Geology topics

Melissa A. Lombard

Publications and source records attributed to Melissa A. Lombard.

At least 19 recordsLinked to original sources

USGS2026

Anthropogenic and geogenic factors affecting groundwater arsenic and potential drinking water exposure in the San Luis Valley, Colorado

Groundwater arsenic is a serious health threat in many regions with limited surface water drinking supplies. In the San Luis Valley, Colorado, USA, where most residents rely on groundwater for drinking water, elevated groundwater arsenic concentrations (≥5 μg/L) were observed in 19.8% of private wells. Many recent studies have leveraged data science methods to estimate the spatial variability of arsenic at local, regional, and global scales. These studies typically predict depth-independent arsenic concentrations due to limited well depth information. However, arsenic concentrations may vary greatly with depth due to heterogeneous aquifer geochemistry, including redox potential, pH, and biogeochemical conditions. In this study, we apply random forest modeling to predict elevated groundwater arsenic concentrations (≥5 μg/L) over space and depth continuously across the San Luis Valley using a community-driven data set of 435 groundwater measurements of major ions and trace metals. Our model reveals the influence of several known or hypothesized drivers or proxy drivers of arsenic in groundwater, including surface elevation, fraction of fine-grained aquifer sediments, well depth, soil pH, long-term subsidence, and geothermal influences. Elevation, percentage of fine-grained sediments, and elemental indicators of geothermal fluid influence are some of the most important predictors of arsenic, while long-term subsidence is found to have a weak but positive relationship with arsenic. The model has a specificity of 0.82 and a sensitivity of 0.81 on held-out test data sets. In addition to improving understanding of drivers of arsenic in the region, this model produces pseudo-3D estimates of groundwater arsenic. The model can also be used to assess the time-dependent exposure to arsenic as the depth of domestic wells changes over time.

Colorado↗

USGS2026

Transdisciplinary approach to private well research

More than 60 million people in the United States and Canada rely on private drinking water systems (mostly private wells), which fall outside of national regulations for water quality and management. This decentralized infrastructure creates unique challenges. First, fragmented policy oversight leads to inconsistent data availability. Second, population heterogeneity in well users requires accounting for the social determinants of health and behavioral differences. Additionally, the individualized nature of well management creates persistent gaps between knowledge generation and the protective action. A broad goal of private well research is to (1) understand, predict, and prevent potential health problems related to well water consumption and (2) enable individual and collective action to reduce exposures to contaminants in well water. Here, we propose a conceptual model to advance private well research through a transdisciplinary approach that links water sources to health and prioritizes engagement among researchers, communities, and decision makers. We also identify challenges and opportunities aimed at improving data systems, refining hazard and risk assessments, linking interdisciplinary research and practical knowledge, and sustaining long-term partnerships. While our geographic focus is on North America, the principles and strategies outlined are globally relevant to addressing health risks associated with unregulated private drinking water sources.

Environmental Science and Technology↗

USGS2026

Groundwater drought in the United States: Spatial and temporal variability

Many communities and ecosystems in the United States that are dependent on groundwater are potentially adversely affected by groundwater drought. We computed yearly groundwater-drought metrics and mean groundwater levels at well locations across the conterminous United States (CONUS), using data from wells and remotely sensed and modeled Gravity Recovery and Climate Experiment Drought Monitor Data Assimilation (GRACE-DADM). We also modeled the probability of low or high human impact at each well location. The spatial distribution of groundwater-drought duration and severity from 2001 to 2020 for 1,510 wells shows longer maximum duration and higher maximum severity events in drier regions like the Southwest than in wetter regions like the Northeast. Based on 613 wells in CONUS from 1981 to 2020, there are many significant decreases in drought duration and severity in the Northeast and many significant increases in annual-mean groundwater levels. In contrast, there are many significant increases in drought metrics and decreases in mean water levels in parts of the Southeast. There are major differences in trends from 2001 to 2020 between well-based and GRACE-DADM-based groundwater metrics in some CONUS regions and a very low correlation between trends at individual locations across CONUS. A potential reason for this disparity is the low GRACE-DADM resolution (∼12 km) and the potential for a large amount of groundwater variation at the local scale. Also, GRACE-DADM represents shallow, unconfined aquifers which may not match the screened interval of the monitoring wells we evaluated. Large spatial gaps in long-term, high frequency, and quality-assured groundwater-well monitoring data present a challenge for understanding groundwater-drought variability across CONUS. Remote sensing tools such as GRACE can help but cannot fully replace well monitoring, as highlighted by our study results. Substantially more long-term monitoring wells would more accurately represent groundwater-drought trends and spatial variability across CONUS, particularly in western regions.

conterminous United States↗

USGS2026

Drinking water arsenic, urinary arsenic biomarkers, and cognitive impairment in the REGARDS study

Background There are several pathways by which inorganic arsenic (iAs) exposure can affect cognition among adults. Few epidemiologic studies evaluate iAs in water and inter-individual differences in urinary arsenic toxicokinetics. We aimed to estimate the association between individual-level urinary arsenic biomarkers, county-level iAs in drinking water, and cognitive impairment in a cohort of Black and White Americans. Methods We evaluated the association between county-level iAs in water and urinary iAs metabolites with incident cognitive impairment in REasons for Geographic and Racial Differences in Stroke (REGARDS). Participants were linked to county-level concentrations of arsenic in public water (n = 15,516) and county-level probabilities of private well arsenic exceeding 10 μg/L (n = 20,448). In addition, urinary concentrations of iAs, monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA) were measured in a subset of participants (n = 1,013). Cognitive impairment was determined by the Six Item Screener (SIS) and the Enhanced Cognitive Battery (ECB). We used multivariable logistic regression to estimate odds ratios. Results Approximately 9 % of participants in REGARDS developed incident cognitive impairment on the SIS over 10 years of follow-up. County-level public water iAs concentrations and private well iAs probabilities were not associated with increased odds of cognitive impairment. Higher concentrations of MMA (OR: 1.74 [95 % CI: 1.22, 2.49]) and iAs (OR: 1.58 [95 % CI: 1.12, 2.22]) in urine were associated with greater odds of cognitive impairment on the SIS. Results for the ECB were similar. Conclusions iAs exposure may be associated with cognitive impairment. Our findings highlight the importance of considering multiple measures of iAs exposure.

Environmental Research↗

USGS2025

Water withdrawal and consumption trends for thermoelectric-power plants in the conterminous United States, 2008-2020

Freshwater-using utility-scale thermoelectric (TE) plant water-use estimates were evaluated for annual trends from 2008 to 2020 across the conterminous United States (CONUS) and within hydrologic regions. Overall, TE water withdrawal and consumption trends declined across CONUS by 14,335 and 278 million liters/day, respectively. Decreasing water withdrawal and consumption trends for TE plants are driven largely by switching from coal-fired plants to other generation technologies. TE plant cooling system technology has also changed, with large declining trends for TE plants using once-through cooling systems and small increasing consumption trends for TE plants using recirculating tower cooling systems. Fifteen hydrologic regions have decreasing trends in withdrawals and consumption. The largest decreases are for coal-fired plants using once-through freshwater cooling systems in the Great Lakes and Ohio hydrologic regions. Natural gas combined cycle plants with recirculating tower cooling systems have increased water consumption trends across most of the CONUS hydrologic regions. Some TE plants with recirculating tower or once-through cooling systems withdraw water volumes that on average are close to or exceed average simulated streamflows. Most of these situations occur in the central and eastern U.S., potentially leading to water availability issues among competing water needs, ecosystem impacts from thermal pollution, and power generation constraints.

conterminous United States↗

USGS2025

Land application of drill waste: A scope analysis

Drilling fluid waste land application, a process where drilling wastes are spread and tilled into the land surface, has become common in some petroleum-producing states, however, the potential benefits and risks of this practice are not well studied. Drilling fluids can be water- or oil-based and can have high concentrations of total soluble salts and total petroleum hydrocarbons. Comprehensive chemical characterization of these fluids is not well documented in the literature, and the extent of land application is largely unknown. We hypothesized that the land application of drill waste would fluctuate over time due to economic factors. To begin to understand the extent of historical and potential future land application, we analyzed data from over 5,800 drilling fluid land application permits collected by the Oklahoma Corporation Commission for years 2000, 2005, 2010, and 2015–2020. During the years studied, drilling fluid wastes were applied to more than 250,000 acres in Oklahoma, with over 54,000 thousand barrels (Mbbl) of liquids and nearly 21,000 Mbbl of solids applied. Land application is widespread (occurring in 59/77 counties), however recent drilling activity, land availability, and the economics of transportation have created conditions favorable for land application specifically in the Anadarko Basin. Land application can co-occur with sensitive areas, such as important groundwater and surface-water drinking sources and agricultural fields used for subsistence or feed crop production. Our approach for quantifying the extent of land application, along with further chemical characterization studies, can aid operators and land managers who are considering this practice in assessing the associated benefits and risks.

Oklahoma↗

USGS2025

Cancer risk and estimated lithium exposure in drinking groundwater in the US

Importance Lithium is a naturally occurring element in drinking water and is commonly used as a mood-stabilizing medication. Although clinical studies have reported associations between receiving lithium treatment and reduced cancer risk among patients with bipolar disorder, to our knowledge, the association between environmental lithium exposure and cancer risk has never been studied in the general population. Objectives To evaluate the association between exposure to lithium in drinking groundwater and cancer risk in the general population. Design, Setting, and Participants This cohort study included participants with electronic health record and residential address information but without cancer history at baseline from the All of Us Research Program between May 31, 2017, and June 30, 2022. Participants were followed up until February 15, 2023. Statistical analysis was performed from September 2023 through October 2024. Exposure Lithium concentration in groundwater, based on kriging interpolation of publicly available US Geological Survey data on lithium concentration for 4700 wells across the contiguous US between May 12, 1999, and November 6, 2018. Main Outcome and Measures The main outcome was cancer diagnosis or condition, obtained from electronic health records. Stratified Cox proportional hazards regression models were used to estimate the hazard ratios (HRs) and 95% CIs for risk of cancer overall and individual cancer types for increasing quintiles of the estimated lithium exposure in drinking groundwater, adjusting for socioeconomic, behavioral, and neighborhood-level variables. The analysis was further conducted in the western and eastern halves of the US and restricted to long-term residents living at their current address for at least 3 years. Results A total of 252 178 participants were included (median age, 52 years [IQR, 36-64 years]; 60.1% female). The median follow-up time was 3.6 years (IQR, 3.0-4.3 years), and 7573 incident cancer cases were identified. Higher estimated lithium exposure was consistently associated with reduced cancer risk. Compared with the first (lowest) quintile of lithium exposure, the HR for all cancers was 0.49 (95% CI, 0.31-0.78) for the fourth quintile and 0.29 (95% CI, 0.15-0.55) for the fifth quintile. These associations were found for all cancer types investigated in both females and males, among long-term residents, and in both western and eastern states. For example, for the fifth vs first quintile of lithium exposure for all cancers, the HR was 0.17 (95% CI, 0.07-0.42) in females and 0.13 (95% CI, 0.04-0.38) in males; for long-term residents, the HR was 0.32 (95% CI, 0.15-0.66) in females and 0.24 (95% CI, 0.11-0.52) in males; and the HR was 0.01 (95% CI, 0.00-0.09) in western states and 0.34 (95% CI, 0.21-0.57) in eastern states. Conclusions and Relevance In this cohort study of 252 178 participants, estimated lithium exposure in drinking groundwater was associated with reduced cancer risk. Given the sparse evidence and unknown mechanisms of this association, follow-up investigation is warranted.

contiguous United States↗

USGS2025

Automating physics-based models to estimate thermoelectric-power water use

Thermoelectric (TE) power plants withdraw more water than any other sector of water use in the United States and consume water at rates that can be significant especially in water-stressed regions. Historical TE water-use data have been inconsistent, incomplete, or discrepant, resulting in an increased research focus on improving the accuracy and availability of TE water-use data using modeling approaches. This paper describes and benchmarks new code that was developed to automate and update a physics-based TE water use model that was previously published. Utilizing the automated physics-based model, monthly TE-power water withdrawal and consumption were calculated for a total of 1341 TE power plants for the 2008–2020 historical reanalysis. The updated and automated physics-based thermoelectric-power water-use model provides spatially and temporally relevant TE water-use estimates that are consistent, reproducible, transparent, and can be generated efficiently for water-using, utility-scale TE-power plants across conterminous United States (CONUS).

Environmental Modelling and Software↗

USGS2024

Association of water arsenic with incident diabetes in U.S. adults: The Multi-Ethnic Study of Atherosclerosis and The Strong Heart Study

OBJECTIVE We examined the association of arsenic in federally regulated community water systems (CWSs) and unregulated private wells with type 2 diabetes (T2D) incidence in the Strong Heart Family Study (SHFS), a prospective study of American Indian communities, and the Multi-Ethnic Study of Atherosclerosis (MESA), a prospective study of racially and ethnically diverse urban U.S. communities. RESEARCH DESIGN AND METHODS We evaluated 1,791 participants from SHFS and 5,777 participants from MESA who had water arsenic estimates available and were free of T2D at baseline (2001–2003 and 2000–2002, respectively). Participants were followed for incident T2D until 2010 (SHFS cohort) or 2019 (MESA cohort). We used Cox proportional hazards mixed-effects models to account for clustering by family and residential zip code, with adjustment for sex, baseline age, BMI, smoking status, and education. RESULTS T2D incidence was 24.4 cases per 1,000 person-years (mean follow-up, 5.6 years) in SHFS and 11.2 per 1,000 person-years (mean follow-up, 14.0 years) in MESA. In a meta-analysis across the SHFS and MESA cohorts, the hazard ratio (95% CI) per doubling in CWS arsenic was 1.10 (1.02, 1.18). The corresponding hazard ratio was 1.09 (0.95, 1.26) in the SHFS group and 1.10 (1.01, 1.20) in the MESA group. The corresponding hazard ratio (95% CI) for arsenic in private wells and incident T2D in SHFS was 1.05 (0.95, 1.16). We observed statistical interaction and larger magnitude hazard ratios for participants with BMI <25 kg/m 2 and female participants. CONCLUSIONS Low to moderate water arsenic levels (<10 µg/L) were associated with T2D incidence in the SHFS and MESA cohorts.

Diabetes Care↗

USGS2024

Estimating lithium concentrations in groundwater used as drinking water for the conterminous United States

Lithium (Li) concentrations in drinking-water supplies are not regulated in the United States; however, Li is included in the 2022 U.S. Environmental Protection Agency list of unregulated contaminants for monitoring by public water systems. Li is used pharmaceutically to treat bipolar disorder, and studies have linked its occurrence in drinking water to human-health outcomes. An extreme gradient boosting model was developed to estimate geogenic Li in drinking-water supply wells throughout the conterminous United States. The model was trained using Li measurements from ∼13,500 wells and predictor variables related to its natural occurrence in groundwater. The model predicts the probability of Li in four concentration classifications, ≤4 μg/L, >4 to ≤10 μg/L, >10 to ≤30 μg/L, and >30 μg/L. Model predictions were evaluated using wells held out from model training and with new data and have an accuracy of 47–65%. Important predictor variables include average annual precipitation, well depth, and soil geochemistry. Model predictions were mapped at a spatial resolution of 1 km 2 and represent well depths associated with public- and private-supply wells. This model was developed by hydrologists and public-health researchers to estimate Li exposure from drinking water and compare to national-scale human-health data for a better understanding of dose–response to low (<30 μg/L) concentrations of Li.

conterminous United States↗

USGS2023

Contribution of arsenic and uranium in private wells and community water systems to urinary biomarkers in US adults: The Strong Heart Study and the Multi-Ethnic Study of Atherosclerosis

Background Chronic exposure to inorganic arsenic (As) and uranium (U) in the United States (US) occurs from unregulated private wells and federally regulated community water systems (CWSs). The contribution of water to total exposure is assumed to be low when water As and U concentrations are low. Objective We examined the contribution of water As and U to urinary biomarkers in the Strong Heart Family Study (SHFS), a prospective study of American Indian communities, and the Multi-Ethnic Study of Atherosclerosis (MESA), a prospective study of racially/ethnically diverse urban U.S. communities. Methods We assigned residential zip code-level estimates in CWSs (µg/L) and private wells (90th percentile probability of As >10 µg/L) to up to 1485 and 6722 participants with dietary information and urinary biomarkers in the SHFS (2001–2003) and MESA (2000–2002; 2010–2011), respectively. Urine As was estimated as the sum of inorganic and methylated species, and urine U was total uranium. We used linear mixed-effects models to account for participant clustering and removed the effect of dietary sources via regression adjustment. Results The median (interquartile range) urine As was 5.32 (3.29, 8.53) and 6.32 (3.34, 12.48) µg/L for SHFS and MESA, respectively, and urine U was 0.037 (0.014, 0.071) and 0.007 (0.003, 0.018) µg/L. In a meta-analysis across both studies, urine As was 11% (95% CI: 3, 20%) higher and urine U was 35% (5, 73%) higher per twofold higher CWS As and U, respectively. In the SHFS, zip-code level factors such as private well and CWS As contributed 46% of variation in urine As, while in MESA, zip-code level factors, e.g., CWS As and U, contribute 30 and 49% of variation in urine As and U, respectively. Impact statement We found that water from unregulated private wells and regulated CWSs is a major contributor to urinary As and U (an estimated measure of internal dose) in both rural, American Indian populations and urban, racially/ethnically diverse populations nationwide, even at levels below the current regulatory standard. Our findings indicate that additional drinking water interventions, regulations, and policies can have a major impact on reducing total exposures to As and U, which are linked to adverse health effects even at low levels.

Journal of Exposure Science and Environmental Epid↗

USGS2023

Cross-sectional associations between drinking water arsenic and urinary inorganic arsenic in the US: NHANES 2003-2014

Background: Inorganic arsenic is a potent carcinogen and toxicant associated with numerous adverse health outcomes. The contribution of drinking water from private wells and regulated community water systems (CWSs) to total inorganic arsenic exposure is not clear. Objectives: To determine the association between drinking water arsenic estimates and urinary arsenic concentrations in the 2003-2014 National Health and Nutrition Examination Survey (NHANES). Methods: We evaluated 11,088 participants from the 2003-2014 NHANES cycles. For each participant, we assigned private well and CWS arsenic levels according to county of residence using estimates previously derived by the US Environmental Protection Agency and US Geological Survey. We used recalibrated urinary dimethylarsinate (rDMA) to reflect the internal dose of estimated water arsenic by applying a previously validated, residual-based method that removes the contribution of dietary arsenic sources. We compared the adjusted geometric mean ratios and corresponding percent change of urinary rDMA across tertiles of private well and CWS arsenic levels, with the lowest tertile as the reference. Comparisons were made overall and stratified by census region and race/ethnicity. Results: Overall, the geometric mean of urinary rDMA was 2.52 (2.30, 2.77) µg/L among private well users and 2.64 (2.57, 2.72) µg/L among CWS users. Urinary rDMA was highest among participants in the West and South, and among Mexican American, Other Hispanic, and Non-Hispanic Other participants. Urinary rDMA levels were 25% (95% CI: 17-34%) and 20% (95% CI: 12-29%) higher comparing the highest to the lowest tertile of CWS and private well arsenic, respectively. The strongest associations between water arsenic and urinary rDMA were observed among participants in the South, West, and among Mexican American and Non-Hispanic White and Black participants. Discussion: Both private wells and regulated CWSs are associated with inorganic arsenic internal dose as reflected in urine in the general US population.

Environmental Research↗

USGS2022

A hydrologic perspective of major U.S. droughts

Drought is a recurring natural hazard that has substantial human and environmental impacts. Given continued global warming and associated climate change, there is concern that droughts could become more severe and longer lasting. To better monitor and understand drought development and persistence, it is helpful to understand the development and climatic drivers of past droughts. In this study we use monthly runoff percentiles to identify five major drought events in the conterminous United States (CONUS) from 1901 through 2020. For each drought event we examined spatial patterns of departures of mean monthly precipitation, temperature, soil moisture storage, and runoff for 2,107 hydrologic units (HUs) across the CONUS. Results indicated that precipitation deficits have been the primary driver of past major-drought events and temperature a secondary driver, even of the most recent drought event (September 1999 through September 2015) when positive temperature anomalies occurred over most of the CONUS. Additionally, negative soil moisture storage departures were more negative than runoff departures during the five drought events we examined, which emphasizes the importance of measuring both runoff and soil moisture to monitor drought conditions. We also examined the use of statistical persistence to develop short-term (i.e., 1 month) forecasts of runoff drought conditions in the CONUS by developing autoregressive integrated moving average (ARIMA) models for each HU. Results indicated that persistence can be used to predict short-term changes in the spatial pattern of drought and the areal extent of drought, but that predictions of runoff magnitude for any particular site are often poor.

International Journal of Climatology↗

USGS2022

Going beyond low flows: Streamflow drought deficit and duration illuminate distinct spatiotemporal drought patterns and trends in the U.S. during the last century

Streamflow drought is a recurring challenge, and understanding spatiotemporal patterns of past droughts is needed to manage future water resources. We examined regional patterns in streamflow drought metrics and compared these metrics to low flow timing and magnitude using long-term daily records for 555 minimally disturbed watersheds. For each streamgage, we calculated streamflow drought duration (number of days) and deficit (flow volume below a specified threshold) for each climate year (April 1–March 31). We identified drought using five thresholds (2%–30%) and two approaches: variable thresholds with unique values for each day of the year, and a fixed threshold based on all period-of-record flows. We then analyzed drought trends using the Mann-Kendall test with persistence adjustment for 1921–2020, 1951–2020, and 1981–2020, and computed correlations between annual streamflow drought metrics and climate metrics using values from a monthly water balance model. Spatial patterns in drought metrics were consistent between variable and fixed approaches, though fixed threshold durations were typically longer and variable threshold deficits larger. High interannual variability in drought duration emerged in the central, interior west, and southwestern U.S., with high deficit variability in the interior west. Drought metrics were weakly correlated with low flow magnitude and timing, providing unique information. Drought duration and deficit increased in the southern and western U.S. for both 1951–2020 and 1981–2020, particularly using fixed thresholds, and paralleled trends in aridity. Projections of continued aridification for the southern and western U.S. may increase drought durations and deficits and intensify water availability impacts.

Water Resources Research↗

USGS2022

Perfluoroalkyl and polyfluoroalkyl substances in groundwater used as a source of drinking water in the eastern United States

In 2019, 254 samples were collected from five aquifer systems to evaluate per- and polyfluoroalkyl substance (PFAS) occurrence in groundwater used as a source of drinking water in the eastern United States. The samples were analyzed for 24 PFAS, major ions, nutrients, trace elements, dissolved organic carbon (DOC), volatile organic compounds (VOCs), pharmaceuticals, and tritium. Fourteen of the 24 PFAS were detected in groundwater, with 60% and 20% of public-supply and domestic wells, respectively, containing at least one PFAS detection. Concentrations of tritium, chloride, sulfate, DOC, and manganese+iron; percent urban land use within 500 m of the wells; and VOC and pharmaceutical detection frequencies were significantly higher in samples containing PFAS detections than in samples with no detections. Boosted Regression Tree models that consider 57 chemical and land-use variables show that tritium concentration, distance to the nearest fire-training area, percentage of urban land use, and DOC and VOC concentrations are the top five predictors of PFAS detections, consistent with hydrologic position, geochemistry, and land use being important controls on PFAS occurrence in groundwater. Model results indicate it may be possible to predict PFAS detections in groundwater using existing data sources.

Glacial aquifer, Mississippi Embayment aquifer, So↗

USGS2022

Arsenic in private well water and birth outcomes in the United States

Background Prenatal exposure to drinking water with arsenic concentrations >50 μg/L is associated with adverse birth outcomes, with inconclusive evidence for concentrations ≤50 μg/L. In a collaborative effort by public health experts, hydrologists, and geologists, we used published machine learning model estimates to characterize arsenic concentrations in private wells—federally unregulated for drinking water contaminants—and evaluated associations with birth outcomes throughout the conterminous U.S. Methods Using several machine learning models, including boosted regression trees (BRT) and random forest classification (RFC), developed from measured groundwater arsenic concentrations of ∼20,000 private wells, we characterized the probability that arsenic concentrations occurred within specific ranges in groundwater. Probabilistic model estimates and private well usage data were linked by county to all live birth certificates from 2016 (n = 3.6 million). We evaluated associations with gestational age and term birth weight using mixed-effects models, adjusted for potential confounders and incorporated random intercepts for spatial clustering. Results We generally observed inverse associations with term birth weight. For instance, when using BRT estimates, a 10-percentage point increase in the probability that private well arsenic concentrations exceeded 5 μg/L was associated with a −1.83 g (95% CI: −3.30, −0.38) lower term birth weight after adjusting for covariates. Similarly, a 10-percentage point increase in the probability that private well arsenic concentrations exceeded 10 μg/L was associated with a −2.79 g (95% CI: −4.99, −0.58) lower term birth weight. Associations with gestational age were null. Conclusion In this largest epidemiologic study of arsenic and birth outcomes to date, we did not observe associations of modeled arsenic estimates in private wells with gestational age and found modest inverse associations with term birth weight. Study limitations may have obscured true associations, including measurement error stemming from a lack of individual-level information on primary water sources, water arsenic concentrations, and water consumption patterns.

Environment International↗

USGS2021

Machine learning models of arsenic in private wells throughout the conterminous United States as a tool for exposure assessment in human health studies

Arsenic from geologic sources is widespread in groundwater within the United States (U.S.). In several areas, groundwater arsenic concentrations exceed the U.S. Environmental Protection Agency maximum contaminant level of 10 μg per liter (μg/L). However, this standard applies only to public-supply drinking water and not to private-supply, which is not federally regulated and is rarely monitored. As a result, arsenic exposure from private wells is a potentially substantial, but largely hidden, public health concern. Machine learning models using boosted regression trees (BRT) and random forest classification (RFC) techniques were developed to estimate probabilities and concentration ranges of arsenic in private wells throughout the conterminous U.S. Three BRT models were fit separately to estimate the probability of private well arsenic concentrations exceeding 1, 5, or 10 μg/L whereas the RFC model estimates the most probable category (≤5, >5 to ≤10, or >10 μg/L). Overall, the models perform best at identifying areas with low concentrations of arsenic in private wells. The BRT 10 μg/L model estimates for testing data have an overall accuracy of 91.2%, sensitivity of 33.9%, and specificity of 98.2%. Influential variables identified across all models included average annual precipitation and soil geochemistry. Models were developed in collaboration with public health experts to support U.S.-based studies focused on health effects from arsenic exposure.

Environmental Science and Technology↗

USGS2021

Assessing the impact of drought on arsenic exposure from private domestic wells in the conterminous United States

This study assesses the potential impact of drought on arsenic exposure from private domestic wells by using a previously developed statistical model that predicts the probability of elevated arsenic concentrations (>10 μg per liter) in water from domestic wells located in the conterminous United States (CONUS). The application of the model to simulate drought conditions used systematically reduced precipitation and recharge values. The drought conditions resulted in higher probabilities of elevated arsenic throughout most of the CONUS. While the increase in the probability of elevated arsenic was generally less than 10% at any one location, when considered over the entire CONUS, the increase has considerable public health implications. The population exposed to elevated arsenic from domestic wells was estimated to increase from approximately 2.7 million to 4.1 million people during drought. The model was also run using total annual precipitation and groundwater recharge values from the year 2012 when drought existed over a large extent of the CONUS. This simulation provided a method for comparing the duration of drought to changes in the predicted probability of high arsenic in domestic wells. These results suggest that the probability of exposure to arsenic concentrations greater than 10 μg per liter increases with increasing duration of drought. These findings indicate that drought has a potentially adverse impact on the arsenic hazard from domestic wells throughout the CONUS.

Conterminous United States↗