title: Combining a road pollution dispersion model with GIS to determine carbon monoxide concentration in Tennessee.
abstract: The purpose of this paper is to develop an air pollution model that is independent from pollution monitoring sites and highly accurate through space and time. Total carbon monoxide concentration is computed with the use of traffic flow data, vehicle speed and dimensions, emission rates, wind speed, and temperature. The data are interpolated using a geographic information system universal kriging technique, and the end results produce state level air pollution maps with high local accuracy. The model is validated against Environment Protection Agency (EPA) pollution data. Overall, the model has 71 % agreement with EPA, overestimating values of carbon monoxide for less than 1 ppm. The model has three advantages over already assessed air pollution models. First, it is completely independent of any air pollution monitoring stations; thus, possible temporary or permanent unreliability or lack of the data is avoided. Second, being based on a 5,710 traffic count network, the problem of remote places coverage is avoided. Third, it is based on a straightforward equation, where minimal preprocessing of traffic and climatic data is required.
authors: Vanderbilt Kennedy Center, Vanderbilt University, Nashville, TN, USA. eva.pantaleoni@vanderbilt.edu
authors: Eva
authors: E
authors: Pantaleoni
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D000397:Air Pollution / Q000706:statistics & numerical data*; D002248:Carbon Monoxide / Q000032:analysis*; D004784:Environmental Monitoring / Q000379:methods*; D040362:Geographic Information Systems; D008956:Models, Chemical; D052638:Particulate Matter / Q000032:analysis; D062206:Spatial Analysis; D013714:Tennessee; D001335:Vehicle Emissions / Q000032:analysis; D014919:Wind
chemical_list: D000393:Air Pollutants; D052638:Particulate Matter; D001335:Vehicle Emissions; D002248:Carbon Monoxide