Arsenic In Groundwater Research Articles

Predicting Arsenic Contamination in Groundwater: A Comparative Analysis of Machine Learning Models in Coastal Floodplains and Inland Basins

Arsenic (As) contamination in groundwater represents a major global health threat, potentially impacting billions of individuals. Elevated As concentrations are found in river floodplains across south and southeast Asia, as well as in the inland basins of China, despite varying sedimentological and hydrogeochemical conditions. The specific mechanisms responsible for these high As levels remain poorly understood, complicating efforts to predict and manage the contamination. Applying hydro-chemical, geological, and soil parameters as explanatory variables, this study employs multiple linear regression (MLIR) and random forest regression (RFR) models to estimate groundwater As concentrations in these regions. Additionally, random forest classification (RFC) and multivariate logistic regression (MLOR) models are applied to predict the probability of As levels exceeding 10 μg/L in the Hetao Basin (China) and Bangladesh. Model validation reveals that RFR explains 80% and 70% of spatial variability of As concentration in the Hetao Basin and Bangladesh, respectively, outperforming MLIR, which accounts for only 35% and 32%. Similarly, RFC outperforms MLOR in predicting high As probability, achieving correct classification rates of 98.70% (Hetao Basin) and 98.25% (Bangladesh) on training datasets, and 82.76% (Hetao Basin) and 91.20% (Bangladesh) on validation datasets. The performance of the MLOR model on the validation set yields accuracy rates of 81.60% and 72.18%, respectively. In the Hetao Basin, Ca2+, redox potential (Eh), Fe, pH, SO42−, and Cl− are key predictors of As contamination, while in Bangladesh, soil organic carbon (SOC), pH, and SO42− are significant predictors. This study underscores the potential of random forest (RF) models as robust tools for predicting groundwater As contamination.

Unraveling the interplay of common groundwater ions in arsenic removal by sulfide-modified nanoscale zerovalent iron.

Sulphidation of nZVI (S-nZVI) has shown to significantly improve the arsenic removal capacity of nZVI, concurrently modifying the sequestration mechanism. However, to better apply S-nZVI for groundwater arsenic remediation, the impact of groundwater coexisting ions on the efficacy of arsenic uptake by S-nZVI needs to be investigated. This present study evaluates the potential of S-nZVI to remove arsenic in the presence of typical groundwater coexisting ions such as Cl-, HA, HCO3-, PO43- and SO42- through batch adsorption experiments. Individually, PO43- and HA had a dominant inhibition effect, while SO42- promoted As(III) removal by S-nZVI. Conversely, for As(V) removal, HCO3- and SO42- impeded the removal process. X-ray spectroscopic investigation suggests that the coexisting ions can either compete with arsenic for the adsorption sites, influence the S-nZVI corrosion rates and/or generate distinct corrosion products, thereby interfering with arsenic removal by S-nZVI. To investigate the cumulative effects of these ions, a 25-1 Fractional Factorial Design of experiments was employed, wherein the concentration of all the ions were varied simultaneously in an optimized manner, and their impact on arsenic removal by S-nZVI was observed. Our results shows that when these ions are present concurrently, PO43-, SO42- and HA still exerted a dominant influence on As(III) removal, whereas HCO3- was the main ions affecting As(V) removal, although the combined influence of the ions was not merely a summation of their individual effects. Overall, the finding of our study might provide valuable insight for predicting the actual performance of S-nZVI in field-scale applications for the remediation of arsenic-contaminated groundwater.

Arsenic-induced transition of thymic inflammation-to-fibrosis involves Stat3-Twist1 interaction: Melatonin to the rescue.

Groundwater arsenic is a notorious toxicant and exposure to environmentally relevant concentrations persists as a healthcare burden across the world. Arsenic has been reported to jeopardize the normal functioning of the immune system, but there are still gaps in the understanding of thymic T cell biology. Immunotoxic influence of arsenic in thymic integrity demands a potent restorative molecule. The objectives of this study were to examine key signaling cross-talks associated with arsenic-induced immune alterations in the thymus and propose melatonin as a potential candidate against immunological complications arising from arsenic exposure. Swiss albino mice were exposed to sodium arsenite (0.05 mg/L; in drinking water) and melatonin (IP:10 mg/kg BW) for 28 days. Melatonin successfully protected thymus from arsenic-mediated tissue degeneration and maintained immune homeostasis including T cell maturation and proliferation by mitigating oxidative stress through Nrf2 upregulation. Additionally, melatonin exerted ameliorative effect against arsenic-induced apoptosis and inflammation by inhibiting p53-mediated mitochondrial cell death pathway and NF-κB-p65/STAT3-mediated proinflammatory pathway, respectively. For the first time, we showed that arsenic-induced profibrotic changes were inhibited by melatonin through targeting of inflammation-associated EMT. Our findings clearly demonstrate that melatonin can be a viable and promising candidate in combating arsenic-induced immune toxicity with no collateral damage, making it an important research target.

Synergistic approach: Microwave assisted carbonisation and high energy ball milling for bionanomaterial fabrication- Analyzing Thermodynamic and kinetic models for arsenite ion adsorption

Arsenic contamination in water poses a significant global health threat, necessitating urgent and comprehensive measures to address this pervasive issue. This research investigates the efficacy of a novel microwave-assisted bionanomaterial derived from Calotropis procera stem, an abundant and eco-friendly adsorbent, for removing arsenite ions from aqueous solutions. Surface properties of Bionanomaterial was Characterised using Scanning Electron Microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), and Brunauer-Emmett-Teller (BET) analysis revealed a significant increase in surface area (578 m2/g) after high-energy ball milling, with SEM images showing an uneven surface with enlarged holes. Optimal arsenite removal was achieved at pH 5, a contact time of 90 min, an adsorbent dosage of 4 g, an initial arsenite concentration of 30 ppm, and a temperature of 60 °C. The zeta potential analysis indicated a shift in the isoelectric point from pH 6.2 to pH 5.0, reflecting effective adsorption and surface charge modification. Thermodynamic parameters suggested that adsorption is endothermic and spontaneous, with the Freundlich isotherm model providing the best fit for the adsorption data. Kinetic studies revealed that the process is governed by rapid external diffusion, intraparticle diffusion, and surface chemisorption, consistent with pseudo-second-order kinetics. These findings highlight the bionanomaterial’s potential as a viable adsorbent for arsenic removal from aqueous solutions.

Arsenic-contaminated groundwater of the Western Banat (Pannonian basin): Hydrogeochemical appraisal, pollution source apportionment, and Monte Carlo simulation of source-specific health risks.

Due to rapid urbanization and industrial growth, groundwater globally is continuously deteriorating, posing significant health risks to humans. This study employed a comprehensive methodology to analyze groundwater in the Western Banat Plain (Serbia). Using Piper and Gibbs plots, hydrogeochemistry was assessed, while the entropy-weighted water quality index (EWQI) was used to evaluate groundwater quality. Pollution sources were identified using positive matrix factorization (PMF) accompanied by Pearson correlation and hierarchical cluster analysis, while Monte Carlo simulation assessed health risks associated with groundwater consumption. Results showed that groundwater, mainly Ca-Mg-HCO3 type, is mostly suitable for drinking. Geogenic pollution, agricultural activities, and sewage were major pollution sources. Consumption of contaminated groundwater poses serious non-carcinogenic and carcinogenic health risks. Additionally, arsenic from geogenic source was found to be the main health risks contributor, considering its worryingly elevated concentration, ranging up to 364 μg/L. These findings will be valuable for decision-makers and researchers in managing groundwater vulnerability. PRACTITIONER POINTS: Groundwater is severely contaminated with As in the northern part of the study area. The predominant hydrochemical type of groundwater in the area is Ca-Mg-HCO3. The PMF method apportioned three groundwater pollution sources. Monte Carlo identified rock dissolution as the primary health risk contributor. Health risks and mortality in the study area are positively correlated.

A novel nanosheets assembled Co2P2O7 microrods for ultrasensitive electrochemical detection of As(III) ions

Arsenic pollution is common in seafood, grains, fruits, vegetables and groundwater. Long-term intake of arsenic-contaminated food or water may lead to various health problems. In this study, a novel nanosheets assembled Co2P2O7 microrod was prepared via a simple one-step hydrothermal method for the electrochemical detection of As(III). The Co2P2O7 microrods showed superior electric conductivity, good dispersion and a unique layered structure, which provided numerous electroactive sites to bind with As(III) and promoted the direct oxidization of As(III) to As(V) on the modified electrode surface. The proposed electrochemical sensor showed a high sensitivity of 4.174 µA/µg L−1 and a wide linear range of 0 ∼ 30 µg L−1 for As(III) detection via differential pulse voltammetry method in 0.1 M HAc-NaAc buffer (pH 5.0). Additionally, it exhibited good repeatability, reproducibility, stability and selectivity for As(III) detection. Moreover, the proposed sensor exhibited satisfactory applicability in hairtail samples.

Assessment on the Exposure of Air, Water and Noise Pollution, and Mental Stress on Preeclamptic Patients of Rajshahi, Bangladesh

Although preeclampsia claims the lives of 70,000 mothers and 500,000 newborns each year worldwide, its origin is still elusive and a number of risk factors such as environmental pollution are not yet addressed properly. In this study, exposures due to the extents of air, water and noise pollution as well as mental stress on preeclamptic patients have been investigated. Using a cross-sectional longitudinal design, 90 women hospitalized with preeclampsia in 7 hospitals of Rajshahi, Bangladesh were considered, of which Rajshahi Medical College Hospital is a tertiary referral hospital. The data were collected by interviewing the patients, physical examinations and merging the patients’ data with British Geological Survey’s groundwater data-sets (n=3,540). For statistical analyses, SPSS software was employed. It was found that most of the patients’ living rooms were within 15 feet from kitchen. Only 10% patients had good room ventilation, while the remaining 90% patients had either moderate or poor room ventilation. Combination of these facts reveals that the preeclamptic patients were subject to moderate CO2 exposure. Since 79% of the preeclamptic patients’ living rooms were below 50 ft from the nearest roads and 84% for 100 ft distance, they would experience noise pollution. Combination of traffic conditions and potential sources of noise pollution revealed that 60% of the preeclamptic patients experienced moderate to intense noise pollution. Groundwater arsenic, calcium, magnesium, iron and sodium concentrations in the patients’ drinking water were higher than WHO guideline values that should favour constipation and mild hypertension. While 70% patients were under high mental stress and 24% under very high mental stress, only 6% patients had moderate mental stress. It is concluded that air, water and noise pollution, and mental stress are potential risk factors of preeclampsia.

Groundwater Arsenic Contamination in the Indo-Gangetic Plain of Bihar: The Psychological Well-being and Quality of Life of its Diseased Inhabitants

The health impacts of groundwater arsenic contamination are only partially known until the arsenic menace is deciphered from a psychological standpoint. Arsenic toxicity’s psychological health and well-being perspective is warranted to attain sustainable development goal 3 of the United Nations towards good health and well-being for all. This study assesses psychological well-being and its substantial effect on the quality of life of the arsenic-affected diseased inhabitants of Bihar who reside in the middle Indo-Gangetic plain. Cross-sectional correlational survey research was done on a sample of 382 inhabitants drawn through purposive sampling. T-test, correlation, and regression analysis were employed for the purpose. The psychological well-being of the arsenic-affected diseased inhabitants was poor compared to that of their healthy counterparts. Further, the quality of life of this population is strongly associated with and affected by their psychological well-being. Findings call for immediate attention and intervention from mental health professionals and policymakers. Knowledge generation about the psychological health impacts of groundwater arsenic contamination paves a path to improved human resources and well-being for sustainable development.

Prediction of arsenic concentration in groundwater of Chapainawabganj, Bangladesh: machine learning-based approach to spatial modeling.

Groundwater in northwestern parts of Bangladesh, mainly in the Chapainawabganj District, has been contaminated by arsenic. This research documents the geographical distribution of arsenic concentrations utilizing machine learning techniques. The study aims to enhance the accuracy of model predictions by precisely identifying occurrences of groundwater arsenic, enabling effective mitigation actions and yielding more beneficial results. The reductive dissolution of arsenic-rich iron oxides/hydroxides is identified as the primary mechanism responsible for the release of arsenic from sediment into groundwater. The study reveals that in the research region, alongside elevated arsenic concentrations, significant levels of sodium (Na), iron (Fe), manganese (Mn), and calcium (Ca) were present. Statistical analysis was employed for feature selection, identifying pH, electrical conductivity (EC), sulfate (SO4), nitrate (NO3), Fe, Mn, Na, K, Ca, Mg, bicarbonate (HCO3), phosphate (PO4), and As as features closely associated with arsenic mobilization. Subsequently, various machine learning models, including Naïve Bayes, Random Forest, Support Vector Machine, Decision Tree, and logistic regression, were employed. The models utilized normalized arsenic concentrations categorized as high concentration (HC) or low concentration (LC), along with physiochemical properties as features, to predict arsenic occurrences. Among all machine learning models, the logistic regression and support vector machine models demonstrated high performance based on accuracy and confusion matrix analysis. In this study, a spatial distribution prediction map was generated to identify arsenic-prone areas. The prediction map also displays that Baroghoria Union and Rajarampur region under Chapainawabganj municipality are high-risk areas and Maharajpur Union and Baliadanga Union are comparatively low-risk areas of the research area. This map will facilitate researchers and legislators in implementing mitigation strategies. Logistic regression (LR) and support vector machine (SVM) models will be utilized to monitor arsenic concentration values continuously.

Determining arsenic stress tolerance genes in rice (Oryza sativa L.) via genomic insights and QTL mapping with double haploid lines

Arsenic, a hazardous heavy metal with potent carcinogenic properties, significantly affects key rice-producing regions worldwide. In this study, we present a quantitative trait locus (QTL) mapping investigation designed to identify candidate genes responsible for conferring tolerance to arsenic toxicity in rice (Oryza sativa L.) during the seedling stage. This study identified 17 QTLs on different chromosomes, including qCHC-1 and qCHC-3 on chromosome 1 and 3 related to chlorophyll content and qRFW-12 on chromosome 12 related to root fresh weight. Gene expression analysis revealed eight candidate genes exhibited significant upregulation in the resistant lines, OsGRL1, OsDjB1, OsZIP2, OsMATE12, OsTRX29, OsMADS33, OsABCG29, and OsENODL24. These genes display sequence alignment and phylogenetic tree similarities with other species and engaging in protein-protein interactions with significant proteins. Advanced gene-editing techniques such as CRISPR-Cas9 to precisely target and modify the candidate genes responsible for arsenic tolerance will be explore. This approach may expedite the development of arsenic-resistant rice cultivars, which are essential for ensuring food security in regions affected by arsenic-contaminated soil and water.

Late Quaternary tectonic uplift and Yellow River evolution create high arsenic aquifers in the Hetao Basin, China

High arsenic (As) groundwater is a global problem primarily originating from As-enriched sediments. The provenance (source) and release mechanisms (sinks) of high As sediment have been identified, but the source-sink transfer is poorly understood, especially the influence of geological and surface processes. In this study, we explore the roles of tectonic movement and Yellow River evolution in provenance formation processes and evaluate the combined effects of provenance and sediment age on the As content of aquifer sediments in the northern Hetao Basin of Inner Mongolia. Based on optically stimulated luminescence (OSL) and 14C dating and detrital zircon U-Pb, As content, and lithological analyses of a 400 m core, we reconstructed As changes over the last 160 ka. Our results show clay deposited in a paleo-lake during the Gonghe movement period in the late Pleistocene (∼100 ka B.P.) is enriched in As (31.8 μg/g) due to significant provenance contributions of the As-bearing Langshan Group under tectonic uplift and mountain erosion. In contrast, clay deposited in the middle Pleistocene (∼160 ka B.P.) has lower As content (7.3 μg/g) due to the Yellow River as the primary provenance. Accordingly, the provenance of basin As forced by tectonic uplift and Yellow River evolution determines the background As of aquifer sediments. After deposition, sediment As content decays over time, with higher decay rates in coarse-grained sands than fine-grained. Overall, both provenance formation and sediment age, representing initial and dynamic states of solid phase As, jointly determine the As content of aquifer sediments. More solid phase As provided by younger sediments from the proximal orogenic provenance and reducing conditions due to frequent river–lake transitions, jointly lead to higher As concentrations in shallow groundwater. The study highlights the potential for using a combined analysis of the tectonic movement-surface processes-environment system to improve understanding of geogenic high As groundwater over global large sedimentary basins in the proximity of young orogenic belts.

Integrated Solution for As(III) Contamination in Water Based on Crystalline Porous Organic Salts.

A stable crystalline organic porous salt (CPOSs-NXU-1) with 1D apertures has been assembled by the solvothermal method, which shows high-sensitivity "turn-on" fluorescence detection and large-capacity adsorption of As(III) ions in water. The detection limits, saturated adsorption capacity, and removal rate of CPOSs-NXU-1 for As(III) ions in an aqueous solution can reach 74.34nm (5.57 ppb), 451.01mgg-1, and 99.6%, respectively, at pH = 7 and room temperature. With the aid of XPS, IR, Raman, and DFT theoretical calculations, it is determined that CPOSs-NXU-1 adsorbed As(III) ions in the form of H2AsO3 - and H3AsO3 through hydrogen bonding between the host and guest. The mechanism for fluorescence sensitization of As(III) ions to CPOSs-NXU-1 is mainly to increase the energy level difference between the ground state and excited state investigated by UV-vis absorption spectra, UV-vis diffuse reflectance spectra, and theoretical calculations. By constructing fluorescent CPOSs, an integrated solution has been achieved to treating As(III) contamination in the water that is equipped with detection and removal. These results blaze a promising path for addressing trivalent arsenic contamination in water efficiently, rapidly, and economically.

Sustaining Irrigation Supplies through Immobilization of Groundwater Arsenic In Situ.

Geogenic arsenic (As) in groundwater is widespread, affecting drinking water and irrigation supplies globally, with food security and safety concerns on the rise. Here, we present push-pull tests that demonstrate field-scale As immobilization through the injection of small amounts of ferrous iron (Fe) and nitrate, two readily available agricultural fertilizers. Such injections into an aquifer with As-rich (200 ± 52 μg/L) reducing groundwater led to the formation of a regenerable As reactive filter in situ, producing 15 m3 of groundwater meeting the irrigation water quality standard of 50 μg/L. Concurrently, sediment magnetic properties were markedly enhanced around the well screen, pointing to neo-formed magnetite-like minerals. A reactive transport modeling approach was used to quantitatively evaluate the experimental observations and assess potential strategies for larger-scale implementation. The modeling results demonstrate that As removal was primarily achieved by adsorption onto neo-formed minerals and that an increased adsorption site density coincides with the finer-grained textures of the target aquifer. Up-scaled model simulations with 80-fold more Fe-nitrate reactants suggest that enough As-safe water can be produced to irrigate 1000 m2 of arid land for one season of water-intense rice cultivation at a low cost without causing undue contamination in surface soils that threatens agricultural sustainability.

Comparative evaluation of diffusion kinetics of arsenic adsorption on iron (oxy) hydroxides containing biopolymer nanocomposite beads

Exposure to arsenic-contaminated water poses great health risks to mankind. Nanocomposite beads have been proven to be an effective alternative for large-scale treatment of arsenic-loaded water. The larger size of the beads makes the adsorbent retrieval process less energy-intensive and prevents accidental leaching of nanoparticles into the surrounding environment. Adsorption using macroporous beads is predominantly a diffusion-controlled process. Therefore, in the present study, the shrinking core model (SCM) was used to compare and evaluate the diffusion kinetics of arsenic adsorption using in-situ precipitated iron (oxy)hydroxide alginate (IIAB) and chitosan beads (IICB). Simulated dynamic nondimensional liquid phase arsenic concentration profiles fit well with the experimental data (SSE = 0.018–0.025). External mass transfer coefficient (kf) and effective diffusivity coefficient (De) for both kinds of beads at different initial arsenic concentrations (C0 ∼ 1 mg.L−1 and 5 mg.L−1) were derived. By comparison of diffusivity values and the simulated concentration front profiles, it was observed that chitosan provided a better porous polymer template with more easily accessible adsorption sites covering up to 85 % of the beads’ volume. Comparison with progression conversion models has also been made to test the effectiveness of SCM fitting.

Melatonin differentially refines the metabolome to improve seed formation during grain developmental stages and enhances yield in two contrasting rice cultivars, grown in arsenic-contaminated soil

The manuscript revealed the ameliorative effects of exogenous melatonin in two distinct reproductive stages, i.e., developing grains (20 days after pollination) and matured grains (40 days after pollination) in two contrasting indica rice genotypes, viz., Khitish (arsenic-susceptible) and Muktashri (arsenic-tolerant), irrigated with arsenic-contaminated water throughout their life-cycle. Melatonin administration improved yield-related parameters like rachis length, primary and secondary branch length, number of grains per panicle, number of filled and empty grains per panicle, grain length and breadth and 1000-grain per weight. Expression of GW2, which negatively regulates grain development, was suppressed, along with concomitant induction of positive regulators like GIF1, DEP1 and SPL14 in both Khitish and Muktashri. Melatonin lowered arsenic bioaccumulation in grains and tissue biomass, more effectively in Khitish. Unregulated production of reactive oxygen species, leading to cellular necrosis caused by arsenic, was reversed in presence of melatonin. Endogenous melatonin level was stimulated due to up-regulation of the key biosynthetic genes, SNAT and ASMT. Melatonin enhanced the production of diverse antioxidants like anthocyanins, flavonoids, total phenolics and ascorbic acid and also heightened the production of thiol-metabolites (cysteine, reduced glutathione, non-protein thiols and phytochelatin), ensuring effective chelation and arsenic detoxification. Altogether, our observation, supported by principal component analysis, proved that melatonin re-programs the antioxidative metabolome to enhance plant resilience against arsenic stress to mitigate oxidative damages and reduce arsenic translocation from the soil to tissue biomass and edible grains.

A comprehensive monitoring approach for a naturally anoxic aquifer beneath a controlled landfill

The processes leading to high levels of arsenic (As), iron (Fe), and manganese (Mn) in groundwater, in a naturally reducing aquifer at a controlled municipal landfill site, are investigated. The challenge is to distinguish the natural water-rock interaction processes, that allow these substances to dissolve in groundwater, from direct pollution or enhanced dissolution of hydroxides as undesired consequences of the anthropic activities above. Ordinary groundwater monitoring of physical-chemical parameters and inorganic compounds (major and trace elements) was complemented by environmental isotopes of groundwater (tritium, deuterium, oxygen-18 and carbon-13) and dissolved gases (carbon-13 of methane and carbon dioxide and carbon-14 of methane). Pearson/Spearman correlation indices, as well as Principal Component Analysis (PCA), were used to determine the main correlations among variables. The concurrent presence of As, Fe and CH4, as reported in similar anoxic environments, suggests that anaerobic oxidation of methane could drive the reductive dissolution of As-rich Fe(III)(hydro)oxides. Manganese is more sensitive to carbon dioxide, possibly due to a decrease in pH which accelerates the dissolution of Mn-oxides. Finally, we found that tritium and deuterium, which have been used for decades as leachate tracer in groundwater, may be subject to false positives due to the reuse of water recovered from leachate treatment (which has the same isotopic signature of leachate) within the plants, to comply with the requirements of the circular economy. The integration of the environmental isotope analysis into the traditional monitoring approach can effectively support the comprehension of processes. However, this strategy needs to be complemented by a good conceptual hydrogeological model and expert evaluation to avoid misinterpretations.

Arsenite oxidation and adsorptive arsenic removal from contaminated water: a review.

Arsenic poisoning of groundwater is one of the most critical environmental hazards on Earth. Therefore, the practical and proper treatment of arsenic in water requires more attention to ensure safe drinking water. The World Health Organization (WHO) sets guidelines for 10μg/L of arsenic in drinking water, and direct long-term exposure to arsenic in drinking water beyond this value causes severe health hazards to individuals. Numerous studies have confirmed the adverse effects of arsenic after long-term consumption of arsenic-contaminated water. Here, technologies for the remediation of arsenic from water are highlighted for the purpose of understanding the need for a single-point solution for the treatment of As(III)-contaminated water. As(III) species are neutral at neutral pH; the solution requires transformation technology for its complete removal. In this critical review, emphasis was placed on single-step technologies with multiple functions to remediate arsenic from water.

Perfluoroalkyl compounds in groundwater alter the spatial pattern of health risk in an arsenic‑cadmium contaminated region

Integrated health risk assessment strategies for emerging organic pollutants and heavy metals that coexist in water/soil media are lacking. Contents of perfluoroalkyl compounds and potentially toxic elements in multiple media were determined by investigating a county where a landfill and a tungsten mine coexist. The spatial characteristics and sources of contaminants were predicted by Geostatistics-based and multivariate statistical analysis, and their comprehensive health risks were assessed. The average contents of perfluorooctane acid, perfluorooctanesulfonic acid, arsenic, and cadmium in groundwater were 3.21, 0.77, 1.69, and 0.14 μg L−1, respectively; the maximum content of cadmium in soils and rice highly reached 2.12 and 1.52 mg kg−1, respectively. In soils, the contribution of mine lag to cadmium was 99 %, and fertilizer and pesticide to arsenic was 59.4 %. While in groundwater, arsenic, cadmium and perfluoroalkyl compounds near the landfill mainly came from leachate leakage. Significant correlations were found between arsenic in groundwater and arsenic and cadmium in soils, as well as perfluoroalkyl compounds in groundwater and pH and sulfate. Based on these correlations, the geographically optimal similarity model predicted high-level arsenic in groundwater near the tungsten mine and cadmium/perfluoroalkyl compounds around the landfill. The combination of analytic network process, entropy weighting method and game theory-based trade-off method with risk assessment model can assess the comprehensive risks of multiple pollutants. Using this approach, a high health-risk zone located around the landfill, which was mainly attributed to the presence of arsenic, cadmium and perfluorooctanesulfonic acid, was found. Overall, perfluoroalkyl compounds in groundwater altered the spatial pattern of health risks in an arsenic‑cadmium contaminated area.

High-efficiency removal of As(iii) from groundwater using siderite as the iron source in the electrocoagulation process.

Electrocoagulation technology, due to its simplicity and ease of operation, is often considered for treating arsenic-contaminated groundwater. However, challenges such as anode wear have hindered its development and application. This study aims to develop a siderite-filled anode electrocoagulation system for efficient removal of As(iii) and investigate its effectiveness. The impact of operational parameters on the removal rate of As(iii) was analyzed through single-factor tests, and the stability and superiority of the device were evaluated. The response surface methodology was employed to analyze the interactions between various factors and determine the optimal operational parameters by integrating data from these tests. Under conditions where the removal rate of As reached 99.3 ± 0.37%, with an initial concentration of As(iii) at 400 μg L-1, current intensity at 30 mA, initial solution pH value at 7, and Na2SO4 concentration at 10 mM. The flocculant used was subjected to characterization analysis to examine its structure, morphology, and elemental composition under these optimal operational parameters. The oxidation pathway for As(iii) within this system relies on integrated results from direct electrolysis as well as ˙O2 -, ˙OH, and Fe(iv) mediated oxidation processes. The elimination of arsenic encompasses two fundamental mechanisms: firstly, the direct adsorption of As(iii) by highly adsorbent flocculants like γ-FeOOH and magnetite (Fe3O4); secondly, the oxidation of As(iii) into As(v), followed by its reaction with siderite or other compounds to generate a dual coordination complex or iron arsenate, thus expediting its eradication. The anodic electrocoagulation system employing siderite as a filler exhibits remarkable efficiency and cost-effectiveness, while ensuring exceptional stability, thereby providing robust theoretical underpinnings for the application of electrocoagulation technology in arsenic removal.

Inclusion of Drinking Water Source and Testing Questions into Electronic Medical Records: Advancing Environmental Medicine and Public Health Outreach in New Jersey.

Chronic arsenic exposure is associated with adverse health outcomes, and early life exposure is particularly damaging. Households with pregnant people and young children drinking from unregulated wells in arsenic-prevalent regions are therefore a public health priority for outreach and intervention. A partnership between Columbia University, New Jersey government partners, and Hunterdon Healthcare has informed Hunterdon County residents of the risks faced from drinking arsenic-contaminated water and offered free well testing through a practice-based water test kit distribution and an online patient portal outreach. Encouraged by those successes, Hunterdon Healthcare incorporated questions about drinking water source and arsenic testing history into the electronic medical record (EMR) template used by most primary care practices in Hunterdon County. The new EMR fields allow for additional targeting of risk-based outreach and water test kit distribution, offering promising new opportunities for public health and environmental medicine outreach, surveillance, and research.