Equityin the Distributionof Regulatory PM_2.5 Monitors

Unequal exposure to air pollution by race and socioeconomic status is well-documented in the U.S. However, relatively little research has examined inequities in the collection of PM_2.5 data, creating a critical gap in understanding which neighborhood exposures are represented in these data sets. In this study, we use multilevel models with random intercepts by county and state, stratified by urbanicity, to assess associations between six key environmental justice (EJ) attributes (%AIAN, %Asian, %Black, %Hispanic, %White, %Poverty) at the census tract level and proximity to the nearest regulatory monitor. Our results show that most EJ attributes exhibit weak or statistically insignificant associations with monitor proximity, with the exception of %Poverty, where higher poverty levels are significantly linked to closer monitors in urban (β = −0.88, 95% CI = [−0.93, −0.83]) and farther monitor distances in rural (β = 0.6, 95%CI = [0.49, 0.71]) areas. While the U.S. EPA’s siting criteria may be effective in ensuring equitable monitor distribution in many contexts, the low density of monitors in rural areas may impact the accuracy of national-level air pollution monitoring.