| Statistical regression models are presented to explain the observed variations in the concentrations of two major pollutants, ozone and carbon monoxide, across a large cross-section of U.S. urban areas. Model specifications are based on the theoretical concept of well-mixed cells, derived from integrating the basic Fickian system of diffusion equations, whereby the regional space is partitioned into a grid of large cells. The concentration in each cell results from the balance of pollutant flows into this cell and pollutant emissions and removal within that cell. It is expressed as the sum of two concentration contributions: (1) the local effect, dependent upon pollution-related factors around the measuring station, and (2) the regional effect, dependent upon pollutant flows originating outside the local area. A large database is developed, making extensive use of GIS technology to spatially relate such data as pollution measurements, meteorological factors, land-use characteristics, Census socioeconomic data, and major highway network characteristics. The results confirm the appropriateness of the well-mixed cell framework, are in line with general knowledge regarding the determinants of ozone and carbon monoxide concentrations, and clarify the role of transportation, residential fuel-use, economic activities, natural environments, and meteorological factors such as temperature and solar radiation. About 50% of the variations in concentrations are explained by these models. Several areas of further research are outlined. |
