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Spatial Variability in Pollutants: Implications for Exposure Assessment
Dr. Larry T. Cupitt
U.S. EPA, National Exposure Research Laboratory, Research Triangle Park, NC
Measurement studies of air pollutants in populated areas have demonstrated that
ambient air concentrations across the community can range from being relatively
uniform to being highly variable in space and time. People, too, are variable – moving
across the community throughout the day and participating in various activities that
affect their actual exposures. The resulting exposure profiles are a function of
temporally- and spatially-varying concentrations and activities. The National exposure
Research Laboratory and others have undertaken a number of studies to assess that
variability in time and space for a variety of pollutants, source-related emissions, and
human activities.
Statistical analyses and modeling have been used to assess the variability in exposure metrics and to relate those metrics to outcomes in complex systems. The impact of that variability on the selection of exposure metric and exposure classification approach (from simple metrics and statistical associations; to statistical interpolation that fuses observational data and modeling results, to cohort estimates of varying complexity and sophistication, to state-of-the-science probabilistic human exposure and dose models, to personal exposure measurement studies) have been explored. Outcome data bases (e.g., environmental or public health data) are also examined; stratifying or matching the outcome data with an appropriate exposure metric is often limited by the content, sparseness, or other restrictions on the outcome data sets.
The efforts to evaluate the value of improved exposure metrics on the ability to relate those metrics with outcomes in complex systems have met with varying degrees of success. This work describes the results of recent efforts, mostly involving air pollutants, to improve the sophistication in the exposure estimate and classification in order to improve the quality of associations between exposure and outcomes at the end of the complex systems, both human and environmental.
Disclaimer: Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official Agency policy.