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UNDERSTANDING THE CORRELATION OF SAN JOAQUIN AIR QUALITY MONITORING WITH AEROSOL OPTICAL THICKNESS SATELLITE MEASUREMENTS

Marshall Wilson Ballard, Michelle Newcomer, J. Rudy, Samuel J. Lake, S. Sambasivam, A. W. Strawa, Christopher C. Schmidt, J. W. Skiles

Year
2007
Citations
7

Abstract

Air quality in the San Joaquin Valley has failed to meet state and federal attainment standards for Particulate Matter (PM) for several years. This is attributed to anthropogenic and natural sources. The Environmental Protection Agency (EPA) and California Air Resources Board (CARB) continuously monitor San Joaquin Valley air quality from selected ground sites, and these efforts can be enhanced by the broad spatial coverage provided by satellites. While previous studies show good correlations between satellite derived Aerosol Optical Thickness (AOT) and PM data on the East Coast, this is not the case in the San Joaquin Valley. This paper compares PM2.5 ground data from CARB and Interagency Monitoring of Protected Environments (IMPROVE) sites with satellite data in an effort to understand the reason behind this discrepancy. AOT values from the Aerosol Robotic Network (AERONET) offer an opportunity to verify satellite accuracy to coincide the AOT and PM2.5 comparison. Fieldwork was conducted using the MicroTops II Sun Photometer to measure AOT values in the city of Fresno and correlate with satellite data. Good correlation between Moderate Resolution Imaging Spectroradiometer (MODIS), Multiangle Imaging Spectroradiometer (MISR) and AERONET are shown. Statistical and spatial analysis of satellite and ground data, demonstrated weak correlations between AOT and PM2.5, and consideration of aerosol speciation did not improve the correlations. Further investigation into the effects of meteorological conditions or aerosol layers aloft is needed to determine the causes of the poor correlation.

Keywords

AERONETSan JoaquinAerosolEnvironmental scienceSatelliteAir quality indexModerate-resolution imaging spectroradiometerSpectroradiometerRemote sensingMeteorology

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