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ESTIMATING GROUND LEVEL PM 2.5 IN THE EASTERN UNITED STATES USING SATELLITE REMOTE SENSING
Citation:
Sarnat, J., V Kilaru, D. J. Jacobs, AND P. Koutrakis. ESTIMATING GROUND LEVEL PM 2.5 IN THE EASTERN UNITED STATES USING SATELLITE REMOTE SENSING. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, 39(9):3269-34278, (2005).
Impact/Purpose:
Our main objective is to assess the exposure of selected ecosystems to specific atmospheric stressors. More precisely, we will analyze and interpret environmental quality (primarily atmospheric) data to document observable changes in environmental stressors that may be associated with legislatively-mandated emissions reductions.
Description:
An empirical model based on the regression between daily average final particle (PM2.5) concentrations and aerosol optical thickness (AOT) measurements from the Multi-angle Imaging SpectroRadiometer (MISR) was developed and tested using data from the eastern United States during the period of 2001. Overall, the empirical model explained 48% of the variability in PM2.5 concentrations. The root mean square error (RMSE) of the model was 6.2 ug/m3 with a corresponding average PM2.5 concentration of 13.8 ug/m3. When PM2.5 concentrations greater than 40 ug/m3 were removed, model results were unbiased estimation of observations. Several factors, such as planetary boundary layer height, relative humidity , season, and other geographical attributes of monitoring sites were found to influence the association between PM2.5 and AOT. The findings of this study illustrate the potential application of satellite remote sensing for regional ambient air quality monitoring. With the continuous advancement of remote sensing technology and global data assimilation systems, AOT measurements, derived from satellite remote sensors, may provide a cost-effective approach as a supplemental source of information for determining ground level particle concentrations.