Search

Sociodemographic disparities in exposures to environmental contaminants pose challenges for environmental justice goals in the United States (U.S.). Marginalized communities are frequently exposed to high levels of toxicants despite federal air and drinking water quality standards aimed at protecting all individuals. Controls on emissions of Hazards Air Pollutants (HAPs) have been in place since 2012 as part of the Mercury and Air Toxics Standards (MATS) for U.S. coal- and oil-fired utilities, but this rule has been subject to many legal challenges. Prior work showed significant sociodemographic disparities in exposures to traditional air pollutants from U.S. power plants due to preferential siting in neighborhoods with relatively lower income and larger proportions of people of color. However, such differences had not been evaluated for mercury (Hg), a neurotoxicant that bioaccumulates in food webs. The Safe Drinking Water Act (SDWA) sets maximum contaminant levels (MCLs) for chemicals found in public water systems (PWS). More frequent MCL violations have been reported in U.S. PWS serving some marginalized communities. Prior research has largely focused on examining MCL violations using categorical models based on county level sociodemographic data. More spatially resolved PWS service area data are now available, allowing for better understanding of the relationship between community sociodemographic factors and water quality. This thesis develops novel statistical approaches for identifying sociodemographic disparities in exposures to toxicants from coal-fired power plants and public drinking water systems at the national level. In my thesis, I first explore potential sociodemographic disparities in exposure to Hg emitted by U.S. coal-fired power plants. Prior to MATS and relative to the U.S. general population, residents living within 5-km of power plants (n = 507) included greater proportions of frequent fish consumers, individuals with low annual income and less than high school education, and limited English-proficiency households. These results reinforce a lack of distributional justice in plant siting found in prior work. In 2020, significantly greater proportions of low-income individuals lived within 5-km of active facilities (n = 277) compared to plants that retired after 2010, suggesting that socioeconomic status may have played a role in retirement. Despite a 91\% decline in atmospheric Hg deposition between 2010-2020, remaining exposure from fish consumption near the largest active coal-fired power plants could still plausibly exceed the U.S. Environmental Protection Agency (U.S. EPA) reference dose for methylmercury. Next I examine associations between sociodemographic factors and detection and concentrations of four common inorganic contaminants in drinking water: arsenic (As), total chromium (Cr), manganese (Mn), and selenium (Se). I compared the results of my analysis between the county and PWS service area scales to better understand how data resolution issues affect conclusions regarding potential sociodemographic disparities. Concentrations of As, Cr, Mn, and Se in >273,000 samples from >21,000 PWS were collected between 2005-2015. I developed hurdle models for each contaminant to examine associations with sociodemographic characteristics of customers served by each PWS. PWS with higher proportions of limited English-speaking households had significantly higher probabilities of detecting As and Se. Among small PWS (serving ≤10,000 customers), these same households were also associated with higher concentrations of As and Se. Greater proportions of Black residents were associated with a lower probability of detecting As, Cr and Se, but significantly higher concentrations of detectable Cr, Mn, and Se, particularly outside of large urban areas. Significant associations for these contaminants were consistent in direction across PWS service area and county spatial units of analysis, but county results tended to exhibit greater effect sizes and fewer significant associations. Overall, this dissertation presents new evidence of sociodemographic differences in human exposures to environmental contaminants. The tools and methodological advances developed in this thesis will help to better identify marginalized populations experiencing disproportionately high health risks from environmental toxicants in the future.