Advances in Simulating Global Fine-Scale Ambient Air Pollutants and Source Contributions

Fine-resolution chemical transport models are essential to resolve fine-scale air pollution patterns due to localized emissions, nonlinear chemical feedbacks, and complex meteorology. However, fine-resolution global simulations of air quality remain rare, especially of the Global South. Recent developments to GEOS-Chem model in its high performance configuration (GCHP) enable routinely conducting global air quality simulations at spatial resolution ~60 times finer than the coarse global models traditionally available to the research community (~25 × 25 km2 vs. ~200 × 200 km2). This dissertation is centered on utilizing and improving fine-resolution simulations to produce more accurate spatial estimates of air pollutants combined with satellite-based observations and ground-based measurements. The first section advances fine-scale estimates of population exposure and sectoral contributions from a global fine-resolution simulation with a focus on the Global South. We analyze the discrepancies of population exposure to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) globally and in populous cities between fine and coarse GCHP simulations. We also examine the resolution dependence of sectoral contributions from the differences of fractional contributions of emission sectors across model resolutions with sector sensitivity tests using GCHP. The second section is aimed at investigating the model resolution effects on geophysical satellite-derived PM2.5, inferred from satellite retrieved aerosol optical depth (AOD) and simulated surface PM2.5 to AOD relationship. We compare satellite-derived PM2.5 concentrations across model spatial resolutions using GCHP and examine the overall resolution sensitivities contributed by different PM2.5 components. We further investigate the resolution effects on the simulated aerosol vertical profile, which shows vertical contrast of near-surface emissions and pollutants transported aloft, especially over isolated sources. Mineral dust exerts strong impacts on air quality as the most abundant aerosol by mass, on ecosystem health through nutrient transport and deposition, and on climate change by affecting the radiative budget globally. The third section is targeted at improving fine mineral dust representation in GEOS-Chem from the surface to the column against satellite-based and ground-based observations, leveraging recent mechanistic understanding of dust source and removal. Specifically, we implement a new dust emission scheme, revisit the size distribution of emitted dust, explicitly track dust with diameter less than 2 μm, and update the parametrization for below-cloud scavenging. In summary, these investigations highlight the capability of a global fine-resolution simulation by the GEOS-Chem model in better resolving the spatial heterogeneity of air pollution due to distinct sources, chemical nonlinearities, and complex meteorology, with implications for location-specific emission mitigation strategies. Model developments to fine mineral dust indicate the importance of consistent representation of size in models versus measurements, the spatial distribution of dust emissions, the size distribution of emitted dust, and the explicit tracking of fine bins for more accurate simulation of fine dust abundance from the surface to the column.