Evaluating health risks in Denver: A social justice perspective

Empirical research on environmental justice and health disparities has examined inequities associated with the distribution of pollution sources based on their location or, more recently, in terms of the quantity or toxicity of substances released. Few quantitative studies have investigated the extent of human exposure to pollutants released from industrial facilities or the potential health outcomes of exposure. This study addresses this limitation by using a new indicator of human health risks of exposure to industrial toxic emissions and incorporating spatial multivariate regression techniques. The specific objective is to examine racial/ethnic and socioeconomic disparities in the distribution of modeled health risks from potential exposure to industrial air pollution in City and County of Denver, Colorado. This location is unique in that it has a long history of mining and industry as well as it is currently experiencing rapid growth and gentrification. Facilities reporting air emissions to the toxic release inventory (TRI) database in 2006 are considered for this study. The pollution data is derived from the USEPA's Risk-Screening Environmental Indicator (RSEI) model, which estimates potential human health risks from air pollutants based on detailed data on toxicity and dispersion of chemical releases from TRI facilities.

The results show that key differences in the significance of explanatory variables between the conventional and spatial regression model. Specifically, the results indicate the overall minority, Black, and Hispanic populations as well as population density are the most significant explanatory factors in predicting health risks while using ordinary least squares and spatial regression modeling techniques.