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Integration of Air Quality Modeling and Monitoring Data for Enhanced Health Exposure Assessment
Citation:
Denby, B., V. Garcia, D. M. HOLLAND, AND C. Hogrege. Integration of Air Quality Modeling and Monitoring Data for Enhanced Health Exposure Assessment . ENVIRONMENTAL MANAGEMENT. Springer-Verlag, New York, NY, , 46-49, (2009).
Impact/Purpose:
Several studies have demonstrated that an accurate assessment of temporal and spatial variations in ambient concentrations is critical for the interpretation of time-series epidemiology studies. Health studies have shown (e.g. Sarnat et al. 2006 and Jerrett et al. 2005) that a more narrow definition of the geographic domain of the study populations leads to stronger associations between exposure and health outcomes (e.g., hospital admissions, mortality counts). In order to improve epidemiology and health impact studies enhanced spatial and temporal coverage and resolution is thus required.
Description:
In order to assess the environmental impact of air pollution on human health it is necessary to establish the concentrations to which the population is exposed. The obvious way to determine this is to measure these quantities. However, given the limited number of monitoring stations available, how is it possible to provide spatially distributed pollution concentrations far from monitoring sites in order to assess the exposure of an entire population? Traditionally ground based monitoring has been used to provide air quality information since it is expected to give the best estimate. This may be suitable when a very limited area is to be assessed, e.g. in occupational health studies, or when monitoring data is representative of a large area, e.g. in rural regions, but generally such monitoring has a limited spatial representativeness. This can be problematic in urban areas since there can be significant variation in air quality due to the heterogeneity of the emissions sources and the complex flow patterns caused by urban morphology.