Influence of Emission Inventories and Secondary Organic Aerosol Chemistry on Simulated Fine Particulate Matter Over the U.S. in a Chemical Transport Model

Abstract Accurately modeling ambient fine particulate matter (diameter 38% higher than the GFAS‐driven simulation (C‐GFAS‐NEI) change. GFED leads to increased organic aerosols (OA) in August, while in December the SOA chemistry scheme drives OA differences between simulations. Compared to ground‐based observations, the C‐GFAS‐NEI simulation has the highest spatial correlation and lowest bias in August, when GFED‐based simulations overestimate PM 2.5 by more than 80% on average. In December, performance was similar across scenarios, with the simple SOA scheme yielding a lower bias than the complex scheme. These findings demonstrate that BB inventories dominate uncertainty in simulated PM 2.5 during wildfire‐impacted periods, whereas SOA chemistry exerts greater influence when wildfire activity is limited. Accounting for these uncertainties can guide emission inventory selection, choice of SOA treatment, and inform future model developments to improve policy or source attribution applications.