Local Pollution Havens in the US

Todd Matthews just published The Enduring Conflict of ‘‘Jobs Versus the Environment’’: Local Pollution Havens as an Integrative Empirical Measure of Economy versus Environment.

Building of Fruedenberg's concept of disproportionality -- unequal access to environmental rights and resources observable in the privileges accrued by relatively few actors to create highly uneven levels of polluting emissions per job created -- Matthews develops the concept of a Local Pollution Haven. These are counties that combine three characteristics: 1) high levels of pollution per amount of economic reward, 2) high levels of toxicity per amount of economic reward and 3) low levels of regulatory control. Here's a map showing the distribution of such counties. Not surprisingly, the havens are heavily concentrated in the South (specifically, the states of Alabama, Tennessee and Mississippi). When compared to non-pollution haven counties, the havens are typically metropolitan or adjacent to metropolitan counties with higher levels of economic inequality, more than twice the proportion of blacks, and little in-migration. Notably missing is the state of Louisiana, often targeted in the environmental justice literature for its predilection to locate refineries and other aspects of the petrochemical industry in poor counties populated by people of color.

Additional details are in the abstract:

The ‘‘jobs versus the environment’’ dichotomy has been a recurring theme in the United States for decades. It is typically taken to refer to a choice or trade-off between economic growth and development and environmental quality or the lack of environmental degradation. Little resolution has occurred after decades of research because of inconsistent or problematic conceptualization and the use of inappropriate spatial units of analysis. Research on international and domestic pollution havens is reviewed in an effort to introduce the Local Pollution Havens concept. Local pollution havens are conceptualized as counties with high levels of pollution per unit of economic reward, high toxicity per unit of economic reward, and low regulation or other social controls. Traditional and spatial statistical techniques are utilized to construct this measure and determine which counties fit the conceptualization. Descriptive statistics and the results of t-tests and logistic regression analyses are presented to demonstrate how these areas differ from other counties. Implications for the remediation of these areas and also avenues of future research are offered.

Reference: Sociological Spectrum 31: 59–85, 2011; DOI: 10.1080/02732173.2011.525696