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Quantifying population exposure to air pollution using individual mobility patterns inferred from mobile phone data


A critical question in environmental epidemiology is whether air pollution exposures of large populations can be refined using individual mobile-device-based mobility patterns. Cellular network data has become an essential tool for understanding the movements of human populations. As such, through inferring the daily home and work locations of 407,435 mobile phone users whose positions are determined, we assess exposure to PM2.5. Spatiotemporal PM2.5 concentrations are predicted using an Aerosol Optical Depth- and Land Use Regression-combined model. Air pollution exposures of subjects are assigned considering modeled PM2.5 levels at both their home and work locations. These exposures are then compared to residence-only exposure metric, which does not consider daily mobility. In our study, we demonstrate that individual air pollution exposures can be quantified using mobile device data, for populations of unprecedented size. In examining mean annual PM2.5 exposures determined, bias for the residence-based exposures was 0.91, relative to the exposure metric considering the work location. Thus, we find that ignoring daily mobility potentially contributes to misclassification in health effect estimates. Our framework for understanding population exposure to environmental pollution could play a key role in prospective environmental epidemiological studies.

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The authors thank Airsage who have provided data for this study through their support of the Senseable City Laboratory at Massachusetts Institute of Technology. This publication was made possible by USEPA grant (RD-835872-01) through the Harvard University United States Environmental Protection Agency sponsored Air, Climate & Environment (ACE) Centre. The contents of the study are solely the responsibility of the grantee and do not necessarily represent the official views of the USEPA. Further, USEPA does not endorse the purchase of any commercial products or services mentioned in the publication.

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The authors declare that they have no conflict of interest.

Correspondence to M. M. Nyhan.

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  • Air pollution
  • Population exposure
  • Mobility
  • Cellular network data
  • PM2.5
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