Segregation and Black/White Differences in Exposure to Air Toxics in 1990

• Published in: Environmental health perspectives 2002-04, Vol.110 (Suppl 2), p.289-295
• Main Author: Lopez, Russ
• Format: Article
• Language: English
• Subjects: African Continental Ancestry Group; Air Pollutants - adverse effects; Black white relations; Census tracts; Chemical hazards; Environmental Exposure; Environmental health; Environmental justice; European Continental Ancestry Group; Hispanic Americans; Hispanics; Humans; Metropolitan areas; Modeling; Models, Theoretical; Population Density; Poverty; Prejudice; Residential segregation; Risk Assessment; Urban Population
• ISSN: 0091-6765; 1552-9924
• DOI: 10.1289/ehp.02110s2289

I examined non-Hispanic Black and non-Hispanic White differences in exposure to noncriteria air pollutants in 44 U.S. Census Bureau-defined metropolitan areas with populations greater than one million, using data on air toxics concentrations prepared for the U.S. Environmental Protection Agency as part of its Cumulative Exposure Project combined with U.S. census data. I measured differences in exposure to air toxics through the calculation of a net difference score, which is a statistical measure used in income inequality analysis to measure inequality over the whole range of exposures. The scores ranged from 11.52 to 83.60. In every metropolitan area, non-Hispanic Blacks are more likely than non-Hispanic Whites to be living in tracts with higher total modeled air toxics concentrations. To assess potential reasons for such a wide variation in exposure differences, I performed a multiple regression analysis with the net difference score as the dependent variable. Independent variables initially included were as follows: the dissimilarity index (to measure segregation), Black poverty/White poverty (to control for Black/White economic differences), population density and percentage of persons traveling to work who drive to work (alone and in car pools), and percentage of workforce employed in manufacturing (factors affecting air quality). After an initial analysis I eliminated from the model the measures of density and the persons driving to work because they were statistically insignificant, they did not add to the predictive power of the model, and their deletion did not affect the other variables. The final model had an R2of 0.56. Increased segregation is associated with increased disparity in potential exposure to air pollution.