Abstract
Air pollution is a major global health risk, contributing to millions of premature deaths annually and disproportionately affecting vulnerable populations. Traditional exposure assessment in air pollution epidemiology often relies on static models that assign pollutant concentrations based on residential locations, which may not fully capture the spatial and temporal variability of exposure as individuals move through diverse microenvironments. This limitation can lead to potential exposure misclassification and obscure health inequities. The emergence of large-scale mobility data from sources such as GPS, mobile devices, wearable sensors and transit records provides a mature and scalable opportunity to refine exposure estimates. Here we explore how integrating human mobility data can advance air pollution epidemiology by enabling personalized exposure trajectories, activity–space analysis and community-level risk assessments. We propose a framework that combines mobility data with pollution, health and built-environment datasets to enhance exposure precision, potentially uncover disparities and inform equitable public health interventions. Despite challenges, including privacy concerns, data integration complexities and ensuring equitable representation, mobility-informed approaches hold the potential to deepen our understanding of air pollution’s health impacts and guide targeted urban policies and interventions for healthier, more equitable environments.
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Q.R.W. acknowledges support from the National Science Foundation under grants 2125326, 2114197, 2228533 and 2402438. Q.R.W. and Y.Z. acknowledge support from Northeastern University’s iSUPER Impact Engine. Any opinions, findings, conclusions or recommendations expressed in the paper are those of the authors and do not necessarily reflect the views of the funding agencies.
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Wang, Q.R., Bell, M.L. & Zhang, Y. Integrating mobility data into air pollution research for public health. Nat. Health (2026). https://doi.org/10.1038/s44360-026-00056-7
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DOI: https://doi.org/10.1038/s44360-026-00056-7
