Abstract
The use of Pollutant Plume Dispersion Models is widespread in the evaluation of point sources of air pollution. These models provide valuable insight into the concentration and dispersion of hazardous materials throughout the atmosphere. Traditional methods of dispersion modeling for the permitting of new sources and the monitoring of existing sources have allowed much room for error in terms of the effect of the pollutants on nearby populations (Hardikar, 1995). The capabilities of GIS technology offer an improved method of conducting air quality modeling for permitting, remediation studies, and environmental monitoring. GIS has the ability to develop and manage a comprehensive database of model output, map layers, and demographic data that can prove extremely valuable in the modeling process. This data can serve to extend the capabilities of air pollution dispersion modeling from mere estimation of concentrations to comprehensive exposure assessment of neighboring populations (Lowry, et al. 1995, Maslia, et al. 1994). A study of the Monticello power plant in northeast Texas was conducted using the SCREEN3 mathematical plume dispersion model, US Census Bureau demographic data, and a GIS to examine the effects of the plant output on the people living in the seven county area surrounding the plant.
Archer, Jeffrey Keith (1998). GIS and plume dispersion modeling for population exposure assessment. Master's thesis, Texas A&M University. Available electronically from
https : / /hdl .handle .net /1969 .1 /ETD -TAMU -1998 -THESIS -A726.