Using a Spatial Statistical Approach to Assess Cumulative Environmental Burdens for Public Housing Developments in the United States

Abstract

While recent studies have drawn attention to the environmental justice implications of specific hazards and pollution sources for inhabitants of public housing developments (PHDs), previous research has not examined whether PHD residents are disproportionately exposed to the cumulative impacts of multiple environmental stressors. We address this gap by conducting the first systematic, national-scale analysis of the relationship between cumulative environmental burdens and PHD residency, using a novel spatial statistical approach for assessing cumulative impacts. We seek to determine whether: (1) PHD units and residents, and (2) socially disadvantaged households residing in PHDs, are significantly overrepresented in census tracts with higher cumulative burdens in the continental U.S. Our study utilizes environmental indicators from the U.S. Environmental Protection Agency’s EJScreen tool (2022), and PHD-related data from the U.S. Department of Housing and Urban Development (December 31, 2022). We implement a spatial cluster analysis technique to designate hot (and cold) spots of tracts with significantly higher (and lower) cumulative burdens compared to other tracts. Results indicate that both PHD units and residents are disproportionately located in hot spot areas, compared to non-PHD housing units and population. For people residing in PHDs, we found Black, Hispanic, and extremely low-income households to be overrepresented in hot spot tracts. Our findings highlight the necessity to reverse these unequal patterns for PHDs, as well as illustrate how emerging spatial statistical approaches can contribute to measuring cumulative impacts and detecting overburdened communities that require policy intervention.