide investors with more certainty.

Clarity in planning and consenting

The Scottish Government has made substantial progress in improving the planning regime for hydrogen projects. The government is committed to preparing and training its planning authorities to expedite hydrogen planning applications. Additionally, it also aims to provide planning authorities with access to specialist expertise and staff upskilling. The government aims to do this this by introducing the planning hub. As a first step towards achieving their goal of improving the planning regime, the Scottish government conducted stakeholder engagement (Improvement Service, 2025), which attempted to understand concerns of both the planning authorities and industry.

The Improvement Services report focussed on five areas: understanding of hydrogen within planning applications, regulatory regime, more clarity on planning process, impact and risk of hydrogen manufacturing, and spatial factors. Some of the key concerns raised by the planning authorities were about lack of clarity on roles when multiple bodies are involved in a planning/consenting process. Additionally, resource constraints faced by the authorities and lack of awareness about hydrogen applications are some of the other concerns raised. For industry, some of the major points raised concerned uncertainty regarding water availability and Hydrogen Allocation Round (HAR) timelines. Industry also proposed conducting wider public engagement to spread awareness about how hydrogen can safely play a role in Scotland’s net zero transition.

All this effort has been crucial in shining some light on the challenges faced by industries and policymakers. To fully capitalise on this initiative, the government should now focus on implementing the findings and recommendations from their engagement.

UK policy gaps

The UK government has implemented many policies that have boosted green hydrogen development in the national economy. Our analysis concludes that the success of such policies should be replicated to similarly develop the HDP space.

Lack of HDP considering in subsidies and obligations

The Hydrogen Storage Business Model (HSBM) does not currently include HDPs in its scope.

There are a number of benefits to including HDPs in HSBM. It would increase the avenues available for storing hydrogen. It would also allow for small scale storage of hydrogen in the form of hydrogen derivatives (HSBM currently focusses on large-scale hydrogen storage). Additionally, inclusion of HDPs in scope may mitigate some of the challenges associated with storing hydrogen, such as safety concerns. For example, as ammonia contains hydrogen, including it in HSBM could act as an alternative way of storing hydrogen.

Supply chain incentives for industry and innovation

We identified a policy gap in relation to encouraging links between industrial clusters, which are well suited to producing HDPs. Chapter 4 showed how there are multiple hubs which are optimal for producing HDPs. Collaboration between the different clusters in these hubs would allow for sharing knowledge and potentially products as well.

There also needs to be a focus on conducting trial and demonstration projects. Many hydrogen projects will use innovative technology which will need to be proven and demonstrated in real-life settings. Trials will go a long way in assessing whether investing in such technologies is worthwhile.

Updating technical and safety regulations

Regulations regarding hydrogen need to be updated in the UK. Onshore hydrogen projects are regulated under the Gas Act 1986 and Planning Act 2008, and hydrogen is generally referred to as a ‘gas’. The Gas Safety Management Regulation (GSMR) prohibits injecting more than 0.1% of hydrogen into gas networks. Although there are discussions ongoing to exempt hydrogen from this rule, there needs to be more clarity here (Pinsent Masons, 2023). Repurposing the gas network to enable hydrogen transport is essential to grow the HDP sector. Green hydrogen is an important input for HDPs. Hence, a developed transport system will remove supply bottlenecks for HDP producers.

Clarity in offshore licensing

The industry seeks more clarity on the timeline and details of future offshore hydrogen regime. These projects will be critical in developing HDP production.

Delays in planning and consenting

Green hydrogen and HDP projects require various regulatory approvals, environmental permits, etc. Many investments are subject to approval of such plans. Delays associated with the planning and consenting regime may extend the lead time of green hydrogen projects. Streamlining the regime will mitigate some of these issues.

International policy gaps

Lack of clarity on emissions factors

There is an urgent need to standardise the emission factors for many fuels, such as ammonia or methanol. Sectors that use such fuels will need a standard emission factor as it eases carbon accounting and adhering to different regulations.

Lack of a standard framework for low-carbon hydrogen

There is a misalignment between low-carbon hydrogen standards in different countries. To foster international trade, a uniform definition of low-carbon hydrogen is needed.

Recommendations

Chapter 7 outlines relevant current policies that can enable development of the hydrogen and HDP sectors in Scotland. While introducing such policies is a significant step towards building the hydrogen space in the UK, some gaps remain. In addition, there is policy action required at an international level. Addressing these issues will significantly improve the prospects of Scotland’s hydrogen and HDP sectors.

A summary of our recommendations is as follows:

  • The Hydrogen Sector Export Plan showcases the Scottish Government’s commitment to building hydrogen export capabilities. However, there is a need for more information on how the Scottish and the UK governments will work together with potential trade partners.
  • Scottish Government should continue the progress on building a hydrogen planning regime. This will build on the introduction of the planning hub and the subsequent stakeholder engagement. This momentum should be continued by addressing the main findings of the Improvement Services report.
  • The UK Government should include HDPs in the scope of subsidies like HSBM. HDP projects face similar risks as hydrogen projects. Therefore, providing similar subsidies to HDPs projects will mitigate risks and provide more certainty.
  • Due to many hydrogen projects using innovative technology, there is a need for increasing the number of trials and demonstration projects.
  • Another important issue is the potential misalignment of many standards and definitions. For instance, different governments should collaborate and decide on a common definition for low-carbon hydrogen. These misalignments will hinder growth opportunities as they increase the risk for potential traders.

There needs to be a more detailed plan for prioritising hub development. Our analysis highlighted the strengths and weaknesses of each hub. These results should be used to organise collaboration between production and demand hubs. Additionally, as shown in the co-location analysis, the ideal production hubs aren’t necessarily the same as the key demand hubs. Sorting this misalignment might require government intervention and support.

Conclusions

In our examination of Scotland’s industrial capabilities to produce hydrogen derivatives and products, we looked at supply chain capabilities, demand opportunities, regulatory and policy analysis.

Our assessment of co-location of supply chain capabilities with demand suggests Aberdeen and Grangemouth stand out as key hubs for the development of HDP production. Additionally, Cromarty and Ayrshire offer strong supply chain capabilities and Glasgow and Fife present significant demand opportunities. Meanwhile, the Western Isles and Argyll and Islands may require targeted support to enhance their supply chain capabilities. The Scottish Borders may need support in developing greater regulatory experience to facilitate HDP development.

Many of the Scottish hubs scored highly on the metric of renewable power generation capacity. This is evidence of Scotland’s biggest strength: access to renewable energy. Regions like Aberdeen, Cromarty, Moray, Shetland and Western Isles were the highest scores. Regarding local policy and planning support, Aberdeen, Ayrshire and Scottish Borders were among the top performers.

Given the nascency of HDP production, a favourable policy environment is needed to ensure rapid adoption of these fuels. In Scotland a more nuanced planning regime would help to support the growth of HDP adoption. Scotland would benefit from a planning regime that accounts for its specific geographic factors.

At the UK level, HDPs should be included in the scope of policies like HSBM. Health and safety regulations should be updated to account for the increasing role of hydrogen and HDPs in the economy of the future.

Our analysis shows that for Scotland to meet its aims of becoming a major exporter of HDPs, it will need a holistic approach to evaluating the strengths of Scotland’s potential hydrogen hubs.

Overall, by balancing cross-hub collaboration with localised development, Scotland can maximise the potential of HDP production from green hydrogen, driving the sector’s long-term growth and resilience.

 

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Appendices

  1. Current state of play

To understand the role that Scotland can play in the hydrogen and HDP sectors of the future, a thorough review of literature was undertaken. The current state of the hydrogen and HDP sectors in Scotland will very much dictate its future prospects. For the purposes of this study, the literature review focussed on many factors associated with the production and export of hydrogen by Scotland. The review allowed us to identify certain common themes related to Scotland’s ambition for net zero and revealed hydrogen’s role in achieving those goals.

We explored the potential key drivers and enablers of the hydrogen and HDP sectors. Then, we analysed barriers Scotland is likely to face in growing its hydrogen supply chain capabilities. Apart from studying strengths and weaknesses specific to Scotland, we also analysed factors specifically relevant to the HDPs in scope of our study.

Scotland specific factors

Most of the literature reviewed concludes that Scotland is very well-placed to be able to produce green hydrogen in the future. There are many factors that work in Scotland’s favour. First and foremost, Scotland’s access to abundant levels of renewable energy, especially offshore wind, is a major strength (ClimateXChange, 2023). Production of green hydrogen will require renewable electricity as the major component. Scotland’s wind resources make it very suitable for producing green hydrogen.

Another major key driver for Scotland’s hydrogen and HDP sectors is the ambitious policies in the EU. These policies are likely to spur hydrogen demand in the next few decades. According to the RePowerEU Strategy, the EU aims to import 10 million tonnes of hydrogen by the year 2030. This provides Scotland with a significant opportunity to be a major exporter of low-carbon hydrogen to the EU (Scottish Government, 2022). Since the Russia-Ukraine conflict, the EU also aims to stop importing natural gas and rely on its domestic capabilities (Scottish Power, 2022). This will also likely further the usage and demand for hydrogen in the continent.

Scotland is also likely to benefit significantly from its geographical proximity to the EU. Hence, Scotland may transport hydrogen and HDPs to the EU at costs lower than faraway regions like North America, the Middle East or Asia (ClimateXChange, 2023).

In addition, there are other factors working in Scotland’s favour. For example, Scotland has a vast oil and gas industry with a highly skilled workforce. These skills can be transferred to the hydrogen and HDP sectors (Scottish Enterprise, 2024).

On the other hand, the literature reviewed also highlighted areas which need further development and focus to enable green hydrogen production. One of the biggest weaknesses identified in the literature is the high costs associated with electricity generation. Electricity cost is one of the biggest components of green hydrogen production. Currently, cost of electricity generation is much higher in Scotland compared to other competitor regions like the USA or the Middle East (ClimateXChange, 2023). This makes green hydrogen production in Scotland more expensive than regions like the US or the Middle East. This could reduce Scotland’s competitive edge to export to the EU.

Past studies also point out the lack of electrolyser manufacturing capabilities in Scotland as a potential bottleneck (ClimateXChange, 2024). Another major challenge faced by Scotland is regarding transporting and storing hydrogen or HDPs (Optimat and Scottish Enterprise, 2023). Scotland lacks a dedicated pipeline infrastructure that could be used to transport hydrogen to the EU. However, many studies point out the possibility to repurpose existing gas pipelines and use them for hydrogen transport. Scotland also lacks onshore deposits for salt caverns. However, this can be mitigated by the existence of depleted gas fields and lined rock caverns (ClimateXChange, 2024).

Some of the studies also mention the lack of projected demand for hydrogen in Scotland as a potential issue. Scotland is not expected to demand very high levels of hydrogen, meaning hydrogen supply capabilities will be built to service external demand. Increasing demand will be contingent on the policies that will be enacted in the future.

Similarly, studies have pointed out the need for more clarity from the government on possible policy actions (Scottish Enterprise and Optimat, 2023). The sector will also benefit from a coordinated response to tackle supply chain issues and more visibility into existing opportunities. Databases similar to the Offshore Energy UK’s Supply Chain Visibility Tool and the North Sea Transition Authority’s (NSTA) Energy Pathfinder will increase awareness and information regarding opportunities and enable potential investors to make informed decisions (Aberdeen City Council, n.d.).

The lack of clarity and uncertainty regarding future policy making explain why hydrogen demand projections by different studies vary significantly. Latest demand projections for Scotland for hydrogen expect demand to be in the range of 0.6-2.7 TWh for 2030 and 2.7-24.7 TWh for 2050 (Morton, et al., 2025). Some studies project the economic impact of exporting hydrogen products to the EU. According to the ambitious scenario of the Hydrogen Action Plan, 2022 report, exporting hydrogen to the EU could create roughly a total of 300,000 jobs in Scotland by 2045. It could also add roughly £25 billion every year to the Scottish economy by 2045 (Scottish Government, 2022).

The findings from these studies show that Scotland has inherent strengths that can be harnessed to build and grow strong hydrogen and HDP sectors. Scotland’s access to renewable energy and the skills possessed by existing workforce puts it in a very robust position. However, building supply chain capabilities in Scotland will also come with its own challenges. The biggest challenge faced by Scotland is the high cost of generating renewable electricity. Lack of storage and transport infrastructure is also a big issue. Many studies have pointed out the need for government support to mitigate such challenges.

HDPs specific literature review

The literature review conducted also focussed specifically on the current state of HDPs production in Scotland and the UK. In some cases, it makes more economic sense to use a hydrogen product than hydrogen itself to achieve decarbonisation. This is specifically true for two hard-to-abate sectors: aviation and shipping. Two of the most mentioned hydrogen products in our literature review were sustainable aviation fuels (SAFs) and ammonia.

SAFs are expected to play a major role in decarbonising aviation. Currently, very little SAF is supplied to Scottish airports. Nevertheless, in the long-term, SAFs will be key to replacing high-carbon jet fuels. According to the SAF Mandate, roughly 2% of the UK’s jet fuel demand in 2025 will be from SAFs. The share of SAFs in final jet fuel demand will increase to 10% by 2030 and to 22% by 2040. The global SAF demand is expected to reach 22.7-32.8 million tonnes by 2030 (Scottish Enterprise and Optimat, 2023).

In addition to SAFs, using hydrogen directly as a fuel is also a solution that can be deployed to decarbonise aviation. Direct use of hydrogen in aviation is not expected to be used as much as SAFs (Scottish Enterprise and Optimat, 2023). This is partly because of hydrogen not being a drop-in fuel, whereas SAFs are. Drop-in fuels are fuels that can be used in an airplane without making any modifications to the engine. This increases cost for air carriers to use it as an alternative to high-carbon fuels currently used. Another major concern is the safety issues that using hydrogen will pose. In addition, due to hydrogen being a lighter fuel, its volumetric density is lower. This means that a lot more hydrogen will be required to operate an airplane, increasing storage requirements and also increasing the weight of the plane. However, even if hydrogen is not used as a fuel itself, it will still play a big role in decarbonising aviation as it is an important input in the production of many SAFs. One such example is Power-to-Liquid (PtL) fuel. PtL fuels are formed by combining carbon and hydrogen together. Renewable electricity is used to remove carbon from CO2 and H from water, making the whole process zero-carbon. The PtL technology is also at a mature technological readiness level (German Environment Agency, 2016).

Similar to SAFs in aviation, low-carbon fuels will play an important role in decarbonising shipping. The hydrogen products mentioned in literature as potentials fuels to decarbonize marine transport are ammonia and methanol. The biggest concern regarding these products is the relatively weak supply chain capabilities in Scotland when compared to the EU. An example of this is the weak shipbuilding supply chain and fewer active commercial shipbuilders of scale. Scotland is unlikely to be able to meet the demand for these fuels for even a small number of cargo vessels (Optimat and Scottish Enterprise, 2023). Security factors could be another possible concern with ammonia. Ammonia is a very toxic fuel, which should only be handled by qualified personnel. Despite their importance in decarbonising certain sectors, the current production of these products is limited. Therefore, more focus needs to be placed on increasing their supply.

Need for further research

Many studies have focussed extensively on analysing both demand- and supply-side factors of Scotland’s hydrogen and HDP sectors. However, our research found that there is not enough information about different geographical hubs in Scotland and the role they can play. The lack of individual focus on different hubs has motivated this study.

  1. Supply chain capabilities of Scotland’s hydrogen hubs

Maximum potential renewable power generation

The maximum potential renewable power generation is defined as the total current, planned and announced installed capacity of solar PV and wind power projects in each hub region. Data was provided by council authority, so data was aggregated according to the defined council authority groupings for each hub. 2023 installed capacities were obtained from the DESNEZ Regional Renewable Statistics (2024). To obtain current capacity, this data was supplemented by projects that came online in 2024, as reported by the DESNEZ Renewable Energy Planning Database (REPD) and desk-based research (2024). Offshore wind projects were assigned to hubs based on their onshore landing points. The resulting current capacities were scaled by the 2023 average load factor for Scotland, appropriate to each technology (DESNEZ, 2024).

The REPD was also used to calculate planned installed capacity. From this database, development statuses encompassed under “planned” included:

  • “Under Construction”.
  • “Awaiting Construction”.
  • “No Application Required”.
  • “Application Submitted”.
  • “Revised”.

For announced installed capacity, we included the 27.6 GW of ScotWind leasing round projects (Offshore Wind Scotland, 2024). The likely onshore landing point (and so corresponding hub) was identified from individual project websites. If this information was not available, the closest hub was allocated the offshore capacity. We included additional announced wind and solar projects from the Global Energy Monitor tracker (2025). To scale the resulting planned and announced capacities, we used load factors reported by DESNZ for UK new build projects (for delivery years 2026-2029) (2024).

To obtain the maximum potential renewable energy power generation for each hub, we then summed the current, planned and announced solar PV and wind power generation. We ranked the hubs from 1 (least generation) to 15 (highest), as shown in Table 13.

Table 12: Summary of data used for the calculation of maximum potential renewable power generation.

Data category

Unit

Value/Data used

Source

Confidence rating

Installed capacity – 2024

MW

Installed capacity of solar PV and wind projects by council authority

(DESNEZ, 2024)

(DESNEZ, 2024)

3

Installed capacity – planned

MW

Planned installed capacity of solar PV and wind projects.

(DESNEZ, 2024)

3

Installed capacity – announced

MW

Capacity of announced solar PV and wind projects

(Offshore Wind Scotland, 2024) (Global Energy Monitor, 2025)

2

Current load factors for Scotland

%

PV: 9.5%

Onshore wind: 23.6%

Offshore wind: 29.5%

(DESNEZ, 2024)

3

Load factors for UK new build projects

%

PV: 10.8%

Onshore wind: 44.8%

Offshore wind: 62.3%

(Department for Energy Security & Net Zero, 2024)

2

 

Table 13: maximum potential renewable power generation by hub.

Hub

Current maximum potential renewable power generation (GW)

Planned/announced maximum potential renewable power generation (GW)

Rank (1 = lowest to 15 = highest)

Aberdeen

0.18

10.87

15

Argyll and Islands

0.10

1.50

8

Ayrshire

0.34

0.75

7

Cromarty

0.49

2.83

14

Duisburg

0.01

0.00

1

Dumfries and Galloway

0.27

1.41

9

Dundee

0.01

0.40

4

Fife

0.03

0.34

3

Glasgow

0.44

0.41

5

Grangemouth

0.06

0.05

2

Moray

0.57

2.08

13

Orkney

0.01

1.95

10

Scottish Borders

0.15

0.78

6

Shetland

0.11

2.07

12

Western Isles

0.01

2.05

11

Water availability

In 2022, Ramboll, on behalf of SGN, investigated water availability for green hydrogen production across Scotland (Ramboll, 2022). This estimated hubs’ maximum green hydrogen production potential based on current water availability and forecasted hydrogen production capacity for 2045.

Water availability was defined as the total volume of effluent water and fresh water, including groundwater, surface water and potable water. Sea water was excluded from the analysis as its availability is effectively unlimited and it is accessible to all Scottish hubs. To evaluate potential water availability, we took the difference between Ramboll’s forecasted green hydrogen production capacity and the maximum production potential for each hub.

To ensure a fair comparison, we used the same methodology and assumptions for Duisburg as for the Scottish hubs. Ramboll outlines this approach on pages 26–27 of their report

(2022). According to the Jülich research centre, Duisburg could have a maximum installed hydrogen capacity of 1 GW by 2050 (Cerniauskas, et al., 2021, p. 79). Since no specific data was available for 2045, we assumed that the installed capacity would be the same as in 2050.

The total water availability for hydrogen production in Duisburg is approximately 18,697,000 cubic metres. This includes:

  • 2,697,000 cubic metres of non-used fresh water ( Statistische Ämter des Bundes und der Länder, 2025).
  • 16,000,000 cubic metres of effluent water from central waste treatment plants (Wirtschaftsbetriebe Duisburg, 2025).

Based on Ramboll’s assumptions, green hydrogen production requires 10 kg water per kg hydrogen. Additionally, we should account for a 20% water loss. Using 2,697,000 cubic metres of fresh water, the maximum hydrogen production potential is approximately 1.5 million tonnes. This result was converted to kilowatt-hours (kWh) using the lower heating value for hydrogen (33.3 kWh). We estimated that Duisburg’s maximum hydrogen production potential is 14 GW using the following equation:

The assumptions for this calculation are detailed in Table 14. Finally, we calculated Duisburg’s water availability by taking the difference between its forecasted hydrogen production capacity and its maximum production potential.

The final rankings from 1 to 15 (with 1 representing the hub with the least water availability) are shown in Table 15.

Table 14: Summary of data used for the calculation of water scarcity.

Data category

Unit

Value/Data used

Source

Confidence rating

Forecasted green hydrogen capacity in Scotland

GW

  • Maximum green production capacity for each hub in 2045.
  • The value for SW Scotland was distributed to the Dumfries and Galloway and Ayrshire hubs equally.

(Ramboll, 2022, p. 3)

2

Surface water availability in Scotland

GW

  • Maximum green hydrogen production capacity for each hub based on surface water availability.
  • The value for SW Scotland was distributed to the Dumfries and Galloway and Ayrshire hubs in a 3:1 ratio. This ratio, and the value for the Scottish borders, was estimated roughly from Figure 15 of the source report.

(Ramboll, 2022, pp. 3, 34)

2

Groundwater availability in Scotland

GW

  • Maximum green hydrogen production capacity for each hub based on groundwater availability.
  • The value for SW Scotland was distributed to the Dumfries and Galloway and Ayrshire hubs in a 1:8 ratio. This ratio, and the value for the Scottish borders, was estimated roughly from Figure 16 of the source report.

(Ramboll, 2022, pp. 3, 35)

2

Effluent water availability in Scotland

GW

  • Maximum green hydrogen production capacity for each hub based on effluent water availability.
  • The value for SW Scotland was distributed to Ayrshire which had the Wastewater Treatment Works. The value for the Scottish borders, was estimated roughly from Figure 18 of the source report.

(Ramboll, 2022, pp. 3, 37)

2

Forecasted green hydrogen capacity in Duisburg

GW

Estimated installed green hydrogen capacity in 2050. Based on Figure 73 of the source report.

(Cerniauskas, et al., 2021, p. 79)

2

Electricity to hydrogen conversion efficiency

%

69%

(Ramboll, 2022, p. 20)

2

Annual operating hours

hrs

7350

(Ramboll, 2022, p. 20)

2

Average operating load

%

70%

(Ramboll, 2022, p. 20)

2

Lower heating value of hydrogen

kWh

33.3

(U.S. Department of Energy, 2025)

3

Water loss allowance

%

20

(Ramboll, 2022, p. 27)

2

Freshwater availability in Duisburg

Cubic metres

Non-public fresh water discharged unused/water given to third parties in 2019.

( Statistische Ämter des Bundes und der Länder, 2025)

3

Effluent water availability in Duisburg

Cubic metres

Total annual wastewater treated in the three municipal wastewater treatment plants.

(Wirtschaftsbetriebe Duisburg, n.d.)

3

Table 15: Raw data and rank for water availability by hub.

Hub

Forecasted green hydrogen capacity in 2045 (GW)

Maximum green hydrogen potential based on total water availability (GW)

Rank (15 = most available to 1 = least available)

Aberdeen

0.50

44.5

9

Argyll and Islands

0.13

11.4

4

Ayrshire

0.50

47.5

10

Cromarty

5.00

61.2

11

Duisburg

1.00

14.0

5

Dumfries and Galloway

0.50

26.7

8

Dundee

0.25

73.0

13

Fife

0.25

67.8

12

Glasgow

2.50

239.2

15

Grangemouth

2.00

145.9

14

Moray

2.00

26.6

7

Orkney

0.05

1.5

2

Scottish Borders

0.00

22.9

6

Shetland

6.30

2.0

1

Western Isles

0.12

9.1

3

Gross Value Added of the energy sector

The Office of National Statistics (ONS) supplied data on the gross value added of the energy and the production sectors (2024). The ONS defined the production sector as SIC07 A-E. For the energy sector (including renewables), the ONS included the following SIC codes:

  • SIC 05: Mining of coal and lignite
  • SIC 06: Extraction of crude petroleum and natural gas
  • SIC 09: Mining support service activities
  • SIC 19: Manufacture of coke and refined petroleum products
  • SIC 20.14: Manufacture of other organic based chemicals
  • SIC 35: Electricity, gas, steam and air conditioning supply
  • SIC 36: Water collection, treatment and supply
  • SIC 38.22: Treatment and disposal of hazardous waste
  • SIC 71.12/2 Engineering related scientific and technical consulting activities
  • SIC 74.90/1 Environmental consulting activities

The GVA data by council area was aggregated to provide a hub-level view. Table 16 provides the data for GVA for each hub in the energy and the production sectors.

Table 16: Raw data and rank for GVA of the energy sector by hub.

Hub

Energy sector GVA (2022; £millions)

Production sector GVA (2022, £millions)

Rank (15 = highest to 1 = lowest)

Aberdeen

25878.9

4480

15

Argyll and Islands

162.1

422

7

Ayrshire

185.3

1762

9

Cromarty

342.8

1426

10

Duisburg

4147

13

Dumfries and Galloway

167.8

980

8

Dundee

146.9

1322

6

Fife

351.4

2232

11

Glasgow

2910.0

7447

14

Grangemouth

512.1

1522

12

Moray

78.7

875

4

Orkney

69.4

130

3

Scottish Borders

43.7

547

2

Shetland

119.4

184

5

Western Isles

16.8

83

1

Table 17: Summary of data used for the calculation of GVA of the energy sector.

Data category

Unit

Value/Data used

Source

Confidence rating

Energy sector GVA in Scotland

£million

  • Approximate GVA for Energy (including Renewables) at basic prices by local authority area in 2022.
  • Where data was non-disclosed for 2022, the value for 2021 was used.

(Scottish Government, 2024)

3

Production sector GVA in Scotland

£million

Regional GVA (balanced) by local authority for the Production Sector in 2022.

(Office for National Statistics, 2024)

3

Production sector GVA in Duisburg

€million

Duisburg GVA at basic prices for the Production Sector in 2022.

(Volkswirtschaftliche Gesamtrechnungen der Länder, 2024)

3

Euro to pound conversion rate

£

12-month average for 2022: £0.8489

(HMRC, 2022)

3

Full time equivalent workers

The data for the current size of workforce in different hubs was taken from Skills Development Scotland. The data was broken down into 32 local authorities. We took the current workforce figures for the Energy and Engineering sectors. The numbers from relevant local authorities were then added to derive the final number for each of our hubs. Table 18 shows the current workforce stats for each hub.

Table 18: Size of workforce in the engineering and energy sectors of Scotland.

Hub

Energy

Engineering

Total

Aberdeen

42900

28200

71100

Argyll and Islands

800

800

1600

Ayrshire

2400

8200

10600

Cromarty

4900

3000

7900

Dumfries and Galloway

1000

1600

2600

Dundee

1300

5100

6400

Fife

1400

10300

11700

Glasgow

16400

39300

55700

Grangemouth

2500

4400

6900

Moray

600

1500

2100

Orkney

300

200

500

Scottish Borders

400

2000

2400

Shetland

300

400

700

Western Isles

200

200

400

Future workforce requirement

The data for the future workforce requirement was taken from Skills Development Scotland’s database. This data was also disaggregated into 32 local authorities. The figures for all relevant local authorities were added to calculate final figures for our hubs. Table 19 shows the final estimates for future expansion demand.

Table 19: Estimated future expansion demand for each hub in Scotland.

Hub

Total Expansion Demand

Aberdeen

-4600

Argyll and Islands

0

Ayrshire

-900

Cromarty

-100

Dumfries and Galloway

-200

Dundee

-500

Fife

-1300

Glasgow

-1500

Grangemouth

-700

Moray

-100

Orkney

0

Scottish Borders

-200

Shetland

0

Western Isles

0

Large-scale storage capacity

Currently, there are no commercial geological hydrogen storage projects in Scotland. So, we have assessed the technical geological storage capacity for each hub. For this, we have used estimates from scientific literature. The sources for each storage technology are detailed in Table 21. We assigned the storage capacities to each hub based on the site’s location or, if offshore, their likely terminal.

We normalised the total large-scale storage capacity for each hub to provide a score from 1-10 (highest capacity). We adjusted the scores of the following hubs by +0.25. This adjustment accounted for the possibility of developing offshore salt caverns and the planned Project Union pipeline that could connect hubs to English salt caverns.

  • Aberdeen
  • Dumfries and Galloway
  • Dundee
  • Fife
  • Glasgow
  • Grangemouth
  • Moray
  • Orkney
  • Scottish Borders

The adjustment helped differentiate low-scoring hubs while maintaining the ranking integrity of those with confirmed storage capacity. Finally, we ranked the hubs from 1-15, where 15 represents the hub with the highest capacity (Table 20).

For Duisburg, we were unable to assess its specific technical storage capacity from scientific literature. However, compared to Scotland, Germany has hydrogen storage projects in the planning phase (Hornby, 2023). Due to the approved German core pipeline network, Duisburg will be connected to these projects. Therefore, due to higher confidence in hydrogen storage availability, we qualitatively assigned Duisburg a score of 3/10. This places Duisburg second to Aberdeen in the final ranking.

Table 20: Large-scale storage capacity by hub.

Hub

Hydrogen storage capacity (TWh) by technology

Rank (1-15)

Onshore salt caverns

Saline aquifers

Offshore oil/gas

Total

Aberdeen

0

1849

1082

2931

15

Argyll and Islands

0

0

0

0

1

Ayrshire

0

0

0

0

1

Cromarty

0

0

0

0

1

Duisburg

0

0

0

0

14

Dumfries and Galloway

0

0

0

0

5

Dundee

0

0

0

0

5

Fife

0

0

0

0

5

Glasgow

0

0

0

0

5

Grangemouth

0

0

0

0

5

Moray

0

118

0

118

13

Orkney

0

0

0

0

5

Scottish Borders

0

0

0

0

5

Shetland

0

82

32

114

12

Western Isles

0

0

0

0

1

Table 21: Summary of data used for the calculation of large-scale storage capacity.

Data category

Unit

Value/Data used

Source

Confidence rating

Hydrogen storage capacity – onshore salt caverns

TWh

0 TWh

(ClimateXChange, 2023)

3

Hydrogen storage capacity – saline aquifers

TWh

Location and technical working hydrogen gas capacity by site

(Safidi, et al., 2021)

2

Hydrogen storage capacity – offshore oil/gas fields

TWh

Location and technical working hydrogen gas capacity by field

(Peecock, et al., 2022)

2

Offshore salt cavern locations

N/A

(Edlmann, et al., 2024)

3

Potential hydrogen pipeline locations

N/A

(Edlmann, et al., 2024)

3

Planned hydrogen storage in Ruhr area

N/A

(Hornby, 2023)

3

Pipeline network infrastructure

To score each hub’s potential pipeline infrastructure, we used the following scale from 1-6:

  • There is no pipeline infrastructure suitable for hydrogen and no proposed or planned new hydrogen pipelines.
  • There are existing gas pipelines which can be repurposed. There are no planned new hydrogen pipelines but there may be some proposed.
  • There is a small-scale (e.g. distribution/spur pipelines) hydrogen pipeline project at any phase of development.
  • There is a large-scale (e.g. trunkline pipelines) hydrogen pipeline project at any phase of development.
  • The hub is a potential international export or import site for hydrogen and HDPs. However, planned pipeline infrastructure is insufficient and/or the site is not well-established for international trade.
  • The hub is a potential international export or import site for hydrogen and HDPs. There is sufficient planned pipeline infrastructure, and the site is well-established for international trade.

We have detailed the justification and sources for each hub’s rating in Table 22. Using these ratings, the hubs were ranked from 1 to 15 (Table 23). 15 represents the hub with the most suitable pipeline network infrastructure.

Table 22: Scoring method for pipeline network infrastructure.

Hub

Rating (1-6)

Justification

Source

Aberdeen

6

  • Identified as potential export route via St Fergus – a well-established export route with existing gas network which can be repurposed.
  • Project Union Hydrogen Backbone project to directly connect.
  • Project Acorn (FEED) plans for 100% conversion of local network at Moray and Aberdeen.

(Net Zero Technology Centre, 2023)

Argyll and Islands

2

  • No known new pipeline infrastructure planned.
  • Not connected to main gas transmission network or planned Hydrogen Backbone.
  • Some smaller gas pipelines may be available for conversion.

(Net Zero Technology Centre, 2023)

Ayrshire

3

  • Transmission Gas Network does not cross the hub.
  • Pre-FEED announced spur line by SGN connected to Hydrogen Backbone.

(Scottish Enterprise, n.d.; SGN, 2021),

Cromarty

5

  • Transmission Gas Network does not cross the hub.
  • Identified as potential export route by NZTC.
  • Hydrogen Backbone link could connect to Cromarty Firth.

(Net Zero Technology Centre, 2023; Scottish Enterprise, n.d.)

Duisburg

6

  • Planned major hydrogen import hub.
  • Will be connected.
  • to approved German core pipeline network.

(Bundesnetzagentur, 2024; Gasunie, 2023)

Dumfries and Galloway

4

  • Existing gas transmissions pipelines, including Scotland to Northern Ireland Pipeline.
  • Announced Project Union and European Backbone transmission infrastructure to run through hub.

(Net Zero Technology Centre, 2023; Scottish Enterprise, n.d.)

Dundee

4

  • Announced Pre-FEED spur lines by SGN connected to Hydrogen Backbone.
  • Announced Project Union to run through region.

(SGN, 2021)

Fife

4

  • Under construction H100 pipeline
  • Announced pre-FEED spur lines by SGN connected to Hydrogen Backbone
  • Project Union projected to run through region.

(SGN, 2021)

Glasgow

3

  • National Grid Gas Transmission Network pipelines cross through South Lanarkshire. Potential for hydrogen blending.
  • Pre-FEED projected spur lines by SGN connected to Hydrogen Backbone.

(SGN, 2021; Scottish Enterprise, n.d.)

Grangemouth

4

  • Project Union Hydrogen Backbone project has a particular focus on connecting directly to Grangemouth.
  • Approved SGN project plans to trial 30 km hydrogen pipeline to Edinburgh.

(SGN, 2021; SGN, 2023)

Moray

3

  • SGN plans to repurpose spur pipeline to connect to Project Union pipeline.
  • Project Acorn (FEED) plans for 100% conversion to hydrogen of local pipeline network at Moray and Aberdeen.

(SGN, 2021; Scottish Government, 2020)

Orkney

5

  • Transmission Gas Network does not cross through the Cluster.
  • However, identified as a potential export site from Flotta. NZTE identified opportunity for new pipeline to connect to SIRGE and UK mainland.

(SGN, 2021; Net Zero Technology Centre, 2023)

Table 23: Hub ranking for pipeline network infrastructure.

Hub

Rank (1 = least suitable to 15 = most suitable)

Aberdeen

14

Argyll and Islands

1

Ayrshire

2

Cromarty

11

Duisburg

14

Dumfries and Galloway

6

Dundee

6

Fife

6

Glasgow

2

Grangemouth

6

Moray

2

Orkney

11

Scottish Borders

6

Shetland

11

Western Isles

2

Ports

We have investigated which hubs are most suitable for meeting maritime shipping fuel demand and for trading hydrogen and HDPs by ship. To evaluate the scale of each hub’s maritime industry, we ranked the hubs based on their total port freight traffic in 2023. This analysis was based on the Department for Transport’s Port Freight Statistics Publication (Maritime Statistics, 2024). The Port0101 dataset breaks down freight traffic by port and council authority. Traffic included domestic and international freight traffic in both directions and we included all ports – major and minor. For Duisburg, we used State Office for Information and Technology NWR data for freight traffic in both directions for 2023 (2024).

We adjusted these initial ranked scores based on several criteria, shown in Table 24. For the port dimensions criterion, if online information was conflicting, we selected the greatest dimension for further scoring. This multi-factor scoring method reflects the diverse functions that ports serve. Based on these final scores, we ranked the hubs from 1 to 15 (Table 25). 15 represents the hub with the most suitable port infrastructure.

Table 24: Score adjustment criteria for scoring port metric.

#

Criteria

Score adjustment

If YES

If NO

1

Does the hub have a port with existing or planned infrastructure for the storage, production or maritime fuelling of hydrogen/HDPs?

+2

–2

2

Does the hub have a port with dimensions suitable for a typical small carrier vessel for transporting gas or ammonia? The Scottish Government defines these dimensions as a 100m length, 25m beam and a 12m draft (2020, p. 63).

+2

–2

3

Does the hub have a port which is considered suitable for hydrogen exports or imports by the government?

+3

–2

Table 25: Summary of data used for scoring the port metric.

Data category

Unit

Value/Data used

Source

Confidence rating

Port freight traffic – Scotland

Thousand tonnes

2023 freight traffic, both directions

(Maritime Statistics, 2024)

3

Port freight traffic – Duisburg

Thousand tonnes

2023 freight traffic, both directions

(Information und Technik Nordrhein-Westfalen, 2024)

3

Port dimensions

metres

Where available – the port’s maximum length, beam and draft

(SHIPNEXT BV, 2025; OneOcean Group Ltd, 2023; Port of Aberdeen, 2025; UKPORTS, 2025)

3

Hydrogen/HDP infrastructure – Duisburg

(Duisport, 2022)

3

Hydrogen/HDP infrastructure – Scotland

(Scottish Government, 2020)

3

Import hub – Duisburg

(Tix, 2024)

3

Export hubs – Scotland

(Scottish Government, 2020)

3

Table 26: Raw data, analysis and rank for ports by hub.

Hub

Port freight traffic (thousand tonnes, 2023)

Criteria 1 (YES = ☒)

Criteria 2

(YES = ☒)

Criteria 3

(YES = ☒)

Rank

(1 = least suitable to 15 = most suitable)

Duisburg

41333

15

Cromarty

7376

13

Fife

18681

13

Grangemouth

18521

12

Shetland

5975

11

Aberdeen

4395

10

Orkney

1689

9

Ayrshire

8923

8

Glasgow

8594

7

Dumfries and Galloway

6511

6

Western Isles

204

5

Moray

108

4

Dundee

996

3

Argyll and Islands

46

2

Scottish Borders

0

1

Local policy and planning support

The data for the local policy and planning support metrics were taken from Scottish government’s Planning Application Statistics database. The data was broken down into 24 local planning authorities. The data was taken from the relevant local authorities and averaged for all our hubs.

It was found that for the average success rate of applications, there was no data for 6 hubs. Table 27 shows the average success rate and average planning duration for each Scottish hub and Duisburg.

Table 27: Average success rate and duration for planning applications

Hub

Average success rate of planning applications

Average duration of planning applications (weeks)

Aberdeen

87%

6.7

Argyll and Islands

No Data

17.6

Ayrshire

50%

6.7

Cromarty

80%

15.3

Duisburg, Germany

No Data

18

Dumfries and Galloway

No Data

13.2

Dundee

79%

11.7

Fife

53%

10.3

Glasgow

70%

14.6

Grangemouth

80%

9

Moray

No Data

7.2

Orkney

No Data

10.6

Scottish Borders

88%

8.2

Shetland

No Data

10.6

Western Isles

No Data

13.9

Sensitivity analysis

For main report, we weighted capability groups according to the working group’s priorities and adjusted these weightings based on data confidence. We normalised each metric ranking from 1-15 into a 1-10 scale. Then, according to the defined weightings, we scaled the metric score for each hub to provide a total score out of 100.

Here, we analyse the sensitivity of this priority scoring by considering two alternative scenarios:

  • The balanced scenario – all metrics are weighted equally at 9.1%.
  • The absolute scenario – Rather than scoring hubs relatively according to metric rankings, we used the absolute data for each metric. For example, for GVA of the energy sector, we normalised the absolute GVA values to give a score from 1-10. The same weightings are used as in the priority scenario.

Table 28: Hub rankings from priority, balanced and absolute scenario.

Rank

(15 = highest score to 1 = lowest score)

Hub scoring method

Priority scenario

Balanced scenario

Absolute scenario

15

Aberdeen

Aberdeen

Aberdeen

1

Argyll and Islands

Argyll and Islands

Argyll and Islands

9

Ayrshire

Ayrshire

Ayrshire

13

Cromarty

Glasgow

Cromarty

14

Duisburg

Duisburg

Duisburg

6

Dumfries and Galloway

Moray

Dumfries and Galloway

8

Dundee

Dundee

Dundee

11

Fife

Grangemouth

Fife

12

Glasgow

Cromarty

Glasgow

10

Grangemouth

Fife

Grangemouth

7

Moray

Shetland

Moray

4

Orkney

Orkney

Orkney

3

Scottish Borders

Dumfries and Galloway

Scottish Borders

5

Shetland

Scottish Borders

Shetland

2

Western Isles

Western Isles

Western Isles

Table 28 shows the final ranking for supply chain capability according to all three scenarios. Several key insights can be taken from our sensitivity analysis:

  • We can see that the hubs at the ranking extremes remain the same. Aberdeen remains the top hub for supply chain capability, while the Western Isles and Argyll and Islands are the bottom hubs.
  • The hubs between these extremes vary according to the scenario. However, the general “upper” (Cromarty, Glasgow, Fife, Grangemouth, Ayrshire) and “lower” (Dundee, Moray, Dumfries and Galloway, Shetland, Orkney and Scottish Borders) groupings identified in the priority scenario are consistent in the balanced and absolute scenarios.
  1. HDP demand in Scotland’s hydrogen hubs

Demand mapping – e-methanol and ammonia for maritime

It is estimated that the UK used roughly 7 million tonnes of fossil marine fuels in the year 2021 (Transport & Environment, 2023). We used the EU Commission’s assumption of 40.5 MJ/kg as the energy content of marine fuel. Using this, we derived the addressable market for the whole of UK. Assuming that the fuel usage by Scottish ports will have the same share, we estimated the addressable market for Scotland’s maritime sector. Using data from the Department for Transport, we calculated the share of freight activity of each hub’s ports in the UK (Maritime Statistics, 2024).

Due to the uncertainties associated with estimating demand for individual HDPs in this sector, our analysis is technologically agnostic. We have not tried to estimate individual demand for each HDP. This analysis only estimated the addressable demand for all HDPs in the maritime sector of Scotland.

Table 29: Estimated shipping fuel demand by hub

Hub

Shipping fuel demand (TWh)

Aberdeen

0.8

Argyll and Islands

0.0

Ayrshire

1.6

Cromarty

1.4

Dumfries and Galloway

1.0

Dundee

0.2

Fife

3.5

Glasgow

1.5

Grangemouth

3.5

Moray

0.0

Orkney

0.5

Scottish Borders

0.0

Shetland

1.2

Western Isles

0.0

Demand mapping – e-methanol for chemicals

In Scotland, we assume that Grangemouth Chemical Science Park is the only large-scale user of methanol as a chemical feedstock. We based this analysis on the estimated syngas produced from two onsite ethane crackers which supply INEOS’ polymer plants (INEOS Group, 2025). The ethane crackers have a production capacity of around 1 million tonnes of ethylene per year (Endeavor Business Media, 2016). From this value, we have reverse calculated the yield of syngas (hydrogen and methane from the crackers). Assuming an 80% yield of ethylene product, 1.25 million tonnes of ethane feedstock is required (Brooks, 2013). From literature, we can expect an estimated 13% yield of syngas (Brooks, 2013). This means 160,000 tonnes of syngas is produced from 1.25 million tonnes of ethane. In the production of petrochemicals, syngas is converted to methanol. Assuming 8600 hours/year of operation and a 62% yield, we can expect to produce around 100,000 tonnes of methanol (Timsina, et al., 2021). We then multiplied this result by the lower calorific value of methanol (19.9 MJ/kg) and the conversion factor of 2.78×10-10to give the energy demand in TWh.

Demand mapping – SAF for aviation

We estimated the addressable market for SAFs in the Scotland by estimating the potential demand for jet fuel in each public airport in Scotland. Due to lack of data on jet fuel consumption in each airport, we took some assumptions to calculate potential demand. It is estimated that the UK used 11 million tonnes of jet fuel in the year 2022. This figure is for all the airports in the UK. So, to determine jet fuel demand for Scotland, we calculated the percentage of aircraft activity in each airport against the total UK aircraft activity. It was then assumed that the proprtion of jet fuel used in an airport will be the same as their share in total aircaft activity.

The table below show the proportion of aircraft movement in each hub and airport.

Table 30: Estimated jet fuel demand in all Scottish airports.

Hub

Airport

Potential

SAF Demand (TWh)

Total hub potential demand (TWh)

Aberdeen

Aberdeen

3.49

3.49

Argyll and Bute

Campbeltown

0.07

0.26

Argyll and Bute

Islay

0.12

0.26

Argyll and Bute

Tiree

0.07

0.26

Cromarty

Inverness

1.20

1.20

Dundee

Dundee

1.66

1.66

Glasgow

Glasgow

3.51

4.45

Glasgow

Glasgow Prestwick

0.94

4.45

Grangemouth

Edinburgh

5.03

5.03

Orkney

Kirkwall

0.54

0.70

Orkney

Wick John O’ Groats

0.16

0.70

Shetland

Lerwick (Tingwall)

0.06

0.93

Shetland

Scatsta

0.19

0.93

Shetland

Sumburgh

0.68

0.93

Western Isles

Barra

0.05

0.55

Western Isles

Benbecula

0.13

0.55

Western Isles

Stornoway

0.37

0.55

Demand mapping – ammonia for fertilisers

To estimate ammonia demand from fertilisers, we first estimated the total demand for nitrogen based fertilsers in Scotland. For our analysis, we assumed that nitrogen-based fertilisers consist of just urea and ammonium nitrate fertilisers. The fertiliser use estimation was done for both cropland and grassland. The average nitrogen based fertiliser application rate was taken from the UK government’s Fertiliser Use Database. The average application rate for nitorgen fertiliser in Scottish croplands is 120 kg/ha. And the average application rate for grassland is 83 kg/ha.

This average application rate was then multiplied by the total estimated crop and grass lands in Scotland. We then estimated the nitrogen content in these two fertilisers. After getting the nitrogen content in them, we estimated the demand for ammonia.

Once the final figure for ammonia was derived, we divided the total use of ammonia for all our hubs. This was done by assuming that each hub’s share of use of ammonia will be the same as their share of total GVA in agriculture. The table below shows our demand estimates for ammonia in each Scottish hub.

Table 31: Estimated ammonia demand from fertilisers in Scotland

Hub

Ammonia fertiliser demand (thousand tonnes)

Ammonia fertiliser demand (TWh)

Aberdeen

27.1

0.140

Argyll and Islands

2.5

0.013

Ayrshire

4.2

0.022

Cromarty

7.4

0.038

Dumfries and Galloway

4.2

0.021

Dundee

2.5

0.013

Fife

4.8

0.025

Glasgow

24.5

0.126

Grangemouth

3.0

0.015

Moray

1.2

0.006

Orkney

0.9

0.005

Scottish Borders

2.8

0.014

Shetland

1.4

0.007

Western Isles

0.0

0.000

 

 

  1. Policy gap analysis

Table 32: Further information about all the policies and regulations we researched.

Region

Policy name

Description

European Union

Net Zero Target

The European Union aims to meet net zero emissions by 2050.

European Union

Hydrogen Strategy

The hydrogen strategy for a climate-neutral Europe was adopted in July 2020.

European Union

RePowerEU

The European Commission implemented the REPowerEU Plan to phase out reliance on Russian fossil fuel imports following the invasion of Ukraine.

European Union

REDIII Targets

Transport: RED III fuel suppliers must achieve a 14.5% reduction in GHG emissions associated with their fuels or achieve at least 29% renewables share in the fuel supply. In addition, at least 5.5% of the fuel mix must be composed of advanced biofuels and RFNBOs (combined binding target).

Industry: The EUs CBAM Regulation (10th May 2023) will be transitioned in during the period of 2023-2026 and then full force from 2026 onwards. The EU’s Fit for 55 proposals include a 50% renewable share for hydrogen used in industry. RED III – Industry must procure at least 42% of its hydrogen from renewable fuels of non-biological origin (RFNBOS) by 2030, though countries that can achieve a fossil-free hydrogen mix of at least 77% by 2030 can see that target reduced by 20%.

European Union

H2Global

H2Global is live (1st auction closed 2023) and formed through H2 purchase and sale agreements through a central body. Managed windows for funding applications through 10-year hydrogen purchase agreements, competition-based procurement process. As of 06/23, H2Global and the Hydrogen Investment Bank have been linked. Working on a European auction open to all EU countries.

European Union

Hydrogen Bank

Acts through an auction system, fixed price payment per kg. Fixed premium per kg hydrogen produced for a maximum of 10 years of operation. Auctions launched under the Innovation Fund in the autumn of 2023.

European Union

Innovation Fund

The innovation fund hydrogen focussed from Nov 2022. Acts through a competitive bidding process – max bid 4 Euro per kg* – and via waves of calls for proposals.

European Union

IPCEI

Important Project of Common European Interest (IPCEI) are live and provided in waves of grant funding. A requirement for projects must be for them to show they are financially viable without subsidies.

European Union

AFIR

AFIR passed March 2023, detailing one HRS to be deployed every 200km along Ten-T core.

European Union

Fitfor55

Fit for 55: 2.6% target for renewable fuels of non-biological origin (RFNBO) in transport by 2030

European Union

EU ETS

The EU Emission Trading Scheme is a “cap and trade” system that limits the amount of greenhouse gases which can be emitted within the EU.

European Union

EU MoUs

The EU has signed MoUs with Japan, Egypt, Mauritania (and others) around hydrogen including export/imports.

European Union

RED Low Carbon Hydrogen Standard

3.38 kg CO2-eq/kg hydrogen (28 gCO2e per MJ) (70% lower compared to emissions from fossil fuels). Two delegated acts under Renewable Energy Directive published by the Commission in Feb-23 – (i) principle of additionality, (ii) methodology for calculating GGG emissions. Rules to apply to imports.

United Kingdom

Net Zero Target

Net zero by 2050. 78% emission reduction by 2035. Mandated in law. Net Zero power system by 2030.

United Kingdom

UK Hydrogen Strategy

Production target of 10 GW by 2030, with at least 6 GW of this coming from green production.

United Kingdom

HPBM

Hydrogen Production Business Model – a CFD funding mechanism bridging the difference between producing low-carbon hydrogen gas and the price of natural gas. Funding provided through allocation rounds.

United Kingdom

Hydrogen Transport Business Model (HTBM)

This is a policy for hydrogen transport projects that are expecting to connect to hydrogen network in the future. The policy aims to mitigate risks for hydrogen network developers. This is done by guaranteeing a fixed rate of return to the developers.

United Kingdom

Hydrogen Storage Business Model (HSBM)

Similar to HTBM, this policy aims to incentivise large scale hydrogen storage.

United Kingdom

Net Zero Hydrogen Fund (NZHF)

The NZHF provides support for a range of different costs such as development or capital expenditures.

United Kingdom

Health and Safety Executive (HSE)

HSE will play a role in determining the safety case for hydrogen in heating. More information from HSE will reduce the uncertainty with hydrogen’s role in decarbonising heat.

United Kingdom

ADR Regulation

ADR regulation lays down specific regulations for transport of “dangerous goods”. This regulation includes in its scope both hydrogen and various HDPs that meet the criteria of being dangerous.

United Kingdom

Gas Safety Management Regulation (GSMR)

GSMR prohibits injecting more than 0.1% hydrogen into the networks. This will need to be updated to expand the role of hydrogen blending into existing pipelines.

United Kingdom

Control of Major Accident Hazard (COMAH)

This applies to many of hydrogen derivatives and products due to their safety concerns.

United Kingdom

LCHS

The UK Low Carbon Hydrogen Standard sets a carbon intensity threshold for hydrogen production of 20 gCO2e/MJ (2.4 kg CO2-eq/kg hydrogen). If the hydrogen produced meets this standard, it can be deemed low-carbon and is eligible for government subsidy.

United Kingdom

UK ETS

The UK’s own ETS scheme since leaving the EU.

United Kingdom

SAF Mandate

The UK has formed a SAF mandate stipulating set targets for percentage shares of SAF, and specific production pathways (such as PtL). Headline figure is that 10% of UK aviation fuel will be SAF by 2030.

United Kingdom

RTFO

The Renewable Transport Fuels Obligation

Germany

Net Zero Target

Net zero by 2045. Emissions shall move to net negative after 2050. Germany has set the preliminary targets of cutting emissions by at least 65 percent by 2030 compared to 1990 levels, and 88 percent by 2040 Mandated in law.

Germany

National Hydrogen Strategy

The German hydrogen national strategy was released in 2020 before being an update was released in 2023.

Germany

H2 Global

H2 Global – value €4 billion. Initial auction of 900mn euros launched in Dec 2022 for H2 derivatives. Government plans to make a further 3.5 billion euros available for new bidding rounds with durations up to 2036.

Germany

Carbon Tax

CO2 tax (introduced in 2023) for Avgas and Jet A-1.

Germany

Hydrogen Mobility Targets

Targets include fuel cell trucks, 20 HRS’s and passenger cars, fuel cell buses for public transportation, and the operation of the first inland ship operating on hydrogen by 2025.

Germany

National MOUs

Several MoUs signed surrounding imports of hydrogen and ammonia into the country – Mauritania MoU could equate to 8 million tonnes/year.

The Netherlands

Net Zero Target

Net zero by 2050. 55% CO2 reduction by 2030. In law.

The Netherlands

National Hydrogen Strategy

The Netherlands hydrogen strategy was released in 2020.

The Netherlands

National Climate Agreement

The national climate agreement contains set targets for fuel cell HDVs, passenger cars and hydrogen refuelling stations.

The Netherlands

Carbon Levy

In 2021, introduced carbon levy for industry – complementary to EU ETS – road mapped to 2030 currently.

The Netherlands

Guarantees of Origin Scheme

Green hydrogen Guarantees of Origin operational from Oct-22, following a Bill (May-22) and trial (summer-22).

The Netherlands

H2Global

300mn euro specific funding from H2Global, including funding for ammonia.

The Netherlands

National MoUs

In 2020, the US and the Netherlands signed a statement of intent to collaborate on hydrogen. The Minister of Energy of Chile and the State Secretary for Economic Affairs and Climate Policy signed a joint statement on collaboration in the field of green hydrogen import and export (July 2021). The UAE Ministry of Energy and Infrastructure and the Dutch Ministry for Foreign Trade and Development Cooperation have signed a Memorandum of Understanding on hydrogen energy. As part of their Joint Economic Committee, the UAE and the Netherlands have been in discussions to identify common interests and create a partnership for decarbonisation of the energy sector and increasing the use of clean hydrogen (March 2022).

Belgium

Net Zero Target

Net Zero by 2050, 55% emissions reductions target in place for 2030.

Belgium

National Hydrogen Strategy

Hydrogen strategy enacted firstly in 2021, with an update in 2022. Both strategies focussed on positioning Belgium as an import and transit location for low-carbon molecules into Europe. The country will remain dependent on energy imports in various forms to cover its domestic demand, estimating between 2 and 6 TWh of renewable hydrogen (or derivatives) in 2030 and between 100 and 165 TWh in 2050

Belgium

Energy Transition Fund

The Energy Transition Fund will fund until 2025, providing 20-30 million euros in support. The federal government has also earmarked 60 million euros (including 50 million euros from the national recovery and resilience plan) to invest and support projects to scale up innovative, low-carbon technologies.

Belgium

Hydrogen Act

The Hydrogen Act establishes a regulatory framework for the transport of hydrogen via pipelines. The act intends to foster the growth of the Belgian hydrogen market and the required hydrogen transport infrastructure. 

How to cite this publication:

Yip, E., Nagpal, D., Wilson, J., Morton, H. (2025) Scotland’s capabilities in producing hydrogen products and derivatives ‘, ClimateXChange. DOI: http://dx.doi.org/10.7488/era/6397

© The University of Edinburgh, 2025

Prepared by Talan on behalf of ClimateXChange, The University of Edinburgh. All rights reserved.

While every effort is made to ensure the information in this report is accurate as at the date of the report, no legal responsibility is accepted for any errors, omissions or misleading statements. The views expressed represent those of the author(s), and do not necessarily represent those of the host institutions or funders.

This work was supported by the Rural and Environment Science and Analytical Services Division of the Scottish Government (CoE – CXC).

ClimateXChange

Edinburgh Climate Change Institute

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+44 (0) 131 651 4783

info@climatexchange.org.uk

www.climatexchange.org.uk


  1. There are two types of estimated demand: replacement and expansion. Replacement demand refers to workers that will be needed to replace the current workforce. Expansion demand represents demand that will arise due to the growth in an industry.


The Scottish Landfill Tax (SLfT), introduced in April 2015, was designed to discourage landfill disposal and encourage prevention, reuse, recycling and energy recovery.  

The tax has two rates. The lower rate of SLfT was designed to provide a low-cost disposal route for inert, low-risk materials, such as rocks and soils.  A higher standard rate targeted more polluting materials to support environmental goals. In early 2024, lower-rate materials exceeded standard-rate materials for the first time.

This research provides an initial evidence base to assess the effectiveness of the lower rate and explore whether changes could better support a low-carbon, circular economy. It examines the most common lower-rate materials, their environmental impacts, the feasibility of diversion and options for policy reform. 

The researchers conducted quantitative and qualitative data analysis, a literature review and stakeholder engagement. 

Findings

Three materials accounted for 77% of all waste landfilled at the lower rate in 2023–24, by weight:  

  • mechanically-treated fines (small particles from treatment of general construction and demolition waste, municipal recyclate etc)
  • soils and stones from construction waste  
  • mechanically-treated mineral fines (small particles from treatment of naturally-occurring materials such as rocks and soils, silt, clay, sand and stones, found in quarry, construction and demolition waste etc) 

Mechanically-treated fines make up the greatest quantities of all lower-rate materials, despite being intended as a residual output from material recovery processes. Trends raise concerns regarding misclassification. 

Environmental impact analysis, based on the quantities landfilled in Scotland, showed that these three materials also have the highest impacts across indicators such as air pollution, water use and resource scarcity.  

This study suggests the lower-rate SLfT may be only partially aligned with Scotland’s current circular economy, waste prevention and climate goals. While it has supported some diversion of inert waste from landfill, it may also be driving unintended behaviours and limiting investment in recovery.

Both fiscal and non-fiscal actions may be needed to address these challenges. The upcoming Scottish Aggregates Tax and wider circular economy policy agenda offer opportunities to align SLfT more closely with long-term environmental objectives. 

For further details, please read the report.

If you require the report in an alternative format, such as a Word document, please contact info@climatexchange.org.uk or 0131 651 4783.

Podcast and blog

Susan Evans and Richard Claxton give an overview of the project and findings in episode 17 of our podcast: Evidence for climate policy in Scotland

A blog post summarising the podcast interview is also available on our website: Project snapshot: Reviewing the landfill tax

Image credit: WOKANDAPIX from Pixabay