1. Environmental Justice: Process and Inequality Charlie Lord BC Law School Environmental Studies Program Boston College

2. EJ Theory Suggests Communities of Color have: More environmental disamenities More environmental disamenities Fewer environmental amenities Fewer environmental amenities Less access to decision-making processes Less access to decision-making processes

3. How has the environmental injustice case been presented? Examination of patterns of amenities/disamenities

4. MA Study by Faber & Kreig Minority communities average more than 4 x’s the number of hazardous waste sites Minority communities average more than 4 x’s the number of hazardous waste sites Minority communities exposed to nearly 5 x’s as many lbs. of chemicals Minority communities exposed to nearly 5 x’s as many lbs. of chemicals

5. MA Study by Faber and Kreig Low income communities exposed to nearly 7 x’s as many lbs. of chemicals Low income communities exposed to nearly 7 x’s as many lbs. of chemicals Low income communities average nearly 2.5 x’s more waste sites and 4 x’s as many waste sites per square mile Low income communities average nearly 2.5 x’s more waste sites and 4 x’s as many waste sites per square mile

6. National Data Robert Bullard Study: 2008 Robert Bullard Study: 2008 2000 Census Data 2000 Census Data Over 9 million people live within 3 Km of a commercial waste facility Over 9 million people live within 3 Km of a commercial waste facility These neighborhoods are 56% people of color These neighborhoods are 56% people of color Non-host communities are 30% people of color Non-host communities are 30% people of color Percentage comparisons: Percentage comparisons: African American 1.8 times greater African American 1.8 times greater Hispanic/Latino 2.3 times greater Hispanic/Latino 2.3 times greater Asian/Pacific Islander 1.8 times greater Asian/Pacific Islander 1.8 times greater

7. National Data Metropolitan Issue Metropolitan Issue Host areas are densely populated Host areas are densely populated 870 people/sq. km 870 people/sq. km 83% of sites are in metro areas (343 sites) 83% of sites are in metro areas (343 sites) Socio-economic disparities Socio-economic disparities Poverty rates 1.5x higher in host areas Poverty rates 1.5x higher in host areas Mean household income is 15% lower Mean household income is 15% lower

8. Methodology Critiques Definition of minority Definition of minority Unit of analysis Unit of analysis Summary: General pattern of distributional inequity Summary: General pattern of distributional inequity

9. Regulatory Salience Critique Distributive injustice alone: Not a concern Distributive injustice alone: Not a concern Absent evidence of discrimination or procedural bias Absent evidence of discrimination or procedural bias Post-siting market dynamics Post-siting market dynamics Which came first: The hazard or the distribution? Which came first: The hazard or the distribution? Community Preference Community Preference Blais: Market in preferences works well enough to conclude that, overall, disparities are generally justified by differing preferences. Blais: Market in preferences works well enough to conclude that, overall, disparities are generally justified by differing preferences.

10. Legal and Political Implications Political Force Political Force “Racism”: Contemporary moral strength “Racism”: Contemporary moral strength Connection to structural repression Connection to structural repression Constitutional Analysis Constitutional Analysis Narrower Narrower Purposeful conduct Purposeful conduct Consciousness of race as motivating factor Consciousness of race as motivating factor Individual actor Individual actor

11. Response Market critique Market critique Cole and Foster Cole and Foster Accept the critique Accept the critique Response: structural racism Response: structural racism Economic and social factors Economic and social factors Segregation in housing Segregation in housing Lack of political power Lack of political power Distributive outcomes are unjust Distributive outcomes are unjust Community Preferences Community Preferences Kaswan Kaswan Similarly: Structural racism suggests community preferences are not met Similarly: Structural racism suggests community preferences are not met

12. Implications Legal and political force measured by: Legal and political force measured by: Distance from Individual Actor Distance from Individual Actor Distance from race as decisional factor Distance from race as decisional factor Or at least consciousness of race as motivating factor Or at least consciousness of race as motivating factor

13. What’s Different About Our Study? Outcome equity vs. Process equity

14. Process-Equity Analysis Focuses on processes that create outcome inequity Focuses on processes that create outcome inequity Especially evidence of race as a known causal factor Especially evidence of race as a known causal factor Examples: hazardous waste facility/incinerator siting, court decisions, zoning maps and decisions Examples: hazardous waste facility/incinerator siting, court decisions, zoning maps and decisions

15. Our Hypothesis Land use processes over time situate disproportionate amount of disamenities in low income/minority communities Land use processes over time situate disproportionate amount of disamenities in low income/minority communities Race was a motivating factor Race was a motivating factor

16. How are we testing this hypothesis? Step 1: Gather data re “noxious use” decisions Step 1: Gather data re “noxious use” decisions Step 2: Overlay locations with race/income data Step 2: Overlay locations with race/income data Step 3: Determine if patterns of inequity exist Step 3: Determine if patterns of inequity exist Step 4: If yes, review and analyze decisional record Step 4: If yes, review and analyze decisional record

17. Zoning Determines where certain uses can occur Determines where certain uses can occur Allocation of Land Uses Allocation of Land Uses As of right As of right Conditional Use Conditional Use

18. Research Plan Zoning Maps Zoning Maps Conditional Use Decisions Conditional Use Decisions 1931-1971(Presumptive right) 1931-1971(Presumptive right) City Council City Council 1971 to present (Specified as of right/conditional) 1971 to present (Specified as of right/conditional) City Council City Council Zoning Board of Appeals Zoning Board of Appeals

19. What data have we found? Zoning Board of Appeals Decisions Zoning Board of Appeals Decisions City Council records City Council records Scale Scale Reviewed every decision 1931-present (10,000) Reviewed every decision 1931-present (10,000) Pulled 3000 decisions for review Pulled 3000 decisions for review Entered 1000 records relevant to environmental disamenities Entered 1000 records relevant to environmental disamenities

20. How did we categorize data? Incinerators Incinerators Recycling facilities Recycling facilities Penal/correctional facilities Penal/correctional facilities Garage/open parking lot Garage/open parking lot 100+ housing unit 100+ housing unit Other uses with environmental impacts Other uses with environmental impacts

21. Example of ZBA Spreadsheet Docket # Year Code Use/Disamenity Location Decision 6-60 1960 6 slaughter house 1242 Hargest Lane App. 475-89 1989 2 waste recycling plant 500 Chemical Rd App. 182-90 1990 2 landfill 3115 ft. w. of App. Patapsco Ave. on Baltin 277-91 1991 1 incinerator 3204-3214 Hawkins Pt. Rd. Disapp. 113-93 1993 4 auto repair shop 3146-3158 Wilkens Ave. Disapp.

22. Example of Ordinance Spreadsheet Number Year Code Disamenity Location 128 1940 6 Oil Storage Tank for Power Plant 2101-2121 Kloman St. 176 1952 6 Smelting Plant N. side of Open St. up to Marely Neck Branch 779 1957 2 Scrap iron and metals 1510 Aspen St. 1099 1971 1 Incinerator Pulaski Highway, Reedbird Ave. 304 1998 4 Open Area Parking Lot 1205 Bank St.

23. Data Analysis Map and analyze records in relation to race and income Map and analyze records in relation to race and income Overlay to demographic data Overlay to demographic data Evaluate change in spatial patterns over time Evaluate change in spatial patterns over time Review and analyze decisional record Review and analyze decisional record Map and analyze records in relation to Redlining Data Map and analyze records in relation to Redlining Data

24. Redlining Data Home Owners Loan Association Home Owners Loan Association Security Grade by Neighborhood Security Grade by Neighborhood High, Still Desirable, Declining, Hazardous High, Still Desirable, Declining, Hazardous Criteria Criteria Occupations of Residents Occupations of Residents Average annual income Average annual income Nationality Nationality Percentage of “negro” families Percentage of “negro” families Threat of Infiltration Threat of Infiltration “negro, foreign born, lower-grade populations” “negro, foreign born, lower-grade populations” Encroachment of Industrial Zone Encroachment of Industrial Zone Baltimore Reports Baltimore Reports Race and Industrial Character Race and Industrial Character

25. Redlining Data Implications Regulatory Salience Critique Regulatory Salience Critique Approval of Conditional Use Approval of Conditional Use Nature of proposed site Nature of proposed site Nature of surrounding area Nature of surrounding area Extent to which proposed use might impair present and future development Extent to which proposed use might impair present and future development Proximity of dwellings, churches, schools Proximity of dwellings, churches, schools Does Redlining Import Race as a Decisional Factor? Does Redlining Import Race as a Decisional Factor?

30. Next Steps: Evaluate the Market Critique Longitudinal analysis Longitudinal analysis Variances and Demographics Variances and Demographics By Decade By Decade Demographics inside impact zones and as compared to control areas or city as a whole Demographics inside impact zones and as compared to control areas or city as a whole Demographics in zones around approved versus disapproved variances Demographics in zones around approved versus disapproved variances Connections to decisional record Connections to decisional record Redlining Analysis Redlining Analysis Correlations between redlining zones and variances Correlations between redlining zones and variances Review of decisional records Review of decisional records