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.

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.

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.

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.

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.

Arsenic biogeochemical cycling association with basin-scale dynamics of microbial functionality and organic matter molecular composition.

Geogenic arsenic (As)-contaminated groundwater is a sustaining global health concern that is tightly constrained by multiple interrelated biogeochemical processes. However, a complete spectrum of the biogeochemical network of high-As groundwater remains to be established, concurrently neglecting systematic zonation of groundwater biogeochemistry on the regional scale. We uncovered the geomicrobial interaction network governing As biogeochemical pathways by merging in-field hydrogeochemical monitoring, metagenomic analyses, and ultrahigh resolution mass spectrometry (FT-ICR MS) characterization of dissolved organic matter. In oxidizing to weakly reducing environments, the nitrate-reduction and sulfate-reduction encoding genes (narGHI, sat) inhibited the dissolution of As-bearing iron minerals, leading to lower As levels in groundwater. In settings from weakly to moderately reducing, high abundances of sulfate-reduction and iron-transport encoding genes boosted iron mineral dissolution and consequent As release. As it evolved to strongly reducing stage, elevated abundance of methane cycle-related genes (fae, fwd, fmd) further enhanced As mobilization in part by triggering the formation of gaseous methylarsenic. During redox cycling of N, S, Fe, C and As in groundwater, As migration to groundwater and immobilization in mineral particles are geochemically constrained by basin-scale dynamics of microbial functionality and DOM molecular composition. The study constructs a theoretical model to summarize new perspectives on the biogeochemical network of As cycling.

Unravelling the impacts of soluble Mn(III)-NOM on arsenic immobilization by ferrihydrite or goethite under aquifer conditions.

The environmental fate of arsenic (As) relies substantially on its speciation, which occurs frequently coupled to the redox transformation of manganese. While trivalent manganese (Mn(III)), which is known for its high reactivity, is believed to play a role in As mobilization by iron (oxyhydr)oxides in dynamic aquifers, the exact roles and underlying mechanisms are still poorly understood. Using increasingly complex batch experiments that mimick As-affected aquifer conditions in combination with time-resolved characterization, we demonstrate that Mn(III)-NOM complexes play a crucial role in the manganese-mediated immobilization of As(III) by ferrihydrite and goethite. Under anaerobic condition, Mn(III)-fulvic acid (FA) rapidly oxidized 31.8% of aqueous As(III) and bound both As(III) and As(V). Furthermore, Mn(III)-FA exerted significantly different effects on the adsorption of As by ferrihydrite and goethite. Mn(III)-FA increased the adsorption of As by 6-16% due to the higher affinity of oxidation-produced As(V) for ferrihydrite under circumneutral conditions. In contrast, As adsorption by crystalline goethite was eventually inhibited due to the competitive effect of Mn(III)-FA. To summarize, our results reveal that Mn(III)-NOM complexes play dual roles in As retention by iron oxides, depending on the their crystallization. This highlights the importance of Mn(III) for the fate of As particularly in redox fluctuating groundwater environments.

Effects of recharge and discharge on delta2H and delta18O composition and chloride concentration of high arsenic/fluoride groundwater from the Datong Basin, northern China.

To better understand the effects of recharge and discharge on the hydrogeochemistry of high levels of arsenic (As) and fluoride (F) in groundwater, environmental isotopic composition (delta2H and delta18O) and chloride (Cl) concentrations were analyzed in 29 groundwater samples collected from the Datong Basin. High arsenic groundwater samples (As > 50 micog/L) were found to be enriched in lighter isotopic composition that ranged from -92 to -78 per thousand for deuterium (delta2H) and from -12.5 to -9.9 per thousand for oxygen-18 (delta18O). High F-containing groundwater (F > 1 mg/L) was relatively enriched in heavier isotopic composition and varied from -90 to -57 per thousand and from -12.2 to -6.7 per thousand for delta2H and delta18O, respectively. High chloride concentrations and delta18O values were primarily measured in groundwater samples from the northern and southwestern portions of the study area, indicating the effect of evaporation on groundwater. The observation of relatively homogenized and low delta18O values and chloride concentrations in groundwater samples from central part of the Datong Basin might be a result of fast recharge by irrigation returns, which suggests that irrigation using arsenic-contaminated groundwater affected the occurrence of high arsenic-containing groundwater in the basin.

Novel insight into arsenic enrichment in aquifer sediments under different paleotemperatures from a molecular-level characterization of sedimentary organic matter.

The heterogeneous distribution of As in sediments is governed by the abundance and type of SOM, which is closely associated with the depositional environment. However, few studies have revealed the effect of depositional environment (e.g., paleotemperature) on As sequestration and transport in sediments from the perspective of the molecular characteristics of sedimentary organic matter (SOM). In this study, we characterized the optical and molecular characteristics of SOM coupled with organic geochemical signatures to illustrate in detail the mechanisms of sedimentary As burial under different paleotemperatures. We identified that alternating paleotemperature changes result in the fluctuation of H-rich and H-poor organic matter in sediments. Further, we found aliphatic and saturated compounds with higher nominal oxidation state of carbon (NOSC) values predominate under high-paleotemperature (HT) conditions, while polycyclic aromatics and polyphenols with lower NOSC values accumulate under low-paleotemperature (LT) conditions. Under LT conditions, thermodynamically favorable organic compounds (higher NOSC values) are preferentially degraded by microorganisms to provide sufficient energy to sustain sulfate reduction, favoring sedimentary As sequestration. Under HT conditions, the energy gained from the decomposition of low NOSC value organic compounds approaches the energy required to sustain dissimilatory Fe reduction, leading to sedimentary As release into groundwater. This study provides molecular-scale evidence of SOM that indicates LT depositional environments favor sedimentary As burial and accumulation.

Insights into the selectivity of metallic oxides for arsenic and phosphate from EXAFS and DFT calculations.

Phosphate is the biggest competitor for arsenic removal. Nanoscale metal oxides (NMOs) are commonly used to treat arsenic-contaminated water, yet their selective adsorption mechanisms for arsenic and phosphate are poorly understood. We quantified the selectivity of iron oxide (Fe2O3), zinc oxide (ZnO), and titanium dioxide (TiO2) nanosheets for arsenic in systems containing arsenic and phosphate, and determined the interaction of phosphate and arsenate/arsenite on metal oxide surfaces through batch experiments, spectroscopic techniques, and DFT calculations. We found that Fe2O3, TiO2, and ZnO nanosheets exhibit selectivity for arsenate/arsenite in the presence of phosphate, with Fe2O3 the most selective, followed by TiO2 and ZnO. The bonding mechanism on these metallic oxide surfaces dominates the selectivity. The more stable inner-sphere complexes of arsenate on the surfaces of Fe2O3 (bidentate binuclear), TiO2 (bidentate binuclear), and ZnO nanosheets (tridentate trinuclear) contribute to their preference for arsenate over phosphate. This difference in arsenate selectivity can be reflected in the difference in adsorption energy, net electron transfer number, and M - O bond length of the most stable inner sphere complexes. Overall, our study elucidated the selective adsorption mechanisms of arsenate/arsenite on Fe2O3, TiO2, and ZnO surfaces and highlighted the need to consider the competition between arsenate and phosphate during their removal from contaminated water.