Abstract
Commuters are exposed to significantly high pollution levels at traffic intersections. This study utilized the generalized Pareto distribution to model commuters’ exposure to extreme particulate matter (PM) levels across 36 traffic intersections in Varanasi, India. A Bayesian hierarchical framework was deployed to account for the seasonal variation. The monthly return levels for extreme PM2.5 (PM10) were 589 (1127), 474 (961), and 429 (902) µg/m3 during winter, spring, and summer, respectively. The extreme PM2.5 and PM10 concentrations exceeded the NAAQS severe category for all three seasons. There is a 0.72 % (1.47 %) chance that during winter, PM2.5 (PM10) levels would exceed that of the Delhi smog event (PM2.5: 585 µg/m3, PM10: 989 µg/m3). These findings raise concerns about public health and the environment, particularly in winter. The results would guide policymakers in enforcing stringent measures to reduce extreme exposures at traffic intersections in densely populated cities.
Published Version
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