Institute of Ecosystem Studies

2008 BES Annual Meeting Presentation and Poster Abstracts

Environmental Justice: Process and Inequality
Lord, Charlie
Co-Authors: Charlie Lord
Abstract: Environmental justice theory demonstrates that disadvantaged groups, especially low-income and racial/ethnic minorities, bear a disproportionate burden of environmental disamenities, enjoy fewer environmental amenities than advantaged populations, and are often excluded or marginalized from decisions that generate such patterns. This project provides a ground breaking method for evaluating the role of race and its treatment in legal and political systems in creating the present day distribution of environmental disamenities. We are exploring whether race, immigration status and/or income are determinative drivers in the distribution of environmental disamenities over time. Most environmental justice studies focus on outcome equity with only a cursory treatment of the processes that create those patterns. The Boston College team is working on a process equity analysis of zoning and nuisance law for the period 1880 to the present. We are assessing whether zoning and nuisance decisions illustrate a pattern over time of approving or allowing certain noxious uses in certain neighborhoods as compared to others and whether the approval patterns correlate to race or income. We hypothesize that neighborhoods dominated by African-Americans, recent immigrants, and low-income groups have been more negatively affected by zoning decisions and nuisance law than the white majority. The team has evaluated over 1000 variances in the City of Baltimore for the period 1931 to 2000. We have mapped these variances and we are analyzing whether there is any correlation between these variances and historic disinvestment in certain neighborhoods as a function of race. We are also analyzing whether there is a disproportionate distribution of these variances according to the demographic characteristics of a neighborhood. The team will present its distributional analysis and preliminary statistical analyses.