Transferability of Machine Learning Models for Geogenic Contaminated Groundwaters.

Machine learning models show promise in identifying geogenic contaminated groundwaters. Modeling in regions with no or limited samples is challenging due to the need for large training sets. One potential solution is transferring existing models to such regions. This study explores the transferability of high fluoride groundwater models between basins in the Shanxi Rift System, considering six factors, including modeling methods, predictor types, data size, sample/predictor ratio (SPR), predictor range, and data informing. Results show that transferability is achieved only when model predictors are based on hydrochemical parameters rather than surface parameters. Data informing, i.e., adding samples from challenging regions to the training set, further enhances the transferability. Stepwise regression shows that hydrochemical predictors and data informing significantly improve transferability, while data size, SPR, and predictor range have no significant effects. Additionally, despite their stronger nonlinear capabilities, random forests and artificial neural networks do not necessarily surpass logistic regression in transferability. Lastly, we utilize the t-SNE algorithm to generate low-dimensional representations of data from different basins and compare these representations to elucidate the critical role of predictor types in transferability.

Antimony Isotope Fractionation during Adsorption on Iron (Oxyhydr)oxides.

The fate of antimony (Sb) is strongly affected by adsorption, yet Sb isotope fractionation and the associated mechanism have not been widely reported. Here we experimentally investigated the process of Sb(V) adsorption on iron (oxyhydr)oxides and the associated isotope effects. Sb isotope fractionation occurs during adsorption (Δ123Sbsolution-mineral = 1.20 ± 0.02‰ for ferrihydrite and 2.35 ± 0.04‰ for goethite). Extended X-ray absorption fine structure (EXAFS) analysis shows that Sb(V) adsorption on iron (oxyhydr)oxides occurs via inner-sphere surface complexation, including mononuclear bidentate edge-sharing (2E) and binuclear bidentate corner-sharing (2C) complexes. A longer atom distance of Sb-Fe in ferrihydrite leads to less Sb isotope fractionation during Sb adsorption than in goethite. The Gibbs free energy and Mayer bond order were calculated based on density functional theory (DFT) and suggested that the strength of the bonding environment can be summarized as Sb(OH)6- > 2E > 2C. In turn, the bonding environment indicates the mechanism of Sb isotope fractionation during the process. This study reveals that Sb isotope fractionation occurs during Sb(V) adsorption onto iron (oxyhydr)oxides, providing a basis for the future study of Sb isotopes and further understanding of the fractionation mechanism.

Enrichment of Geogenic Organoiodine Compounds in Alluvial-Lacustrine Aquifers: Molecular Constraints by Organic Matter.

Organoiodine compounds (OICs) are the dominant iodine species in groundwater systems. However, molecular mechanisms underlying the geochemical formation of geogenic OICs-contaminated groundwater remain unclear. Based upon multitarget field monitoring in combination with ultrahigh-resolution molecular characterization of organic components for alluvial-lacustrine aquifers, we identified a total of 939 OICs in groundwater under reducing and circumneutral pH conditions. In comparison to those in water-soluble organic matter (WSOM) in sediments, the OICs in dissolved organic matter (DOM) in groundwater typically contain fewer polycyclic aromatics and polyphenol compounds but more highly unsaturated compounds. Consequently, there were two major sources of geogenic OICs in groundwater: the migration of the OICs from aquifer sediments and abiotic reduction of iodate coupled with DOM iodination under reducing conditions. DOM iodination occurs primarily through the incorporation of reactive iodine that is generated by iodate reduction into highly unsaturated compounds, preferably containing hydrophilic functional groups as binding sites. It leads to elevation of the concentration of the OICs up to 183 µg/L in groundwater. This research provides new insights into the constraints of DOM molecular composition on the mobilization and enrichment of OICs in alluvial-lacustrine aquifers and thus improves our understanding of the genesis of geogenic iodine-contaminated groundwater systems.

Dissimilatory Iodate-Reducing Microorganisms Contribute to the Enrichment of Iodine in Groundwater.

Iodate reduction by dissimilatory iodate-reducing microorganisms (DIRMs) plays a crucial role in the biogeochemical cycling of iodine on Earth. However, the occurrence and distribution of DIRMs in iodine-rich groundwater remain unclear. In this study, we isolated the dissimilatory iodate-reducing bacteriumAzonexus hydrophilusstrain NCP973 from a geogenic high-iodine groundwater of China for the first time. The analysis of genome, transcriptome, and heterologous expression revealed that strain NCP973 uses the dissimilatory iodate-reducing enzyme IdrABP1P2 to reduce dissolved or in situ sediment-bound iodate to iodide. The location of IdrABP1P2 in the conjugative plasmid of strain NCP973 implies that IdrABP1P2 could be spread by horizontal gene transfer and allow the recipient microorganisms to participate in the enrichment of iodide in aquifers. Based on the global iodine-rich groundwater metagenomes and genomes, the identification of idrA showed that phylogenetically diverse DIRMs are widely distributed not only in geogenic high-iodine groundwater of China but also in radionuclide-contaminated groundwater of USA as well as in subsurface cavern waters in Germany and Italy. Moreover, the abundance of idrA was found to be higher in groundwater with a relatively high iodine content. Collectively, these results suggest that terrestrial iodine-affected groundwater systems are another important habitat for DIRMs in addition to marine environments, and their activity in aquifers triggers the mobilization and enrichment of iodine in groundwater worldwide.

Impact of long-term irrigation practices on distribution and speciation of arsenic in agricultural soil.

To better understand the impact of long-term irrigation practices on arsenic (As) accumulation in agricultural soils, 100 soil samples from depths of 0-20 cm were collected from the Datong basin, where the As-contaminated groundwater has been used for irrigation for several decades. Soil samples were analyzed for major elements, trace elements, and As, Fe speciation. Results reveal As content ranging from 4.00 to 14.5 mg/kg, an average of 10.2 ± 2.05 mg/kg, consistent with surveys conducted in 1998 and 2007. Arsenic speciation ranked in descending order as follows: As associated with silicate minerals (AsSi, 29.70 ± 7.53 %) > amorphous Fe-minerals associated As (AsFeox1, 26.40 ± 3.27 %) > crystalline Fe-minerals associated As (AsFeox2, 24.02 ± 4.60 %) > strongly adsorbed As (AsSorb, 14.29 ± 2.81 %) > As combined with carbonates and Fe-carbonates (AsCar, 2.30 ± 0.44 %) > weakly adsorbed As (AsDiss, 2.59 ± 1.00 %). The anomalous negative correlation between As and Fe content reflects the primary influence of soil provenance. Evidence from major element compositions and rare earth element patterns indicates that total As and Fe contents in soils are controlled by parent materials, exhibiting distinct north-south differences (As: higher levels in the north, lower levels in the south; Fe: higher levels in the south, lower levels in the north). Evidence from the Chemical Index of Alteration (CIA) and As/Ti ratio suggests that chemical weathering has led to As enrichment in the central basin. Notably, relationships such as AsDiss/Ti, AsSorb/Ti with CIA and total Fe content indicate significant influences of irrigation practices on adsorbed As (both weakly and strongly adsorbed) contents, showing a pattern of higher levels in the central basin and lower levels in the Piedmont. However, total As content remained stable after long-term irrigation, potentially due to the re-release of accumulated As via geochemical pathways during non-irrigated periods. These findings demonstrate that the soil systems can naturally remediate exogenous As contamination induced by irrigation practices. Quantitative assessment of the balance between As enrichment and re-release in soil systems is crucial for preventing soil As contamination, highlighting strategies like water-saving techniques and fallow periods to manage As contamination in agricultural areas using As-contaminated groundwater for irrigation.

Understanding spatial heterogeneity of groundwater arsenic concentrations at a field scale: Taking the Datong Basin as an example to explore the significance of hydrogeological factors.

The spatial heterogeneity of arsenic (As) concentration exceeding the 10 µg/L WHO limit at the field scale poses significant challenges for groundwater utilization, but it remains poorly understood. To address this knowledge gap, the Daying site was selected as a representative case (As concentration ranged from 1.55 to 2237 µg/L within a 250 × 150 m field), and a total of 28 groundwater samples were collected and analyzed for hydrochemistry, As speciation, and stable hydrogen and oxygen isotope. Principal component analysis was employed to identify the primary factors controlling groundwater hydrochemistry. Results indicate that the spatial heterogeneity of groundwater As concentration is primarily attributed to vertical recharge and competitive adsorption. Low vertical recharge introduces reductive substances, such as dissolved organic matter, which enhances the reductive environment and facilitates microbial-induced reduction and mobilization of As. Conversely, areas with high vertical recharge introduce oxidizing agents like SO42- and DO, which act as preferred electron acceptors over Fe(III), thus inhibiting the reductive dissolution of Fe(III) oxides and the mobilization of As. PCA and hydrochemistry jointly indicate that spatial variability of P and its competitive adsorption with As are important factors leading to spatial heterogeneity of groundwater As concentration. However, the impacts of pH, Si, HCO3-, and F- on As adsorption are insignificant. Specifically, low vertical recharge can increase the proportion of As(III) and promote P release through organic matter mineralization. This process further leads to the desorption of As, indicating a synergistic effect between low vertical recharge and competitive adsorption. This field-scale spatial heterogeneity underscores the critical role of hydrogeological conditions. Sites with close hydraulic connections to surface water often exhibit low As concentrations in groundwater. Therefore, when establishing wells in areas with widespread high-As groundwater, selecting sites with open hydrogeological conditions can prove beneficial.

Antimicrobial resistance characteristics and phylogenetic relationships of pleuromutilin-resistant Enterococcus isolates from different environmental samples along a laying hen production chain.

Antimicrobial resistance in the laying hen production industry has become a serious public health problem. The antimicrobial resistance and phylogenetic relationships of the common conditional pathogen Enterococcus along the laying hen production chain have not been systematically clarified. 105 Enterococcus isolates were obtained from 115 environmental samples (air, dust, feces, flies, sewage, and soil) collected along the laying hen production chain (breeding chicken, chick, young chicken, and commercial laying hen). These Enterococcus isolates exhibited resistance to some clinically relevant antibiotics, such as tetracycline (92.4%), streptomycin (92.4%), and erythromycin (91.4%), and all strains had multidrug resistance phenotypes. Whole genome sequencing characterized 29 acquired antibiotic resistance genes (ARGs) that conferred resistance to 11 classes of antibiotics in 51 pleuromutilin-resistant Enterococcus isolates, and lsa(E), which mediates resistance to pleuromutilins, always co-occurred with lnu(B). Alignments with the Mobile Genetic Elements database identified four transposons (Tn554, Tn558, Tn6261, and Tn6674) with several ARGs (erm(A), ant(9)-la, fex(A), and optrA) that mediated resistance to many clinically important antibiotics. Moreover, we identified two new transposons that carried ARGs in the Tn554 family designated as Tn7508 and Tn7492. A complementary approach based on conventional multi-locus sequence typing and whole genome single nucleotide polymorphism analysis showed that phylogenetically related pleuromutilin-resistant Enterococcus isolates were widely distributed in various environments on different production farms. Our results indicate that environmental contamination by antimicrobial-resistant Enterococcus requires greater attention, and they highlight the risk of pleuromutilin-resistant Enterococcus and ARGs disseminating along the laying hen production chain, thereby warranting effective disinfection.

Spatiotemporal Variability of Groundwater Iodine in the Northern Arid Basins: Significance for Safe Water Supply.

The genesis of geogenic iodine (I)-contaminated groundwater poses a significant threat to long-term water exploitation. Safe and sustainable water supply, particularly in the northern arid basins, demands a quantitative prediction of the high variability of I distribution over hydrogeological timescales. Here, bioenergetics-informed reactive transport modeling was combined with high-resolution molecular characterization of fueling organic matter to decipher the time-controlled interactions between vertical flow and (bio)geochemical processes in I transport within the Datong aquifers. The declining reactivities of I-bearing organic matter and Fe oxides in the 15-40 m depth decreased the rate of I release, while a growing number of pore volumes flushed through the aquifers to leach out I- and organic I. This removal effect is compensated by the desorption of I- from Fe oxides and secondary FeS generated from the concurrent reduction of Fe oxides and SO42-. Consequently, peak concentrations of groundwater I- may have appeared, depending upon the vertical recharge rate, at the first several pore volumes flushed through the aquifers. The current vertical distributions of the various I species likely represent a quasi-steady state between I mobilization and leaching. These new mechanistic insights into the dynamic hydrogeological-(bio)geochemical processes support secure groundwater use in the I-affected northern arid basins.

Groundwater Quality and Health: Making the Invisible Visible.

Linking groundwater quality to health will make the invisible groundwater visible, but there are knowledge gaps to understand the linkage which requires cross-disciplinary convergent research. The substances in groundwater that are critical to health can be classified into five types according to the sources and characteristics: geogenic substances, biogenic elements, anthropogenic contaminants, emerging contaminants, and pathogens. The most intriguing questions are related to quantitative assessment of human health and ecological risks of exposure to the critical substances via natural or induced artificial groundwater discharge: What is the list of critical substances released from discharging groundwater, and what are the pathways of the receptors' exposure to the critical substances? How to quantify the flux of critical substances during groundwater discharge? What procedures can we follow to assess human health and ecological risks of groundwater discharge? Answering these questions is fundamental for humans to deal with the challenges of water security and health risks related to groundwater quality. This perspective provides recent progresses, knowledge gaps, and future trends in understanding the linkage between groundwater quality and health.

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.

Prediction modeling of geogenic iodine contaminated groundwater throughout China.

Geogenic iodine-contaminated groundwater represents a threat to public health in China. Identifying high-iodine areas is essential to guide the mitigation of this problem. Considering that traditional analytical techniques for iodine testing are generally time-consuming, laborious, and expensive, alternative methods are needed to supplement and enhance existing approaches. Therefore, we developed an artificial neural network (ANN) model and assessed its feasibility in terms of predicting high iodine levels in groundwater in China. A total of 22 indicators (including climate, topography, geology, and soil properties) and 3185 aggregated samples (measured groundwater iodine concentrations) were utilized to develop the ANN model. The results showed that the accuracy and area under the receiver operating characteristic curve of the model on the test dataset are 90.9% and 0.972, respectively, and climate and soil variables are the most effective predictors. Based on the prediction results, a high-resolution (1-km) nationwide prediction map of high-iodine groundwater was produced. The high-risk areas are mainly concentrated in the central provinces of Henan, Shaanxi, and Shanxi, the eastern provinces of Henan, Shandong, and Hebei, and the northeastern provinces of Liaoning, Jilin, and Heilongjiang. The total number of people estimated to potentially be at high-risk areas because they use untreated high-iodine groundwater as drinking water is approximately 30 million. Considering the growing demand for groundwater in China, this work can guide the prioritization of groundwater contamination mitigation efforts based on regional groundwater quality levels to enhance environmental management.

Predicting geogenic groundwater fluoride contamination throughout China.

Endemic fluorosis exists in almost all provinces of China. The long-term ingestion of groundwater containing high concentrations of fluoride is one of the main causes of fluorosis. We used artificial neural network to model the relationship between groundwater fluoride concentrations from throughout China and environmental variables such as climatic, geological. and soil parameters as proxy predictors. The results show that the accuracy and area under the receiver operating characteristic curve of the model in the test dataset are 80.5% and 0.86%, respectively, and climatic variables are the most effective predictors. Based on the artificial neural network model, a nationwide prediction risk map of fluoride concentrations exceeding 1.5 mg/L with a 0.5 × 0.5 arc minutes resolution was generated. The high risk areas are mainly located in western provinces of Xinjiang, Tibet, Qinghai, and Sichuan, and the northern provinces of Inner Mongolia, Hebei and Shandong. The total number of people estimated to be potentially at risk of fluorosis due to the use of untreated high fluoride groundwater as drinking water is about 89 million, or 6% of the population. The high fluoride groundwater risk map helps the authorities to prioritize areas requiring mitigation measures and thus facilitates the implementation of water improvement and defluoridation projects.

Characterization and whole-genome sequencing of broad-host-range Salmonella-specific bacteriophages for bio-control.

Salmonella Enteritidis (S. Enteritidis), which could cause human disease and death by consuming the contaminated food, is an important zoonotic pathogen. With the rapid increase of antibiotic resistance all over the world, bacteriophage-based bio-control has gradually attracted public attention widely. In order to find a suitable phage treating S. Enteritidis infection, four phages infecting S. Enteritidis were isolated from poultry fecal samples. Host range showed that four phages had a broad-host-range to Salmonella isolates. The morphological analysis illustrated that all of those phages were classified as the Myoviridae family. The one-step growth curve indicated that bacteriophage BPSELC-1 has a short latent period of about 10 min and a large burst size of 500 pfu/cell in comparison to the other three phages. Then phage BPSELC-1 was sequenced and conducted in vitro experiment. The genome of phage BPSELC-1 is 86,996 bp in size and has 140 putative genes containing structure proteins-encoding genes, tRNA genes and DNA replication or nucleotide metabolism genes. Importantly, no known virulence-associated, antibiotic and lysogeny-related genes were identified in the genome of BPSELC-1. In vitro experiment of phage treatment pointed out that the number of viable S. Enteritidis ATCC 13076 was reduced by 5.9×log10 at MOI of 102 after 4 h. To the best of our knowledge, the phage BPSELC-1 exhibited higher efficiency in S. Enteritidis treatment compared to previous studies. Moreover, it is promising to be used as a broad-spectrum candidate against Salmonella infections in commercial owing to its broad-host-range.

Iron isotope evidence for arsenic mobilization in shallow multi-level alluvial aquifers of Jianghan Plain, central China.

Intake of groundwater with arsenic (As) concentrations exceeding the World Health Organization standard of 10 µg L-1 adversely impacts over 100 million people worldwide. Geogenic As contaminated groundwater within central Yangtze River Basin has recently been reported, but the variations within different depths of aquifers are not commonly observed and the processes controlling As variations have yet to be resolved. Here we report the significant As variations within two different depths (10 m and 25 m) of shallow multi-level alluvial aquifers at Jianghan Plain, a floodplain in the central Yangtze River Basin, which is also a recently discovered geogenic As affected area with cases of waterborne arsenicosis. The multi-year monitoring of aquifer chemistry results show that the As concentrations increase with the Fe(II) concentrations when As contents are relatively lower (<200 µg L-1) in upper phreatic aquitard (at 10 m depth), while decrease with Fe(II) concentrations when As contents are much greater in lower confined aquifer (at 25 m depth), and the highest is up to 1070 µg L-1. Iron isotope analysis were conducive to characterize Fe cycling in the aquifers and thus illustrate geochemical processes controlling As mobilization of shallow groundwaters. Results showed that groundwater is generally enriched in isotopically light Fe with δ56Fe values between - 1.60‰ and + 0.06‰ (median - 0.55‰). In the upper phreatic aquitard, microbial reductive dissolution of As-associated Fe(III) oxides, hydroxides and oxyhydroxides is the major process controlling As concentrations lower than 200 µg L-1. The reduction process could lead to the increasing As concentrations with the gradually increasing δ56Fe values, and a positive correlation between Fe and Î´56Fe, and between dissolved As and δ56Fe values is observed, respectively. In strongly reducing conditions as the lower confined aquifer, jointly microbial reduction of sulfate promotes the As mobilization through HS- abiotic reduction of Fe(III) minerals, resulting in As concentrations greater than 200 µg L-1. These findings could provide new insights for differentiating the major factors controlling As mobilization at different depths of aquifers, and provide better water managements for similar geogenic As-affected shallow alluvial aquifers.

Electrochemically induced oxidative precipitation of Fe(II) for As(III) oxidation and removal in synthetic groundwater.

Mobilization of Arsenic in groundwater is primarily induced by reductive dissolution of As-rich Fe(III) oxyhydroxides under anoxic conditions. Creating a well-controlled artificial environment that favors oxidative precipitation of Fe(II) and subsequent oxidation and uptake of aqueous As can serve as a remediation strategy. We reported a proof of concept study of a novel iron-based dual anode system for As(III) oxidation and removal in synthetic groundwater. An iron anode was used to produce Fe(II) under iron-deficient conditions, and another inert anode was used to generate O2 for oxidative precipitation of Fe(II). For 30 min's treatment, 6.67 µM (500 µg/L) of As(III) was completely oxidized and removed from the solution during the oxidative precipitation process when a total current of 60 mA was equally partitioned between the two anodes. The current on the inert anode determined the rate of O2 generation and was linearly related to the rates of Fe(II) oxidation and of As oxidation and removal, suggesting that the process could be manipulated electrochemically. The composition of Fe precipitates transformed from carbonate green rust to amorphous iron oxyhydroxide as the inert anode current increased. A conceptual model was proposed for the in situ application of the electrochemically induced oxidative precipitation process for As(III) remediation.

Response of growth and superoxide dismutase to enhanced arsenic in two Bacillus species.

Species differences in inorganic arsenic tolerance were investigated by comparing the responses of Bacillus subtilis (B. subtilis) and Bacillus thuringiensis (B. thuringiensis) to elevated concentrations of As(III) and As(V). The cell densities in treatments were always lower during the experiment compared to controls, with the exception of exposure to 1.0 mg As(V) l(-1) on the first day. It was also found that relative growth rate (RGR) of B. thuringiensis was lower than that of B. subtilis. Furthermore, RGR of each Bacillus species was negative correlation with toxicity of inorganic arsenic. However, total cell number still increased in each treatment according to cell density and RGR assays. Superoxide dismutase (SOD) activity of both Bacillus species was promoted by As(III) and As(V), especially under high arsenic concentration condition. In addition, SOD activity of B. thuringiensis was higher than that of B. subtilis during the same exposure time. In lipid peroxidation assay, thiobarbituric acid-reactive substances (TBARS) content of each Bacillus species had a significant increase with increment of arsenic concentration. Moreover, significant difference was observed between the two Bacillus species under high arsenic concentration. TBARS content of B. thuringiensis was higher than that of B. subtilis, indicating that effect of arsenic on cell membranes of B. thuringiensis was much more than that of B. subtilis. These results suggest that the two Bacillus species could adapt and live in high arsenic aquifers, although their growth and cell membranes were affected by As treatment in a way.

Unraveling the role of anthropogenic and hydrologic drivers with respect to the optical and molecular properties of dissolved organic matter and organic phosphorus in a P-contaminated river.

Anthropogenic and hydrological drivers are key factors influencing the fate of dissolved organic matter (DOM) and dissolved organic phosphorus (DOP) in river runoff. However, how anthropogenic disturbances and hydrological conditions jointly affect the composition and characteristics of DOM and DOP in river runoff remains unclear. This study used fluorescence spectroscopy, Fourier transform ion cyclotron resonance mass spectrometry, and the stable water isotopes to interpret the chemical composition and properties of DOM and DOP as well as their linkages to anthropogenic disturbances and hydrological conditions in a typical P-contaminated tributary to the central Yangtze River. The results show in the wet season, the average abundance of humic-like components in DOM exceeded 60 %, while the average abundance of tryptophan-like components in DOM exceeded 50 % in the dry season. During the dry season, hydrological conditions had a greater impact on highly unsaturated DOM compounds compared to anthropogenic disturbances because a decrease in precipitation reduced the transport of terrestrial DOM into aquatic systems and increased water retention time in the river, promoting the production of unsaturated compounds from photochemistry. The effects of the two factors were similar in the wet season because active agricultural activities and intense precipitation jointly facilitated the entry of exogenous humics into the runoff, leading to the similar relative abundance of highly unsaturated DOM compounds associated with both factors. Anthropogenic disturbances had a greater impact on aliphatic DOM and DOP than hydrological conditions, which was associated with intense human activities in the watershed, such as phosphate mining, agricultural cultivation, and domestic sewage discharge. This study provides new knowledge about the composition, properties and underlying mechanisms of DOM and DOP in the P-contaminated watershed runoff.

Coupled redox cycling of arsenic and sulfur regulates thioarsenate enrichment in groundwater.

High­arsenic groundwater is influenced by a combination of processes: reductive dissolution of iron minerals and formation of secondary minerals, metal complexation and redox reactions of organic matter (OM), and formation of more migratory thioarsenate, which together can lead to significant increases in arsenic concentration in groundwater. This study was conducted in a typical sulfur- and arsenic-rich groundwater site within the Datong Basin to explore the conditions of thioarsenate formation and its influence on arsenic enrichment in groundwater using HPLC-ICPMS, hydrogeochemical modeling, and fluorescence spectroscopy. The shallow aquifer exhibited a highly reducing environment, marked by elevated sulfide levels, low concentrations of Fe(II), and the highest proportion of thioarsenate. In the middle aquifer, an optimal ∑S/∑As led to the presence of significant quantities of thioarsenate. In contrast, the deep aquifer exhibited low sulfide and high Fe(II) concentration, with arsenic primarily originating from dissolved iron minerals. Redox fluctuations in the sediment driven by sulfur­iron minerals generated reduced sulfur, thereby facilitating thioarsenate formation. OM played a crucial role as an electron donor for microbial activities, promoting iron and sulfate reduction processes and creating conditions conducive to thioarsenate formation in reduced and high­sulfur environments. Understanding the process of thioarsenate formation and the influencing factors is of paramount importance for comprehending the migration and redistribution of arsenic in groundwater systems.

Spectroscopic and modeling approaches of arsenic (III/V) adsorption onto Illite.

Illite plays an essential role in arsenic (As) transportation in the subsurface. Despite extensive investigations into As adsorption onto illite, debates persist due to the absence of direct evidence revealing the underlying processes. In this research, we conducted batch experiments and employed spherical aberration-corrected scanning transmission electron microscope, X-ray absorption spectroscopy, and density functional theory-based calculations to elucidate the mechanisms for the adsorption of two major inorganic As species (As(III) and As(V)) onto illite. Experimental results indicate adsorption capacities of 0.251 and 0.667 µmol/g for As(III) and As(V) onto illite, respectively. As(III) adsorption occurs within 300 min, whereas As(V) is rapidly adsorbed within 500 min, after which it tends to stabilize. Both As species can adsorbed onto the basal surface via electrostatic forces, where cations act as a bridge, leading to specific-cation effects. Conversely, As adsorption onto the edge surface can be ascribed to inner-sphere complexes via As-O-Al bonds, causing a negatively shifted isoelectric point of illite. These mechanisms collectively account for the partially reversible adsorption and two-stage kinetics pattern. Finally, a process-based surface complexation model was developed to predict As adsorption onto illite, which includes the inner/outer-sphere complexation and monodentate/bidentate complexes.

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.