North American Fine Particulate Matter Chemical Composition for 2000–2022 from Satellites, Models, and Monitors: The Changing Contribution of Wildfires

Abstract

Air quality management benefits from an in-depth understanding of the emissions associated with, and composition of, local PM_2.5 concentrations. Here, we investigate the changing role of biomass burning emissions to North American PM_2.5 exposure by combining multiple satellite-, ground-, and simulation-based data sets biweekly at a 0.01° × 0.01° resolution from 2000 to 2022. We also developed a Buffered Leave Cluster Out (BLeCO) method to address autocorrelation and computational cost in cross-validation. Biomass burning emissions contribute an increasingly large fraction to PM_2.5 exposure in the United States and Canada, with national annual population-weighted mean contributions increasing from 0.4 μg/m³ (3–5%) in 2000–2004 to 0.8–0.9 μg/m³ (9–14%) by 2019–2022, led by western North American 2019–2022 annual contributions of 1.4–1.9 μg/m³ (15–27%) and maximum seasonal contributions of 3.3–5.5 μg/m³ (29–49%). Other components such as nonbiomass burning Organic Matter (OM) and nitrate can be regionally as (or more) important, albeit with distinct seasonal variability. The contribution of total OM to PM_2.5 exposure in the United States in 2016–2022 is 42.2%, comparable to all other anthropogenically sourced components combined. Comparison of BLeCO and random 10-fold cross-validation suggests that random 10-fold cross-validation may significantly underrepresent true uncertainty for total PM_2.5 concentrations due to the clustered nature of PM_2.5 ground-based monitoring.