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IMPROVING NATIONAL AIR QUALITY FORECASTS WITH SATELLITE AEROSOL OBSERVATIONS
Citation:
AL-SAADI, J. A., J. SZYKMAN, R. B. PIERCE, C. KITTAKA, D. O. NEIL, D. A. CHU, L. REMER, L. GUMLEY, E. PRINS, L. WEINSTOCK, C. MACDONALD, R. WAYLAND, F. DIMMICK, AND F. FISHMAN. IMPROVING NATIONAL AIR QUALITY FORECASTS WITH SATELLITE AEROSOL OBSERVATIONS. BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY 86(9):1249-1261, (2005).
Impact/Purpose:
Our research objectives are to: (a) develop new methods using satellite remote sensor data for the rapid characterization of LC condition and change at regional to national scales; (b) evaluate the utility of the new NASA-EOS MODIS (Moderate Resolution Imaging Spectrometer) leaf area index (LAI) measurements for regional scale application with landscape process models (e.g., biogenic emissions and atmospheric deposition); (c) provide remote sensor derived measurement data to advance the development of the next generation of distributed landscape process-based models to provide a predictive modeling capability for important ecosystem processes (e.g., nutrients, sedimentation, pathogens, etc.); and (d) integrate in situ monitoring measurement networks with UAV and satellite based remote sensor data to provide a continuous environmental monitoring capability.
Description:
Air quality forecasts for major US metropolitan areas have been provided to the public through a partnership between the US Environmental Protection Agency and state and local air agencies since 1997. Recent years have witnessed improvement in forecast skill and expansion of forecasts to additional pollutants and lacalities. Accurate air quality forecasts allow individuals to minimize the adverse health impacts of poor air quality by adjusting their plans for outdoor activities to reduce exposure. Accurate forecasts can also allow the severity of pollution episodes to be reduced by enabling timely implementation of mitigation strategies. Yet air quality forecasting is quite complex; in addition to all the difficulties associated with weather forecasting, it requires knowledge of local and regional pollution conditions and the ability to predict the evolution and transformation of the trace constituents comprising pollution. While pollution episodes are commonly attributed to nearby emissions and local meteorological conditions, it is increasingly recognized that long-range transport of non-local pollutants is often a factor (NARSTO, 2003). Therefore local air quality forecasts depend on knowledge of pollutant concentrations and emissions at surrounding, and potentially distant, locations. The most direct way to obtain this knowledge is from the pollutant measurements routinely made at surface monitoring stations across the country. However, large regions of the US are devoid of surface monitors and coastal regions are often influenced by polluted air approaching over water. In addition, pollution may be transported aloft, undetected by surface monitors, and then descend to influence air at the ground.