Impact of agricultural interventions on ammonia emissions and on PM2.5 concentrations in the UK: a local and regional modelling study

Abstract

The contribution of agricultural emissions of fine particulate matter (PM2.5) poses significant health and environmental challenges, particularly in the UK where intensive farming activities contribute to elevated pollutant levels. This contribution includes direct emissions and PM2.5 formed through chemical reactions from precursors such as ammonia (NH3). The study aims to analyse the impact of a series of mitigation measures through emission scenarios (low, medium, high uptake) on the dairy, pig, and poultry sectors in 2030, mainly focusing on NH3 emissions. Under the high-uptake scenario, NH3 emissions could decrease by up to 13 % nationally, with reductions reaching as high as 20 % in certain regions. The Community Multiscale Air Quality (CMAQ) and the Atmospheric Dispersion Modelling System (ADMS) models were used. CMAQ allows one to understand the contribution made by agricultural NH3 to secondary PM2.5 at a regional scale, while ADMS is used to better understand near-field dispersion and the dilution of primary pollutants. Despite the impact of the changes in emissions due to the mitigation measures compared to the future baseline scenario, changes are not reflected on regional-scale PM2.5 concentrations since the maximum modelled decrease was around 1 %–1.5 %. This finding is explained by an NH3-rich atmosphere reducing the impact of these reductions in NH3 emissions on mitigating PM2.5 concentrations. Results from ADMS show that the NH3 and PM2.5 concentrations are quickly dispersed near the farms, highlighting the usefulness of local modelling in addressing impact studies on PM2.5 formation near these sources. Indeed, for the five studied livestock farms, it has been found that 50 % of maximum NH3 and PM2.5 concentrations are located within a distance between 100 and 400 m, and up to 90 % of concentrations have decreased within 700 m. The study also demonstrates the complementary use of local and regional modelling in understanding PM2.5 dispersion near agricultural areas. The comparison with ground-based measurements may suggest a non-representation of atmospheric processes in the PM2.5 formation by CMAQ (with an underestimation of PM2.5 concentrations by approximately 50 %). It underscores the need for integrated modelling approaches to guide mitigation strategies for both primary and secondary PM2.5, as well as to improve our understanding of the chemical atmospheric processes involved in secondary inorganic aerosols.