A study of the spatiotemporal health impacts of ozone exposure.
Exposure analysis and mapping of spatiotemporal pollutants in relation to their health effects are important challenges facing environmental health scientists and integrated assessment modellers. In this work, a methodological framework is discussed to study the impact of spatiotemporal ozone (O3) exposure distributions on the health of human populations. The framework, however, is very general and can be used to study various other pollutants. The spatiotemporal analysis starts with exposure distributions producing the input to pollutokinetic (or toxicokinetic) laws which are linked to effect models which, in turn, are integrated with relationships that describe how effects are distributed across populations. Important characteristics of the environmental health framework are holisticity and stochasticity. Holisticity emphasizes the functional relationships between composite space/time O3 maps, pollutokinetic models of burden on target organs and tissues, and health effects. These relationships offer a meaningful physical interpretation of the exposure and biological processes that affect human exposure. Stochasticity involves the rigorous representation of natural uncertainties and biological variations in terms of spatiotemporal random fields. The stochastic perspective introduces a deeper epistemological understanding in the development of improved models of spatiotemporal human exposure analysis and mapping. Also, it explicitly determines the knowledge bases available and develops logically plausible rules and standards for data processing and human exposure map construction. The proposed approach allows the horizontal integration among sciences related to the human exposure problem that leads to accurate and informative spatiotemporal maps of O3 exposure and effect distributions and an integrative analysis of the whole risk case. By processing a variety of knowledge bases, the spatiotemporal analysis can bring together several sciences which are all relevant to the aspect of human exposure reality that is examined.
Christakos
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G
Department of Environmental Sciences and Engineering, School of Public Health, University of North Carolina at Chapel Hill, 27599-7400, USA. george_christakos@unc.edu
Kolovos
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A
D001822:Body Burden; D003627:Data Interpretation, Statistical; D004784:Environmental Monitoring / Q000379:methods*; D006304:Health Status; D006305:Health Status Indicators; D006801:Humans; D019359:Knowledge; D008377:Maps as Topic; D008657:Metabolic Clearance Rate; D015233:Models, Statistical; D010083:Oxidants, Photochemical / Q000009:adverse effects* / Q000032:analysis* / Q000378:metabolism; D010126:Ozone / Q000009:adverse effects* / Q000032:analysis* / Q000378:metabolism; D015203:Reproducibility of Results; D018570:Risk Assessment; D013269:Stochastic Processes; D013997:Time Factors; D014481:United States
D010083:Oxidants, Photochemical; D010126:Ozone