In 2016, approximately 15 million people lived within one mile of Superfund sites, including approximately 5% of all children in the United States (US) under 5 years of age. Lead (Pb), arsenic (As), and cadmium (Cd) are among the top ten contaminants on the Agency for Toxic Substances and Disease Registry?s 2017 Substances Priorities List for Superfund sites. These and other metals/metalloids can contaminate surface waters and groundwater systems, leading to elevated exposures through drinking water. Across the US, tens of millions of individuals consume drinking water with concentrations of heavy metals in excess of regulatory guidelines. Exposures to heavy metals have been associated with many negative impacts on public health, including impacts on neurodevelopment and cognitive aging. However, the contribution of different Superfund sites to this contamination problem remains poorly characterized on a national scale. This is important because regulations for drinking water contaminants and risk mitigation actions are often undertaken at the federal level, but most prior work has focused on site-specific studies. Proximity to Superfund sites may be associated with higher risk of contamination by heavy metal mixtures in tap water. This relationship is likely more prominent in private wells than in municipal drinking water supplies, where the finished water quality is influenced by water treatment technologies. Across different geographic areas, there are considerable differences in municipal water treatment technology and continuous development of innovative technologies, but little information is available on how this affects spatial patterns of metal concentrations in tap water.
In Aim 1, we will characterize the role of Superfund sites across the country for heavy metals in private wells by developing novel hybrid mechanistic-empirical models for heavy metals across the US using a large database of measurements in groundwater from the USGS, locations of point sources such as Superfund sites, and hydrogeological features/predictors that affect the fate and transport of trace metals.
For Aim 2, we will use new measurements and models to identify the spatial co- occurrence of different metal mixtures relevant to human exposures from drinking water. This analysis will be used to identify the composition of metal mixtures for in vitro toxicity tests on brain organoids in Project 2.
Aim 3 will leverage >28 million measurements of heavy metals from municipal water supplies to field-evaluate the role of different treatment technologies. This will provide insights into the effectiveness of treatment technologies and can help inform Project 4 as well as Superfund site managers responsible for remediation. This project provides a link between biomedical research in the MEMCARE Center, human exposures, and potential benefits of remediation technology being developed in Project 4.

Public Health Relevance

Improved exposure and risk assessment methods, particularly for heavy metal mixtures in private wells surrounding Superfund sites, and information on the field-effectiveness of water treatment technology are needed to manage contaminated site remediation goals and develop drinking water guidance. This project will develop a novel statistical tool to forecast the contribution of Superfund sites to heavy metal mixtures in private wells and will evaluate the effectiveness of water treatment technologies to remove heavy metal concentrations in public water supplies. The hybrid mechanistic-empirical models for heavy metals in drinking water developed as part of this project can be broadly used to identify populations potentially at risk for elevated exposures to heavy metals through contaminated drinking water.

National Institute of Health (NIH)
National Institute of Environmental Health Sciences (NIEHS)
Hazardous Substances Basic Research Grants Program (NIEHS) (P42)
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Harvard University
United States
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