Highlights • Wearable monitors enable high temporal resolution analysis of personal exposure • Microenvironments were identified by GIS-based spatial clustering of measurements • Most vulnerable community had highest observed personal-ambient ratios in the home • High variability in personal PM2.5 despite low variability in ambient PM2.
This study elucidates PM2.5 exposure disparities in a socioeconomically diverse air basin that is heavily burdened by air pollution. A novel spatial clustering approach is applied to classify the microenvironments of more than 900,000 high temporal resolution personal exposure data points. Results from the study indicate that participants from the lowest socioeconomic status community experienced overall higher personal exposures over consecutive 24-hr monitoring periods, despite high participant mobility and low variability in ambient PM2.5 during the study. Our inclusive monitoring protocol minimizes participant fatigue and is well-suited for real-time, long-term characterization of PM2.5 exposure disparities in underserved communities.
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