How or When Samples Are Collected Affects Measured Arsenic Concentration in New Drinking Water Wells

Erickson, Melinda L.; Malenda, Helen F.; Berquist, Emily

doi:10.1111/gwat.12643

Cited by 12 publications

(5 citation statements)

References 36 publications

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“…The total modeled area is about 50,000 km 2 . The two study regions each have complex glacial geology overlying bedrock (Figure and previously described in Erickson et al, ). The unconsolidated sediments in the regions are composed of deposits from multiple glacial advances and retreats, the last occurring during the late Pleistocene period, 16,000–12,000 years ago (Lusardi, ).…”

Section: Hydrogeologic Settingmentioning

confidence: 99%

Predicting geogenic Arsenic in Drinking Water Wells in Glacial Aquifers, North‐Central USA: Accounting for Depth‐Dependent Features

Erickson

Elliott

Christenson

et al. 2018

Water Resources Research

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Chronic exposure to arsenic (As) via drinking groundwater is a human health concern worldwide. Probabilities of elevated geogenic As concentrations in groundwater were predicted in complex, glacial aquifers in Minnesota, north-central USA, a region that commonly has elevated As concentrations in well water. Maps of elevated As hazard were created for depths typical of drinking water supply and with well construction attributes common for domestic wells. Conventional variables describing aquifer properties and materials, position on the hydrologic landscape, and soil geochemistry were among the most influential for predicting the probability of elevated As. We also found that certain well construction attributes were influential in predicting As hazard. Smaller distances between the top of the well screen and overlying aquitard (proximity) and shorter well screen lengths were each associated with higher probabilities of elevated As. Influential predictor variables, which are either mapped across the region or are well construction attributes, are proxies in the model for measurable physical or geochemical causes of elevated As (e.g., redox condition, till or aquifer sediment chemistry, and water chemistry), which are not mapped across the region. Our setting shares some important characteristics with deltaic and other high-As aquifers in Southeast Asia: late Quaternary age, complex layering of coarse-and fine-grained materials, low-As sediment concentrations, and geochemical controls on As mobilization. Translating three-dimensional geologic and geochemical understanding of As mobility to quantifiable variables for modeling with powerful, flexible statistical tools could improve predictions and help identify safer groundwater supply options in the USA, Southeast Asia, and elsewhere.Plain Language Summary This study demonstrates that certain well construction attributes are influential in predicting arsenic (As) concentrations in drinking water wells. Smaller distances between the top of the well screen and overlying aquitard, and shorter well screen lengths, were each associated with higher probabilities of elevated As. Chronic exposure to As via drinking groundwater is a human health concern worldwide, and Minnesota, USA, commonly has elevated As concentrations in well water. This study describes a new, novel, and important finding from an As probability model: Controllable well construction choices (not just location or depth) influence As concentrations in drinking water from wells.

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Section: Hydrogeologic Settingmentioning

confidence: 99%

Predicting geogenic Arsenic in Drinking Water Wells in Glacial Aquifers, North‐Central USA: Accounting for Depth‐Dependent Features

Erickson

Elliott

Christenson

et al. 2018

Water Resources Research

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“…The concentration of SO 4 2− in groundwater was considered less prone to sorption, precipitation and geochemical reduction (Kim et al, 2017). Erickson et al (2018) observed that the concentration of As in groundwater from new wells was highly variable relative to that found when sampled months later. Although the concentrations of PTEs were lower than the drinking water quality guidelines (WHO, 2017), some (e.g.…”

Section: Discussionmentioning

confidence: 87%

Trace elements in groundwater near an abandoned mine tailings dam and health risk assessment (NE Zimbabwe)

Kanda

Makumbe

2021

WSA

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Groundwater from shallow hand-dug wells at an abandoned gold mine tailings dam was characterised for selected physicochemical parameters during dry and wet seasons of 2018 and 2019. Health risk exposure of the local population (adults and children) through ingestion and dermal exposure was assessed. Groundwater quality parameters were lower than international drinking water quality guidelines (p < 0.05). The parameters were significantly influenced by season of the year (As, Cl−, SO42−), nature (As, Cd, Cl−, Fe, NO3−, SO42−), depth (Cd, Cl−, Fe, Ni, SO42−) and direction of the well (Cu, Cl−, Fe, NO3−, Pb, SO42−) (p < 0.05) relative to the tailings dam. Groundwater did not pose non-carcinogenic risk due to studied trace elements. However, arsenic had the potential to cause medium to high cancer risk to the local population. We propose re-vegetation of the tailings dam, diversion of surface tailings drainage to a containment pond and the provision of continuous piped water supplies.

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“…In particular, field filtration of samples was reported to influence the measured concentration of several trace elements in water [75]. Filtered samples generally cause less variability of groundwater As concentration in a well compared to unfiltered samples [76].…”

Section: Data Quality Assessment and Preparation Of The Working Datasetmentioning

confidence: 99%

Deriving Natural Background Levels of Arsenic at the Meso-Scale Using Site-Specific Datasets: An Unorthodox Method

Filippini

Zanotti

Bonomi

et al. 2021

Water

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Arsenic is found in groundwater above regulatory limits in many countries and its origin is often from natural sources, making the definition of Natural Background Levels (NBLs) crucial. NBL is commonly assessed based on either dedicated small-scale monitoring campaigns or large-scale national/regional groundwater monitoring networks that may not grab local-scale heterogeneities. An alternative method is represented by site-specific monitoring networks in contaminated/polluted sites under remediation. As a main drawback, groundwater quality at these sites is affected by human activities. This paper explores the potential for groundwater data from an assemblage of site-specific datasets of contaminated/polluted sites to define NBLs of arsenic (As) at the meso-scale (order of 1000 km2). Common procedures for the assessment of human influence cannot be applied to this type of dataset due to limited data homogeneity. Thus, an “unorthodox” method is applied involving the definition of a consistent working dataset followed by a statistical identification and critical analysis of the outliers. The study was conducted in a highly anthropized area (Ferrara, N Italy), where As concentrations often exceed national threshold limits in a shallow aquifer. The results show that site-specific datasets, if properly pre-treated, are an effective alternative for the derivation of NBLs when regional monitoring networks fail to catch local-scale variability.

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How or When Samples Are Collected Affects Measured Arsenic Concentration in New Drinking Water Wells

Cited by 12 publications

References 36 publications

Predicting geogenic Arsenic in Drinking Water Wells in Glacial Aquifers, North‐Central USA: Accounting for Depth‐Dependent Features

Predicting geogenic Arsenic in Drinking Water Wells in Glacial Aquifers, North‐Central USA: Accounting for Depth‐Dependent Features

Trace elements in groundwater near an abandoned mine tailings dam and health risk assessment (NE Zimbabwe)

Deriving Natural Background Levels of Arsenic at the Meso-Scale Using Site-Specific Datasets: An Unorthodox Method

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