Arsenic Concentrations In Groundwater Research Articles

Geo-spatial epidemiology of gallbladder cancer in Bihar, India

Recently, a substantial increase in gallbladder cancer (GBC) cases has been reported in Bihar, India. The region's groundwater can naturally contain harmful concentrations of arsenic, which appears to be epidemiologically linked to the unusually high incidence. However, the root causes remain largely unexplored. Recent findings of uranium in the state's groundwater may also have associations. This study investigates the geo-spatial epidemiology of GBC in Bihar, India—with a focus on the correlation between environmental carcinogens, particularly arsenic and uranium in groundwater, and the incidence of GBC. Utilizing data from 8460 GBC patients' registration records over an 11-year period at a single health center, the research employs Semi-parametric Geographically Weighted Poisson Regression (S-GWPR) to account for non-stationarity associations and explores significant factors contributing to GBC prevalence at a subdistrict level. The S-GWPR model outperformed the standard Poisson regression model. The estimates suggest that arsenic and uranium concentrations in groundwater did not present significant associations; however, this could be due to the lower resolution of this data at the district level, necessitating higher resolution data for accurate estimates. Other socio-environmental factors included demonstrated significant regional heterogeneity in their association with GBC prevalence. Notably, each 1 % increase in the coverage of well- and canal-irrigated areas is associated with a maximum of 3.0 % and 5.2 % rise in the GBC incidence rate, respectively, likely attributable to carcinogen exposure from irrigation water. Moreover, distance to the health center and domestic electricity connections appear to influence the number of reported GBC cases. The latter suggests that access to electricity might have facilitated the use of groundwater pumps—increasing exposure to carcinogens. The results underscore the necessity for targeted health policies and interventions based on fine-resolution spatial analysis, as well as ongoing environmental monitoring and research to better understand the multifaceted risk factors contributing to GBC.

Machine learning prediction of health risk and spatial dependence of geogenic contaminated groundwater from the Hetao Basin, China

Geogenic contaminated groundwater (GCG), characterized by elevated arsenic, fluoride, and iodine levels, present a significant challenge to public health and government management. Conventional survey-based approaches of collecting groundwater samples, conducting physicochemical tests, and performing spatial interpolation to obtain regional groundwater chemical component maps are inefficient and costly. More importantly, it does not take into account the actual hydrogeological conditions or the characteristics of pollutant transport and enrichment. To address this issue, we utilized Support Vector Machine (SVM), Random Forest (RF), Adaptive Boosting (AdaBoost), and Extreme Gradient Boosting (XGBoost) to analyze the likelihood of occurrence of arsenic, fluoride, and iodine as well as their spatial distribution in shallow groundwater from the Hetao Basin. Our study incorporated 20 indicators related to meteorology, soil physicochemical properties, and groundwater conditions, along with 1505 labeled samples consisting of groundwater arsenic, fluoride, and iodine concentrations and their corresponding coordinates. Subsequently, the study automatically analyzed the meteorological, soil physicochemical properties and groundwater conditions by constructing a machine learning model using the available data. In order to optimise and select the best prediction model, this paper presents a quantitative evaluation of the prediction performance of various machine learning models. The accuracy (AC), area under curve (AUC) and mean squared error (MSE) were calculated to predict the spatial distribution of CGC. Subsequently, the optimized model for predicting the spatial distribution of GCG was selected. The results showed that the XGBoost algorithm provided optimal predictions for groundwater with arsenic concentrations above 10 μg/L and fluoride concentrations exceeding 1.5 mg/L, whereas the RF model provided the best predictions for groundwater with arsenic concentrations surpassing 50 μg/L and iodine concentrations exceeding 100 μg/L. Subsequently, groundwater health risk zones were delineated based on an optimal prediction model, and demographic analysis was conducted in both the direct and potential groundwater risk zones. Model predictions indicated that hundreds of thousands of people in the Hetao Basin were facing a public health crisis caused by high concentrations of arsenic, fluoride and iodine in groundwater. These findings underscore the significant health challenge in the study area. Considering the agricultural development and increasing groundwater use in the area, our findings can guide local governments in managing the extent of groundwater development, establishing control zones, and enhancing protection measures for populations at risk from groundwater contamination.

Land-use interactions, Oil-Field infrastructure, and natural processes control hydrocarbon and arsenic concentrations in groundwater, Poso Creek Oil Field, California, USA

Like many hydrocarbon production areas in the U.S., the Poso Creek Oil Field in California includes and is adjacent to other land uses (agricultural and other developed lands) that affect the hydrology and geochemistry of the aquifer overlying and adjacent to oil development. We hypothesize that the distributions of hydrocarbons and arsenic in groundwater in such areas will be controlled by complex interactions between mixed land uses, oil-field infrastructure, and natural processes. In 2020–2021, samples of groundwater and surface water were collected and analyzed for a large suite of inorganic and organic chemicals and isotope and gas tracers to test this hypothesis. Those data are supplemented with ancillary data on historical geochemistry, hydrology, geology, and oil-field infrastructure. Hydrocarbons in groundwater (e.g., methane through pentane gases and benzene) are associated with natural processes (e.g., fault offsets or transition in sediment depositional environment) and oil-field infrastructure (e.g., fluid-migration pathways associated with uncemented annulus in oil wells or unlined pits). Arsenic concentrations >10 μg per liter (μg/L; maximum concentration 12.9 μg/L) are associated with natural processes in old, high-pH groundwater, and more recent recharge of water from natural and/or engineered recharge processes. Along the southwest margin of the oil field, pumping for drinking-water and irrigation supplies in combination with engineered groundwater recharge produce a depression in groundwater elevations where groundwater with elevated sulfate concentrations from agricultural areas and groundwater with hydrocarbons from the oil field mix to produce a zone of sulfate reduction that removes hydrocarbons and arsenic from groundwater but produces elevated sulfide (S2-) concentrations (maximum concentration 29 mg per liter, mg/L). In this study, multiple approaches were required to resolve the overlapping effects of land uses, oil-field infrastructure, and natural processes on the distributions of hydrocarbons and arsenic in groundwater. The combined use of geographic, historical, physical, chemical, isotopic, and other information to constrain processes could be a useful approach for studies in other hydrocarbon-production areas. This is particularly important where land uses affect aquifer hydrology to an extent that causes mixing of groundwaters with different chemical compositions.

Deciphering the spatial heterogeneity of groundwater arsenic in Quaternary aquifers of the Central Yangtze River Basin

Significant spatial variability of groundwater arsenic (As) concentrations in South/Southeast Asia is closely associated with sedimentogenesis and biogeochemical cycling processes. However, the role of fine-scale differences in biogeochemical processes under similar sedimentological environments in controlling the spatial heterogeneity of groundwater As concentrations is poorly understood. Within the central Yangtze Basin, dissolved organic matter (DOM) and microbial functional communities in the groundwater and solid-phase As-Fe speciation in Jianghan Plain (JHP) and Jiangbei Plain (JBP) were compared to reveal mechanisms related to the spatial heterogeneity of groundwater As concentration. The optical signatures of DOM showed that low molecular terrestrial fulvic-like with highly humified was predominant in the groundwater of JHP, while terrestrial humic-like and microbial humic-like with high molecular weight were predominant in the groundwater of JBP. The inorganic carbon isotope, microbial functional communities, and solid-phase As-Fe speciation suggest that the primary process controlling As accumulation in JHP groundwater system is the degradation of highly humified OM by methanogens, which drive the reductive dissolution of amorphous iron oxides. While in JBP groundwater systems, anaerobic methane-oxidizing microorganisms (AOM) coupled with fermentative bacteria, iron reduction bacteria (IRB), and sulfate reduction bacteria (SRB) utilize low molecular weight DOM degradation to drive biotic/abiotic reduction of Fe oxides, further facilitating the formation of carbonate associated Fe and crystalline Fe oxides, resulting in As release into groundwater. Different biogeochemical cycling processes determine the evolution of As-enriched aquifer systems, and the coupling of multiple processes involving organic matter transformation‑iron cycling‑sulfur cycling-methane cycling leads to heterogeneity in the spatial distribution of As concentrations in groundwater. These findings provide new perspectives to decipher the spatial variability of As concentrations in groundwater.

Functionalized activated carbon with whey protein amyloid fibrils for adsorption of arsenic from water

Globally, more than 200 million people are exposed to elevated concentrations of arsenic in groundwater, thus representing an important environmental and public health problem. Apart from inorganic species, water quality suffers also from the occurrence of organic pollutants discharged by the food sector like whey, a by-product of the dairy industry. The valorisation of these organic residues is relevant to reduce water pollution and to develop new materials for different applications. This research reports the synthesis and evaluation of a novel adsorptive activated carbon composite modified with whey protein amyloids for arsenic removal from water. The adsorbent was characterized with FT-IR spectroscopy, X-ray diffraction, N2 physisorption, pH at point of zero charge determination, and thermogravimetric analysis. Experimental adsorption kinetics and isotherms of arsenic removal were determined at optimal pH 5.0, best fitted with the PSO and Sips model, respectively. The corresponding maximum adsorption capacity for As5+ was 0.16 mmol g−1 through an endothermic process. Surface complexation was the predominant phenomenon in the adsorption mechanism as the As-O bond was formed via whey’s functional groups, hydroxyl, amine, and amide, with the latter having the strong affinity to arsenate as elucidated by the HSAB theory. This study highlights the potential of whey protein as a raw material to produce added-value products and its performance as a precursor of novel adsorbents for water purification, therefore minimizing their associated disposal cost and addressing relevant environmental concerns such as arsenic contamination.

Chemical Characteristics of Shallow Groundwater in the Yellow River Diversion Area of Henan Province and Identification of Main Control Pollution Sources

The northern plain of Henan in the lower reaches of the Yellow River is an area where the Yellow River is frequently diverted. The shallow groundwater quality in this area is poor， and many types of components have been found to be exceeding the limit value； however， the contribution of various environmental factors to water quality needs to be further quantified. In order to clarify the genesis of water quality of shallow groundwater in the study area， 330 groups of shallow groundwater samples were collected via a regional water quality survey. The evolution of shallow groundwater quality in the Yellow River diversion area of northern Henan was revealed using the principal component-absolute principal component score-multiple linear regression （PCA-APCS-MLR） model. The results showed that the components with a shallow groundwater excess rate greater than 10% in descending order were manganese， iron， total hardness， total dissolved solids， sodium， fluoride， arsenic， chloride ions， sulfate， and ammonium. In particular， the excess rate of manganese reached 76%. The four factors of dissolution enrichment， native origin of soil， redox conditions， and agricultural activities were identified as the main reasons for poor groundwater quality， which accounted for 71.24% of the cumulative interpretation rate of variance. In addition， the recharge from the surface water also influenced the groundwater quality. The effects of dissolution between the water and aquifer matrix and redox condition in the aquifer of the Yellow River dried-riverway like Xinxiang were significantly enhanced， resulting in the increasing concentration of iron， arsenic， total hardness， TDS， and other components in groundwater. Fluoride enrichment was caused by dissolution enrichment， the origin of the soil， and lateral replenishment of the Yellow River. Groundwater with high manganese concentration was widely affected by the soil matrix. Nitrate pollution of the groundwater was caused by the extensive use of chemical fertilizers in agricultural activities in individual areas.

GIS based Groundwater Vulnerability Assessment of Lahore a Metropolitan using Modified DRASTIC Model

The metropolitans of the developing countries are experiencing the hazard of low quality drinking water. Lahore, the heart of Pakistan, has over 12 million population and is going to face the shortage of clean drinking water. The study was designed to create a groundwater vulnerability map of Lahore using modified DRASTIC model. The water table, land use/cover, hydraulic conductivity, vadose zone, soil and aquifer media layers of Lahore aquifer were analyzed using ‘geostatistical analyst’ and ‘spatial analyst’ extensions of ArcGIS software to compute the groundwater vulnerability. The Vulnerability index of modified DRASTIC model ranged from 64 – 144. The spatial variability of modified DRASTIC index were divided into 4 categories, namely, Low, Moderate, High and Very High groundwater vulnerable zones. The modified DRASTIC model revealed that 51.38% areas have low vulnerability, 36.77% areas have moderate vulnerability, 9.48% areas have high vulnerability and 2.37% areas have very high vulnerability to groundwater pollution. The ‘high’ and ‘very high’ vulnerability classes were found in the western parts of Lahore. The results of modified DRASTIC model were validated using the groundwater contamination data of arsenic in the study area. The groundwater arsenic concentrations map also showed higher values in the northwestern parts while in the eastern parts of the study area, the arsenic concentrations had a decreasing trend. In Ravi Town, the arsenic concentrations were positively correlated with modified DRASTIC vulnerability index and inversely correlated with water table depth (p < 0.01). It is recommended that the arsenic removal plants should be installed at all the tubewells with higher arsenic levels (arsenic concentration > 50 ppb) to provide safe drinking water to the citizens of Lahore. It is recommended that the modified DRASTIC model based on geospatial techniques can be applied on other metropolitans of the world for taking preventive measures against massive water pollution.

A case study on regional arsenic sources and its distribution in Mekong River groundwater

Arsenic contamination in the Mekong River is a well-known environmental issue yet to be resolved due to its transboundary nature which further limits its access and data collection. Other than that, the key mechanisms that controlling the arsenic release in Mekong sub-region groundwater was heterogeneously distributed and can be varied from region to region. The main purpose of this project is to identify the regional arsenic contamination levels in the hope of helping the government integrate regional groundwater arsenic risk reduction policy in their near future planning. Sampling was conducted during May and August 2022 in Cambodia and Laos, respectively. The findings revealed that the topography of certain areas in Cambodia has exposed significantly high concentrations of arsenic in groundwater compared to those in Laos. About 33% of the sampling sites in Cambodia had shown a high arsenic contamination (> 10 µg/L, WHO guideline) with its concentration ranging from 47.7 ± 0.8 to 696.9 ± 5.6 ppb. The physicochemical properties revealed that the arsenic controlling mechanisms were totally different between both study area. More regional and site-specific arsenic contamination research related to climate change and arsenic hydrology at regional levels should be carried out to ensure the water safety plan in specific regions. Further, we believe that the findings of this study will be beneficial to policy and regional water safety plans for the Mekong River, especially in Cambodia.

Groundwater contamination & health risk assessment with special reference to As in different tehsils of Bhakkar district

The present study was conducted to evaluate the concentration of arsenic in groundwater in Bhakkar district, Western Punjab Province, Pakistan. To analyze hydrochemical characteristics, 68 groundwater samples from various water schemes in four tehsils were taken. While most of the samples' concentrations of major cations and anions were within the WHO's maximum allowed range, almost 44% had higher arsenic levels than what was considered acceptable for drinking water. Gibbs diagrams were used to show how groundwater chemistry is affected by the dominance of rocks and evaporation crystallization. An investigation of the Indus River's lateral distribution and upstream to downstream locations' arsenic concentrations showed variability. According to the Health Risk Assessment (HRA), samples from Bhakkar tehsil (73.3%), Darya Khan tehsil (60%), and Kalur Kot tehsil (13.3%) all surpassed the hazard quotient level of “1,” whereas all samples from Mankera tehsil were within acceptable bounds. The hazard quotient numbers displayed a range of 0.038–5.127, with an average of 1.149 – suggesting that a considerable portion of people consuming water laden with high levels of arsenic may suffer from non-cancerous health complications. Moreover, the carcinogenic risk values were as high as 2.31 × 10−3, implying a heightened danger of cancer over the long term due to arsenic-contaminated water. It was determined that Bhakkar tehsil had the highest quantity of arsenic among the tehsils in the Bhakkar district, making the groundwater unfit for drinking.

Elevated arsenic concentrations in groundwater of the Upper Indus Plain of Pakistan across a range of redox conditions

Groundwater of the Ravi River floodplain is particularly elevated in arsenic (As) on both sides of the Pakistan-India border. To understand this pattern, 14 sites were drilled to 12–30 m depth across floodplains and doabs of Pakistan after testing over 20,000 wells. Drill cuttings were collected at 1.5 m intervals, 132 of which were sand overlain by 77 intervals of clay and/or silt. Radiocarbon dating of clay indicates deposition of the aquifer sands tapped by wells 20–30 kyr ago. Most (85 %) of the sand samples were gray in color, indicating partial reduction to Fe(II) oxides, whereas most (92 %) of the clay and/or silt samples were orange. Associations between groundwater electrical conductivity, dissolved Fe, sulfate, and nitrate suggest that wells can be elevated (>10 μg/L) in As in the region due to either reductive dissolution of Fe oxides, evaporative concentration, or alkali desorption. In the Ravi floodplain, 47 % of 6445 wells tested contain >10 μg/L As compared to only 9 % of 14,165 tested wells in other floodplains and doabs. The As content of aquifer sands in the Ravi floodplain of Pakistan averages 4 ± 4 mg/kg (n = 66) and is higher than the average of 2 ± 2 mg/kg (n = 51) for aquifer sands outside the Ravi. Synchrotron spectroscopy and column-based speciation indicate predominance of As(V) over As(III) in both aquifer sands and groundwater. Whereas multiple processes may be responsible for elevated levels of As in groundwater across the region, spatial heterogeneity in groundwater As concentrations in the Ravi floodplain seems linked to variations in As concentrations in aquifer sands. Regulation by the solid phase may limit variations in groundwater As over time in response to natural and human-induced changes in hydrology. This means spatial heterogeneity could be taken advantage of to lower the exposure across the region with more testing and targeted drilling.

Large Scale Nationwide Screening of Bioavailable Tetracyclines and Arsenic Using Whole-cell Bioreporter from Pangasius and Tilapia Aquaculture System in Bangladesh

In this study, a large-scale screening of bioavailable tetracycline (TC) and arsenic (As) was carried out using Whole-Cell biosensor bacteria from the pond surface waters of selected pangasius and tilapia farms across Bangladesh. Bioavailability of Tetracyclines and Arsenic was detected using biosensor bacteria E. coli K12 pTetLux1 and E. coli DH5R (pJAMA-arsR), respectively. 62 samples were within the tetracycline detection limit; others were below the detection limit. The highest concentration 31.27µg/l was found in a pond of Jashore and the lowest concentration 2.57µg/l, was measured from Trishal, Mymensingh. Tetracyclines were detected in 19.57 % of all analyzed samples and varied from below the detection limit to a maximum of 31.27 μg/l. Khulna showed the maximum percentage of detected samples (90%), followed by Mymensingh (52%), Cumilla (27.5%), Jashore (14%), Bogura (14%), and Sathkhira (10%). Bioavailable As were detected in only 5.7% of all analyzed samples. Detectable as samples were higher in number among the collected samples at Madaripur and higher in percentage at Sathkhira (30%) followed by Madaripur (20%), Cumilla (5%), and Gopalgonj (3.2%). The pick level of Arsenic was found in Madaripur, which was 9.45 µg/l and the lowest figure was 2.35 µg/l, found in Cumilla. Though the concentrations of arsenic in groundwater (tube well water) were high in all studied regions, the concentrations of arsenic in pond water were low in every region. The concentration of as in the experimental ponds was neither very high nor in the danger limit. Use of shallow tube well water, fertilizers, drugs, pesticides, and herbicides possessed with as during fish culture might be the source of as contamination. However, extensive use of antibiotics results in the emergence and spread of antibiotic resistance in the aquatic environment.

Enrichment mechanism of arsenic in deep confined aquifers of Guide Basin under the influence of geothermal activities

High arsenic (As) concentrations in groundwater affected by geothermal activity have been reported worldwide, but the genesis mechanism is not adequately understood. To address this issue, 22 groundwater samples and 69 sediment samples were collected from the Guide basin in northwest China for hydrochemical and geochemical analyses and laboratory experiments. Results indicated that Fe/Mn oxide minerals were the main carriers of As, which was proved by a positive correlation between As and Fe or Mn in sediments. Analysis of hydrologic characteristics showed that direct contribution of As from geothermal water to confined groundwater was probably not significant in the Guide basin. Results of laboratory experiments indicated that As release from aquifer sediments was accelerated by increased temperature under different pH and ORP conditions. Raising temperature may stimulate the release of As by promoting dissolutions of As-bearing Fe (hydr)oxides, weathering of As-bearing silicates and As desorption from sediments into groundwater. The research results can not only increase the understanding of arsenic enrichment mechanism in groundwater under geothermal geological background, but also provide a scientific basis for other high-As groundwater with similar geological background in the world.

Water Supply Systems for Settlements with Arsenic-Contaminated Groundwater—Making the Right Choice

The environmentally and economically sustainable provision of safe drinking water remains one of the most significant public health challenges facing society. It is particularly difficult in small municipalities that lack the human and financial resources to maintain complex and/or expensive water treatment systems, especially in regions where the water is naturally contaminated with toxic substances such as arsenic. This paper analyses two municipalities (Kanjiža and Senta) in northern Serbia with groundwater arsenic concentrations significantly higher than the 10 µg/L maximum allowable concentration. Two different water supply approaches are compared: (1) local supply, where each settlement has their own treatment plant using existing sources; (2) creation of a centralised network, which connects several settlements together with better quality water sources. The analysis considers techno-economical aspects and the quantity and quality of available water, as well as the yields investment and exploitation cost projections for both approaches. The results demonstrate that for small municipalities, a holistic approach to decision making is necessary to find the best solutions for drinking water supply, which in the case of the two municipalities studied is connection to a centralised system supplied from better quality water sources and the creation of connections beyond municipal administrative boundaries.

Factors controlling groundwater Arsenic concentration in the Red River Delta, Vietnam

The Red River Delta (RRD) has a high population density with about 19 million inhabitants. Water supply is from surface water and groundwater resources, in which surface water is from rivers and groundwater is mainly taken from aquifers in Quaternary sediments. Last two-decade research’s results show that groundwater in some areas in the RRD are contaminated with high elevated levels of Arsenic. Many research studies investigating Arsenic pollution have found that concentrations in water samples surveyed in Hung Yen, Hanoi, Ha Nam etc exceed the permissible value for domestic use as WHO guideline and Vietnam standard as well. The key factors controlling the distribution of Arsenic in the groundwater from previous studies are formation environment, sedimentary facies, sedimentary age, salinity of pore water and even neo-tectonic activity. However, which factor is more important for controlling groundwater arsenic distribution in the RRD need to be clarified. Therefore, the objective of this study is to determine the degree of controlling factors on the distribution of Arsenic in groundwater in the RRD. An overview of previous studies on the origin of Arsenic in groundwater is the first step to analyse the factors affecting the distribution of Arsenic in groundwater. A method of superposition of the controlling factors on the basis of ArcGIS was applied. Each controlling factor was classified and assigned a certain value. The weights of the factors were determined based on expert opinions and analytical hierarchical process (AHP) method. The results of model calibration based on the current distribution of Arsenic concentration map of the Holocene and Pleistocene aquifers allow confirming the reliability of the weights of controlling factors. Research results show that the groundwater Arsenic concentration in the RRD depends mainly on the distribution of Holocene alluvium and its age. The remaining factors are very insignificant in this case.

Hydrogeochemical and sediment parameters improve predication accuracy of arsenic-prone groundwater in random forest machine-learning models

The relative importance of groundwater geochemicals and sediment characteristics in predicting groundwater arsenic distributions was rarely documented. To figure this out, we established a random forest machine-learning model to predict groundwater arsenic distributions in the Hetao Basin, China, by using 22 variables of climate, topographic features, soil properties, sediment characteristics, groundwater geochemicals, and hydraulic gradients of 492 groundwater samples. The established model precisely captured the patchy distributions of groundwater arsenic concentrations in the basin with an AUC value of 0.84. Results suggest that Fe(II) was the most prominent variable in predicting groundwater arsenic concentrations, which supported that the enrichment of arsenic in groundwater was caused by the reductive dissolution of Fe(III) oxides. The high relative importance of SO42− indicated that sulfate reduction was also conducive to groundwater arsenic enrichment in inland basins. Nevertheless, parameters of climate variables, sediment characteristics, and soil properties showed secondly important roles in predicting groundwater arsenic concentrations. The other two models, which excluded parameters of groundwater geochemicals and/or sediment characteristics, showed much worse predictions than the model considering all variables. This highlights the importance of variables of groundwater geochemicals and sediment characteristics in improving the precision and accuracy of predicting results. Future studies should probe a method constructing the random forest predicting model with high precision based on the limited number of groundwater samples and sediment samples.

Arsenic in groundwater in the Grand Canyon region and an evaluation of potential pathways for arsenic contamination of groundwater from breccia pipe uranium mining

The Grand Canyon in northern Arizona is an international tourist destination, a home or sacred place to many Native Americans, and hosts some of the highest-grade uranium deposits in the United States. Although potential contamination of water resources by uranium from mining activities is a concern, other elements commonly associated with these uranium deposits may pose a greater risk to human populations in the area. This study presents an assessment of arsenic in groundwater in the Grand Canyon area. First, sampling results for arsenic are presented and areas with elevated arsenic concentrations are discussed. Potential pathways of groundwater contamination by arsenic from uranium mines are then discussed to elucidate situations and conditions under which elevated concentrations of arsenic might be expected to become mobilized from breccia-pipe uranium mining activities. Results for arsenic in groundwater in the study area were available for 652 samples collected from 230 sites. Arsenic concentrations in groundwater ranged from less than reporting limits in 60 samples to a maximum concentration of 875 μg/L at Pumpkin Spring. About 88% (202) of the sites sampled had a maximum arsenic concentration below the drinking water standard of 10 μg/L. Available data from near former or current breccia-pipe uranium mines in the area indicate limited evidence to-date of mining effects on elevated arsenic in groundwater, although slow groundwater flow paths in the region may result in extended times of decades or more for groundwater to reach discharge locations. Post-mining entry of groundwater into the shaft and underground mine workings, with subsequent transport of metal-enriched groundwater offsite, may be a potential pathway of groundwater arsenic contamination from mining, although concentrations would likely be attenuated by contact with sedimentary rock units and dilution with native groundwater along flow paths. Monitoring of perched groundwater at reclaimed mine sites post-reclamation could provide data on the effectiveness of clean-closure practices on protecting groundwater quality in the area.

A hydrochemical and isotopic approach for source identification and health risk assessment of groundwater arsenic pollution in the central Yinchuan basin

Arsenic contamination of groundwater is becoming a major global issue as it can severely affect the safety of drinking water and human health. In this paper, 448 water samples were investigated to study the spatiotemporal distribution, source identification and human health risk of groundwater arsenic pollution in the central Yinchuan basin by applying a hydrochemical and isotopic approach. The results showed that arsenic concentrations in groundwater ranged from 0.7 μg/L to 26 μg/L with a mean of 2.19 μg/L, and 5.9% of samples were above 5 μg/L, indicating the arsenic pollution of groundwater in the study area. High arsenic groundwater was mainly distributed in the northern and eastern areas along the Yellow river. The main hydrochemistry type of high arsenic groundwater was HCO3·SO4–Na·Mg, and the dissolution of arsenic-bearing minerals in sediment, irrigation water infiltration and aquifer recharge from the Yellow river were the main sources of arsenic in groundwater. The arsenic enrichment was dominantly controlled by the TMn redox reaction and the competitive adsorption of HCO3−, and the influence of anthropogenic activities was limited. The health risk assessment suggested that the carcinogenic risk of As for children and adults greatly exceeded the acceptable risk threshold of 1E-6, displaying a high carcer risk, while the non-carcinogenic risks of As, F−, TFe, TMn and NO3− in 2019 were largely higher than the acceptable risk threshold (HQ > 1). The present study provides insight into the occurrence, hydrochemical processes and potential health risk of arsenic pollution in groundwater.

3D-printed device for the kinetic determination of As(III) in groundwater samples by digital movie analysis

High concentrations of inorganic arsenic in groundwater for human consumption is a worldwide common problem. Particularly, the determination of As(III) becomes important, since this species is more toxic than organic, pentavalent and elemental arsenic forms. In this work, a 3D-printed device that included a 24-well microplate was developed to perform the colourimetric kinetic determination of arsenic (III) by digital movie analysis. A smartphone camera attached to the device was used to take the movie during the process where As(III) inhibited the decolourization of methyl orange. The movie images were subsequently transformed from RGB to YIQ space to obtain a new analytical parameter called “d”, which was related to the chrominance of the image. Then, this parameter allowed the determination of the inhibition time of reaction (tin), which was linearly correlated with the concentration of As(III). A linear calibration curve (R = 0.9995) in the range from 5 μg L−1 to 200 μg L−1 was obtained. The method was precise (RSD = 1.2%), and the limits of detection (LOD) and quantification (LOQ) were 1.47 μg L−1 and 4.44 μg L−1, respectively. These values were lower than the limit established by the World Health Organization for total arsenic in drinking water (10 μg L−1). The accuracy of the method was assessed by a recovery study with optimal results (94.3%–104.0%). Additionally, the Analytical GREEnness metric approach was applied, obtaining a score 1.7 times higher than previously published works. The method is simple, portable and low-cost, being in compliance with various principles of green analytical chemistry.

Arsenic pollution and associated human health hazards in Rupnagar district, Punjab, India.

The hydrosphere although covering almost 70% of the Earth contributes only 3% of fresh water out of which groundwater covers almost 98%. The presence of some unwanted substance in this limited natural resource causes pollution when the substance causes serious harm to human beings and to the total ecosystem in a way. Arsenic is such a pollutant that is most naturally released in groundwater and long-term exposure to As-rich groundwater causes skin lesions and often leads to different types of cancers in humans. Rupnagar district in the Malwa region of Punjab is situated alongside the river Satluj which is one of the five important tributaries of Indus. The lowest reported concentration of As in this district is 10µg/L and the highest is 91µg/L. The higher values of As (> 50µg/L) that are above the permissible limit of IS 10500, 2004 in drinking water, are dominantly found in the western and south-western parts of the district. The average hazard quotient (HQ) indicates high risk for the consumers of the As-polluted groundwater in the district. The present study deals with the major cause of high arsenic (As) concentration in groundwater and its correlation with intensive agriculture in the Rupnagar district. Owing to the large size of the district, GIS techniques like ArcGIS 10.4.1 and QGIS 3.22.8 software were used for analysis in this study. The study reveals that high As concentration (> 50µg/L) is mostly found in agricultural lands and moderate concentration of As (10-50µg/L) in groundwater is distributed all over the district and are mostly reported from the urbanised areas. Overall, the water table shows a declining trend but no such decline is observed in the western and south-western parts of the district. As pollution in groundwater can also be caused due to water level decline owing to intensive agriculture and rapid water abstraction though As is naturally sourced in groundwater. A detailed study using the geochemical analysis of groundwater in the district can be effective in clearing out the scenario in the study area.

Sulfate reduction accelerates groundwater arsenic contamination even in aquifers with abundant iron oxides.

Groundwater contamination by geogenic arsenic is a global problem affecting nearly 200 million people. In South and Southeast Asia, a cost-effective mitigation strategy is to use oxidized low-arsenic aquifers rather than reduced high-arsenic aquifers. Aquifers with abundant oxidized iron minerals are presumably safeguarded against immediate arsenic contamination, due to strong sorption of arsenic onto iron minerals. However, preferential pumping of low-arsenic aquifers can destabilize the boundaries between these aquifers, pulling high-arsenic water into low-arsenic aquifers. We investigate this scenario in a hybrid field-column experiment in Bangladesh where naturally high-arsenic groundwater is pumped through sediment cores from a low-arsenic aquifer, and detailed aqueous and solid-phase measurements are used to constrain reactive transport modelling. Here we show that elevated groundwater arsenic concentrations are induced by sulfate reduction and the predicted formation of highly mobile, poorly sorbing thioarsenic species. This process suggests that contamination of currently pristine aquifers with arsenic can occur up to over 1.5 times faster than previously thought, leading to a deterioration of urgently needed water resources.