Selective Chromogenic Chemosensors for Arsenite Anion: A Facile Approach to Analyzing Arsenite in Honey, Milk, and Water Samples

In this study, two chemosensors, N5R1 and N5R2, based on 5-(4-nitrophenyl)-2-furaldehyde, with varying electron-withdrawing groups, were synthesized and effectively employed for the colorimetric selective detection of arsenite anions in a DMSO/H2O solvent mixture (8 : 2, v/v). Chemosensors N5R1 and N5R2 exhibited a distinct color change upon binding with arsenite, accompanied by a spectral shift toward the near-infrared region (Δλmax exceeding 200 nm). These chemosensors established stability between a pH range 6-12. Among them, N5R2 displayed the lowest detection limit of 17.63 ppb with a high binding constant of 2.6163×105 M-1 for arsenite. The binding mechanism involved initial hydrogen bonding between the NH binding site and the arsenite anion, followed by deprotonation and an intramolecular charge transfer (ICT) mechanism. The mechanism was confirmed through UV and 1H NMR titrations, cyclic voltammetric studies, and theoretical calculations. The interactions between the sensor and arsenite anions were further analyzed using global reactivity parameters (GRPs). Practical applications were demonstrated through the utilization of test strips and molecular logic gates. Real water samples, honey, and milk samples were successfully analyzed by both chemosensors for the sensing of arsenite.

Arsenic redox disequilibrium in geogenic contaminated groundwater: Bioenergetic insights from organic molecular characterization and gene-informed modeling

Biotransformation of arsenic (As) influences its speciation and mobility, obscuring mechanistic comprehension on spatiotemporal variation of As concentration in geogenic contaminated groundwater. In particular, unresolved processes underlying As redox disequilibrium in comparison to major redox couples discourage practical efforts to rehabilitate the As-contaminated groundwater. Here, quantitative metagenomic sequencing and ultrahigh-resolution mass spectrometry (FT-ICR-MS) were jointly applied to reveal the links between vertical distribution of As metabolic gene assemblages and that of free energy density of dissolved organic matter (DOM) in As-contaminated groundwater of Datong Basin. Observed small excess of Gibbs free energy available by DOM relative to that required for As(V)-to-As(III) reduction exerts thermodynamic constraint on metabolism-mediated redox transformation of As. Accordingly, the vertical distribution of dissolved As(V)/As(III) ratio correlated significantly with that of ars+acr3 and arr encoding As(V) reduction and aio encoding As(III) oxidation in the moderately/strongly reducing groundwater. Further gene-informed biogeochemical modeling suggests that a net effect of these kinetics-restricted bidirectional metabolic pathways leads to co-preservation of As(V) and As(III) even at relatively high rates of ars+acr3 encoded As(V) reduction. This study therefore provides new insights into bioenergetic constraints on As hydrobiogeochemical behavior, with implications for other redox-sensitive contaminants in the groundwater systems.

DFT Study on the Mechanism of As(III) Oxidation in the Presence of Fe(II) and O2

In natural aquatic environments, the fate of arsenic (As) is significantly influenced by redox processes involving iron (Fe) species. Understanding the mechanisms governing As transformation in the presence of Fe species is crucial for comprehending its environmental impact and advancing remediation strategies. In this work, the oxidation of As(III) in oxygenated Fe(II) solutions was investigated. Density functional theory (DFT) methods were employed to explore the reaction of Fe(II) with 3O2 and subsequent As(III) oxidation by reactive species generated from Fe(II) oxidation. Electron paramagnetic resonance analysis was utilized to confirm the formation of reactive species in the solution. Based on these results, it is concluded that 1O2, ·O2H, and Fe(IV) are the critical oxidants responsible for As(III) oxidation in oxygenated Fe(II) solutions under circumneutral conditions. 1O2 readily oxidizes As(III) by forming an arsenic superoxide AsO5H3. Interaction of As(III) with ·O2H or Fe(IV) leads to As(IV), which is further oxidized to As(V) by 3O2, Fe(III), and Fe(IV).

Understanding the Global Distribution of Groundwater Sulfate and Assessing Population at Risk

Besides sulfate-induced diarrhea, recent studies have emphasized that groundwater sulfate drives the release of arsenic in groundwater and accelerates water pipeline corrosion. Despite its impact on public health and urban infrastructure, sulfate has been overlooked in water supply research. Here, we used a random forest model to develop a 1 km global map depicting the probability of sulfate exceeding 250 mg/L in groundwater based on the World Health Organization's guidelines. The map was further applied to estimate the exposed population and identify contributors of sulfate exceedance in global hotspot regions. The results revealed that sulfate exceedance in groundwater was widespread in 156 countries. Approximately 194 million people use water with sulfate levels exceeding 250 mg/L. Among them, around 17 million people face groundwater sulfate concentrations surpassing 500 mg/L, with 82% of these individuals residing in ten specific countries. Contributing factor analysis in these countries indicates that annual precipitation and sedimentary rocks are the primary factors contributing to sulfate concentration prediction, while other natural and anthropogenic predictors exhibit region-specific impact patterns. This study uncovered a significant prevalence of elevated sulfate levels in groundwater, highlighting the need to integrate sulfate into water safety management practices.

Effect of Fenton-Based Processes on Arsenic Removal in the Presence of Humic Acid

Geogenic arsenic (As) contamination in groundwater poses a significant public health risk in many regions worldwide. Previous studies have reported hydrogen peroxide (H2O2) concentrations ranging from 5.8 to 96 μmol L-1 in rainwater, which may contribute to the oxidation and removal of As. However, the influence of natural organic matter, such as humic acid (HA), on rainwater-borne H2O2-induced Fenton processes for the oxidation and removal of As remains unclear. In this study, the Fenton process was employed to investigate changes in As(V), As(III), and their mixtures, both in the presence and absence of HA. The results showed that low concentrations of HA (0-10 mg/L) promoted the oxidation of As(III) and removal of As(V) when As(V) and As(III) were present individually. However, when As(V) and As(III) coexisted, HA inhibited the Fenton process for As(V) removal. This inhibition was likely due to As(III) competing strongly with HA for hydroxyl radicals in the Fenton reaction system. Additionally, the presence of HA hindered the Fe(III)-driven removal of As(V), a product of the Fenton reaction. These findings further enhance our understanding of the potential role of rainwater-borne H2O2 in the transformation of As species in open water environments.

Spatial distribution and hydrogeochemical processes of high iodine groundwater in the Hetao Basin, China

To understand the genesis and spatial distribution of high iodine groundwater in the Hetao Basin, 540 groundwater samples were analyzed for the chemistry and isotope. Total iodine concentrations in groundwater range from 1.32 to 2897 μg/L, with a mean value of 159.2 μg/L. The groundwater environment was mainly characterized by the weakly alkaline and reducing conditions, with the iodide as the main species of groundwater iodine. High iodine groundwater (I > 100 μg/L) was mainly distributed in shallow aquifers (< 30 m) of Hangjinhouqi near the Langshan Mountain and the discharge areas along the main drainage channels. The δ18O and δ2H values ranged from -12.09 ‰ to -3.99 ‰ and - 91.58 ‰ to -52.80 ‰, respectively, and the correlation between groundwater iodine and isotopes indicates the dominant role of evapotranspiration in the enrichment of iodine in the shallow groundwater with depth <30 m. It was further evidenced by the correlation between groundwater iodine and Cl/Br molar ratio, and significant contributions of climate factors identified from the random forest and XGBoost. Moreover, irrigation practices contribute to high iodine levels, with surface water used for irrigation containing up to 537.8 μg/L of iodine, which can be introduced into shallow aquifer directly. The iodine in irrigation water can be retained in the soil or shallow sediment, and later leach into groundwater under favorable conditions.

Identifying groundwater ammonium hotspots in riverside aquifer of Central Yangtze River Basin

Elevated ammonium (NH4-N) contents in groundwater are a global concern, yet the mobilization and enrichment mechanisms controlling NH4-N within riverside aquifers (RAS) remain poorly understood. RAS are important zones for nitrogen cycling and play a vital role in regulating groundwater NH4-N contents. This study conducted an integrated assessment of a hydrochemistry dataset using a combination of hydrochemical analyses and multivariate geostatistical methods to identify hydrochemical compositions and NH4-N distribution in the riverside aquifer within Central Yangtze River Basin, ultimately elucidating potential NH4-N sources and factors controlling NH4-N enrichment in groundwater ammonium hotspots. Compared to rivers, these hotspots exhibited extremely high levels of NH4-N (5.26 mg/L on average), which were mainly geogenic in origin. The results indicated that N-containing organic matter (OM) mineralization, strong reducing condition in groundwater and release of exchangeable NH4-N in sediment are main factors controlling these high concentrations of NH4-N. The Eh representing redox state was the dominant variable affecting NH4-N contents (50.17 % feature importance), with Fe2+ and dissolved organic carbon (DOC) representing OM mineralization as secondary but important variables (26 % and 5.11 % feature importance, respectively). This study proposes a possible causative mechanism for the formation of these groundwater ammonium hotspots in RAS. Larger NH4-N sources through OM mineralization and greater NH4-N storage under strong reducing condition collectively drive NH4-N enrichment in the riverside aquifer. The evolution of depositional environment driven by palaeoclimate and the unique local environment within the RAS likely play vital roles in this process.

3D printed microplasma optical emission spectrometry coupled with ZIF-8 based dispersive solid-phase extraction for field analysis of waterborne arsenic

BACKGROUND

Arsenic contamination of drinking water has become a public health challenge over the world, particularly in Bangladesh, India, and China. Compared to the most used field test kits of waterborne arsenic, miniature microplasma atomic spectrometry retains advantages of accuracy, elemental specificity, and less matrix interference. Despite increased interest in arsenic detection by using miniature microplasma spectrometry, the improvements of its analytical performance, manufacturing cost and consistency still remain significant challenges.

RESULTS

Herein, a miniature, battery-operated, and integrated hydride generation point discharge optical emission spectrometer (HG-μPD-OES, 116 mm length × 92 mm width × 104 mm height) was printed with a simple 3D printer and used for the highly sensitive and element-specific determination of arsenic by coupling to a dispersive solid-phase extraction (d-SPE) using zeolitic imidazolate framework-8 as adsorbent. The d-SPE simplifies sample treatment, significantly alleviates the interference arising from transition metal ions and improves sensitivity. A LOD of 0.07 μg L-1 for arsenic was obtained with relative standard deviations (RSDs, n = 11) better than 3.8 %.

SIGNIFICANCE

The 3D printing technique significantly improves the manufacturing cost and fabricating consistency of HG-μPD-OES. LOD were remarkably improved 27-fold compared to those obtained by conventional HG-μPD-OES, providing a promising method for the reliable, sensitive, and convenient field analysis of waterborne arsenic even its concentration as low as 0.2 μg L-1. The practicability and accuracy of the proposed method have been successfully verified via the field analysis of waterborne arsenic in a Certified Reference Material (GBW(E)080390) and a series of river and lake water samples.

Cadmium-Assisted Photochemical Vapor Generation of Arsenic from Low Concentration of Formic Acid Media

A highly sensitive method for the determination of total arsenic (As) has been developed using photochemical vapor generation (PVG) coupled with inductively coupled plasma mass spectrometry (ICP MS). The efficient PVG of As is reported for the first time in the presence of Cd(II) in diluted formic acid (FA) medium. The PVG efficiency of 93 ± 1% can be achieved in the system with 0.15% (v/v) FA and 40.0 mg L-1 Cd(II) under 100 s UV irradiation. The limit of detection (LOD, 3σ) for As was determined to be 0.2 ng L-1, which was enhanced about 43-fold over the traditional solution nebulization method. The anti-interference capability against sample matrices was enhanced compared to previous PVG systems that used diluted formic acid alone or a combination of sodium formate and sodium sulfite as the medium. The established method was applied for the analysis of natural waters and certified reference materials (CRMs) of rice with satisfactory results. The mechanism of the PVG system was investigated, and the generation of volatile As species as AsH3 was found in all investigated systems, including monomethylarsonic acid (MMA), dimethylarsinic acid (DMA), As (III), and As(V). Additionally, volatile cadmium species were also generated simultaneously. The efficient reduction of As in diluted FA observed in this study is beneficial to understanding the interaction between As and Cd in the photochemical process.

Machine learning models for predicting the rejection of organic pollutants by forward osmosis and reverse osmosis membranes and unveiling the rejection mechanisms

While forward osmosis (FO) and reverse osmosis (RO) processes have been proven effective in rejecting organic pollutants, the rejection rate is highly dependent on compound and membrane characteristics, as well as operating conditions. This study aims to establish machine learning (ML) models for predicting the rejection of organic pollutants by FO and RO and providing insights into the underlying rejection mechanisms. Among the 14 ML models established, the random forest model (R2 = 0.85) and extreme gradient boosting model (R2 = 0.92) emerged as the best-performing models for FO and RO, respectively. Shapley additive explanations (SHAP) analysis identified the length of the compound, water flux, and hydrophobicity as the top three variables contributing to the FO model. For RO, in addition to the length of the compound and operating pressure, advanced variables including four molecular descriptors (e.g., ATSC2m and Balaban J) and three fingerprints (e.g., C=C double bond and carbonyl group) significantly contributed to the prediction. Besides, the associations between these highly ranked variables and their SHAP values shed light on the rejection mechanisms, such as size exclusion, adsorption, hydrophobic interaction, and electrostatic interaction, and illustrate the role of the operating parameters, such as the FO permeate water flux and RO operating pressure, in the rejection process. These findings provide interpretable predictive models for the removal of organic pollutants and advance the mechanistic understanding of the rejection mechanisms in the FO and RO processes.

Differential Selectivity of Human and Mouse ABCC4/Abcc4 for Arsenic Metabolites

Millions of people globally are exposed to the proven human carcinogen arsenic at unacceptable levels in drinking water. In contrast, arsenic is a poor rodent carcinogen, requiring >100-fold higher doses for tumor induction, which may be explained by toxicokinetic differences between humans and mice. The human ATP-binding cassette subfamily C (ABCC) transporter hABCC4 mediates the cellular efflux of a diverse array of metabolites, including the glutathione (GSH) conjugate of the highly toxic monomethylarsonous acid (MMAIII), monomethylarsenic diglutathione [MMA(GS)2], and the major human urinary arsenic metabolite dimethylarsinic acid (DMAV). Our objective was to determine if mouse Abcc4 (mAbcc4) protected against and/or transported the same arsenic species as hABCC4. The anti-ABCC4 antibody M4I-10 epitope was first mapped to an octapeptide (411HVQDFTA418F) present in both hABCC4 and mAbcc4, enabling quantification of relative amounts of hABCC4/mAbcc4. mAbcc4 expressed in human embryonic kidney (HEK)293 cells did not protect against any of the six arsenic species tested [arsenite, arsenate, MMAIII, monomethylarsonic acid, dimethylarsinous acid, or DMAV], despite displaying remarkable resistance against the antimetabolite 6-mercaptopurine (>9-fold higher than hABCC4). Furthermore, mAbcc4-enriched membrane vesicles prepared from transfected HEK293 cells did not transport MMA(GS)2 or DMAV despite a >3-fold higher transport activity than hABCC4-enriched vesicles for the prototypic substrate 17β-estradiol-17-(β-D-glucuronide). Abcc4(+/+) mouse embryonic fibroblasts (MEFs) were ∼3-fold more resistant to arsenate than Abcc4(-/-) MEFs; however, further characterization indicated that this was not mAbcc4 mediated. Thus, under the conditions tested, arsenicals are not transported by mAbcc4, and differences between the substrate selectivity of hABCC4 and mAbcc4 seem likely to contribute to arsenic toxicokinetic differences between human and mouse. SIGNIFICANCE STATEMENT: Toxicokinetics of the carcinogen arsenic differ among animal species. Arsenic methylation is known to contribute to this, whereas arsenic transporters have not been considered. Human ATP-binding cassette subfamily C member 4 (hABCC4) is a high-affinity transporter of toxicologically important arsenic metabolites. Here we used multiple approaches to demonstrate that mouse Abcc4 does not protect cells against or transport any arsenic species tested. Thus, differences between hABCC4 and mAbcc4 substrate selectivity likely contribute to differences in human and mouse arsenic toxicokinetics.

Differential response of catalase to As (III) and As (V): Potential molecular mechanism under valence effect

Arsenic (As) is the most prolific contaminant in food, triggering arseniasis primarily via contaminated rice and drinking contaminated water. However, toxicological data for arsenite (As (III)) and arsenate (As (V)) on antioxidant enzyme catalase (CAT) at molecular level is shortage. The interaction mechanism of As (III) and As (V) with CAT was investigated using enzyme activity detection, multi-spectroscopic techniques, isothermal titration calorimetry and computational simulations. Results indicated As (III) and As (V) induced protein skeleton relaxation, secondary structure transformation, fluorescence sensitization and particle alteration of CAT, particularly As (III). Moreover, As (III)/As (V) bound to CAT through hydrogen bonding and hydrophobic. As (III) and As (V) contacted with core residues His 74, Asn 147 and His A74, Trp A357, respectively, thereby inhibiting CAT activity. Overall, As (III) is more aggressive against the structure and physiological function of CAT than As (V). Our findings enhance the understanding of health risk related to dietary As exposure.

Redox Dynamic Interactions of Arsenic(III) with Green Rust Sulfate in the Presence of Citrate

Arsenic is a global pollutant. Recent studies found that Fe(II) can oxidize As(III), but the extent of oxidation with mixed-valent iron minerals and the mechanisms involved are unknown. In this study, we investigated whether As(III) can be oxidized under reducing conditions using green rust sulfate (GR-SO4), an Fe mineral containing both Fe(II) and Fe(III). Batch sorption experiments showed that GR-SO4 (1 g L-1) effectively sorbs environmentally relevant concentrations of As(III) (50-500 μg L-1) under anoxic, neutral pH conditions with and without citrate (50 μM). X-ray absorption near-edge structure spectroscopy analysis at the As K-edge demonstrated that approximately 76% of As(III) was oxidized to As(V) by GR-SO4. Complete oxidation of As(III) was observed in the presence of citrate. As(III) oxidation can be linked to the phase transformation of GR-SO4 to goethite, resulting in new reactive Fe(III) species that plausibly drive oxidation. Citrate enhanced this process by stabilizing Fe on the mixed GR-SO4/goethite surface, preventing its reduction back to Fe(II) and facilitating further As(III) oxidation without significant Fe loss to the solution. This study highlights the cryptic As(III) oxidation that occurs under reducing conditions, providing new insights into the cycling of arsenic in mixed phases of iron-rich, anoxic environments.

Machine learning predicts heavy metal adsorption on iron (oxyhydr)oxides: A combined insight into the adsorption efficiency and binding configuration

The adsorption of heavy metal on iron (oxyhydr)oxides is one of the most vital geochemical/chemical processes controlling the environmental fate of these contaminants in natural and engineered systems. Traditional experimental methods to investigate this process are often time-consuming and labor-intensive due to the complexity of influencing factors. Herein, a comprehensive database containing the adsorption data of 11 heavy metals on 7 iron (oxyhydr)oxides was constructed, and the machine learning models was successfully developed to predict the adsorption efficiency. The random forest (RF) models achieved high prediction performance (R2 > 0.9, RMSE < 0.1, and MAE < 0.07) and interpretability. Key factors influencing heavy metal adsorption efficiency were identified as mineral surface area, solution pH, metal concentration, and mineral concentration. Additionally, by integrating our previous binding configuration models, we elucidated the simultaneous effects of input features on adsorption efficiency and binding configuration through partial dependence analysis. Higher pH simultaneously enhanced adsorption efficiency and affinity for cations, whereas lower pH benefited that for oxyanions. While higher mineral surface area improved the metal adsorption efficiency, the adsorption affinity could be weakened. This work presents a data-driven approach for investigating metal adsorption behavior and elucidating the influencing mechanisms from macroscopic to microcosmic scale, thereby offering comprehensive guidance for predicting and managing the environmental behavior of heavy metals.

Arsenic release during groundwater recharge and effects of coexisting ions in a typical inland basin with high arsenic concentration: Modeling and batch experiment

Groundwater recharge is a viable solution to groundwater overexploitation. However, the injection of recharge water may break the dissolution balance and induce the release of trace elements especially arsenic (As), which has been identified in river deltas. Only a few studies have been conducted in inland basins with high As concentration, high pH, and low Eh. Aiming to analyze As release with groundwater recharge in inland high-As regions and determine the effects of coexisting ions in recharge water, this study established PHase Equilibria Calculation (PHREEQC) models using rainwater and groundwater data from three inland sedimentary basins with slow groundwater flow in semi-arid regions. The simulations fitted with the batch experiments, achieving an R-squared (R2) of 0.98. The coexisting ions in the recharge water significantly affected As release during recharge. Ca2+ inhibited the release of total arsenic (Total-As) by increasing the surface charge of iron oxides. NO3- inhibited Total-As release by promoting the conversion of trivalent As into pentavalent As. Conversely, HCO3- facilitated As release by competing with arsenate for adsorption sites. On the basis of the modeling and batch experiment results, Total-As release with groundwater recharge was predicted. The results indicated that the high Ca2+ concentration in the recharge water inhibited the As release by 83.5 %, which can be used as a strategy to control As release during groundwater recharge in high-As inland basins.

Quantitative expression of LNAPL pollutant concentrations in capillary zone by coupling multiple environmental factors based on random forest algorithm

The capillary zone plays a crucial role in migration and transformation of pollutants. Light nonaqueous liquids (LNAPLs) have become the main organic pollutant in soil and groundwater environments. However, few studies have focused on the concentration distribution characteristics and quantitative expression of LNAPL pollutants within capillary zone. In this study, we conducted a sandbox-migration experiment using diesel oil as a typical LNAPL pollutant, with the capillary zone of silty sand as the research object. The variation characteristics of LNAPL pollutants (total petroleum hydrocarbon) concentration and environmental factors (moisture content, electrical conductivity, pH, and oxidationreduction potential) were essentially consistent at different locations with the same height. These characteristics differed within range of 10.0-50.0 cm and above 60.0 cm from groundwater. A model for quantitative expression of concentrations was constructed by coupling multiple environmental factors of 968 sets-7744 data via random forest algorithm. The goodness of fit (R2) for both training and test sets was greater than 0.90, and the mean absolute percentage error (MAPE) was less than 16.00 %. The absolute values of relative errors in predicting concentrations at characteristic points were less than 15.00 %. The constructed model can accurately and quantitatively express and predict concentrations in capillary zone.

Fast On-Site Speciation and High Spatial Resolution Imaging of Labile Arsenic in Freshwater and Sediment Using the DGT-SERS Sensor

Diffusive gradients in thin films (DGT) technique is renowned for in situ passive sampling but not for rapid on-site analysis, whereas surface-enhanced Raman spectroscopy (SERS) excels in ultrasensitive on-site detection but is limited by substrate contamination from complex matrices. Here, a hierarchical nanostructure of silver (Ag) mirror-supported large Ag nanoparticles (∼120 nm) was grown in situ in polyacrylamide hydrogel with a restricted pore size (PAM/Ag mirror/AgNPs) to serve as both the DGT binding phase and the SERS substrate. The substrate exhibited a maximum electric field enhancement factor of 9.9 × 108 and a signal relative standard error of 4.8%. Using the DGT-SERS sensor, As(III) and As(V) in freshwater were simultaneously detected at limits of 0.9 and 0.8 μg L-1, respectively, applicable across a wide range of environmental conditions. The DGT-SERS effectively mitigated the interfacial reduction of As(V) caused by humic acid by excluding it from plasmonic hotspots through size exclusion of the diffusive layer. The Raman analysis of a DGT sample in the field requires only 2 s using a portable spectrometer without DGT device disassembly. More importantly, the DGT-SERS captured the first two-dimensional image of As(III) and As(V) in one DGT at the micron scale resolution, revealing their spatially supplementary distribution patterns at the sediment-water interface. This study paves the way for next-generation speciation imaging DGT and the application of SERS in complex environments.

Sustainable chloramine-functionalized iron hydroxide nanofiber membrane for arsenic(Ⅲ) removal via oxidation-adsorption mechanism

Arsenic-contaminated groundwater is an intractable environmental problem worldwide, particularly As(III), which is not only highly toxic but also resistant to removal. In this study, sustainable chloramine-functionalized iron hydroxide cellulose nanofibrous membrane (Fe-CNFM-Cl) was prepared by electrostatic spinning followed by chemical grafting for As(III) decontamination. In situ engineered iron hydroxides were uniformly dispersed in cellulose nanofibers for As adsorption. The oxidative chlorine (+1) in the grafted chloramine could oxidize As(III) to readily removable As(V). Benefiting from oxidation-enhanced adsorption, Fe-CNFM-Cl was able to remove As(III) reliably. Using Fe-CNFM-Cl, As(III) levels were purified from 1418.73 μg L-1 to meet drinking water standards within 300 min. Additionally, Fe-CNFM-Cl exhibited high iron utilization with a normalized As adsorption capacity of 214.55 ± 15.52 mg g-iron-1. Fe-CNFM-Cl performed effectively over a broad pH range of 3-9. Common anions and humic acid hardly inhibit As(III) removal except at high concentrations of phosphate. During the removal of As(III), a portion of As(III) was oxidized to As(V) by activated chlorine. The adsorption and oxidation capacity of the used Fe-CNFM-Cl could be well recovered by desorption with NaOH solution followed by chlorination with NaClO solution. In addition, it could reliably purify the As(III) levels in natural groundwater to below 10 μg L-1. The study contributes a novel strategy for the development of multifunctional iron-based cellulose biocomposite sorbents for the effective removal of As(III) from water.

Prolonged exposure to NaAsO2 induces thyroid dysfunction and inflammatory injury in Sprague‒Dawley rats, involvement of NLRP3 inflammasome‒mediated pyroptosis

Arsenic, a well-known hazardous toxicant, has been found in recent years to act as an environmental endocrine disruptor that accumulates in various endocrine organs, impeding the normal physiological functions of these organs and altering hormone secretion levels. Moreover, some research has demonstrated a correlation between arsenic exposure and thyroid functions, suggesting that arsenic has a toxicological effect on the thyroid gland. However, the specific type of thyroid gland damage caused by arsenic exposure and its potential molecular mechanism remain poorly understood. In this study, the toxic effects of sodium arsenite (NaAsO2) exposure at different doses (0, 2.5, 5.0 and 10.0 mg/kg bw) and over different durations (12, 24 and 36 weeks) on thyroid tissue and thyroid hormone levels in Sprague‒Dawley (SD) rats were investigated, and the specific mechanisms underlying the effects were also explored. Our results showed that NaAsO2 exposure can cause accumulation of this element in the thyroid tissue of rats. More importantly, chronic exposure to NaAsO2 significantly upregulated the expression of NLRP3 inflammasome-related proteins in thyroid tissue, leading to pyroptosis of thyroid cells and subsequent development of thyroid dysfunction, inflammatory injury, epithelial-mesenchymal transition (EMT), and even fibrotic changes in the thyroid glands of SD rats. These findings increase our understanding of the toxic effects of arsenic exposure on the thyroid gland and its functions.

Time-varying contributions of FeII and FeIII to AsV immobilization under anoxic/oxic conditions: The impacts of biochar and dissolved organic carbon

Engineering black carbon (e.g. biochar) has been widely found in natural environments due to natural processes and extensive applications in engineering systems, and could influence the geochemical processes of coexisting arsenic (AsV) and FeII, especially when they are exposed to oxic conditions. Here, we studied time-varying kinetics and efficiencies of AsV immobilization by solid-phase FeII (FeIIsolid) and FeIII (FeIIIsolid) in FeII-AsV-biochar systems under both anoxic and oxic conditions at pH 7.0, with focuses on the effects of biochar surface and biochar-derived dissolved organic carbon (DOC). Under anoxic conditions, FeII could rapidly immobilize AsV via co-adsorption onto biochar surfaces, which also serves as the dominant pathway of AsV immobilization at the initial stage of reaction (0-5 min) under oxic conditions at high biochar concentrations. Subsequently, with increasing biochar concentrations, FeIIIsolid precipitation from aqueous FeII (FeIIaq) oxidation (5-60 min) starts to play an important role in AsV immobilization but in decreased efficiencies of AsV immobilization per unit iron. In the following stage (60-300 min), FeIIsolid oxidation is suppressed and leads to AsV release into solutions at >1.0 g·L-1 biochar. The decreasing efficiency of AsV immobilization over time is attributed to the gradual release of DOC into solution from biochar particles, which significantly inhibit AsV immobilization when FeIIIsolid is generated from FeIIsolid oxidation in the vicinity of biochar surfaces. Specifically, 4.06 mg·L of biochar-derived DOC can completely inhibit the immobilization of AsV in the 100 μM FeII system under oxic conditions. The findings are crucial to comprehensively understand and predict the behavior of FeII and AsV with coexisting engineering black carbon in natural environments.

Roxarsone reduces earthworm-mediated nutrient cycling by suppressing aggregate formation and enzymic activity in soil with manure application

The application of manure and earthworms are frequently used in fertilization practices to improve C, N, and P cycling in soil, which may be adversely affected by roxarsone (ROX), as an organoarsenical pollutant. To effectively address this issue, in this work, the interactive impacts of ROX and earthworm Eisenia foetida on the aggregate formation, input of organic carbon (OC), and changes in the available N and P following 56-day cultivation were systematically investigated. Compared to the control, earthworms increased the mean weight diameter (MWD) of the soil aggregates from 0.6 to 1.1 mm. Thereby, they activated soil enzymes including catalase (CAT), sucrase (SC), urease (UE), and neutral phosphatase (NP), with the soil's pH decreased to 7.1. Consequently, the values of OC, soluble nitrite (NO3-N), and Olsen-P content were respectively increased by 0.78-, 1.69-, and 0.87- folds in the E treatment (14.3 vs. 25.5 g/kg, 12.8 vs. 33.3 mg/kg, and 7.8 vs. 14.6 mg/kg). Although the changes in the R treatment were slight, ROX reduced the earthworm-mediated improvements of soil fertility during the application of the RE treatment compared to the E treatment, i.e., the values of MWD, OC, NO3-N, and Olsen-P were reduced to 0.9 mm, 20.4 g/kg, 25.4 mg/kg, and 11.6 mg/kg, respectively. From the well-fitted structural equation models, it was demonstrated that earthworms enhanced the aggregate formation and nutrient cycling of OC, NO3-N, and Olsen-P, which were inhibited by ROX. Overall, these adverse effects can be offset by earthworm addition, which can play the dual role of monitor and driver for the soil properties. Our work provides insightful strategies for ROX-bearing manure management.

Advancing groundwater quality predictions: Machine learning challenges and solutions

Machine learning (ML) is revolutionizing groundwater quality research by enhancing predictive accuracy and management strategies for contamination. This comprehensive review explores the evolution of ML technologies and their integration into environmental science, assessing 230 papers to understand the advancements and challenges in groundwater quality research. It reveals that a substantial portion of the research neglects critical preprocessing steps, crucial for model accuracy, with 83 % of the studies overlooking this phase. Furthermore, while model optimization is more commonly addressed, being implemented in 65 % of the papers, there is a noticeable gap in model interpretability, with only 15 % of the research providing explanations for model outcomes. Comparative evaluation of ML algorithms and careful selection of evaluation metrics are deemed essential for determining model fitness and reliability. The review underscores the need for interdisciplinary collaboration, methodological rigor, and continuous innovation to advance ML in groundwater management. By addressing these challenges and implementing solutions, the full potential of ML can be harnessed to tackle complex environmental issues and ensure sustainable groundwater management. This comprehensive and critical review paper can serve as a guiding framework to establish minimum standards for developing ML in groundwater quality studies.

Neurotransmitter Metabolism in Arsenic Exposure-Induced Cognitive Impairment: Emerging Insights and Predictive Implications

Scholars have long been interested in the association between arsenic (As) exposure and neurological disorders; however, existing systematic epidemiological investigations are insufficient and lack the inclusion of diagnostic or predictive biological markers. This study sought to evaluate the association between As exposure and cognitive impairment and identify potential biomarkers by developing predictive models. Here, we found that logarithm (Ln)-transformed urinary As concentrations were negatively linearly related to the mini-mental state examination (MMSE) score exposure-response curves. Subsequently, we identified a unique plasma neurometabolite profile in subjects exposed to As compared with the reference group. Further analyses showed that tryptophan, tyrosine, dopamine, epinephrine, and homovanillic acid were all significantly associated with both urinary As concentrations and MMSE scores. Notably, the association between As exposure and MMSE scores was partly mediated by tryptophan, tyrosine, dopamine, and epinephrine. Importantly, an unprecedented prediction model utilizing neurotransmitters was established to assess the risk of cognitive impairment due to As exposure. A 91.1% consistency rate was found between the predicted and the actual probabilities. Additionally, machine learning models also produced highly accurate predictions. Overall, this study revealed a dose-dependent cognitive decline in As-exposed adults accompanied by a disturbance in the signature of neurotransmitter metabolites, offering new predictive insights.

Arsenic Stress Mitigation Using a Novel Plant Growth-Promoting Bacterial Strain Bacillus mycoides NR5 in Spinach Plant (Spinacia oleracea L.)

Present study aimed to identify arsenic (As)-resistant bacterial strains that can be used to mitigate arsenic stress. A bacterium Bacillus mycoides NR5 having As tolerance limit of 1100 mg L-1 was isolated from Nag River, Maharashtra, India. It was also equipped with plant growth-promoting (PGP) attributes like phosphate solubilization, siderophores, ammonia, and nitrate reduction, with added antibiotic tolerance. Furthermore, scanning electron microscopy (SEM) and transmission electron micrograph (TEM) suggested biosorption as possible mechanisms of arsenic tolerance. A strong peak in FTIR spectra at 3379.0 corresponding to amine in As-treated NR5 also indicated metal interaction with cell surface protein. Amplification of arsenic reductase gene in NR5 further suggested intracellular transformation of As speciation. Moreover, As tolerance capability of NR5 was shown in spinach plants in which the bacterium effectively mitigated 25 ppm As by producing defense-related proline molecules. Evidence from SEM, TEM, and FTIR, concluded biosorption possibly the primary mechanism of As tolerance in NR5 along with the transformation of arsenic. B. mycoides NR5 with PGP attributes, high As tolerance, and antibiotic resistance mediated enhanced As tolerance in spinach plants advocated that the strain can be a better choice for As bioremediation in contaminated agricultural soil and water.

Molecular and cell phenotype programs in oral epithelial cells directed by co-exposure to arsenic and smokeless tobacco

Chronic arsenic exposure can lead to various health issues, including cancer. Concerns have been mounting about the enhancement of arsenic toxicity through co-exposure to various prevalent lifestyle habits. Smokeless tobacco products are commonly consumed in South Asian countries, where their use frequently co-occurs with exposure to arsenic from contaminated groundwater. To decipher the in vitro molecular and cellular responses to arsenic and/or smokeless tobacco, we performed temporal multi-omics analysis of the transcriptome and DNA methylome remodelling in exposed hTERT-immortalized human normal oral keratinocytes (NOK), as well as arsenic and/or smokeless tobacco genotoxicity and mutagenicity investigations in NOK cells and in human p53 knock-in murine embryonic fibroblasts (Hupki MEF). RNAseq results from acute exposures to arsenic alone and in combination with smokeless tobacco extract revealed upregulation of genes with roles in cell cycle changes, apoptosis and inflammation responses. This was in keeping with global DNA hypomethylation affecting genes involved in the same processes in response to chronic treatment in NOK cells. At the phenotypic level, we observed a dose-dependent decrease in NOK cell viability, induction of DNA damage, cell cycle changes and increased apoptosis, with the most pronounced effects observed under arsenic and SLT co-exposure conditions. Live-cell imaging experiments indicated that the DNA damage likely resulted from induction of apoptosis, an observation validated by a lack of exome-wide mutagenesis in response to chronic exposure to arsenic and/or smokeless tobacco. In sum, our integrative omics study provides novel insights into the acute and chronic responses to arsenic and smokeless tobacco (co-)exposure, with both types of responses converging on several key mechanisms associated with cancer hallmark processes. The generated rich catalogue of molecular programs in oral cells regulated by arsenic and smokeless tobacco (co-)exposure may provide bases for future development of biomarkers for use in molecular epidemiology studies of exposed populations at risk of developing oral cancer.

Detoxification of ars genotypes by arsenite-oxidizing bacteria through arsenic biotransformation

The detoxification process of transforming arsenite (As(III)) to arsenate (As(V)) through bacterial oxidation presents a potent approach for bioremediation of arsenic-polluted soils in abandoned mines. In this study, twelve indigenous arsenic-oxidizing bacteria (AOB) were isolated from arsenic-contaminated soils. Among these, Paenibacillus xylanexedens EBC-SK As2 (MF928871) and Ochrobactrum anthropi EBC-SK As11 (MF928880) were identified as the most effective arsenic-oxidizing isolates. Evaluations for bacterial arsenic resistance demonstrated that P. xylanexedens EBC-SK As2 (MF928871) could resist As(III) up to 40 mM, while O. anthropi EBC-SK As11 (MF928880) could resist As(III) up to 25 mM. From these bacterial strains, genotypes of arsenic resistance system (ars) were detected, encompassing ars leader genes (arsR and arsD), membrane genes (arsB and arsJ), and aox genes known to be crucial for arsenic detoxification. These ars genotypes in the isolated AOBs might play an instrumental role in arsenic-contaminated soils with potential to reduce arsenic contamination.

Intestinal microbiota dysbiosis contributes to the liver damage in subchronic arsenic-exposed mice

There is an extensive amount of evidence that links changes in the intestinal microbiota structure to the progression and pathophysiology of many liver diseases. However, comprehensive analysis of gut flora dysbiosis in arsenic-induced hepatotoxicity is lacking. Herein, C57BL/6 mice are exposed to arsenic (1, 2, or 4 mg/kg) for 12 weeks, after which fecal microbiota transplantation (FMT) study is conducted to confirm the roles of the intestinal microbiome in pathology. Treatment with arsenic results in pathological and histological changes in the liver, such as inflammatory cell infiltration and decreased levels of TP and CHE but increased levels of ALP, GGT, TBA, AST, and ALT. Arsenic causes an increase in the relative abundance of Escherichia-Shigella, Klebsiella and Blautia, but a decrease in the relative abundance of Muribaculum and Lactobacillus. In arsenic-exposed mice, protein expressions of Occludin, ZO-1, and MUC2 are significantly decreased, but the level of FITC in serum is increased, and FITC fluorescence is extensively dispersed in the intestinal tract. Importantly, FMT experiments show that mice gavaged with stool from arsenic-treated mice exhibit severe inflammatory cell infiltration in liver tissues. Arsenic-manipulated gut microbiota transplantation markedly facilitates gut flora dysbiosis in the recipient mice, including an up-regulation in Escherichia-Shigella and Bacteroides, and a down-regulation in Lactobacillus and Desulfovibrio. In parallel with the intestinal microbiota wreck, protein expressions of Occludin, ZO-1, and MUC2 are decreased. Our findings suggest that subchronic exposure to arsenic can affect the homeostasis of the intestinal microbiota, induce intestinal barrier dysfunction, increase intestinal permeability, and cause damage to liver tissues in mice.

Study on the influence of active oxygen on the natural oxidation of arsenopyrite under different temperature conditions

Arsenic (As), a toxic element, contaminates farmlands, rivers, and groundwater, posing severe environmental and health risks. Notably, As-containing materials in tailings are affected by temperature variations during long-term storage, and this considerably impact the oxidation and migration of elements in arsenopyrite.This study focused on arsenopyrite and investigated the process of its oxidative dissolution and release of arsenic under different temperature conditions by using in-situ XRD, in-situ XPS and electron paramagnetic resonance spectroscopy(EPR), The role of oxygen free radicals in the oxidation of arsenopyrite was elucidated. It has been established that under high-temperature conditions As, iron (Fe), and sulfur (S) are primarily present As(V)/As(IV), Fe(III), and SO42-, respectively. The O2⋅- generated during the oxidation of As(III) by O2, OH⋅ produced by the Fe(II)/FeOH2+ reaction, and H2O2 formed via their interaction play a crucial role in the photochemical oxidation of arsenopyrite. These findings provide a theoretical basis for the formation of ferric arsenate precipitation, contributing in the adsorption and immobilisation of oxidatively released arsenic.

Assessing the impact of arsenite and arsenate on Sarcodia suae: a tale of two toxicities

Inorganic arsenic (iAs), which predominantly occurs as arsenite (As3+) and arsenate (As5+) in natural water, is primarily accumulated by seaweed in marine environments. However, the detailed mechanisms through which As3+ and As5+ affect the physiological processes of these organisms remain largely unknown. This study focused on evaluating the toxicological effects of As3+ and As5+ on the seaweed Sarcodia suae. Exposure to As3+ and As5+ resulted in IC50 values of 401.5 ± 9.4 μg L-1 and 975.8 ± 13 μg L-1, respectively. Morphological alterations and a reduction in phycoerythrin content were observed, particularly under As3+ exposure, with increased lipid peroxidation as evidenced by higher malondialdehyde levels. Exposure to As3+ also elevated the production of superoxide radicals, while decreasing hydrogen peroxide levels specifically in the presence of As3+. The induction of antioxidative enzyme activities, namely superoxide dismutase, catalase, glutathione reductase, and ascorbate peroxidase was observed, signaling an adaptive response to iAs-induced oxidative stress. Moreover, levels of the antioxidants ascorbate and glutathione were elevated post-exposure, especially in response to As3+. Additionally, bioaccumulation of arsenic was significantly higher in the As3+ compared to As5+. Collectively, the data suggest that As3+ imposes greater adverse effects and oxidative stress to S. suae, which responds by adjusting its antioxidative defense mechanisms to mitigate oxidative stress.

Enhancing and sustaining arsenic removal in a zerovalent iron-based magnetic flow-through water treatment system

In areas affected by arsenicosis, zerovalent iron (ZVI)/sand filters are extensively used by households to treat groundwater, but ZVI surface passivation and filter clogging limit their arsenic (As) removal performance. Here we present a magnetic confinement-enabled column reactor coupled with periodic ultrasonic depassivation (MCCR-PUD), which efficiently and sustainably removes As by reaction with continuously generated iron (oxyhydr)oxides from ZVI oxidative corrosion. In the MCCR, ZVI microparticles self-assemble into stable millimeter-scale wires in forest-like arrays in a parallel magnetic field (0.42-0.48 T, produced by two parallel permanent magnets), forming a highly porous structure (87 % porosity) with twice the accessible reactive surface area of a ZVI/sand mixture. For a feed concentration of 100 μg/L As(III), the MCCR-PUD, with a short empty bed contact time (1.6 min), treated ca. 7340 empty bed volume (EBV) of water at breakthrough (10 μg/L), 9.4 folds higher than that of a ZVI/sand filter. Due to the large interspace between ZVI wires, the MCCR-PUD effectively prevented column clogging that occurred in the ZVI/sand filter. The high water treatment capacity was attributed to the much enhanced ZVI reactivity in the magnetic field, sustained through rejuvenation by PUD. Furthermore, most of As was structurally incorporated into the produced iron (oxyhydr)oxides (mostly ferrihydrite) in the MCCR-PUD, as revealed by Mössbauer spectroscopy, X-ray absorption spectroscopy, and sequential extraction experiments. This finding evinced a different mechanism from the surface adsorption in the ZVI/sand filter. The structural incorporation of As also resulted in much less As remobilization from the produced corrosion products during aging in water, in total ∼1 % in 28 days. Furthermore, the MCCR-PUD exihibted robust performance when treating complex synthetic groundwater containing natural organic matter and common ions (∼3700 EBV at breakthrough). Taken together, our study demonstrates the potential of the magnetic confinement-enabled ZVI reactor as a promising decentralized As treatment platform.

Precipitation, temperature, and landcovers drive spatiotemporal variability of groundwater nitrate concentration across the Continental United States

Groundwater nitrate contamination, especially in agriculturally active regions, is a well-recognized environmental concern. Understanding how this contamination evolves across the continental USA (CONUS) and through time is important to designing effective mitigation strategies. Despite extensive research on nitrate contamination, no existing studies can accurately predict changes in groundwater nitrate concentrations over time across the CONUS. To bridge this gap, we compiled a comprehensive dataset for a systematic evaluation of the potential influence of climate dynamics, landcover changes, and crucial soil and geological properties on groundwater contamination. We employed an interpretable machine learning approach, using 293,775 groundwater nitrate observations and 12 independent variables, to estimate annual groundwater nitrate concentrations at the county level from 2001 to 2020. Our model is the first one capable of accurately forecasting temporal changes in groundwater nitrate concentration across the entire CONUS. Our analysis reveals county level groundwater nitrate concentration changes occurred over the past two decades, particularly in regions initially with high concentrations in 2001, ranging from -16.2 mg/L-N to +6.5 mg/L-N between 2001 and 2020. 27 counties in the country appeared to have new concentrations greater than or equal to the maximum concentration level (MCL) at least once during this period. We revealed direct relationships between groundwater nitrate concentrations and climate factors, including that temperature and precipitation dominate the interannual variability in groundwater nitrate concentration in 75.2 % of counties. Notably, we have established a clear correlation between groundwater nitrate concentration and precipitation. Specifically, when annual precipitation falls below a threshold of about 748 mm, an increase of precipitation can directly result in elevated nitrate concentrations in groundwater, indicating heightened vulnerability to contamination due to climate change. This study forms a pivotal foundation for forecasting groundwater nitrate concentration changes across the continent and assessing the potential impact of climate change on future groundwater nitrate concentrations.

Arsenic exposure and measures of glucose tolerance in Bangladeshi adults: A cross-sectional study

Background

Arsenic has been associated with diabetes and impaired glucose tolerance in many studies, although some reports have shown null findings.

Methods

We conducted a cross-sectional study among 300 adults in Bangladesh. Participants were randomly selected from a roster of 1800 people who previously participated in studies of arsenic and skin lesions. We measured fasting glucose and insulin levels. We assessed drinking water arsenic concentration using graphite furnace atomic absorption spectrophotometry (GF-AAS) and toenail arsenic concentration using inductively coupled mass spectrometry (ICP-MS). We ran covariant-adjusted, linear regression and spline models to examine associations of arsenic concentrations with the homeostatic model assessment of insulin resistance (HOMA-IR), a marker of insulin resistance, and HOMA of beta-cell function (HOMA-β), a marker of beta-cell function.

Results

Among 285 participants with complete data, the median (IQR) arsenic concentration was 4.0 (6.9) μg/g in toenails and 39.0 (188.5) μg/L in drinking water. Arsenic concentrations were not associated with insulin resistance or beta-cell function. HOMA-IR was 0.67% lower and HOMA-β was 0.28% lower per µg/g increment in toenail arsenic, but these effect estimates were small, and confidence intervals crossed the null value.

Conclusions

Although arsenic exposure has been associated with diabetes, we found no evidence of an adverse effect on insulin resistance or beta-cell function.

Response of Plant Endophyte Communities to Heavy Metal Stress and Plant Growth Promotion by the Endophyte Serratia marcescens (Strain JG1)

Effects of heavy metals on soil microbial communities have been extensively studied due to their persistence in the environment and imposed threats to living organisms; however, there is a lack of in-depth studies of the impacts of heavy metals on plant endophyte communities. Therefore, the responses of plant endophyte communities to different concentrations of heavy metals were investigated in this study. The endophyte communities of plants existing in severely (W1, Pb, 110.49 mg/kg, Cd, 1.11 mg/kg), moderately (W2, Pb, 55.06 mg/kg, Cd, 0.48 mg/kg), and mildly (W3, Pb, 39.06 mg/kg, Cd, 0.20 mg/kg) contaminated soils were analyzed by 16s rRNA high-throughput Illumina sequencing. Furthermore, networks were constructed to illustrate the relationships between microorganisms and environmental factors. High-quality sequences were clustered at a 97% similarity level. Results revealed that the diversity of the community and relative abundance of Cyanobacteria phylum increased with decreasing levels of pollution. Cyanobacteria and Proteobacteria were found to be the dominant phylum, while Methylobacterium and Sphingomonas were observed as the dominant genus. Tukey's HSD test showed that the relative abundances of Cyanobacteria and Proteobacteria phyla and Methylobacterium and Sphingomonas genera differed significantly (p < 0.01) among the plants of the three sample sites. Environmental factor analysis revealed a significant negative correlation (p < 0.01) of Cyanobacteria and a significant positive correlation (p < 0.01) of Methylobacterium with the heavy metal content in the environment. These findings suggest that Cyanobacteria and Methylobacterium may be phylum and genus indicators, respectively, of heavy metal toxicity. Tax4Fun analysis showed the effect of heavy metal toxicity on the abundance of genes involved in plant metabolism. In addition, culturable endophytic strains were isolated to study their resistance to heavy metal stress and their ability to promote plant growth. The potting tests showed that the JG1 strain was tolerant to heavy metals, and it could significantly promote the growth of the host plant under stress caused by multiple heavy metals. Compared to the control, the JG1-treated plants showed a 23.14% increase in height and a 12.84% increase in biomass. Moreover, AP, AK, and HN contents in JG1-treated plants were 20.87%, 12.55%, and 9.03% higher, respectively, under heavy metal stress. The results of this study provide a scientific basis for the construction of an efficient plant endophyte restoration system.

Evaluation of the lithium resource in the Smackover Formation brines of southern Arkansas using machine learning

Global demand for lithium, the primary component of lithium-ion batteries, greatly exceeds known supplies, and this imbalance is expected to increase as the world transitions away from fossil fuel energy sources. High concentrations of lithium in brines have been observed in the Smackover Formation in southern Arkansas (>400 milligrams per liter). We used published and newly collected brine lithium concentration data to train a random forest machine-learning model using geologic, geochemical, and temperature explanatory variables and create a map of predicted lithium concentrations in Smackover Formation brines across southern Arkansas. Using these predicted lithium maps with reservoir parameters and geologic information, we calculated that there are 5.1 to 19 million tons of lithium in Smackover Formation brines in southern Arkansas, which represents 35 to 136% of the current US lithium resource estimate. Based on these calculations, in 2022, 5000 tons of dissolved lithium were brought to the surface within brines as waste streams of the oil, gas, and bromine industries.

Arsenic exposure is associated with elevated sweat chloride concentration and airflow obstruction among adults in Bangladesh: a cross sectional study

Arsenic is associated with lung disease and experimental models suggest that arsenic-induced degradation of the chloride channel CFTR (cystic fibrosis transmembrane conductance regulator) is a mechanism of arsenic toxicity. We examined associations between arsenic exposure, sweat chloride concentration (measure of CFTR function), and pulmonary function among 285 adults in Bangladesh. Participants with sweat chloride ≥ 60 mmol/L had higher arsenic exposures than those with sweat chloride < 60 mmol/L (water: median 77.5 μg/L versus 34.0 μg/L, p = 0.025; toenails: median 4.8 μg/g versus 3.7 μg/g, p = 0.024). In linear regression models, a one-unit μg/g increment in toenail arsenic was associated with a 0.59 mmol/L higher sweat chloride concentration, p < 0.001. We found that toenail arsenic concentration was associated with increased odds of airway obstruction (OR: 1.97, 95%: 1.06, 3.67, p = 0.03); however, sweat chloride concentration did not mediate this association. Our findings suggest that sweat chloride concentration may be a novel biomarker for arsenic exposure and also that arsenic likely acts on the lung through mechanisms other than CFTR dysfunction.

Characteristics and Mechanism of Hematite Dissolution and Release on Arsenic Migration in Heterogeneous Materials

The migration of arsenic in groundwater is influenced by the heterogeneity of the medium, and the presence of iron minerals adds complexity and uncertainty to this effect. In this study, a stratified heterogeneous sand column with an embedded hematite lens at the coarse-to-medium sand interface was designed. We introduced an arsenic-laden solution and controlled groundwater flow to investigate the spatiotemporal characteristics of arsenic migration and the impact of hematite dissolution. The results showed that the medium structure significantly influenced the arsenic migration and distribution within the lens-containing sand column. The clay layers directed the lateral migration of arsenic, and the arsenic concentrations in deeper layers were up to seven times greater than those on the surface. The extraction experiments of solid-phase arsenic revealed that the main adsorption modes on quartz sand surfaces were the specific adsorption (F2) and adsorption on weakly crystalline iron-aluminum oxides (F3), correlating to the specific and colloidal adsorption modes, respectively. Monitoring the total iron ions (Fe(aq)) revealed rapid increases within the first 14 days, reaching a maximum on day 15, and then gradually declining; these results indicate that hematite did not continuously dissolve. This study can aid in the prevention and control of arsenic contamination in groundwater.

Critical assessment of recent advancements in chitosan-functionalized iron and geopolymer-based adsorbents for the selective removal of arsenic from water

Inorganic arsenic (As), a known carcinogen and major contaminant in drinking water, affects over 140 million people globally, with levels exceeding the World Health Organization's (WHO) guidelines of 10 μg L-1. Developing innovative technologies for effluent handling and decontaminating polluted water is critical. This paper summarizes the fundamental characteristics of chitosan-embedded composites for As adsorption from water. The primary challenge in selectively removing As ions is the presence of phosphate, which is chemically similar to As(V). This study evaluates and summarizes innovative As adsorbents based on chitosan and its composite modifications, focusing on factors influencing their adsorption affinity. The kinetics, isotherms, column models, and thermodynamic aspects of the sorption processes were also explored. Finally, the adsorption process and implications of functionalized chitosan for wastewater treatment were analyzed. There have been minimal developments in water disinfection using metal-biopolymer composites for environmental purposes. This field of study offers numerous research opportunities to expand the use of biopolymer composites as detoxifying materials and to gain deeper insights into the foundations of biopolymer composite adsorbents, which merit further investigation to enhance adsorbent stability.

Remediation of arsenic- and nitrate-contaminated groundwater through iron-dependent autotrophic denitrifying culture

Groundwater contamination with arsenic and nitrate poses a pressing concern for the safety of local communities. Bioremediation, utilizing Fe(II)-oxidizing nitrate reducing bacteria, shows promise as a solution to this problem. However, the relatively weak environmental adaptability of a single bacterium hampers practical application. Therefore, this study explored the feasibility and characteristics of a mixed iron-dependent autotrophic denitrifying (IDAD) culture for effectively removing arsenic and nitrate from synthetic groundwater. The IDAD biosystem exhibited stable performace and arsenic resistance, even at a high As(III) concentration of 800 μg/L. Although the nitrogen removal efficiency of the IDAD biosystem decreased from 71.4% to 64.7% in this case, the arsenic concentration in the effluent remained below the standard (10 μg/L) set by WHO. The crystallinity of the lepidocrocite produced by the IDAD culture decreased with increasing arsenic concentration, but the relative abundance of the key iron-oxidizing bacteria norank_f_Gallionellaceae in the culture showed an opposite trend. Metagenomic analysis revealed that the IDAD culture possess arsenic detoxification pathways, including redox, methylation, and efflux of arsenic, which enable it to mitigate the adverse impact of arsenic stress. This study provides theoretical understanding and technical support for the remediation of arsenic and nitrate-contaminated groundwater using the IDAD culture.

Biological arsenite oxidation on iron-based adsorbents in groundwater filters

Iron-based adsorbents are commonly used to remove arsenic (As) from water for drinking water purposes. Here, we study the role of biological As(III) oxidation on iron-based adsorbents in filters and its effect on overall As uptake. A lab-scale filter with iron oxide coated sand (IOCS), a commonly used adsorbent, was operated with water containing As(III) and As(V), while water samples were taken periodically over its height. As(III) oxidation initiated after approximately 10 days and increased to a first order rate constant of 0.09 s-1 after 57 days resulting in full oxidation of As(III) in <50 s. Consequently, the filter shifted from an As(III) to an As(V) adsorbing filter. Oxidation was not observed after inhibiting the microbial activity using sodium azide confirming its biogenic nature. This implies that As(III) oxidizing biomass can grow on iron-based adsorbents in water filters without requiring inoculation. As the experimental conditions were similar to full-scale As treatment plants, we believe that biological As(III) oxidation is widely overlooked in these systems. Occurrence of biological oxidation is, however, beneficial for removal, as at pH <8 the adsorption capacity for As(V) can be up to 10-fold higher than for As(III). With these new insights, arsenic treatment using iron-based adsorbents can be further optimized. We suggest a more robust new design with a biological active As(III) oxidizing top layer and an As(V) adsorbing bottom layer.

Characteristics and partitions of traditional and emerging organophosphate esters in soil and groundwater based on machine learning

Organophosphate esters (OPEs) pose hazards to both humans and the environment. This study applied target screening to analyze the concentrations and detection frequencies of OPEs in the soil and groundwater of representative contaminated sites in the Pearl River Delta. The clusters and correlation characteristics of OPEs in soil and groundwater were calculated by self-organizing map (SOM). The risk assessment and partitions of OPEs in industrial park soil and groundwater were conducted. The results revealed that 14 out of 23 types of OPEs were detected. The total concentrations (Σ23OPEs) ranged from 1.931 to 743.571 ng/L in the groundwater, and 0.218 to 79.578 ng/g in the soil, the former showed highly soluble OPEs with high detection frequencies and concentrations, whereas the latter exhibited the opposite trend. SOM analysis revealed that the distribution of OPEs in the soil differed significantly from that in the groundwater. In the industrial park, OPEs posed acceptable risks in both the soil and groundwater. The soil could be categorized into Zone I and II, and the groundwater into Zone I, II, and III, with corresponding management recommendations. Applying SOM to analyze the characteristics and partitions of OPEs may provide references for other new pollutants and contaminated sites.

Harnessing machine learning for assessing climate change influences on groundwater resources: A comprehensive review

Climate change is a major concern for a range of environmental issues including water resources especially groundwater. Recent studies have reported significant impact of various climatic factors such as change in temperature, precipitation, evapotranspiration, etc. on different groundwater variables. For this, a range of tools and techniques are widely used in the literature including advanced machine learning (ML) and artificial intelligence (AI) approaches. To the best of the authors' knowledge, this review is one of the novel studies that offers an in-depth exploration of ML/AI models for evaluating climate change impact on groundwater variables. The study primarily focuses on the efficacy of various ML/AI models in forecasting critical groundwater parameters such as levels, discharge, storage, and quality under various climatic pressures like temperature and precipitation that influence these variables. A total of 65 research papers were selected for review from the year 2017-2023, providing an up-to-date exploration of the advancements in ML/AI methods for assessing the impact of climate change on various groundwater variables. It should be noted that the ML/AI model performance depends on the data attributes like data types, geospatial resolution, temporal scale etc. Moreover, depending on the research aim and objectives of the different studies along with the data availability, various sets of historical/observation data have been used in the reviewed studies Therefore, the reviewed studies considered these attributes for evaluating different ML/AI models. The results of the study highlight the exceptional ability of neural networks, random forest (RF), decision tree (DT), support vector machines (SVM) to perform exceptionally accurate in predicting water resource changes and identifying key determinants of groundwater level fluctuations. Additionally, the review emphasizes on the enhanced accuracy achieved through hybrid and ensemble ML approaches. In terms of Irish context, the study reveals significant climate change risks posing threats to groundwater quantity and quality along with limited research conducted in this avenue. Therefore, the findings of this review can be helpful for understanding the interplay between climate change and groundwater variables along with the details of the various tools and techniques including ML/AI approaches for assessing the impacts of climate changes on groundwater.

Construction of an adverse outcome pathway framework for arsenic-induced lung cancer using a network-based approach

Environmental pollutants are considered as a cause of tumorigenesis, but approaches to assess their risk of causing tumors remain insufficient. As an alternative approach, the adverse outcome pathway (AOP) framework is used to assess the risk of tumors caused by environmental pollutants. Arsenic is a pollutant associated with lung cancer, but early assessment of lung cancer risk is lacking. Therefore, we applied the AOP framework to arsenic-induced lung cancer. A systematic review revealed increased risks of lung cancer following exposure to a range of arsenic concentrations in drinking water (OR = 1.83, 95 % CI = 1.46-2.30). We obtained, from public databases, genes related to risk of arsenic-induced lung cancer. Then, Cox and LASSO regressions were used to screen target genes from the risk genes. Subsequently, target genes, phenotypes, and pathways were used to construct the computational AOP network, which was determined by Cytoscape to have 156 edges and 45 nodes. Further, target genes, phenotypes, and pathways were used as molecular initiating events and key events to construct the AOP framework depending on upstream and downstream relationships. In the AOP framework, by Weight of Evidence, arsenic exposure increased levels of EGFR, activated the PI3K/AKT pathway, regulated cell proliferation by promoting the G1/S phase transition, and caused generation of lung cancers. External validation was achieved through arsenite-induced, malignant transformed human bronchial epithelial (HBE) cells. Overall, these results, by integration into existing data to construct an AOP framework, provide insights into the assessment of lung cancer risk for arsenic exposure. Special attention needs to be focused on populations with low-dose arsenic exposure.

N6-methyladenosine facilitates arsenic-induced neoplastic phenotypes of human bronchial epithelial cells by promoting miR-106b-5p maturation

Arsenic is a widespread carcinogen and an important etiological factor for lung cancer. Dysregulated miRNAs have been implicated in arsenic carcinogenesis and the mechanisms of arsenic-induced dysregulated miRNAs have not been fully elucidated. N6-methyladenosine (m6A) modification is known to modulate pri-miRNA processing. However, whether m6A-mediated pri-miRNA processing is involved in arsenic carcinogenesis is poorly understood. Here, we found that m6A modification was significantly increased in arsenite-transformed human bronchial epithelial BEAS-2B cells (0.5 µM arsenite, 16 weeks). Meanwhile, METTL3 was significantly upregulated at week 12 and 16 during cell transformation. The proliferation, migration, invasion, and anchorage-independent growth of arsenite-transformed cells were inhibited by the reduction of m6A levels through METTL3 knockdown. Further experiments suggest that the oncogene miR-106b-5p is a potentially essential m6A target mediating arsenic-induced lung cancer. miR-106b-5p was observed to be upregulated after exposure to arsenite for 12 and 16 weeks, and the reduction of m6A levels caused by METTL3 knockdown inhibited miR-106b-5p maturation in arsenite-transformed cells. What's more, miR-106b-5p overexpression successfully rescued METTL3 knockdown-induced inhibition of the neoplastic phenotypes of transformed cells. Additionally, Basonuclin 2 (BNC2) was uncovered as a potential target of miR-106b-5p and downregulated by METTL3 via enhancing miR-106b-5p maturation. Additionally, the METTL3 inhibitor STM2457 suppressed neoplastic phenotypes of arsenite-transformed BEAS-2B cells by blocking pri-miR-106b methylation. These results demonstrate that m6A modification promotes the neoplastic phenotypes of arsenite-transformed BEAS-2B cells through METTL3/miR-106b-5p/BNC2 pathway, providing a new prospective for understanding arsenic carcinogenesis.

Rapid Oxidative Dissolution of Zerovalent Iron Induced by Sulfite for Efficient Removal of Arsenate and Arsenite: Selective Formation of Scorodite

In this study, we proposed a moderate oxidation strategy for accelerating the oxidative dissolution of zerovalent iron (ZVI) using sulfite (S(IV)), thereby improving the removal of As(V) and As(III). Results revealed that, in the presence of 2.0 mM S(IV), both As(V) and As(III) were selectively converted into scorodite at pH0 3.0-7.0, while As(III) oxidation and As(V) immobilization were impressed over pH0 8.0-10.0. Batch experiments, radical quenching experiments, and electron spin resonance (ESR) measurements demonstrated that ZVI initially boosted S(IV) activation to generate SO4•-, •OH, and protons, and in turn, ZVI was further oxidized more intensely by these radicals than by oxygen. Concurrently, substantial protons derived from S(IV) oxidation neutralized hydroxyls produced by ZVI oxidation, maintaining an acidic environment conducive to the generation of scorodite rather than iron (hydr)oxides. Characterizations of X-ray diffraction (XRD), Raman, attenuated total reflectance-Fourier transform infrared (ATR-FTIR), X-ray photoelectron spectroscopy (XPS), X-ray absorption fine structure (XAFS), field emission scanning electron microscopy (FESEM), and high-resolution transmission electron microscopy (HRTEM) confirmed that scorodite was formed in situ and then exfoliated from the surface of ZVI, and approximately 75% of ZVI could still be recovered, which contributed to efficient As removal in successive runs and real As-polluted wastewater. The application of S(IV) achieved a balance among ZVI reactivity improvement, As(V)/As(III) removal, and raw material consumption, making it a promising approach for addressing arsenic contamination in wastewater treatment.

Electrochemically-assisted intensification of As(III) removal through integrated alkalization and oxidation process

In response to the need for trace arsenic removal and detoxification, an electro-assisted self-alkalization and oxidant-free processes (ESOP) cell was developed and investigated. It was found that the ESOP removed 90.3 % of arsenic and reduced the As(III) concentration from 150 µg L-1 to less than 5 µg L-1 in its cathode chamber. The As removal involved migration of As(III) and As(V) from the cathode to the anode driven by electrical current. In the ESOP cathode, As(III) was dissociated to As(III) oxyanions via alkalization and then oxidized into As(V) by H2O2. Nearly 80 % of As(III) migration could be attributed to the oxidation by H2O2 and approximately 20 % dissociation by pH alkalization. The voltage-controlled conditions (1.2 -1.5 V) achieved a peak cumulative H2O2 concentration of 10.9 mg L-1. The ESOP demonstrated a high As(III) oxidation to As(V) conversion efficiency of 97.0 % as well as a low energy cost of 0.013 kWh m-3 at 1.2 V. The migrated arsenic was stabilized onto the anode electrode through in-situ electro-oxidation of As(III) and electrosorption of As(III, V); this would help with the post-treatment waste disposal. Those results have provided important insights into an electrochemical approach for highly efficient arsenic detoxification.

Metagenomic and FT-ICR MS insights into the mechanism for the arsenic biogeochemical cycling in groundwater

Arsenic (As) is a groundwater contaminant of global concern. The degradation of dissolved organic matter (DOM) can provide a reducing environment for As release. However, the interaction of DOM with local microbial communities and how different sources and types of DOM influence the biotransformation of As in aquifers is uncertain. This study used optical spectroscopy, Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), metagenomics, and structural equation modeling (SEM) to demonstrate the how the biotransformation of As in aquifers is promoted. The results indicated that the DOM in high-As groundwater is dominated by highly unsaturated low-oxygen(O) compounds that are quite humic and stable. Metagenomics analysis indicated Acinetobacter, Pseudoxanthomonas, and Pseudomonas predominate in high-As environments; these genera all contain As detoxification genes and are members of the same phylum (Proteobacteria). SEM analyses indicated the presence of Proteobacteria is positively related to highly unsaturated low-O compounds in the groundwater and conditions that promote arsenite release. The results illustrate how the biogeochemical transformation of As in groundwater systems is affected by DOM from different sources and with different characteristics.

Evaluation of arsenic phytoremediation potential in Azolla filiculoides Lam. plants under low pH stress conditions

The Azolla filiculoides plants were challenged with different arsenic (As) concentration under low pH stress conditions. The growth rate and doubling time of the plants were severely affected by higher As treatments at pH 5.00 when compared with stress pH 4.75 treatments. Hence, pH 5.00 was considered for further studies. In 10-30 μM As treated cultures, after 6 days, the relative growth rate (RGR) of Azolla plants was significantly reduced and in higher concentration of As, the RGR was negatively regulated. The root trait parameters were also significantly affected by increasing concentrations of As. Further, photosynthetic performance indicators also show significant decline with increasing As stress. Overall, the plants treated with 40 and 50 μM of As displayed stress phenotypes like negative RGR, reduced doubling time and root growth, browning of leaves and root withering. The total proline, H2O2, POD and Catalase activities were significantly affected by As treatments. Meantime, 30 μM of As treated cultures displayed 15 μg/g/Fw As accumulation and moderate growth rate. Thus, the Azolla plants are suitable for the phytoremediation of As (up to 30 μM concentration) in the aquatic environment under low pH conditions (5.00). Furthermore, the transcriptome studies on revealed that the importance of positively regulated transporters like ACR3, AceTr family, ABC transporter super family in As (10 μM) stress tolerance, uptake and accumulation. The transporters like CPA1, sugar transporters, PiT were highly down-regulated. Further, expression analysis showed that the MATE1, CIP31, HAC1 and ACR3 were highly altered during the As stress conditions.

Optimizing cropland use to reduce groundwater arsenic hazards in a naturally arsenic-enriched grain-producing region

In the Hetao Basin, a grain-producing region plagued by naturally occurring arsenic (As) pollution, understanding the role of agricultural cultivation activities in mobilizing As in groundwater is worthwhile. Here we investigated the impact of cropland use characteristics on groundwater As hazards using a model that combines Random Forest (RF) classification with SHapley Additive exPlanation (SHAP). The analysis incorporated eight cropland use characteristics and three natural factors across 1258 groundwater samples as independent variables. Additionally, an optimized cropland use strategy to mitigate groundwater As hazards was proposed. The results revealed that crop cultivation area, especially within a 2500m-radius buffer around sampling points, most significantly influenced the probability of groundwater As concentrations exceeding an irrigation safety threshold of 50 μg/L, achieving an AUC of 0.86 for this prediction. The relative importance of crop areas on As hazards were as follows: sunflower > melon > wheat > maize. Specifically, a high proportion of sunflower area (>30%), particularly in regions with longer cropland irrigation history, tended to elevate groundwater As hazards. Conversely, its negative driving force on groundwater As hazards was more pronounced with the increase in the proportion of wheat area (>5%), in contrast to other crops. Transitioning from sunflower to wheat or melon cultivation in the northeast of the Hetao Basin may contribute to lower groundwater As hazards. This study provides a scientific foundation for balancing food production with environmental safety and public health considerations.

Effects of the combined regulation of nitrogen, phosphorus, and potassium nutrients on the migration and transformation of arsenic species in paddy soil

Nitrogen (N), phosphorus (P) and potassium (K) are three macroelements in agriculture production, but their combined effects on arsenic (As) toxicity and its translocation in rice plants are not clear. In this study, an orthogonal rotation combination based on different N, P and K (NPK) concentration was first designed to examine their combined effect on the As toxicity, its transformation and migration in rice plants based on the hydroponic culture and pot soil culture. The results showed that 2.0 mg/L arsenite (As(III)) had obvious toxicity on the growth of indica LuYouMingZhan (LYMZ) and the optimal NPK concentration was 28.41, 6 and 50 mg/L based on the quadratic regression of the recovery rate of chlorophyll SPAD value of indica LYMZ. The optimal NPK combination significantly alleviated the physiological toxicity of As(III) on indica LYMZ rice seedling and decreased the accumulation of inorganic As in their roots and shoots by 23.8±1.8 % and 33.4±2.4 % respectively; further pot culture from different As(III) polluted soil showed that the optimal NPK combination significantly increased the dry weight of roots, stems, sheaths and leaves of indica LYMZ rice plants as well as yield indicators by 6.4 %-61.7 % and 7.1 %-89.8 % respectively, decreased the accumulation of As(III) and arsenate by 6.25 %-100 % and 12.36 %-100 % respectively in their roots, stems, sheaths, leaves, brans and kernels except As(III) concentration in their sheaths, decreased the accumulation of dimethylarsenate in their sheaths, leaves, brans and kernels, and had the best repair effect on the translocation of As species in 50 mg/kg As(III)-added soil. Our study provided a desirable strategy for alleviating As toxicity in paddy soil and reducing As pollution in rice plants.