Estimating PM2.5 component concentrations and size distributions using satellite-retrieved fractional aerosol optical depth: Part 2 - A case study

We use the fractional aerosol optical depth (AOD) values
derived from Multiangle Imaging Spectroradiometer
(MISR) aerosol component measurements, along with
aerosol transport model constraints, to estimate groundlevel
concentrations of fine particulate matter (PM2.5)
mass and its major constituents in the continental United
States. Regression models using fractional AODs predict
PM2.5 mass and sulfate (SO4) concentrations in both the
eastern and western United States, and nitrate (NO3) concentrations
in the western United States reasonably well,
compared with the available ground-level U.S. Environment
Protection Agency (EPA) measurements. These
models show substantially improved predictive power
when compared with similar models using total-column
AOD as a single predictor, especially in the western
United States. The relative contributions of the MISR aerosol
components in these regression models are used to
estimate size distributions of EPA PM2.5 species. This
method captures the overall shapes of the size distributions
of PM2.5 mass and SO4 particles in the east and west,
and NO3 particles in the west. However, the estimated
PM2.5 and SO4 mode diameters are smaller than those previously reported by monitoring studies conducted at
ground level. This is likely due to the satellite sampling
bias caused by the inability to retrieve aerosols through
cloud cover, and the impact of particle hygroscopicity on
measured particle size distributions at ground level.