Modeling the spatial patterns of PM2.5 in Georgia with satellite remote sensing and meteorological information
We will integrate aerosol retrievals from MODIS, GOES, MISR, and OMI, meteorology, land use information, and EPA PM2.5 measurements over the 20-county metropolitan Atlanta area. Then we will develop a spatial statistical model using this database to estimate daily PM2.5 exposures, and generate daily concentration estimates for the model grid. These estimates will be compared to Tracking Network's two current methods of estimating PM2.5. Predictions will also be validated prospectively. Finally we will incorporate the validated estimates in the largest single-city, U.S. time-series epidemiologic analyses examining the association between PM2.5 and cardiorespiratory emergency department visits and comparing the results to those generated using CDC's current PM2.5 exposure estimation methods.
The anticipated results will include detailed analyses of the spatial/temporal patterns of PM2.5 pollution in the domain, a statistical evaluation of the advantages of estimating PM2.5 concentrations with this model as compared to methods already available, and an assessment of the potential benefit of including satellite observations to the Tracking Network. This project will help NASA to achieve its objectives of understanding and improving predictive capability for changes in air quality associated with changes in atmospheric composition, and expanding and accelerating the realization of societal benefits from Earth system science.