An Environmental Justice Analysis: Superfund Sites and Surrounding Communities in Illinois

Abstract

Since the inception of the environmental justice movement in the late 1980s, studies have been conducted at national, regional, state, and local levels. However, environmental justice within the state of Illinois is largely unresearched. This article attempts to fill this gap by examining whether the presence of a Superfund site affects the surrounding communities in the state of Illinois with the intent to aid future siting decisions of hazardous sites and the amelioration of current sites. Geographic Information Systems (GIS) was used to create buffer zones of one-, two-, and five-miles surrounding current Illinois Superfund sites. We then used these neighborhoods of the same size to analyze the current economic and racial demographics of Illinois communities that contain Superfund sites. Specifically, variables considered as indicators of environmental injustice were analyzed, including race, median household income, and homeownership. Our results support prior research that suggested race, rather than class, was the major indicator of environmental inequality. Additionally, as the distance from the Superfund site increases, the number of communities with socio-demographic disparities decreases. Our conclusions provide important theoretical implications for environmental justice research by distinguishing the racial factor from other socioeconomic factors (e.g., income and homeownership) and by identifying the socio-demographic characteristics associated with distance from a Superfund site.

Spatial distribution of unconventional gas wells and human populations in the Marcellus Shale in the United States: Vulnerability analysis

“…The spatial coincidence method simply treats populations within a certain geographic unit containing a polluting facility as potentially exposed to environmental burdens, while the proximity analysis assumes populations living within a certain specified distance of the polluting facility are impacted, and those outside the buffer are not impacted. The proximity analysis method more adequately captures the potential for exposure than the spatial coincidence method (Chakraborty & Maantay, 2011), and many GIS-based environmental justice studies use it to determine the exposure potential (Maranville, Ting, & Zhang, 2009;Miranda, Keating, & Edwards, 2008).…”

“…We chose these buffer distances because they proved to be an effective representation of variation in human exposure to industrial pollution in previous studies (BurwellNaney et al, 2013;Maranville et al, 2009;Mohai & Saha, 2006;Perlin, Wong, & Sexton, 2001). A combination of two buffers and four selection methods produced eight possible outcomes from the proximity method.…”

Unequal Trajectories: Racial and Class Differences in Residential Exposure to Industrial Hazard

“…Although this literature provides a somewhat inconsistent picture of the extent of environmental inequality, most authors indicate that the distribution of industrial hazards—e.g., Superfund fund sites, hazardous waste sites, chemical spills, and manufacturing areas—are disproportionately located in neighborhoods occupied by racial minorities (Maranville, Ting, and Zhang 2009; Stretesky and Hogan 1998). There is continuing debate concerning the cause of this racial-environmental inequality, but there is a general consensus that racial minorities are disproportionately exposed to environmental hazards.…”

Mountaintop Removal and Job Creation: Exploring the Relationship Using Spatial Regression

“…Such distances capture the majority of direct environmental impacts (e.g., detectable stream degradation) associated with MTR (see U.S. EPA 2005) and fall within parameters used in prior studies that have examined the spatial relationship between disadvantaged populations and their proximity to environmental hazards (Mennis 2002;Bullard et al 2007;Maranville, Ting, and Zhang 2009;Mohai et al 2009). According to the developer of the method, locating the place-point data and corresponding buffer zones along gridlines was a technique useful for quasi-geostatistical sampling of databases for exploratory geoinformatic analysis (W. L. Myers, personal communication, e-mail, 3 January 2011).…”