Abstract
Background: Mobile sources such as traffic and airports contribute significantly to concentrations of nitrogen oxides (NOx) and nitrogen dioxide (NO2). Exposure to these pollutants in turn are associated with a range of negative health outcomes. Accurate, high resolution spatiotemporal models of NOx /NO2 are needed to support further epidemiological research. Traffic tailpipe emissions are especially elevated under high engine load (acceleration), and our earlier work shows accounting for airport emissions may decrease measurement error in our spatiotemporal NOx models. The goal of this work is to showcase improvements in accounting for these mobile sources more accurately and these features’ importance in our spatiotemporal NOx models. Methods: We calculated airport-related NOx emissions by allocating airport-related NOx emissions from CARB’s CEPAM emission inventory tool to each airport in California from 2004 through 2019. For 2020 and 2021, emissions were further scaled on a weekly basis to account for decreased flight volume during the COVID period. To account for on-road vehicle tailpipe emissions due to acceleration at intersections, we developed a dataset representing intersection density, broken into class by intersection type based on road class type and supported by GPS activity data. These variables were incorporated into spatiotemporal modeling of outdoor NOx/NO2 concentrations in California. Results: Airport emissions and intersection density were ranked highly by variable importance within the model. The transportation-related emissions surrogates improved the spatial representation of NOx/NO2 at fine scales, supporting accurate air quality exposure estimates. Conclusions: Our findings demonstrate how improved measures of mobile source emissions (beyond distance to airports or roads) that capture gradients in emission patterns across spatial features (e.g. road class) can enhance spatiotemporal prediction performance of high resolution exposure models. Keywords: Air pollution, NOx, transportation, mobile sources
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