Comparison of global air pollution impacts across horizontal resolutions

The impact of ambient air pollution on human health, especially fine particulate matter (PM2.5) and tropospheric ozone (O3), is a significant global environmental concern. Atmospheric chemical transport models (CTMs) have been used to determine the concentrations of air pollutants at which health concerns arise. It is therefore critically important to fully understand the limitations of these atmospheric CTMs. There is a lack of consensus on how the resolution of a CTM in the horizontal direction affects the accuracy with which it predicts changes in air pollution levels. Low-spatial-resolution and high-spatial-resolution domains for estimating O3 and PM2.5 concentrations were created to examine the impact of nested-grid simulations on model outputs. We compared modeling outcomes and observations to validate the accuracy of each resolution and assessed the changes in agricultural and health implications. The model validation demonstrated that increasing the resolution improved the reproducibility of the observation regionally but did not necessarily improve the overall global results. Moreover, the differences in the changes of global agricultural and health effects were minor and comparable to the uncertainty associated with emissions inventories and CTMs. Some of the regional variations were larger than the global total, which could be a significant issue in some contexts or for specific objectives. Although improvements in the resolution of the CTM could potentially alter the predicted effects of air pollution in certain regions, the impact of these resolution changes on global-scale results was found to be minimal.