Dataset Information

Uranium and radon in private bedrock well water in Maine: geospatial analysis at two scales.

ABSTRACT: In greater Augusta of central Maine, 53 out of 1093 (4.8%) private bedrock well water samples from 1534 km(2) contained [U] >30 ?g/L, the U.S. Environmental Protection Agency's (EPA) Maximum Contaminant Level (MCL) for drinking water; and 226 out of 786 (29%) samples from 1135 km(2) showed [Rn] >4,000 pCi/L (148 Bq/L), the U.S. EPA's Alternative MCL. Groundwater pH, calcite dissolution and redox condition are factors controlling the distribution of groundwater U but not Rn due to their divergent chemical and hydrological properties. Groundwater U is associated with incompatible elements (S, As, Mo, F, and Cs) in water samples within granitic intrusions. Elevated [U] and [Rn] are located within 5-10 km distance of granitic intrusions but do not show correlations with metamorphism at intermediate scales (10(0)-10(1) km). This spatial association is confirmed by a high-density sampling (n = 331, 5-40 samples per km(2)) at local scales (?10(-1) km) and the statewide sampling (n = 5857, 1 sample per 16 km(2)) at regional scales (10(2)-10(3) km). Wells located within 5 km of granitic intrusions are at risk of containing high levels of [U] and [Rn]. Approximately 48?800-63?900 and 324?000 people in Maine are estimated at risk of exposure to U (>30 ?g/L) and Rn (>4000 pCi/L) in well water, respectively.

SUBMITTER: Yang Q

PROVIDER: S-EPMC3993615 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Uranium and radon in private bedrock well water in Maine: geospatial analysis at two scales.

Yang Qiang Q Smitherman Paul P Hess C T CT Culbertson Charles W CW Marvinney Robert G RG Smith Andrew E AE Zheng Yan Y

Environmental science & technology 20140328 8

In greater Augusta of central Maine, 53 out of 1093 (4.8%) private bedrock well water samples from 1534 km(2) contained [U] >30 μg/L, the U.S. Environmental Protection Agency's (EPA) Maximum Contaminant Level (MCL) for drinking water; and 226 out of 786 (29%) samples from 1135 km(2) showed [Rn] >4,000 pCi/L (148 Bq/L), the U.S. EPA's Alternative MCL. Groundwater pH, calcite dissolution and redox condition are factors controlling the distribution of groundwater U but not Rn due to their divergent ...[more]

PMID: 24655434

Similar Datasets

Project description:Arsenic is a naturally occurring toxic element often concentrated in groundwater at levels unsafe for human consumption. Private well water in the United States is mostly unregulated by federal and state drinking water standards. It is the responsibility of the over 13 million U.S. households regularly depending on private wells for their water to ensure it is safe for drinking. There is a consistent graded association with health outcomes at all levels of socioeconomic status (SES) in the U.S. Differential exposure to environmental risk may be contributing to this persistent SES-health gradient. Environmental justice advocates cite overwhelming evidence that income and other SES measures are consistently inversely correlated with exposure to suboptimal environmental conditions including pollutants, toxins, and their impacts. Here we use private well household surveys from two states to investigate the association between SES and risks for arsenic exposure, examining the potentially cumulative effects of residential location, testing and treatment behavior, and psychological factors influencing behavior. We find that the distribution of natural arsenic hazard in the environment is socioeconomically random. There is no evidence that higher SES households are avoiding areas with arsenic or that lower SES groups are disproportionately residing in areas with arsenic. Instead, disparities in exposure arise from differing rates of protective action, primarily testing well water for arsenic, and secondly treating or avoiding contaminated water. We observe these SES disparities in behavior as well as in the psychological factors that are most favorable to these behaviors. Assessment of risk should not be limited to the spatial occurrence of arsenic alone. It is important that social vulnerability factors are incorporated into risk modeling and identifying priority areas for intervention, which should include strategies that specifically target socioeconomically vulnerable groups as well as all the conditions which cause these disparities in testing and treatment behavior.

Project description:Approximately one million people in the UK are served by private water supplies (PWS) where main municipal water supply system connection is not practical or where PWS is the preferred option. Chronic exposure to contaminants in PWS may have adverse effects on health. South West England is an area with elevated arsenic concentrations in groundwater and over 9000 domestic dwellings here are supplied by PWS. There remains uncertainty as to the extent of the population exposed to arsenic (As), and the factors predicting such exposure. We describe a hazard assessment model based on simplified geology with the potential to predict exposure to As in PWS. Households with a recorded PWS in Cornwall were recruited to take part in a water sampling programme from 2011 to 2013. Bedrock geologies were aggregated and classified into nine Simplified Bedrock Geological Categories (SBGC), plus a cross-cutting "mineralized" area. PWS were sampled by random selection within SBGCs and some 508 households volunteered for the study. Transformations of the data were explored to estimate the distribution of As concentrations for PWS by SBGC. Using the distribution per SBGC, we predict the proportion of dwellings that would be affected by high concentrations and rank the geologies according to hazard. Within most SBGCs, As concentrations were found to have log-normal distributions. Across these areas, the proportion of dwellings predicted to have drinking water over the prescribed concentration value (PCV) for As ranged from 0% to 20%. From these results, a pilot predictive model was developed calculating the proportion of PWS above the PCV for As and hazard ranking supports local decision making and prioritization. With further development and testing, this can help local authorities predict the number of dwellings that might fail the PCV for As, based on bedrock geology. The model presented here for Cornwall could be applied in areas with similar geologies. Application of the method requires independent validation and further groundwater-derived PWS sampling on other geological formations.

Dataset Information

Uranium and radon in private bedrock well water in Maine: geospatial analysis at two scales.

Publications

Uranium and radon in private bedrock well water in Maine: geospatial analysis at two scales.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets