Geospatial Estimation of Individual Exposure to Air Pollutants: Moving from Static Monitoring to Activity-Based Dynamic Exposure Assessment

Abstract

Spatiotemporal variability of air pollutant concentrations and individuals' mobility are likely to play an important role in health outcomes and, therefore, time–activity-based exposure assessments are likely to be more sensitive compared to static residence-based air pollution estimates. Applied research on the effects of the variability underlying air pollutant concentrations and individuals' mobility on personal exposure estimates remain limited, however. We demonstrate how consideration of individuals' mobility and the spatiotemporal variability of ambient air pollution affect personal exposure estimates using both real-world data and simulated environmental conditions. Our findings suggest that time–activity-based exposure estimates might be quite similar to static estimates if spatiotemporal patterns of air pollution concentration surfaces lack autocorrelation or if an individual has a low level of mobility. There can be substantial differences, though, between two approaches when the air pollution concentrations are characterized by a model of air pollution that shows low variation over time and space and individuals' time spent away from home is substantial.