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Development of Gridded Fields of Urban Canopy Parameters for Advanced Urban Meteorological and Air Quality Models
Burian, S. J. AND J. K. CHING. Development of Gridded Fields of Urban Canopy Parameters for Advanced Urban Meteorological and Air Quality Models. U.S. Environmental Protection Agency, Washington, DC, EPA/600/R-10/007, 2009.
The National Exposure Research Laboratory′s (NERL′s) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA′s mission to protect human health and the environment. AMAD′s research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the Nation′s air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.
Urban dispersion and air quality simulation models applied at various horizontal scales require different levels of fidelity for specifying the characteristics of the underlying surfaces. As the modeling scales approach the neighborhood level (~1 km horizontal grid spacing), the representation of urban morphological structures requires much greater detail. To provide the most accurate surface characterization possible for an air quality modeling study of Houston, Texas, airborne LIDAR (Light Detection and Ranging) data were obtained from TerraPoint LLC at 1-m horizontal grid cell spacing for Harris County, Texas, an area of approximately 5800 km2. The data were managed in the ESRl ArcView 3.3 and ArcGIS 8.2 GIS software packages. Scripts and computer codes were written in Avenue, Visual Basic for Applications, and Fortran to compute 20 urban canopy parameters (UCPs) including building height statistics and histograms, height-to-width ratio, plan area density function, frontal area density function, roughness length. displacement height, mean orientation of streets, and sky view factor. In addition, procedures were developed to approximate several UCPs that could not be determined from the elevation data, including surface cover type, building material fraction, and percent directly connected impervious area.