Social vulnerability to toxic risk from commercial and industrial chemical releases.

摘要

This research develops a model of social vulnerability to toxic risk from industrial and commercial chemical releases into the air, the water, and on the land. Results are interpreted through distributive justice theory, which defines the fair exchange and allocation of public goods.;The research design is a cross-sectional comparison of 330 counties in the eight southeastern states of the United States. Data is used from the 1990 U.S. Census, presidential elections, and the U.S. Environmental Protection Agency (EPA). Analyses included descriptive multi-geographic comparative analyses, a within-county quantitative and qualitative analysis; estimation of the path model with four toxic release density and four toxic release severity indicators; and, to examine the hypothesis that race moderates risk, multi-sample comparisons were made between counties with high concentrations of African-Americans and those with high concentrations of European-Americans.;The toxic release severity indicators, used by the EPA as toxic risk screening tools, were found to be highly unreliable, as were the density indicators for land and water releases. The model fit the data for air release indicators, with fugitive air releases being the strongest indicator. Population density was easily the single-most powerful social vulnerability indicator. Human capital, economic, and political resource indicators together did not add significantly to the effect of population density on toxic risk, nor were the multi-sample racial composition samples significantly different.;The findings suggest building theory that integrates population dynamics, community planning, economic development, social welfare and social justice, with the risk of diminishing the capacity of the natural environment to sustain human well-being through chemical contamination. Methodological recommendations include expanding the study of social vulnerability and toxic risk spacially, conceptually, and analytically through nested geographic analyses; resolving issues of multivariate-non-normal distributions; testing the reliability of toxic risk screening instruments; and maximizing the benefits of combined quantitative and qualitative analyses. Implications for social work practice to reduce toxic risk are discussed, including the use of macro-level interventions, new collaborations, and an environmental lens through which to assess threats from by-products of technological processes, and to protect and sustain the natural environment that sustains human well-being.