2007 AGU Fall Meeting, December 10-14,San Francisco, CA
Assessing U.S Air Quality Using CALIPSO and MODIS Data via Giovanni
1Ana Prados, 2Gregory Leptoukh, 3Erica J. Alston, and 3Irina N. Sokolik
1University of Maryland Baltimore County/JCET/NASA GSFC, Greenbelt, MD
2NASA Goddard Space Flight Center, Greenbelt, MD
3School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA
The NASA Goddard online system Giovanni (http://giovanni.gsfc.nasa.gov) provides the scientific community with web based visualization, exploration, and analysis tools relevant to air quality. Relevant data products include MODIS Aerosol Optical Depth (AOD), CALIOP aerosol information, and PM2.5 and ozone surface monitor data. Giovanni services include maps, time series, Hovmoller plots, statistical analysis of one or more data sets for a selected region, and image animations of satellite data. For A-Train sensors, Giovanni is capable of providing vertical profile information for various atmospheric components measured along the A-Train orbit tracks. Additionally, the capability to generate AOD/PM2.5 correlation maps, a research tool for understanding the utility of satellite data for monitoring U.Spollution at various temporal and spatial scales, has been added to the Giovanni system.
We present several high pollution events in U.S based on these Giovanni analysis and visualization tools. On August 1-5, 2007 a combination of local pollution sources, long range transport of smoke from Canada and the U.S northwest, and hot and humid conditions lead to a high PM2.5 event over the eastern half of the continental U.S. CALIOP profile data from Giovanni are used here to analyze the vertical transport of the pollution plumes and to better understand the satellite observations and the relative contribution of the various pollution sources to surface PM2.5 concentrations.
In the spring of 2007, large wildfires occurred in Georgia and Florida. During the active burning period, Atlanta experienced seven PM2.5 National Ambient Air Quality Standard (NAAQS) exceedances, most occurring during May. Correctly predicting air quality during a wildfire can be difficult, as shown by the missed Air Quality Index (AQI) forecasts for those exceedance days. We use ground-based and multi-satellite data to characterize the impact of these fires on air quality in the Atlanta metropolitan area. The AOD/PM2.5 correlations in conjunction with data on optical properties of urban aerosols and meteorological conditions are examined to determine satellite value-added information for improving air quality modeling in urban areas.
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