Traditionally, air quality in populated areas has been assessed through regional chemical transport model (CTM) simulations, loosely constrained by observations from sparse networks of surface monitoring stations. Advances in satellite aerosol type retrievals can improve near-surface air quality concentration estimates, by providing measurements offering broad regional context. This can be especially valuable where surface monitors are scarce or entirely absent, and model biases can be large, e.g., downwind of major pollution sources.
We developed a physical retrieval technique that applies aerosol amount and type information from the MISR instrument, to constrain urban-scale CTM estimates of surface, total PM2.5 mass and speciated concentrations. The satellite-constrained, physically based approach lends itself to long time-series exposure studies, and also shorter time-series exposure studies when used in combination with satellite-driven statistical models. Our physical technique is complimentary to satellite-based statistical models, because it offers the ability to apply satellite-derived column observations directly to total and speciated surface particle concentrations, and is less dependent on having robust surface-based-measurement statistics to constrain the result.
We hope to continue this work at GSFC, first providing additional assessment of the strengths and limitations of this innovative technique in multiple regions for which there is ample surface-based validation data. We will then apply it broadly over populated regions downwind of major pollution sources for which surface-based measurements are limited or entirely absent.
Seminar Series Coordinators