Environmental Injustice at School: A New Environmental Policy Analysis Framework

• In Event: Environmental Justice and Distributional Equity

Abstract

Background: For the past four decades, environmental justice (EJ) literature has revealed unequal distribution of pollution across residential areas based on racial and ethnic demographics and socioeconomic status (SES). Though nonetheless important, a weakness of this scholarly concentration is that it overlooks the fact that many adults spend significant time at work and children at school. While there have been some studies on workplace EJ, there are only a few that involve examining environmental injustice for students and schools.

Objective: This study is a step forward in the literature by focusing on school EJ. It investigates the extent to which U.S. public K-12 schools of different racial and ethnic composition, poverty levels, and institutional types are exposed to two pollutants: ozone and PM2.5. In addition, we provide a new analytical framework for environmental policies that takes into account both equity variables (race and ethnicity, SES, etc.) and multiple cross-contextual variables (residential, workplace, or school pollution).

Methods: We merge data from the Segregation Tracking Project (STP), the Education Demographic and Geographic Estimates (EDGE) program, and the Environmental Justice Screening and Mapping Tool 2.3 (EJSCREEN) to form a school-level dataset that contains racial and ethnic demographics, free and reduced-price lunch enrollment, charter and magnet status, and point location of each school; and ozone and PM2.5 pollution levels measured at the census block group (CBG) in which each school is located. Then, we use statistical models to test EJ effects at school, including associations between school attributes, on one hand, and air pollution measured by raw value and health risk thresholds set by the World Health Organization (WHO) and Environmental Protection Agency (EPA) on the other. Lastly, in trying to identify the causal pathways, we employ two-stage least squares (2SLS) regression models.

Results: Preliminarily findings indicate that educational institutions with higher proportions of minority students, with higher percentages of students qualified for free lunch, and those identified as charter or magnet schools are subject to higher levels of ozone and PM2.5 pollution, all else equal, compared to schools with larger proportion of White non-Hispanic students, fewer poor students, and standard public-school status.

Conclusion: The findings provide an important piece of the puzzle to the field of EJ by analyzing environmental injustice at school. Together with EJ effects at home and at work, we have a more complete picture of systematic inequalities in pollution exposure among people across multiple domains of their daily lives. Moreover, the call for a framework that incorporates both equity and multiple cross-contextual variables beyond residence into policy analysis sheds light on a future analytical path for environmental policies.

Authors

• Gesihan Zhang, Claremont Graduate University
  Non-Presenting Co-Author

• Lucas Kyle Wilder, Claremont Graduate University
  Non-Presenting Co-Author

• Heather E. Campbell, Claremont Graduate University
  Presenting Author