Agriculture contributes to 18% of greenhouse gas (GHG) emissions in Scotland and is required to reduce its emissions by 31% from 2019 levels by 2032, according to the Scottish Government’s update to the Climate Change Plan.

Reductions to reach Scotland’s net zero GHG emissions targets can be achieved through mitigation and carbon sequestration measures implemented on farms. Taken together with options identified in the wider food chain and land use, such as dietary change, land use change and food waste reduction, there is clear potential to move food production closer to net zero.

This report provides an updated assessment of the emission reduction potential of the most effective mitigation measures in Scotland.

Researchers assessed 25 farm technologies, or 39 when considered for different livestock types, and practices that can reduce GHG emissions in Scotland by 2050 – modelling constraints required using 2050 instead of the net zero target of 2045, which is not excepted to impact mitigation as all the mitigation measures are fully implemented in the model by the early 2040s.

The measures were derived via a systematic process taking forward the most suitable options for Scotland for quantitative modelling, drawing from relevant UK and Scotland reports. Details of the agricultural activity scenarios used can be found in appendix B of the report.

Key findings

  • Assuming mitigation measures are taken by 45% of farmers, the total mitigation potential in 2050 is between 0.9 and 4.3 metric tons of carbon dioxide equivalent (Mt CO2e). The mitigation attributable to changing practices and technologies on farms is between 0.4 and 0.9 Mt CO2e in 2050, while the remaining mitigation is due to reduced agricultural activity.
  • The Tailwinds and Widespread Engagement activity scenario offer the highest total GHG reduction, most of it arising from reduced agricultural activity.
  • The Business as Usual activity scenario, which includes no behavioural and technological changes, has the highest abatement potential on farms, consistent with this scenario having the largest dairy herd, grassland area and arable production, but offers the lowest overall GHG mitigation. However, reducing the land areas and livestock numbers, by increasing yield and reducing demand for livestock products, generates higher total abatement, considering uptake of the measures by 45% of farmers.

Five mitigation measures stand out as providing high emission reduction potential at negative or low abatement cost in most scenarios:  

  • Growing clover-grass mix instead of pure grass is the most cost-effective mitigation option and also one of the measures that offer the largest abatement.
  • Using genomics in dairy breeding could provide net savings to the farmers and offers high emissions reduction potential in most scenarios.
  • Increasing the beef output from dairy herds using sexed semen could offer considerable mitigation at zero net cost.
  • Finishing beef animals faster is also cost effective and offers high mitigation.
  • Using nitrate as a feed additive for beef costs less than the carbon price.

For further details about the findings and the overall study can be found in the report attached.

Scotland is committed to meeting a net-zero target for greenhouse gas (GHG) emissions by 2045. Agriculture and the land use sector can help in two ways: by changing practices to reduce GHG emissions and by storing carbon in the soil and plants. In 2018 agriculture and related land use was responsible for 23% of total Scottish emissions. 

The Climate Change Plan (CCP) is a key policy tool which was revised in December 2020 (after this research was completed) to help Scotland meet the new net-zero target. Policy development is informed by the Scottish ‘TIMES model’. This model pulls together emission, mitigation and mitigation cost data from all sectors to help understand the strategic choices required to decarbonise an economy. It identifies the effectiveness of carbon reduction measures to enable a consistent comparison of the costs of action across all sectors.

To ensure the model uses the most recent data for agriculture, our research updated estimates of the mitigation potential and the cost-effectiveness of a selection of agricultural mitigation options. It took into account the significant recent improvements in UK agricultural GHG inventory reporting (Smart Inventory).

We assessed 14 farm technologies and practices which can reduce GHG emissions in Scotland. Some of these measures can be applied to multiple types of livestock, raising the number of mitigation options to 21.

The aim was to estimate the different measures’ average mitigation potential, capital and recurring costs per unit (e.g. hectare or animal), and total maximum applicability on-farm. 

Key findings
  • The mitigation measures applicable to agricultural land can save between 7 and 553* kg CO2e every year on each hectare where they are applied. The single most effective measure is increased cultivation of grain legumes (i.e. peas and beans) which provides 553 kg CO2e per hectare savings annually (see Table 1). The second and third most effective measures (on an area basis) are variable rate nitrogen and lime application (precision farming) and soil pH management (i.e. liming when necessary), providing 151 and 112 kg CO2e mitigation per hectare annually, respectively.
  • Intercropping can provide the highest cost savings to farmers per hectare per year (£45); variable rate nitrogen and lime application, crop varieties with higher nitrogen use efficiency and soil pH management can also provide savings. Grain legume cultivation is the most expensive option (£406 per hectare per year).
  • The cattle mitigation measures assessed can save between 57 and 854 kg CO2e every year for each animal they are applied to; 3NOP feed additive, breeding for low methane emissions and slurry store cover with impermeable cover are the most effective.
  • Cattle measures’ net costs range from a saving of £359 to a cost of £31 per animal per year. The dairy breeding measure could save £359 per animal per year, and improved health of dairy animals, dairy precision feeding, beef breeding for low methane emissions and covering beef slurry stores can also save farmers money. The most expensive cattle measure is administering 3NOP feed additive to beef animals (£31 per animal per year).
  • The sheep measure investigated can provide 15 kg CO2e mitigation per animal annually and a cost saving of £0.36 per head.
  • The two measures applicable to pigs could reduce emissions by 25 and 86 kg CO2e per head per year, for a £0.87 saving or cost of £0.52 per animal per year, respectively.

It is important to note that these are average estimates. On an individual farm basis, both the mitigation and the net costs can be very different. 

* Three changes have been made to the original report download:

– The Executive Summary stated that the mitigation measures applicable to agricultural land can save between 7 and 151 kg CO2e every year on each hectare where they are applied. The second figure should have been 553kg. This has now been corrected above and in the pdf.

– The original omitted three of the authors.

– In Section 3.2.2, a reference to Defra’s support has been added.

 

Agriculture accounts for the second largest proportion of greenhouse gas emissions in Scotland, particularly through the use of fertilisers, livestock manures and other organic materials such digestate or compost. One approach that could help to reduce these emissions is the use of nitrogen accounting tools. In this report we compare available nitrogen accounting tools to assess their potential application focusing on Scottish agriculture.

 

With a focus on input-output models, we evaluate the strengths and weaknesses of different models, their practical potential for application to Scottish farm businesses, and their potential to support policy decisions.

 

Key Findings
  • Generally, there are common knowledge gaps across many of the tools assessed.  This includes a lack of detailed description for nitrogen parameters such as deposition, gaseous losses (particularly ammonia losses), fixation rates (based on legume type and coverage), content in feed, machinery use and wider. Gaps were also found in evidence for the use of novel technologies on farms, efficiency differences from livestock breeding programmes and how the nitrogen accounting tools link more widely, for example with sectors such as industry, transport, human consumption and waste.
  • We found that the tools available have been designed for specific (different) purposes that vary in spatial scale and which differ in complexity, both in how easy they are to use and in the details describing nitrogen pathways in agricultural systems.
  • At the national and regional scale from the identified tools, the model by Vogt and the UK Smart Inventory shows the greatest potential to be developed into a national level policy monitoring tool. On the other hand, Farmscoper and IMAGE would be suitable to explore alternative scenarios in the near and further future, respectively.
  • The tool evaluation process determined that, of the tools reviewed, PLANET, MANNER-NPK and potentially FarmAC are most suitable for Scottish application for calculating farm-level budgets at this time. However, the OverseerFM tool provides the most holistic coverage of farm level management practices influencing nitrogen inputs, transformations, storage and outputs from a farm.

The UK’s inventory of greenhouse gas emissions measures progress towards reduction targets. The methodology for agriculture has recently changed to better reflect the current science on the GHG emissions from agriculture.

The new methodology is called the ‘smart inventory’. It includes a wider range of technologies and management options than the previous inventory based on more recent science, although there are still gaps in our understanding.

This report summarises how different changes to  agricultural practice in Scotland are (or could be) recognised in the smart inventory. It provides information to policy makers on what changes can be captured in the UK GHG inventory, and what further steps could be taken to reflect Scottish agricultural practices more accurately.

Key findings

  • The smart inventory reflects the mitigation activities for which we currently have robust data and analysis
  • Annual Scotland-specific data are used in many activities (e.g. crop areas, fertilisation rates livestock numbers, milk yield, slaughter weight), but more specific activity data either are either not updated annually or not systematically collected for Scotland.
  • Inventory development is a continuous process and future data collection should be planned with the Inventory team in order to maximise the use of the data in the inventory. 
  • There are four main data categories that would enhance data collection initially:
    a) Nitrogen fertilisation of minor crops and novel legumes 
    b) Area and fertilisation information on  intercropping
    c) Ruminant diets
    d) Manure management and storage information

This report looks at options for reducing the greenhouse gas emissions from Scottish Farms. It analyses a range of options across changes in management of fertiliser, soil and manure, livestock feeding and energy use. Some of these changes require an investment in new tools, equipment or other installations on farm.

The analysis indicates that the 20 technology options considered could reduce emissions by between 9 and 150 kt CO2e GHG annually if they were implemented to their fullest potential across Scotland. Doing this would also have other positive environmental effects (e.g. with regards to soil or water quality).

The report recommends use of complementary incentive mechanisms to encourage uptake of the technologies. These could include:

  • increased emphasis on these technologies in extension services or mechanisms;
  • support for collaborative implementation of the technologies;
  • foot printing/accounting schemes for validating and signalling on-farm and supply chain progress; and
  • a comprehensive approach to each stage of the supply chain.