Abstract
The U.S. EPA Air Pollutants Exposure Model (APEX) is a stochastic model simulating inhalation exposure using fine-scale population demographics, human activity and physiology, time series of ambient chemical concentrations, and parameterizations of chemical infiltration into microenvironments. For a recent high-resolution population-based exposure assessment of three U.S. urban areas (Tulsa, OK; Indianapolis, IN; Fall River, MA), we used APEX to estimate the percent of the study population experiencing 5-minute SO2 exposures at or above selected benchmark levels (100–400 ppb, 100-ppb increments) and the resultant lung-function decrements. We generated complete time series of 5-minute ambient SO2 concentrations at thousands of receptors in each study area, combining modeled hourly concentrations with continuous 5-minute ambient measurements for 2011–2013, then adjusted to just meet the current national ambient air quality standard. We developed new model input data and algorithms as a function of sex and age to support the high resolution of this assessment, including data on demographics, commuting patterns, and asthma prevalence at the level of U.S. Census blocks, and algorithms to estimate short-term breathing rates and energy expenditure. Results showed notable differences in SO2 exposure by location, with fewer elevated exposures and health risks estimated in Tulsa, OK relative to the other study areas. An important factor in these results is the lower numbers of people estimated to live or work in areas of higher SO2 concentrations in the Tulsa scenario relative to the other scenarios. These results indicate the importance of the accuracy and spatiotemporal resolution of the air concentration and population data in estimating population exposures and health risks to inform policy decisions.
Published Version
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