Associations Between Landfill Proximity and Water Quality Analytes from Private Domestic Wells in Rural Virginia

Abstract

The Chickahominy T.R.U.T.H. (Trust, Research, Understand, Teach, and Heal) Project investigates water quality concerns, including potential contamination from a nearby landfill, and their corresponding health implications among residents of rural Charles City County, Virginia. This rural, majority-racial-minority county includes citizens of the Chickahominy Indian tribe. The T.R.U.T.H. Project utilizes a community-based participatory research approach and environmental justice-focused lens to study water quality and health; the present study represents the first comprehensive analysis of the drinking water quality of homes with domestic groundwater wells. We collected water samples from 121 participants located within a four-mile radius of the landfill, analyzing over 200 potential analytes that may affect water quality. Among the measured analytes, water pH, aluminum, iron, manganese, and hardness as CaCO₃ were most frequently identified as having ratings outside of established EPA limits (“Bad”). Logistic regression models demonstrated that proximity to streams near the landfill was associated with significantly greater odds of worse water quality for several analytes. Specifically, residing within a mile of these streams was associated with greater odds of “Fair” or worse turbidity (OR = 4.31, 95% CI 1.31–19.53) and zinc levels (OR = 2.63, 95% CI 1.23–5.86). Additionally, residing within half a mile of a proximate stream was linked with “Poor” or worse hardness ratings (OR = 10.71, 95% CI 1.64–86.96); residing within a mile of the landfill was associated with “Bad” water pH levels (OR = 10.50, 95% CI 1.16–95.68). Though many tested analytes did not have concerning ratings or were not significantly associated with proximity to the landfill or streams, the above findings suggest that anthropogenic factors, particularly landfill proximity, may influence water quality with regard to specific analytes. Therefore, addressing water quality through enhanced monitoring, contaminant remediation, and community education is crucial for restoring trust in drinking water and improving public health outcomes.

1. Introduction

The quality and safety of drinking water is fundamental to public health. The physical and chemical properties of water, such as hardness and pH, can modify water’s taste and odor, diminish the effectiveness of soaps and detergents, and affect plumbing systems [1,2,3,4,5,6]. Additionally, the presence of heavy metals/metalloids in drinking water, such as arsenic or chromium, poses significant health risks, as these metals can accumulate in the body and lead to long-term health problems including Parkinson’s disease, muscular dystrophy, and cancer [7,8]. Contaminated water sources can also serve as vectors for harmful microorganisms, including bacteria, viruses, and parasites, causing waterborne illnesses such as cholera and typhoid [6,9,10,11]. Exposure to these contaminants can have severe consequences, particularly for vulnerable populations including children and the elderly [9,11].

One way in which the likelihood of such exposure is lessened is through access to public drinking water systems. The majority of United States (U.S.) households are served by public water systems, which are held to rigorous federal and state quality standards. The creation of these public water systems has been particularly beneficial for public health, with one study attributing almost two-thirds of the declines in child mortality and nearly one-half of overall mortality declines between 1900 and 1936 to their advent [12]. Regulations such as the Safe Drinking Water Act ensure adequate filtration, frequent monitoring, and tracking of contamination levels and water properties in public water systems [13]. However, domestic groundwater wells are usually not included in public water treatment and quality monitoring efforts. As such, these wells frequently have higher concentrations of contaminants and other hazardous water conditions [14]. Thus, understanding and monitoring the properties of drinking water are crucial for ensuring water safety [15,16]. Such monitoring is particularly relevant in rural and underserved communities, where residents are more likely to obtain their drinking water from domestic groundwater wells that are more vulnerable to contamination than public water systems [17]. Further, though public water systems are often subject to frequent monitoring and treatment, private well owners must generally ensure their own water supply’s safety at their own expense, making rural communities more susceptible to the effects of groundwater pollution [17,18,19].

Anthropogenic hazards, such as landfills, are also more likely to be located in rural, structurally underserved and minoritized communities [20]. For example, a large-scale national analysis found strong and statistically significant associations between the proportion of Black and Latine residents living in an area and the area’s presence of non-hazardous waste landfills, even after controlling for other socio-economic factors [20]. Landfills can introduce pollutants into local water sources, potentially affecting the health and well-being of residents. Numerous studies have documented contaminants in groundwater near landfills [18,19,21,22]. One possible mechanism by which this can occur is leachate transfer. Leachate produced during municipal solid waste decomposition can migrate through the soil and enter the local water supply [18,23]. This leachate may contain heavy metals and organic pollutants, which may adversely affect the health of the surrounding communities [18,24,25,26,27,28]. Therefore, addressing private well water contamination is vital for mitigating these health risks.

This issue of drinking water quality is particularly relevant in Charles City County, Virginia, a rural community with a population of 6610 and where 53% of residents are from racial and ethnic minority groups, including the Chickahominy Indian Tribe [29]. This community relies heavily on private wells for their water supply [30], like many other rural communities in Virginia [31,32]. The proximity of some of these wells to the municipal landfill or streams near it poses unique challenges for maintaining drinking water quality, which has prompted concerns among residents about their drinking water. These concerns were further amplified by suspicions of a cancer cluster within the community, which seemed to follow the establishment of the landfill. In response, a community–academic partnership was formed between the Chickahominy Indian Tribe and Virginia Commonwealth University’s Massey Comprehensive Cancer Center to assess perceptions of cancer risk and provide comprehensive drinking water testing in the homes of residents living within a four-mile radius of the landfill.

The quality and safety of drinking water are essential for public health, not only for the apparent reasons but also because it is a resource often taken for granted. The documented consequences of residing in communities facing the threat of water contamination include numerous adverse health outcomes and altered behaviors. The term “threat” is crucial in this context; even the perceived risk that the water used for daily consumption might be harmful may significantly influence individual and community behaviors. Herein, we report novel findings from the Chickahominy T.R.U.T.H. Project. Using a community-engaged approach, we sampled water from private wells and examined samples for contaminants in order to investigate associations between water quality and proximity to a municipal landfill. This research holds critical significance in unraveling potential environmental and racial health disparities in this community.

2. Methods

2.1. Study Sample and Design

The water samples analyzed in this study were collected as part of the Chickahominy T.R.U.T.H. (Trust, Research, Understand, Teach, and Heal) Project, which is a community–academic partnership between citizens of the Chickahominy Indian Tribe and Virginia Commonwealth University’s Massey Comprehensive Cancer Center. This initiative will be referred to as the T.R.U.T.H. Project throughout the study. The partnership seeks to understand the impact of structural and environmental factors on perceived cancer risk among residents of Charles City County, VA, USA. A detailed description of the project’s design and study population has been previously published [33]. For context, we will first provide a brief overview of relevant aspects of the T.R.U.T.H. Project’s research design and sample as they pertain to the current investigation. Project participants were recruited via advertisements posted in local business and newspapers, on social media, and a study website. Postcards describing the study were also mailed to all households in the county. Concurrently, residents were trained as Health Brigadiers. In one phase of the project, Health Brigadiers conducted semi-structured interviews with participating Charles City County residents, using an interview guide focused on health beliefs, perceptions of cancer risk, experiences, and attitudes. These questions were related to concerns of potentially elevated cancer rates in the community and subsequent establishment of the partnership. The T.R.U.T.H. Project also involved collecting drinking water samples, primarily from private wells at the homes of participating adults (18+ years) residing within a four-mile radius of the local landfill in Charles City County, Virginia. This radius was selected based on geographical data, environmental considerations, and recommendations from the tribal environmental director [33].

2.2. Description of the Landfill, Proximate Streams, and Underlying Geology

The Charles City landfill is a sanitary landfill that has been operational since 1990, covering approximately 100 acres and designed to handle municipal solid waste. The facility is designed to manage a significant volume of waste, with a capacity that allows it to accept thousands of tons of municipal solid waste annually [34,35]. The landfill employs various waste management strategies to optimize its operations, including the management of leachate and landfill gas, which are byproducts of waste decomposition [36]. The landfill’s design incorporates features that facilitate the degradation of waste, which is critical for extending the lifespan of the facility and minimizing its environmental footprint. This includes the implementation of biological, chemical, and physical processes that occur within the landfill, promoting waste breakdown and reducing the volume of waste over time. Furthermore, the landfill’s management practices align with contemporary waste management strategies that are meant to emphasize sustainability and environmental protection [34,35].

Publicly available information detailing the specific design and construction of the Charles City County Landfill is limited. However, through a Freedom of Information Act request to the County of Charles City, we obtained information regarding the planned cell construction. The design was to include a 1-foot compacted clay liner with a permeability of 10⁻⁷ cm/sec or less, in combination with a 60-mil HDPE liner, followed by 18 inches of sand with a leachate collection system. Additionally, an 80-mil HDPE liner was planned to be placed above this system, also covered by 18 inches of sand, and include a leachate collection system designed to allow identification of the phase from which leachate is collected. Notably, the landfill has been subject to multiple violations identified by the Virginia Department of Environmental Quality (DEQ) over the years. In 2019, DEQ determined that existing controls were failing to minimize pollutants in stormwater discharges from the site, and modifications to these control measures were deemed necessary to reduce environmental impacts.

We geocoded the location of the centroid of the landfill using latitude and longitude coordinates. The landfill is also located near numerous streams and small waterways. We obtained the shapefiles defining the geographic extent of these streams and waterways using a public database [37] and geocoded these as well.

Regarding underlying geology, Charles City County contains several confined aquifers separated from each other by thick layer of clay, as well as an unconfined shallow aquifer that provides water for the shallow wells that comprise the majority source of drinking water in the county [30]. Because the unconfined aquifer is shallow, it is considered susceptible to contamination. Continued groundwater withdrawal has lowered water levels throughout aquifers in recent decades. Regarding lithology, a total of eight formations are found in the county (Shirley, Charles City, Chuckatuck, Alluvium, Windsor, Bacons Castle, Chesapeake, Tabb). The primary and secondary rock types within these formations include gravel, sand, silt, clay or mud, or alluvium [38].

2.3. Data Collection

Previously recruited T.R.U.T.H. Project participants who lived within a four-mile radius of the landfill were approached by trained Health Brigadiers, who obtained consent and collected water samples. Drinking water samples from each participant in the study were collected using the EnviroTestKits SafeHome Ultimate Drinking Water Test Kit [39]. This direct-to-consumer product tests for approximately 200 properties and potential contaminants, categorized as metals, semi-volatile organic compounds, trihalomethanes, volatile organics, physical properties, and inorganics, which are referred to collectively as “analytes” herein. The majority of samples were collected from study participants (age 18+) whose homes’ primary water source was a private well. Water was primarily collected from the kitchen tap, although bathroom taps were used for a small number of homes. Additionally, a small number of water samples were collected from streams near the landfill. Samples were sent to an Environmental Protection Agency (EPA)-certified laboratory for analysis, and results were returned for N = 121 participants.

2.4. Laboratory Rating

Analytes were rated by the kits as belonging to one of four mutually exclusive categories: “Good”, “Fair”, “Poor”, or “Bad”. A “Good” rating indicated that the analyte was not detected in the water sample or that the concentration fell within the EPA’s acceptable range. A “Fair” rating indicated that the concentration was detected in the sample (if no EPA limit had been established for the analyte) or that the concentration was less than half of the EPA limit (if an EPA limit had been established for the analyte). A “Poor” rating indicated that the concentration was greater than half of the EPA limit for the analyte. A “Bad” rating indicated that the concentration was above the EPA’s limit for that analyte or that the concentration fell above the EPA’s acceptable range if applicable. Determination of concentrations was based on EPA Method 200.7 for metals, Method 524.2 for volatiles, Method 525.2 for semi-volatiles, Method 300.1 for ions, Standard Method (SM)-4500H+B for pH, SM-2320B for Alkalinity, Bicarbonate, and Carbonate, and SM-2510B for Conductivity (private communication with SafeHome).

2.5. Exposure Assignment

First, participants’ residential addresses were geocoded using the “tidygeocoder” package in R [40]. Two participants did not have addresses that produced valid geocoded coordinates, making the sample size N = 119 for the analysis described in Section 2.4. For each participating household, we calculated their Euclidean (straight-line) distance to the landfill and to the closest proximate stream within a one-mile radius of the centroid of the landfill. A map illustrating this process is provided in Figure 1. These continuous distance exposure measures, along with dichotomized versions, were used in our analysis.

2.6. Statistical Analysis

We fit logistic regression models to estimate the associations between the exposure measures and the water sampling outcomes. For each analyte, we defined three binary outcome variables: one grouping “Fair”, “Poor”, and “Bad” ratings as the occurrence of the outcome; another grouping “Poor” and “Bad” ratings; and a third considering only “Bad” ratings. Models were fitted only if the outcome occurred at least once among participants. Separate logistic regression models were fitted for each outcome variable and analyte, using different forms of exposure measures: within one mile (binary), within one half of a mile (binary), and using continuous distance to the landfill and proximate streams. Associations were considered significant if the p-value for the regression coefficient was less than 0.05. For these significant associations, we reported odds ratios along with their 95% confidence intervals. We also conducted a sensitivity analysis controlling for the underlying geological characteristics of water sampling locations using lithology data from the Virginia Department of Energy [38]. All analyses were conducted in R, Version 4.3.1 [41].

3. Results

A total of 153 residences, including one tribal center and one church, were invited to participate in the study. Of these, 151 residents expressed interest, while 2 declined participation, resulting in a recruitment rate of 98.7%. During the study period, water samples were collected from residences, one creek, a marshland area in the landfill, and two community buildings (the church and the tribal center). Among the residential water samples, 26 were collected from shallow wells (<50 feet) and the remainder from deep wells (>100 feet).

Several analytes received “Fair” or worse ratings (Figure 2) for all or all but one sample. These included various physical properties (hardness as CaCO₃, Langelier Index, Ryznar Index, Total Dissolved Solids (TDS), alkalinity as CaCO₃, bicarbonate, and conductivity) and the Aggressive Index. Additionally, other analytes such as calcium, sodium, turbidity, and strontium received “Fair” or worse ratings for over 100 samples. Four analytes (fluoride, water pH, aluminum, and iron) received “Poor” or worse ratings (Figure 3) for more than 10 samples. Finally, 12 and 9 samples had ratings of “Bad” for water pH and aluminum, respectively (Figure 4). The majority of water pH ratings that were “Poor” or worse were slightly acidic (water pH values of 5.5–6.5).

There were 43 analytes with at least one “Fair” or worse rating. In the logistic regression models (

Table 1. Summary of significant associations from logistic regression models for drinking water analytes and exposures to landfill and proximate streams.

Analyte	Outcome	Exposure	p-Value	Odds Ratio (95% Confidence Interval)
Zinc (Metals)	Fair or worse	Stream, <1 mi	0.015	2.63 (1.23, 5.86)
Turbidity (Physical properties)	Fair or worse	Stream, <1 mi	0.028	4.31 (1.31, 19.53)
Hardness as CaCO3 (Physical properties)	Poor or worse	Stream, <0.5 mi	0.013	10.71 (1.64, 86.96)
Water pH (Physical properties)	Bad	Landfill, <1 mi	0.026	10.50 (1.16, 95.68)

), samples taken from participants residing near streams proximate to the landfill were significantly more likely to have “Fair” or worse ratings for two analytes. Specifically, residing within a mile of a stream proximate to the landfill was associated with significantly higher odds of “Fair” or worse turbidity (OR = 4.31, 95% CI [1.31, 19.53], p = 0.028) and of “Fair” or worse zinc levels (OR = 2.63, 95% CI [1.23, 5.86], p = 0.015).

There were ten analytes with at least one “Poor” or worse rating and five analytes with at least one “Bad” rating. The proximity measures were also related to two of these more concerning ratings (Table 1). Specifically, residing within half a mile of a stream near the landfill was associated with significantly higher odds of a “Poor” or worse rating of hardness as CaCO₃ (OR = 10.71, 95% CI [1.64, 86.96], p = 0.013). Residing within a mile of the landfill was associated with significantly higher odds of a “Bad” rating for water pH (OR = 10.50, 95% CI [1.16, 95.68], p = 0.026, Table 1). A map illustrating the spatial distribution of these two water quality outcomes by their proximity to the landfill and proximate streams is provided in Figure 5.

The sensitivity analysis found that the underlying lithology did not confound any of the significant associations identified above. Specifically, residing within a mile of a proximate stream remained associated with significantly greater odds of “Fair” or worse turbidity (OR = 4.66, 95% CI [1.40, 21.27], p = 0.022) and of “Fair” or worse zinc (OR = 2.50, 95% CI [1.15, 5.63], p = 0.023); residing within half a mile of a proximate stream remained associated with significantly greater odds of “Poor” or worse hardness as CaCO₃ (OR = 9.22, 95% CI [1.41, 74.88], p = 0.020); and residing within a mile of the landfill remained associated with significantly greater odds of a “Bad” water pH rating (OR = 13.42, 95% CI [1.44, 127.15], p = 0.016).

4. Discussion

This study examined drinking water quality indicators primarily from private wells in the Chickahominy tribal community in Charles City County, VA, USA, as well as proximity to a municipal solid waste landfill. Our findings echo residents’ concerns about their drinking water, with numerous analytes showing suboptimal EPA-defined ratings. Specifically, physical properties, such as hardness as CaCO₃ and water pH, and metals, such as aluminum, iron, and manganese, had “Bad” ratings at multiple residential locations in our sample. We also observed a significant number of “Fair”, “Poor”, and “Bad” readings for several analytes, as well as significant associations between proximity to the landfill and sub-optimal readings of four analytes (zinc, turbidity, hardness, water pH). Importantly, these associations were not a function of the underlying geology, as identified by the sensitivity analysis. These results highlight the significant influence of anthropogenic factors, especially proximity to potential contamination sources, in shaping water quality.

There is evidence in the literature suggesting associations between proximity to landfills and water quality measures. For example, a recent study identified greater turbidity and hardness in drinking water sites close to a landfill than far from it [42]. Talalaj and Biedka utilized a landfill water pollution index and identified a higher concentration of zinc proximate to a landfill, possibly due to its harboring of zinc-based materials and fertilizer products [43]. Additional studies identified that residence in the counties surrounding an EPA Superfund-designated waste site was associated with increased bladder cancer deaths and incidence of other cancers [44] and that residing adjacent to a landfill in Quebec was associated with increased incidence of stomach, liver, lung, and prostate cancer in men and with stomach and cervical cancer in women [45]. Finally, an analysis of twenty-four years of readings surrounding a landfill found that pollutant levels were notably higher closer to than farther from the landfill [46]. While the findings in our study do not associate a specific landfill with the incidence of specific cancers, we believe that further investigation of the findings identified here is warranted given the elevated levels of drinking water contaminants proximate to the landfill.

The analytes with sub-optimal ratings in our study have been associated with health consequences and may possibly decrease trust in the quality and health of residential well water in Charles City County. For example, CaCO₃ (or hardness) indicates high levels of calcium and magnesium in the water, which can lead to scaling in pipes and appliances, potentially causing skin irritation and exacerbating skin conditions [47]. Excessive TDS indicates high concentrations of dissolved substances, which can affect the taste of water and may include harmful contaminants [48,49,50]. Further, elevated levels of alkalinity and bicarbonate can also contribute to scaling and taste issues [51,52]. High turbidity indicates the presence of suspended particles, which can harbor harmful microorganisms and reduce the effectiveness of disinfection processes.

Several analytes with multiple “Poor” or worse ratings have been linked with health consequence as well. Elevated fluoride levels, while beneficial in small amounts for dental health, can lead to dental and skeletal fluorosis at high concentrations [53,54]. Abnormal water pH levels, such as those seen in our sample (specifically, the majority of which that were slightly acidic), can cause gastrointestinal discomfort and potential pipe corrosion [55]. High aluminum levels have been associated with neurodegeneration and other negative neurological effects [56,57]. Elevated iron levels can cause gastrointestinal issues and lend an unpleasant taste and color to drinking water, affecting its palatability [58,59].

While this study was not designed to associate the Charles City County landfill with increased incidences of specific cancers or other health outcomes, we believe that further investigation is warranted. Future research should explore the potential health impacts of the findings identified here, given the elevated levels of drinking water contamination and “Fair” or below ratings on water quality indicators proximate to the landfill and its streams. Rightfully, these findings may impact the community’s perception of their drinking water quality, leading to decreased confidence in the safety of their water supply. Such a lack of trust can result in residents avoiding tap water, potentially consuming inadequate amounts of water, turning to more expensive bottled water, or drinking other non-water liquids, which could exacerbate health inequities and financial burdens. The psychological stress and anxiety related to perceived water contamination can also negatively affect overall well-being and community morale [60]. Therefore, addressing these water quality issues is essential to restoring trust and ensuring the health and safety of the community.

Notably, Charles City County residents are among the approximately 13% of U.S. residents who obtain their water from private wells rather than the public water systems that have more rigorous water quality standards [61]. For multiple reasons that include ongoing residential segregation, economic injustice, zoning decisions that exclude certain communities, and uneven governmental investment, rural communities and communities with large Black, Indigenous, and Latine populations are less likely to be served by public water systems, instead relying on private wells [62]. Prior research has documented a number of health disparities related to these inequities in water source and quality. For example, a 2017 study found higher rates of emergency room utilization for acute gastrointestinal illness in a predominantly Black community that relies on private wells for drinking water and calculated that at least 22% of these emergency room visits could be prevented by extending the public water system [63]. Another study found higher levels of arsenic in private wells as compared to public water systems, with elevated arsenic levels also seen in counties with larger Indigenous and Latine populations [64]. Likewise, a North Carolina study found that blood lead concentration levels were an average of 20% higher in children whose primary water source was private wells, as compared to public water sources, even after controlling for individual- and community-level factors [65]. Higher lead exposures have been noted across the lifespan for Black individuals as compared to their white counterparts [66], and inequities in access to higher-quality drinking water have been named as a contributing factor. This finding is notable because there is no safe level of lead exposure [65]. Our finding of elevated water properties associated with damage and corrosion to pipes raises similar concerns about the potential of increased exposure to lead for Charles City County residents.

The American Public Health Association has named water quality as an important health equity issue [67], while the American Academy of Pediatrics has called for measures to increase access to public water systems and decrease children’s exposure to water from private wells [14]. Similarly, anthropogenic hazards such as landfills and other sources of contamination are significantly more likely to be located in low-income communities of color, a practice known as environmental racism [68]. This combination of disproportionate burden of exposure to environmental hazards and a lower likelihood of being served by public water systems [62,69] therefore makes rural communities of color more susceptible to the health impacts of groundwater pollution.

It is worth noting that of the approximately 200 analytes tested, the vast majority did not have concerning readings from the water sampling analysis. Specifically, only five specific analytes had any “Bad” readings (denoting levels above EPA limits) in our sample, and only three of these (water pH, aluminum, and iron) had more than five such readings. Despite the significant associations we identified with proximity to the landfill and proximate streams, some of the detected analytes are naturally occurring, and fortunately, none of the analytes with “Bad” readings detected in our sample were any of the seven identified toxic legacy and emerging drinking water contaminant groups (arsenic, disinfection by-products, fracking-related substances, lead, nitrate, per- and polyfluorinated alkyl substances (PFAS), and uranium) [70].

Our study had several strengths. First is the design of the Chickahominy T.R.U.T.H. Project as a community–academic partnership that is motivated by community health concerns and operates with shared understanding, respect, and teamwork between all parties involved. Second is the use of powerful and comprehensive drinking water sampling kits for many study participants across our study region. Third is the use of standardized, validated EPA test methods and precise geospatial exposure assignment through geocoding and landfill, as well as proximate stream locations. Fourth is an intuitive and comprehensive analytic pipeline, which involved first defining exposure based on geographic proximity and then testing exposures with binarized analyte outcomes with logistic regression models. This pipeline can be extended or adapted to similar contexts.

The strengths of our study should be viewed in the context of its limitations. First, there is a possibility of existing analyte concentrations that fell below the detection limits of the test kits. Second, though the water sampling kits tested over 200 analytes, there is a possibility that other analytes in drinking water could be relevant for health consequences. Third, our study was cross-sectional in nature, and factors other than proximity to the landfill or proximate streams may also be associated with the sub-optimal ratings identified. Fourth, samples were collected only once at residential addresses due to the ongoing recruitment, consent, and interviewing structure of the T.R.U.T.H. Project. It is possible that temperature and precipitation variations on different sampling days may have played a role in sampling results. It would be beneficial in future research to perform water sampling several times over a longer time period to examine the stability of the testing results over time. Finally, future research should ensure comprehensive sampling coverage in this region proximate to the landfill to more fully investigate the role of proximity with continuous measures of water quality, as well as incorporate data on microbiological components.

Importantly, the Chickahominy T.R.U.T.H. Project establishes a foundation for future research and policy development aimed at safeguarding vulnerable populations from environmental health risks. These findings inform public health strategies, shape policy decisions, and promote community engagement with environmental health issues. For example, study participants with “Bad” readings of certain analytes can be offered additional water treatment services and/or additional testing kits to be able to monitor for changes in drinking water quality over time. This effort aims to support more equitable and effective health interventions and policies tailored to address the specific vulnerabilities and concerns of those relying on private well water, particularly in rural Charles City County, VA, USA.

5. Conclusions

This study suggests the influence of anthropogenic factors on private well water quality in a rural community of color in Virginia, demonstrating an association between proximity to a landfill and diminished water quality for several analytes. This effort establishes a foundation for future community-engaged research and policy development aimed at increasing access to public water systems and reducing health disparities. Our study findings highlight the need for targeted interventions to enhance water safety and rebuild community confidence in the drinking water supply. Priority actions should focus on improving water quality through intensified monitoring, remediating contaminated sites, and educating community members on water safety to enhance their ability to identify potential issues and seek appropriate intervention. Transparent communication and community involvement in water management decisions are crucial for rebuilding trust. Additionally, future research and health disparity reduction efforts should focus on measuring and addressing the impacts of anthropogenic hazards on private well water. By addressing these critical issues, we can pave the way for enhanced public health outcomes and a revitalized sense of trust and security in the safety of drinking water for all residents.