A Physical Approach to Constraining Chemical Transport PM2.5 Modeling Outputs Using Surface-Monitor Measurements and Satellite Retrievals

Improved satellite retrievals of aerosol type can provide broad regional context and can decrease metric uncertainties and errors, increasing the accuracy of near-surface air quality characterization. The frequent, spatially extensive and radiometrically consistent instantaneous constraints can be especially useful in areas away from ground monitors and progressively downwind of emission sources. We demonstrate a physical approach of using satellite retrievals to further improve regional-scale chemical transport model (CTM) spatiotemporal estimates of PM_2.5, its major chemical component species, and its related uncertainties. This approach complements the more widely applied statistical modeling methods. It uses ground-based monitors where available, combined with aerosol optical depth from both the Multi-angle Imaging SpectroRadiometer (MISR) Research Aerosol retrieval algorithm (RA) and Moderate Resolution Imaging Spectroradiometer Multi-Angle Implementation of Atmospheric Correction (MAIAC) advanced algorithm, as well as MISR qualitative constraints on aerosol size, shape, and light-absorption properties.

The technique developed here leverages the complete spatiotemporal coverage of CTMs and their physical constraints, such as aerosol mass balance and meteorological consistency. The CTM also aids in identifying relationships between observed species concentrations and emission sources. We examine the optimal application of incorporating 275 m horizontal-resolution aerosol airmass-type maps from the MISR RA and total-column aerosol optical depth from the MISR RA and MAIAC into regional-scale CTM outputs. The impact on surface PM_2.5 fields progressively downwind of large single sources will be discussed and evaluated using concurrent ambient air quality observations. Assessing this physical technique in well-instrumented regions opens the possibility of applying it globally over areas where surface air quality measurements are limited or entirely absent.