Understanding UK Air Quality with a Chemistry Transport Model

Ambient air pollution exposure was associated with 4.2 million premature deaths globally in 2019. In the UK, it is considered the single biggest environmental health issue, with particular concern regarding pollution from nitrogen dioxide (NO2), Ozone (O3) and Particulate Matter (PM2.5). Numerical representations (models) allow us to interrogate our understanding of processes controlling pollution but are inherently simplified representations. This work uses the GEOS-Chem atmospheric chemistry transport model run in both its nested and stretched grid configuration to extend our understanding of air pollution over the UK.

Compared to observations, the model systematically underestimates Nitrogen Oxides (NOx) in non-rural environments, potentially due to spatial resolution. This underestimate could lead to an overestimation of O3 concentrations in these environments, but is balanced by a model underestimate in background O3 flowing into the UK. It is estimated that 78% of UK O3comes from outside of the UK. Reducing UK NOx emissions increases wintertime O3 by reducing NO titration, and reduces overall summertime O3 production. Higher spatial resolutions reduce bias and improve correlations with observations for both NOx and O3, due to better representation of local emissions and lower O3 production rates.

Despite capturing the average concentrations of ammonia and sulphur dioxide reasonably, model overestimates in inorganic aerosols lead to an overestimate of PM2.5. Changes to Industrial SO2 emission injection heights improve estimates for SO2, with small improvements for PM2.5 and aerosol sulfate. Population-weighted PM2.5 violates both the WHO 5 ugm-3 and UK's 10 ugm-3 guidelines in the standard model. Removal of all UK anthropogenic and agricultural emissions reduces the population exceeding the WHO guideline from 95% to 27%, but highlights the challenge of complying with the guideline. Higher spatial resolutions increase PM2.5 bias overall, but model-observation correlations continue to improve with higher resolutions.