Elucidating the Differences in Metal Toxicity by Quantitative Adverse Outcome Pathways

Numerous studies have reported that the toxicity differences among metals are widespread; however, little is known about the mechanism of differences in metal toxicity to aquatic organisms due to the lack of quantitative understanding of their adverse outcome pathway. Here, we investigated the effects of Cd and Cu on bioaccumulation, gene expression, physiological responses, and apical effects in zebrafish larvae. RNA sequencing was conducted to provide supplementary mechanistic information for the effects of Cd and Cu exposure. On this basis, we proposed a quantitative adverse outcome pathway (qAOP) suitable for metal risk assessment of aquatic organisms. Our work provides a mechanistic explanation for the differences in metal toxicity where the strong bioaccumulation of Cu enables the newly accumulated Cu to reach the threshold that causes different adverse effects faster than Cd in zebrafish larvae, resulting in a higher toxicity of Cu than that of Cd. Furthermore, we proposed a parameter C_IT/BCF (the ratio of internal threshold concentration and bioaccumulation factor) that helps to understand the toxicity differences by combining the information of bioaccumulation and internal threshold of adverse effects. This work demonstrated that qAOP is an effective quantitative tool for understanding the toxicity mechanism and highlight the importance of toxicokinetics and toxicodynamics at different biological levels in determining the metal toxicity.

Trace elements in public drinking water in Chinese cities: Insights from their health risks and mineral nutrition assessments

The trace elements in the public drinking water have a duality: on the one hand, trace elements play an important role in maintaining human metabolism; on the other hand, high trace elements levels lead to significant health risks. To determine the impacts of trace elements in the public drinking water on physical health in China, water samples were collected from 314 Chinese cities to analyze the concentrations and spatial distributions of trace elements on a national scale. On this basis, the non-carcinogenic health risk assessments and the nutrient-based scores of trace elements (NSTEs) were applied to evaluate the public drinking water quality in terms of safety and nutrition. Most of the water samples were weakly alkaline: pH values fell in the range of 6.62-8.54, with a mean of 7.80. The results indicated that Sr and F^- had the highest concentrations in public drinking water, with averages of 0.3604 mg/L and 0.2351 mg/L, respectively. Moreover, hazard index (HI) values in different regions followed the order: northwest China (NWC) > northern China (NC) > Qinghai-Tibetan Plateau (QT) > southern China (SC). The percentages of water samples with HI > 1 in SC, NC, NWC, and QT were 5.49%, 16.82%, 25.81%, and 16.67%, respectively, indicating that the public drinking water in some cities had significant non-carcinogenic health risks. In addition, the intakes of Mn, Fe, Cu, and Rb through public drinking water made negligible contributions to their recommended nutrient intakes. In contrast, trace elements like Sr, F, B, Li, Mo, etc., contributed a lot. The NSTEs in NWC and most parts of NC were relatively high with averages of 8.0300 and 11.2082, respectively; however, the NSTEs in SC and the northeast part of NC were low with averages of 3.3284 and 5.2106, respectively. The results from this study provide a reference for establishing the public drinking water standards and improving drinking water quality.

Monitoring and prediction of high fluoride concentrations in groundwater in Pakistan

Concentrations of naturally occurring fluoride in groundwater exceeding the WHO guideline of 1.5 mg/L have been detected in many parts of Pakistan. This may lead to dental or skeletal fluorosis and thereby poses a potential threat to public health. Utilizing a total of 5483 fluoride concentrations, comprising 2160 new measurements as well as those from other sources, we have applied machine learning techniques to predict the probability of fluoride in groundwater in Pakistan exceeding 1.5 mg/L at a 250 m spatial resolution. Climate, soil, lithology, topography, and land cover parameters were identified as effective predictors of high fluoride concentrations in groundwater. Excellent model performance was observed in a random forest model that achieved an Area Under the Curve (AUC) of 0.92 on test data that were not used in modeling. The highest probabilities of high fluoride concentrations in groundwater are predicted in the Thar Desert, Sargodha Division, and scattered along the Sulaiman Mountains. Applying the model predictions to the population density and accounting for groundwater usage in both rural and urban areas, we estimate that about 13 million people may be at risk of fluorosis due to consuming groundwater with fluoride concentrations >1.5 mg/L in Pakistan, which corresponds to ~6% of the total population. Both the fluoride prediction map and the health risk map can be used as important decision-making tools for authorities and water resource managers in the identification and mitigation of groundwater fluoride contamination.

Regional Scale Assessment of Shallow Groundwater Vulnerability to Contamination from Unconventional Hydrocarbon Extraction

Concerns over unconventional oil and gas (UOG) development persist, especially in rural communities that rely on shallow groundwater for drinking and other domestic purposes. Given the continued expansion of the industry, regional (vs local scale) models are needed to characterize groundwater contamination risks faced by the increasing proportion of the population residing in areas that accommodate UOG extraction. In this paper, we evaluate groundwater vulnerability to contamination from surface spills and shallow subsurface leakage of UOG wells within a 104,000 km2 region in the Appalachian Basin, northeastern USA. We test a computationally efficient ensemble approach for simulating groundwater flow and contaminant transport processes to quantify vulnerability with high resolution. We also examine metamodels, or machine learning models trained to emulate physically based models, and investigate their spatial transferability. We identify predictors describing proximity to UOG, hydrology, and topography that are important for metamodels to make accurate vulnerability predictions outside their training regions. Using our approach, we estimate that 21,000-30,000 individuals in our study area are dependent on domestic water wells that are vulnerable to contamination from UOG activities. Our novel modeling framework could be used to guide groundwater monitoring, provide information for public health studies, and assess environmental justice issues.

The catalytic aerial oxidation of As(III) in alkaline solution by Mn-loaded diatomite

The oxidization of As(III) to As(V) is necessary for both the detoxification of arsenic and the removal of arsenic by solidification. In order to achieve high efficiency and low cost As(III) oxidation, a novel process of catalytic aerial oxidation of As(III) is proposed, using air as oxidant and Mn-loaded diatomite as a catalyst. Through systematic characterization of the reaction products, the catalytic oxidation reaction law of Mn-loaded diatomite for As(III) was found out, and its reaction mechanism was revealed. Results show that Mn-loaded diatomite achieved a good catalytic effect for aerial oxidation of As(III) and maintained high performance over multiple cycles of reuse, which was directly related to the structure of diatomite and the behavior of manganese. Under the conditions of a catalyst concentration of 20 g/L, an air flow rate of 0.3 m³/h, a reaction temperature of 50 °C and an initial pH of 12.6, 96.04% As(III) oxidation was achieved after 3 h. Furthermore, the efficiency of As(III) oxidation did not change significantly after ten cycles of reuse. XPS analysis of the reaction products confirmed that the surface of the catalyst was rich in Mn(III), Mn(IV) and adsorbed oxygen(O-H), which was the fundamental reason for the excellent performance of Mn-loaded diatomite in the catalytic oxidation of As(III).

Partitioning and (im)mobilization of arsenic associated with iron in arsenic-bearing deep subsoil profiles from Hong Kong

Understanding the arsenic (As) enrichment mechanisms in the subsurface environment relies on a systematic investigation of As valence species and their partitioning with the Fe (oxyhydr)oxide phases in the subsoil profile. The present study explored the distribution, speciation, partitioning, and (im)mobilization of As associated with Fe in four subsoil cores (∼30 m depth) from Hong Kong using sequential chemical extraction and X-ray absorption near edge spectroscopy. The subsoil profiles exhibited relatively high concentrations of As at 26.1-982 mg/kg (median of 112 mg/kg), and the As was dominated by As(V) (85-96%) and primarily associated with the residual fraction (50.7-94.7%). A small amount of As (0.002-13.2 mg/kg) was easily mobilized from the four subsoil profiles, and a concentration of water-soluble As higher than 100 μg/L was observed for only some subsoil layers. The molar ratios of As:Fe in the oxalate-extractable Fe fraction ranged from 1.2 to 76.5 mmol/mol (median of 11.1 mmol/mol), revealing the participation of poorly crystalline Fe (oxyhydr)oxides in immobilizing most of the high geogenic As. The primary phases of ferric (oxyhydr)oxides were characterized as ferrihydrite (16-53%), lepidocrocite (0-32%), and goethite (0-62%), and these phases contributed to the sufficient ability of the subsoil to sequester 45.3-100% (median of 98.8%) of the exogenous As(V) (1.0 mg/L) in adsorption experiments. In contrast to As(V), exogenous As(III) showed a lower removal percentage (3.9-79.1%, median of 45.1%). The study revealed that the chemical speciation of As and Fe in the subsoil profiles is useful for predicting the immobilization of high geogenic As in the region, which is also helpful for the safe utilization of As-containing soil during land development worldwide.

Species transformation and removal mechanism of various iodine species at the Bi2O3@MnO2 interface

Long-term exposure to excessive iodine via drinking water significantly increases the risk of thyroid diseases. Further, the mechanisms and feasible technologies for iodine removal are far from being well elucidated. In this study, we constructed a heterogeneous Bi₂O₃@MnO₂ interface with oxidation and adsorption efficiency toward iodide (I^-), and investigated the performance and mechanisms involved in iodine removal. Bi₂O₃@MnO₂ at the optimized Bi/Mn ratio of 0.05:1 had a maximum adsorption capacity of 1.19, 1.21, and 1.06 mg/g toward I^-, iodine elemental (I₂), and iodate (IO₃^-), respectively. According to the density functional theory (DFT) calculation, Bi₂O₃@MnO₂ had an adsorption energy of -2.34, -2.11, and -3.89 eV for I^-, I₂, and IO₃^-, and exhibited a better band structure and state density character for iodine removal. Based on the results of XPS, HPLC, and LC-ICP-MS characterization, Bi₂O₃ plays an important role in adsorbing and capturing I^- whereas MnO₂ dominates the moderate oxidation of I^- and the adsorption of I^- and I₂. The adsorbed I^- and I₂ concentrations on the Bi₂O₃@MnO₂ surfaces were 146.3 μg/L and 18.3 μg/L. Notably, IO₃^- was not detected owing to its moderate oxidation effect. The coexisting ions of chloride (Cl^-) and bromide (Br^-) tended to occupy the Bi₂O₃ lattice and form insoluble BiOCl and BiOBr. Further, reductive species, such as sulphite (SO₃^2-), may reduce MnO₂ to Mn(III) and Mn(II). The synergistic effect between moderate oxidation and adsorption led to Bi₂O₃@MnO₂ with high iodine removal capability. Overall, this study proposes a strategy for designing suitable interfaces and adsorbents for iodine removal; however, further studies are necessary to advance its application in practice.

Nrf2/Keap1 pathway in countering arsenic-induced oxidative stress in mice after chronic exposure at environmentally-relevant concentrations

Contamination of drinking water by carcinogen arsenic (As) is of worldwide concern as its exposure poses potential threat to human health. As such, it is important to understand the mechanisms associated with As-induced toxicity to humans. The Nrf2/Keap1 signal pathway is one of the most important defense mechanisms in cells to counter oxidative stress; however, limited information is available regarding its role in countering As-induced stress in model animal mouse. In this study, we assessed the responses of Nrf2/keap1 pathway in mice after chronic exposure to As at environmentally-relevant concentrations of 10-200 μg L^-1 for 30 days via drinking water. Our results indicate that chronic As exposure had limited effect on mouse growth. However, As induced oxidative stress to mice as indicated by increased content of malondialdehyde (MDA; 52-90%), an index of lipid peroxidation. Further, arsenic exposure reduced the activity of superoxide dismutase (SOD; 14-18%), an indication of reduced anti-oxidative activity. Besides, arsenic exposure increased MnSOD mRNA transcription by 25-66%, and decreased the mRNA transcriptions of Cu/ZnSOD by 72-83% and metallothionein by 16-75%, a cysteine-rich protein involved in metal detoxification. To counter arsenic toxicity, the expression of transcription factor for Nrf2 and Keap1 was increased by 2.8-8.9 and 0.2-8.1 fold in mice. To effectively reduce As-induced oxidative stress, the Nrf2/Keap1 transcription factor upregulated several downstream anti-oxidative genes, including heme oxygenase-1 (0.9-2.5 fold), glutamate-cysteine ligase catalytic subunit (0.6-1.7 fold), and NADH quinone dehydrogenase 1 (2.1-4.8 fold). This study shows the importance of Nrf2/Keap1 signaling pathway and associated anti-oxidative enzymes in countering As-toxicity in mice, possibly having implication for human health.

Groundwater-native Fe(II) oxidation prior to aeration with H2O2 to enhance As(III) removal

Groundwater contaminated with arsenic (As) must be treated prior to drinking, as human exposure to As at toxic levels can cause various diseases including cancer. Conventional aeration-filtration applied to anaerobic arsenite (As(III)) contaminated groundwater can remove As(III) by co-oxidizing native iron (Fe(II)) and As(III) with oxygen (O₂). However, the As(III) removal efficiency of conventional aeration can be low, in part, because of incomplete As(III) oxidation to readily-sorbed arsenate (As(V)). In this work, we investigated a new approach to enhance As(III) co-removal with native Fe(II) by the anaerobic addition of hydrogen peroxide (H₂O₂) prior to aeration. Experiments were performed to co-oxidize Fe(II) and As(III) with H₂O₂ (anaerobically), O₂ (aerobically), and by sequentially adding of H₂O₂ and O₂. Aqueous As(III) and As(V) measurements after the reaction were coupled with solid-phase speciation by Fe and As K-edge X-ray absorption spectroscopy (XAS). We found that complete anaerobic oxidation of 100 µM Fe(II) with 100 µM H₂O₂ resulted in co-removal of 95% of 7 µM As(III) compared to 44% with 8.0-9.0 mg/L dissolved O₂. Furthermore, we found that with 100 µM Fe(II), the initial Fe(II):H₂O₂ ratio was a critical parameter to remove 7 µM As(III) to below the 10 µg/L (0.13 µM) WHO guideline, where ratios of 1:4 (mol:mol) Fe(II):H₂O₂ led to As(III) removal matching that of 7 µM As(V). The improved As(III) removal with H₂O₂ was found to occur partly because of the well-established enhanced efficiency of As(III) oxidation in Fe(II)+H₂O₂ systems relatively to Fe(II)+O₂ systems. However, the XAS results unambiguously demonstrated that a large factor in the improved As(III) removal was also due to a systematic decrease in crystallinity, and thus increase in specific surface area, of the generated Fe(III) (oxyhydr)oxides from lepidocrocite in the Fe(II)+O₂ system to poorly-ordered Fe(III) precipitates in the Fe(II)+H₂O₂ system. The combined roles of H₂O₂ (enhanced As(III) oxidation and structural modification) can be easily overlooked when only aqueous species are measured, but this dual impact must be considered for accurate predictions of As removal in groundwater treatment.

Photocatalysis for arsenic removal from water: considerations for solar photocatalytic reactors

The following work provides a perspective on the potential application of solar heterogeneous photocatalysis, which is a nonselective advanced oxidation process considered as a sustainable technology, to assist in arsenic removal from water, which is a global threat to human health. Heterogeneous photocatalysis can oxidize trivalent arsenic to pentavalent arsenic, decreasing its toxicity and easing its removal with other technologies, such as chemical precipitation and adsorption. Several lab-scale arsenic photocatalytic oxidation and diverse solar heterogeneous photocatalytic operations carried out in different reactor designs are analyzed. It was found out that this technology has not been translated to operational pilot plant scale prototypes. General research on reactors is scarce, comprising a small percentage of the photocatalysis related scientific literature. It was possible to elucidate some operational parameters that a reactor must comply to operate efficiently. Reports on small-scale application shed light that in areas where other water purification technologies are economically and/or technically not suitable, and the solar energy is available, shed light on the fact that solar heterogeneous photocatalysis is highly promissory within a water purification process for removal of arsenic from water.

Photooxidation of Fe(II) to schwertmannite promotes As(III) oxidation and immobilization on pyrite under acidic conditions

Pollution of arsenic (As) in acid mine drainage (AMD) is a universal environmental problem. The weathering of pyrite (FeS₂) and other sulfide minerals leads to the generation of AMD and accelerates the leaching of As from sulfide minerals. Pyrite can undergo adsorption and redox reactions with As, affecting the existing form and biotoxicity of As. However, the interaction process between As and pyrite in AMD under sunlight radiation remains unclear. Here, we found that the oxidation and immobilization of arsenite (As(III)) on pyrite can be obviously promoted by the reactive oxygen species (ROS) in sunlit AMD, particularly by OH. The reactions between hole-electron pairs and water/oxygen adsorbed on excited pyrite resulted in the production of H₂O₂, OH and O₂^-, and OH was also generated through the photo-Fenton reaction of Fe²⁺/FeOH²⁺. Weakly crystalline schwertmannite formed from the oxidation of Fe²⁺ ions by OH contributed much to the adsorption and immobilization of As. In the mixed system of pyrite (0.75 g L^-1), Fe²⁺ (56.08 mg L^-1) and As(III) (1.0 mg L^-1) at initial pH 3.0, the decrease ratio of dissolved total As concentration was 1.6% under dark conditions, while it significantly increased to 69.0% under sunlight radiation. The existence of oxygen or increase in initial pH from 2.0 to 4.0 accelerated As(III) oxidation and immobilization due to the oxidation of more Fe²⁺ and production of more ROS. The present work shows that sunlight significantly affects the transformation and migration of As in AMD, and provides new insights into the environmental behaviors of As.

Arsenic Oxidation and Removal from Water via Core-Shell MnO2@La(OH)3 Nanocomposite Adsorption

Arsenic (As(III)), more toxic and with less affinity than arsenate (As(V)), is hard to remove from the aqueous phase due to the lack of efficient adsorbents. In this study, a core-shell structured MnO₂@La(OH)₃ nanocomposite was synthesized via a facile two-step precipitation method. Its removal performance and mechanisms for As(V) and As(III) were investigated through batch adsorption experiments and a series of analysis methods including the transformation kinetics of arsenic species in As(III) removal, FTIR, XRD and XPS. Solution pH could significantly influence the removal efficiencies of arsenic. The adsorption process of As(V) occurred rapidly in the first 5 h and then gradually decreased, whereas the As(III) removal rate was relatively slower. The maximum adsorption capacities of As(V) and As(III) were up to 138.9 and 139.9 mg/g at pH 4.0, respectively. For As(V) removal, the inner-sphere complexes of lanthanum arsenate were formed through the ligand exchange reactions and coprecipitation. The oxidation of As(III) to the less toxic As(V) by δ-MnO₂ and subsequently the synergistic adsorption process by the lanthanum hydroxide on the MnO₂@La(OH)₃ nanocomposite to form lanthanum arsenate were the dominant mechanisms of As(III) removal. XPS analysis indicated that approximately 20.6% of Mn in the nanocomposite after As(III) removal were Mn(II). Furthermore, a small amount of Mn(II) and La(III) were released into solution during the process of As(III) removal. These results confirm its efficient performance in the arsenic-containing water treatment, such as As(III)-contaminated groundwater used for irrigation and As(V)-contaminated industrial wastewater.

Microbially mediated arsenic mobilization in the clay layer and underlying aquifer in the Hetao Basin, Inner Mongolia, China

The clay layer is a source to facilitate arsenic (As) enrichment in the aquifer. However, little is known about microbial processes in the clay layer and their roles in As mobilization in the underlying aquifer. In this study, high-throughput sequencing of full-length 16S rRNA gene and metagenomics were used to characterize the microbial composition and functional potential in a sediment borehole across the clay and sand layers in Hetao Basin, Inner Mongolia, China. Results showed the significant differences between the clay layer and underlying sand layer in the geochemistry, microbial composition and functional potential. Fermentation, Fe(III) reduction, As(V) reduction, sulfate reduction, thiosulfate disproportionation, reductive tricarboxylic acid and Wood-Ljungdahl pathway identified in sediments from the clay layer were positively correlated to the observed high levels of TOC, soluble ammonium, H₃PO₄-extractable As(III) and As(V) and HCl-extractable Fe(II). Although the microbial compositions of the clay and sand layers were different, the microbial functional potential at the interface between the clay and sand layers was similar with the characteristics of fermentation, ammonification and As(V) reduction. The similarity of microbial functional potential at the interface may be attributable to the interaction between the sand and adjacent clay layer with the fluctuation of groundwater level. These metabolic products from the microbial processes in the clay layers and interface would migrate into the underlying groundwater during groundwater overpumping, which facilitates As enrichment in groundwater.

Embryonic Arsenic Exposure Triggers Long-Term Behavioral Impairment with Metabolite Alterations in Zebrafish

Arsenic trioxide (As2O3) is a ubiquitous heavy metal in the environment. Exposure to this toxin at low concentrations is unremarkable in developing organisms. Nevertheless, understanding the underlying mechanism of its long-term adverse effects remains a challenge. In this study, embryos were initially exposed to As2O3 from gastrulation to hatching under semi-static conditions. Results showed dose-dependent increased mortality, with exposure to 30-40 µM As2O3 significantly reducing tail-coiling and heart rate at early larval stages. Surviving larvae after 30 µM As2O3 exposure showed deficits in motor behavior without impairment of anxiety-like responses at 6 dpf and a slight impairment in color preference behavior at 11 dpf, which was later evident in adulthood. As2O3 also altered locomotor function, with a loss of directional and color preference in adult zebrafish, which correlated with changes in transcriptional regulation of adsl, shank3a, and tsc1b genes. During these processes, As2O3 mainly induced metabolic changes in lipids, particularly arachidonic acid, docosahexaenoic acid, prostaglandin, and sphinganine-1-phosphate in the post-hatching period of zebrafish. Overall, this study provides new insight into the potential mechanism of arsenic toxicity leading to long-term learning impairment in zebrafish and may benefit future risk assessments of other environmental toxins of concern.

Effects of geochemical and hydrodynamic transiency on desorption and transport of As in heterogeneous systems

Spatial and temporal variations in groundwater As concentrations are mainly caused by changes in geochemical and hydrodynamic conditions. In this study, the effects of geochemical and hydrodynamic transiency on As desorption and transport in a layered heterogeneous system with preferential flow paths during continuous or intermittent water extraction were investigated. A flume desorption experiment was performed after an adsorption experiment lasting 99 d with competitive adsorption anions (phosphate) in the influent. The results indicated that although competitive adsorption between As and phosphate at the water/solid interface significantly promoted As desorption from solid materials, marked amounts of As desorbed slowly or were on irreversible sorption sites in the system. As adsorbed by the sand and clay near the preferential flow paths was preferentially released, while the release of As from the interiors of the clay zones was limited by diffusion. Water extraction accelerated As transport between the different layers, and this increased the overall rate of As release from zones limited by diffusion. Desorption rate of As in the layered system was fast initially, followed by a period of slow desorption rate that lasted months. The desorption hysteresis was due to slow desorption controlled by diffusion. The results provide important insights for understanding and modeling As desorption and transport in field systems.

Coupled Aerobic Methane Oxidation and Arsenate Reduction Contributes to Soil-Arsenic Mobilization in Agricultural Fields

Microbial oxidation of organic compounds can promote arsenic release by reducing soil-associated arsenate to the more mobile form arsenite. While anaerobic oxidation of methane has been demonstrated to reduce arsenate, it remains elusive whether and to what extent aerobic methane oxidation (aeMO) can contribute to reductive arsenic mobilization. To fill this knowledge gap, we performed incubations of both microbial laboratory cultures and soil samples from arsenic-contaminated agricultural fields in China. Incubations with laboratory cultures showed that aeMO could couple to arsenate reduction, wherein the former bioprocess was carried out by aerobic methanotrophs and the latter by a non-methanotrophic bacterium belonging to a novel and uncultivated representative of Burkholderiaceae. Metagenomic analyses combined with metabolite measurements suggested that formate served as the interspecies electron carrier linking aeMO to arsenate reduction. Such coupled bioprocesses also take place in the real world, supported by a similar stoichiometry and gene activity in the incubations with natural paddy soils, and contribute up to 76.2% of soil-arsenic mobilization into pore waters in the top layer of the soils where oxygen was present. Overall, this study reveals a previously overlooked yet significant contribution of aeMO to reductive arsenic mobilization.

Global arsenic dilemma and sustainability

Arsenic (As) is one of the most prolific natural contaminants in water resources, and hence, it has been recognized as an emerging global problem. Arsenic exposure through food exports and imports, such as As-contaminated rice and cereal-based baby food, is a potential risk worldwide. However, ensuring As-safe drinking water and food for the globe is still not stated explicitly as a right neither in the United Nations' Universal Declaration of Human Rights and the 2030 Sustainable Development Goals (SDGs) nor the global UNESCO priorities. Despite these omissions, addressing As contamination is crucial to ensure and achieve many of the declared human rights, SDGs, and global UNESCO priorities. An international platform for sharing knowledge, experience, and resources through an integrated global network of scientists, professionals, and early career researchers on multidisciplinary aspects of As research can act as an umbrella covering the activities of UN, UNESCO, and other UN organizations. This can deal with the mitigation of As contamination, thus contributing to global economic development and human health. This article provides a perspective on the global As problem for sustainable As mitigation on a global scale by 2030.

Geogenic manganese and iron in groundwater of Southeast Asia and Bangladesh - Machine learning spatial prediction modeling and comparison with arsenic

Naturally occurring, geogenic manganese (Mn) and iron (Fe) are frequently found dissolved in groundwater at concentrations that make the water difficult to use (deposits, unpleasant taste) or, in the case of Mn, a potential health hazard. Over 6000 groundwater measurements of Mn and Fe in Southeast Asia and Bangladesh were assembled and statistically examined with other physicochemical parameters. The machine learning methods random forest and generalized boosted regression modeling were used with spatially continuous environmental parameters (climate, geology, soil, topography) to model and map the probability of groundwater Mn > 400 μg/L and Fe > 0.3 mg/L for Southeast Asia and Bangladesh. The modeling indicated that drier climatic conditions are associated with a tendency of elevated Mn concentrations, whereas high Fe concentrations tend to be found in a more humid climate with elevated levels of soil organic carbon. The spatial distribution of Mn > 400 μg/L and Fe > 0.3 mg/L was compared and contrasted with that of the critical geogenic contaminant arsenic (As), confirming that high Fe concentrations are often associated with high As concentrations, whereas areas of high concentrations of Mn and As are frequently found adjacent to each other. The probability maps draw attention to areas prone to elevated concentrations of geogenic Mn and Fe in groundwater and can help direct efforts to mitigate their negative effects. The greatest Mn hazard is found in densely populated northwest Bangladesh and the Mekong, Red and Ma River Deltas of Cambodia and Vietnam. Widespread elevated Fe concentrations and their associated negative effects on water infrastructure pose challenges to water supply. The Mn and Fe prediction maps demonstrate the value of machine learning for the geospatial prediction modeling and mapping of groundwater contaminants as well as the potential for further constituents to be targeted by this novel approach.

Arsenic Mobilization and Transformation by Ammonium-Generating Bacteria Isolated from High Arsenic Groundwater in Hetao Plain, China

Arsenic (As) mobilization in groundwater involves biogeochemical cycles of carbon, iron, and sulfur. However, few studies have focused on the role of nitrogen-metabolizing bacteria in As mobilization, as well as in the transformation between inorganic and organic As in groundwater. In this study, the nitrogen and As metabolisms of Citrobacter sp. G-C1 and Paraclostridium sp. G-11, isolated from high As groundwater in Hetao Plain, China, were characterized by culture experiments and genome sequencing. The results showed Citrobacter sp. G-C1 was a dissimilatory nitrate-reducing bacterium. The dissimilatory nitrate reduction to ammonia (DNRA) and As-detoxifying pathways identified in the genome enabled Citrobacter sp. G-C1 to simultaneously reduce As(V) during DNRA. Paraclostridium sp. G-11 was a nitrogen-fixing bacterium and its nitrogen-fixing activity was constrained by As. Nitrogen fixation and the As-detoxifying pathways identified in its genome conferred the capability of As(V) reduction during nitrogen fixation. Under anaerobic conditions, Citrobacter sp. G-C1 was able to demethylate organic As and Paraclostridium sp. G-11 performed As(III) methylation with the arsM gene. Collectively, these results not only evidenced that ammonium-generating bacteria with the ars operon were able to transform As(V) to more mobile As(III) during nitrogen-metabolizing processes, but also involved the transformation between inorganic and organic As in groundwater.

Siamese Network-Based Transfer Learning Model to Predict Geogenic Contaminated Groundwaters

Exposure to geogenic contaminated groundwaters (GCGs) is a significant public health concern. Machine learning models are powerful tools for the discovery of potential GCGs. However, the insufficient groundwater quality data and the fact that GCGs are typically a minority class in data hinder models to produce meaningful GCG predictions. To address this issue, a deep learning method, Siamese network-based transfer learning (SNTL), is used to estimate the probability that hazardous substances are present in groundwater above a threshold based on limited and class-imbalanced data. SNTL greatly reduces the amount of required training data and eliminates negative effects of class-imbalanced data on prediction model performance. The predictions of three typical GCGs (high arsenic/fluoride/iodine groundwater) show that the SNTL models provide higher (about 80%) and more balanced sensitivity and specificity than benchmark Random Forest models, indicating that SNTL models can predict both GCGs and non-GCGs. Therefore, protecting populations from GCG exposure in areas where other prediction methods fail to contribute risk information due to poor groundwater quality data can be enabled by SNTL.

Hydrochemical characteristics and quality assessment of shallow groundwater in Yangtze River Delta of eastern China

Water resource is in high demand within the Yangtze River Delta, given its developed economy. Long-term exploitation of this resource has posed risks of artificial pollution and seawater intrusion to the shallow groundwater. This study aims to reveal the hydrochemical characteristics and health risks of shallow groundwater in the coastal plain of the Yangtze River Delta, as well as to discuss the possible factors affecting groundwater quality. Standard methods for hydrochemical parameter measurements, water quality assessment, and health risk models were applied to fulfill the objectives of the study. The results showed that the shallow groundwater was slightly alkaline, and the average values of total dissolved solids (TDS) and total hardness (TH) were 930.74 mg/L and 436.20 mg/L, respectively. The main hydrochemical types of groundwater were HCO₃-Ca·Mg and HCO₃-Ca·Na, accounting for 44.3% and 47.5%, respectively. In addition, As concentration was generally high, with a mean value of 0.0115 mg/L. The principal factors affecting the groundwater components include water-rock interactions (especially silicate), cation exchange, seawater intrusion, and human activities. The data also showed that As is strongly influenced by the redox of Fe, Mn, and NO₃^-. The results of the groundwater quality evaluation indicated that the shallow groundwater in some regions was unsuitable for drinking and agricultural irrigation. Health risk assessment showed that 44.3% of the water samples had significant health risks, which was attributed to the high As concentration. Therefore, it is urgent to establish long-term As monitoring to maintain sustainable groundwater management and drinking water safety. The results of this study provide essential data for water resource management and human health security in the Yangtze River Delta.

Zinc supplementation prevents arsenic-induced dysregulation of ZRANB2 splice function

Environmentally relevant (100 nM) inorganic arsenic (iAs) exposure displaces zinc from zinc fingers of upstream splice regulator ZRANB2 disrupting the splicing of its target TRA2B. Excess zinc displaced iAs from ZRANB2 zinc fingers in cell free system. Thus, the hypothesis that zinc supplementation could prevent iAs-mediated disruption of ZRANB2 splice function in human keratinocytes was tested. The data show that zinc supplementation prevented iAs-induced dysregulation of TRA2B splicing by ZRANB2 as well as the induction of ZRANB2 protein expression. These results provide additional support for the hypothesis that zinc supplementation could prevent iAs-mediated disease in iAs-exposed populations.

Interplay between arsenic and selenium biomineralization in Shewanella sp. O23S

Bacteria play crucial roles in the biogeochemical cycle of arsenic (As) and selenium (Se) as these elements are metabolized via detoxification, energy generation (anaerobic respiration) and biosynthesis (e.g. selenocysteine) strategies. To date, arsenic and selenium biomineralization in bacteria were studied separately. In this study, the anaerobic metabolism of As and Se in Shewanella sp. O23S was investigated separately and mixed, with an emphasis put on the biomineralization products of this process. Multiple analytical techniques including ICP-MS, TEM-EDS, XRD, Micro-Raman, spectrophotometry and surface charge (zeta potential) were employed. Shewanella sp. O23S is capable of reducing selenate (SeO₄^2-) and selenite (SeO₃^2-) to red Se(-S)⁰, and arsenate (AsO₄^3-) to arsenite (AsO₃^3-). The release of H₂S from cysteine led to the precipitation of AsS minerals: nanorod AsS and granular As₂S₃. When As and Se oxyanions were mixed, both As-S and Se(-S)⁰ biominerals were synthesized. All biominerals were extracellular, amorphous and presented a negative surface charge (-24 to -38 mV). Kinetic analysis indicated the following reduction yields: SeO₃^2- (90%), AsO₄^3- (60%), and SeO₄^2- (<10%). The mix of SeO₃^2- with AsO₄^3- led to a decrease in As removal to 30%, while Se reduction yield was unaffected (88%). Interestingly, SeO₄^2- incubated with AsO₄^3- boosted the Se removal (71%). The exclusive extracellular formation of As and Se biominerals might indicate an extracellular respiratory process characteristic of various Shewanella species and strains. This is the first study documenting a complex interplay between As and Se oxyanions: selenite decreased arsenate reduction, whereas arsenate stimulated selenate reduction. Further investigation needs to clarify whether Shewanella sp. O23S employs multi-substrate respiratory enzymes or separate, high affinity enzymes for As and Se oxyanion respiration.

Global analysis and prediction of fluoride in groundwater

The health of millions of people worldwide is negatively impacted by chronic exposure to elevated concentrations of geogenic fluoride in groundwater. Due to health effects including dental mottling and skeletal fluorosis, the World Health Organization maintains a maximum guideline of 1.5 mg/L in drinking water. As groundwater quality is not regularly tested in many areas, it is often unknown if the water in a given well or spring contains harmful levels of fluoride. Here we present a state-of-the-art global fluoride hazard map based on machine learning and over 400,000 fluoride measurements (10% of which >1.5 mg/L), which is then used to estimate the human population at risk. Hotspots indicated by the groundwater fluoride hazard map include parts of central Australia, western North America, eastern Brazil and many areas of Africa and Asia. Of the approximately 180 million people potentially affected worldwide, most reside in Asia (51-59% of total) and Africa (37-46% of total), with the latter representing 6.5% of the continent's population. Africa also contains 14 of the top 20 affected countries in terms of population at risk. We also illuminate and discuss the key globally relevant hydrochemical and environmental factors related to fluoride accumulation.

Genome-Resolved Metagenomic Analysis of Groundwater: Insights into Arsenic Mobilization in Biogeochemical Interaction Networks

High-arsenic (As) groundwaters, a worldwide issue, are critically controlled by multiple interconnected biogeochemical processes. However, there is limited information on the complex biogeochemical interaction networks that cause groundwater As enrichment in aquifer systems. The western Hetao basin was selected as a study area to address this knowledge gap, offering an aquifer system where groundwater flows from an oxidizing proximal fan (low dissolved As) to a reducing flat plain (high dissolved As). The key microbial interaction networks underpinning the biogeochemical pathways responsible for As mobilization along the groundwater flow path were characterized by genome-resolved metagenomic analysis. Genes associated with microbial Fe(II) oxidation and dissimilatory nitrate reduction were noted in the proximal fan, suggesting the importance of nitrate-dependent Fe(II) oxidation in immobilizing As. However, genes catalyzing microbial Fe(III) reduction (omcS) and As(V) detoxification (arsC) were highlighted in groundwater samples downgradient flow path, inferring that reductive dissolution of As-bearing Fe(III) (oxyhydr)oxides mobilized As(V), followed by enzymatic reduction to As(III). Genes associated with ammonium oxidation (hzsABC and hdh) were also positively correlated with Fe(III) reduction (omcS), suggesting a role for the Feammox process in driving As mobilization. The current study illustrates how genomic sequencing tools can help dissect complex biogeochemical systems, and strengthen biogeochemical models that capture key aspects of groundwater As enrichment.

Cu and As(V) Adsorption and Desorption on/from Different Soils and Bio-Adsorbents

This research is concerned with the adsorption and desorption of Cu and As(V) on/from different soils and by-products. Both contaminants may reach soils by the spreading of manure/slurries, wastewater, sewage sludge, or pesticides, and also due to pollution caused by mining and industrial activities. Different crop soils were sampled in A Limia (AL) and Sarria (S) (Galicia, NW Spain). Three low-cost by-products were selected to evaluate their bio-adsorbent potential: pine bark, oak ash, and mussel shell. The adsorption/desorption studies were carried out by means of batch-type experiments, adding increasing and individual concentrations of Cu and As(V). The fit of the adsorption data to the Langmuir, Freundlich, and Temkin models was assessed, with good results in some cases, but with high estimation errors in others. Cu retention was higher in soils with high organic matter and/or pH, reaching almost 100%, while the desorption was less than 15%. The As(V) adsorption percentage clearly decreased for higher As doses, especially in S soils, from 60−100% to 10−40%. The As(V) desorption was closely related to soil acidity, being higher for soils with higher pH values (S soils), in which up to 66% of the As(V) previously adsorbed can be desorbed. The three by-products showed high Cu adsorption, especially oak ash, which adsorbed all the Cu added in a rather irreversible manner. Oak ash also adsorbed a high amount of As(V) (>80%) in a rather non-reversible way, while mussel shell adsorbed between 7 and 33% of the added As(V), and pine bark adsorbed less than 12%, with both by-products reaching 35% desorption. Based on the adsorption and desorption data, oak ash performed as an excellent adsorbent for both Cu and As(V), a fact favored by its high pH and the presence of non-crystalline minerals and different oxides and carbonates. Overall, the results of this research can be relevant when designing strategies to prevent Cu and As(V) pollution affecting soils, waterbodies, and plants, and therefore have repercussions on public health and the environment.

rspatialdata: a collection of data sources and tutorials on downloading and visualising spatial data using R

Spatial and spatio-temporal data are used in a wide range of fields including environmental, health and social disciplines. Several packages in the statistical software R have been recently developed as clients for various databases to meet the growing demands for easily accessible and reliable spatial data. While documentation on how to use many of these packages exist, there is an increasing need for a one stop repository for tutorials on this information. In this paper, we present rspatialdata a website that provides a collection of data sources and tutorials on downloading and visualising spatial data using R. The website includes a wide range of datasets including administrative boundaries of countries, Open Street Map data, population, temperature, vegetation, air pollution, and malaria data. The goal of the website is to equip researchers and communities with the tools to engage in spatial data analysis and visualisation so that they can address important local issues, such as estimating air pollution, quantifying disease burdens, and evaluating and monitoring the United Nation’s sustainable development goals.

Arsenic Exposure, Blood DNA Methylation, and Cardiovascular Disease

BACKGROUND

Epigenetic dysregulation has been proposed as a key mechanism for arsenic-related cardiovascular disease (CVD). We evaluated differentially methylated positions (DMPs) as potential mediators on the association between arsenic and CVD.

METHODS

Blood DNA methylation was measured in 2321 participants (mean age 56.2, 58.6% women) of the Strong Heart Study, a prospective cohort of American Indians. Urinary arsenic species were measured using high-performance liquid chromatography coupled to inductively coupled plasma mass spectrometry. We identified DMPs that are potential mediators between arsenic and CVD. In a cross-species analysis, we compared those DMPs with differential liver DNA methylation following early-life arsenic exposure in the apoE knockout (apoE-/-) mouse model of atherosclerosis.

RESULTS

A total of 20 and 13 DMPs were potential mediators for CVD incidence and mortality, respectively, several of them annotated to genes related to diabetes. Eleven of these DMPs were similarly associated with incident CVD in 3 diverse prospective cohorts (Framingham Heart Study, Women's Health Initiative, and Multi-Ethnic Study of Atherosclerosis). In the mouse model, differentially methylated regions in 20 of those genes and DMPs in 10 genes were associated with arsenic.

CONCLUSIONS

Differential DNA methylation might be part of the biological link between arsenic and CVD. The gene functions suggest that diabetes might represent a relevant mechanism for arsenic-related cardiovascular risk in populations with a high burden of diabetes.

Quantifying the impacts of COVID-19 on Sustainable Development Goals using machine learning models

The COVID-19 pandemic has posed severe threats to global sustainable development. However, a comprehensive quantitative assessment of the impacts of COVID-19 on Sustainable Development Goals (SDGs) is still lacking. This research quantified the post-COVID-19 SDG progress from 2020 to 2024 using projected GDP growth and population and machine learning models including support vector machine, random forest, and extreme gradient boosting. The results show that the overall SDG performance declined by 7.7% in 2020 at the global scale, with 12 socioeconomic SDG performance decreasing by 3.0–22.3% and 4 environmental SDG performance increasing by 1.6–9.2%. By 2024, the progress of 12 SDGs will lag behind for one to eight years compared to their pre-COVID-19 trajectories, while extra time will be gained for 4 environment-related SDGs. Furthermore, the pandemic will cause more impacts on countries in emerging markets and developing economies than those on advanced economies, and the latter will recover more quickly to be closer to their pre-COVID-19 trajectories by 2024. Post-COVID-19 economic recovery should emphasize in areas that can help decouple economic growth from negative environmental impacts. The results can help government and non-state stakeholders identify critical areas for targeted policy to resume and speed up the progress to achieve SDGs by 2030.

The groundwater arsenic contamination in the Bengal Basin-A review in brief

The presence of arsenic in the groundwater of the densely-populated Bengal Basin evolved as a mass-poisoning agent and is a reason for the misery of millions of people living here. High-level arsenic was detected in the shallow aquifer-tube wells of the basin in the late-20th century. The redox conditions and the biogeochemical activities in the shallow aquifers support the existence of arsenic in its most toxic +3 state. The shallow aquifers are constructed by the Holocene reduced grey sands, having a lesser capacity to hold the arsenic brought from the Himalayas by the Ganga-Brahmaputra-Meghna river system. Among several other hypotheses, the reductive dissolution of arsenic bearing Fe-oxyhydroxides coupled with the microbial activities in the organic-matter-rich Holocene grey sands is believed to be the primary reason for releasing arsenic in groundwater of basinal shallow aquifers. The deep aquifers below the late Pleistocene aquifers and the Palaeo-interfluvial aquifers capped by the last glacial maximum Palaeosol generally contain arsenic-free or low-arsenic water. Ingress of arsenic into the deep aquifers from the shallow aquifers was considered to have been caused by extensive non-domestic pumping. However, studies have found that extensive pumping is unlikely to contaminate the deep aquifer water with higher levels of arsenic within decadal time scales. Irrigation-pumping may produce hydraulic barriers between the shallow and deep aquifer-groundwater and distributes arsenic in the topsoil by flushing. Significant disparities have been observed among the Bengal basinal groundwater arsenic concentrations. However, abrupt spatial variation in groundwater arsenic concentrations has been a key feature of the basin.

SnO2 Nanoparticles-CeO2 Nanorods Enriched with Oxygen Vacancies for Bifunctional Sensing Performances toward Toxic CO Gas and Arsenate Ions

In this paper, we present a novel, one-step synthesis of SnO₂ nanoparticle-CeO₂ nanorod sensing material using a surfactant-mediated hydrothermal method. The bifunctional utility of the synthesized sensing material toward room-temperature sensing of CO gas and low-concentration optosensing of arsenic has been thoroughly investigated. The CeO₂-SnO₂ nanohybrid was characterized using sophisticated analytical techniques such as transmission electron microscopy, X-ray diffraction analysis, energy-dispersive X-ray analysis, X-ray photoelectron spectroscopy, and so forth. The CeO₂-SnO₂ nanohybrid-based sensor exhibited a strong response toward CO gas at room temperature. Under a low concentration (3 ppm) of CO gas, the CeO₂-SnO₂ sensing material showed an excellent response time of 21.1 s for 90% of the response was achieved with a higher recovery time of 59.6 s. The nanohybrid sensor showed excellent low-concentration (1 ppm) sensing behavior which is ∼6.7 times higher than that of the pristine SnO₂ sensors. The synergistically enhanced sensing properties of CeO₂-SnO₂ nanohybrid-based sensors were discussed from the viewpoint of the CeO₂-SnO₂ n-n heterojunction and the effect of oxygen vacancies. Furthermore, the SnO₂-CeO₂ nanoheterojunction showed luminescence centers and prolonged electron-hole recombination, thereby resulting in quenching of luminescence in the presence of arsenate ions. The photoluminescence of CeO₂-SnO₂ is sensitive to the arsenate ion concentration in water and can be used for sensing arsenate with a limit of detection of 4.5 ppb in a wide linear range of 0 to 100 ppb.

Arsenic Exposure via Contaminated Water and Food Sources

Arsenic poisoning constitutes a major threat to humans, causing various health problems. Almost everywhere across the world certain “hotspots” have been detected, putting in danger the local populations, due to the potential consumption of water or food contaminated with elevated concentrations of arsenic. According to the relevant studies, Asia shows the highest percentage of significantly contaminated sites, followed by North America, Europe, Africa, South America and Oceania. The presence of arsenic in ecosystems can originate from several natural or anthropogenic activities. Arsenic can be then gradually accumulated in different food sources, such as vegetables, rice and other crops, but also in seafood, etc., and in water sources (mainly in groundwater, but also to a lesser extent in surface water), potentially used as drinking-water supplies, provoking their contamination and therefore potential health problems to the consumers. This review reports the major areas worldwide that present elevated arsenic concentrations in food and water sources. Furthermore, it also discusses the sources of arsenic contamination at these sites, as well as selected treatment technologies, aiming to remove this pollutant mainly from the contaminated waters and thus the reduction and prevention of population towards arsenic exposure.

Developmental arsenic exposure impairs cognition, directly targets DNMT3A, and reduces DNA methylation

Developmental arsenic exposure has been associated with cognitive deficits in epidemiological studies, but the underlying mechanisms remain poorly understood. Here, we establish a mouse model of developmental arsenic exposure exhibiting deficits of recognition and spatial memory in the offspring. These deficits are associated with genome-wide DNA hypomethylation and abnormal expression of cognition-related genes in the hippocampus. Arsenic atoms directly bind to the cysteine-rich ADD domain of DNA methyltransferase 3A (DNMT3A), triggering ubiquitin- and proteasome-mediated degradation of DNMT3A in different cellular contexts. DNMT3A degradation leads to genome-wide DNA hypomethylation in mouse embryonic fibroblasts but not in non-embryonic cell lines. Treatment with metformin, a first-line antidiabetic agent reported to increase DNA methylation, ameliorates the behavioral deficits and normalizes the aberrant expression of cognition-related genes and DNA methylation in the hippocampus of arsenic-exposed offspring. Our study establishes a DNA hypomethylation effect of developmental arsenic exposure and proposes a potential treatment against cognitive deficits in the offspring of pregnant women in arsenic-contaminated areas.

The impact of prenatal and early-life arsenic exposure on epigenetic age acceleration among adults in Northern Chile

Exposure to arsenic affects millions of people globally. Changes in the epigenome may be involved in pathways linking arsenic to health or serve as biomarkers of exposure. This study investigated associations between prenatal and early-life arsenic exposure and epigenetic age acceleration (EAA) in adults, a biomarker of morbidity and mortality. DNA methylation was measured in peripheral blood mononuclear cells (PBMCs) and buccal cells from 40 adults (median age = 49 years) in Chile with and without high prenatal and early-life arsenic exposure. EAA was calculated using the Horvath, Hannum, PhenoAge, skin and blood, GrimAge, and DNA methylation telomere length clocks. We evaluated associations between arsenic exposure and EAA using robust linear models. Participants classified as with and without arsenic exposure had a median drinking water arsenic concentration at birth of 555 and 2 μg/l, respectively. In PBMCs, adjusting for sex and smoking, exposure was associated with a 6-year PhenoAge acceleration [B (95% CI) = 6.01 (2.60, 9.42)]. After adjusting for cell-type composition, we found positive associations with Hannum EAA [B (95% CI) = 3.11 (0.13, 6.10)], skin and blood EAA [B (95% CI) = 1.77 (0.51, 3.03)], and extrinsic EAA [B (95% CI) = 4.90 (1.22, 8.57)]. The association with PhenoAge acceleration in buccal cells was positive but not statistically significant [B (95% CI) = 4.88 (-1.60, 11.36)]. Arsenic exposure limited to early-life stages may be associated with biological aging in adulthood. Future research may provide information on how EAA programmed in early life is related to health.

Inorganic arsenic promotes apoptosis of human immortal keratinocytes through the TGF-β1/ERK signaling pathway

Chronic exposure to high-dose inorganic arsenic through groundwater, air, or food remains a major environmental public health issue worldwide. Apoptosis, a method of cell death, has recently become a hot topic of research in biology and medicine. Previous studies have demonstrated that extracellular signal-regulated kinase (ERK) is related to arsenic-induced apoptosis. However, the reports are contradictory, and the knowledge of the above-mentioned mechanisms and their mutual regulation remains limited. In this study, the associations between the TGF-β1/ERK signaling pathway and arsenic-induced cell apoptosis were confirmed using the HaCaT cell model. The relative expressions of the indicators of the TGF-β1/ERK signaling pathway, apoptosis-related genes (cytochrome C, caspase-3, caspase-9, cleaved caspase-3, cleaved caspase-9, and Bax), the mitochondrial membrane potential, and the total apoptosis rate were significantly increased (P < .05), while the expression of the antiapoptosis gene Bcl-2 was significantly decreased (P < .05) in cells of the group exposed to arsenic. Moreover, the results demonstrated that the ERK inhibitor (PD98059) and TGF-β1 inhibitor (LY364947) could inhibit the activation of the ERK signaling pathway, thereby reducing the mitochondrial membrane potential, the total apoptosis rate, and the expression of pro-apoptosis-related genes in the cells, while the expression of the antiapoptosis gene Bcl-2 was significantly increased (P < .05). By contrast, the recombinant human TGF-β1 could promote apoptosis of the HaCaT cells by increasing the activation of the ERK signaling pathway (P < .05). These results indicate that inorganic arsenic promotes the apoptosis of human immortal keratinocytes through the TGF-β1/ERK signaling pathway.

Removal of arsenic by metal organic framework/chitosan/carbon nanocomposites: Modeling, optimization, and adsorption studies

In this work removal of the arsenic (As) spiked in water through adsorption using synthesized nanocomposites as a adsorbent. The Zn-BDC@chitosan/carbon nanotube (Zn-BDC@CT/CNT) and Zn-BDC@chitosan/graphene oxide (Zn-BDC@CT/GO) were synthesized from metal organic framework, carbon nanotube/graphene oxide and natural polysaccharide. Results of adsorption experiments showed that the Zn-BDC@CT/GO possessed a higher adsorption capacity than that of the Zn-BDC@CT/CNT. A study on the adsorption of As onto Zn-BDC@CT/GO was conducted and the process parameters were optimized by response surface methodology (RSM). A five-level, four-factor central composite design (CCD) has been used to determine the effect of various process parameters on As uptake from aqueous solution. By using this design a total of 20 adsorption experimental data were fitted. The regression analysis showed good fit of the experimental data to the second-order polynomial model with coefficient of determination (R²) value of 0.9997 and model F-value of 1099.97. The adsorption matched with the pseudo-second-order model and the Freundlich model. The thermodynamic parameters revealed that the nature of adsorption was feasible, spontaneous and endothermic process. Adsorption of As in the presence of other competitive ions was not significantly affected The effective adsorption performance also sustained even after ten adsorption-desorption cycles, indicating favorable reusability.

Research Progress on Adsorption of Arsenic from Water by Modified Biochar and Its Mechanism: A Review

Arsenic (As) is a non-metallic element, which is widely distributed in nature. Due to its toxicity, arsenic is seriously harmful to human health and the environment. Therefore, it is particularly important to effectively remove arsenic from water. Biochar is a carbon-rich adsorption material with advantages such as large specific surface area, high porosity, and abundant functional groups, but the original biochar has limitations in application, such as limited adsorption capacity and adsorption range. The modified biochar materials have largely enhanced the adsorption capacity of As in water due to their improved physicochemical properties. In this review, the changes in the physicochemical properties of biochar before and after modification were compared by SEM, XRD, XPS, FT-IR, TG, and other characterization techniques. Through the analysis, it was found that the adsorbent dosage and pH are the major factors that influence the As adsorption capacity of the modified biochar. The adsorption process of As by biochar is endothermic, and increasing the reaction temperature is conducive to the progress of adsorption. Results showed that the main mechanisms include complexation, electrostatic interaction, and precipitation for the As removal by the modified biochar. Research in the field of biochar is progressing rapidly, with numerous achievements and new types of biochar-based materials prepared with super-strong adsorption capacity for As. There is still much space for in-depth research in this field. Therefore, the future research interests and applications are put forward in this review.

Multilayered TNAs/SnO2/PPy/β-PbO2 anode achieving boosted electrocatalytic oxidation of As(III)

Dealing with arsenic pollution has been of great concern owing to inherent toxicity of As(III) to environments and human health. Herein, a novel multilayered SnO₂/PPy/β-PbO₂ structure on TiO₂ nanotube arrays (TNAs/SnO₂/PPy/β-PbO₂) was synthesized by a multi-step electrodeposition process as an efficient electrocatalyst for As(III) oxidation in aqueous solution. Such TNAs/SnO₂/PPy/β-PbO₂ electrode exhibited a higher charge transfer, tolerable stability, and high oxygen evolution potential (OEP). The intriguing structure with a SnO₂, PPy, and β-PbO₂ active layers provided a larger electrochemical active area for electrocatalytic As(III) oxidation. The as-synthesized TNAs/SnO₂/PPy/β-PbO₂ anode achieved drastically enhanced As(Ⅲ) conversion efficiency of 90.72% compared to that of TNAs/β-PbO₂ at circa 45.4%. The active species involved in the electrocatalytic oxidation process included superoxide radical (•O₂^-), sulfuric acid root radicals (•SO₄^-), and hydroxyl radicals (•OH). This work offers a new strategy to construct a high-efficiency electrode to meet the requirements of favorable electrocatalytic oxidation properties, good stability, and high electrocatalytic activity for As(III) transformation to As(V).

Genetic interpretation and health risk assessment of arsenic in Hetao Plain of inner Mongolia, China

Arsenic is a toxic element widely spread in soils and groundwater that can cause a great hazard to ecology and human health. In this paper, 51 groundwater and 12 sediment samples were analyzed to investigate the sources and evolution mechanism of arsenic and identify the hydrochemical characteristics of groundwater in Hetao Plain, Inner Mongolia through Kriging interpolation, Piper trilinear diagram and ion correlation analysis. Results show that high arsenic groundwater is mainly distributed in the areas with reducing environment. Arsenic has a strong positive correlation with bicarbonic acid and a negative correlation with nitric acid. Arsenic in the sediment is easily adsorbed by iron-manganese compounds. In a reducing environment, arsenic is however released while iron-manganese oxides are reduced. Through triangular fuzzy numbers, a health risk assessment was conducted to evaluate the hazard caused by high arsenic groundwater to humans. Results suggest that the highest carcinogenic risk values of arsenic for children, men, and women are 3.9 × 10^-3, 2.38 × 10^-3, and 2.35 × 10^-3, respectively that greatly exceeds the acceptable risk value. The findings of this paper provide useful insight into the occurrence mechanism of arsenic in those areas with high arsenic groundwater and the potential health risk to humans.

Assessing the Association of Element Imbalances With Arsenism and the Potential Application Value of Rosa roxburghii Tratt Juice

Endemic arsenism caused by coal burning is a unique type of biogeochemical disease that only exists in China, and it is also a disease of element imbalances. Previous studies have shown that element imbalances are involved in the pathogenesis of arsenic; however, the interaction between the various elements and effective preventive measures have not been fully studied. This study first conducted a cross-sectional study of a total of 365 participants. The results showed that arsenic exposure can increase the content of elements (Al, As, Fe, Hg, K, and Na) in the hair (p < 0.05), but the content of other elements (Ca, Co, Cu, Mn, Mo, P, Se, Sr, V, and Zn) was significantly decreased (p < 0.05). Also, the high level of As, Fe, and Pb and the low level of Se can increase the risk of arsenism (p < 0.05). Further study found that the combined exposure of Fe–As and Pb–As can increase the risk of arsenism, but the combined exposure of Se–As can reduce the risk of arsenism (p < 0.05). In particular, a randomized, controlled, double-blind intervention study reveals that Rosa roxburghii Tratt juice (RRT) can reverse the abovementioned element imbalances (the high level of Al, As, and Fe and the low level of Cu, Mn, Se, Sr, and Zn) caused by arsenic (p < 0.05). Our study provides some limited evidence that the element imbalances (the high level of As, Fe, and Pb and the low level of Se) are the risk factors for the occurrences of arsenism. The second major finding was that RRT can regulate the element imbalances, which is expected to improve arsenism. This study provides a scientific basis for further understanding a possible traditional Chinese health food, RRT, as a more effective detoxication of arsenism.

Microbial Community Structure of Arsenic-Bearing Groundwater Environment in the Riverbank Filtration Zone

Arsenic (As) contamination of groundwater is a global public health problem. Microorganisms have a great effect on the migration and transformation of arsenic. Studying the effect of microbial community structure and function on arsenic release in the groundwater environment of the riverbank filtration zone has important theoretical and practical significance. In this paper, in-situ monitoring technology and molecular biology technology were used to study the microbial community in the process of river water infiltration in the Shenyang Huangjia water source, China. The results showed that the structure, diversity and abundance of the microbial community in groundwater were closely related to the arsenic content. Proteobacteria was the dominant phylum in groundwater of the study area, and Acinetobacter, Pseudomonas, Sulfuritalea, Sphingomonas and Hydrogenophaga etc. were the main dominant bacterial genera. In addition to reducing and oxidizing arsenic, these functional microorganisms also actively participated in the biogeochemical cycle of elements such as iron, manganese, nitrogen and sulfur. There was a significant correlation between dominant bacteria and environmental factors. Fe/Mn had a significant positive correlation with As, which brought potential danger to the water supply in high iron and manganese areas.

Transporters and Toxicity: Insights from the International Transporter Consortium Workshop 4

Over the last decade, significant progress been made in elucidating the role of membrane transporters in altering drug disposition, with important toxicological consequences due to changes in localized concentrations of compounds. The topic of "Transporters and Toxicity" was recently highlighted as a scientific session at the International Transporter Consortium (ITC) Workshop 4 in 2021. The current white paper is not intended to be an extensive review on the topic of transporters and toxicity but an opportunity to highlight aspects of the role of transporters in various toxicities with clinically relevant implications as covered during the session. This includes a review of the role of solute carrier transporters in anticancer drug-induced organ injury, transporters as key players in organ barrier function, and the role of transporters in metal/metalloid toxicity.

Effects of Fe(II)-induced transformation of scorodite on arsenic solubility

Scorodite (FeAsO₄·2H₂O) is a pivotal secondary ferric arsenate that immobilizes most of arsenic (As) in acidic As-contaminated environments, but secondary As pollution may occur during dissolution of scorodite in environments involving redox changes. Reductive dissolution of scorodite by coexisting dissolved Fe²⁺ (Fe(II)_aq) under anaerobic conditions and its effects on the behavior of As have yet to be examined. Here, this study monitored the changes in mineralogy, solubility and speciation of As during scorodite transformation induced by Fe(II) under anaerobic conditions at pH 7.0 and discussed the underlying mechanisms. Mössbauer and X-ray diffraction (XRD) analysis showed the formation of parasymplesite and ferrihydrite-like species during scorodite transformation, which was highly controlled by Fe(II)_aq concentrations. 1 mM Fe(II)_aq enhanced As mobilization into the solution, whereas As was repartitioned to the PO₄^3--extractable and HCl-extractable phases with 5 and 10 mM Fe(II). The neo-formed parasymplesite and ferrihydrite-like species immobilized dissolved As(V) through adsorption and incorporation. Additionally, As(V) reduction occurred during Fe(II)-induced scorodite transformation. Our results provide new insights into the stability and risk of scorodite in anaerobic environments as well as the geochemical behavior of As in response to Fe cycling.

Assessment of groundwater arsenic contamination using machine learning in Varanasi, Uttar Pradesh, India

This paper presents a machine learning approach for classification of arsenic (As) levels as safe and unsafe in groundwater samples collected from the Indo-Gangetic region. As water is essential for sustaining life, heavy metals like arsenic pose a public health concern. In this study, various tree-based machine learning models namely Random Forest, Optimized Forest, CS Forest, SPAARC, and REP Tree algorithms have been applied to classify water samples. As per the guidelines of the World Health Organization (WHO), the arsenic concentration in water should not exceed 10 μg/L. The groundwater quality parameter was ranked using a classifier attribute evaluator for training and testing the models. Parameters obtained from the confusion matrix, such as accuracy, precision, recall, and FPR, were used to analyze the performance of models. Among all models, Optimized Forest outperforms other classifier as it has a high accuracy of 80.64%, a precision of 80.70%, recall of 97.87%, and a low FPR of 73.33%. The Optimized Forest model can be used to test new water samples for classification of arsenic in groundwater samples.

Arsenic bioaccumulation and biotransformation in aquatic organisms

Arsenic exists universally in freshwater and marine environments, threatening the survival of aquatic organisms and human health. To elucidate arsenic bioaccumulation and biotransformation processes in aquatic organisms, this review evaluates the dissolved uptake, dietary assimilation, biotransformation, and elimination of arsenic in aquatic organisms and discusses the major factors influencing these processes. Environmental factors such as phosphorus concentration, pH, salinity, and dissolved organic matter influence arsenic absorption from aquatic systems, whereas ingestion rate, gut passage time, and gut environment affect the assimilation of arsenic from foodstuffs. Arsenic bioaccumulation and biotransformation mechanisms differ depending on specific arsenic species and the involved aquatic organism. Although some enzymes engaged in arsenic biotransformation are known, deciphering the complicated synthesis and degradation pathway of arsenobetaine remains a challenge. The elimination of arsenic involves many processes, such as fecal excretion, renal elimination, molting, and reproductive processes. This review facilitates our understanding of the environmental behavior and biological fate of arsenic and contributes to regulation of the environmental risk posed by arsenic pollution.

Mapped Predictions of Manganese and Arsenic in an Alluvial Aquifer Using Boosted Regression Trees

Manganese (Mn) concentrations and the probability of arsenic (As) exceeding the drinking-water standard of 10 μg/L were predicted in the Mississippi River Valley alluvial aquifer (MRVA) using boosted regression trees (BRT). BRT, a type of ensemble-tree machine-learning model, were created using predictor variables that affect Mn and As distribution in groundwater. These variables included iron (Fe) concentrations and specific conductance predicted from previously developed BRT models, groundwater flux and age estimates from MODFLOW, and hydrologic characteristics. The models also included results from the first airborne geophysical survey conducted in the United States to target an entire aquifer system. Predictions of high Mn and As occurred where Fe was high. Predicted high Mn concentrations were correlated with fraction of young groundwater (less than 65 years) computed from MODFLOW results. High probabilities of As exceedance were predicted where groundwater was relatively old and airborne electromagnetic resistivity was high, typically proximal to streams. Two-variable partial-dependence plots and sensitivity analysis were used to provide insight into the factors controlling Mn and As distribution in groundwater. The maps of predicted Mn concentrations and As exceedance probabilities can be used to identify areas where these constituents may be high, and that could be targeted for further study. This paper shows that incorporation of a selected set of process-informed data, such as MODFLOW results and airborne geophysics, into a machine-learning model improves model interpretability. Incorporation of process-rich information into machine-learning models will likely be useful for addressing a wide range of problems of interest to groundwater hydrologists.