Chemical Composition of PM2.5 from a Geophysical-Statistical Method that Combines Information from Satellites, Models, and Monitors

We develop spatially complete estimates of total and compositional fine particulate matter (PM_2.5) concentrations over North America, Europe and China from 2000 to 2016 by combining aerosol optical depth (AOD) from multiple sources (Dark Target, Deep Blue, MAIAC, and MISR satellite retrievals, as well as GEOS-Chem simulation) with the simulated geophysical relationship of AOD to PM_2.5 and relative component contributions. These geophysical estimates are further calibrated using ground-based observations of total PM_2.5 over each region, and of PM_2.5 composition over North America. The inclusion of ground-based monitors significantly improves agreement compared to geophysical-based estimates alone, increasing the R² between cross-validated ground-based observations and purely geophysical estimates by 0.16-0.29, improving slopes, and clearly demonstrating the added value of ground-based observations, combined with satellite retrievals and chemical models, for continental-scale air quality applications.