Estimating fine particulate matter component concentrations and size distributions using satellite-retrieved...

We develop a method that uses both the total column aerosol optical depth (AOD) and the fractional AOD values for different aerosol types, derived from Multiangle Imaging SpectroRadiometer (MISR) aerosol data, to estimate ground-level concentrations of fine particulate matter (PM2.5) mass and its major constituents in eastern and western United States. Compared with previous research on linking column AOD with ground-level PM2.5, this method treats various MISR aerosol components as individual predictor variables. Therefore, the contributions of different particle types to PM2.5 concentrations can be estimated. When AOD is greater than 0.15, MISR is able to distinguish dust from non-dust particles with an uncertainty level of approximately 4%, and light-absorbing from non-light-absorbing particles with an uncertainty level of approximately 20%. Further analysis shows that MISR Version 17 aerosol microphysical properties have good sensitivity and internal consistency among different mixture classes. The retrieval uncertainty of individual fractional AODs ranges between 5 and 11% in the eastern United States, and between 11 and 31% in the west for non-dust aerosol components. These results provide confidence that the fractional AOD models with their inherent flexibility can make more accurate predictions of the concentrations of PM2.5 and its constituents.