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. 2004 Dec;112(17):1717-24.
doi: 10.1289/ehp.7066.

GIS modeling of air toxics releases from TRI-reporting and non-TRI-reporting facilities: impacts for environmental justice

Dana C Dolinoy  1 , Marie Lynn Miranda
Affiliations

GIS modeling of air toxics releases from TRI-reporting and non-TRI-reporting facilities: impacts for environmental justice

Dana C Dolinoy et al. Environ Health Perspect. 2004 Dec.

Abstract

The Toxics Release Inventory (TRI) requires facilities with 10 or more full-time employees that process > 25,000 pounds in aggregate or use > 10,000 pounds of any one TRI chemical to report releases annually. However, little is known about releases from non-TRI-reporting facilities, nor has attention been given to the very localized equity impacts associated with air toxics releases. Using geographic information systems and industrial source complex dispersion modeling, we developed methods for characterizing air releases from TRI-reporting as well as non-TRI-reporting facilities at four levels of geographic resolution. We characterized the spatial distribution and concentration of air releases from one representative industry in Durham County, North Carolina (USA). Inclusive modeling of all facilities rather than modeling of TRI sites alone significantly alters the magnitude and spatial distribution of modeled air concentrations. Modeling exposure receptors at more refined levels of geographic resolution reveals localized, neighborhood-level exposure hot spots that are not apparent at coarser geographic scales. Multivariate analysis indicates that inclusive facility modeling at fine levels of geographic resolution reveals exposure disparities by income and race. These new methods significantly enhance the ability to model air toxics, perform equity analysis, and clarify conflicts in the literature regarding environmental justice findings. This work has substantial implications for how to structure TRI reporting requirements, as well as methods and types of analysis that will successfully elucidate the spatial distribution of exposure potentials across geographic, income, and racial lines.

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Figures

Figure 1
Figure 1. Durham county, North Carolina (USA).
Figure 2
Figure 2. Two demographic variables for Durham County: (A) median household income and (B) percent African American.
Figure 3
Figure 3. Boundaries for Durham County for (A) census tracts and census block groups and (B) census blocks and ZIP codes.
Figure 4
Figure 4. TRI-reporting and non-TRI-reporting facilities in all TRI SIC codes in Durham County. The yellow box represents central Durham.
Figure 5
Figure 5. TRI-reporting and non-TRI-reporting facilities in SIC Code 2752 (printing-lithography) and their estimated emissions of certain glycol ethers. The yellow box represents central Durham.
Figure 6
Figure 6. Modeled air emissions (ng/m3) of certain glycol ethers for (A) TRI-reporting and (B) non-TRI-reporting facilities.
Figure 7
Figure 7. CDF curves of modeled census-block–level exposure for African-American and white subpopulations for (A) TRI sites alone and (B) all emitters.
Figure 8
Figure 8. CDF curves of modeled census-block–level exposure for child and adult subpopulations for (A) TRI sites alone and (B) all emitters.
Figure 9
Figure 9. Modeled inclusive air emissions (ng/m3) of certain glycol ethers for all facilities at (A) the census tract and (B) the census block group level.
See this image and copyright information in PMC

References

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