Big mobility data reveals hyperlocal air pollution exposuredisparities in the Bronx, New York City

Recent studies confirm that air pollution disproportionately affects socially disadvantaged populations^1-3. Yet, they have not fully explored the effect of personal mobility on population exposure. Our study bridges the existing gap in quantifying mobility-based air pollution exposure across socio-demographic groups. We combine the granular mobility of over 500,000 unique users daily and air pollution data at 100 m resolution to quantify disparities in particulate matter exposure in the Bronx, New York City, a racially diverse and dense urban area. Using individual daily particulate matter exposure rather than population-weighted concentrations, this approach not only reveals the streets with the highest prevalence of air pollution but also how different demographic groups are exposed. We observe significantly different spatial patterns between personal exposure and exposure disparities, where people from Hispanic-majority and low-income neighborhoods are the most severely and disproportionately exposed to fine particulate matter (PM_2.5) pollution. We reveal that race/ethnicity is a much stronger indicator of exposure disparity than income. The study further demonstrates that within-group variation contributes a major portion of exposure disparities, suggesting more granular mitigation plans are needed to target high-exposure individuals of socially disadvantaged groups in addition to generic air quality improvement.