HR: 17:15h
AN: A54C-06    [Abstracts]
TI: Three-Dimensional Air Quality System (3D-AQS)
AU: * Engel-Cox, J
EM: engelcoxj@battelle.org
AF: Battelle Memorial Institute, 2101 Wilson Boulevard, Suite 800, Arlington, VA 22201,
AU: Hoff, R
EM: hoff@umbc.edu
AF: Joint Center for Earth Systems Technology/UMBC, 1000 Hilltop Circle, Baltimore, MD 21250,
AU: Weber, S
EM: webers@battelle.org
AF: Battelle Memorial Institute, 2101 Wilson Boulevard, Suite 800, Arlington, VA 22201,
AU: Zhang, H
EM: hazhang1@umbc.edu
AF: Joint Center for Earth Systems Technology/UMBC, 1000 Hilltop Circle, Baltimore, MD 21250,
AU: Prados, A
EM: aprados@pop600.gsfc.nasa.gov
AF: Joint Center for Earth Systems Technology/UMBC, 1000 Hilltop Circle, Baltimore, MD 21250,
AB: The 3-Dimensional Air Quality System (3DAQS) integrates remote sensing observations from a variety of platforms into air quality decision support systems at the U.S. Environmental Protection Agency (EPA), with a focus on particulate air pollution. The decision support systems are the Air Quality System (AQS) / AirQuest database at EPA, Infusing satellite Data into Environmental Applications (IDEA) system, the U.S. Air Quality weblog (Smog Blog) at UMBC, and the Regional East Atmospheric Lidar Mesonet (REALM). The project includes an end user advisory group with representatives from the air quality community providing ongoing feedback. The 3DAQS data sets are UMBC ground based LIDAR, and NASA and NOAA satellite data from MODIS, OMI, AIRS, CALIPSO, MISR, and GASP. Based on end user input, we are co-locating these measurements to the EPA's ground-based air pollution monitors as well as re-gridding to the Community Multiscale Air Quality (CMAQ) model grid. These data provide forecasters and the scientific community with a tool for assessment, analysis, and forecasting of U.S Air Quality. The third dimension and the ability to analyze the vertical transport of particulate pollution are provided by aerosol extinction profiles from the UMBC LIDAR and CALIPSO. We present examples of a 3D visualization tool we are developing to facilitate use of this data. We also present two specific applications of 3D-AQS data. The first is comparisons between PM2.5 monitor data and remote sensing aerosol optical depth (AOD) data, which show moderate agreement but variation with EPA region. The second is a case study for Baltimore, Maryland, as an example of 3D-analysis for a metropolitan area. In that case, some improvement is found in the PM2.5 /LIDAR correlations when using vertical aerosol information to calculate an AOD below the boundary layer.
UR: http://alg.umbc.edu/3D-AQS/
DE: 0305 Aerosols and particles (0345, 4801, 4906)
DE: 0345 Pollution: urban and regional (0305, 0478, 4251)
DE: 0368 Troposphere: constituent transport and chemistry
DE: 0478 Pollution: urban, regional and global (0345, 4251)
DE: 0480 Remote sensing
SC: Atmospheric Sciences [A]
MN: 2007 Fall Meeting