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Author ORCID Identifier



Open Access Dissertation

Document Type


Degree Name

Doctor of Philosophy (PhD)

Degree Program


Year Degree Awarded


First Advisor

Michael Ash

Second Advisor

James Boyce

Third Advisor

Anita Milman

Subject Categories

Other Economics


Rising income and wealth disparities are increasingly viewed as serious economic and social problems, but what are the environmental consequences of an unequal distribution of income and wealth? Are low income neighborhoods disproportionately negatively affected by pollution exposure, and does economic inequality thus manifest itself in environmental inequality? Are poor or unequal communities less successful in collectively organizing local environmental improvements and does inequality thus increase pollution exposure for all residents? This dissertation provides some empirical evidence on these questions. Chapter 1 analyzes regional variations in environmental disparities in US cities. Using geographic micro-data from EPA's Risk Screening Environmental Indicators on industrial air pollution exposure and socio-economic data from the US Census at the blockgroup-level, we find strong empirical evidence for environmental disparities by income and race/ethnicity in US cities. However, we also find some striking regional variations in the magnitude in cities across the country. A finding that stands out across regions is that race and ethnicity are stronger predictors for air pollution exposure in the poorer half of neighborhoods in US cities. Chapter 2 investigates if neighborhood inequality affects the neighborhood's organizing capacities for local environmental improvements, using census tract-level data on industrial air pollution from EPA's Risk Screening Environmental Indicators and income and demographic variables from the American Community Survey and EPA's Smart Location Database. Estimating a spatial model of pollution exposure, we find evidence that overall neighborhood inequality - as measured by the ratio between the fourth and the second income quintile or the neighborhood Gini coefficient - increases local exposure, whereas a concentration of top incomes reduces local exposure. Chapter 3 analyzes the socio-demographic correlates of proximity to fracking wells in five US states. The geocoded fracking well data were merged with blockgroup-level socio-economic variables from the American Community Survey and the Smart Location database; the socio-economic characteristics of neighborhoods with increased proximity to fracking activity were compared. I find that racial and ethnic minorities disproportionately live near fracking wells, and that educational attainments decline with proximity to fracking activity. However, there are substantial regional variations in these patterns.