This article presents a case study of Toxics Release Inventory (TRI) air pollution exposure risks across metropolitan St. Louis. The first section critically reviews environmental justice research and related barriers to environmental risk management. Second, the paper offers a conventional analysis of the spatial patterns of TRI facilities and their surrounding census block group demographics for metropolitan St. Louis. Third, the article describes the use of an exposure risk characterization for 319 manufacturers and their air releases of more than 126 toxic pollutants. This information could lead to more practical resolutions of urban environmental injustices. The analysis of TRIs across metropolitan St. Louis shows that minority and low-income residents were disproportionately closer to industrial pollution sources at nonrandom significance levels. Spatial concentrations of minority residents averaged nearly 40% within one kilometer of St. Louis TRI sites compared to 25% elsewhere. However, one-fifth of the region's air pollution exposure risk over a decade was spatially concentrated among only six facilities on the southwestern border of East St. Louis. This disproportionate concentration of some of the greatest pollution risk would never be considered in most conventional environmental justice analyses. Not all pollution exposure risk is average, and the worst risks deserve more attention from environmental managers assessing and mitigating environmental injustices.
In the 20 years since a president committed federal government agencies to achieving environmental justice (EJ), states have been at the forefront of policy development. But states have varied in the nature and extent of their EJ efforts. We use Guttman Scaling to measure state EJ effort and test hypotheses regarding the relative importance of problem severity, politics, and administrative variables to variation in state policy development. Our analysis offers a novel characterization of state policy intensity and demonstrates its scalability. Income-based problem severity, environmental group membership, and nonwhite populations were important predictors of state EJ policy intensity during our study period. The political geography of EJ policy also displayed a distinctive southern pattern and the EJ policy intensity model contrasted significantly with a model of environmental policy innovation. The findings suggest that state EJ politics are more indicative of redistributive policy than regulatory.
Not all pollution was distributed equally in a dynamic urban landscape. Using techniques to examine skewed riskscapes and socioeconomic urban geographies provided a foundation for future research on the connections among environmental health hazard sources, socially vulnerable neighborhoods, and health inequity.
Objective
To examine state‐level environmental inequality trends over time by constructing a new, longitudinal data set and comparing change in environmental and economic inequality.
Methods
We use Environmental Protection Agency's (EPA) RSEI (Risk‐Screening Environmental Indicator) database to create measures of exposure to industrial air toxins and inequality in exposure by race and poverty status. Measures were calculated for each of three periods: 1990–1994, 2000–2004, and 2010–2014.
Results
Exposure declined but inequality persisted. The geographic patterns displayed by race‐ and poverty‐related environmental inequality differ. But, states with higher levels of race‐based inequality had higher levels of exposure. Poverty‐based environmental and economic inequality exhibited a moderate, positive relation that was spatially patterned.
Conclusion
While environmental quality improved, we saw little progress in reducing environmental inequality. Though both race‐ and poverty‐based inequality remain, they result from different mechanisms. Future research should examine the relations between deindustrialization and economic, environmental, and political inequality.
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