Greenhouse gas emissions from Scottish farming: an exploratory analysis of the Scottish Farm Business Survey and Agrecalc

The Scottish Government has set ambitious targets for reducing greenhouse gas (GHG) emissions from Scottish agriculture; in 2018 these emissions represented 16% of the nation’s total. As part of a commitment to reach net-zero emissions by 2045, the Climate Change Plan update requires the equivalent of a 31% reduction in agricultural emissions by 2032 from 2018 levels. However, between 1990 and 2019 Scottish agriculture’s emissions decreased by only 13%.

This report explores how data on emissions and nitrogen from the Scottish Farm Business Survey, using Agrecalc, can be used to help design policies aimed at reducing emissions in a sustainable way. Agrecalc is a farm carbon calculator developed by SRUC and used widely within Scotland.

Findings and recommendations

For dairy farms a linear relationship was found between production and GHG emissions intensity– in other words, as milk production per ha increases, GHG emissions per ha increase. Other farm types showed no clear linear trends between production and emissions.
Emissions intensity varied both between and within farm types. Variation between farm types largely reflects differences in enterprise mix. For example, ruminant livestock enterprises are intrinsically more intense emitters than arable enterprises.
Variation within a given farm type can also reflect how enterprises are managed; for example, through adoption of innovations and best practice. The results show some evidence for this, although the patterns are neither linear nor consistent.
We find little evidence of a clear relationship between lower emissions and stronger economic performance. Nor do we find clear evidence for the effects of managerial efficiency.
We found that Nitrogen Use Efficiency (NUE) is a potentially useful agri-environmental metric, as this provides a proxy for farm level efficiency of nutrient use. However, the NUE values calculated from the current SFBS dataset omit important input information, such as legumes. Therefore, its value should be further assessed and measured before potential use as a farm performance metric.
We found farms with similar structural characteristics have different emissions intensities. Collection of additional SFBS data items could improve subsequent analysis.
Although the focus has been on gross emissions, the approach could usefully be extended to consider net emissions, in particular, sequestration into farm soils and woodland. This may, however, need to await further refinements to Agrecalc and collection of additional SFBS variables, such as hedgerow quality.