Work completed: December 2023

DOI: http://dx.doi.org/10.7488/era/3666

This research was carried out in 2022/23 and was based on the market conditions at that time. Policy related to and emphasis on electricity networks has changed significantly since this research was conducted and therefore not all aspects of the report reflect the current landscape.

Executive summary

Solar panels can help decarbonise Scotland’s energy supply and there are plans to reduce barriers to enable greater deployment in Scotland. The Scottish Government recently consulted on the potential for a solar ambition and a Solar Vision is in development.

The solar industry has been calling for a 4-6 GW solar photovoltaic (PV) ambition by 2030, to put Scotland in line with the UK target of 70 GW by 2035. This can be broken down as 2.5 GW rooftop solar (1.5 GW domestic and 1 GW commercial), with the remaining capacity made up of large-scale grounded mounted solar.

Our work investigates the benefits and impacts of deploying 2.5 GW of rooftop solar PV installation onto the electricity network in Scotland by 2030. The distribution network operators are forecasting lower levels of solar PV uptake in their future energy scenarios.

We consider the benefits, high-level estimate of reinforcement investments needed to accommodate it and the potential impact on consumer bills. We also consider wider costs to the transmission network.

Benefits and opportunities

The rise of electricity generation connected to a distribution network, known as embedded generation, offers new opportunities to the distribution network for managing the future growth of demand. Potential network benefits include:

• Reduction in electricity infrastructure investments due to generation meeting demand
• Reduced line losses from transmitting electricity across the transmission network due to more demand being met by onsite generation.
• Supporting demand in other areas by selling excess power

Financial benefits for consumers adopting solar PV arise from lower electricity bills. Benefits could be increased if demand could be shifted to times of excess generation. Stakeholders from the distribution networks considered that increased solar PV deployment would provide greatest opportunities for commercial consumers whose peak demand during the day would be most likely to match peak solar generation.

We also found that the co-location of commercial or domestic scale battery storage alongside solar PV would provide the greatest economic opportunities by extending the duration throughout the day when demand is met by on-site generation. This could also reduce network impacts by delaying the need for network upgrades.

Impacts and costs

We estimate that 27% (209) primary substations in Scotland might become overloaded with an increased deployment of rooftop solar. The impact is additional to that from other low-carbon technologies (e.g. wind, ground mounted solar, battery storage) as forecast by Distribution Network Operators. The majority (84%) of these substations are located in Scottish Power Energy Networks region, with 16% in Scottish & Southern Electricity Networks region.

Our high-level estimates of total costs for all forecasted network interventions are:

• Scottish Power Energy Networks (SPEN): £130 million worth of work to upgrade high-voltage substations and low-voltage networks and £120 million to upgrade transmission infrastructure.
• Scottish & Southern Electricity Networks (SSEN): £20 million worth of work to upgrade high-voltage substations and low-voltage networks, and £30 million to upgrade transmission infrastructure.

These are based on network reinforcement costs for a mix of areas representative of Scotland and key information on network location and capacity, and magnitude of solar PV in the area, with the results scaled up to represent all of Scotland. The cost of traditional network reinforcement involves replacing substations and overloaded equipment with that of a higher capacity rated equipment.

The distribution costs will be paid by all consumers in Scotland through their energy bills. The estimated average annual increase in domestic consumer energy bills is £0.53 in the SSEN area and £1.81 in the SPEN area. The estimated average annual increase in non-domestic consumer energy bills is £7.17 in SSEN’s area and £24.46 in SPEN’s area.

Alternative ways to release additional capacity from existing assets that could reduce costs include:

• Flexibility services, which contracts consumers/aggregators to generate power or shift load at times of congestion to support constraint management.
• Reconfiguring networks to release capacity from feeders that are close to operational limits.
• Smart solutions and approaches to release capacity, for instance low-voltage monitoring for better informed design and operation, dynamic variable ratings to factor in seasonality and electronic control of power flows.

These have the potential of decreasing or delaying the need for reinforcement but will not entirely negate this need.

Overall, it is difficult to quantify whether the benefits outweigh the impacts on the grid and on consumer bills, but steps can be taken to reduce the potential impacts and enable greater benefits to be realised. Examples include investing in on-site battery storage and continued deployment of network flexibility and innovation solutions.

Recommendations

• Network interventions are triggered because Distribution Network Operators are required to use a conservative assumption that less generation will be consumed onsite with more exported to the network. This could be an area to explore.
• Incentivising the requirement to have domestic and non-domestic battery storage in conjunction with solar PV to absorb any excess solar, thus preventing exports, may reduce the scale of network interventions needed. Battery storage can provide greater network flexibility by charging and discharging as required.
• A co-ordinated approach is needed between key stakeholders including the Distribution Network Operators, transmission operators, local authorities and the solar industry to ensure that a significant increase in solar PV can be accommodated. Improved evidence of large quantities of solar being proposed is needed to allow the network operators to plan accordingly and justify their decisions to Ofgem.

Glossary of terms

Introduction

Background

Scotland has made significant progress in decarbonising its energy sector through the growth of renewable electricity generation technology. The Scottish Government has a statutory target legislated in the Climate Change (Scotland) Act 2019 to reach net zero emissions by 2045. This will require further decarbonisation across the entire energy sector in Scotland. The draft Energy Strategy and Just Transition Plan and the Climate Change Monitoring report set out targets for the transformation of Scotland’s energy sector from 2030 and beyond. There is an ambition to deliver at least 20 GW of additional low-cost renewable capacity by 2030, and for at least the equivalent of 50% of Scotland’s energy across heat, transport, and electricity demand to come from renewable sources.

Over recent years, domestic, non-domestic and commercial buildings have been encouraged to become more energy efficient and reduce electricity consumption from the grid. As well as the use of energy efficiency measures, there has been an increase in the adoption of low carbon technologies (LCT), such as rooftop solar PV. Schemes such as Feed in Tariff (FIT) and Smart Export Guarantee (SEG) have further contributed to the rise in solar PV installations. The SEG scheme provides a payment to renewable energy generators for every kilowatt-hour (kWh) of energy that is exported to the grid via a p/kWh tariff agreement.

The Scottish Government recently consulted on the potential for a solar ambition. The solar industry has been calling for a 4-6 GW solar photovoltaic (PV) ambition by 2030, which would align Scotland with the UK Governments target for solar [1]. This can be broken down into the following:

• 1.5 GW domestic rooftop solar
• 1 GW commercial rooftop solar
• Remaining capacity made up of large-scale grounded mounted solar

This level of solar ambition will require additional electricity network capacity, with cost implications in the form of necessary distribution and transmission network interventions. The distribution network costs will, in part, be passed onto electricity consumers across Scotland while transmission costs are levied on consumers at GB level. If distribution network intervention costs are higher in specific network regions, then consumers who sit in this region will pay more towards distribution costs through their energy bills than those in other network regions.

Aims and approach

This report focuses on 2.5 GW of rooftop solar PV installations, spread across domestic and non-domestic premises, and provides an assessment into the impacts on the electricity network and the resulting costs and benefits of greater solar PV deployment in Scotland.

The level of investment needed to accommodate the additional solar installations and potential impact on consumers energy bills is estimated using credible assumptions but is not definitive. The assessment also considers wider costs to the transmission network. Our work was informed through desktop research, stakeholder engagement and analysis using data obtained from DNOs and reports in the public domain.

Electricity network overview

The electrical infrastructure in Scotland is made of two key parts: the transmission network and the distribution network. The transmission network includes the 400 kV, 275 kV and 132 kV network and operated by Transmission Owners (TOs), and the distribution network which includes lower voltage networks and is operated by the Distribution Network Operators (DNOs).

The transmission and distribution networks in Scotland are operated by the following organisations (see Figure 1):

• Scottish Power Energy Networks (SPEN), made up of 2 key parts:
  • Scottish Power (SP) Distribution are the DNO of the distribution network in Central & Southern Scotland
  • SP Transmission are the TO for Central & Southern Scotland
• Scottish & Southern Electricity Networks (SSEN), made up of 2 key parts:
  • SSEN Distribution, who are the DNO for the North of Scotland
  • SSEN Transmission are the TO for the North of Scotland

Figure 1 Electricity network operator map for Scotland

At the distribution level, there are four types of electrical substations used to distribute electrical power from the transmission network to consumers:

• Grid Supply Points (GSPs): Provide the connection between the transmission system and the distribution network. GSPs step the voltage down from the transmission network voltage of either 400 kV, 275 kV or 132 kV to the highest distribution network voltage known as the sub-transmission network or EHV network.
• Bulk Supply Points (BSPs): Step the incoming 132 kV voltage down to 33 kV, which is then distributed to different primary substations in the region. Some very large industrial and commercial loads may be directly fed at this level.
• Primary Substations: Take the incoming 33 kV feeder and steps the voltage down to 11 kV which directly supplies some larger commercial loads, as well as the secondary substations.
• Secondary Substations: Take the incoming 11 kV feeder and steps the voltage down to Low Voltage (LV), which will typically supply residential areas.

Solar PV connection types

All solar PV installations (and other generation types) connecting to the distribution network must comply with the Distribution Code and either Engineering Recommendation (EREC) G98 or G99 as applicable [2] [3]. The Distributed Generation Connection Guides (DGCG) outline the steps to be carried out to obtain a connection agreement and gain approval to connect solar PV assets to the network [4].

The DGCG considers both EREC G98 and EREC G99:

• G98 for small-scale installations: This is applicable for small-scale installations with a total capacity of no more than 16 amps per phase connected at low voltage (230 V). This equates to a maximum peak power of 3.68 kW single phase or 11.04 kW three-phase. An example of a G98 application is domestic rooftop solar PV.
• G99 for large-scale installations: This is applicable for installations with a total installed capacity greater than 16 amps per phase connected at either low voltage (Type A only) or high voltage levels. G99 includes four types:
  • Type A: From 0.8 MW to < 1 MW
  • Type B: From 1 MW to < 10 MW
  • Type C: From 10 MW to < 50 MW
  • Type D: greater than or equal to 50 MW

Depending on available roof space, a commercial rooftop solar installation may fall into the G99 Type A category. Larger G99 types are likely to be ground-mounted.

Project findings

Potential opportunities for distribution networks from increased solar PV deployment

Distribution network equipment has traditionally been sized to supply the peak load, which is the maximum demand that an area is expected to draw from the wider electricity network. This is to ensure that consumers do not pay for network infrastructure that is not used, known as stranded assets. The electrification of heat and transport through the introduction of heat pumps and electric vehicle charging points will add to the peak demand, potentially resulting in greater network constraints and triggering necessary interventions as a result. There are new ways to manage the impacts, including using the techniques described in Section 4.3.3. The rise of embedded connected generation will offer new opportunities to the distribution network when it comes to managing the future growth of demand.

Benefits include the following:

• Reduction in electricity infrastructure: Connecting distributed generation close to the point of use (e.g., rooftop solar PV behind the meter) could result in a reduced need for distribution infrastructure as the demand is being offset by generation. Increased distributed generation can reduce the average load on network assets and can defer the immediate need for asset replacement and when replacement is required. For example, charging of EVs could be timed to match the generation profile of the solar, reducing the need to supply power from elsewhere in the grid. However, the scale of 2.5 GW of additional solar will need to be investigated further to understand this opportunity in more detail.
• Reduced line losses: Generation can supply loads within the distribution network, reducing the distance between where supply and demand are located, which reduces energy losses.
• Supporting demand in other areas: Generators can sell excess power that cannot be consumed locally to the network to support other demand users. This can have the benefit of reducing network demand during periods of high demand, thus enabling more capacity to be made available for supporting more connections in wider network.

Leveraging these benefits requires active support for flexibility technologies and accounting for these benefits in network design.

Due to its inherent nature, solar PV generates in a finite window which is not generally at times of peak demand. This makes solar less directly beneficial than other renewable energy technologies that have some part of their energy generation window overlapping with the peak demand window. Engagement with DNO stakeholders resulted in the following conclusions on solar opportunities to the network:

• A greater deployment of solar PV in the future will provide only small opportunities to reduce peak demand on the wider network. This is because solar generation is greatest in the summer on sunny days, and the demand peaks in the winter evenings when solar generation is usually at its lowest.
• Domestic consumers who deploy rooftop solar PV are unlikely to present opportunities to the network as it is unlikely that generation will coincide with peak domestic demand.
• There may be greater opportunities to the network from commercial consumers whose demand will peak during the day with a greater chance of matching the peak in solar PV generation. This would especially be the case for commercial buildings with flexible demand, or who provide EV charging points to their employees.

However, it is the view of the stakeholders that co-locating domestic and commercial scale battery storage within the premise along with solar PV can provide greater economic opportunities. It will enable greater benefits to the distribution network to be realised as it will allow consumers to offset their peak demand and extend the duration during which electricity stored from solar PV can meet their own energy requirements [5]. This could provide a valuable flexibility service to the network and delay the need for expensive network upgrades, which can reduce network costs and consumers’ energy bills. Overall, battery storage should be encouraged alongside solar to enable greater opportunities for both the network and technology to be realised going forward.

Potential benefits to consumers from increased solar PV deployment in Scotland

Connecting solar consumers

For an individual connecting solar consumer, the main benefits of installing solar PV include a reduction in electricity costs and direct access to zero carbon renewable electricity.

The Carbon Trust publishes information online to advise businesses on the potential of renewable energy and to assess whether using renewable technologies is a viable option for a business [6]. According to the Carbon Trust, typical small-scale installations are around 15 to 25 square metres, with a 3 kW system comprising of around 15 panels taking up an area of 20 square meters and can generate roughly 2,500 kWh per annum [7]. Maintenance costs are low and estimated payback time varies significantly and will depend on the circumstances of each site. Some domestic installations report a payback period of just 4 years, reduced from previous years due to higher electricity prices in the UK [8].

The potential benefit to individual connecting solar consumers will be on a case-by-case basis and depends on how much solar can be generated and the times of day the consumer is at home to maximise the benefits. For example, an average assumption for domestic solar panels is that 30% of generation is consumed at home and 70% is exported when the owners are out at work from 9-5pm [9]. If the consumer is at home during the day, then self-consumption will increase, while a commercial building is likely to use over 80% onsite. In summer, this offset might be significant, though this will be lower in winter when generation will be lower, and demand is often higher. Installing solar PV can bring financial incentives where a payment can be received from a supplier for a proportion of solar that is sold directly to the grid through securing Smart Export Guarantees [10].

Stakeholders agreed that installing energy storage alongside solar PV can be used to extend the duration when power from solar can offset consumer demand, enabling further reduction in energy bills. Using energy storage can provide benefits by storing the excess solar energy that cannot be consumed at the time of generation, which reduces the level of exports onto the distribution network. This could help to reduce the need for network interventions if the design methods adopted by the DNOs allow for this.

All consumers across Scotland

The scale of solar PV installations in a 2.5 GW ambition will trigger network interventions because the DNOs are required to make conservative assumptions that less generation will be consumed onsite with more exported onto the network. This will have an impact on all consumers electricity bills in Scotland (not only those consumers with solar PV); however, consumers with solar installations will be less impacted compared to consumers without solar installations. Adopting flexibility measures such as domestic and commercial scale battery storage to absorb and reduce the excess solar generation exporting onto the grid will reduce network interventions, and thus reduce overall consumer costs. This should be encouraged alongside the installation of solar PV to maximise the potential of the technology and extend the duration at which demand can be met by on-site generation.

Potential for distribution connected solar PV deployment in Scotland’s energy network

DNO forecasts of rooftop solar PV connections

The decarbonisation of a wide range of economic sectors, including the electrification of transport and heating, is expected to result in high adoption of low-carbon technologies (such as heat pumps and EV chargers) on the electricity distribution grid. As a result, greater network capacity will be required to facilitate supplying these additional loads, and the network load profiles will become less predictable. This could raise new operational and management challenges to the DNOs. In order to plan in advance of future network pinch points, the DNOs carry out studies to identify where network intervention is required between now and 2050 to enable informed investment priority decisions to be made.

As part of their licence, DNOs are responsible for facilitating and creating the network infrastructure to meet electricity demand. To accomplish this, the DNOs forecast and understand consumers changing electricity needs under varying levels of consumer ambition, government policy support, economic growth, and technological development. The DNOs present these results in form of their DFES data, which provide a breakdown of different demand and generation technologies across each scenario up to 2050 and is updated every year after the DNOs have revised their modelling data. Both SP Distribution [11] and SSEN Distributions latest DFES data was assessed as part of this project. SSEN Distribution DFES results is not published in the public domain, this information was obtained directly.

Using the latest DFES data on Scotland’s energy network, the Figure 2 shows both SP Distribution and SSEN Distributions forecasts of new small-scale solar installation until 2030 using 2020 as the baseline.

Figure 2: Estimated new solar rooftop installations across Scotland in 2030 (2020 base year) Source: DFES forecasted generation capacity scenarios

Figure 2 shows that projected small-scale solar PV uptake in 2030 is significantly less than the 2.5 GW number suggested by the solar industry. Even the scenario with the highest projected numbers (Leading the Way) forecasts only 13% (c.325 MW) of the 2.5 GW solar industry ambition. This indicates that the evidence collected by DNOs from stakeholder meetings with Local Authorities (LA) and generation developers is for a lower level of solar deployment.

Accommodating a significant number of small-scale solar installations

From our engagement with DNO stakeholders, we understand that individual small-scale (G98) applications are of less concern due to their small export capacity; however, a large cluster within a specific network area will pose greater network challenges. The impact will be location dependent as network topology and capacity will vary. In some cases, depending on the makeup of the LV feeder, the cross-sectional area of the cable, the number of consumers supplied on that feeder and the size of the houses, there may be no problems connecting a significant amount of PV in an area. However, in other cases, network reinforcement may be required with the addition of even a modest amount of PV generation.

DNO stakeholders informed us that major network interventions needed to accommodate a significant amount of G98 applications are designed based on ‘worst case’ principles, where minimum consumer demand and maximum generation output are witnessed on the DNOs network. This approach has been used by DNOs over many years to establish if the network can still operate safely and reliably when there is an excess of generation exports due to low consumer site demand.

Network impact assessments allow the DNO to understand the impacts as a result of accommodating more generation connections. Areas of investigation for the DNOs include:

• Thermal overload
• Voltage rises
• Increased harmonic and fault level contributions

If EREC standards of compliance are not meet through utilisation of the existing network, network interventions are required, and the scale of the work needed is proportional to the resulting network impact.

Larger rooftop solar PV installations (G99 connections) require approval from the DNO before connection is granted. In contrast, G98 connections are ‘fit and inform’, where the connection can proceed without DNO approval. The connections are managed by the DNOs on a first come first serve basis by placing G99 applicants into a managed queue. A network impact assessment is carried out and any reinforcement costs incurred by the DNO are included in the final connection offer. The timescales for accommodating G99 solar PV connections (mainly commercial buildings) depends on the scale of the upgrades needed; however, DNOs are licenced by Ofgem and are obligated to make a final connection offer within the set timescales.

Innovative methods of accommodating new connections

Historically, the connection agreements for generators and load connected at low voltage allowed import or export of the full rated power with no restriction to time or duration. Connections and the network had to be reinforced to allow this. This would involve replacing cables, overhead wires, transformers, and switchgears. Broadly speaking, the more reinforcement works needed at high voltage levels results in greater the reinforcement costs.

However, in recent years DNOs have introduced new methods that enable smarter use of the network equipment and reduce the amount of traditional reinforcement that is needed to accommodate the significant uptake of generation.

The type of interventions used by DNOs include:

• Network flexibility though flexible connection agreements: Flexible connection agreements allow the DNO to manage the load and generation connected to the network to some extent, providing a lever to alleviate overload on equipment or voltage issues. Examples include requiring the generation or load to operate differently if there is an outage of equipment on the network, at certain times during the year, or in response to signals from the DNO. This means that less reinforcement is needed to connect the new load or generation, potentially reducing the cost and time to connection. This does mean though that some developments would not be able to export power at certain times if they signed up to flexible connection agreement.
• Network reconfiguration: This involves using remote controlled switches (mostly manual switching is done at LV level) to reconfigure the network and shift generation output from network equipment that is heavily loaded to another area of the network that is lightly loaded. This helps to release capacity on the network, reduce network constraints and avoid network upgrade investment.
• Other innovative solutions: Both SP Distribution and SSEN Distribution are actively deploying new smart network management tools to manage the network more efficiently to allow a transition away from traditional ways of operating. For example, collection of network data to make more informed decisions on network operation or control systems to manage the network better during peak operation periods which will help reduce network constraints and maintain voltage tolerance limits.

It is important to note that innovative solutions will not alleviate all traditional reinforcement requirements. If the options above fail to provide the necessary network capacity needed to accommodate more generation then infrastructure will need to be upgraded.

Connecting a significant volume of rooftop solar generation

A significant rise in solar PV connections could be accommodated in an efficient manner if the DNOs and policymakers work in collaboration to understand the policy signals, increase data transparency, understand the role different parties need to play and investment required to make this happen in a timely manner.

In order to maintain a smooth transition to greater solar PV uptake, improved intelligence is needed, particularly at LA level, to understand where solar PV is likely to be located. More local information could provide more accurate data to update DNO modelling tools. This will give the DNOs a better picture of where networks will likely require intervention and inform their investment priority decisions ahead of time. This will also provide evidence to justify DNO decisions to Ofgem.

DNOs have an obligation to provide an option to connect, but the timescales for making connections will vary depending on how much network intervention is needed. The cost of providing such interventions is, in part (depending on the particular situation) borne by the developer seeking the ability to export. The scale of investment needed in specific locations could affect connection timescales.

Innovative approaches should continue to be used where possible to reduce the cost and time to connect. This will minimise the barriers to develop new renewable generation projects while maintaining a secure and reliable power supply. Innovative approaches are also a more efficient and cost-effective approach to asset management.

Impacts of increased solar PV deployment on electricity networks

Potential network challenges of increased rooftop PV

The changing nature of the electricity distribution network as a result of dynamic power flows and increased unpredictability in load profile behaviour requires a transition away from traditional ways of operating. For example, electricity networks in Scotland are traditionally managed to meet the maximum demand throughout the day and year by sizing assets accordingly. However, the rise of generation at distribution level creates new challenges, such as demand reduction, increased thermal constraints, reverse power flows, greater voltage constraints, greater fault level contributions and harmonic contributions. These are detailed in Section 7.1.

The impacts depend greatly on the size, design and local network condition of each individual connection. Additional PV generation would also be connected within the context of other LCTs such as heat pumps, batteries, electric vehicles, wind and larger solar generation. It is difficult to predict the specific challenges and impacts which will be experienced with accuracy.

DNO stakeholders informed us that they are most concerned about voltage rises which must be maintained within the correct limits. This will be a big challenge in summer when there is excess generation flowing in the opposite direction onto the network, which increases network voltages. The exact scale is unknown and even a small deviation from voltage limits can damage network infrastructure and appliances because all electrical equipment is designed to handle voltages within specified tolerances.

Estimated scale of network impact

We conducted an analysis to determine how many primary substations are likely to require intervention in 2030 as a result of greater solar PV deployment in Scotland. The analysis used 1.5 GW domestic rooftop solar and 1 GW commercial rooftop solar by 2030, information provided by the DNOs and data from the DNOs DFES. The DFES provides generation forecasts up to 2050, including the distribution of that forecast across primary transformers. It was assumed that the additional solar generation was spread across the network in accordance with the forecasted distribution pattern. The uplifted generation forecast numbers for rooftop solar PV were then used to understand where substations were likely to be overloaded and may require interventions in 2030 by using the DNO headroom report on capacity availability [12] [13]. The methodology behind the analysis is discussed further in the Appendix Section 7.2.

The projected percentage of primary substations that may require intervention in 2030 due to the 2.5 GW solar rooftop are shown in Table 1.

Table 1: Primary substations that may require interventions by network area (Source: DFES data)

We found that 46% of total primary substation equipment in SP Distribution and approximately 9% of total primary substation in SSEN Distribution could be overloaded as a result of increased solar PV generation. This represents 176 primaries out of 385 in SP Distribution’s area and 33 out of 384 in SSEN Distributions area. The analysis can be broken down further into low, medium and highly constrained sites:

Table 2: Extent of site constraints for overloaded sites

The majority of these network interventions are projected to take place in SPENs distribution network area, which is likely to be linked to the fact that it is located in busier urban areas, whereas SSEN Distribution area is more rural.

We carried out a high-level analysis to estimate the cost of interventions for upgrading distribution network infrastructure to accommodate the 2.5GW solar rooftop in 2030. The estimated cost of reinforcement provided by DNOs for selected study areas was scaled up to estimate the reinforcement cost for the entire network.

The methodology used to estimate this cost is described in Section 7.3.

Figure 3: Estimated cost of interventions in 2030 in both SPEN and SSENs distribution boundaries (£ millions)

It can be seen that the cost of intervention is higher in the SP Distribution area (£134m compared to £17m in SSEN Distribution area). This can be attributed to a greater number of interventions being forecast as required in the SP Distribution area.

Impacts on consumers’ bills and potential mitigations

Rules for connection charges and Use of System charges

The DNOs are licenced by the energy regulator, Ofgem, who sets rules regarding the amount of revenue DNOs can recover from consumers, this includes connection charges.

Connection charges for rooftop solar covers the cost of replacing or upgrading equipment to facilitate new generation connections. The DNO determines the extent of network reinforcement required, and the subsequent cost, by studying the impact of the additional generation on the network.

G98 connections, which are likely to include all domestic-scale and smaller commercial rooftops, do not incur connection charge. Larger generation installations under G99 may trigger an upfront connection charge depending on the capacity of the local network. Multiple generation installations in close proximity installed by the same party, for example a housing association fitting solar panels across many properties in one area, may also result in a connection charge.

For all cases, additional costs not covered by the connection charge are recovered through Use of System (UoS) charges. UoS charges are charged to all consumers through their electricity bills. The DNOs are required to calculate these UoS charges annually utilising the Common Distribution Charging Methodology (CDCM) [14]. Each DNO is required to publish their statement of charges in advance of application [15]. These statements provide detail of how the charges are determined for demand or generation customers, and these are further split by domestic and non-domestic categories. The charging statements also contain worked examples of how any reinforcement costs are calculated.

There are a number of steps used to calculate the Distribution Use of System (DUoS) charges which will be impacted by increased solar PV installation. For example, for each category of demand users the DNO estimates the following load characteristics:

• A load factor, defined as the average load of a user group over the year, relative to the maximum load level of that user group; and
• A coincidence factor, defined as the expectation value of the load of a user group at the time of system simultaneous maximum load, relative to the maximum load level of that user group.

In determining the load characteristics of each category of demand user, the DNO will analyse meter and profiling data for the most recent 3 year period for use in the calculation of charges. Load factors and coincidence factors are calculated individually for each of the 3 years and a simple arithmetic average is then used in tariff setting. Large scale PV deployment would impact these calculations but without detailed data it is not possible to accurately determine what the resultant potential impact might be.

The DNO determines a set of different distribution time bands, based on the underlying demand profiles and associated costs – these could be expected to change given large scale PV deployment in some areas. These time bands can only be revised annually on 1 April. It is likely that the large-scale rollout of solar PV for domestic customers will reduce their consumption during daylight hours (co-incident with system peak times) thus leading to a lower DUoS cost over those periods.

The DNO also forecasts the volume chargeable to each tariff component under each tariff for the charging year, which are separately determined for the Domestic Aggregated and Non-Domestic Aggregated tariffs. These volumes would be impacted by PV deployment relating to the two different categories, thus impacting the relevant tariffs differently.

The Significant Code review undertaken by Ofgem “Network Access and Forward-Looking Charges” [16] came into effect from 1 April 2023. This resulted in a reduction in the contribution to network reinforcement made by G99 connections. This improves the business model for many generators, who would otherwise have had to pay larger upfront costs. A summary of the previous and new rules for connection charging is provided below with some key terms.

• Onsite works: This is works needed onsite to accommodate the installation and includes facilitating a connection to the distribution network.
• Reinforcement works: This involves replacing equipment on the existing network to accommodate new connections. This usually involves replacing cables, transformers and switchgears etc.
• Connecting solar consumers: This refers to domestic and commercial entities who have rooftop solar installations. A G98 installation is typically relevant to connecting consumers who are domestic, while G99 is more relevant to connecting consumers who are commercial entities.

Table 3: The new Ofgem Significant Code Review rules for recovering network upgrade costs from generation connections that trigger the need for reinforcement (Source: Ofgem [16])

Potential impact on consumer bills

Large-scale solar PV adoption will impact the DUoS calculations for consumers. In order to assess the cost impact of the large scale roll out of rooftop solar on all consumer bills (not only consumers with solar installations) we assumed that all network interventions required to accommodate 2.5 GW of solar would be socialised. This is a simplified assumption that provides an estimate of the maximum impact UoS charges has as a result of the modelled interventions. A more accurate assessment would require more data regarding locations of commercial and domestic properties and the scale of solar to be adopted at the premises. This is because larger commercial buildings adopting solar PV will likely make a direct contribution to network intervention costs, thus reducing the UoS spread across all remaining consumers.

According to Scottish Government energy data, non-domestic consumers account for 60% of Scotland’s total electricity consumption. As a result, non-domestic consumers will pay more towards DUoS directly due to their higher energy consumption [17]. We applied a non-domestic to domestic electricity consumption ratio of 60:40 in both DNO licence areas in Scotland. This allocated 60% of the intervention costs in each DNO area to non-domestic, with the remaining 40% of the costs going to domestic consumers.

We then spread the costs using the ratio of number of non-domestic to domestic premises to obtain an indication of the increase in non-domestic and domestic energy bills which could be realised following large-scale solar deployment. SSEN provided this split, where out of total consumers in their licenced area that have electricity meters, 90% are non-domestic premises while 10% are domestic. The Department of Energy Security and Net Zero (DESNZ) has published information on GB electricity meters, and a similar ratio was observed [18]. SPEN did not provide the split in their region, so we have assumed the same ratio will apply.

Table 4 shows the annual impact of socialising the reinforcement investment required at distribution level to accommodate 2.5 GW rooftop solar. Costs per consumer bill split between domestic and non-domestic consumers in Scotland irrespective if they have solar or not have been estimated. Section 7.4 explains the methodology used to calculate this estimate.

Table 4: Annual impact of socialising the reinforcement cost at distribution level on consumers in Scotland (£/year/customer bill)

Non-domestic consumers will pay a bigger contribution towards reinforcements triggered by solar PV uptake due to their higher energy consumptions, while domestic consumers pay less towards DUoS. These costs are based on assumptions applied due to lack of available data during the research and should therefore be treated as indicators of what the additional costs over and above baseline energy bills could be but they are not definitive.

The DNOs did not validate or confirm the methodology we used to derive these numbers. These provide a highest cost estimate due to the assumption that all Scottish consumers will pay 100% of reinforcement costs through their electricity bills. However, it is likely that some commercial solar connecting consumers will pay a proportion of the reinforcement costs they triggered upfront directly. This would reduce the impact on all consumer bills but is unlikely to have a large impact. It was not possible to separate the reinforcement cost triggered by commercial consumers due to data limitations.

Potential impacts on the transmission network

A proposed ambition 2.5 GW of small-scale rooftop solar PV by 2030 is likely to trigger the need for network reinforcement across the transmission network in Scotland and the rest of GB. The exact nature and scale of the upgrades required is difficult to predict as there is uncertainty as to where the clusters of solar will be located and the nature of impacts are locationally dependent. Different areas of the transmission network have varying levels of headroom and different amounts of generation could be accepted before voltage and fault levels are triggered.

The nature of transmission network impacts and the intervention design works needed to accommodate future connections (including solar PV and other generation technologies) are determined from the Security and Quality of Supply Standard (SQSS) [19]. This sets the criteria for electricity transmission network planning.

• Network Assessment Approach: The TOs take a deterministic snapshot methodology approach to reduce the risk of transmission assets being overloaded and generators being constrained on their respective networks. In this deterministic methodology, the TOs study the summer minimum demand against the maximum generation output on a given local area network for the assessment of any new generation connecting.
• The results of network impact assessments: The TOs assess thermal, voltage and fault level constraints on the network and conclude if greater solar PV embedded in the distribution network could trigger non-compliance with grid code procedures if reverse power was realised.

The timelines to resolve transmission constraint issues can be significant and are longer than the timescales needed for distribution upgrades.

A high-level analysis was carried out to estimate the transmission network costs incurred by the TOs to upgrade the network. Figure 4 shows the estimated cost on the transmission network in Scotland is over £150 million with £122 million (81%) of this in the SPEN transmission network and £30 million (19%) in the SSEN transmission network.

Section 7.3 explains the methodology used to estimate these costs in more detail. In brief, the estimated cost of reinforcement provided by TOs for our selected study areas was scaled up to estimate the reinforcement cost for the entire network. SPEN transmission reinforcement costs were estimated using cost of reinforcement shared by SSEN transmission for the study area.

There will also be an incremental impact on the transmission network in England which will trigger additional transmission costs due to greater transmission capacity required to accommodate greater solar exports. These have not been considered in this study and the numbers provided below are for transmission assets that are located only in Scotland.

Figure 4: Estimated cost of interventions in 2030 in both SP and SSENs transmission boundaries (£ millions)

The investments made by the TO will be recovered through the price control mechanism with the cost being socialised across all GB energy consumers. Our estimated costs are provided to give insight into the scale of the challenge to reinforce the transmission network but are not definitive. Further, more detailed analysis would be required to reliably quantify the estimated costs associated with interventions in the transmission network.

Conclusions

We assessed the likely benefits and impacts of a proposed ambition for an additional 2.5 GW solar PV at distribution level in Scotland by 2030. In conclusion:

• An additional 2.5 GW solar ambition would enable progress towards net zero targets. The Scottish Government has set a target to reach net zero carbon emission by 2045 and increased rooftop solar could contribute to the ambition to deliver at least 20 GW of additional low-cost renewable capacity by 2030.
• Individual financial benefits are based on the reduction in electricity bills for consumers adopting solar PV. Benefits could be increased if demand could be shifted to times of excess generation.
• Network benefits could be realised by pairing solar PV with battery storage as this will improve flexibility. Solar PV is an intermittent energy source and unlikely to reduce peak demand significantly.
• DNOs would be obliged to make a firm or flexible connection offer to facilitate the extra solar PV in a cost-effective manner. Advance visibility of where large quantities or clusters of rooftop solar PV connections would be located would help DNOs understand the scale of intervention needed and in what timescale it can be delivered.
• We estimate that 30% of primary transformers will require intervention to accommodate a 2.5 GW solar ambition. Most of these will be lightly constrained sites that are less than 10% overloaded. The impact is highly uncertain and depends on specific location of large quantities of solar PV and the status of the local electricity network.
• The cost of this impact is uncertain; we estimate £150m in the distribution networks, and over £150m in transmission networks. These are based on highest-cost assumptions that traditional methods are used for capacity release eg that overloaded equipment is replaced with higher rated equipment.
• The required intervention will be largely paid for by consumers. The network intervention costs associated with implementing the additional rooftop PV will be socialised to all consumers through electricity bills. A proportion of larger installations may be payable through connection charges by the connecting consumer.
• The estimated average annual increase in energy bills for domestic consumers is £0.53 and £1.81 in SSEN and SPEN areas respectively. The average annual increase in non-domestic consumers energy bills is estimated at £7.17 in SSENs area and £24.46 in SPENs area. These are indicators based on assumptions but are not definitive, and the approach has not been validated or confirmed by the DNOs.
• Adopting flexibility measures such as domestic and commercial scale battery storage will reduce the excess solar generation exporting onto the grid. This will reduce network interventions and thus reduce consumer costs. This should be encouraged alongside the installation of solar PV to maximise the potential of the technology and extend the duration at which demand can be met by on-site generation.
• Network interventions are triggered in part because DNOs are required to use the conservative assumption that less generation will be consumed onsite with more exported onto the network.
• Incentivising the requirement to have domestic and non-domestic battery storage in conjunction with solar PV to absorb any excess solar, thus preventing exports, may reduce the scale of network interventions needed. Battery storage can provide greater network flexibility by charging and discharging as required.
• Network operators are developing innovative ways of managing networks which could reduce the costs. Solutions including flexibility, reconfiguring the network, improved network visibility and active network approaches are increasingly being used. These approaches could also speed up the time taken to offer new connections. While these approaches could decrease the need for reinforcement, they are unlikely to entirely mitigate the need to be consistent with relevant technical requirements.
• A co-ordinated approach is needed between key stakeholders including the DNOs, TOs, LAs and the solar industry to ensure that a significant increase in solar PV can be accommodated. Improved evidence of large quantities of solar being proposed is needed to allow the DNOs to plan accordingly and justify their decisions to Ofgem.
• Overall, it is difficult to quantity whether the benefits outweigh the impacts on the grid and on consumer bills, but steps can be taken to reduce the impact and enable greater benefits to be realised. Examples include investing in on-site battery storage and continued deployment of network flexibility and innovation solutions.

References

Appendices

Network challenges

Demand Reduction through the use of onsite generation will change the daily domestic and commercial load profiles and make them more unpredictable and more difficult to plan the network. Network operators strive to balance demand and generation in order to maintain grid stability and reliability. An increase in solar PV connections will lead to greater network challenges around grid stability. As distributed generation grows it will remove a significant portion of demand from the network during certain time periods, while higher up in the grid, greater numbers of renewable energy plants (offshore and onshore wind) will be connected leading to greater network imbalance. This will exacerbate the situation and pose additional challenges to grid operation. The National Grid may seek to reduce the imbalance by asking large-scale wind operators to reduce energy output or switch off which leads to constraint payments being made. The deployment of greater network demand through large-scale battery storage and hydrogen production is being actively encouraged to reduce the network imbalances.

Examples of network challenges are as follows:

Increased thermal constraints, where significant generated power is fed into the network, for example if there are clusters of PV generation in one area, and there is a mismatch between onsite solar generation and demand on a sunny day. This can overload equipment causing them to heat up beyond their rated temperatures, causing damage or aging. This will be common in summer where there is mismatch between solar generation and onsite demand.

Reverse power flows, where power is fed into the network from generation resulting in power flowing in the opposite direction than designed. Some substations with new equipment will be able to handle greater reverse power flows, however, older equipment or that with a particular design may have less or no reverse power capability and may require maintenance or replacement.

Greater voltage constraints, where voltage rises due to the reduction in load or the increase in generation across an area of network. All networks are designed to operate at voltages within acceptable tolerances and DNOs have a frequent task to maintain voltages within the correct limits. If voltages go outside their limits, this poses risk to asset health which could be damaged as a result. Greater solar connections runs the risk of exceeding voltage limits as laid out in the DNO licences. Voltage constraints are the biggest concern to the DNOs as they have the biggest impact.

Greater fault level contributions, where the solar PV installations contribute towards greater network fault currents, which are triggered due to disturbances on the network. Faults on the network can cause inrushes of current which can damage critical infrastructure. The network and its protection equipment must be designed to accommodate the fault level for a short time in order to keep equipment and people safe. PV generation contributes to fault level (large inrush of current when there is a fault on the network), and so connection designs must accommodate it. If the fault level rating of equipment is exceeded the DNO will replace the assets. As a result, a significant cluster of generation will increase fault level contributions right up to transmission level.

Harmonic contribution, where PV generation creates distortions in the Alternating Current (AC) signal resulting in a reduction in power quality being delivered to consumers and some consumer equipment might flicker or not operate properly. PV generation contributes to harmonic issues as a result of the inverter equipment, but this contribution is limited by regulation.

Methodology for estimating proportion of interventions needed

The DNOs forecast and understand consumers changing electricity needs under varying levels of consumer ambition, government policy support, economic growth, and technological development. The DNOs create forecasts for multiple scenarios through their DFES data (Leading the Way, Consumer Transformation, System Transformation, Steady Progression) [11] [20]. DFES data from both SPEN and SSEN using the Consumer Transformation Scenario was used in our analysis. This scenario assumes greater consumer engagement, which leads to greater deployment of low-carbon technologies, such as solar PV, to offset network demand. We consider that this assumption would be consistent with increased solar deployment.

Primary substations which are likely to require intervention in 2030 were determined by spreading the 2.5 GW of solar PV across all primary substation assets in Scotland. We used the DNOs modelling assumptions to determine where they believe the high clusters of future solar installations will be located and spread the extra the 2.5 GW using the same pattern of distribution. The detailed approach is described below:

1. We used DNOs DFES modelling tools to determine how much rooftop solar PV is estimated between now and 2030 across all primary substation assets. This was clear from SPEN modelling, but SSEN did not provide a degree of granularity and we estimated as the solar PV numbers.
2. The DNOs own estimates of rooftop solar PV were removed from the analysis to leave an indication into forecast individual large-scale solar PV (ground-mounted). This was to avoid including the 2.5 GW over and above the DNOs rooftop solar PV forecast as this would duplicate the number of households that has solar PV.
   • We calculated the proportion of rooftop solar to total solar using DFES data. The DFES data only provided total rooftop solar numbers across each year rather than across each individual substation per year which reduces the level of granularity. However, the combined solar PV numbers (rooftop + ground mounted) was provided for each substation across every year. We expressed the total rooftop solar PV numbers to the combined solar PV numbers in 2030 as a percentage. This allowed us to estimate the proportion ratio of rooftop solar in 2030, which was then used to separate the rooftop component from the overall total solar PV numbers across all primary substation data. This provided an estimate of rooftop solar PV across each primary substation.
3. 2.5 GW of solar capacity was then spread in a similar proportion to the original DNO forecast of rooftop solar across all primary substations to provide an uplifted forecast. For example, if the DNO was estimating that 2 MW of rooftop solar PV would be located in an area in Glasgow, we estimated that 15 MW would be realised in that area in 2030 using the following calculation:
   • Uplifted forecast = (2MW / total forecasted rooftop solar PV in 2030 from DNOs modelling tools) * 2.5GW
4. The proportion of primary substations that will require interventions was estimated by subtracting the uplifted forecast from the DNOs published headroom report figures.

Methodology for estimating cost of intervention

We used four study areas in order to assess the cost of interventions needed. The study areas covered four categories:

• Rural
• Domestic properties in urban areas
• Mixed domestic & commercial in urban areas
• Commercial properties in urban areas

A primary substation was selected for each study area that was close to being overloaded by using the DNOs published heat map data.

Table 5 Study areas used to assess cost of intervention

The study areas were submitted to both the DNOs and TOs to gain high level estimates of the type of interventions deployed and the cost of interventions.

Due to time constraints, the DNOs and TOs could not commit to undertaking a detailed analysis, which involves undertaking detailed power flow analysis. The results provided are estimates of interventions from previous assessments carried out by the DNOs. The results of the DNOs and TOs analysis are detailed below.

Table 6 Cost of interventions and assumptions provided by the DNOs for each study area

The estimated cost of reinforcement provided by DNOs for the selected study areas was scaled up to estimate the reinforcement cost for the entire network. The headroom capacity numbers across all primary substations that may require intervention was used to scale up the costs.

The results of the investigation with the TOs are provided in Table 7.

Table 7 Cost of interventions and assumptions provided by TO for study area

SPEN transmission reinforcement costs were estimated using the cost of reinforcement shared by SSEN transmission for the study area.

Methodology for estimating the impact on consumer bills

The steps below explain the methodology to estimate the impact of socialised costs on consumer bills split between domestic and non-domestic.

1. Allocated 60% of the estimated interventions costs directly to non-domestic consumers with the remaining 40% going to domestic through the DUoS mechanism, which allocates socialised costs to the higher energy consumer. 60% of Scotland’s total electricity consumptions comes from non-domestic.
2. Socialised costs were treated as standard network capex and so were added to the DNOs Regulatory Asset Base (RAB).
3. The total socialised cost to be recovered through deprecation over a period of 45 years (assumption shared by SSEN DNO).
4. The DNOs regulated rate of return was applied to the investment.
5. SSENs split of non-domestic and domestic consumers in their licences area (90:10) was provided for the investigation. SPEN did not provide a similar split; however, it is assumed that the same ratio split applies.
6. Using the total costs allocated to non-domestic and domestic based on their energy consumptions, and using the quantity of customers split between domestic and non-domestic, an annual impact per customer split between domestic and non-domestic could be obtained.

The numbers are reflective of 2030 prices as this is when 2.5 GW could be realised. The year 2030 was used in isolation throughout this analysis rather than assessing the impact each year up to 2030 as we could not be sure how much solar would be added each year. It was therefore assumed that the grid would see 2.5GW in 2030.

Stakeholder engagement findings

This section presents areas of discussion in a series of stakeholder engagement meetings with DNOs and TOs. The meetings aimed to understand the following:

• The potential for greater solar PV deployment in Scotland and how existing distribution and transmission networks will accommodate them in additional to other generation technologies
• The impacts on the networks as a result of greater solar PV connections and the resulting interventions deployed by the network operators to manage the increase in connection requests
• Establish the intervention assumptions and resulting cost to deploy these interventions when solar PV connections trigger the need when capacity headroom is no longer available
• Explore the opportunities that solar PV can bring to future distribution network
• Explore gathering data on the cost of interventions to support with the analysis

SSEN Transmission

A meeting was held between Ricardo and SSEN Transmission on 20 February 2023 to establish the implications on the North of Scotland transmission network because of greater solar PV connections and how this would be accommodated. A summary of the meeting with the questions relevant for the discussion are summarised below.

Area of discussion: The process that transmission networks use to accommodate a significant increase in PV connections across Scotland’s energy network

The meeting focused on the following topics:

• SSEN TOs view of the 2.5 GW solar PV target by 2030.
• How transmission network impacts are assessed, and the rules adopted for network reinforcement designs.
• The ability of the transmission network to accommodate 100% reverse power flow and identify what needs to happen to accommodate this in the future.
• Establish the impacts on the network from greater generation connections that are off most concern to the transmission network.
• What type of interventions are being deployed to mitigate the impact on consumers.

SSEN DNO

Two meetings were held between Ricardo and SSEN Distribution on 24 January and 10 February 2023 to establish the implications on the North of Scotland distribution network because of greater solar PV connections and how this would be accommodated. A summary of the meeting with the questions relevant for the discussion are summarised below.

Area of discussion: How will existing networks will accommodate a significant increase in solar PV connections across Scotland’s energy network?

Areas explored:

• How are G98 (‘fit and inform’) connections accommodated? How can this be done at a large-scale?
• How are G99 (large-scale) connections accommodated, and how can they be accommodated at large-scale?
• What is the timeframe for a G99 application to be granted approval by SSEN? How is this impacted by a large proportion of consumers requesting connections to the same part of the network?
• What type of interventions are being considered? Any smart grid solutions?
• Do you think it will be technically feasible to accommodate 2.5GW of additional small-scale rooftop solar across Scotland’s energy network by 2030?

SPEN DNO

A meeting was held between Ricardo and SPEN Distribution on 15 February 2023 to establish the implications on the Central and Southern distribution network in Scotland because of greater solar PV connections and how this would be accommodated.

Area of discussion: How will existing networks accommodate a significant increase in solar PV installations between now and 2030?

Areas explored:

• How are G98 (‘fit and inform’) connections accommodated? How can this be done at a large-scale?
• How are G99 (large-scale) connections accommodated, and how can they be accommodated at large-scale?
• What is the timeframe for a G99 application to be granted approval by SPEN? How is this impacted by a large proportion of consumers requesting connections to the same part of the network?
• What type of interventions are being considered? Any smart grid solutions?
• Do you think it will be technically feasible to accommodate 2.5GW of additional small-scale rooftop solar across Scotland’s energy network by 2030?

Solar Energy Scotland

A meeting was held between Ricardo and Solar Energy Scotland (SES) on 28 July 2023 to discuss the solar industry view on the solar ambition, benefits of solar and areas of concern for how new connections are currently assessed by DNOs.

© The University of Edinburgh, 2024
Prepared by Ricardo Energy & Environment 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, 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.

Research completed: January 2024

DOI: http://dx.doi.org/10.7488/era/4033

Executive summary

This study reviewed the use of fiscal levers to reduce greenhouse gas (GHG) emissions across the world. These levers include taxes, levies, duties or charges applied by governments on major sources of emissions.

It focused mainly on direct carbon taxes which are applied to specific goods – typically fuels – based on the amount or intensity of greenhouse gases they produce. It also considered indirect taxes, which place a price on other forms of pollution, such as air or water, but often target GHGs as well. Grants and subsidies are not in scope.

The study examined whether these levers have been effective in decreasing GHG emissions, the revenue that has been raised, and how governments have used that revenue. It looked at six international case studies in more detail. It also examined relevant fiscal levers currently applied in the UK and Scotland, and the possible implications for Scotland of adopting any new lever, based on the case studies. This study does not make policy recommendations, nor does it consider the costs and benefits if they were adopted.

Findings

The study focused mainly on the use of direct carbon taxes both nationally and sub-nationally (in specific regions or provinces within a country) around the world. Key findings are:

• The use of carbon taxes is increasingly common. There are 37 direct carbon taxes in 27 jurisdictions globally, most of them in Europe. Several jurisdictions outside Europe have adopted taxes and more are considering them. About 6% of global GHG emissions are taxed by carbon taxes and this share has increased over the past 15 years. Sub-national carbon taxes have also been applied by Canada and Mexico.
• Taxes differ in terms of GHG coverage and carbon price: We identified three broad categories:
• ‘High ambition’ instruments with both a relatively high price and coverage of GHGs;
• A mixed level of ambition, with either high prices and low coverage; or a high share but low prices;
• Relatively low prices and coverage.
• The balance of evidence suggests carbon taxes have reduced GHG emissions where adopted, but the data is limited, uncertain and rarely quantifies carbon leakage – when businesses transfer production to other countries with laxer emission constraints. Other regulatory measures are likely to be required alongside them to meet wider climate policy goals. There is limited detailed evidence on how affected businesses and households adjust behaviour in response to taxes.
• Carbon taxes have generated government revenue; between several billion dollars in Sweden to tens of million in Iceland. The potential for revenue generation depends on the prevailing carbon price and coverage of the tax, as well as the size of the economy, its carbon intensity and energy mix. They have been relatively straightforward and inexpensive to administer for governments. Some direct carbon taxes have been used to raise revenues for specific purposes. These have typically been channelled towards green technology and specific rebates or tax cuts for affected groups, including low-income households.
• Implementation has been politically challenging. Carbon taxes have been repealed in Australia, delayed in New Zealand and a planned acceleration of the carbon price was suspended in France. A legal challenge was brought in Mexico over whether the regional government had legal authority to implement a proposed tax.

Current fiscal levers in the UK and Scotland

Fiscal levers that target or address GHG emissions focus on energy and energy intensive industries, transportation and resource use. Examples include Fuel Duty, the Climate Change Levy, the Renewable Energy Obligation and the UK Emission Trading System, as well as Air Passenger Duty and vehicle excise duty. A devolved tax, the Air Departure Tax (Scotland) Act 2017, is being progressed, but needs to address the Highland and Islands exemption and safeguard connectivity. The Scottish Landfill Tax applies to waste disposed to landfill.

The introduction of new national devolved taxes can only be delivered by agreement of the Scottish and UK Parliaments or through a change to the devolution settlement. Four of the six case studies have similarities to UK levies, which would need amending, but two would be entirely new. We consider how elements of the case studies could be applied in Scotland but make no recommendations on whether this would be advisable.

Principles for implementation

Any financial lever would be designed based on the six principles in Scotland’s Framework for Tax: proportionality, efficiency, certainty, convenience, engagement and effectiveness. As such, the precise design of any lever would need to be subject to careful consideration and clear communication in terms of its scope, phase-in, price (including future price escalation), sectors and activities on which it is levied and any relevant exemptions. Distributional effects would have to be carefully considered, including if and how revenue should be reallocated, to whom and under what conditions.

Successful fiscal levers have been based on transparent design, regular monitoring and communication of revenues, costs and benefits, with rapid adjustments if unexpected adverse effects occur. They have formed part of wider fiscal reforms, with a clear strategic objective. Any potential options would be required to undergo extensive further consultation and robust impact assessment to fully understand the costs and benefits.

Glossary

Introduction

Scotland has a legally binding target to reach “net zero” by 2045, as well as annual climate targets. “Net zero” means reducing carbon emissions to almost zero, with any remaining emissions absorbed by nature (such as via forests) or by technologies (such as carbon capture and storage). Rapid transformation across Scotland’s economy and society is required to meet this goal and the Climate Change Plan sets out a pathway and policies to deliver the targets. The Scottish Government has also committed to a just transition, which endeavours to make rapid decarbonisation beneficial and positive for society. There is currently a gap in our evidence base on the potential role for fiscal levers to deliver reductions in greenhouse gas emissions. For the purposes of this study, we define fiscal levers as taxes, levies, duties, or charges. The use of subsidies, grants and loans are not in scope of this work.

We summarise the results of a targeted evidence review on the international use of fiscal levers seeking to reduce GHG emissions, which have either been considered or adopted by national or sub-national governments. We examine the evidence for how well certain fiscal levers have worked internationally, both in terms of reducing emissions of GHGs and in raising government revenue. We analyse six case studies in detail. After reviewing existing fiscal levers in Scotland, we also assess the potential implications for Scotland.

This report should not be interpreted to mean the Scottish Government intends to adopt the examples analysed in this report, nor any fiscal lever. The purpose is to provide an evidence base for the Scottish Government in their consideration of policy action as part of a strategic approach to climate change mitigation.

Overview of methodology

We conducted a targeted literature review of the global use of fiscal levers currently in place – or being considered – that seek to reduce GHG emissions, either directly or indirectly. We then selected six case study examples that were judged to be relevant to Scotland for further exploration. We conducted semi-structured interviews with academics and technical specialists and with experts in the case study jurisdictions to obtain greater insights. We also conducted a high-level review of existing environmental fiscal levers in the UK (including energy, transport and pollution or resources taxes), focusing the analysis on those that deliver reductions in GHG emissions. This was to help understand whether the six case study examples could be implemented by the Scottish Government under current devolved competencies, or whether their adoption would require joint action with the UK Government. More detail on the methodology we used is in Appendix A.

This approach has limitations. The project was undertaken over a short period, between July and October 2023. As such, the report presents selected results of a targeted search of a large secondary literature supplemented by the interviews referred to above, and it has not been possible to examine all issues in detail. No economic modelling has been undertaken on the potential scope or effects of the levers identified.

The use of fiscal levers for GHG emission reductions

Given the size of the literature and the complexity of the issues involved, we have simplified the review into a smaller number of lever typologies and identified lessons learned via successes and challenges encountered. The information in this chapter is drawn from secondary literature and a small number of targeted interviews with subject matter experts.

We have defined fiscal levers as a tax, duty, levy or charge. Typically enacted by a national or sub-national government, they seek to induce changes in behaviour of companies and consumers via changes in the prices of goods and services. This is sometimes referred to as ‘carbon pricing’, which means levers which apply a price to GHG emissions with the intention of reducing them. Carbon pricing can provide an effective and cost-efficient approach to reducing GHG emissions in multiple economic sectors. They do so by incentivising changes in behaviour, via changes in prices, on both the supply side (i.e., amongst the suppliers of goods and services to invest in new abatement technologies or more efficient processes or products) as well as the demand side (i.e., among consumers in their purchasing choices). They also have the potential to raise government revenue.

Economists often refer to GHGs (and other forms of pollution) as negative externalities. This is a type of market failure where the social costs (in this case the damages caused by climate change to current and future generations) are greater than the private costs from specific transactions (i.e., one only pays for the fuel, not the harm from emissions when filling a tank of petrol). A carbon price is a way of correcting the market failure by ensuring those wider costs are captured or ‘internalised’ in transactions (Coyle, 2020).

The scope of this study does not extend to any assessment of the use of grants and subsidies, including so called “environmentally harmful subsidies” (World Bank, 2023a). These have been considered in Scotland in separate work (Blackburn, 2022).

Typologies of fiscal levers

We developed a list of typologies of fiscal levers to enable their effectiveness to be assessed. We have taken a simple approach to aid clarity, and therefore define five broad types of fiscal lever for this study. These are broadly in line with the categories used by the World Bank (2023b). The types of lever are:

Direct taxation schemes

These are taxes which provide a direct price signal and have the explicit aim to reduce GHG emissions, often referred to in the literature as ‘carbon taxes’. They are levied on emissions, for example £ per tonne of CO₂ equivalent (tCO₂e), or on £ on emissions per litre of fuel. Costs incurred increase in direct proportion to emissions, but costs may be reduced or avoided by changes to production processes or purchasing decisions, where feasible. In practice all such direct taxes are applied only to certain sectors or economic activities, with various exemptions. Given that the focus of the work are levers to reduce GHG emissions, we have focused our research on direct taxes, where the link to GHG reduction is clearest.

Indirect taxation schemes

These are taxes which provide an indirect price signal and may have multiple aims, which include addressing GHGs as well as other forms of pollution, such as air or water pollution. The tax may be applied on a range of activities but are not directly proportionate to embodied GHGs.As such there is a much wider range of such taxes in operation.We summarise such schemes at a high-level.

Carbon credit schemes

These are systems where tradable carbon credits (again typically representing 1tCO₂e) can be generated via voluntary emission reduction activities. Such activities are varied and can include emission avoidance as well as removal, for example tree planting, or carbon capture and storage activities. These credits can be sold (either by businesses achieving the credits or the organisation that administers the scheme). Demand for such credits (and hence value) are generated via the requirements of other carbon pricing or climate change mitigation policies. These are discussed further below, but our research indicates they offer limited potential for revenue raising by a host government, so are not prioritised in this study.

Emission Trading Scheme (ETS)

A Government places a limit on the mass of GHG emissions from the affected entity (usually businesses within a defined economic sector, or undertaking specific economic activities, e.g. agriculture, or aviation) defined in the legislation. Emissions units or allowances, typically representing one tonne of CO₂ equivalent (1tCO₂e), are typically auctioned to businesses. These can be traded to enable them to emit GHGs, within a given period. The price from the auction and/or a traded second market represents the price of carbon. There are two main types of ETS:

• Cap and trade ETS: Governments set a cap on total GHG emissions from one or more economic sectors (or specific entities). They then sell allowances, typically in auctions, or distribute them for free (or a combination of both) up to the level of the cap. The cap (or the number of free allowances) may be progressively reduced. The European Union (EU) and UK ETSs are examples.
• Rate based ETS: Here the total emissions are not fixed, but entities are allocated a performance benchmark (typically based on the emission intensity of their output). This then serves as a limit on net emissions. Emission allowances can be earned where entities’ emissions are lower than the benchmark and these can then be traded with those who exceed it. The China national ETS system is an example.

The UK ETS replaced the UK’s participation in the EU ETS on 1 January 2021. The UK ETS applies in England, Scotland, Wales and Northern Ireland, whose governments comprise the UK ETS Authority. In Scotland, the Scottish Environment Protection Agency (SEPA) administer the scheme (UK Gov, 2023a). The UK ETS was originally based on the EU ETS but has since diverged in structure and operation. Given that Scotland currently has an ETS system, further research on such schemes have not been prioritised in the current research. However, in some jurisdictions, national governments have applied domestic ETS to additional sectors not covered by, for the example, the EU scheme. We refer to these as ‘national ETS’. These are included in the research as they could potentially be applied in Scotland.

Carbon border adjustment mechanism (CBAM)

These are policy mechanisms which impose a carbon price at the border on embodied emissions in specific goods imported from elsewhere. These seek to ensure a level playing field between the carbon price imposed via domestic legislation (such as via an ETS) and goods produced outside that jurisdiction as well as mitigate the risk of carbon leakage (i.e., displacement of carbon intensive activities outside of regulated jurisdiction) which may lead to a lower level of emission reduction overall.

The EU CBAM entered a transitional phase in October 2023. This is aligned with the phase-out of the allocation of free allowances under the EU ETS. The first reporting period ends on the 31^st January 2024 (European Commission, 2023).

The UK Government is considering a range of further potential policy measures to mitigate the risk of carbon leakage in future. One such policy being considered is a UK CBAM. A consultation on these options was conducted jointly by HM Treasury and the Department of Energy Security and Net Zero between the 30th March and 22nd June 2023. The UK Government is currently considering these responses (UK Gov, 2023b). As such, this review does not focus on CBAM measures in other jurisdictions.

Direct taxation schemes

We used data from the World Bank carbon pricing dashboard (World Bank 2023c) to provide an overview of the characteristics of direct carbon pricing instruments as of March 2023. This dashboard identifies a total of 73 such instruments implemented in 39 national jurisdictions across the world. Together, these cover 11.6 gigatonnes CO₂e (GtCO₂e) of emissions (23% of global GHG emissions). Of these, 37 instruments are direct carbon tax instruments, the remainder are ETS instruments. These carbon taxes have been implemented in 27 national jurisdictions and they cover 2.7 GtCO₂e about 5.6% of global GHG emissions. Several trends are evident from these data.

The vast majority of direct carbon tax instruments in operation are in high-income countries, particularly Europe. In terms of timescales for adoption the earliest adopters of national carbon tax instruments in the 1990s are in Northern Europe (Finland, Sweden, Norway, Denmark) but also Poland. The 2000s saw modest further adoption, with only Estonia, Latvia, Switzerland, Ireland and Iceland adopting national carbon tax instruments by 2010. Thereafter, several further European and Non-European countries adopted instruments (the UK Carbon Price Support and carbon taxes in France, Portugal, Spain, Ukraine, Japan and Mexico). These were followed relatively quickly by carbon taxes in Argentina, Chile, Colombia, then Canada, Singapore and South Africa.

In several jurisdictions, carbon taxes have been applied alongside national (or supranational) ETS instruments. These include several in EU Member States (including the UK at the time), as well as Mexico and Canada.

There are only two jurisdictions where sub-national carbon taxes are in operation. There are a total of five in Canada: British Columbia (BC) which was the first subnational carbon tax anywhere in the world; Northwest Territories; Newfoundland and Labrador; New Brunswick and Prince Edward Island. Mexico has several such instruments, the Zacatecas carbon tax, and instruments in Queretaro and Yucatan, for example. In both cases, these are applied alongside a national carbon pricing mechanism; the Canadian federal fuel charge and the Mexican carbon tax, respectively. As would be the case in Scotland, they are also applied alongside an ETS instrument (the Canadian Federal Output based Pricing System (OBPS) and the Mexican pilot ETS, respectively.

Recently, several further jurisdictions are considering instruments. These include the New Zealand agricultural carbon tax, and taxes in Indonesia and three African states: Botswana, Senegal and Morocco. Manitoba in Canada, Mexico (Jalisco), Catalonia and Hawaii are considering new subnational instruments.

Figure 3.1 provides a visual overview of carbon taxes that are either implemented (in operation), scheduled for implementation (adopted in legislation with an official start date) or under consideration (the relevant government has announced its intention to work toward an initiative). Those that are implemented or scheduled are in blue; those under consideration – four subnational taxes and five national – are in yellow.

Figure 8.1 (Appendix C) provides time series data on the share of global GHGs covered in the various carbon tax instruments between 1990 and 2023. This provides an indication of the overall significance of their use globally. Note, due to data limitations the share of emissions shown in the figure from 2015 onwards is based on 2015 global emissions data. Several trends are evident, based on these data:

• As of March 2023, carbon tax instruments covered 5.4% of global GHG emissions. This was slightly down from a peak in 2019 of 5.7%. This is likely to reflect reductions in GHG emissions associated with mandatory lockdowns during the Covid-19 pandemic, alongside some emission reductions in at least some jurisdictions.
• Increases in coverage are evident in the last 15 years, arising from the introduction of new instruments in 2011 (Ukraine), 2012 (Japan), 2014 (France and Mexico), and 2019 (South Africa).
• Over the same period however, total global GHG emissions increased by around 50%, from about 31 million kilotonnes of CO₂e (ktCO₂e) in 1990 to over 46 million in 2020 (latest data). Whilst there are some uncertainties in the data, the overall rate of increase in global GHG does appear to have slowed after 2013 (World Bank 2023d).^[1]

In terms of overall ambition for the carbon tax instrument, Figure 8.2 (Appendix C) presents data from March 2023 which compares the carbon price (in US Dollars per tCO₂e) with the share of GHG emissions that are covered by the relevant tax. The figure also shows ETSs for comparison. These data highlight that existing instruments vary in both price and coverage. Overall, we can identify three broad groupings based on the overall level of ambition of existing instruments:

• High ambition: those with relatively high carbon prices and relatively broad coverage as a proportion of total GHG emissions in that jurisdiction. The carbon taxes in Liechtenstein, Sweden, Switzerland, Norway and Finland are such examples.
• Mixed ambition: this is a larger group with some trade-offs apparent between share or price. For example, Uruguay’s carbon tax, levied on gasoline, provides the highest carbon price but only covers a small share (less than 20% of relevant GHGs). Conversely, Singapore and Japan have wider coverage but a lower price. Others have middling coverage and price, for example France, Canada’s federal fuel charge, Iceland, Denmark and Portugal.
• Low ambition: a smaller group with relatively low prices and coverage. For example, Poland, Estonia, Argentina, Chile and Colombia.

Indirect taxation schemes

The World Bank (2023) defines indirect carbon pricing as other policies which might change the price of products associated with GHG emissions, but they do so in ways not directly proportional to the emissions associated with those products. So these levers do not tax carbon or tax at a rate proportionate to carbon content. Rather, they tax carbon intensive activities or services (or focus on other forms of pollution, such as air pollution, which also has the benefit of producing GHG reductions alongside), hence indirectly create a carbon price signal and encouraging the reduction of GHG emissions. Indirect taxation schemes are therefore very broad. As such, the World Bank (2023c) note that indirect carbon pricing policies are far more common and wide-ranging than direct pricing. This diversity and the weaker causal link with reductions in GHG emissions present a challenge for assessing their effectiveness in this study. As a result, we have given them a lower priority than direct taxation schemes for the purposes of the evidence review.

Examples of indirect taxes exist across many different sectors. They include landfill taxes, such as those in place in Bulgaria (EEA 2022a) and Austria (IEEP, 2016a) or ‘pay as you throw’, schemes for example in Lithuania (EEA 2022b). Pay as you throw schemes are designed to incentivise citizens to separate their waste at source and charge a fee for the collection of residual waste from households.

France has a ‘General Tax on polluting activities’ which applies to companies which are engaged in the storage, thermal treatment or transfer of non-hazardous and hazardous waste (French Ministry of Finance 2023). Latvia employs a National Resources Tax (Latvian Ministry of Finance, 2020), which applies to the extraction of natural resources, environmental pollution, disposal and use of hazardous goods as well as the packaging used in business activities.

In the field of air quality, levers include the Bonus Malus Scheme in France (see Section 8.9 for further detail), air pollution load charge in Hungary, which applies to emissions of nitrogen oxides, sulphur dioxides and non-toxic dust (IEEP 2016b) and a tax on emissions of SO₂ and NO₂ in Galicia, Spain (Xunta de Galacia, nd). Other levers include an incentive fee on volatile organic compounds as is in place in Switzerland, and a Pesticide Tax (Sweden and Denmark).

Finland also employs a tax on peat use for energy. However, this represents a unique situation as peat is in fact subsidised in comparison to the tax rates of other fuels, and peat makes up a significant part of Finland’s energy mix.

Carbon credit schemes

We have used data from the World Bank carbon pricing dashboard (World Bank 2023c) to provide an overview of carbon credit schemes, their use, prominence in global trading, and role in international climate agreements.

Carbon credits are units that represent emission reduction activities that include either avoiding the carbon being produced (e.g., capturing methane from landfills), or removing carbon from atmosphere (e.g., sequestering carbon through planting trees or directly capturing carbon from the air and storing it). One credit is typically equivalent to one metric tonne of a carbon dioxide equivalent (tCO₂e) reduced or removed.

Carbon credit schemes create opportunities for investors and corporations to trade carbon credits. The carbon credit market has grown significantly since the concept was establish alongside the 1997 Kyoto Protocol. It experienced a further surge in interest following the Paris Agreement of 2015, more than doubling in size over five years (Dyck, 2022), though the sector grew less between 2021 and 2022, reflecting challenging economic conditions and criticism of the integrity of some schemes (World Bank 2023c). Carbon credits are supplied via regional, sub-national and national governments (such as the California Compliance Offset Program), at international scale through international treaties (such as the Kyoto Protocol and the Paris Agreement), and independently, via non-governmental entities (such as Gold Standard). The largest share of carbon credits is issued via independent non-governmental mechanisms, which had driven much of the overall growth seen between 2018 and 202.1 Figure 8.3 in Appendix C provides more detail.

The biggest driver for demand on carbon credits is companies purchasing credits, usually from independent suppliers, to compensate for emissions-heavy activities, either voluntarily or in response to regulation. However, carbon credits can be controversial because it is not always clear that carbon has in fact been saved or stored, and there are concerns with the ways in which schemes are set up, managed and promoted. The carbon credit market is currently evolving to respond to these concerns (Donaho, 2023).

Effectiveness of fiscal levers

We interpret effectiveness as the extent to which the policy has achieved its desired objectives and reached the affected group(s) (Scot Gov, 2018), compared to the starting (or baseline) position (i.e. has the instrument led to decreases in GHG emissions in the sector or activities targeted). We have also considered the extent to which impacts can be attributed to the policy in question, compared to other factors. We focus on the available secondary evidence and on direct tax examples. We have sought evidence on policy objectives of interest to the Scottish Government; namely the extent to which the instruments have resulted in GHG emission reductions, preferably where these have been quantified and attributed to the tax, and the extent to which they have generated revenues for the host government. Where possible, we consider whether the policy has brought about behaviour change in response to the tax. We have also considered data on the revenues that the tax has created, as well as how that revenue has been used by the host government. Other unintended impacts are noted, where evidence allows.

Before we consider data from specific instruments, a key broader conclusion is that several sources do not consider that existing carbon tax instruments are sufficient to address climate change goals. The Intergovernmental Panel on Climate Change (IPCC) estimated that to meet global GHG reduction requirements the average G20 economy needs to reduce its GHG emissions by over 10% every year (Green, 2021). The sources above suggests that the price and scope of existing instruments are not sufficient to deliver this kind of reduction.

Evidence on effectiveness – GHG emissions and behaviour change

In analysing the literature, we looked for secondary evidence on the overall effectiveness of different fiscal levers. Our assessment was limited by two key factors. First, it is not always possible to attribute GHG reductions to one policy instrument, compared to the various other factors influencing GHG emissions and all such estimates are subject to uncertainty. Possible other factors include rates of overall economic growth, growth within sectors, economic structure (i.e., size of emission intensive sectors and trends within these), imports and exports, as well as economic shocks such as recessions, the Covid-19 pandemic, and the Russian invasion of Ukraine. Similarly, there are several policies that may affect GHG emissions, so it can be difficult to ascribe GHG reduction to one climate-related policy over another. Second, there is a time lag between policy implementation and observed changes which, in this case, limits the available evidence.

Overall, the balance of evidence suggests that the fiscal levers reviewed have reduced GHG emissions in the relevant jurisdictions, but the precise reduction is unclear. A 2021 review (Green, 2021) collated available quantitative ex post evidence on GHG emissions reductions attributed to either ETSs or carbon taxes.^[2] Key findings are below (note further detail is provided in Table 8.1 in Appendix C, which contains discussion on the findings of several specific studies, including quantitative GHG emission reduction estimates).

• Although carbon pricing has dominated many political discussions of climate change, only 37 studies assess the actual effects of the policy on emission reductions. Of these, the vast majority are focused on European examples. In turn, most of these examples focus on ETSs, rather than carbon taxes, per se. Similarly, there are few studies which compare either carbon taxes or ETSs to other climate change mitigation policies to establish the relative effectiveness and efficiency of policy measure or packages.
• Most studies suggest that the aggregate reductions from carbon pricing (note this refers to both ETSs and carbon taxes) on emissions are generally limited. The overall reductions observed were on average up to 2% per year (again this refers to both ETSs and carbon taxes). However, there is considerable variation in the GHG reductions seen between sectors.
• In general, the review concluded that the existing evidence suggested carbon taxes may have performed better than ETSs in producing emission reductions. Note this conclusion should be interpreted with caution; it may reflect the prevailing carbon price, rather than the mechanism itself and much of the evidence on emission reductions from ETSs discussed in the review focussed on the EU ETS. Some of the studies on which this conclusion is drawn are based on the pilot phase of the EU ETS, which involved free allocations to several sectors, a higher emissions cap and a relatively low carbon price. Future evidence should be monitored to examine whether that conclusion remains valid.
• However, there is more evidence that other regulatory instruments beyond either ETSs or carbon pricing probably have a greater effect than either measure acting alone. A 2020 study concluded that “the real work of emission control is done through regulatory instruments” (Cullenward and Victor, cited in Green 2021). A 2018 review provides some evidence that nations which are part of the EU ETS and are without a carbon tax experienced emission reduction in those sectors not covered by the ETS at a slightly faster rate than those that applied a domestic carbon tax, alongside the EU ETS (Haites, 2018, cited in Green 2021). There are clearly several factors at play.
• Experience to date indicates that in comparison with ETSs, establishing and administering carbon taxes in the host government are comparatively straightforward and inexpensive.

We have identified limited evidence on the behavioural effects of the taxes. Two studies (Tvinnereim and Mehling 2018, Rosenbloom et al 2020, cited in Green, 2021) consider this. They conclude that there is little evidence that the taxes directly result in wider decarbonisation. The studies suggest a more common response is to mitigate the flow of emissions, via fuel switching or efficiency improvements, rather than more significant changes in manufacturing process or technologies. This may be a product of the nature of the instrument, the activities on which the taxes are targeted or current relatively low prices. It may also reflect a lack of coordination of wider climate mitigation policy, which as we have seen above, is likely to be necessary to sustain wider emission reductions.

Evidence on effectiveness – Revenue generation and ‘hypothecation or earmarking’

We reviewed evidence on both the revenue generated by carbon taxes as well as how these revenues have been used. The available data reflects different time periods and there are some methodological inconsistencies. Two overall conclusions are apparent. First, that carbon taxes have generated substantial income for the host government. Second, that a key characteristic of carbon taxes in operation to date is that a substantial proportion of that revenue is often allocated (or ‘earmarked’ or ‘hypothecated’) for specific purposes. Occasionally this hypothecation is explicit in the legislation, hence legally binding, while in other cases this allocation is via a political commitment, hence potentially subject to change with associated changes in Government.

A 2016 review (Carl and Fedor, 2016) of 56 national or subnational instruments found revenues from carbon pricing (i.e., taxes and ETSs) amounted to $28.3 billion in 2013. Of this, well over $20 billion was raised from carbon taxes.^[3] Of this only a small proportion of this revenue overall (about 15% was allocated to ‘green spending’. The review concluded that it was much more common for carbon tax revenues to be reallocated in the form of tax cuts and rebates and this accounted for about 44% of revenues at the time. About 28% were not allocated for a specific purpose, referred to as ‘unconstrained’. The same review indicates indirect taxes are often not reallocated for specific purposes (Carl and Fedor, 2016). Analysis of specific carbon tax instruments were also included, with results shown in Table 8.2 in Appendix C. These data indicate that taxes accounted for revenues between $30 million per year (Iceland) to $1 billion or more (Denmark, British Columbia and Norway). Sweden’s is by far the largest at $3.5 billion and it also has the largest per capita cost and share of GDP. These data indicate – at the time – that the most ambitious schemes constitute well under 1% of GDP. Further quantitative data is set out in Table 8.2 in Appendix C.

More recent data show that by 2022 (World Bank 2023), revenues from carbon pricing had increased significantly to $95 billion, of which carbon taxes generated 31% (just under $30 billion).^[4] Although revenues from carbon taxes had increased, this had been driven by rising revenues from ETSs. The overall tax revenue is not just a by-product of prices, but of the share of GHG emission covered, exemptions, the carbon intensity of sectors, and carbon leakage. For example, South Africa’s carbon tax covers nearly 10 times more emissions than Colombia’s and at a higher rate but was delivering a similar amount of revenues (World Bank 2023).

For comparison, a more recent study based on 40 countries also examined the level and use of revenue (OECD, 2019). This source examines whether the revenue reallocations were legally binding (i.e., set out in the relevant legislative act) or based on a political commitment (i.e., via ministerial or policy statement). The review also provides further detail on precisely how the revenues have been used. These full data are produced in Table 8.3 in Appendix C.

Again, the data show that a consistent feature of carbon taxes is the extent to which the revenues are used for specific purposes; around two thirds of total revenues have some form of hypothecation or constraint. They have been particularly directed toward reducing the taxation burden in other spheres, such as associated with employment or in provision of direct financial relief or subsidy to specific groups. Moreover, the review found that introduction of carbon taxes has frequently been part of broader tax reforms and that it has been more common for carbon tax revenue to be allocated based on political, rather than legal commitments. The authors indicate that the tax reform potential of carbon taxes (i.e., reducing the tax liabilities from labour and capital) may form part of the motivation for adoption, alongside the climate mitigation potential in at least some jurisdictions (OECD, (2019).

Lessons learned

We reviewed evidence on where carbon taxes have been effective, as well as where setbacks have occurred and why. We highlight data gaps and conclude with recommendations identified in the literature on how a hypothetical UK carbon tax might be applied.

Are carbon taxes regressive?

A small number of studies have explicitly reviewed the evidence on distributional effects from carbon taxes (i.e., to whom the costs are incurred, with a particular focus on different impacts based on income) and whether carbon pricing results in generally progressive or regressive effects. For example, Ohlendorf et al (2018) provide a meta-review, but the information identified has generally focussed on low and middle-income countries and shown different results. The review notes that literature reviews have shown mostly regressive impacts in developed countries, but that this is not necessarily the case in developing countries. More progressive outcomes were observed for reforms that remove fossil fuel subsidies as well as some transportation policy. Overall, the review is inconclusive and provides limited lessons for Scotland. The tax itself is likely to be regressive, where additional costs incurred via carbon taxes are passed through supply chains to end users or consumers. Without the revenue recycling/rebate measures described above this may disproportionately affect those on the lowest incomes (Ohlendorf et al 2018, LSE, 2019). The UK Government Net Zero Review examines household exposure to the costs associated with the net zero transition. The review concludes that forecasting household costs in detail is not possible, but costs may fall on households via a number of routes. These include via Government decisions on tax and expenditure, via businesses and reflected in prices, wages and consumer choices (HM Treasury, 2021).

What has worked in the application of carbon taxes?

Overall, we found several examples where carbon taxes have been applied, maintained, contributed to emission reduction and generated revenue for the host government, whilst maintaining popular support. However, in every case, the design of the tax has considered the unique context in each jurisdiction.

A significant element of revenue recycling is a characteristic of most instruments adopted to date. An OECD review notes it has been possible, “in most circumstances”, to strike a balance between using the revenue in ways that are socially useful and that contribute to public support for carbon pricing. Such revenue recycling should not be seen as a panacea for public support, however. Introducing carbon pricing instruments generally is seen as more challenging when general public confidence in government is low (note this is not defined and is clearly relative). Such lack of confidence further limits the options for revenue use, by reducing the space for more significant tax reforms and increasing the political appeal for lump sum transfers of revenue (OECD, 2019).

Others have seen the degree of hypothecation of revenues as a way of ensuring ‘lock in’ of the front-end prices and increasing the overall longevity and stability of the instrument. For instance, by ensuring the back-end uses of the proceeds are visible, it is harder to change prices or exempt certain sectors for reasons of political expediency (Carl and Fedor, 2016).

A further balance must be struck between rigid hypothecation of the revenues, which may constrain flexibility, and the benefits of clearly communicating what revenues are being generated and how they are to be used. This communication is considered to be key for creating public support and any policy should be developed in conjunction with stakeholders and be subject to a detailed cost-benefit analysis (OECD, 2019).

Sweden’s carbon tax, for example, may be seen as an exception to this. Some analysis suggests that it has been subject to so many changes that the ultimate effect of the carbon tax is not clearly distinct from effects of other measures e.g., value added tax, excise duties, etc. (Carl and Fedor, 2016). However, what is clear from the Swedish example is that the tax was part of a wider reform which itself had a clear objective (Section 8.6). This may explain at least some of the public support, even with a relatively high carbon price.

The justification made at the time for the introduction of carbon taxes vary and are not confined to emission reduction objectives. For example, reducing taxation in other areas, such as on labour (British Columbia, Sweden) as well as using them for wider fiscal recovery after financial crisis (Ireland, Iceland). Other rationale includes the relative simplicity and stability relative to ETS instruments (Carl and Fedor, 2016).

In the past, carbon taxes have provided a degree of price predictability and of revenue certainty for the host government. For instance, the British Columbia government has been able to predict revenues at least a year ahead within a 5% margin for error (Carl and Fedor, 2016). This would seem to be a feature of the design of the tax (i.e., the sectors at which it is targeted and the overall share of GHG affected).

Gradual introduction of the tax was seen as a positive feature (for example British Columbia), avoiding a sudden increase in the cost base for affected sectors and mitigating unintended consequences. However, they are also seen as visible, tangible and “politically immediate” ways of demonstrating progress toward climate mitigation (Carl and Fedor, 2016, LSE, 2019).

What lessons have been observed in the application of carbon taxes?

It is equally important to draw lessons on where they have not worked or have encountered problems. Reflecting on implementation, we find that existing carbon taxes are generally not sufficient, either in price or scope, to meet existing climate policy goals.

Carbon taxes have also been politically difficult to implement. They have proved controversial in many jurisdictions, including several with similarities to Scotland. Green (2021) suggests this opposition comes from two sources. The first source is the emitting industries themselves. Second, some evidence is presented by Green (2022) that the public tend to prefer other policies to carbon pricing. Use of dividends (i.e., rebates) may mitigate this risk, but only as part of a wider climate change mitigation package of policy.

The review has identified several jurisdictions where significant setbacks have been observed. The clearest case is in Australia where an existing carbon tax policy was cancelled. The tax generated what were at the time the largest overall revenues and per capita costs in the world. This was despite having a carbon price ($30 per tonne as of 2016) which was comparable with other jurisdictions. The revenues were a product of the relative carbon intensity of the country’s – largely coal fired – energy generation infrastructure. Repealing the tax became a key element of the opposition party’s ultimately successful political campaign (Carl and Fedor, 2016).

Mexico is the first Latin American country which has introduced sub-national carbon taxes. Durango is the most recent State to enact one, in January 2023 and others are considering implementing them. Baja California (a Mexican State) introduced a carbon tax as of 2022 as a part of broader fiscal reforms. The tax was levied on emissions from gasoline and diesels. A legal challenge was subsequently brought in Baja California, by the Mexican Federal Government and a group of regulated entities. This argued that under the Mexican Constitution, only the federal government could implement a tax on fuels. The Mexican Supreme Court ruled in favour of the Federal Government (World Bank 2023c).

In France a planned acceleration of the carbon price increase was suspended in 2018. At that point the price was around $50 per tonne. This was in response to a public backlash on the perceived unfairness of the tax, which was introduced at the same time as broader reforms which were perceived as benefiting the wealthy (IMF, 2019). The wider backlash was epitomised by the ‘gilets jaunes’ or ‘yellow vests’ protests about fuel prices.

There are other examples where the instruments have been adjusted, paused, amended or the price escalator has been delayed or otherwise changed. For example, British Columbia and particularly New Zealand, where a proposed ‘fart tax’ was cancelled and an agricultural tax has been delayed (see Section 3.7.4).

A specific challenge is that the UK – and by implication, Scotland – has one of the most complex tax systems in the world. Some experts have consistently criticised a lack of an overall coherent tax strategy for the UK, particularly considering the implications of demographic changes for future taxation targeted at the economically active working age population (Johnson, 2023).

What are the data gaps?

Our review and the interviews have generated limited specific detail on impacts within affected sectors, as well as details on the behavioural response of those sectors. This reflects methodological challenges as well as time lags between policy action and observed effects. It has also identified limited quantitative information on carbon leakage. The emission reduction estimates are likely to be somewhat overstated, given that this has not been quantified.

Recommendations for the UK in the literature

A 2019 policy brief from the Grantham Institute reviewed the global evidence and provided a series of explicit recommendations for the UK if it were to implement a carbon tax (LSE, 2019). The recommendations were:

• The tax rate should be high enough to be consistent with net zero policy objectives. This implied a starting rate somewhere around £40 per tonne (as of 2020) (note this also depends on the scope of the tax, which is not specified in detail in the paper, but would need to be applied “in most sectors”). It should complement and be carefully designed alongside other climate change mitigation policies.
• Credibility requires clear rules, a design that is not susceptible to political pressure and visibility on how the trajectory of prices or scope may change over time (i.e., annually, based on factors like investment cycles or emission performance).
• The price should start low and rise over time. This doesn’t only allow affected industries time to respond but allows evidence on effectiveness and any unintended effects to be observed in practice.
• The use of the proceeds should be carefully and regularly explained alongside information on the economic, social and environmental costs and benefits (via a published, independent cost-benefit analysis, for example).

Case studies

To gain further depth on specific international examples of fiscal levers, we assessed six case studies in further detail. Their selection was based on six predetermined criteria (see Section 8.1.2 in Appendix A on the methodology for the overall study for more detail). An overview of the selected case studies, and the accompanying rationale for their selection against these criteria is in Table 3.1, below. Each criterion has been assigned a red [R], amber [A] or green [G] (RAG) rating. This is based on a judgement of the researchers on the overall similarities between the case study jurisdiction and the Scottish context. For comparison, the Scottish population was some 5.4 million (in 2022), whilst GDP per capita was $42,362 (in 2021).^[5] Given Scotland’s devolved powers to create taxes with consent of UK Parliament, we include examples where instruments have been applied sub-nationally (for example Canada, Wallonia). There are cases which include rural and island communities or significant renewable energy generation potential (for example New Zealand). Scotland’s ambition is for Net Zero by 2045 and 75% reduction in emission by 2030, so we have selected jurisdictions with similarly ambitious targets (for example Sweden and Austria).

We discuss key features and potential lessons for Scotland in Sections 3.7.1 to 3.7.4 below the table. Full details of the case studies are in Appendix D.

Impact on GHG emissions

The available evidence linking each fiscal lever with GHG emission reduction varies significantly. The case studies include two direct taxes – both of which are applied to various fuels based on their CO₂ content – in Sweden and British Columbia (BC), Canada. These levers have been in place for a relatively long period, so have generally good ex-post evidence available. Bernard and Kichian (2019) have calculated that the British Columbia carbon tax, once reaching the rate of $30/ton of CO₂, achieved an estimated 1.13-million-ton reduction in CO₂ emissions. This equates to an average annual reduction of 1.3% relative to British Columbia’s 2008 diesel emissions and 0.2% relative to all BC CO₂ emissions in 2008. However, they do not think it is a viable strategy for achieving net zero goals in isolation. With regards to the Swedish carbon tax, a review of ex-post analyses of carbon taxes by Green (2021) reveals different results around Sweden’s emission reductions. For example, research by Andersson (2019) found an average emission reduction of 6.3% per year between 1990 and 2005, Fernando (2019) found an annual average reduction of 17.2% and research by Shmelev and Speck (2018) found no effect on emissions. A study conducted by Jonsson, Ydstedt, & Asen (2022) state that GHG emissions have declined by 27% between 1990 and 2018. This highlights various methodological differences in conducting these ex-post analyses, and the difficulty in establishing the baseline of what emissions reductions would have occurred even in the absence of the lever.

The Austrian national ETS (nETS) – which extends the EU ETS, of which Austria is a part, to other sectors – is still in a phased implementation stage and will establish a set price which increases each year, reaching a market phase in 2026. Ex-ante modelling conducted by the Austrian government expects the scheme to reduce GHG emissions 800,000 tonnes by 2025. The proposed tax on agricultural emissions in New Zealand has not yet been finalised.

The evidence suggests the French Bonus Malus scheme – which incentivises uptake of low emission vehicles with a combination of fees and rebates – has been effective in shifting vehicle sales toward more environmentally friendly vehicles. Even though progress has slowed in recent years, average emissions have reduced significantly from 149 gCO₂/km in 2010 to 111 gCO₂/km in 2017. The relationship between the agricultural tax in Wallonia – which is applied at a farm level on the effects on water resources from livestock and land cultivation – and GHG emissions is much less clear.

Revenue generation and use

Data availability on revenue generated by these schemes varies. In all cases, a key element has been that revenues are either directly recycled back to citizens or are offset in other parts of the budget. This has occurred via direct payments/rebates to households or implementing other tax cuts alongside the lever.

The British Columbia carbon tax was designed to be revenue neutral and so was implemented alongside a wider scheme of tax cuts, and is now part of the Canadian Federal approach, which gives direct payments back to households. In 2019, SEK 22.2 billion was generated via the Swedish carbon tax, which is approximately 1% of Sweden’s total tax revenue. The carbon tax revenue goes into the overall government budget, and is not hypothecated, thus it is unclear where the revenue generated is distributed (Jonsson, Ydstedt, & Asen, 2022). The Austrian nETS was implemented as part of a wider policy package. Although revenue for the emissions allowances goes directly into the main budget and there is no hypothecation, ‘climate bonus’ payments are given directly back to households. Revenue in 2022 was approximately €800 million and the government have reallocated around €1 billion.

Since 2014, the Bonus Malus scheme has generated surplus revenue for the French general budget. For 2018, the malus was set at a level that covered the costs of the bonus payments (EUR 261 million) and the additional bonus for scrapped vehicles (EUR 127 million). The agricultural tax in Wallonia generates an annual revenue of around €1.2 million, however, it is unclear how this is subsequently used.

Behaviour change

There is some evidence on how the case study examples influence behaviour change. The carbon tax in British Columbia has been shown to have had a role in decreasing consumer demand for fossil fuels and natural gas (Pretis, 2022). Additional studies from Xiang and Lawley (2018) and Antweiler and Gulati (2016) also draw correlations between the implementation of the tax and a decrease in fuel demand.

The carbon tax in Sweden has shown to be effective in shifting market investment into low-carbon technology, specifically in renewable energy sources such as hydro and wind (Hildingsson and Knaggård, 2022). Levying the carbon tax at different rates on fuels has also resulted in behaviour changes in companies. Between 1993 and 1997, the higher tax rate on fuels used within domestic heating systems compared to fuels used within industry resulted in industries selling their by-products to domestic heating companies, while continuing to burn fossil fuels themselves (Johansson, 2000).

One interviewee suggested that the Austrian nETS, whilst in its fixed price stage, is not expected to generate a strong enough price signal to result in a clear and significant change in behaviour. However, other parts of the policy package have been designed to specifically change behaviour (such as subsidies for changing heating systems in households). The Bonus Malus scheme has had a clear impact on shifting vehicle sales in France towards less CO₂ intensive vehicles. However, the scheme may have a rebound effect, as the lower fuel expenditure for consumers due to more efficient vehicles may lead to an increase in vehicle use and thus in fuel consumed (and thus on emissions). There is no evidence regarding the behavioural effects of the agricultural tax in Wallonia.

Unexpected challenges

In British Columbia, the tax was initially designed without exemptions and applied universally. However, after competitiveness concerns were raised, the government introduced a one-time exemption worth $7.6 million in 2012, followed by an ongoing exemption in 2013 to greenhouse growers and an exemption for gasoline and diesel used in agriculture in 2014.

When implementing their nETS, the Austrian government experienced challenges designing the scheme around the existing EU ETS. To ensure that emissions were not double counted, exemptions from the national ETS were given to installations already regulated under the EU ETS. This proved a challenging exercise for the Austrian government.

Challenges have been observed for the proposed agricultural tax in New Zealand. Whilst these are political in nature, they have presented challenges for the implementing government. The original proposal for a split-gas, farm-level levy was revoked after a consultation highlighted public concerns about the impact on the cost and potential implications on availability of produce. A series of media outlets reported tensions between the agricultural sector in New Zealand and the government. Farmers expressed concerns regarding both the profitability and competitiveness of their business, with some expecting to have to reduce their herd size (Pannett, 2023). After revoking the original planned tax, the NZ government are now implementing mandatory monitoring and reporting of emissions from agriculture, to eventually transition into pricing of emissions.

Overview of fiscal levers in the UK

We investigated existing UK environmental fiscal levers, including taxes in the energy intensive industries, the power generation, transport, and pollution and resource sectors in Appendix B. We focused analysis on those that deliver reductions in GHG emissions. These include:

• Fiscal levers specifically targeted to reduce GHG emissions.
• Fiscal levers specifically targeted to address environmental impacts and affecting GHG emissions.

These were classified using the typologies developed in Section 3.1. Fiscal levers that do not contribute to reducing GHG emissions have not been considered. A complete list of environmental taxes in the UK (at time of writing) is in Section 8.1.4.

Existing fiscal levers which target or address GHG emissions focus on energy and energy intensive industries, transportation (road and air transport) and resource use. Examples include Fuel Duty, the Climate Change Levy (CCL), the Renewables Obligation (RO), the UK ETS, the UK Air Passenger Duty (APD), and the Vehicle Excise Duty (VED).

Under the current devolution settlement, most tax powers remain reserved to the UK Government and Parliament. However, any existing national tax can potentially be devolved to the Scottish Parliament. New national taxes can be created through a mechanism allowing the UK Parliament, with the consent of the Scottish Parliament, to grant powers for new national devolved taxes to be created in Scotland (Scottish Parliament, 2021).

Overview of fiscal levers in Scotland and implications of the case studies

Devolution is the statutory delegation of powers from the central government of a sovereign state to govern at a subnational level. It is a form of administrative decentralisation. Devolved territories have the power to make legislation relevant to the area, thus granting them higher levels of autonomy. In the UK, devolution is the term used to describe the process of transferring power from the centre (Westminster) to the nations and regions of the United Kingdom (Torrance, 2022). Devolution provides Scotland, Wales and Northern Ireland with forms of self-government within the UK. In the case of Scotland, this includes the transfer of legislative powers to the Scottish Parliament and the granting of powers to the Scottish Government. While the UK Parliament still legislates for Scotland, it does not do so for devolved matters without the consent of the Scottish Parliament.

The devolution process has led to calls for the Scottish Parliament to be given more responsibility over revenue raised and spent in Scotland. There are existing devolved environmental taxes under the Scottish Government’s remit that contribute to reducing GHG emissions. We have also considered implications of the case studies from a legal and regulatory perspective. No assessment is made of the potential costs and benefits of adoption nor of the practical challenges associated with them.

Legal and regulatory fiscal system in Scotland

The legislative framework for devolution to Scotland was originally set out in the Scotland Act 1998. The Scotland Act 1998 established the Scottish Parliament and set out the matters on which the Scottish Parliament cannot legislate and make laws, known as general and specific reservations. Everything not listed as a reserved matter is assumed to be devolved. Reserved taxation matters include VAT rates, Fuel Duty, and Corporation Tax. The Scottish Parliament currently has devolved responsibilities in relation to five taxes (Scottish Government (2021), as follows:

• Scottish Income Tax, which is partially devolved. It is collected and administered by HMRC on behalf of the Scottish Government.
• Land and Buildings Transaction Tax, a tax paid in relation to land and property transactions in Scotland, and Scottish Landfill Tax, a tax on the disposal of waste to landfill, are fully devolved national taxes and are managed and collected by Revenue Scotland.
• The Scottish Parliament also has powers over local taxes for local expenditure. Currently, the two main local taxes are Council Tax and Non-Domestic Rates (also known as business rates), which are collected by local authorities. Note that a review of local taxes is not covered in this study.

In addition, powers in relation to two further taxes have been devolved to the Scottish Parliament, but these have not yet been implemented and the relevant reserved taxes therefore continue to apply. These taxes are Air Departure Tax, a tax on all eligible passengers flying from Scottish airports, which will replace Air Passenger Duty when introduced, and a devolved tax on the commercial exploitation of crushed rock, gravel, or sand, which will replace the Aggregates Levy when introduced.

The Scottish Parliament has the power to create new local taxes (i.e. local taxes to fund local authority expenditure). There is also a mechanism allowing the UK Parliament, with the consent of the Scottish Parliament, to devolve powers for new national devolved taxes to be created in Scotland. This is unlikely to be a swift process and would likely depend on the complexity of the new national tax and negotiation over devolution of the requisite powers.

The UK Internal Market Act 2020 (IMA) seeks to prevent internal trade barriers among the four countries of the United Kingdom. Schedule 1, paragraph 11 of the IMA specifically exempts taxes (Legislation.gov.uk, 2020a). However, new regulatory acts considered to create additional administrative burdens which may affect intra UK trade may be challenged under the IMA.

Devolved fiscal levers to deliver reductions in GHG emissions in Scotland

The Commission on Scottish Devolution (also referred to as the Calman Commission), established in 2007, identified some taxes (including the Landfill Tax and the Air Passenger Duty) where devolved powers could be applied. Following this, the Scotland Act 2012 devolved powers for a Landfill Tax to the Scottish Parliament to cover landfills and transactions taking place in Scotland, which led to the Landfill Tax (Scotland) Act 2014. At the time of writing, this is the only fully devolved fiscal lever delivering reductions in GHG emissions that currently applies in Scotland.^[6] Although the Scotland Act 2016 included the power to introduce a devolved tax on the carriage of passengers by air from airports in Scotland (i.e. to replace the present, UK-wide Air Passenger Duty). The Air Departure Tax (Scotland) Act 2017 was passed by the Scottish Parliament 2017, however the introduction of the tax has been deferred due to state aid (and now subsidy control) issues. The Scotland Act 2016 Act also made provisions for the creation of a devolved tax on extraction of aggregates, which is currently being legislated for in the Scottish Parliament, although this does not specifically look to reduce greenhouse gas emissions.

Indirect Taxation Schemes

The Scottish Landfill Tax (SLfT) replaced the UK Landfill Tax in Scotland from 1 April 2015 under the Landfill Tax (Scotland) Act 2012. The SLfT is part of Scotland’s Zero Waste Scheme and aims to encourage the prevention, reuse and recycling of waste in the country. It is administered by Revenue Scotland with support from the Scottish Environment Protection Agency (SEPA). SLfT is a tax on the disposal of waste to an authorised or non-authorised landfill in Scotland. The taxation of disposals to unauthorised sites (that is illegal dumping) is a key difference between SLfT and UK Landfill tax.

The Scottish Government is responsible for setting the rates of the tax as part of the annual Scottish Budget and determining which waste is subject to it. The tax is paid on the disposal or unauthorised disposal of waste to landfill and is calculated based on the weight and type of the waste material. A standard rate of £102.10 per tonne is applied, while a lower rate of £3.25 per tonne is paid on less polluting (referred to as ‘inert’)^[7] materials. Tax revenues have decreased from £149 million in 2015-2016 to £125 million in 2021-2022. The SLfT has been a major part of the success in driving change in Scotland’s waste performance (Revenue Scotland, 2021).

Air Departure Tax (ADT). The Scotland Act 2016 included the power to introduce a devolved tax on the carriage of passengers by air from airports in Scotland. This allows Scotland to design a replacement for APD. The Air Departure Tax (Scotland) Act 2017 made provision for such a tax, which will be managed and collected by Revenue Scotland. However, the tax has not yet been introduced and UK APD continues to apply.

The Scottish ADT will tax flights departing from an airport in Scotland (this includes airports in the Highlands and Islands regions). As with the UK APD, the amount of tax payable depends on the destination of the passenger and the characteristics of the aircraft (take-off weight,^[8] flight distance seat pitch and seating capacity). Depending on the aircraft, the passenger will pay either the standard, premium or special rate.^[9] Certain flights and passengers are exempt from ADT. Exemptions apply to flights operated under a public service obligation, which may include many flights to/from small islands, although the Air Departure Tax (Scotland) Act 2017 making provision for such a tax does not mention any exemptions for passengers on flights leaving from airports in the Scottish Highlands and Islands. There are also exemptions for emergency medical service flights, military, training or research flights. Passenger exemptions apply to persons that are working during the flight, such as flight crew, cabin attendants, persons undertaking repair, maintenance, safety or security work, persons not carried for reward, such as Civil Aviation Authority flight operations inspectors, or children under the age of 16 (FCC Aviation, 2023).

ADT was originally expected to come into force on 1 April 2018. However, on April 2019 the Scottish Government deferred the introduction of ADT beyond April 2020 until issues have been resolved regarding the tax exemption for flights departing from airports in the Highlands and Islands regions. The devolution process is, thus, on hold. In the meantime, UK APD (and the rates and bands that currently exist) and the current Highlands and Islands exemption continues to apply.

Implications of the case studies for Scotland

We assessed whether the six case study examples (Section 3.7) could hypothetically be implemented by the Scottish Government under current devolved competencies. We also provide a high-level explanation of practical issues (e.g., target of the lever and groups affected). No assessment is made of the costs and benefits of adoption.

While the balance of evidence suggests that similar taxes have reduced GHG emissions where they have been applied elsewhere, the net effect on GHG emissions in the host jurisdiction is uncertain. Challenges in implementation have also been observed and there is limited detailed evidence on behavioural effects. These issues will need to be further investigated before any such tax could be considered for Scotland. If the Scottish Government were to consider exploring any of the examples we have looked at, it would be necessary to undertake thorough policy scoping, analysis and consultation, in addition to the agreement of both the UK and Scottish Parliaments. The Scottish Government could also consider these points in the context of its wider discussions with the UK Government on the direction of climate and fiscal policies as part of a collaborative approach.

Direct Carbon Tax

The UK CCL (which is in practice similar to direct carbon taxes in place in several countries or regions, including Sweden and British Columbia) could be devolved to the Scottish Parliament through an agreement between the Scottish and UK governments and parliaments on the transfer of powers.

A new Scottish carbon tax could then in theory replace the UK CCL in Scotland. This could be broadly similar to the UK CCL, although the Scottish Government could also make its own decisions on issues such as scope and rates to better align it with Scotland’s socioeconomic conditions and emissions reduction targets. Were the Scottish Government to consider such a measure, it would require significant exploration of options and detailed analysis to ensure it achieved these objectives, including consultation and engagement with stakeholders.

Emissions Trading System

The UK ETS is jointly operated by the Scottish Government, UK Government, Welsh Government and Northern Ireland Executive through the UK ETS Authority. It relies primarily on legislation that is devolved (the Climate Change Act), although parts of the ETS relating to auction processes are based on legislation that is more often considered reserved and, thus, relies on UK parliament.

A new ‘Scotland ETS’ could hypothetically replace the UK ETS. This would require prior consent of the UK Parliament, Welsh Parliament, and Northern Ireland Assembly to have effect, as well as the agreement of the Scottish Parliament. The agreement of the Scottish Parliament could be sought through new specific legislation (either primary or secondary). Thus, an Act of the Scottish Parliament to make provision about the functioning of the ETS in Scotland would be required. This could in theory cover additional sectors not covered by the UK ETS, similar to the Austrian nETS operating alongside the EU ETS. However, any such proposal would require comprehensive policy scoping and consultation, in addition to the need for agreement from each legislative body, as detailed above.

Bonus Malus Scheme for Vehicles

The UK VED (similar to the bonus malus scheme explained in Appendix D) paid by businesses and households could in theory be devolved to the Scottish Parliament. Thus the new Scotland VED would replace the UK VED through an agreement between the Scottish and UK governments and parliaments on the transfer of powers.

This could potentially allow for innovation, as differences are in principle permitted, as happened with landfill tax (the SLfT applies on the disposal of waste to both authorised and non-authorised landfills, whereas the UK landfill tax only applies to disposals to authorised sites). It could therefore be feasible to create bonuses to incentivise buyers to purchase low or zero emission vehicles (along the lines of the Bonus-Malus in France), which UK VED does not currently offer. However, this would require detailed policy scoping and consultation to ensure any potential measure operates fairly and effectively, as well as having the consent of both the UK and Scottish Parliaments.

Tax on agricultural emissions

Under Section 80B of the Scotland Act 1998 (as amended), a new tax on agricultural emissions similar to the tax on agricultural emissions proposed in New Zealand (for further details, see Appendix D) could in theory be created in Scotland as the UK Parliament can, with the consent of the Scottish Parliament, devolve powers for new national devolved taxes to be created in Scotland.

This tax might operate by putting a price on agricultural GHG emissions, for example, and could include farmers and growers who operate on Scottish territory, depending on their GHG emissions. The lessons learned from the example in New Zealand clearly demonstrate that consideration of any such measures would require rigorous policy design, consultation and close collaboration with stakeholders in the sector. Whilst new taxes can be effective in changing behaviours and reducing GHG emissions, there is an important and challenging balance to strike between protecting jobs and the viability of industries such as agriculture whilst also meeting net zero targets.

Conclusions

Of the various policies to mitigate the effects of climate change, the use of fiscal levers (taxes, levies, duties or charges) to reduce GHG emissions has gained increased attention and wider adoption by policymakers around the world. Different types of fiscal levers include emission trading schemes; carbon credit schemes; carbon border adjustment mechanisms; and carbon taxes. We focused on direct carbon taxes. Subsidies, grants and loans by the UK or Scottish Governments were not in scope.

International review of fiscal levers for GHG emissions

Use of carbon taxes is increasingly common. 37 direct carbon taxes are in operation in 27 jurisdictions globally. The majority are applied in high-income countries, particularly Europe. Scandinavian countries were among the earliest adopters. Many of these taxes have been applied alongside an ETS. There has been less use outside Europe to date. However, several jurisdictions are currently considering them.

Sub-national carbon taxes have been applied successfully: Of particular relevance to Scotland, two jurisdictions have applied carbon taxes sub-nationally: Canada, which has five, and Mexico, which currently has two with further instruments planned.

Existing instruments differ in terms of GHG coverage and carbon price: about 6% of global GHG emissions are taxed by carbon taxes. This share has increased significantly over the past 15 years. Existing instruments differ in scope, price and coverage. For example, Sweden has a ‘high ambition’ instrument and was one of the earliest adopters with the highest carbon tax globally. Other instruments have a mixed level of ambition e.g. high prices and low share (Uruguay) or high share but low prices (Singapore). Relatively low prices and shares include some Eastern European and South American states.

The balance of evidence suggests carbon taxes have reduced GHG emissions, with caveats. Despite the extensive literature on the merits of carbon taxation, actual data on their impact on GHG emissions is limited. Any assessment of impact is methodologically challenging, particularly in attributing GHG reductions to the specific tax. Effects of carbon leakage are rarely quantified, so estimates may overstate reductions in GHG emissions when taking a global view. Despite these challenges, the evidence indicates that carbon taxes have generally reduced GHG emissions in the relevant sector or jurisdiction. There is some limited evidence that carbon taxes perform better than ETSs in terms of GHG reduction, but both are likely to need additional regulatory measures to deliver the scale of decarbonisation necessary. The extent of reductions attributed to the taxes to date are not considered sufficient to meet broader climate goals.

Evidence on behavioural effects within affected sectors is more limited. The available evidence indicates that fuel switching or efficiency improvements may be more common responses than significant changes to manufacturing processes or technologies. Analysis of the Swedish carbon tax suggests some decreased demand for petrol was offset by increases for diesel but it was considered to have supported a shift in investment toward low-carbon technologies. It is not clear if responses were a result of the design of the tax or a reflection of prevailing prices and/or coverage.

Carbon taxes have generated government revenue but their magnitude depends on the design of the tax. The data contain some methodological and reporting inconsistencies, but 2013 information suggested revenues differed between some $3.5 billion (Sweden) and tens of million (Iceland). Data from 2019 show similar orders of magnitude, but the values for specific jurisdictions differ. The share of GDP represented by the taxes were all under 1% of national GDP at that time. By 2022 carbon tax revenues were upwards of $30 billion globally. Overall, revenues reflect the carbon price, as well as factors including the size of the economy, the coverage of the tax, exemptions, the carbon intensity of the jurisdiction and energy mix. The available evidence suggests that direct carbon taxes are relatively straightforward and inexpensive to administer for the host government.

Direct carbon taxes have involved extensive allocations of revenues for specific purposes. Many of the instruments for which data are available contained extensive allocations, as a percentage of revenue. These were often legally binding or via political commitment. Specific allocations include for green spending and particularly on specific rebates or tax cuts to affected groups, including low-income households and some businesses. British Columbia’s carbon tax was designed to be revenue neutral. In Sweden and Iceland, revenues are unconstrained and used to finance general government expenditure.

Implementation has been politically challenging. Australia is the only jurisdiction identified where an existing carbon tax was repealed. Repealing the tax became a central element of a successful opposition election campaign. Similarly, a planned acceleration of the carbon price was suspended in France as a result of widespread civil unrest, citing the perceived unfairness of the tax, having been introduced alongside tax cuts for the wealthy. A successful legal challenge was brought in Mexico over whether the regional government had legal authority to implement a subnational tax.

Potential implications for Scotland

Our high-level review of existing fiscal levers in the UK identified several existing taxes in the energy, transport and resource sectors which specifically target or address GHG emissions.

The Scotland Act 2012 (Section 80B) provides the Scottish Parliament with the power to devolve any existing national tax of any description to Scotland and create new national taxes such as on activities currently not taxed under the UK tax code. Any changes to existing taxes or the introduction of new taxes will require the agreement of the Scottish Parliament and the prior consent of the UK Parliament to have effect. Several of the case studies contain elements that are in practice similar to existing UK levies, but which would need amending if they were to be considered for Scotland.

Any new carbon tax could hypothetically be applied in Scotland, potentially as part of a devolved Scottish Climate Change levy. Similarly, a new ‘Scotland ETS’ could hypothetically replace the UK ETS, with adjustments in scope to incorporate additional sectors. This would require prior consent of the UK Parliament, Welsh Parliament and Northern Ireland Assembly, as well as the agreement of the Scottish Parliament. A devolved VED could theoretically replace the UK VED in Scotland. New national taxes could also be created in Scotland, requiring consent of both the UK and Scottish Parliaments. In each case, new Scottish legislation would be required.

Principles for implementation

This review has highlighted several fiscal levers used in other countries to reduce GHG emissions. Should any of these be explored further, Scotland’s Framework for Tax sets out the principles and strategic objectives that underpin the Scottish approach to taxation and any new measures (Scottish Government, 2021). These principles are:

• Proportionality: Taxes should be levied in proportion to taxpayers’ ability to pay and a fair system should reflect relative income or wealth of the taxpayer.
• Efficiency: Prospects for revenue should be balanced against the potential for unintended behavioural responses.
• Certainty: So that businesses and individuals can plan and invest with confidence, taxpayers must know what is to be paid, by whom and when.
• Convenience: Taxes should be collected in a way that maximises convenience for taxpayers. Policy should be simple, clear and straightforward and opportunities to streamline the tax system taken.
• Engagement: To ensure accountability and maintain trust, governments should consult as widely as possible on tax design.
• Effectiveness: Taxes should raise the expected revenues and achieve their intended aims. Opportunities for tax avoidance should be minimised.

As such, the effectiveness of any fiscal lever depends on the precise design of the lever and should be subject to careful consideration and clear communication in terms of its scope, phase-in, price (including future price escalation), sectors and activities on which it is levied and any relevant exemptions. Distributional effects should be carefully considered, including if and how revenue should be reallocated, to whom and under what conditions. challenges in implementation have been observed. Successful fiscal lever examples have been based on transparent design, regular monitoring and communication of revenues, costs and benefits, with rapid adjustments if unexpected adverse effects occur. Successful examples have also formed part of wider fiscal reforms, with a clear strategic objective.

Any potential instrument should be subject to detailed economic modelling, including testing different price rates and trajectories, an assessment of the risk of carbon leakage (with or without a UK CBAM), economic competitiveness and innovation effects, distributional effects (and potential mitigation via revenue reallocation), and any impacts on small and medium sizes businesses. This should be published in a robust Regulatory Impact Assessment to provide a comprehensive evaluation of any prospective measures, and ensure they adhere to the principles of the Framework for Tax while achieving GHG reductions through behavioural change.

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Appendices

Appendix A. Methodology

This section provides a more detailed overview of the methodology we used.

Literature review

First, we conducted a targeted literature review on fiscal levers used to reduce greenhouse gas emissions. We focussed on academic and grey literature sources using agreed search terms. These were: ‘fiscal levers’, ‘tax’, ‘levy’, ‘duties’, ‘charges’, ‘carbon tax’, ‘environmental tax’ ‘carbon pricing’, ‘carbon credits’ ‘greenhouse gas emissions’, ‘Net Zero’, ‘climate change’, ‘fiscal measures’, ‘environmental behaviours’, ‘behaviour change’, ‘dis/incentive’, ‘rural” & “island’, ‘revenues’, and ‘devolved’. We used Boolean operators e.g., AND/OR etc to create relevant search strings from these key words and to refine the search results. We used additional terms including ‘effectiveness of’, ‘review of’, ‘evaluation of’, ‘impact assessment of’ and ‘meta-review of’ to identify additional evidence for specific schemes once they had been identified.

We searched databases including PubMed, Web of Science All Databases and Scopus to identify relevant academic literature sources. We also looked for legislation as well as publications from national Governments, supranational organisations such as the European Commission or OECD as well as non-governmental organisations. The grey literature was identified via Google searches and searches of relevant government/organisation websites.

As we identified sources, we screened them using executive summaries or abstracts to ascertain their relevance and quality. If we decided the source was relevant and of sufficient quality, we logged them in a data source register, which was a live Excel document (stored on the project SharePoint site) that was available to all team members. We recorded the source details (title, author, year, source) and information on the contents of the publication, such as the type(s) of lever it discusses, geographical scope, relevance for GHG emissions as well as an indication of the methodological rigour, accuracy and robustness of the source. This ensured that we clearly documented the evidence, and that we could share resources efficiently across the project team. As part of this exercise, 36 sources were logged, informing the beginning of the more in-depth research undertaken for each individual case study.

As we logged the sources in the register, we undertook a secondary screening exercise of the lever examples – where specific examples were discussed – categorising them into an initial list of typologies. This also identified a ‘longlist’ of potential case studies of specific lever examples for more detailed analysis.

Case study selection

We shortlisted six case studies to be analysed in greater detail, from a long list of 12. The case study selection process was twofold. First, initial assessment during literature review stage of the project. While logging the data in the live excel sheet, we conducted a high-level assessment of the relevance of the identified fiscal levers to the Scottish context. Each case study was assigned a RAG rating based on an assessment against six criteria agreed with CxC and the Scottish Government. These criteria were:

• Population, economic structure and GDP: Countries/regions that with comparable population, GDP/GDP per capita and economic structure (i.e., size of manufacturing sectors, predominance of service sectors) were prioritised. This may include certain EU Member States, for example.
• Administrative and legal arrangements and competencies: Countries/regions with similar administrative arrangements (i.e., devolved competencies or instruments applied sub-nationally) were prioritised. Examples may include U.S. States, Australian territories or Belgian Regions.
• Shared challenges: Countries/regions with similar characteristics to Scotland, such as extensive peatland, rural/island communities or extensive renewable energy resources may provide valuable insight. This may include Ireland, Canada, Estonia, Sweden, Finland and Germany, for example.
• Climate ambition: Countries/regions with similar levels of ambition in terms of climate change mitigation should be prioritised. For example, those with net zero targets set out in national legislation.
• Diversity of approaches: Different levers and typologies should be covered in the case studies to allow for a comprehensive analysis.
• Data and evidence: Sufficient data and evidence on the lever and its effectiveness must be available to support case study analysis.

We then used this RAG rating to select the most relevant case studies, which were presented to the project steering group for agreement. The project steering group selected the final six case studies for the project. These case studies are contained in Appendix C.

Semi-structured interviews

To supplement the literature review, we conducted 7 semi-structured interviews of c.45 minutes via MS teams. In two cases, the interviewees requested to respond in writing. Two rounds of interviews were conducted.

We conducted the first round of interviews with experts who could offer an international perspective on the use of fiscal levers for greenhouse gas emission reductions. The purpose of these interviews was to gain expert input on the global picture, to ensure that sound case study options had been selected and to ensure that the project team was aware of all available evidence. We held interviews with Stefano Carattini, an academic specialising in carbon taxation worldwide, Ian Parry an expert from the IMF and Professor Lorraine Whitmarsh, an academic specialising in behavioural change in the face of environmental legislation and carbon taxation.

The second round of interviews aimed to gain more targeted information about specific case studies in the relevant jurisdictions. We aimed to obtain evidence on the effectiveness of the fiscal levers and fill in any data gaps that had persisted after the literature review. These interviews included civil servants working on the policy in the relevant governments where these could be identified, as well as academics with the required expertise working in the relevant countries. We were able to arrange interviews with experts from four out of the six case studies analysed in this study. Experts in British Columbia, Austria, Wallonia and Sweden were consulted. Difficulties related to recent elections, and the early nature of the implementation of the tax in New Zealand meant that no civil servants were available to contribute to our study in this jurisdiction. In France, the expert we contacted rejected our interview request, based on the time which had elapsed since the individual was involved with that instrument. We were satisfied with the amount of information publicly available regarding the Bonus Malus scheme, however.

We provided each interviewee with an interview guide in advance of the interview. The guide included a letter of introduction on the project and a short project briefing note, an interview consent form, detailing how the information would be used and stored (in accordance with GDPR). We requested that each interviewee signed and returned the form in advance of the interview. We recorded the interviews, subject to interviewee consent, and stored their data securely. The recordings were used to create meeting notes which were agreed by both the interviewee and the interviewer.

Fiscal levers in the UK and Scotland

We first identified existing environmental fiscal levers in the UK (including taxes in the energy, transport and pollution/resource sectors). The main source of information was the Office of National Statistics (ONS). The UK environmental taxes annual bulletin from the ONS shows the value and composition of UK environmental taxes, by type of tax and economic activity. These levers were:

• Environmental taxes in the energy sector include the following: Tax on Hydrocarbon oil; Climate Change Levy; Fossil Fuel Levy; Gas Levy; Hydro-Benefit; Renewable Energy Obligations; Contracts for Difference;) UK Emissions Trading Scheme; Carbon Reduction Commitment
• Environmental taxes in the transport sector include the following: Air Passenger Duty; Rail Franchise Premia; Vehicle Registration Tax; Northern Ireland Driver Vehicle Agency; Fuel Duty; Vehicle Excise Duty (VED) paid by businesses; VED paid by households; Boat Licenses; Air Travel Operators Tax; Dartford Toll
• Pollution Resources taxes include the following: Landfill Tax; Fishing Licenses; Aggregates Levy; Plastic Packaging Tax.

As the focus of our assignment is on fiscal levers to deliver reductions in GHG emissions, we focused our analysis on those that deliver reductions in GHG emissions. These include:

1. Fiscal levers specifically targeted to address environmental impacts and affecting GHG emissions.
2. Fiscal levers specifically targeted to reduce GHG emissions.

The Rail Franchise Premia (premium paid by train companies to UK government to provide specified train services), the Boat Licenses (annual charge required by owners of boats who use or keep their boats on inland waterways in the UK), the Air Travel Operators Tax (an insurance scheme ran by the UK Civil Aviation Authority), the Dartford Toll (toll for motorists to use the Dartford Crossing), the Fishing Licenses (required to fish for certain species of fish in various locations across the UK), the Aggregates Levy (a tax on sand, gravel or rock that has been dug from the ground, dredged from the sea or imported into the UK), and the Plastic Packaging Tax (on finished plastic packaging components containing less than 30% recycled plastic) have not been considered in our analysis. These taxes do not contribute to reducing GHG emissions, either directly or indirectly. The Contracts for Difference and the Vehicle Registration Tax have not been considered either. The Contracts for Difference offers generators a contract with a known strike price for renewable electricity sold and, thus, it is considered a subsidy and not a tax. The Vehicle Registration Tax is a tax on vehicle registration in the UK.

For taxes covered in our assessment (Tax on Hydrocarbon oil (Fuel Duty); Climate Change Levy^[10]; Gas Levy; Hydro-Benefit; Renewable Energy Obligations; UK Emissions Trading Scheme^[11]; Carbon Reduction Commitment; Air Passenger Duty; VED paid by businesses; VED paid by households and the Landfill Tax), we conducted a literature review of several academic and grey literature sources that reported information. This related to the following issues: objective of the tax, revenue generated, year of introduction, what is taxed and how tax is collected. This provided a good background overview.

Within the UK, the devolution process has led to calls for the Scottish Parliament to be given more responsibility over revenue raised and spent in Scotland. Following the review of existing UK taxes, the next step has been to look at the environmental taxes under the Scottish Government’s remit that contribute to reducing GHG emissions.

The devolution process was examined. This includes Section 80B of the Scotland Act 1998 (as amended), which devolves powers to add new national taxes in Scotland with the agreement of the Scottish Parliament. It also includes the Calman Commission, which supported the principle of devolution and identified some taxes (Stamp Duty Land Tax, Landfill Tax, the Aggregates Levy and Air Passenger Duty, and elements of Income Tax) where devolved powers could be applied. We reviewed the current legal framework and identified existing environmental fiscal levers in Scotland with an impact on GHG emissions where this devolution process has been applied. This only includes the Scottish Landfill Tax, which was devolved to the Scottish Parliament following the Scotland Act 2012 and replaced Landfill Tax on transactions taking place in Scotland. The Air Departure Tax (Scotland) has also been reviewed following the Scotland Act 2016. According to this Act, Air Passenger Duty is due to be fully devolved to Scotland and to be replaced by Air Departure Tax. However, this devolution process is currently on hold until a solution can be identified that protects Highland and Island connectivity and complies with UK subsidy controls.

For the devolved taxes (this includes the Scottish Landfill Tax and the (Scottish) Air Departure Tax, even though the latter is still on hold) we conducted a literature review of academic and grey literature sources that reported information related to the following issues: objective of the tax, revenue generated, year of introduction, what is taxed and how tax is collected. A brief description of the levy/tax is presented, including, depending on the availability of official data, the rates applied, the taxable event, the taxable person and other additional considerations.

Finally, we examined whether the six case study examples could be implemented by the Scottish Government under current devolved competencies, or whether their adoption would require joint action by the UK Government. This was carried out with reference to two key legislative acts. First, the Scotland Act 1998 that established the Scottish Parliament and gave it the power to legislate on certain matters, including certain elements of taxation. Second, Scotland Act 2012 (which amends the Scotland Act 1998) and gives the Scottish Parliament the power to (a) create new taxes in Scotland (such as on activities currently not taxed under the UK tax code) and (b) devolve any tax of any description with the prior consent of the UK Parliament (in addition to fully devolve the power to raise taxes on waste disposal to landfill).

Appendix B. Fiscal levers to deliver reductions in GHG in the UK

Direct taxation schemes

Tax on Hydrocarbon oil (or Fuel Duty)

Fuel Duty is charged on the purchase of petrol, diesel and a variety of other fuels. It is levied per unit of fuel purchased and is included in the price paid for petrol, diesel and other fuels used in vehicles or for heating. The rate depends on the type of fuel, as follows (Office for Budget Responsibility, 2023):

• The headline rate on standard petrol, diesel, biodiesel and bioethanol is 52.95 pence per litre.
• The rate on liquefied petroleum gas is 28.88 pence per kilogram.
• The rate on natural gas used as fuel in vehicles is 22.57 pence per kilogram.
• The rate on fuel oil burned in a furnace or used for heating is 9.78 pence per litre.

In 2022, Fuel Duty revenue was £24.8 billion. It is the largest environmental tax, comprising 52.5% of environmental taxes and 70.2% of energy taxes in 2022 (Office for National Statistics 2023). Data for Scotland is not reported.

Climate Change Levy (CCL)

This levy was introduced by the UK Government in April 2001. It is an environmental tax charged on the energy used by businesses to encourage them to become more energy efficient, while helping to reduce their overall emissions. By 2022, the tax generated revenues of more than £2 billion in the UK (Office for National Statistics, 2023). Data for Scotland indicates that the share collected in Scotland was between 8 and 9% from 2001 to 2019. Revenues collected in Scotland reached £158 million in 2018-2019.

Specifically, the tax applies to four groups of energy products: electricity; coal and lignite products; liquid petroleum (LPG); and natural gas when supplied by a gas utility. The CCL is paid via two rates: the main levy rate (for energy suppliers) and the carbon price support rate (for electricity producers). The CCL must be declared (via submission of a Climate Change Levy return to HMRC) and paid every three months, although small businesses can apply to make annual returns instead of quarterly returns.

Main levy rate

The main levy rate is applied to companies in the industrial, public services, commercial and agricultural sectors, and according to their consumption of electricity, gas and solid fuels (e.g., coal, coke, lignite or petroleum coke). Energy suppliers are responsible for charging the correct levy to their customers (SEFE Energy, 2023).

The levy rate varies for each category of taxable commodity, according to energy content: kilowatt-hours (kWh) for gas and electricity; and kilograms for all other taxable commodities. The rates do not apply to domestic consumers and charities for non-business use. There are also reduced rates for energy consumers that hold a climate change agreement (United Nations, 2012). Climate change agreements (CCA) are voluntary agreements made between UK industry and the relevant Environment Agency to reduce energy use and CO₂ emissions. CCAs are available for a wide range of industry sectors from major energy-intensive processes such as chemicals and paper to supermarkets and agricultural businesses such as intensive pig and poultry farming.

Carbon price support rate

Carbon price support rates apply to owners of electricity generating stations and operators of combined heat and power stations. They become liable for the carbon price support rate when (a) gas passes through the meter at the registration station and or (b) LPG, coal and other solid fossil fuels are delivered through the entrance gate at the generation station. Electricity generators are responsible for measuring, declaring and paying the correct carbon price support rate.

Renewable Energy Obligations

The Renewables Obligations (RO) were introduced in April 2002 in Great Britain, and in 2005 in Northern Ireland, with the aim of increasing the use of renewable energy to help reduce GHG emissions. Revenue from the tax has increased since its introduction, reaching £6.6 billion in 2022 (Office for National Statistics, 2023). Disaggregated data for Scotland is not reported.

This scheme requires electricity suppliers to generate a certain proportion of electricity from renewable sources. It imposes an annual obligation to present to the Office of Gas and Electricity Markets (OFGEM) a specified number of Renewables Obligation Certificates (ROCs) per megawatt hour (MWh) of electricity supplied to their customers during each obligation period. Suppliers can therefore comply with their obligation in two ways: buying and then redeeming ROCs or paying a buy-out price to OFGEM. The energy must be generated in the UK to qualify for ROCs and the eligible renewable sources include landfill gas, sewage gas, hydro (20MW or less), onshore wind, offshore wind, biomass (agricultural and forestry residues), energy crops, wave power and photovoltaics.

The government sets the RO obligation each year based on predictions of the amount of electricity that will be generated in the UK and the number of ROCs that OFGEM will issue to eligible renewable generators. This obligation level is published at least six months before the start of each obligation period, which runs from April 1 through March 31 (Office of Gas and Electricity Markets, 2023).

Carbon Reduction Commitment (CRC)

The CRC was introduced in 2010 to improve energy efficiency and reduce carbon dioxide emissions in private and public sector organisations that are high energy users, although it was closed in 2019. In the years that the tax was in force, the revenue collected ranged from £0.2 billion to £0.7 billion (Office for National Statistics, 2023).

Organisations that met the qualification criteria were required to participate and purchase allowances for every tonne of carbon emitted. For example, the scheme included supermarkets, water companies, banks, local authorities and all central government departments. Participating organisations were required to monitor their energy use and report annually on their energy supply. The Environment Agency’s reporting system then applied emission factors to calculate participants’ CO₂ emissions based on this information. Participants were then required to purchase and surrender allowances for their emissions (UK Government, 2023d).

Emission trading schemes

UK ETS

The UK ETS was established on 1 January 2021. It replaced the EU ETS following the UK’s exit from the EU. The scheme revenue was £4.3 billion in 2022 (Office for National Statistics, 2023).

The UK ETS covers energy-intensive industries, power generation and aviation. For aviation, the routes covered by this scheme include UK domestic flights, flights between UK and Gibraltar, flights between Great Britain and Switzerland, and flights departing the UK to European Economic Area states, conducted by all aircraft operators, regardless of nationality. For installations, the UK ETS applies to regulated activities that result in GHG emissions (except installations whose primary purpose is the incineration of hazardous or municipal waste). Activities in scope are listed in Schedule One (aviation) and Schedule Two (installations) of the in the Greenhouse Gas Emissions Trading Scheme Order 2020 (Legislation.gov.uk, 2020). The scope of the scheme is set to expand to include more high-emitting areas. It will be applicable to large maritime vessels of 5,000 gross tonnage and above from 2026. From 2028, it will also include waste incineration and energy generated from waste.

Installations with combustion activity below 35MW rated thermal capacity (small emitters), installations with emissions of less than 2.500t CO₂e per year (ultra-small emitters) and operators that provide services to hospitals can opt out of the UK ETS. Instead of having to obtain allowances and thus having allowance surrender obligations, these installations will be subject to emissions targets. However, they will be required to monitor their emissions and notify the regulator if they exceed the threshold.

Free allocation of allowances to eligible installation operators and aircraft operators is maintained to reduce the risk of carbon leakage for UK businesses (UK Government, 2023c). The maximum number of free allowances was set at around 58 million in 2021 (approximately 37% of the 2021 cap) and will decline by 1.6 million allowances per year (ICAP, 2022). Eligible installations must submit a verified Activity Level Report. If the data in the Activity Level Report shows an increase or decrease in activity of 15% or more from historical activity levels, their free allocation will be recalculated. Specific data for Scotland has not been reported.

Free allocations will be made available for operators of eligible installations who applied for a free allocation of allowances for the 2021 to 2025 allocation period and for new entrants to the UK ETS. The free allocation will also apply to the allocation period 2026 to 2030, although free allocations are intended to reduce over time. From 2026, flight operators and aviation businesses will need to buy allowances for every tonne of carbon they emit.

Indirect taxation schemes

Air Passenger Duty (APD)

UK APD is a tax levied on airlines based on the number of passengers carried when departing from a UK airport. It was introduced in 1994 to raise funds for the government and to regulate larger aircraft, but over the years it has become an important environmental tax. The amount of APD is based on the distance travelled and the class of service. There are four different pricing bands. Pricing as of April 2023^[12] is:

• For domestic flights (only within England, Scotland, Wales and Northern Ireland), the APD is £6.50 in economy, and £13 in a premium cabin.
• For international flights of up to 2,000 miles (short haul), the APD is £13 in economy, and £26 in a premium cabin.
• For international flights of 2,001 to 5,500 miles (long haul), the APD is £87 in economy, and £191 in a premium cabin.
• For international flights of more than 5,500 miles (ultra long haul), the APD is £91 in economy, and £200 in a premium cabin.

This tax does not apply to flights to the UK, as it is a departure tax only, nor to children under the age of 16 (OMAAT, 2023). Passengers carried on flights leaving from airports in the Scottish Highlands and Islands region are exempt, but passengers on flights from other areas of the UK to airports in Scotland are not. As with other environmental taxes, the government’s revenue from the APD has increased over time. Although it declined between 2020 and 2021 due to restrictions placed on air travel during the COVID-19 pandemic, it reached £2.9 billion in 2022 (Office for National Statistics, 2023). According to HM Revenue & Customs, UK APD collections from Scotland have been over 9% since 1999 and over 10% since 2018, amounting to over £380 million in 2022.

Vehicle Excise Duty (VED)

This is paid by businesses and households as a tax levied on vehicles using public roads in the UK. It is payable annually by owners of most types of vehicles, collected by the Driver and Vehicle Licensing Agency. The amount of VED depends on the year of registration of the vehicle: before or after 1 April 2017, or before 1 March 2001. Further changes will come into effect in April 2025, affecting new and existing electric vehicles.

For cars registered before 1 March 2001 the excise duty is based on engine size. Vehicles with an engine size < 1549 cc pay £180 (single annual payment), while vehicles with an engine size > 1549 cc pay £295 (single annual payment). For vehicles registered between 1 March 2001 and 31 March 2017 a standard rate between £0 (up to 100 g/CO₂/km, which includes hybrid vehicles) and £630 (Over 255 g/CO₂/km) is charged based on theoretical CO₂ emission rates per kilometre. The standard rate is only paid in the year the vehicle is first registered.

For vehicles registered from April 2017 onwards, VED are paid every year. First-year VED payments are based on theoretical CO₂ emission rates per kilometre and are in the range between £0 (up to 0 g/CO₂/km, which does not include hybrid vehicles) and £2000 (Over 255 g/CO₂/km). Drivers of Ultra Low Emission Vehicles (ULEVs) are particularly incentivised as they pay zero VED. Drivers of relatively fuel-efficient petrol or diesel cars (up to 10g/km CO₂) pay up to £10 for the year of initial registration (depending on the car’s official CO₂ emissions), while drivers of less fuel-efficient cars pay up to a maximum of £2,000. For the second year and beyond, most drivers pay a fixed flat rate of £140 regardless of their vehicle’s CO₂ emissions (except for zero-emission cars which pay zero). Apart from the payment period, the biggest changes from April 2017 are that hybrid vehicles are no longer rated at £0 and that cars with a retail price above £40,000 will pay a £310 supplement for years 2 to 6. The reformed VED system retains and strengthens the CO₂-based first year rates to incentivise uptake of the very cleanest cars whilst moving to a flat standard rate.

Electric vehicles (EVs) are currently exempt and drivers of EVs pay no VED. However, from 2025 EVs first registered on or after 1 April 2017 will be liable to pay the lower rate in the first year and the standard rate from the second year of registration onwards. This also applies to zero emission vans and motorcycles (Office for Budget Responsibility, 2023).

Landfill tax

The landfill tax was introduced in the UK in October 1996 to encourage recycling and increase the use of reusable materials. Since its introduction, the amount of waste sent to landfill has fallen by 60%. The tax applies to all waste disposed at a licensed landfill site unless the waste is exempt. It is charged by weight and there are two charge rates: a lower rate for ‘inactive waste’, such as rocks or soil, currently £3.25 per tonne, and a standard rate for all other waste, currently £102.10 per tonne. Rates are updated by the UK Government annually and come into effect on 1 April each year.

The landfill tax is paid by the operators or owners of landfill sites, who often pass on the costs to waste producers such as companies or local authority. Households are not required to pay landfill tax directly as local councils and authorities are responsible for the disposal of household waste. However, the cost may be further passed on to households that end up paying it indirectly via their council tax bill.

In 2022, the UK government raised £0.8 billion from the landfill tax (Office for National Statistics, 2023). The revenue is used for a variety of purposes, including supporting environmental projects and programs (Business Waste, 2023). According to HM Revenue & Customs, Scotland’s share of the total collected by the UK Landfill Tax was 13% in 2014-2015 (the tax was devolved to Scotland in 2015), amounting to a collection of £0.15 billion.

Appendix C. Supplementary data

Figure 8.1: Share of GHG emissions covered, as of March 2023 (World Bank 2023c)

Figure 8.3: An overview of global carbon credit issuance (World Bank 2023c)

Notes:

1. natural gas carbon tax, mineral oil tax and solid fuel carbon tax, data from 2012
2. domestic consumption tax on energy products (carbon dioxide), data for 2014 and reflects a partial year
3. Carbon tax on carbon of fossil fuel origin

Appendix D. Case studies

For all case studies, RAG rating for similarities to Scotland denoted red [R], amber [A] and green [G].

Case study 1

Lever type: Direct Carbon TaxJurisdiction: British Columbia, Canada

Case study 2

Lever type: Direct Carbon TaxJurisdiction: Sweden

Case study 3

Lever type: National ETS (nETS)Jurisdiction: Austria

Case study 4

Lever type: Proposed tax on agricultural emissionsJurisdiction: New Zealand

Case study 5

Lever type: Indirect tax (Bonus Malus scheme)

Jurisdiction: France

Case study 6

Lever type: Indirect tax (Environmental impacts of farming)Jurisdiction: Wallonia, Belgium

© The University of Edinburgh, 2024
Prepared by Logika Group and Metroeconomica 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, 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.

1. 
   

   Official data indicate that between 2013 and 2020, the increase was less than 1%, but 2020 emissions were affected by the restrictions associated with the COVID-19 pandemic. A more accurate comparison of underlying trends may be between 2013 and 2018, where global GHG emission increased by just under 5%. ↑

   
   
2. 
   

   Note the evidence in this paper was drawn from peer reviewed academic research and grey literature published since 2000. The review focussed on emission reduction evidence, it did not consider the balance of costs and benefits, technological innovation or issues associated with equity, for example. It excluded national evaluation reports, reflecting the diversity in methodological approaches and a potential lack of independence in these sources. The latter critique is questionable, as third parties often conduct them. Our secondary review has also not identified such evaluations, which is an acknowledged limitation of the review. ↑

   
   
3. 
   

   Defined as levies applied downstream to the emission of carbon dioxide and other GHGs or upstream to the sale of carbon intensive fuels. ↑

   
   
4. 
   

   Note the two figures are not directly comparable, the 2016 review is based on a selection rather than an overall estimate of total revenues. Moreover, the two studies appear to use different definitions of “carbon taxes” and for example do not appear to treat e.g., fuel/excise taxes in the same way. ↑

   
   
5. 
   

   £30,793 in 2021, converted to US dollars for consistency in jurisdictions, using the average exchange rate for 2021 of 1.3757. Source: https://www.exchangerates.org.uk/GBP-USD-spot-exchange-rates-history-2021.html ↑

   
   
6. 
   

   i.e., it is managed, and revenues are collected by Revenue Scotland. In this context, partially devolved, is where instruments are managed and revenues collected by HMRC on behalf of the Scottish Government. ↑

   
   
7. 
   

   Defined by the European Environment Agency as wastes that do not undergo any significant physical, chemical, or biological transformations when deposited in a landfill. ↑

   
   
8. 
   

   The maximum mass at which the aircraft is certified for take-off due to structural or other limits ↑

   
   
9. 
   

   The special rate applies to business jets with a take-off distance weight (MTOW) of more than 20 tons and a maximum seating capacity of less than 19 passengers. The Scottish standard rate applies if the aircraft does not qualify for the special rate and the seat pitch does not exceed 1,016 meters. Otherwise, passengers will be charged the premium rate. ↑

   
   
10. 
    

    Prior to the introduction of the Climate Change Levy, a Fossil Fuel Levy introduced in 1990 existed. The tax was paid by suppliers of electricity from non-renewable energy sources and ended following the introduction of the Climate Change Levy. ↑

    
    
11. 
    

    The United Kingdom Emissions Trading Scheme replaced the European Union Emissions Trading Scheme in 2021 following the UK’s exit from the EU. ↑

    
    
12. 
    

    Up to 31 March 2023, there were 2 destination rate bands ↑

    
    
13. 
    

    Based on the 2020 annual average exchange rate of CAD 1.7202 to 1 GBP. https://www.exchangerates.org.uk/GBP-CAD-spot-exchange-rates-history-2020.html ↑

    
    
14. 
    

    £30,793 in 2021, converted to US dollars for consistency in jurisdictions, using the average exchange rate for 2021 of 1.3757. Source: https://www.exchangerates.org.uk/GBP-USD-spot-exchange-rates-history-2021.html ↑

    
    
15. 
    

    Air and climate – Air and GHG emissions – OECD Data ↑

    
    
16. 
    

    Information obtained during the case study expert interview phase of the stakeholder consultation ↑

    
    
17. 
    

    Information obtained during the case study expert interview phase of the stakeholder consultation ↑

    
    
18. 
    

    Information obtained during the case study expert interview phase of the stakeholder consultation ↑

    
    
19. 
    

    https://www.seedyourfuture.org/greenhousegrower#:~:text=A%20greenhouse%20grower%20specializes%20in%20growing%20plants%20in%20a%20greenhouse%20environment ↑

    
    
20. 
    

    £30,793 in 2021, converted to US dollars for consistency in jurisdictions, using the average exchange rate for 2021 of 1.3757. Source: https://www.exchangerates.org.uk/GBP-USD-spot-exchange-rates-history-2021.html ↑

    
    
21. 
    

    £30,793 in 2021, converted to US dollars for consistency in jurisdictions, using the average exchange rate for 2021 of 1.3757. Source: https://www.exchangerates.org.uk/GBP-USD-spot-exchange-rates-history-2021.html ↑

    
    
22. 
    

    Information obtained during the case study expert interview phase of the stakeholder consultation ↑

    
    
23. 
    

    Information obtained during the case study expert interview phase of the stakeholder consultation ↑

    
    
24. 
    

    Information obtained during the case study expert interview phase of the stakeholder consultation ↑

    
    
25. 
    

    Information obtained during the case study expert interview phase of the stakeholder consultation ↑

    
    
26. 
    

    Information obtained during the case study expert interview phase of the stakeholder consultation ↑

    
    
27. 
    

    £30,793 in 2021, converted to US dollars for consistency in jurisdictions, using the average exchange rate for 2021 of 1.3757. Source: https://www.exchangerates.org.uk/GBP-USD-spot-exchange-rates-history-2021.html ↑

    
    
28. 
    

    Provisional data ↑

    
    
29. 
    

    £30,793 in 2021, converted to US dollars for consistency in jurisdictions, using the average exchange rate for 2021 of 1.3757. Source: https://www.exchangerates.org.uk/GBP-USD-spot-exchange-rates-history-2021.html ↑

    
    
30. 
    

    Fiscal horsepower is a unit indicating the tax burden on a vehicle. In the past it was related to engine power, hence this measure is also referred to as “fiscal power”. In Spain, for example, it is usually obtained from the engine capacity. In France, the calculation is different: since July 1998 (Article 62 of Law n°98-546 of 2 July 1998), the fiscal power depends on the standardised CO₂ emission value in g/km and the maximum engine power in kW. ↑

    
    
31. 
    

    £30,793 in 2021, converted to US dollars for consistency in jurisdictions, using the average exchange rate for 2021 of 1.3757. Source: https://www.exchangerates.org.uk/GBP-USD-spot-exchange-rates-history-2021.html ↑

    
    

Research completed March 2024

DOI: http://dx.doi.org/10.7488/era/5316

Executive summary

Background

The Scottish Government’s Climate Change Plan Update (CCPu) sets out an ambition for the agriculture sector to reduce emissions by 31% from 2019 levels by 2032, and a commitment to “work with the agriculture and science sectors regarding the feasibility and development of a SMART target for reducing Scotland’s emissions from nitrogen (N) fertiliser.”

The agricultural sector is dependent on N inputs, both organic and inorganic. The inefficient use of these inputs creates N wastage, impacting air and water quality and the climate. The global nature of the issue provides an opportunity for Scottish agriculture to learn from other countries on how to improve Nitrogen Use Efficiency (NUE), i.e. taking action to reduce agricultural N losses while maintaining and supporting the sector in terms of income and yield.

This report explores the potential for setting a NUE target for agriculture in Scotland. It examines N flows found in Scottish agriculture as shown in the Scottish Nitrogen Balance Sheet (SNBS), providing a clear analysis of the opportunities and barriers.

Key findings

Whilst there is theoretical potential for setting a NUE target for Scotland, there are practical obstacles that policy makers would need to overcome for the target to be implemented.

This research argues sector specific NUE values are not currently feasible due to the calculation set-up in the SNBS and the assumption that production will remain stable, with only inputs decreasing.

• We suggest that the SNBS calculations need refinement to attribute flows of N to the different measures and sectors. In the current version of the SNBS, the NUE calculations do not align directly with what happens in practice because there are overlaps and movements of N flows between the different agricultural sectors.
• These are not easily viewed in isolation and not necessarily attributed to the correct sector. For example, mitigation measures around manure management will, in practice, be mainly implemented by the livestock sector but will, in the current calculations, be attributed to the arable sector because they are linked to reduced emissions from spreading of organic matter to soils.

Opportunities

• The SNBS would offer an effective data source for setting and monitoring progress towards a single nationwide NUE target that covers all sectors.
• Many mitigation measures with known impacts on reducing N waste and improving N use are already in use in Scotland. Measures with the greatest potential improvement on NUE are
• nitrification inhibitors
• improving livestock nutrition, and
• improving livestock health.
• Note – that the improvement reflects implementing the relevant measure individually and does not consider any combination effects or interactions with other measures.
• The lowering of N-related emissions through reaching a NUE target will positively contribute to other emission reduction targets and the potential for an increase in farm business profitability.

Barriers

• Since a sector specific NUE target is currently not feasible, the remaining option is a single nationwide target.
• However, the arable, horticultural and livestock sectors would need to implement distinct mitigation measures, start from differing baselines, and will react inconsistently to implemented changes. This is partially due to the current limitations in the SNBS, but also due to the much lower baseline of current NUE values, setting a nationwide NUE target might cause the livestock sector to feel unfairly targeted.
• Some mitigation measures require significant capital expenditure to implement.
• The concept of NUE is complex and clear communication is required to ensure that targets and measures are clearly understandable and achievable to generate support from the farming sector.
• We examined different scenarios to model a potential target. The table below shows an achievable target and one that is more ambitious. The 2045 (Ambitious) scenario is based on transformational change across the sector.

• No country currently uses a standalone NUE target. Several countries have set N-related targets, some of which include information on NUE. Notably, the Colombo Declaration represents the first time that governments are collaborating on a global N management target on N waste.

Conclusions and recommendations

While this research identified opportunities for setting a NUE target for Scottish agriculture, more work is needed to fully understand the following elements:

• differential flows for each sector
• make appropriate changes to the SNBS
• ensure that the role of legumes in emissions reduction is fully integrated and
• carefully plan communication to achieve support from the farming sector.

A NUE target is not currently the most appropriate option for Scotland. This is partially due to the methodology in the current SNBS.

Recommendations

• Explore the potential for a more granular breakdown, and accurate representation of N flows in the SNBS. This may be difficult but would significantly help both monitoring and setting of a SMART NUE target.
• Creating a NUE target requires considering several criteria including mitigation measures, current uptake, applicability, expected future uptake, timescales, and sector breakdown. It is important to understand that other agricultural practices may impact N flows, as will changes in the size of agricultural sectors, and achieving these targets in practice will require supporting instruments to encourage the uptake of these measures. This research recommends that:
• N waste be considered as a target instead of a NUE target and that a SMART analysis is carried out to explore a N waste target further. Opportunities for setting a N waste reduction target include:
• It is an easier concept to communicate to the farming community.
• It values any N as a resource until it is lost as waste, creating options for greater collaboration between the arable, horticulture and livestock sectors. Any potential bias towards a sector will be avoided.
• A N waste target would achieve reductions in national NUE thereby achieving the same objectives without the current issues around NUE targets.
• Experience of the United Nations Environment Assembly and the Green Deal’s Farm to Fork targets has shown more potential in successfully reducing N pollution when focusing on reducing N waste over NUE targets as a policy option.
• If a decision is made to set a NUE target, the underlying assumptions should first be updated based on latest available evidence, for example using the updated Up to date Farm Census data. would strengthen any underlying assumptions and may directly influence the potential for the mitigation measures, particularly relating to slurry and manure management.
• The SNBS be improved by assigning distinct N flows to N waste and N re-use. A SMART target analysis for N waste will be beneficial to set a challenging and realistic target.

Glossary / Abbreviations table

Table 1: Glossary/ abbreviations table

Introduction

Nitrogen and its relevance to agriculture

Crops require nitrogen (N) to maximise growth. Most crops take up N from the soil in the form of nitrate (NO₃-). NO₃– in soils come from three major sources, the application of organic livestock manures, the application of inorganic N fertilisers and nitrogen fixing plants such as legumes. During harvest and through grazing, N is removed from the system. N can also be lost from soil through NO₃– leaching and through emissions of ammonia (NH₃) and nitrous oxide (N₂O). The N cycle (Figure 1) shows how different forms of N flow through the agricultural system.

Figure 1: The Nitrogen Cycle

An excess of N can both directly and indirectly lead to soil, water and air quality deterioration which is detrimental to human and ecosystem health (e.g., affecting respiratory systems and reducing oxygen in water). According to the IPCC AR5 Synthesis Report, N₂O has a global warming potential (GWP) 273 times that of carbon dioxide (CO₂) over a 100-year timescale. In Scotland N₂O is responsible for a quarter of the agriculture sector’s total GHG emissions.

More detail can be found in Appendix A on the process of leaching, the effects of eutrophication and how N₂O and NH₃ are emitted from agricultural sources and in Appendix B on the chemical processes of N conversion.

Nitrogen Use Efficiency

Nitrogen use efficiency (NUE) describes the ratio between total N input (e.g., fertiliser) and total N output (e.g., harvested product) expressed as a percentage (%)_. Figure 2 presents a visual example of NUE.

Figure 2. NUE diagram. Source: Udvardi et al., 2021

NUE gives an indication of the efficiency of crop utilisation of N. Generally, the higher the percentage NUE the better as this means less loss of N to air and water and indicates the crop is efficient in the uptake of N. However, pushing the ratio too high (for example over 90% in a cereal crop) can indicate ‘soil nutrient mining’ leaving not enough available N to maintain healthy crop growth and soil ecosystems (Sanchez, 2002). When NUE is too low (less than 50% in cereal crops), a large amount of N is likely being lost to the water and air. An ideal NUE would therefore be between 50% and 90%. NUE efficiency is also greatly impacted by climatic conditions, with changes in microbial activity in drought and frozen soils, along with increased risk of denitrification or leaching when soils are waterlogged.

NUE values are therefore both indicators of resource efficiency and markers for improvement. Key factors influencing NUE include crop type and rotation, soil pH and texture, climate, ammonia, leaching, biological utilisation of N and N management amongst others. As such, an absolute NUE reference value cannot be universally applied and will need to be understood and optimised for specific systems.

Nitrogen and NUE targets in other countries

Introduction

A Rapid Evidence Assessment (REA) seeking evidence relating to the setting and use of nitrogen and NUE targets was undertaken and identified peer-reviewed academic literature as well as government policies and websites. The review also identified grey literature sources such as farming and industry press reports. This search included, but was not limited to, targets for NUE, N emissions and N fertiliser use. The methodology can be found in Appendix C. The review focussed on identifying:

• Relevant scientific research on NUE target setting (4.2)
• Countries with N-related target/s, including types, values and timeframes (4.3)
• Relevance to Scottish agriculture, agricultural sectors and N flows (4.4).

Research on NUE target setting

This section includes information found through the REA on global NUE trends and relevant scientific research on the possibility of setting a NUE target including the necessary considerations (e.g., differences in farming sectors). 95 sources of literature were reviewed through the REA, 38 of which were from the UK, 32 from European countries and the remaining from other countries from around the world. Search strings used to gather this data can be found in Appendix C.

The NUE trend in the UK shows an increase from 1961 to 2014 (Lassaletta, L et al., 2014) which is likely a response to both regulation and market forces (for example the Nitrates Directive and changes in farm incomes). A full list of country-specific changes (%) in NUE values from 1961 to 2014 can be found in Appendix D. Following on from these observations, the research discussed below highlights the requirements and considerations for setting a NUE target.

Studies such as Quemada et al., 2020 collected farm-level data from 1240 farms across Europe and through statistical analysis, present NUE targets for different agricultural systems (e.g., 23% for a pig farm and 61% for an arable farm) which demonstrates the possibility of setting farm-level NUE targets. However, the study also highlights the importance of how differences in farming sectors will impact target setting.

A study conducted by Antille et al., 2021 states that there is no universal method for the calculation and reporting of NUE across all agricultural sectors. Furthermore, research projects which provide recommendations for NUE targets also suggest that such targets could be dependent on the agricultural system and its management, as well taking the ‘4R nutrient stewardship’ approach (right fertilizer type, right amount, right placement and right time) (Waqas et al., 2023). These approaches are country and region specific, dependent on climate, farmer knowledge, technological advancement and availability.

The EU Nitrogen Experts Panel (EUNEP) (initiated by an industry-based organisation ‘Fertilizers Europe’) recommends a maximum NUE of 90% (Duncombe, 2021), with an ‘ideal range’ of 50% to 90%. This range has been set to reflect that a NUE value below 50% is likely to result in N lost to the environment, while a value above 90% could result in soil N mining. Further detail is given in section 3.2. Whilst it is important to note that values will vary according to context (soil, climate, crop etc), the identification of this ‘ideal range’ by the EUNEP helps us to understand the opportunity and potential for setting a NUE target.

The research has highlighted that whilst it is possible to set NUE targets, there are a number of variables which impact upon setting a NUE target. These variables include the differences in farming sectors, differences in farming management, a lack of universal calculation and reporting of NUE, country / region specificity and climate.

N targets by country – types and policy context

There are currently no standalone country level NUE targets. Several countries, however, have set N targets through various means, some of which include information or actions on NUE. The review of approaches and literature can be summarised as having three main reasons/drivers for introducing N targets, these are all focused on responding to environment and climate impacts of N emissions:

• To lower GHG emissions
• To improve water quality
• To improve air quality

The underlying impact of N-related targets all seek to reduce N waste^[1], however, the two primary mechanisms differ in their points of measurement. Some targets are set to reduce N emissions whilst others are set to improved water or air quality. Table 2 gives an overview of existing initiatives across the world and their main N target with relation to agriculture. Many are relatively vague and reflect the difficulty in setting firm policy across regions or countries. No set value was found for the targets in table 2 that do not include a percentage or numeric change. These initiatives or legislation are described in further detail below.

Table 2. Overview of existing initiatives on N targets.

International action

The UN Environment Program (UNEP) previously considered ‘an aspirational goal for a 20% relative improvement in full-chain NUE by 2020’ (Sutton et al., 2014). However, Sutton et al., (2021) found that this could lead to an unfair distribution of effort whereby everyone had to increase their NUE by a relative amount. If this was the case a farm currently operating with high efficiency, e.g., 60% NUE, would have to increase by 12% to reach this 20% target. Whereas a farm operating with low efficiency e.g., 10% NUE, would have to increase by 2% to reach the same 20% target.

To overcome this unfair distribution, a target to halve N waste was seen as a more equitable approach as less waste means less action is needed. For example, to reduce N waste by 50%, a farm with higher N waste e.g., 100t N/yr would have to reduce by 50 t N/yr and a farm with less N waste e.g., 10 t N/yr would have to reduce by 5t N/yr. Therefore, the largest effort needed is placed on farms with higher N waste (low NUE) as opposed to farms already operating with high efficiency (high NUE).

Alongside the support from the UNEP and the technical support of the International Nitrogen Management System (INMS), the Colombo Declaration represents the first-time that governments are collaborating on an ambitious, quantitative, and global N management target by seeking to cut N waste by 50% across the world.

Outside Europe

New Zealand’s Climate Change Response (Zero Carbon) Amendment Act 2019 includes a target to reduce N₂O emissions to net zero by 2050. Canada (which has set a target to reduce fertiliser emissions by 30% by 2030) applies a region-specific approach due to the vast expanse of the country having variable meteorological conditions.

The European Union

The Nitrates Directive (1991) aims to protect water quality across Europe by preventing nitrate losses from agricultural sources through the promotion of good farming practices and includes limitations on N application from manures. Nitrate Vulnerable Zones (NVZs) are areas where the water bodies, such as lakes or rivers, are considered ‘at risk’ because there they have more than 50 mg/l of NO₃^– or are eutrophic. Farmers in these areas must comply with rules set out in the Member States’s action programmes to reduce the risk and the Managing Authorities need to report on NO₃^– concentrations in ground and surface waters. The Directive does not focus on N emissions other than NO₃^–. While the Nitrates Directive has driven a reduction in nutrient application over the last 30 years, targets have failed to improve NUE in many areas with reported high levels of N surplus (N remaining beyond plant and soil requirements) found in the Netherlands, Belgium, north-west Germany, Luxembourg and Brittany in France.

The National Emissions reduction Commitment (NEC) Directive (2016) is the current primary European regulation requiring actions to improve air quality and sets targets for reduction in the emissions of key air pollutants. This is important in an agricultural context due to the inclusion of setting reduction targets for NH₃. Target reductions are specific to each Member State and vary significantly with the target NH₃ reduction for 2030 ranging from 1% for Estonia and 32% for Hungary.

The European Green Deal (2019) is the EU’s holistic plan to achieve net zero GHG emissions across the EU, while improving biodiversity and human health. The Farm to Fork strategy (2020) includes targets to reduce the use of N fertilisers and losses of N to the environment to support improvements in air and water quality and to reduce emissions of GHGs. The strategy sets a target to reduce nutrient losses by at least 50%, while ensuring that there is no deterioration in soil fertility. The European Commission expect this to reduce the use of fertilisers by at least 20% by 2030.

Considering the European wide scope of the directives and strategies to reduce N pollution, our study findings were surprising in that examples of nationwide NUE targets are limited. Whilst no country has a standalone NUE target, some countries such as Ireland and Denmark have incorporated NUE as an ‘action’ as part of a programme or another target (e.g., GHG target).

The Danish example relates to the historic, 1980 ‘Good Agricultural Practice Program’ where increasing NUE was part of a suite of actions to reduce N use. This program was unsuccessful in limiting emission effects and as such ‘harmony rules’ were introduced, which, along with other measures, increased the Danish national NUE to an average of 40%. The Danish harmony rules prescribe the minimum area that a livestock farm must have for spreading livestock manure from their livestock production, thus limiting N inputs to land from livestock manure (Sommer and Knudsen., 2021).

Ireland’s Climate Action Plan 2021 put forward a suite of actions to deliver their GHG target that includes N. Action 359 details the implementation of ‘a suite of measures to improve NUE’. Teagasc, who is leading this action, sees that there is room for improvement across Irish dairy farms with an industry target of 35% NUE “set for farmers to achieve in the coming years” – an improvement of 10% from the current NUE of 25%.

Also in 2021, Denmark introduced the ‘Green transition of Danish agriculture’ which has set an agricultural target to reduce GHG emissions by 55-60% by 2030, including a reduction of N emissions by 10,800 tonnes by 2027. The specific impacts on the aquatic environment are further covered through their Action Plan on the Aquatic Environment III which has targets to reduce N leaching.

France, through the French Climate and Resilience Law 2021, have set targets for reduction of N₂O emissions by 15% of 2015 levels and NH₃ emissions by 13% of 2005 levels by 2030 (Hawley., 2022). This law includes measures to reduce the use of mineral N fertilisers.

The United Kingdom

In the UK, there are N relevant targets at both UK-wide and devolved levels. Nitrate vulnerable zones (NVZ), designated as part of the Nitrates Directive (1991), aim to reduce nitrate water pollution by encouraging good farming practice. Areas where the concentration of nitrate in water exceed 50 mg/l in ground and/or surface waters have been designated as NVZs. There are at least 70 NVZs in England and Wales, covering 55% of agricultural land in England and 2.3% of Wales. Five areas of Scotland (Lower Nithsdale, Lothian and Borders, Strathmore and Fife (including Finavon), Moray, Aberdeenshire / Banff and Buchan, and Stranraer Lowlands) have been designated as NVZs.

The National Emissions Ceilings Regulations (NECR) (2018) commits the UK to reduce NH₃ of 8% by 2020 and 16% by 2030, both relative to 2005 levels. The 2020 target was not met, but there has been a 12% reduction since 2005^[2]. The NECR also contains reduction targets for nitrogen oxides (NO_x), of 55% by 2020 (which was met) and 73% by 2030 but agriculture is a less important source.

Wales have set a target of reducing its total agriculture specific GHG emissions by 28% by 2030 compared to 1990. There are currently no UK-wide agriculture specific GHG emissions reduction targets, however, there is a UK-wide target of net zero by 2050, and agriculture will play an important role in achieving this target. For example, Defra has implemented new regulations on the use of urea fertilisers from 2023, which means that only urease-inhibitor treated or protected urea fertilisers may be used throughout the year, while untreated/unprotected urea fertilisers may only to be used from 15^th January to 31^st March each year. This regulation is expected to deliver an 11kt reduction in ammonia emissions by 2024/2025.

Why set a NUE target in Scotland?

It is important to consider the size and balance of the different Scottish agricultural sectors to understand the NUE potential of each sector. This section provides detail on the different forms of N found in Scottish agriculture, their impact on flows of N and how they can be targeted to improve NUE. A list of mitigation measures to improve NUE can be found in Appendix E and the impacts of these measures on NUE in Scotland are discussed in section 6.2.

The most recent Scottish GHG Statistics (2021) states that 2MtCO₂e of N₂O was emitted from the agricultural sector, which is a quarter of Scotland’s agriculture sector’s total GHG emissions and 2/3rds of total N₂O emissions. N₂O is emitted from soils after the application of N-fertilisers and manures (Brown, 2021). In addition, 90% of Scotland’s total NH₃ emissions are attributed to the agricultural sector. Tackling the emissions of these pollutants will directly contribute to the following Scottish Government policies and ambitions:

• The Nitrates Directive is the basis of Scotland’s five NVZs under the Nitrate Vulnerable Zones (Scotland) Regulations 2008^[3],
• the Scottish Government’s Biodiversity strategy to 2045: tackling the nature emergency, has the ambition of “restored and regenerated biodiversity across the country by 2045”,
• the Scottish Government’s Cleaner Air for Scotland 2 delivery plan
• the Pollution Prevention and Control (Scotland) Regulations 2012,
• target 7 of the Kunming-Montreal Global Biodiversity Framework to ‘reduce excess nutrients lost to the environment by at least half including through more efficient nutrient cycling and use’. The UK is a signatory to this framework and Scotland signed the associated Edinburgh Declaration,
• National GHG targets set by the Climate Change (Emissions Reduction Targets) (Scotland) Act 2019
• the CCPu sets out an ambition for the Scottish agriculture sector to reduce emissions by 31% from 2019 levels by 2032, and a commitment to “work with the agriculture and science sectors regarding the feasibility and development of a SMART target for reducing Scotland’s emissions from nitrogen (N) fertiliser.”

Understanding N flows in Scotland

In recognition of the potential for reducing N to reduce total GHG emissions, the Climate Change (Emissions Reduction Targets) (Scotland) Act 2019 set requirements for Scottish Ministers to create a Scottish Nitrogen Balance Sheet (SNBS) from 2022 (Figure 3). The N flows in the SNBS combine data across all sectors of the economy and environment forming an evidence base to support the optimal use of N across all economic sectors to achieve optimal economic and environmental outcomes. While the SNBS was published in 2022, the data within it relates to 2019. Scotland is currently the only country to have planned to regularly update a cross-economy and cross-environment N balance sheet.

Figure 3. Scottish Nitrogen Balance Sheet (baseline data (mainly 2019)). Source: 3. Results from the initial version of the Scottish Nitrogen Balance Sheet – Establishing a Scottish Nitrogen Balance Sheet – gov.scot (www.gov.scot)

The annual SNBS report to the Scottish Parliament presents an assessment of:

• progress towards implementing proposals and policies relevant to improving NUE in Scotland,
• any future opportunities for improving NUE in Scotland, and
• how NUE is expected to contribute to the achievement of future emissions reduction targets (as per section 98 of the Climate Change (Emissions Reduction Targets) (Scotland) Act 2019)

In 2022, the SNBS report published NUE values for agriculture as a whole sector (27%) with more granular figures of 65% for crop production NUE and 10% for livestock feed conversion. This valuable baseline shows NUE’s potential for improvement which can reduce emissions from all forms of N to support improvements in air and water quality with positive implications to both human (Pozzer et al., 2017) and biodiversity health (Houlton et al., 2019). While the SNBS is a valuable baseline for improving N management it is important to note the specificities of its set-up particularly on how different quantities of N are attributed to different sectors and how this relates to what happens in practice (more detail on this can be found in Section 6.5).

Research has found that the global arable NUE is 35%. When we do not consider all the variables which impact NUE and NUE target setting, as discussed in sections 3.2 and 4.2, the Scottish arable NUE of 65% appears to compare well to international data, however, some EU countries have arable NUEs of up to 77%, showing there may be room for improvement. The 2022 SNBS report states total N losses from agriculture to the environment amount to 30.2 kt N/yr as air pollutants (NH_3, nitrogen dioxide (NO₂) and N₂O) and 104 kt N/yr from runoff and leaching from agricultural soils.

Targeting different forms of N

Figure 4 Scottish agricultural sectors (Scottish Agricultural Census June 2021)

The different N inputs and outputs of Scottish agriculture are described below (also see Figure 3). Most of Scotland’s 5.64 million ha of agricultural area is best suited to livestock farming with a significant proportion occupied by cattle and sheep in Less Favoured Areas (LFAs) (55% or 3,159,137 ha) followed by crops and grass (1,885,701 ha), shown in Figure 4. Non-LFA cattle and sheep (107,712 ha) and specialist dairy (106,935 ha) are large sources of N in manure. More intensive sectors such as pigs and poultry do not have a direct correlation between NUE and land area, however they are significant sources of manures and contribute to N inputs. These areas are used to track N flows from the SNBS against sectors of particular potential in section 4.4.2. Note that forestry and aquaculture are out of scope of this project but will have impacts on Scottish N flows.

NUE varies between different Scottish farm types as the biological utilisation of N influences the potential NUE. The SNBS shows that livestock farms currently have a lower NUE (10%) than arable farms (65%). This is partly due to the relative inefficiency in the conversion of ingested N in feed converting to stable N within livestock products (milk and meat).

N Inputs

Fertiliser as the N input

The SNBS details that one of the largest flows of N in Scotland (143.8 kt N/y) is the use of inorganic fertiliser on arable crops and grass, with 62.1kt of this inorganic N applied to crops per year and 81.7kt going to grass ^[4]. The British Survey of Fertiliser practice states that in 2022, 63 kg N/ha were applied on average to all crops and grass in Scotland.

There is little information on N use in Scottish horticulture and permanent crops. Nonetheless, N fertiliser recommendations for vegetables, minority arable crops, bulbs, soft fruit and rhubarb crops exist. The high value of many of these crops and the technological advances taking place in this sector facilitate a higher degree of precision in management (e.g., GPS use for N application, leaf N monitoring, fertiliser application within irrigation water etc), which allows a better understanding of N flows in these systems. Targeted N applications could lead to reductions in inputs and waste thereby improving overall NUE for these crops. However, to date there are no recommended NUE levels for these specialist crops, thus more research is needed to understand the impact of reduced N applications on crop health and yield.

The evidence relating to the N requirements for the majority of crop and grass areas in Scotland is well described within the technical notes, and recommendations for NUE targets could build upon the evidence supporting these recommendations. Like specialist crops, improvements in fertiliser practices and technology can support improvements in N applications which will help matching of N inputs to crop requirements with greater precision and thus improves NUE.

Livestock Feed intake as the N input

The optimum levels for dietary crude protein are often exceeded to ensure that N intake does not limit either growth or welfare. This excess of N supply in the diet results in surplus N being excreted through manure and urine leading to N losses. Cattle cannot efficiently convert dietary N (efficiency ranging between 22-33%) and therefore, on average, 75% of consumed N is wasted, mainly through excretion. Matching N supply in feed with livestock requirements is part of ‘precision livestock feeding’ which can increase farm profitability, reduce emission intensity of methane (Rooke et al., 2016) and reduce N intake and excretion. Reductions to NH₃ and N₂O emissions from livestock sources due to precision feeding vary widely. However, studies have found that a reduction in crude protein of 2% leads to a 24% reduction in NH₃ emissions in broilers, and a 1% crude protein reduction in pig feed results in a 10% reduction in NH₃ emissions (Santonja, 2017).

The SNBS found one of the largest N flows is N excreted by livestock (142.9 kt N/y). The control of N levels added to soil from livestock directly impacts the input part of the livestock NUE calculation. A NUE target aimed at the livestock sector may be most impactful as it currently has the lowest NUE (10%) whilst also covering the largest amount of agricultural land (combined total of 3.3 million ha) meaning even a small, targeted improvement in NUE for livestock could have a significant impact on the overall N budget.

N Outputs

Ammonia as the output

NH₃ from agricultural sources produces particulate matter which can impact human health, causing diseases such as cardiovascular and respiratory disease. In addition, NH₃ emissions can result in the long-range transport of N compounds and this N deposition can cause acidification and eutrophication. Scottish agriculture accounts for 90% of total NH₃ emissions, which have decreased by 12% over the last 30 years. NH₃ is tied specifically to the (housed) livestock sector, with most emissions (35% of NH₃ emissions) coming from cattle manure management. Livestock housing and storage of manure is responsible for 10.5kt N/y in the form of NH₃ emissions, therefore improvements targeted at this sector would directly improve NUE. Examples of mitigation measures which can be introduced to lower the NH₃ emissions in this sector are detailed in Table 3 under section 6.2.1 and include slurry store covers and slurry acidification.

Use of urea based inorganic fertilisers can lead to significant losses of NH₃. High temperatures and winds at the time of fertiliser application or very dry conditions can lead to high levels of NH₃ volatilisation (the conversion of NH₄+ to NH₃ gas) with a significant proportion of the N being lost and unavailable to the plants. A useful mitigation measure is the use of urease inhibitors with urea fertilisers to reduce these emissions.

Nitrate leaching as the output

Excessive leaching of N from agricultural activity can lead to water pollution and eutrophication which can then result in the loss of aquatic biodiversity and GHG emissions. The SNBS shows N run-off and leaching from crops and arable land as 45.5 kt N/yr and from grass as 58.5 kt N/yr. This N is lost as NO₃^–, which is readily mobile in soil water or runoff. Any N that is lost from the soil is no longer available to plants thereby lowering the potential NUE and increasing agricultural pollution.

According to Adaptation Scotland, Scotland is predicted to experience an increase in rainfall, with intense, heavy rainfall events increasing in both winter and summer. This has the potential to increase N leaching as soil moisture controls both crop N uptake and N leaching (McKay Fletcher et al., 2022). In addition, Scotland’s topography affects the rate of run-off as steep slopes promote surface run-off. When considering Scotland’s topography and the predicted change in rainfall, the potential for leaching will increase and continue to negatively affect water quality. Those areas currently most at risk are classified as NVZs.

Nitrous oxide emissions as the output

N₂O is a GHG that accumulates in the atmosphere and directly contributes to climate change. The SNBS shows 5.9kt N₂O per year is emitted from the agriculture sector. This includes 0.9kt from livestock (including manure management), 3.8kt from soil management (including mineral fertiliser use), and 1.2kt of indirect emissions (from N deposition and NO₃^– leaching). N₂O is produced in the process of denitrification, where denitrifying bacteria under conditions where oxygen is limited (for example waterlogged soils) use the NO₃^– available in soil. By using the NO₃^–in soil, these bacteria reduce the NO₃^– available by plants potentially negatively impacting yield. In conditions where NO₃^– is available in excess denitrification can reduce NO₃^– losses through leaching. However, since N₂O is produced in the process, negative impacts on climate are the result. Total elimination of N₂O emissions from agriculture is not possible; however, some mitigation is possible through improvements in soil conditions and avoidance of N fertiliser application under wet conditions (Munch and Velthof, 2007).

Crop and livestock outputs

Crop and livestock products are the useful outputs of N from agriculture. In Scotland these account for 54.5kt N per year. This value includes livestock products, including meat, milk, eggs, and wool, and harvested crops used for food for human consumption (but excludes crops for animal feed or fodder). Useful crop outputs also include seed, feed and straw, but these are retained in the agricultural system and so are not final outputs.

Cereals, explicitly for alcohol production, accounts for the largest useful output flow in Scotland at 20.5kt N, followed by livestock products at 19.6kt N and crop product for human consumption at 12.2kt N (all values per year).

Optimising the quantity of N recovered in these outputs i.e. the N is taken up by the plant or animal and used to increase growth, relative to the quantity of inputs (feed and fertiliser) is key to reducing N waste and improving NUE. Managing the quantity of N application to meet crop and livestock requirements alongside the soil conditions will improve the overall NUE.

Viability of a SMART Target for NUE in Scotland

This section looks at the viability of setting a NUE target for Scotland and provides a summary of the risks and benefits of setting a Specific, Measurable, Achievable, Relevant, and Time-Bound (SMART) NUE target in Scotland and presents how a range of influences can support or hinder the achievement of a NUE target. Information on N targets in other countries was considered and analysed for their applicability to Scotland. Since no other country has a standalone NUE target, we had to rely on information on other N targets for our analysis and transfer these finding to a NUE target for Scotland. The methodology can be found in Appendix F.

Analysis Tools

SWOT analysis

Strengths, weaknesses, opportunities, and threats (SWOT) of setting N-related targets were analysed based on the information gathered on N targets in other countries. We also included analysis of GHG and climate related targets where relevant to increase the body of information. This information was then used to assess applicability of setting a NUE target for Scottish agriculture with the limitation that the analysis was based on N, GHG and climate related, rather than NUE specific targets. The SWOT analysis shows a range of influences which can support or hinder the achievement of a NUE target. The full SWOT analysis can be found in Appendix F.

PESTLE analysis

Setting NUE and other N targets are subject to a range of enablers and barriers. Therefore, a political, economic, social, technical, legal, and environmental (PESTLE) analysis was undertaken to assess the feasibility of setting a NUE target for Scottish agriculture, again, with the limitation that the analysis was based on N, GHG and climate related rather than NUE specific targets. The PESTLE assessment took place following the SWOT analysis to ensure the findings from the SWOT were assessed and, if relevant, included into the PESTLE categories. The full PESTLE analysis can be found in Appendix F.

Discussion

Supporting a SMART NUE target

The SNBS is reviewed and updated annually and provides a source of data for measuring and monitoring the changes in NUE and thus the progression of a NUE target. In addition, all mitigation measures identified in section 6.2 and analysed for their effect on Scottish agriculture NUE are captured by the SNBS. The use of the SNBS enables a measurable target. This was identified as a strength and technical enabler in the analysis of setting a NUE target.

Another strength and technical enabler identified through the analysis includes the mitigation measures required to achieve a NUE target. N-related mitigation measures are well understood, and many are relatively low cost and already practiced in Scottish agriculture (e.g., use of catch and cover crops) which makes reduction in N losses achievable. Furthermore, measures continue to be developed through additional research e.g. in Canada to understand the emission reduction potential, costs and benefits of different measures at farm level.

Section 6.4 recommends years 2030, 2040 and 2045 as deadlines which would ensure a NUE target is time-bound. These years align with other emission targets set in Scottish Government which may affect agriculture and therefore complement a new, potential NUE target. Including three timed steps into a binding target would also help measure the progression of the NUE target whilst also encouraging the delivery of high reductions.

A NUE target would be relevant in meeting statutory emission reduction targets. Introducing a NUE target would lower N-related emissions and would therefore contribute to other emissions reduction targets, for example the CCPu which aims to reduce agricultural GHG emissions by 31% from 2019 levels by 2032. Similarly, a NUE target would be relevant to several other environmental issues as the implementation and success of a NUE target would have multiple benefits for example, improvements to water quality, air quality (Sutton et al., 2014), human health and biodiversity (Houlton et al., 2019).

The SWOT and PESTLE analysis identified influences needed to support a specific and achievable NUE target by detailing opportunities which could assist with the implementation of such a target. Regulatory instruments include BAT/mitigation measures and fertiliser use limits, economic instruments include taxes and subsidies, and communicative instruments include extension services and awareness (Oenema et al., 2011).

Other positive influences include an increase in farm profitability following the implementation of mitigation measures such as precision livestock feeding and matching N supply to demand) which was found as a strength and economic enabler through the analysis. Moreover, through the introduction of a NUE target, there would be an opportunity to involve advisors and consultants which may also lead to the implementation of better advice and practice regarding N use in Scottish agriculture.

Hindering a SMART NUE target

All analysis was based on N targets rather than NUE targets due to the lack of any NUE specific targets in other countries. Therefore, clear evidence on NUE targets is lacking and the analysis of a NUE target for Scotland is based on assumptions through transferring information from N-related targets to NUE.

To achieve any potential NUE targets a range of new techniques, technologies and systems would be required. These are referred to as mitigation measures. There is already a good body of evidence and supporting examples of the implementation of mitigations. These have been identified as a strength and enabler as some examples such as variable rate N application (precision farming) can save farmers money on inputs by only purchasing and applying N as needed. Others, however, require significant capital expenditure with upfront investment of time and money required to implement some of the mitigation measures (for example, low emission slurry application equipment). This has also been identified as a weakness and economic barrier which may be experienced by Scottish farmers. This could directly impact upon the achievability of a NUE target. Similarly, several barriers to uptake of mitigation measures were identified as a threat through the SWOT analysis. Barriers include lack of awareness and knowledge of why and how to improve N use, and farmer’s personal beliefs, both of which may lead to Scottish farm managers finding it difficult to quantify the benefits to their business and understand the relevance of a NUE target. These barriers would generally hinder the achievability of a NUE target.

In trying to make a NUE target relevant in terms of meeting statutory emission reduction targets, there is a risk when reducing N-related emissions, through mitigation measures, that pollution-swapping takes place. An example of this is the decrease in NH₃ emissions and an increase in N₂O emissions (due to nitrification/denitrification processes) when using slurry injection (a type of low emission slurry application) compared to surface application. Pollution-swapping as an unintended consequence of some mitigation measures was identified as a threat and environmental barrier in introducing a NUE target.

Farmers’ perception of a national NUE target for Scotland may limit target achievability. Scottish farmers may not understand how their practices impact NUE and how introducing on-farm mitigation measures may impact on a general NUE target for Scottish agriculture. For example, questions may arise on how many and at what frequency the relevant mitigation measures need to be introduced by each farmer to achieve this overarching target. To overcome this, some farmers may respond more positively to several more specific targets, for example a reduction of fertiliser input (by a certain amount and by a certain date). Alternatively, ensuring a NUE target is accompanied with very specific and relevant action points on how this NUE target would be achieved so that farmers have a clear understanding on what is expected of them and their farming system to contribute to a national NUE target.

The time taken to create and process the appropriate legislation for a NUE target can be uncertain and longwinded. This process has the potential to directly impact the time-bound element of a SMART NUE target.

In the Netherlands, an ambitious target led to civil unrest where more than 10,000 Dutch farmers have been protesting following government plans to reduce N emissions. Similarly, when targets or limits are seen to be a barrier to economic performance, implementation of new regulation can become challenging, as is seen in the case of revising the approach towards Nutrient Neutrality in England. The use of a SMART target is therefore critical to avoid the implementation of a policy which is neither appropriate nor achievable.

In the main, these examples relate to current exceedances of regulations under the Habitats or Nitrates directives, follow a long period of previous actions and constraints on the farming sector and relate to farming systems which are very different to those present within Scotland. In addition, these regulations are not focused on NUE but rather on the achievement of environmental targets and so do not consider the productive potential of the sector. Notwithstanding these differences, these risks do indicate the importance of well formulated targets, based on sound scientific understanding and with a clear plan for consultation and implementation on their achievement and delivery.

The political and legal barriers identified include the potential for pushback on mitigation measures which are seen to reduce productive output and a concern that Scottish farmers may not comply with regulatory requirements. This could directly impact upon the achievability of a NUE target.

Development of a NUE target for Scotland

Assessment using the Scottish Nitrogen Balance Sheet

The SNBS has been used as a baseline to assess how practices that influence N pools or flows may impact the agricultural NUE value. This dataset contains values for key sectors, pools (stores of N within parts of the N cycle e.g. in manure, in soils or in livestock/crops), and flows of N (movement of N into different pools as the N form changes or is taken up by plant or animals). These flows include inputs to the system (e.g. fertilisers, animal feed), useful outputs (e.g. meat, cereals), and waste (e.g. NO₃^– leaching, NH₃ emissions). Each of these flows have a value in kt N/yr assigned. The NUE is improved by either increasing the output flow values or reducing input and waste flow values. This can be modelled by estimating the impact of a mitigation measure (e.g. improved nutrient planning or reduced protein livestock feed) and applying these values to the relevant N flow in the SNBS (for improved nutrient planning this would be reduced inputs of fertiliser and reduced N emissions to atmosphere). This produces estimates for N flows that can then be summarised in NUE calculations as currently setup in the SNBS, resulting in estimates of improved NUE values (see Appendix E for a detailed methodology and all assumptions).

Mitigation measures

The effect of mitigation measures on Scottish agriculture’s NUE

This section presents and discusses the effects of 18 different mitigation measures on the current NUE of Scottish agriculture.

The table below presents modelled estimates for the NUE of Scottish agriculture, by individual measure and at each future projected target year. The values reflect implementing the relevant measure individually and compared to the current whole-agriculture NUE of 27.2% (i.e. preventing soil compaction may improve total NUE by 0.1% by 2030). The results show the impact for the relevant measure in isolation and do not reflect any combination effects for interactions with other measures. Further detail on the assumptions and methodology can be found in Appendix E. The 2030, 2040 and 2045 scenarios are based on minimal change, continuing recent trends of recent changes in uptake, but including greater increases where there is precedent to, e.g. low emissions spreading techniques all increasing to 95% by 2030 as this will be required under the New General Binding Rules on Silage and Slurry. However, the 2045 Ambitious scenario is based on a transformational change across the sector where there is greater effort to improve NUE to meet a legally binding target. Therefore, the improved NUE in the 2045 and 2045 (Ambitious) scenarios may be viewed as the range where a target may be set, where the lower bound of the range (2045 scenario) is more achievable, while the higher bound (2045 (Ambitious) scenario) would require more effort across stakeholders to be achieved but is a better value.

Table 3 List of mitigation measures and their effect on Scottish agriculture NUE (%) compared to the current whole agriculture NUE of 27.2%. The two 2045 scenarios can be viewed as an ideal range for NUE; where the lower bound (2045 scenario) reflects changes to agriculture planned to come in (current and upcoming legislation, expert judgement on technological developments etc.); while the upper bound (2045 ambitious scenario) reflects the possibility for a greater push from industry and government to improve NUE (financial incentives, increased awareness of N management, etc.).

There are potential interactions/overlaps between several of these measures. Where this occurs, measures cannot be applied on the same unit (area of land/head of livestock) at the same time as they are mutually exclusive. We have avoided double counting these effects by resolving the total maximum applicability across overlapping measures i.e. the combination of measures cannot exceed the total land available to apply the measure to.

The key outcomes are:

• The measures with the greatest potential improvement on NUE are nitrification inhibitors, improving livestock nutrition, and improving livestock health.
• Nitrification inhibitors are more effective at improving NUE than urease inhibitors as they can be applied to a greater proportion of fertiliser products used in Scotland (both NO₃^– and urea-based products, while urease inhibitor can only be applied to urea-based products).
• Improving livestock nutrition will improve NUE by reducing the overall quantity of N being fed to livestock while maintaining liveweight yield.

Measures that are based on the use of legume crops were not included in the modelling of the new NUE values, as the reduced requirement for inorganic fertiliser input will be offset by increased biological fixation of N from the atmosphere. Both flows are included in the N input values when calculating NUE in the SNBS. Therefore, the total N inputs levels will stay constant, as will the outputs, and so there is no impact on NUE. However, there are benefits of legume crops beyond an improvement to NUE, which should be considered, namely the effects of reduced requirement for inorganic fertiliser inputs (lower GHG emissions), improved soil health and soil function, and reduced costs. This is likely to be economically beneficial to the farmer, as soil health benefits the local ecosystem and improves resilience, reduced fertiliser use avoids emissions from manufacture and transportation of inorganic fertiliser; all of which are benefits from moving to a circular economy.

Potential N savings through implementation

The table below summarises the potential savings of N inputs of mineral fertiliser in both absolute values in kt N yr^-1, and relative to the quantity in the current SNBS as a %. The values presented here include fertiliser use savings due to legume-based measures (legume-grass mixtures, and legumes in crop rotations). The effect of these measures is not included in calculations of NUE due to the assumption that the saved fertiliser N application will be replaced by increased N deposition from the atmosphere.

Table 4 Absolute values of N inputs of mineral fertiliser saved in kt N per year and as % of the quantity in the current SNBS when all modelled measures are included. The two 2045 scenarios can be viewed as an ideal range for NUE; where the lower bound (2045 scenario) reflects changes to agriculture planned to come in (current and upcoming legislation, expert judgement on technological developments etc.); while the upper bound (2045 ambitious scenario) reflects the possibility for a greater push from industry and government to improve NUE (financial incentives, increased awareness of N management, etc.).

Recommended criteria for target(s) setting for Scotland

When modelling the NUE improvements and the establishment of potential targets, the key criteria for consideration are listed below.

Mitigation measures

The measures/farming practices that have been included for modelling are the result of literature searches and expert judgement. Measures that impact N flows in agricultural systems, and the relevant data, were extracted from literature. These were then reviewed to ensure applicability to Scotland, and any other measures that were identified by experts as being important were also researched.

Current uptake

The current uptake provides a basis from which to estimate what future uptake may be possible and the likely rate of additional implementation. It also supports the calculation of a baseline or counterfactual against which change can be measured. These values come from the same sources which have provided the NUE impact values (see Appendix E for detail on current uptake for each measure).

Applicability

The applicability values refer to the portion of a SNBS N flow that a measure’s impact value can apply to. Expected future uptake

The expected future uptake values are estimates based on expert judgment and consultation within the project team. The values for each measure can be found in Appendix E and are additional to the current uptake levels. These values increase over time to reflect increasing commitment to NUE improvements. The two 2045 scenarios can be viewed as an ideal range for NUE; where the lower bound (2045 scenario) reflects changes to agriculture planned to come in (current and upcoming legislation, expert judgement on technological developments etc.); while the upper bound (2045 ambitious scenario) reflects the possibility for a greater push from industry and government to improve NUE (financial incentives, increased awareness of N management, etc.). The expected future uptake ranges from 1% to 100% depending on the measure and scenario. For example, soil compaction was only expected to increase by 2% even in the 2045 (Ambitious) scenario as it was assumed that where soil compaction is occurring most farmers will already be taking steps to improve it. While low emission spreading techniques increased to 95% by 2030 to reflect the New General Binding Rules on Silage and Slurry. A full example is provided in Appendix G.

Timescales

We modelled potential NUE targets for Scottish agriculture for 2030, 2040, and 2045. These were chosen to align with Scotland’s Climate Change Act 2019 with a target date of 2045 for reaching net zero GHG emissions.

One NUE target for Scottish agriculture or per sector?

Currently, the arable sector is more N efficient than the livestock sector (65% and 10% respectively). This difference is due to inherent qualities of livestock systems with animals unable to process N as protein as efficiently as plants uptake N. The current NUE should, however, be seen as a baseline, and the scale of improvements from this should be the focus rather than an absolute target applicable to all sectors and systems. The majority of measures included in the modelling of NUE improvements target the soil N pools (arable and grass land), therefore separate targets for each sector are advisable.

Analysis of recommendations

The table below presents the estimated NUE values in 2030, 2040, and 2045 based on increased uptake of on-farm measures. As well as an additional value for the year 2045 where increased ambition has been included in the projected uptake values.

Table 5. Potentially achievable NUE estimates in 2030, 2040 and 2054 based on increased uptake of on-farm measures. The two 2045 scenarios can be viewed as an ideal range for NUE; where the lower bound (2045 scenario) reflects changes to agriculture planned to come in (current and upcoming legislation, expert judgement on technological developments etc.); while the upper bound (2045 ambitious scenario) reflects the possibility for a greater push from industry and government to improve NUE (financial incentives, increased awareness of N management, etc.).

The NUE values that are modelled in this study are based on the selected measures, and the achievement of these NUE targets rely on their implementation. Other agricultural practices may impact N flows, as will changes in the size of agricultural sectors.

Similarly, the NUE values that have been calculated are based on the levels of implementation that have been included in the modelling. Achieving these targets in practice will require supporting instruments to encourage the uptake of these measures. As stated in Section 6.2.1, the NUE values in the above table for 2030 and 2040 reflect assumptions on uptake based on minimal change and not a transformational change to the sector (such as the setting of a target). Therefore, these values should not be viewed as potential targets for these years, but as indicators of the feasibility of improvements to NUE in Scottish agriculture.

Sector specific NUE values are not currently feasible due to the calculation set-up in the current SNBS (which flows are considered as inputs/outputs for arable and livestock), and the assumption made in the modelling that production will not increase and only inputs will decrease. This set-up leads to results that make it seem that the arable sector is mining N, which is not the case. Improvements to the set-up of calculations to overcome this barrier are outlined in Section 6.5 below.

Guidance for future implementation

In the current version of the SNBS, the NUE calculations do not align directly with what happens in practice in the different agricultural sectors because there are overlaps and movements of N flows between the different agricultural sectors that are not easily viewed in isolation. For example, in practice, improvements to NUE due to implementation of manure management measures will largely be implemented by the livestock sector. However, given the current set-up of the calculations in the SNBS, N flows related to manure management may not be attributed to the livestock sector NUE values as they will reduce emissions from spreading of organic matter to soils, which would be reported in the arable sector calculation. This would make it more difficult to use the SNBS to set and measure sectoral targets. Therefore, accurately monitoring the changes in NUE and attributing these changes to the correct sector would be important if considering sectoral targets. Accurately representing N flows in the SNBS to the relevant sector may be difficult, due to, for example, data availability, different ways data is collected across mitigation measures and sectors and difficulties in correctly separating overlaps and movements of N flows between the different agricultural sectors, however, could significantly help the feasibility of achieving and monitoring NUE targets.

When reflecting the potential impacts of mitigation measures on the values in the SNBS, certain hurdles resulting from the disaggregation of flows make it more difficult and possibly less accurate. More details of these hurdles, and how they were overcome, can be found in Appendix E, but a key example here is the use of slurry acidification on livestock slurry. In the SNBS there is one flow of N from manure management to atmosphere which includes all manure storage types and all livestock types. However, the implementation potential and mitigation impact potential will vary between storage and livestock types. This required an assumption to be made on the breakdown of this manure management N flow so that the appropriate uptake levels and impact values can be applied to the correct portion of the total N value (in this instance the Scottish Agricultural Census was used). This can be considered a sound approach to reflect the mitigation measures in the current SNBS, however going forward, to improve the ease and accuracy with which targets can be projected and improvements can be measured, a more granular breakdown on the N flows in the agricultural sector in the SNBS are required.

Conclusions

A NUE target for Scotland

The rationale behind setting a NUE target for Scotland is to reduce the impacts of N wastages to the environment to lower GHG emissions and improve water and air quality. NUE values can be used as indicators for N resource use efficiency and as markers for improvement. Scotland is in the unique position to use and regularly update a cross-economy and cross-environment N Balance Sheet (SNBS). The SNBS provides a valuable baseline in the current performance of Scottish agriculture and provides a tool to tackle all forms of N pollution.

However, setting a NUE target is not without challenges and nowhere in the world has yet set a NUE target. NUE values are impacted by various factors (soil type, climate, crop type, livestock type, etc). Whilst research shows that the ideal range for NUE is between 50-90%, it is crucial to understand the different forms of N inputs and outputs and to allocate these correctly to the different farming sectors.

As no other country has yet set a standalone NUE target, we had to solely rely on other N-related targets for our evidence base. Our analysis of the viability of setting a NUE target for Scotland is therefore based on assumptions through transferring information from N-related targets to NUE.

The SWOT and PESTLE analysis carried out in this study highlighted several factors which can influence the success of a SMART NUE target for Scottish agriculture. Importantly, the use of the SNBS would make the target measurable and the fact that many N-related mitigation measures are well understood and already practiced in Scottish agriculture would make the target achievable. However, some mitigation measures require significant capital expenditure, such as slurry management equipment, or increased ongoing investment, such as nitrification inhibitors, or a change in focus, such as better-balanced protein in livestock feed. These changes would need support from the farming sector. Using NVZ regulations as an example, a small study conducted in 2016 (Macgregor and Warren 2016) showed that some farmers regarded the NVZ regulations as “burdensome and costly”. To avoid similar responses to setting NUE targets, farmers would need to be able to quantify the benefits to their business and understand the relevance of a NUE target for climate and the environment. It is therefore important to accompany NUE targets with specific actions points expected by farming businesses. Providing funding to farmers to help implement mitigation measures and share knowledge on the impact to their businesses, the climate, water quality, air quality and biodiversity is likely to aid faster and easier uptake of these measures.

Looking at initiatives worldwide, we know that N use can be targeted in many different forms (fertiliser use, livestock diet, reduction of N waste, reduction of emission of air pollutants, etc.) and alongside the proven mitigation measures discussed above, it is clear that improvements to NUE are achievable.

Modelling NUE improvements using the SNBS

In this study, the SNBS has been used to model NUE improvements by estimating the impact of a mitigation measure and applying these values to the relevant N flow in the SNBS. It is important to note that these results show the impact for the relevant measure in isolation so do not reflect any combination effects for interactions with other measures. In the arable sector, the mitigation measures with the greatest potential to improve NUE are the use of variable rate N application (precision farming) and the use of nitrification inhibitors potentially increasing NUE to 28.8% and 29.7%, respectively, by 2045. In the livestock sector, improving nutrition and improving livestock health (NUE of 31.7% and 29.4% respectively by 2045) have the greatest potential. Overall, the modelling suggests that total NUE of Scottish agriculture could be increased to 38.2-40.9% by 2045, depending on the level of implementation of mitigation measures.

Sector specific NUE values are not presently feasible due to the calculation set-up in the SNBS and the assumptions that production will remain stable, with only inputs decreasing. In the current version of the SNBS, the NUE calculations do not align directly with what happens in practice in the different agricultural sectors because there are overlaps and movements of N flows between the different agricultural sectors that are not easily viewed in isolation and not necessarily attributed to the correct sector. For example, mitigation measures around manure management will, in practice, be mainly implemented by the livestock sector but will, in the current calculations, be attributed to the arable sector because they are linked to reduced emissions from spreading of organic matter to soils.

The feasibility of a NUE target for Scotland

This research indicates that a NUE target for Scotland is not currently feasible. We see potential for such a target in the future but recommend to first consider several points for improvement.

• The SNBS. Improvements to the calculations and attributions of flows of N to the different measures and sectors are required. The modelling for this report depends on assumptions and figures from another CXC report (Eory, et al., 2023). We recommend updating this data with real on farm data to better inform assumptions that follow from it.
• The sectors. Currently, the arable sector is more N efficient than the livestock sector (65% and 10% respectively). Sector specific targets would be helpful due to differences in current NUE, N inputs and N wastages but this is presently not possible due to the current limitations in the SNBS.
• The mitigation measures. More data on the impacts of mitigation measures under Scottish conditions would increase the accuracy of modelling achievable aims. Since NUE values are both indicators of resource efficiency and markers for improvement, it is possible to focus on mitigation measures with the most potential to improve NUE values.
• Farmers. It is highly important to ensure that targets and measures are clearly understandable and achievable for farmers to create support from the farming sector.

A potential target figure?

If a NUE target was set, this could be in line with the modelled potential NUE estimates of 38.2-40.9% by 2045, depending on mitigation measure implementation. To achieve greater improvement, a combined push from industry and government (financial incentives, increased awareness of N management, etc.) is required. This additional push is reflected in our ‘Ambitious scenario’.

However, based on our research findings, the barriers identified to implementing an achievable and successful NUE target and the need for farmer and industry support to achieve changes in practices and expectations, we conclude that focusing on reducing N waste is likely to have more success than NUE targets as a policy option. Experience from the United Nations Environment Assembly’s discussions on N and the Green Deal’s Farm to Fork targets, has shown more success in including the reduction of N pollution in policy when focusing on N waste over NUE targets. NUE can instead be used as a technical tool to mark improvements, with the SNBS key to setting a baseline and providing a visualisation of the combined impacts of implemented mitigations measures over time. We therefore recommend setting a target for N waste.

An alternative – a N waste target?

Opportunities for setting a N waste reduction target include:

• It is an easier concept to communicate to the farming community and other N producing sectors.
• It gives the opportunity to value any N as a resource until it is lost as waste, creating options for greater collaboration between the arable, horticulture and livestock sectors. Any potential bias towards a sector will be avoided.
• Each individual farmer and land manager would be encouraged to reduce N waste for the economic and environmentally beneficial outcomes. The positive messages around a N waste target would be likely to create support from the farming sector.
• Achievements towards an N waste target would achieve reductions in national NUE thereby achieving the same objectives without the current issues around NUE targets.

Following the Colombo Declaration of 50% reduction of N waste and the Green Deal target of reducing nutrient waste by 2030, a reduction of 50% of N waste in Scottish agriculture would align with other examples. However, we recommend further research to determine a realistic N waste target for Scotland.

Research gaps for setting a N waste target

In the SNBS, N flows would need to be properly assigned to N waste and N re-use. Legumes would need to be included in the SNBS because N waste is likely to be lower than N input. A SMART target analysis for N waste would be beneficial to set a challenging and realistic target. It would be helpful to closer investigate the relationship between N waste and NUE targets if a NUE target is the long-term aim.

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Appendix / Appendices

Appendix A: Nitrogen and its relevance to agriculture

Leaching and the effects on eutrophication

Leaching is the loss of N (as nitrate) as water drains through the soil moving nitrate away from the root zone. Both organic forms of N (such as slurry and manures) and inorganic fertilisers are liable to leaching. When nitrate is leached from soils, it can enter watercourses contributing to environmental problems such as eutrophication. Eutrophication is an accumulation of nutrients in watercourses causing excessive plant and algal growth resulting in reduced water quality and impacts upon fish, invertebrates and plant diversity. The extent of leaching is determined by factors such as soil type, crop cover, land management methods, geological characteristics and meteorological conditions prior to, during and following the application of the nutrients.

How NH₃ is emitted from agricultural sources

Loss of ammonia which is a significant air pollutant impacting upon both human health and biodiversity (respiratory harms and nutrient enrichment of sensitive habitats) is common from agricultural systems. Ammonia is lost through volatilisation of ammonium (NH₄+).

How N₂O is emitted from agricultural sources

Nitrous oxide is emitted in the process of denitrification, a bacterial process in waterlogged soils that converts nitrate to nitrous oxide and N₂ (for more explanation regarding the chemical processes involved please see Annex F). N₂O is a potent greenhouse gas and forms a significant contribution to agriculture’s impact on climate warming.

Appendix B: Chemical processes of Nitrogen

Appendix C: Rapid evidence assessment methodology

The Rapid Evidence Assessment (REA) methodology used for this project aligns with NERC methodology and comprised of the following steps.

• Define the search strategy protocol, identify key search words or terms, define inclusion/exclusion criteria. A list of key words, terms and search strings were created and reviewed by the project steering group to direct the REA review to the most relevant sources.
• Searching for evidence and recording findings. Literature was searched using Google Scholar, utilising our accounts with Science Direct and Research Gate to access restricted PDF’s where required. When searching through Government websites (to find policy initiatives and associated targets), the search engine Google was used. Searches were divided into academic literature and government websites (including farming press and industry). A unique search reference was assigned for each individual search, and the date, search string used, total number of results found, and the total number of relevant papers found were recorded. Examples of search strings include:
• “Nitrogen” “target” “Europe”
• NH₃ target agriculture
• Nitrate leaching target
• Emission reduction target Denmark

All results were recorded in an excel spreadsheet with information extracted on the following:

• Country
• Target
• Target timeframe
• Benefits and risks/challenges of proposed target
• Mitigation measures (introduced, planned and proposed/suggested)

A RAG (red, amber, green) rating was also assigned for each source, based on the following criteria:

• Screening. Sources of evidence were then screened initially by title and then accepted papers were screened again using the summary or abstract. Literature was screened for information on the following inclusion criteria:
• Nitrogen target (including but not limited to target for NUE or nitrogen emissions, or nitrogen fertiliser use, or nitrogen deposition)
• Benefits and risks of introducing a target
• Mitigation methods that improve NUE, or decrease nitrogen inputs
• Extract and appraise the evidence. The screening provided an organised list of papers which enabled evidence to be extracted directly from the literature into the report. Literature extracted also guided the internal workshop and supported information included in the SWOT and PESTLE tables.

How was the evidence found used. Evidence gathered from the REA was used to identify the different types of N targets used in other countries and provided a discussion following examples of the relevance of these targets to Scottish agriculture (section 4). The evidence was also used to identify the benefits and risks of setting a NUE target for Scotland and assisted the SWOT and PESTLE analysis (section 5) and to inform criteria and underpin recommendations for setting an appropriate target/s for Scotland.

Appendix D: Country-specific changes (%) in NUE values from 1961 to 2014

Table 6: Country-specific changes (%) in NUE values from 1961 to 2014 (Our World in Data)

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Appendix E: Analysis & recommendation development Methodology

• Data collection

Relevant measures were collated from results of the REA. The impact factors for these measures on N flows was extracted into an excel file.

• Data extraction

All relevant data points were extracted from the papers into an Excel spreadsheet manually.

• Data appraisal

A RAG rating was applied to all data sources based on the quality of the data (including publishing date, assumptions made, applicability etc.). Where data was considered to be very poor quality, alternative sources to fill or improve this data point were sourced.

• Mapping

Relevant mitigation measures were mapped on to the SNBS according to what nitrogen flows they impacted. This allowed for accurate modelling of the change in nitrogen flow, and subsequently nitrogen use efficiency, if the measures are implemented at the estimated uptake rates in the given years.

• Calculations

Once the impact values had been mapped on to relevant N flows, they were evaluated to ensure that the theory behind these values relate and can therefore be applied to the values in the SNBS. This involved ensuring that each measure had a relative impact value as percentage, and that the baseline is applicable to that in the SNBS.

Applicability: the portion of the relevant flow in the SNBS that the measure/impact value applies to e.g. emissions from livestock are grouped in one flow in the SNBS, and so a measure/impact value relevant to only dairy animals can only be applied to a portion of the N flow value. There were several sources used to determine this granularity of application. For livestock sectors the Scottish agricultural census data was used. The total livestock number in heads was divided by the total number of livestock from all sectors and reported as a percentage. Fertiliser use was determined from data within the Agricultural SMT produced by ADAS.

Some measures that include N fixation may not improve NUE but will reduce mineral N inputs.

Current uptake: An estimation of the portion of the relevant N flow that is subject to the impact of the measures. This is subtracted from the overall applicability as the impact is already considered in the current NUE values. In this way double counting of impacts is avoided.

Maximum future impact: Calculated as applicability minus current uptake, multiplied by the impact value. This calculates the impact the measure may have if implemented on all remaining applicable units. The value is then multiplied by the projected future uptake value in each of the time points to produce an estimate for the impact that could be expected.

• Quality Assessment

All data inputs, calculations, and outputs of this task were reviewed internally by the sector experts to ensure robustness and validity. Where possible the results were also compared to peer reviewed literature to ensure that they were consistent with the current scientific understanding.

• Assumptions around SNBS

There is no flow that relates to N from soil into grass, so impacts on this could not be quantified in the SNBS.

Crop residue N is recycled within the system. Therefore, this flow is not considered in the NUE calculations in the SNBS, and so any impacts to crop residue N due to implementation of measures will not be reflected in an improvement to NUE. To compensate for this, improvements to crop residue N was modelled as a reduction in N inputs from fertilisers.

There is around 30kt N unaccounted for through livestock flows. This is perhaps accounted for in what is considered in the report as ‘stocks’ – i.e. an amount of N in living livestock at any one time.

Appendix F: Description of measures and assumptions

In the following tables, where the source is given as “other CXC paper” this is referring to the paper Eory, V., et al. (2023) and “MACC Update” refers to the paper Eory V., et al. (2015).

• Preventing soil compaction

Approximately 20% of arable land in Scotland is susceptible to soil compaction and is therefore eligible to have compaction prevention applied. This measure is expected to increase yields and crop residue N, and so is assumed to reduce mineral N requirements.

• Optimal soil pH

This measure involves applying lime to soils to ensure that soil pH is in the optimal range for N availability. This means that when applying N fertilisers there will be less excess N as it will be more bioavailable and taken up by crops. This has been found to increase crop residue N and yield, both by 6%, while reducing the emission of N₂O by 3%, in arable and grassland. It has previously been assumed that approximately 9% of arable land and 22% grassland are applicable to have pH optimised.

• Use of catch/cover crops

Catch/cover crops are non-productive plants cultivated between catch crops with the effect of taking up excess N that was left in soil, having not been taken up by the preceding cash crop. This reduces the amount of N (in the form of NO₃^– ) that is lost in leaching by 45%. The applicability of this measure to crops has previously been set to 34%.

• Variable rate nitrogen application

Variable rate nitrogen application (VRNT) is where a digital map or real-time sensors supports a decision tool that calculates the N needs of the plants, transfers the information to a controller, which adjusts the spreading rate (Barnes et al. 2017). This measure is applicable to all land that receives fertiliser. 2-22% of farms use precision farming technologies and 16% used variable rate application, though only 11% use yield mapping (25% cereal farms, 18% other crop farms, 5% pig/poultry and dairy farms, 2% grazing livestock farms, 11% mixed farms). This measure can increase yield, reduce fertiliser use rates, and increase crop residue N. As with all measures yield is kept constant with current levels, and crop residue N is considered through a decrease in N fertilisation. Therefore, this measure is modelled as a decrease to N inputs through three mechanisms.

• Urease Inhibitors

Urease inhibitors slow down the hydrolysis of urea to ammonia when urea-based fertilisers are applied to soils, reducing ammonia emissions and increasing the N available to plants.

• Nitrification Inhibitor

• Improved Nutrition

Improving the nutrition of livestock can involve matching N in feed to the needs of the animal, improving the availability of N in the feed to animal, improving the digestibility of the feed so that more N is utilised by the animal and converted to liveweight. This can reduce N inputs and/or reduce N losses while keeping useful N outputs constant, and so increases NUE. From previous modelling of this measure in Scotland it was found that the N content of feed could be reduced by 2% in beef, poultry, and dairy, while excreted N could be reduced by 5% in pigs and 2% in sheep. The applicability of this measure for each livestock type is based on the proportion of total livestock units of each livestock type based off the Scottish Agricultural Census. The current uptake is based off data from previous reports modelling this measure in Scotland.

• Improved health

This measure includes eliminating issues including worms, liver fluke, and lameness, increasing the productivity/efficiency of the animals. While in theory 100% of the herd could have improved health (the stance taken in CXC A scenario), an 80% applicability value was chosen, following the assumption in CXC marginal abatement. This will produce a slightly more conservative estimate of the impact on NUE, to allow for not all diseases/health issues that contribute to lower productivity being treatable/eradicated, and a portion of the herd that may already be achieving higher health. Previous studies focusing on improving livestock health to mitigate nutrient loss, greenhouse gas loss etc. focused on the mechanism of increased productivity. Therefore, as we are keeping yields constant in this model the increased productivity is factored in as a reduction in feed inputs. 

• Livestock Genetics

Livestock genetics techniques can be used with various goals including increasing productivity, climate resilience, or reducing emissions. For improving NUE of livestock systems the key goal is increasing efficiency i.e. increasing the utilisation of N and yield of livestock products, compared to the feed N intake levels. The uptake of using better genetic material is only around 20-25% in the dairy herd, and still lower in the beef herd (Defra 2018). The outcomes of this measure will depend on the breeding tools used and the breeding goal chosen. Three more specific measures have been gathered from the literature, and their potential impact on NUE has been modelled. These are:

• Increased uptake of the current approach in the dairy herd,
• Using the current breeding goals but enhancing the selection process by using genomic tools, in dairy and beef,
• New breeding goals to include lower GHG emissions, using genomic tools.

In 2018 usage of improved genetic material was reported as 20-25% in the dairy herd, and less in the beef herd. However, several previous projects modelling similar measures set the current uptake at 0% of both dairy and beef herds.

• Slurry acidification

Livestock excreta is susceptible to N volatilization, leading to losses to the atmosphere using storage, and leaching during spreading. Acidification of slurry can immobilize the N and reduce these losses. The impact of acidification is largely measured and reported in reductions to emissions, however, as the emissions values are not considered in the NUE calculations this has to be transformed to an impact on inputs. Higher N in slurry will increase yields/maintain yields with lower inputs. Therefore, in this model we include the impact of slurry acidification as a reduced input of N to land receiving fertiliser.

• Slurry store cover

Based on an impermeable slurry cover. Impact and uptake values taken from previous CXC paper. The flow in the SNBS does not distinguish between NH₃ emissions from housing and spreading and N₂O emissions from animal husbandry in general. The portion of each of these gaseous emissions was then extrapolated from the SMT. An impermeable cover is applicable to 100% of slurry tanks and lagoons as there is no available uptake data.

• Low Emission Housing

Acid air scrubbers can remove nitrogen from air, reducing NH3 emissions, which can then be applied to soils as N fertiliser, and essentially recovering more N in useful outputs by reducing waste N in emissions. Approximately 90% of recovered N can be reinput into the soil. The removal efficiency depends on the specific machinery used and approximately 90% can be expected for acid air scrubbers.

• Novel Crops

Novel crops (crops with improved NUE) is designed to reflect the impact of growing new cultivars of crops that can maintain (or improve yields) with a lower requirement for N inputs as fertiliser. Previous

• Rapid Incorporation

• General Assumptions:
• Take the total inputs and subtract the total loss to atmosphere as NH₃ and loss to run off and leaching
• Maybe assume that N₂ and NOx stay constant, NH₃ and N₂O, estimate the losses and subtract from inputs
• Ignore crop residue N, check how this impacts flow
• Increased N fixation will lead to reduced mineral fertiliser inputs, balance out
• Reduced losses (N₂O, NH₃, leaching) will reduce inputs in equal amounts (may need to apply a percentage to this, as farmers may only reduce inputs by 80%, may have to look into the literature)
• Maintain yield (useful outputs), and so any change to output will be modelled as a change to inputs. This is based on the principle that there will be economic drivers at play that will mean on a Scotland wide scale production levels will be maintained, and so if there is a yield increase/decrease on one farm this will be balanced out by the converse on a different farm. Any yield increase/decrease will be felt as the converse in inputs – feed, fertiliser etc. will be reduced in line with the estimated increase of milk, liveweight, crop, etc.
• All legume measures will not impact NUE as any saving in N fertilisation will be balanced by increased biological fixation.
• Assumed that legumes are included once in every five years. Therefore, a fertiliser saving is felt in two of every five years and so impacts 40% of the mineral fertiliser input to crops flow (one year (20%) will be saved from the legume cycle, and one year (20%) from the subsequent crop year due to residual soil N).
• Within the SNBS, nitrogen flows to or from livestock pools were given as a single value for all livestock, rather than by type. However, the measures relating to livestock were species-specific (e.g. slurry acidification in dairy slurry and pig slurry). To compensate for this the number of heads of each livestock type (from the Scottish agricultural census) was converted to livestock units, and then the proportion of total livestock amount of each type was calculated and applied to the relevant measures.
• A single flow value is provided in the SNBS for all mineral fertiliser to crops and all mineral fertilisers to grass, however several of the measures only impact a certain type of fertiliser or may have a different impact depending on the type of fertiliser.

Appendix G: SWOT and PESTLE Analysis

The risks and benefits to Scotland from determining a NUE target were determined through giving consideration to numerous avenues of information and data. Evidence gathered following the completion of Task 1 (evidence review) focusing upon risks and benefits of setting NUE targets in other countries were collated and analysed. This was followed by an internal workshop, led by key experts within the agricultural field, to determine the applicability of the information to Scotland, during which time additional risks and benefits were identified. Following the internal Workshop, a more detailed study of the aspirations and trends in agricultural practices set by the Scottish Government was undertaken. The SWOT (strengths, weaknesses, opportunities, threats) and PESTLE (political, economic, sociological, technological, legal and environmental) tables were populated to better understand the complexities of the information gathered by Ricardo, with the analysis tools providing a summary of the risks and benefits of setting a NUE target in Scotland and demonstrating how a range of influences can support or hinder the achievement of a NUE target. The points presented in both the SWOT and PESTLE analysis have varying degrees of severity therefore a judgment on overall supporting and hindering influences cannot be made on the number of points alone.

SWOT

Strengths, weaknesses, opportunities, and threats (SWOT) of setting N-related targets were analysed based on the information gathered on N targets in other countries. We also included analysis of GHG and climate related targets where relevant to increase the body of information. This information was then used to assess applicability of setting a NUE target for Scottish agriculture with the limitation that the analysis was based on N, GHG and climate related rather than NUE specific targets. The SWOT analysis shows a range of influences which can support or hinder the achievement of a NUE target.

PESTLE

Setting NUE and other N targets are subject to a range of enablers and barriers. Therefore, a political, economic, social, technical, legal, and environmental (PESTLE) analysis was undertaken to assess the feasibility of setting a NUE target for Scottish agriculture, again, with the limitation that the analysis was based on N, GHG and climate related rather than NUE specific targets. The PESTLE assessment took place following the SWOT analysis to ensure the findings from the SWOT were assessed and, if relevant, included into the PESTLE categories.

Appendix H: Worked example

To aid in understanding the approach taken to calculate the impact of each measure on the NUE worked example, for slurry acidification has been presented below.

Slurry acidification can reduce the NH₃ volatilisation at the storage stage by 75% for dairy, beef and pigs. It will also reduce N₂O at the spreading stage by 23%. This measure cannot be applied on all managed livestock manure, and can be applied only where slurry is stored in tanks. Approximately, 41%, 4%, and 38% of dairy, beef, and pig excreta is on a slurry system, respectively, and approximately 50% is in slurry tanks rather than lagoons, for each livestock type. Therefore, this measure can be applied to approximately, 21%, 2%, and 19% of all dairy, beef, and pig excreta.

The relevant flows with the SNBS for these two impact values are N2O emissions from animal husbandry (including manure management), with a value of 0.92 kt N yr^-1, and NH3 from housing and storage of manure, with a value of 10.5 kt N yr^-1.

These flow values represent the absolute quantity of N transferring from the excreta pool to the atmosphere, for all livestock and storage types. Of total livestock units in Scotland, approximately 42% are beef, 11% are dairy, and 12% are pigs.

The uptake levels of this measure in 2030 is estimated to be 7%.

The current uptake is assumed to 0%.

The applicability of this measure on dairy is:

Portion of livestock that are dairy animals * portion of dairy excreta suitable for acidification

0.11 * 0.21

= 0.0228

Therefore, the impact of slurry acidification on the dairy sector is:

Applicability * (1-Current Uptake) * Impact Value * 2030 Uptake

0.0228 * (1-0.00) * -0.75 * 0.07

= -0.12%

Apply this to the absolute value for dairy from the SNBS:

10.5 * 0.0012

= 0.0126 kt N yr^-1

This calculation is carried out for all three livestock types, and for the N2O value. The total N saved is 0.03 kt N yr^-1, which is subtracted from the quantity of mineral fertiliser applied to soils:

143.78 – 0.03

= 143.74 kt N yr^-1

The NUE is recalculated taking into account the new mineral fertiliser quantity:

(Inputs / Outputs) * 100

(200.08 / 54.48) * 100

= 27.23%

© The University of Edinburgh, 2024
Prepared by Ricardo PLC 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, 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.

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. 
   

   N waste is reactive nitrogen (Nr) that is not used in the nitrogen cycle. Higher N waste reduces NUE. ↑

   
   
2. 
   

   The 2021 total is an adjusted total to consider compliance, meaning the contribution of emissions from non-manure digestate spreading is removed ↑

   
   
3. 
   

   A NVZ designation limits the total amount of N (from livestock manure) that can be applied to agricultural land in that area. Scottish NVZ designation is reviewed every four years and nitrate concentrations in surface and ground water are measured by The Scottish Environment Protection Agency (SEPA). ↑

   
   
4. 
   

   N fertilisers are used most commonly in the forms of ammonium nitrate and to a lesser extent urea both as a solid prill (pellet) which is spread using a broadcast spreader. ↑

   
   

Research completed October 2023

DOI: http://dx.doi.org/10.7488/era/5005

Executive summary

Introduction

Land use transformation (and related reductions in greenhouse gas emissions) will be necessary to achieve Scotland’s ambitions to reach net zero emissions by 2045 as well as biodiversity and climate change targets. A variety of support systems for land use transformation, such as financial support and advice, are already in place. This study aims to understand how and why land managers engage, or not, with these support systems. This helps inform how policy could be best deployed to accelerate the process of change.

Influences on land manager decision making

We found substantial evidence for land manager behaviour and decision making that influences engagement with support systems. Their decisions are determined by a range of interacting internal and external factors, primarily related to financial, practical and cultural influences, which can be enabling or restricting, such as:

• personal values and knowledge
• perceived loss of control
• social norms/pressures
• trust in sources of information and advice e.g. land agents
• administrative burdens/transaction costs
• financial incentives
• awareness and understanding
• clarity of the benefits of change.

Restrictive barriers are compounded by context specific factors that vary across individual businesses, such as tenure, business scale and biophysical constraints.

Findings

Overall, the public sector grant-giving support network is logical to use. Most schemes are accessed through the Rural Payments and Inspections Division (RPID) portal. Other schemes are straightforward with regard to procedures. The RPID portal only requires one set of login credentials to access a wide range of support systems. Support systems under this umbrella are easy to access and do not require additional login credentials.

The administrative burden associated with applying to schemes, i.e. form filling, is a barrier to engagement. Procedural support (i.e. form filling by an adviser) is widely available from both public and private advisory sources but requires additional resource to procure. This is distinct from practical support, such as site-specific implementation advice, which was frequently mentioned by stakeholders as key to facilitating the uptake of environmental management practices and yet less readily available.

Land managers often decide whether to engage with support and advice based on confidence in its source. For example, farmers are more likely to trust advisers or organisations that have a background in practical farming over those from a consulting or academic background.

Land managers in Scotland primarily access public funding support. Some access private finance to supplement their income or achieve specific goals. Those accessing private finance generally do it to avoid the conditionality of public funding support and retain operational control over the management of their land. Combining Agri-Environment Schemes and e.g. the Peatland Code is perceived as overly cumbersome, with interactions between schemes, different application dates and the need to demonstrate additionality proving complex.

The breadth of support sources is confusing for some land managers. Better alignment, or at least signposting between sources, would be helpful. Ideally this needs to be via people as well as (rather than just) an online portal. This will enable land managers to choose the correct support more readily, according to their own circumstances.

Applicants would prefer administrative simplicity and greater flexibility. Therefore, efforts to streamline application and monitoring processes, reduce information burdens, widen application windows and vary contract lengths, are justifiable.

Administrative touch points and contractual constraints are only one influence on land manager behaviour. Improved accessibility and flexibility will not, by themselves, increase overall engagement with land use change. Other measures will also be needed such as attractive payment rates, sufficient technical advice and training, and management flexibility. Further research from workshops with potential support recipients, ideally out of peak summer work season, would help understand how future engagement can be maximised.

Abbreviations table

Introduction

Rural land use in Scotland directly supports the national economy, rural communities, and local businesses. Sustainable land use holds a key role delivering Scotland’s biodiversity goals and response to climate change. Agriculture is the second largest source of greenhouse gas emissions in Scotland, behind the transport sector, with emissions largely coming from livestock and soils.^[1] In order to achieve biodiversity recovery and climate mitigation and adaptation, agricultural transformation is required to reduce emissions, and capture carbon in vegetation and soils. A continued, long-term expansion and integration of regenerative agriculture, afforestation and peatland restoration will be necessary and is currently underway as part of the plan to achieve Scotland’s net zero targets.

This research was undertaken to gain a better understanding of the key influences that have a bearing on land manager decision making, including their motivations, what they want to achieve for their operation and their appetite for change.

The aims of the project were to map current support services across different land use sectors to inform our understanding of a land manager’s ability to make decisions and access funding and advice for different land uses. One of the key influences on land manager decision making is their awareness and engagement with support systems. “Support systems”, for the purpose of this report, refers to all sources of support that a land manager in Scotland could access to aid their management of their operation. This includes the following sources:

• Public funding support (e.g. Agri-Environment Climate Scheme (AECS))
• Private funding support (e.g. Woodland Carbon Code (WCC))
• Procedural and practical support from advisors, both public and private (e.g. Farm Advisory Service (FAS))
• Informal networks (Family, friends, and peers)

We looked at availability and links between existing and relevant land use information systems, support services, and current incentives for land use transformation which are directly related to achieving Net Zero and/or nature restoration.

Through stakeholder interviews and other evidence, we established where, when and how different rural land managers interact with the systems and services; we then collated the evidence for issues and barriers to access them. The results are presented using SWOT and PESTLES analysis, conclusions, and visualisations.

When we defined “land manager” we focussed our research on managers of agricultural land, including moorland, peatland and forestry, whether that be farmers, crofters, large estates or organisations such as NGOs.

Understanding land manager behaviour in relation to their awareness of, and drivers of actions that support (or not) environmental outcomes is complex. Decisions and outcomes in this area are a result of multiple interactions between agronomic, cultural, social and psychological factors, all of which sit within the national, regional and specific site context (Mills et al, 2016). Therefore, understanding land manager engagement with current support systems will prove equally complex.

To further our understanding, we carried out an evidence review of the literature. This informed the design of typical land manger archetypes to facilitate the analysis of how specific sectors in Scotland are engaging and accessing support systems. Please see Table 6 in Appendix B for the longlist of archetypes. The long list was used to gather further data, through stakeholder interviews, from both support providers and receivers, across the spectrum of land manager sectors in Scotland. Twenty-five stakeholder interviews were conducted, with participants ranging from support recipients such as crofters and farmers, to support providers and academics. Views from the agriculture, forestry and peatland sectors were captured. Attitudes relating to land managers’ ability and willingness to engage with support systems as well as what determines the level of engagement with these systems were explored. This included the types of support available, their pros and cons, as well as whether they were felt to be accessible, credible and available.

Reflecting its relative prominence within public expenditure and land-based businesses in rural areas, agriculture dominates much of published literature on land-use support. This evidence was supplemented by feedback from stakeholder interviewees, including individuals representing other sectors. The final step was to map the experience of six chosen, prioritised, archetypes in more detail. These are presented in section 6.2.

Full details of our methodology can be found in Appendix A-D.

This study included:

• Carrying out a rapid literature review. (methodology in Appendix D)
• Identifying and mapping the most prominent existing and relevant land use information systems, support services and the current incentives for land use transformation directly related to achieving Net Zero and/or nature restoration. (Appendix A)
• Developing typologies for land managers who might engage with these systems. (Appendix B)
• Agreeing a discussion guide (see Appendix C) for semi-structured interviews.
• Identifying a list of target candidate interviewees who were chosen to represent recipients of support, providers of information and advice, and academic experts. (Appendix C)
• Analysis of where, when, and how land managers interact with the systems and services.
• Presentation of evidence for issues and barriers to access these systems and services from the stakeholder interviews.

Introduction to land manager decision making

The literature is consistent in reporting that land manager decision making, regarding the use and management of their land, and therefore support system engagement, is influenced by both internal and external factors which combine to create individual circumstances. (Buamgart-Getz et al. 2012; Mills et al. 2016; Barnes et al. 2021; Conti et al. 2021; Thompson et al. 2021a).

These factors affect a land manager’s willingness and ability to adopt environmental management practices. The importance of this is underlined by the fact that climate is the most important element of agricultural productivity in many instances (Scottish Government, 2012). Therefore, once bio-physical conditions (an external factor in itself) have determined what management measures are suitable for a land manager, the wider range of internal/external factors will influence engagement with specific support systems offering funding, information, advice, and training. Table 1 below displays the different internal and external factors that influence land manager decision making, as identified by Thompson et al. (2021a).

Table 1 – Internal and external factors influencing land manager decision making – (adapted from Thompson et al. (2021a)).

The way these factors affect and interplay with land manager willingness – and their ability to adopt environmental practices – are shown in Figure 1 (after Mills et al. (2016)). For example, a land manager with limited resources, reliant on informal networks of support, with a strong anti-change personal attitude is unlikely to engage with environmental practices and support systems. Another land manager with higher access to finance, human and social capital, more formalised support networks and a positive outlook on environmental practices would be more likely to engage.

Figure 1 – Factors influencing land manager engagement, willingness and ability to adopt (from Mills et al. 2016).

These examples are clearly extreme ends of the spectrum. Landowners will all have a unique set of factors that influence their decision making when it comes to adopting environmental practices and engaging with specific support systems. It is for this reason that understanding and predicting land manager environmental behaviour and engagement with support systems is complex.

It is important to note that most of the literature on the subject of land manager engagement/motivations with support systems focuses on farmers. For example, (Sutherland et al. 2011) who state “research into actor influences on land use change (attitudes, motivations and objectives held by individuals and groups) has traditionally focused on single sectors, particularly farming. Neither is the range of landholding entities addressed, as emphasis is typically on private owners.”

Some studies (Ambrose-Oji, 2019; Tyllianakis et al. 2023) have explored wider land manager engagement with support systems in detail, however the focus in the academic literature remains centred on farmers. The reasons behind this focus are not currently clear, but it may be due to the large engagement of the agricultural industry with support systems, particularly financial support.

We have attempted to fill this gap in the literature through targeted stakeholder interviews with individuals representing land managers outside, as well as within, the agricultural industry.

Our evidence review has suggested that engagement with current support systems is primarily influenced by certain personal values and knowledge, perceived loss of control, excessive administrative burdens/transaction costs, a lack of credible financial incentives, a lack of awareness, understanding and clarity of the benefits of certain support schemes and social norms/pressures. These barriers are then further compounded by context specific factors that vary across individual businesses, such as tenure, business scale and biophysical constraints.

Land manager engagement with support systems is discussed in more detail in Section 6

Review of support systems

The next stage of this study attempted to identify the current land use support systems that land managers are engaging with in Scotland. This allowed us to map current support services across sectors in Scotland. Once we established the variety of support systems, we could begin to understand how land managers are interacting and engaging with these systems, whilst identifying key barriers and opportunities that could be used to inform future policy support.

We achieved this by firstly identifying a range of typical land manager archetypes in Scotland, followed by a review of all visible support systems identified through academic and grey literature review.

More detail on the types of support available is given in Appendix A Support in terms of funding is available from Government and the Private sector. Advice and information can be sought from direct Government sources plus third-party sources funded by Government (e.g. the Farm Advisory Service) but also independent third-party provision. Third sector, charities and Non-Governmental Organisations also provide landowners with advice and funding to undertake measures that align with their objectives.

Initial land use support system mapping

The infographic on the following page (Figure 2) displays a high-level mapping overview of the current land use support systems in Scotland and the extent to which land managers are engaging with each. Most land managers engage with government agency support and funding, with agricultural land managers doing this to a greater extent. This is mostly limited to schemes such as BPS and LFASS as these offer large rewards for less administrative actions compared to other schemes, such as AECS. Other land managers are more likely to be engaging with corporate buyers and private sector sources of support, such as emerging natural capital opportunities.

Figure 2 demonstrates clearly that the land manager support network in Scotland is a complex entity, with different land managers drawing from a wide range of support sources. Whilst it has not been possible to quantify the exact support flows between support providers and support receivers, we have provided an indication of the overall network and flow of support in Scottish Agriculture, helping us map current land manager engagement with support systems.

Figure 2 – Land use support system providers in Scotland. Source: Adapted from Sutherland et al. (2023)

Stakeholder views on engagement with support systems

It was recognised from the outset that the results of the evidence review must be calibrated against the lived experience of key stakeholders. We were able to conduct 25 interviews, and had scheduled to supplement this with additional workshops, but it proved very difficult to gain substantive input from planned workshops due to the timing overlap with the peak summer workload alongside harvesting.

We have captured the results of the stakeholder feedback below. This should be read alongside the review of the literature which is presented in section 7. Whilst there are significant similarities between the evidence from the literature review and stakeholder perceptions from the interviews, we recognise that this evidence would be usefully supplemented by a more in-depth form of action research with a wider stakeholder group, in particular potential support recipients, which would help to deliver more substantive results.

Factors influencing land managers’ decisions.

Stakeholder interviewees identified many factors influencing the ability and willingness of land managers to change management practices and/or land use patterns. Although varying in terms of emphasis and specific examples offered, there was a high degree of agreement across stakeholders (and consistency with the literature) regarding the main categories of (interacting) influences, which can be summarized as follows:

Confidence and understanding

Land management involves a range of tasks requiring both practical skills (e.g. handling livestock and machinery) but also organizational (e.g. resource allocation) and strategic (e.g. business planning). Changing land management practices and/or land use patterns requires expanding this skill set. However, not all land managers currently have the necessary skills, leading to many having a low understanding of how to change and low confidence in abilities to change successfully. Conflicting messages about the definitions, relative merits and compatibility of different practices (e.g. afforestation, regenerative agriculture) cause significant confusion, reinforcing an underlying wariness of changing unnecessarily.

Indeed, stakeholders were concerned that basic awareness amongst many land managers of requirements for change under both future agricultural policy, but also private supply-chain pressures, is still very low. Clearer and more consistent messaging from government and industry leaders would help, particularly if it was accompanied by more detail on practical support measures, including funding levels, the provision of information, advice and training, and any implications for future eligibility for land-related tax breaks and other public funding sources.

Resource constraints

Although any given parcel of land can be used for a variety of purposes, its underlying natural capital and biophysical characteristics (e.g. climate, topography, soils) exert a significant influence over its inherent suitability for different uses. Consequently, land managers do not all face the same land use possibilities to deliver particular ecosystem services. The Less Favoured Area (LFA) designation recognizes this in agricultural production terms but variation in suitability to deliver other ecosystem services is also recognized through various environmental designations (and indeed spatial targeting of agri-environment measures).

Farm type provides a convenient, albeit crude, indicator of likely flexibility in agricultural land use, with many hill and upland livestock farms being particularly constrained. The JHI Agricultural Land Capability Map (and equally the forestry suitability map) offers a more refined indication, but greater use of maps to categorise potential to deliver wider, environmental services would be helpful. For example, High Nature Value (HNV) farming.

Beyond biophysical constraints, farm businesses are also constrained by the availability and quality of other resources – in particular, working capital, equipment and labour. Stakeholders stressed that many farm businesses operate on very slim margins and are risk averse, limiting the scope for experimentation and investment in new management practices or forms of land use. Financial support can help to overcome this, as can support scheme contracts’ length and flexibility. However, labour scarcity and the relentless nature of farming often leave little spare time to devote to engaging with the process of change.

Geographical remoteness and/or poor communications connectivity can add further challenges. So can small scale – smaller businesses with fewer resources (especially labour) typically lack both the economies of scale and flexibility available to larger businesses to accommodate/experiment with change. This limits their ability to be creative and do something different. Some larger businesses have recruited in-house expertise and/or they directly commission academic and other consultants, particularly in relation to emerging nature-based solutions and rewilding exercises.

Transaction costs

The transaction costs of seeking information, advice, training, and external funding to implement change can be significant. To make it easy for all applicants, sources of information, advice, training and funding should be easy to locate. Administrative processes for applications, monitoring and reporting should be simple and accessible, including in their choice of language and terminology.

Stakeholders acknowledged that accountability for public expenditure necessarily requires a degree of bureaucratic oversight. However, they expressed concern that the complexity of some funding schemes^[2] was a deterrent to some applicants, including those with little spare time and/or an unfamiliarity with administrative processes. This phenomenon was described as ‘form anxiety’. The difficulties of coordinating across multiple sources of information, advice and training were recognized, and it was suggested that clearer signposting and the use of one-stop-shops would be welcome.

Smaller businesses lacking the staff and/or finance to hire specialist advisors may be particularly affected by transaction costs, facing a proportionately greater burden than larger businesses. For example, there is often a fixed cost element to application processes regardless of the level of funding sought and having to seek information directly rather than being able to delegate to staff can have a high opportunity cost.

Tenure

Farm tenure exerts a direct influence over land managers’ ability to undertake change, particularly between different land uses. Specifically, whilst owner-occupiers have the freedom to choose how they manage their land, tenants are constrained by the terms of their lease. The degree of restriction varies across different types (e.g. length) of tenancy, with crofting tenure adding some further complexities, particularly in relation to common grazing.

In most cases, agricultural tenancies restrict the range of land use activities permitted. For example, afforestation and non-agricultural enterprises are typically precluded from leases by default (although may be agreed via negotiation). Moreover, non-agriculturally productive parcels of land (e.g. pre-existing woodland, riparian habitats) are often excluded from the area covered by a lease. Consequently, the ability of many tenants to implement and benefit from land use change is currently constrained.

However, some stakeholders believed that the issues around tenure constraints had become better understood in recent years and were hopeful that the forthcoming Agriculture Bill would address many of them.

Motivations and norms

Beyond the practical constraints suggested above that influence a land manager’s ability to change, willingness to change is also affected by various factors. In particular, by an individual land manager’s attitude towards and motivation for land management and by cultural norms held by family, friends and peer groups.

Land managers need to perceive how change fits with business viability and continuity. Some land managers (e.g. rewilding estates, NGOs) may be motivated to undertake change primarily by seeking environmental improvements. Others may be more motivated by the traditional farming values centred around food production, and they be more fundamentally opposed to activities perceived as incompatible with growing or rearing consumable produce. The latter is particularly relevant to debates around afforestation and (to a lesser extent) peatland restoration.

Many land managers are starting from a mainstream farming perspective, although not all are; other groups are perhaps more open to change such as community groups, foresters and horticultural producers. Stakeholders suggested that variation in willingness to change was likely to be significant across the full population of land managers and would complicate any targeting of encouragement to change.

Stakeholders also noted that willingness to change could ultimately be influenced by financial pressures, whether via public finding or market signals, but that sustainable change would require cultural shifts – winning hearts and minds. This implies a need for clear industry leadership backed-up by the provision of information, advice and training plus (probably) encouragement for generational renewal. Negative perceptions of bureaucracy and of support payments simply flowing to advisers (a ‘consultants charter’) are widespread.

Types and sources of support

Stakeholders identified different types of support for land managers, distinguishing funding from other forms of support.^[3]

Funding

Funding was further divided into public and private, although the emphasis was very much upon public funding. Public funding for land management is dominated by agricultural support, notably decoupled area payments plus limited voluntary coupled support. Significant funding is also available for forestry and peatland restoration, plus wider agri-environmental schemes, innovation funds and various capital grant schemes. Public funding is also available to land-based businesses from other sources, such as the Enterprise Networks (see Table 2 for listing).

Stakeholders regarded public funding as essential to achieving management and land use change; in particular to offer financial incentives (or at least reduce disincentives) to make change worthwhile and to encourage any necessary capital investments. However, it was noted that inflation continues to erode the real terms value of public funding, decreasing the leverage that it has over management decisions.

Private funding for changing land management is also available. For example, there are high-profile cases of new and large landowners essentially self-funding and/or harnessing emerging environmental funding mechanisms. The latter include the Woodland Carbon Code and the Peatland Code.

However, the accessibility of such mechanisms to all land managers (e.g. tenants, common grazing, smaller holdings, community owners) is imperfect. Moreover, considerable uncertainty exists over the future value of carbon credits, and the possibility of claims over them by downstream supply-chain partners. Consequently, notwithstanding Scottish Government aspirations to increase private funding, stakeholders expressed some scepticism about the potential of private funding to replace public funding.

Non-funding support

Stakeholders also sub-divided non-funding support, into procedural support to help land managers navigate bureaucratic processes (e.g. advice on how to complete application forms, enrol in training programmes) and support to help with actual activities on-the-ground (e.g. training in new management practices). Both were regarded as necessary, but the degree of procedural support required relates back to concerns about transaction costs.

Procedural support tends to either take the form of information and general advice provided by the source of any funding, or the form of professional assistance to comply with application and reporting processes. For example, public funding is accompanied by online (and sometimes print) public guidance material plus online, phone and (sometimes) face-to-face advice on (e.g.) eligibility criteria, payment rates and evidence requirements. Private sources (e.g. land agents, consultants) often mirror this, but also offer further hands-on assistance to gather necessary data and complete paperwork plus more bespoke advice for individual land managers.

Practical support is similarly available in different forms from a variety of sources. Indeed, stakeholders emphasized the huge variety of forms and sources (see Table 2 for listing). For example, information is available via print and social media from public (e.g. Scottish Government, NatureScot, SEPA, Universities), private (e.g., levy bodies, consultants, input suppliers) and third-sector (e.g. NGOs) providers and advice can be offered one-to-one or one-to-many^[4] either online or face-to-face. Moreover, face-to-face may involve a simple meeting or a site visit or demonstration. Vocational training (e.g. via Lantra or colleges) tends to involve face-to-face events, but online training can suit some strategic and planning type skills development. Stakeholders suggested that the breadth of support sources was confusing for some land managers and better alignment or at least signposting between sources would be helpful, although signposting ideally needs to be via people as well as (rather than just) an online portal, for land managers to define the correct source of support for their own individual circumstances.

Importantly, stakeholders also stressed the role of informal sources of information and advice. For example, family and friends plus unrelated business professionals (e.g. accountants, vets). Peer group networks (local but also international) of like-minded people can also be important – indeed some stakeholders identified these as particularly relevant for emerging practices such regenerative agriculture and agro-forestry which some stakeholders regarded as not well-served by more formal support mechanisms. Peer networking can be encouraged through trained facilitators and funding.

Availability, accessibility and relevance

Uptake of information, advice and training requires land managers to trust the source and to see the relevance of what is being offered. This poses a demand-side challenge in persuading land managers of the need for change and relates back to points made above regarding the need for clear, consistent messaging from government and industry leaders to set the tone – particularly in relation to strategic business skills and new technical skills.

However, it also poses supply-side challenges in terms of the availability and accessibility of information, advice and training. Government only has leverage of this through either direct provision itself, or funding of third parties to provide support. Stakeholders noted that availability was already patchy geographically and in terms of specialist topics. Moreover, they were not confident that public funding levels would be sufficient to cover all future requirements – implying a need to prioritise particular topics or groups of land managers, and/or to rely more upon online and one-to-many methods (despite experiential, hands-on learning being viewed as more effective).

Citing diminishing returns and the 80/20 rule^[5], some questioned the merits of trying to accommodate all ‘hard to reach’ groups (e.g. smaller producers, new entrants, women, the very young, those with poor mental health). However, the Women in Agriculture initiative was cited as a good example of targeting.

Furthermore, even if future funding was sufficient, stakeholders were not confident that sufficient appropriate advisors would be available in the short-term. Trust depends on perceived credibility and, rightly or wrongly, in many cases this requires advisors to have agricultural backgrounds – yet the types of management and land use changes required extend beyond agriculture. This implies a need to upskill existing advisors but also to recruit advisors from different backgrounds – either to work in teams or (hopefully) to be accepted as credible by land managers.

Stakeholders offered a variety of solutions to this problem, including allowing the Farm Advisory Service (FAS) to evolve in terms of its modes of operation and topic overage but also to sub-contract other independent and/or specialist advisers (including existing land managers) as appropriate. Deployment of RPID staff to offer advice as well as conducting inspections was also suggested, reminiscent of previous policy eras and also, to some extent, emulating more recent practice in forestry and catchment management.

The use of facilitators rather than advisors was supported by some stakeholders, reflecting (possibly) easier recruitment (technical expertise is less essential than people skills) and perceived advantages of facilitated experiential learning rather than expert instruction.

It was also suggested that advisors should be included more formally in policy design and monitoring processes since they are well placed to offer insights into how ideas will be received and implemented on-the-ground. It was noted that total formal advisory capacity includes those working for input (e.g. seed, feed, fertiliser) suppliers as well as those aligned with FAS or working independently.^[6]

Table 2 – Cited examples of support

Land manager experiences of support systems

As part of this research project, we attempted to identify and map all existing and relevant land use information systems, support services and the current incentives for land use transformation directly related to achieving Net Zero and/or nature restoration. An outline of all the support schemes identified can be found in Appendix A. We then collected additional information on a sub-set of current support systems administered by the Scottish Government, to explore specific touch points for land managers. To frame this exercise, we firstly mapped the main agencies within the Scottish government that are responsible for the relevant land manager support systems (Figure 3).

Figure 3 underlines that multiple agencies are responsible for providing and administrating support to land managers in Scotland. This has the effect of increasing administrative burdens for land managers if systems across agencies are not in sync in terms of data collection and system operation.

Figure 3 – Agencies responsible for land manager support in Scottish Government

Insights from the literature

We can gain significant insight from published grey literature about where, when, and how land managers interact with support systems and services. There are three highly relevant published pieces of work. The first is the RPID customer satisfaction survey (RPID, 2021), where RPID customers gave their views on the application process and how it could be improved. 2147 customers filled in this survey, providing a robust sample size to gather insights from. The second piece of work is the NatureScot Research Report 1254 (NatureScot, 2021), where biodiversity outcomes were evaluated. This included a quick survey of applicants’ views on the application process. The third piece of work is ‘Doing Better Initiative to Reduce Red Tape for Farmers & Rural Land Managers’ (SRUC, 2014) where regulations (or their implementation) that impinge on business decisions were identified and solutions were put forward to address these.

Administrative burdens

The general literature review (reported in Section 7) and Stakeholder views (reported in Section 5) revealed that the administrative burden and ‘form anxiety’ associated with support schemes can significantly affect land manager engagement with support systems.

We can relate this to the RPID survey responses, in particular the question ‘Applications made to other schemes in the last twelve months’. Interestingly, 77% of RPID customers stated that they did not make another application to another non-SAF (Outside BPS, LFASS, AECS, FGS) scheme in the last 12 months.

Groups who had not made another scheme application are compared below:

• More owners (80%) than tenants (74%) and business partners (70%);
• More other businesses (84%) and farms (79%) than crofts (73%);
• More older (84%) than younger (66%) customers; and
• More customers that completed their SAF with support (81%) than those that completed it on their own (74%).

This would suggest that for the majority of RPID customers, the main support systems they are engaging with fall within the bracket of the SAF administrative process. It appears that many land managers are only engaging with SAF and not applying for schemes outwith this (e.g. AECS, Peatland Action etc.). Although it is difficult to draw conclusions from this question alone, the supporting evidence from this report would suggest that the administrative burdens are a considerable factor in preventing land managers from engaging with other support systems outside their SAF application.

For instance, the RPID survey found that a substantial number of RPID customers felt that application processes were too complicated, or the application forms were too long or complicated. When asked what customers’ main reasons for dissatisfaction with information from RPID, the main two reasons given were:

• The application process is too complicated (53%)
• Application forms are too long/complicated (52%)

Furthermore, in the 2013 RPID customer satisfaction survey, the most common reason for dissatisfaction with information from RPID was ‘not enough information being available’ (29%). This suggests that the administrative burden involved with applying for rural funding schemes has become a more significant influence on farmer decisions in the period between 2013-2021.

The challenges of administrative burdens are further reinforced when customers were asked about the ‘aspects of RPID’s performance customers would like to see improved’ where the most popular answer was ‘application forms are easy to complete’ (42%). One respondent was quoted:

“Website and all forms etc. need to be rewritten and simplified. They need to be clear and concise and user friendly. Use words not acronyms. Use far fewer words.”

We find further evidence to support this in SRUC (2014) where a list of recommendations is provided to the Scottish Government on how to reduce red tape burdens placed on farmers and land managers. Recommendation 5 states that an IT system should be developed that reduces the form filling burden for farmers and land managers – reducing administration costs. This recommendation also suggests that a full review of data requests from farmers and land managers is undertaken to ensure that duplication is minimised.

Despite this point being raised in 2014, the findings from the RPID survey suggest that from 2013 to 2021 administrative burdens on land managers applying for government support schemes have increased.

Support required to access funding

There is also substantial evidence that suggests that many land managers in Scotland require support to submit applications to financial support systems. Evidence for this is provided by the RPID survey, where the following three points were cited as the reasons why customers needed some support with their Single Application Form submission:

• Personal (e.g., first time completing form, learning disability) – 43%
• Mistakes (e.g., want to avoid mistakes) – 41%
• Forms (e.g., difficulty accessing forms, take too long to complete) – 34%

This would suggest that many land managers find the current administrative processes involved with submitting applications to support systems a significant barrier to engagement and require support to ensure that they can access these. The response to this question suggests that the current complexity is leading landowners to obtain procedural support to complete their applications.

Of those that are using procedural support to complete applications, SRUC agents are the most common support agents being used (48% of cases). Interestingly, other business (not farmers) used commercial agents to support applications 51% of the time.

Land manager support system mapping

This section presents three infographics (drawn from RPID survey data and our findings from the previous sections of this study) representing the typical land manager pathways to access agricultural support systems in Scotland. Each infographic is broken down into four main sections (from left to right). The first section, motivations, highlights the broad overarching motivations that a land manager is looking to achieve within their business objectives. This includes motivations such as ‘business support’ and ‘woodland establishment’. The following section highlights the agency touchpoints that a land manager will engage with if they decide to follow one or multiple of the previous motivations. This includes both the agency (such as RPID) and the specific scheme that relates to that motivation (such as the Forestry Grant Scheme for Woodland establishment). The third section shows the administrative actions that are associated with engaging with each different support scheme, including information such as what IT system is used (e.g. RPID portal) and if support is generally needed by a third party. The final section details what kind of login credentials are needed for each administrative action and if these are shared or unique for each scheme.

Figure 4 represents all the pathways open to land managers, providing an overview of the support system landscape. Figure 5 highlights the pathways that a typical farming land manager could take. Figure 6 highlights the pathway that a non-farming land manager, such as an estate, could take. The following sub-sections draw out some of the key findings and help understand where, when and how land managers interact with support systems and services.

Figure 4 – land manager support system map

This figure presents an overview of all the motivations, touchpoints and administrative actions that a land manager could undertake if they were to take certain pathways. Key points from this infographic include:

• It appears that land managers only need to have one login credential to access all support services via RPID (Rural Payments and Inspections Division) in Scotland. This is the RPID portal login, where land managers can access the SAF, AECS application, SSBSS & SUSSS form and FGS application. For those schemes not under the umbrella of the RPID portal (Peatland Action), online submissions are required that do not require login credentials (FAS applications still require RPID Business Reference Number however). This would suggest that login credentials do not pose a significant barrier to land manager engagement with support systems.
• Regarding touch points, RPID is the agency that land managers are most likely to be engaging with for funding. This is because the most popular support schemes (BPS, LFASS, AECS etc.) are administrated through this agency. Other support schemes that are not administrated by RPID, such as the Forestry Grant Scheme, are still accessed through the RPID portal. FAS and Peatland Action support schemes are accessed outwith the RPID portal, but require relatively simple administrative inputs to complete.
• Overall, the RPID public sector support system network is administratively logical from a high-level perspective. The majority of schemes are accessed through the RPID portal, and those that are not are procedurally straightforward in terms of required steps. However, the level of detailed information needed by certain schemes makes accessing a wide range of these extremely challenging for some land managers in Scotland (recalling from section 5 that land managers differ widely with respect to skills and confidence to tackle administrative processes and implement management changes). For example, AECS applications are considered very complex due to the level of information that needs to be provided along with the lengthy application form/process. Furthermore, Forestry Grant Scheme applications require a level of detail that is beyond most typical land managers’ (farmers etc.) knowledge, leading to a reliance on external specialists to complete applications.
• On the whole, this would suggest that the complexities in land manager support systems, including the level of detail needed for specific applications are reducing engagement with systems that could encourage improved environmental management practices. This does not take into account private schemes, such as the Woodland Carbon Code, which would only add to this complexity.
• All other things being equal, administrative simplicity is preferable to complexity and (for applicants) greater flexibility is preferred. Hence efforts to, for example, streamline application and monitoring processes, reduce information burdens, widen application windows and vary contract lengths, are justifiable. However, accountability for public expenditure requires a degree of bureaucracy to ensure that funds are disbursed and used as intended, and simplicity and flexibility for applicants may impose additional complexity for administrators. Consequently, there are trade-offs, and the scope for improvements in process design alone will typically be limited.
• This implies that other steps need to be taken to improve accessibility, including the provision of additional procedural information and advice – which necessarily incurs additional public administrative costs, raising familiar questions regarding the appropriate degree of such assistance and whether it should be universal or targeted at specific groups.
• Moreover, administrative touch-points and contractual constraints are only one influence on land manager behaviour, implying that improved accessibility and flexibility will not by itself increase overall engagement with land use change. Other measures will also be needed. For example, attractive payment rates, sufficient technical advice and training, and support for capital investments.

Figure 5 – farmer decision pathway map

This figure presents an indicative pathway through the support systems that would be taken by a land manager (farmer) who does not have any specific environmental goals (woodland establishment, peatland restoration) but would like to improve the efficiency of their operation and reduce their overall impact on the environment. It is important to stress that this pathway is indicative, and it is not intended to represent all farmers in all locations. In reality, as explained in the literature review in section 7 later, all land managers will have a unique set of motivations, barriers and opportunities regarding land management practices that will affect their engagement with support systems. The findings from this infographic are summarised below:

• The majority of farming land managers will be engaging with support systems that are accessed through the SAF process (BPS etc.) as these are familiar and provide a high level of financial support for a relatively small administrative and practical input.
• Land managers of this type could also be engaging with AECS. This provides the land manager with an opportunity to improve the economic performance of their operations, whilst also benefitting the environment. Land managers will often choose options that require the smallest practical/administrative inputs compared to financial returns. Many land managers will require support from a third party to complete their AECS application due to the complexity of information required.
• Many land managers of this type will rely on FAS and other agents, along with informal networks, to provide procedural support to their applications to support systems. This is because farming land managers are often time-poor due to their focus on practical activities on farm, relying on others to assist with the administrative processes of applying to support schemes.

Figure 6 – Non-farmer decision pathway map

This figure presents an indicative pathway through the support systems that would be taken by a land manager (non-farming) who is looking to diversify the use of their land, improving economic and environmental performance simultaneously. Again, it is important to stress that this pathway is indicative, and it is not intended to represent all non-farming land managers in all locations. In reality, as explained in the literature review, all land managers will have a unique set of motivations, barriers and opportunities regarding land management practices that will affect their engagement with support systems. The findings from this infographic are presented below:

• Non-farming land managers are much more likely to engage with a wider range of support systems outwith those administered by RPID. This may be due to a mixture of different beliefs, fewer/different constraints on time and resources and more desire to diversify income streams to ensure financial resilience.
• These land managers still often rely on external specialists to assist with certain elements of the application process, such as external forestry consults when applying for the Forest Grant Scheme.

Figure 4. Land manager support system map

Figure 5 – farmer decision pathway map (N.B. this is indicative and not intended to represent all farmers in all locations.)

Figure 6 – Non-farmer decision pathway map (N.B. this is indicative and not intended to represent all non-farming land managers in all locations.

Land manager attitudes – a review of the literature

Factors affecting engagement with support schemes

The literature review highlighted that internal factors such as attitudes, beliefs and personal values can have a significant impact on engagement with support systems.

Values and knowledge

It was recognised as far back as the 1970’s (Gasson 1973) that farmers do not always make financially rational decisions and that a range of social and intrinsic factors may also be prioritised; risk perception, values and knowledge are particularly influential in business decision making.

Land managers, in particular farmers, generally have a strong sense of self and are often influenced by their intrinsic values. This theme can be explored when looking at land manager attitudes towards planting trees on their land. Historic literature suggests that land managers have a resistance to creating woodland and forests, due to traditional values surrounding the belief that measurable productivity and growth are their traditional core purpose. Burton et al. (2008) explores the importance of the ‘good farmer’ identity, where social status and personal validation is derived by the evidence of delivering a skilled role on landscapes, i.e. livestock farming. Burton (2004) concludes that planting woodland and forest (afforestation), as well as engagement with other non-farming activities, represents both a loss in productive output and a symbolic loss of the opportunity to demonstrate farming skill and knowledge.

Farmers often resist afforestation on this basis, with agriculture and forestry historically being viewed as competitors for land rather than complementary land management practices that could be adopted as a sustainable approach to single proprietary unit diversification (Nicholls, 1969; Hopkins et al. 2017). Therefore, as many farmers perceive themselves to be farmers only, they are unwilling to change their practices due to inherent values that are tied to their current activity. This trend is likely to be seen across most landowners, not just restricted to afforestation, who will possess their own objectives, values and knowledge. For example, Moxey et al. (2021) note that the willingness to participate in peatland restoration schemes is highly variable, and that cultural ties shape attitudes towards restoration activities.

On the other hand, some land managers have intrinsic values that prioritise attempting to balance the need for a productive enterprise and protecting/enhancing the environment. Mills et al., (2017) found that it was common to hear that farmers were attempting to find a balance between production and environmental management, which were not always seen as conflicting needs.

This is reflected by the well documented finding that farmers (and land managers as a whole) are often willing to adopt environmental measures if they are perceived to increase the efficiency of on farm activities and therefore prove cost effective (Feliciano et al. 2014). For example, Farsted et al. (2022) noted that climate mitigation measures are mainly perceived as, treated as, and appreciated for offering farm-beneficial functions other than climate change mitigation by Norwegian farmers. This is also reflected in the Farm Practices Survey (2022) where 44% of farmers thought that reducing emissions would improve farm profitability and that the main motivation for farmers to take action to reduce GHGs on farm was that it was considered good business practice (84%).

Unsurprisingly, those land managers that are personally concerned/motivated to address climate change are more likely to be undertaking environmental management measures on their land. Those who are less engaged are likewise less likely to be undertaking environmental management practices.

Ease of transition, control and risk perception

An important aspect of land manager engagement with support systems is the perceived degree of control afforded by the available schemes and the ease of operational transition.

Academic literature in this area has focused on exploring the barriers that prevent uptake of Agri-Environment Schemes (AES), specifically focusing on schemes that restrict land manager’s ability to control and own the final product that is being delivered. For example, Lampkin et al. (2021) suggest that a top-down prescriptive approach of some AESs has failed to engage farmers in a way that would give them ownership of the delivery of environmental goods. This view is supported by Daxini et al. (2019) who found that the intention to follow a Nutrient Management Plan is primarily driven by perceived behavioural control.

Thompson et al. (2021) further suggest that farmers are more likely to participate in AESs if they retain some control over implementation, which requires flexible terms and regular monitoring. Therefore, it appears an important element of how land managers engage with current support systems involves analysing the degree to which each support system will affect operational control.

Another key internal factor that will influence land manager engagement with support systems is risk perception. Multiple sources suggest that the clarity and certainty of the final objective of any support scheme is important to its uptake and success. Analysis from the James Hutton Institute (Rajagopalan and Kuhfuss, 2017) suggested that the uptake of the Agri-Environment Climate Scheme (AECS) was restricted by the lack of flexibility in options, along with the uncertainty on the environmental outcome due to the influence of external factors outside of the land managers’ control (climate, pests etc.)

Kuhfuss et al. (2018) also suggest the success of AES may vary depending on the clarity of the objectives and perceived challenges in achieving them. For example, afforestation is a relatively easy concept to understand and is generally low risk, however peatland restoration is much more difficult conceptually and is seen as a higher risk option. Indeed, peatland restoration may seem to be of high risk because UK peatlands are at the southern limit in the northern hemisphere and therefore at risk due to anticipated climatic changes.

The tolerance of land manager to the inherent risks that are involved with engaging with support schemes that require alterations in management practices is an important factor in determining uptake.

Socio-demographic, age and education

The traditional view within the literature is that older land managers are less willing to change land management practices and that younger and more educated farmers are more willing to adopt new practices and engage with environmental support schemes. Sutherland et al. 2016; Mills et al. 2016; Brown, 2019)

This is often supported by evidence that younger people have a higher degree of environmental concern, risk tolerance and openness to new practices (Dessart et al. 2019). Therefore, younger land managers may be more able to engage with support systems and understand the requirements and trade-offs involved. Benni et al. (2022) reported that the age and education of farmers was not found to affect time requirements to fill in administrative burdens. This suggests that the transaction costs associated with support systems does not interplay with age and education levels of applicants.

When analysing the factors behind farmers’ adoption of ecological practices, Thompson et al. (2023) found that socio-economic factors were insignificant more often than they were significant. Despite these findings, Tyllianakis and Martin-Ortega (2021) argue that the evidence base suggests that wealthier land managers stand to gain more than less wealthy land managers in enrolling in AESs. The impact of socio-economic and demographic factors on land manager engagement is therefore likely to vary considerably across different sectors and organisational structures.

Engagement and trust of official advice vs. informal networks

Due to the rise of information available (mainly through the expansion of digital services), answers can be found to many real-world and agricultural issues and questions online. Rust et al. (2021) suggest that farmers have previously often relied on in-person advice from traditional ‘experts’, such as agricultural advisors, to inform farm management practices. Sutherland et al. (2013) stress the importance of the perceived credibility of sources of advice. This view is supported by Daxini et al. (2019) who found that trust in technical sources of information (e.g. advisor and discussion group) is found to be a more influential determinant of farmers’ attitude, subjective norm and perceived behavioural control than trust in social information sources (e.g. family and the media).

Nonetheless, Birner et al. (2006) and Sutherland et al. (2022, 2023) highlight the breadth of sources of information, advice and training utilised by land managers, encompassing family and friends, peer groups, accountants, vets, input suppliers, private consultants, NGOs and public sector bodies, accessed in different modes including via print and social media, online, one-to-one meetings, group meetings and events/demonstrations.

This is discussed further by Rust et al. (2021), who suggest that farmers are now changing their information sources due to the rise of online sources of knowledge and advice, foregoing traditional ‘expert’ advice in preference for peer-generated information. They found that farmers regularly use online sources to access soil information and often changed practices based on information from social media. Results from their survey suggested that farmers placed more trust in other farmers and peer networks rather than traditional ‘experts’, particularly those from academic and government institutions, who they believed were not empathetic with the farmers’ needs.

This could be further compounded by many farmers deciding not to engage with advisory services at all. Dunne et al. (2019) found that almost one-third of farmers in Ireland were not using extension services and a further third had contracts with private sector and public sector advisors.

Research from the James Hutton Institute (Hopkins et al. 2020) also found that new entrants to farming are less likely to engage with subsidies and support systems than existing farmers in the sector. In particular, new entrants did not think that the ‘official’ Farm Advisory Service (FAS) and the Scottish Government were helpful when starting their enterprise. This finding is mirrored by Labarthe et al. (2022), who suggest that new entrants to agriculture are often disconnected from knowledge structures, as they often operate businesses that are not typically addressed by advisory services. Other ‘hard to reach’ or less engaged groups can include women farmers and those suffering from poor mental health (Hurley et al. 2022).

Understanding how land managers engage with knowledge networks and their trust of these networks is an important factor in determining their experience of support systems. By improving farmers’ awareness, it is expected that changes in behaviour would be reflected in the adoption of improved management practices. However, Okumah et al. (2021) argue that the limited research in this area so far has shown that the link between awareness and adoption exists. This link is indirect and is mediated and moderated by other factors. Nevertheless, on balance, it seems that hypothetically, with all factors being equal, more awareness is better than less awareness.

Summary

The willingness of land managers to engage with forms of support for changing management practices and land use patterns is influenced by a number of internal factors. These include the compatibility of change with land managers’ self-identify of what it means to be a land manager, particularly a farmer – something that is ingrained and often inter-generational, making it difficult to alter in the short-term. Similarly, inflexible management prescriptions are at odds with cherished decision-making autonomy and change can be perceived as incurring higher than acceptable levels of risk, although attitudes can be softened if prescriptions align with personal or business objectives.

Weak confidence and understanding regarding the purpose and practicalities of change reinforce business-as-usual, with a lack of trust in the credibility and relevance of available sources of information, advice and training further constraining engagement. Such internal factors vary across individual land managers, but there is some evidence that greater openness to change may be associated with (younger) age and (greater) education but also that some groups, including women, new entrants with no prior experience and people suffering from poor mental health, may be further disconnected from support systems.

External factors influencing land manager engagement with support schemes

Alongside the internal factors identified above, there are significant external factors that influence land manager behaviours, including the physical, environmental, business structure, financial, knowledge availability, social norms and time factors on land management.

Funding, costs and policy indicators

As with any business operation, the need to generate revenue to ensure the survival of the business is a high priority for any land manager. The majority of land managers, especially tenants, seek to make a profit from their land. Therefore, financial considerations are paramount to the landowners’ decision-making process, underlining the importance of support schemes and their potential to influence change.

Previous research has indicated that given the unpredictability of agricultural and land-based activities, only when economic conditions were stable could land managers focus on other activities – including environmental considerations (Scottish Government, 2012). Measures that do not guarantee financial benefits – e.g., that may have a negative impact on production or come at a cost to the farmer – are unlikely to be adopted in the absence of other tangible benefits.

In the latest Farm Practices Survey (2022), 32% of farmers who were already taking actions to reduce GHG emissions stated that environmental measures were too expensive to implement. This may explain why Ruto and Garrod (2009) found payment rates to be a key driver and Pineiro et al. (2021) conclude that interventions that lead to short term financial benefits have higher adoption rates than those that concentrate on delivering ecological service provision. This view is supported by Mills et al. (2016) who state that current financial incentives and regulatory approaches have had a degree of success in encouraging environmental practices, but these are ultimately transient drivers that have not led to long-term sustainability.

Within this, policy uncertainty may further hinder the uptake of environmental land management practices. Kuhfuss et al. (2018) describe these uncertainties as:

• differences in sources in funding (public vs private)
• eligibility rules
• financial uncertainty of prices in the carbon markets and
• potential emerging markets that may provide better results.

This is further compounded by whether a payment by results or an activity model is used. Moxey at al. (2021) reinforce this point by suggesting that peatland restoration work is hindered by the perceived ineligibility for agricultural support payments, tax breaks and concerns over future support arrangement and carbon market fluctuations.

Bio-physical constraints, tenure and structure

Environmental constraints often limit which environmental measures can be implemented on a spatial scale. Location, climate and environmental quality are key determinants of which support schemes are viable for a land manager’s piece of land as they affect what is implementable practically in local conditions in relation to opportunities. An example of this is the large amount of peatland and moorland that provides potential for peat bog restoration management practices: in these locations woodland planting should be discouraged (Lampkin et al. 2021). Paulus et al. (2022) provide further evidence to support this point by suggesting that environmental management practices are more likely to be implemented on sites with unfavourable agricultural conditions.

Two more important factors are the size of the enterprise and the tenure of the land. Regarding tenure, a meta-analysis of 46 studies (Baumgart-Getz et al. 2012) looking at the adoption of best-management practices found secure tenure to be a positive indicator of adoption, and the findings are likely to apply to climate friendly measures as well. This suggests that land managers who either own their land or are on secure tenancies with a good relationship with their landlord are more likely to adopt environmental measures due to the long-term security that their tenure status affords them.

Multiple sources within the literature also suggest that larger enterprises may be more willing and able to engage with support systems, particularly those with environmental outcomes (Mills et al. 2013; Paulus et al. 2022). Smaller enterprises are likely to have fewer opportunities to take elements out of production and fewer resources to apply without impacting their net income.

Ease of access to support

A key determinant of engagement with support systems is the perceived and actual accessibility of these schemes.

If a scheme is considered to be straightforward and easy to apply for, there is likely to be high engagement. The opposite is true of a scheme that is considered complex and time consuming. For example, for land managers the administrative load (transaction costs) and time commitment is often the determining factor on whether to participate or not. A common criticism of AESs is that they often carry high transaction costs, especially in comparison to more traditional support schemes (Kuhfuss et al. 2018).

Lampkin et al. (2021) suggest that schemes have become increasingly complex, partially in response to regulatory, audit and compliance issues. The administrative burden can also vary across enterprise type, with Benni et al. (2022) finding that dairy producers face substantially higher transaction costs than arable producers. Furthermore, once schemes are in place, the ongoing maintenance requirement for many AES (reporting etc.) can prove a further barrier to uptake (MacKay & Prager, 2021).

The Peatland Code can be used to understand some of the accessibility issues found in the Scottish agricultural sector. Moxey et al. (2021) suggest that the administrative burden associated with applying for joint funding via AESs and via the Peatland Code is perceived as overly complex, with interactions between them further increasing this. The study notes that the issue of interacting schemes occurs when having to demonstrate additionality, aligning funding cycles between different sources and coordinating across multiple land managers and investors.

Novo et al. (2021) also found that challenges in understanding the application process and funding mechanism were a barrier mentioned by interviewees in their study regarding the peatland carbon code.

Therefore, the perceived and actual transaction costs associated with support systems are a barrier to uptake. When looking to address this, Westway et al. (2023) caution that simplicity is important to encourage uptake, however oversimplification of schemes can lead to unintended consequences and needs to be balanced against public accountability for expenditure.

Knowledge availability, sharing and awareness

Engagement with support schemes and uptake of specific on farm measures is frequently linked with the knowledge and understanding of the individual land manager (Toma et al. 2018).

A lack of knowledge and understanding has been frequently cited as a key barrier to new management practices. This is further enhanced when new technological and informational processes are needed for alternative practices and if the costs/benefits are not clear or easy to judge. This finding is supported by results from the Farm Practitioner Survey (2022), where the most reported reason for not taking action was being unsure on what to do due to too many conflicting views (44%). These informational barriers are important as 30% responded that a lack of information was another key reason for not taking action.

This sentiment is echoed by two specific examples in Scotland. Firstly, Moxey et al. (2021) found that the awareness of the need for and benefits of peatland restoration is generally not well known amongst land managers, along with the voluntary market of the Peatland Code. Secondly, Lozada & Karley (2022) suggest that more evidence and greater awareness are needed amongst land managers about the financial and social outcomes of agroecological practices to facilitate uptake.