Screening for Justice

• In Event: Environmental Justice: Assessing Problems and Remedies

Abstract

A large cross-section of U.S. citizens continue to experience disparities in environmental hazards in air, water, and drinking water. Unsurprisingly, these disparities are borne to a greater degree by low-income, communities of color. A critical challenge for public policy is to examine how to efficiently and effectively address these environmental inequities with innovative policy instruments.

A natural place to look for solutions is enhanced government enforcement of environmental regulations. After all, government behavior has been identified as a contributing factor to ongoing inequities. Weak regulatory enforcement both raises the incidence and duration of environmental violations (Nadeau 1997) and fails to deter both targeted facilities as well as nearby facilities (Gray and Shimshack 2011; Shimshack 2014). And, because enforcement is highly discretionary, it has long been investigated by political scientists interested in explaining the political, institutional, economic, and social determinants of patterns over time and geographic space (Konisky 2007, Konisky and Reenock 2018; Switzer and Teodoro 2018; Woods 2022).

One such innovative policy instrument is the EPA’s environmental justice screening and mapping tool, known as EJScreen, which the agency introduced to the public in 2015. This tool allows EPA and state enforcement agencies to screen communities for their vulnerability to a variety of environmental and socioeconomic indicators. Enforcement officers can then employ a bespoke set of indicators to set thresholds that define ‘vulnerable’ communities based upon their socioeconomic and pollution burdens. Once these communities are identified, officers could then, in theory, optimally set their enforcement strategies to reduce environmental disparities. However, this process introduces a provocative possibility. Namely, even with aggressive enforcement, given the nature of the relationship between facilities’ inspections, enforcement actions, compliance, and finite resources, there may exist no threshold high enough that could effectively reduce disparities across communities.

In this paper, we are interested in answering two questions. What might environmental enforcement patterns look like under a counterfactual of enforcement agencies utilizing the EPA’s screening tools, effectively? And, given the historical relationship between inspections, enforcement outcomes, and pollution reduction, what vulnerable community thresholds, if any, are an optimal target to pursue?

To answer these questions, we consider the effect of such screening strategies on enforcement officers’ behavior. To do this we combine the EPA’s screening data on socioeconomics and pollution burden with historical enforcement and compliance data on major polluting facilities under the Clean Air Act. We focus on a data window that begins five years prior to the release of the screening tool (2010) and continue five years past its release (2020). This yields an average of approximately 16,000 operating facilities per year. We then examine historical relationships between standard community indicators of minority and poverty. We then estimate several models in which we comparatively rescale the vulnerability of a community using the EPA’s screening data to assess the impact on inspections and enforcement outcomes. Our findings suggest that while a useful tool, EJScreen, may fall short of the goal of eliminating environmental disparities.

Authors

• David Konisky, Indiana University, Bloomington

• Christopher M. Reenock, Florida State University

• James Carroll Stewart, Florida State University