Equity in the Distribution of Regulatory PM2.5 Monitors

TL;DR

This study investigates the distribution of PM2.5 monitors across U.S. neighborhoods, revealing disparities especially in rural, high-poverty areas, and highlights potential gaps in air quality data representation.

Contribution

It provides a detailed analysis of environmental justice factors influencing monitor placement, using multilevel models to identify inequities in air quality data collection.

Findings

Most EJ attributes show weak association with monitor proximity.

Higher poverty levels in rural areas are linked to fewer monitors.

Monitor distribution may be less equitable in rural, impoverished communities.

Abstract

Unequal exposure to air pollution by race and socioeconomic status is well-documented in the U.S. However, there has been relatively little research on inequities in the collection of PM2.5 data, creating a critical gap in understanding which neighborhood exposures are represented in these datasets. In this study we use multilevel models with random intercepts by county and state, stratified by urbanicity to investigate the association between six key environmental justice (EJ) attributes (%AIAN, %Asian %Black, %Hispanic, %White, %Poverty) and proximity to the nearest regulatory monitor at the census tract-level across the contiguous 48 states. We also separately stratify our models by EPA region. Our results show that most EJ attributes exhibit weak or statistically insignificant associations with monitor proximity, except in rural areas where higher poverty levels are significantly linked to greater monitor distances ($\beta$ = 0.6, 95%CI = [0.49, 0.71]). While the US EPA's siting criteria may be effective in ensuring equitable monitor distribution in some contexts, the low density of monitors in rural areas may impact the accuracy of national-level air pollution monitoring.