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Environmental Justice Tools Analysis: Which Metropolitan Atlanta County Faces the Largest Disparity Distribution of Environmental Burdens by Income, Poverty and Race/Ethnicity?

Wellington Onyenwe, MPH(c)1,2; W. Michael Caudle, PhD1; Tim Frederick, MPH2; Thomas Clasen, PhD1; Stefanie Sarnat, PhD1

1Emory University, Rollins School of Public Health, 2U.S. Environmental Protection Agency

Wellington C. Onyenwe Emory University, Rollins School of Public Health Email: [email protected]

Contact 1. "CDC's Core Environmental Health Services." Centers for Disease Control and Prevention. Centers for Disease Control and Prevention, 24 May 2013. Web. 01 Apr. 2014. <http://www.cdc.gov/nceh/information/ehs.htm>.

2. Oraka E, Iqbal S, Flanders WD, Brinker K, Garbe P. Racial and ethnic disparities in current asthma and emergency department visits: findings from the National Health Interview Survey, 2001-2010. J Asthma. 2013 Jun;50(5):488-96. doi:

10.3109/02770903.2013.790417. Epub 2013 May 8. PubMed PMID: 23544662.

3. Oraka E, Kim HJ, King ME, Callahan DB. Asthma prevalence among US elderly by age groups: age still matters. J Asthma. 2012 Aug;49(6):593-9. doi: 10.3109/02770903.2012.684252. Epub 2012 Jul 6. PubMed PMID: 22765313.

4. Cureton S. Environmental victims: environmental injustice issues that threaten the health of children living in poverty. Rev Environ Health. 2011;26(3):141-7. Review. PubMed PMID: 22206190.

5. Redwood Y, Schulz AJ, Israel BA, Yoshihama M, Wang CC, Kreuter M. Social, economic, and political processes that create built environment inequities: perspectives from urban African Americans in Atlanta. Fam Community Health. 2010

Jan-Mar;33(1):53-67. doi: 10.1097/FCH.0b013e3181c4e2d4. PubMed PMID: 20010005.

References *Full list of references available upon request

This project seeks to identify the urban vs. rural relationships between vulnerable populations and US Environmental Protection Agency (EPA) Toxics Release Inventory (TRI) sites in Metropolitan Atlanta through geospatial mapping. The focus was on geographic and social trends of Metropolitan Atlanta, Georgia at the census-level in order to explore the geographic patterns between populations of interest and environmental risk factors. The populations selected were children under 5 years of age, white/Caucasian and non-white/Caucasian ethnic groups (African American, Asian/Pacific Islander, Hispanic/Latino and Native American/Indigenous Peoples). These populations were selected to investigate any possible socioeconomic and demographic correlation between them and TRI site locations through neighborhood analysis. Various population densities were used to analyze population proximity to TRI sites and potential Environmental Justice implications thereof. The tools used were Environmental Systems Research Institute (ESRI) ArcGIS software, EPA’s Scorecard Tool and GreenLaw.org’s Neighborhood Profile Tool.

Introduction

Methods and Materials

Fulton county had most TRI facilities per square mile and highest population density after standardization; faces the largest disparity distribution of environmental

burdens by income, poverty and race/ethnicity in high pollution scores.

Super-imposed maps show blocks with highest demographic scores are in areas with the highest pollution score; while blocks with the lowest demographic scores/lowest quantile tended to be in areas with lower pollution scores.

Most facilities’ driving distances overlap in study area, though the same is not said for the walking distances. Population density per square mile increases as we move

toward the center of the map (Fulton County area).

197 counted facilities with 642 environmental violations from companies recorded from TRI sites; hypothetically averages out to about one TRI facility per every 21.19

square miles and one environmental violation per every 6.50 square miles.

Discussion

Waldo Tobler stated, "Everything is related to everything else, but near things are more related than distant things."27 When dealing with most every aspect of this project, it holds true. Even when we examine the spatial configurations of demographics, pollutions scores, TRI sites and population density it is evident that nearer items are more related than distant things. One can instantly see the cluster relationship between TRI sites on both ArcGIS buffer and GreenLaw maps. It would be interesting to perform the study again, with even more variables, once certain technological limitations are overcome in the near future.

Conclusions

REPLACE THIS BOX WITH YOUR ORGANIZATION’S

HIGH RESOLUTION LOGO

Largest Disparity Distribution of Burden by Race/Ethnicity

Henry County Release of Toxic

Chemicals

Indicator of Chemical

Releases

Ratio

People of Color 40000 2.35

Whites 17000

Hall County Cancer Risks from

Hazardous Air

Pollutants

Added Risk Per

1,000,000

Ratio

People of Color 160 1.33

Whites 120

Hall County Facilities Emitting

Criteria Air Pollutants

Facilities Per Square

Mile

Ratio

People of Color .32 3.81

Whites .084

Largest Disparity Distribution of Burden by Income

Rockdale County Release of Toxic

Chemicals


Releases

Ratio

Low Income Families 44000 2.20

High Income

Families

20000

Fulton County Cancer Risks from

Hazardous Air

Pollutants

Added Risk Per

1,000,000

Ratio

Low Income Families 360 1.38

High Income

Families

260

Fulton County Facilities Emitting



Mile

Ratio

Low Income Families 5.3 4.08

High Income

Families

1.3

Largest Disparity Distribution of Burden by Poverty


Chemicals


Releases

Ratio

Families Below

Poverty

49000 2.33

Families Above

Poverty

21000


Hazardous Air

Pollutants

Added Risk Per

1,000,000

Ratio

Families Below

Poverty

360 1.33

Families Above

Poverty

270




Mile

Ratio

Families Below

Poverty

5.8 3.87

Families Above

Poverty

1.5

Largest Disparity Distribution of Burden by Childhood Poverty


Chemicals


Releases

Ratio

Kids Below Poverty 48000 2.40

Kids Above Poverty 20000


Hazardous Air

Pollutants

Added Risk Per

1,000,000

Ratio

Kids Below Poverty 360 1.38

Kids Above Poverty 260




Mile

Ratio

Kids Below Poverty 5.9 3.93

Kids Above Poverty 1.5

Identify the urban vs. rural relationships between population densities and US Environmental Protection Agency (EPA) Toxics Release Inventory (TRI) sites in Metropolitan Atlanta through

proximity analysis and geospatial mapping.

Identify risk estimates of releases of toxic chemicals, cancer risks from hazardous air pollutants and facilities emitting criteria air

pollutants.

Analyze these distributions of burden of race/ethnicity, income, poverty and childhood poverty in efforts to identify potential

socioeconomic correlations relative to TRI site locations through comparative statistics.

Specific Aims

Interactive mapping

toolset created by eight identified and overlaid types of air, water, and land pollution points in

the 14-county Metropolitan Atlanta

region.

ArcGIS Proximity Analysis toolset of the software will be used to discover proximity relationships and buffer regions of

urban vs. rural population densities in Metropolitan Atlanta.

Toolset for risk estimates of toxic chemicals

releases, cancer risks from hazardous air

pollutants and facilities emitting criteria air pollutants through

comparative statistics.

Figure A (Courtesy GreenLaw) depicts TRI sites per 10km2 blocks in metropolitan Atlanta.

Table 1 EPA’s Scorecard tool depicts the counties with the largest distributions of burdens by each of the measured specific

categories.

Figure 13 (Courtesy GreenLaw) shows the relationship between prevalence of pollution

points and family income.

Figure 7 (Courtesy GreenLaw) shows a direct correlation between prevalence of pollution

points and non-white populations.

Figure 8 (Courtesy GreenLaw) shows a direct correlation between prevalence of pollution points compared to linguistic isolation rates.

Figure 9 (Courtesy GreenLaw) shows a direct correlation between prevalence of pollution

points and poverty rates.

Figure 5 shows quantiles of pollution score mapping to

minimize bias and/or skewing of the data. Pollution scores with

higher summed values were grouped into the higher

quantiles and conversely scores with lower relative values were

grouped into the lower quantiles.30

Figure 6 shows quantiles of

demographic scores; blocks with highest demographic scores, described blocks associated

with the most at-risk population (e.g., dominated by non-white

population, low property value, or low-income characteristics);

while blocks with the lowest demographic scores were scored

in the lowest quantile.30

(Both Courtesy GreenLaw)

W. Michael Caudle, PhD1; Tim Frederick, MPH2; Thomas Clasen, PhD1; Stefanie Sarnat, PhD1; Onyemaechi Nweke, PhD2; LaToria Whitehead, PhD3; Sharunda Buchanan, PhD3; Richard Hertzberg, PhD1,3; Owen Devine, PhD1,3; John Pearce, PhD1; Jessica Kolling, MPH3; P. Barry Ryan, PhD1; Paige Tolbert, PhD1; Michael Page, PhD1; Nick DiLuzio, MEM/MF, CCF4; James R. Henderson, P.E.4; Kathryn A. Wurzel, MPH, DABT4; David Deganian, JD4; Justine Thompson, JD4. 1. Emory University (Woodruff Geospatial Library/Rollins School of Public Health) 2. U.S. Environmental Protection Agency (Superfund/Environmental Justice/Region 4) 3. U.S. Centers for Disease Control and Prevention (National Center for Environmental Health) 4. GreenLaw/New Fields

Acknowledgements

Figure B (Courtesy ArcGIS) depicts TRI sites with1-Mile and 5-Mile buffer zones. The buffer overlay shows how specific

populations would be affected through exposure.

Figure 3 (Courtesy GreenLaw) depicts population density of metropolitan Atlanta, people per square mile.

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