Modeling of Human Exposure to Benzene in Urban Environments

Abstract

Urban areas characterized by high spatial and temporal variability in air pollution levels require implementation of comprehensive approaches to address exposure of individuals. The main objective of this study was to implement a quantitative assessment of individual exposure to benzene in urban environments. For this purpose, ExPOSITION model based on a global positioning system (GPS) tracking approach was applied to estimate individual exposure in different microenvironments. The current investigation provides an application example and validation of the modeling approach against personal and biological exposure measurements collected during the measurements campaign. The probabilistic approach using the Johnson system of distributions was implemented to characterize variability of indoor concentrations. The results obtained for daily average individual exposure to benzene corresponded to mean levels of 1.6 and 0.8–2.7 μg/m3 in terms of 5th–95th percentiles. Validation of the model results against several personal exposure samples collected for the selected individuals revealed a Pearson’s correlation coefficient of .66. This modeling approach explicitly addressed the temporal and spatial variability in the exposure and established a source–receptor relationship.