Abstract
Long-term air pollution exposure may lead to an increase in incidences and mortality rates of chronic diseases and adversely affect human health. The effects of long-term air pollution exposure have not been comprehensively studied due to the lack of human mobility data collected over a long period. In this study, we develop and apply a personal mobility model to long-term hourly air pollution concentration predictions to quantify personal long-term air pollution exposure for all individuals. We implement our model assuming mobility patterns for commuters and homemakers, and separate between weekdays and weekend. Our results show that NO2 exposure of commuters are on average slightly higher and vary less spatially as they are exposed to NO2 at multiple locations.
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