Distributions of Human Exposure to Ozone During Commuting Hours in Connecticut using the Cellular Device Network
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Epidemiologic studies have established associations between various air pollutants and adverse health outcomes for adults and children. Due to high costs of monitoring air pollutant concentrations for subjects enrolled in a study, statisticians predict exposure concentrations from spatial models that are developed using concentrations monitored at a few sites. In the absence of detailed information on when and where subjects move during the study window, researchers typically assume that the subjects spend their entire day at home, school or work. This assumption can potentially lead to large exposure misclassification. In this study, we aim to determine the distribution of the exposure misclassification for an air pollutant (ozone) when individual mobility is taken into account in contrast to assuming that subjects are static. To achieve this goal, we use cell-phone mobility data on 388,972 AT&T users in the state of Connecticut during July, 2016, in conjunction with an ozone pollution model, and compare individual ozone exposure assuming static versus mobile scenarios. Our results show that exposure models not taking mobility into account often provide poor estimates of individuals commuting into and out of urban areas: the average 8-hour maximum difference between these estimates can exceed 80 parts per billion (ppb). However, for most of the population, the difference in exposure assignment between the two models is small, thereby validating many current epidemiologic studies focusing on exposure to ozone.
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