Mechanisms of arsenic contamination associated with hydrochemical characteristics in coastal alluvial aquifers using multivariate statistical technique and hydrogeochemical modeling: a case study in Rayong province, eastern Thailand

Marine microplastics enhance release of arsenic in coastal aquifer during seawater intrusion process

Microplastics (MPs), omnipresent contaminants in the ocean, could be carried by seawater intrusion into coastal aquifers, which might affect the fate of heavy metals existing in aquifers. Herein, we investigated the release behavior of arsenic (As) in coastal aquifers during MPs-containing seawater intrusion by applying laboratory experiment and numerical simulation. We found that seawater with marine MPs enhanced the release of As in aquifers, especially for dissolved As(V) and colloidal As. Negatively charged MPs competed with As(V) for the adsorption sites on iron (hydr)oxides in aquifers, resulting in the desorption of As(V). In addition, MPs could promote the release of Fe-rich colloids by imparting negative charge to its surface and providing it with sufficient repulsive force to detach from the matrix, thereby leading to the release of As associated with Fe-rich colloid. We also developed a modeling approach that well described the transport of As in coastal aquifer under the impact of MPs, which coupled variable density flow and kinetically controlled colloids transport with multicomponent reactive transport model. Our findings elucidated the enhancement of MPs on the release of As in aquifers during seawater intrusion, which provides new insights into the risk assessment of MPs in coastal zones.

Integrating machine learning models with cross-validation and bootstrapping for evaluating groundwater quality in Kanchanaburi province, Thailand

Exploring the potential of new models for mapping groundwater quality presents a major challenge in water resource management, particularly in Kanchanaburi Province, Thailand, where groundwater faces contamination risks. This study aimed to explore the applicability of random forest (RF) and artificial neural networks (ANN) models to predict groundwater quality. Particularly, these two models were integrated into cross-validation (CV) and bootstrapping (B) techniques to build predictive models, including RF-CV, RF-B, ANN-CV, and ANN-B. Entropy groundwater quality index (EWQI) was converted to normalized EWQI which was then classified into five levels from very poor to very good. A total of twelve physicochemical parameters from 180 groundwater wells, including potassium, sodium, calcium, magnesium, chloride, sulfate, bicarbonate, nitrate, pH, electrical conductivity, total dissolved solids, and total hardness, were investigated to decipher groundwater quality in the eastern part of Kanchanaburi Province, Thailand. Our results indicated that groundwater quality in the study area was primarily polluted by calcium, magnesium, and bicarbonate and that the RF-CV model (RMSE = 0.06, R2 = 0.87, MAE = 0.04) outperformed the RF-B (RMSE = 0.07, R2 = 0.80, MAE = 0.04), ANN-CV (RMSE = 0.09, R2 = 0.70, MAE = 0.06), and ANN-B (RMSE = 0.10, R2 = 0.67, MAE = 0.06). Our findings highlight the superiority of the RF models over the ANN models based on the CV and B techniques. In addition, the role of groundwater parameters to the normalized EWQI in various machine learning models was found. The groundwater quality map created by the RF-CV model can be applied to orient groundwater use.

Integrated Approach to Hydrogeochemical Assessment of Groundwater Quality in Major Industrial Zone of Punjab, Pakistan

Groundwater contamination with arsenic (As) is a significant concern in Pakistan's Punjab Province. This study analyzed 69 groundwater samples from Faisalabad, Gujranwala, Lahore, and Multan to understand hydrogeochemistry, health impacts, contamination sources, and drinking suitability. Results revealed varying as concentrations across districts, with distinctive cation and anion orders. Faisalabad exhibited Na+ > Mg2+ > Ca2+ > K+ > Fe2+ for cations and SO42- > Cl- > HCO3- > NO3- > F- for anions. Gujranwala showed Na+ > Ca2+ > Mg2+ > K+ for cations and HCO3-  > SO42- > Cl- > NO3-  > F- for anions. In Lahore, demonstrated: Na+ > Ca2+ > Mg2+ > Fe > K+ for cations and HCO3-  > SO42- > Cl- > NO3-  > F- for anions. Multan indicated K+ > Ca2+ > Mg2+ > Na+ > Fe for cations and HCO3-  > SO42- > Cl- > F- > NO3- ) for anions. Hydrochemical facies were identified as CaHCO3 and CaMgCl types. Principal Component Analysis (PCA), highlighted the influence of natural processes and human activities on groundwater pollution. Water Quality Index (WQI) result reveal that most samples met water quality standards. The carcinogenic risk values for children exceeded permissible limits in all districts, emphasizing a significant cancer risk. The study highlights the need for rigorous monitoring to mitigate (As) contamination and protect public health from associated hazards.

Study on inverse geochemical modeling of hydrochemical characteristics and genesis of groundwater system in coal mine area - a case study of Longwanggou Coal Mine in Ordos Basin

The exploitation of coal resources has disturbed the equilibrium of the original groundwater system, resulting in a perturbation of the deep groundwater dynamic conditions and hydrochemical properties. Exploring the formation of mine water chemistry under the conditions of deep coal seam mining in the Ordos Basin provides a theoretical basis for the identification of sources of mine water intrusion and the development and utilization of water resources. This paper takes Longwanggou Coal Mine as the research area, collects a total of 106 groups of water samples from the main water-filled aquifers, comprehensively uses Piper trilinear diagram, Gibbs diagram, ion correlation, ion ratio coefficient and mineral saturation index analysis, and carries out inverse geochemical modeling with PHREEQC software, so as to analyze the hydrochemical characteristics and causes of the main water-filled aquifers in deep-buried coal seams in the research area. The results show that the main hydrochemical processes in the study area are leaching and cation exchange, and the groundwater is affected by carbonate (calcite, dolomite), silicate (gypsum) and evaporite. Calculations of mineral saturation indices and PHREEQC simulations have led to the conclusion that the dissolution of rock salt and gypsum in groundwater accounts for most of the ionic action. Na+, Cl- and SO42- are mainly derived from the dissolution of rock salt and gypsum minerals, while Ca2+ and Mg2+ are mostly derived from the dissolution of dolomite and calcite. The results of the inverse geochemical modeling are consistent with the theoretical analysis.

Rapid groundwater decline and some cases of recovery in aquifers globally

Groundwater resources are vital to ecosystems and livelihoods. Excessive groundwater withdrawals can cause groundwater levels to decline1-10, resulting in seawater intrusion11, land subsidence12,13, streamflow depletion14-16 and wells running dry17. However, the global pace and prevalence of local groundwater declines are poorly constrained, because in situ groundwater levels have not been synthesized at the global scale. Here we analyse in situ groundwater-level trends for 170,000 monitoring wells and 1,693 aquifer systems in countries that encompass approximately 75% of global groundwater withdrawals18. We show that rapid groundwater-level declines (>0.5 m year-1) are widespread in the twenty-first century, especially in dry regions with extensive croplands. Critically, we also show that groundwater-level declines have accelerated over the past four decades in 30% of the world's regional aquifers. This widespread acceleration in groundwater-level deepening highlights an urgent need for more effective measures to address groundwater depletion. Our analysis also reveals specific cases in which depletion trends have reversed following policy changes, managed aquifer recharge and surface-water diversions, demonstrating the potential for depleted aquifer systems to recover.

Appraisal of groundwater quality with WQI and human health risk assessment in Karamık wetland and surroundings (Afyonkarahisar/Turkey)

Groundwater in Karamık wetland and surroundings, which is one of the important wetlands in Turkey, was examined and the chemical properties and quality of groundwater were determined in the present study. In addition, the possible risks to human health as a result of groundwater usage were investigated along with spatial analyses carried out using Geographic Information Systems (GIS). Physicochemical analyses were carried out on 25 samples taken from groundwater. The dominant ions in the study area are Ca, Mg, and HCO₃. When the results are compared with the limit values in the valid drinking water guidelines such as TSI-266 (Standards for drinking waters, 2005) and WHO (Guidelines for drinking-water quality, 2011), the groundwaters were not suitable for use as drinking water in terms of NO₃, Fe, Pb and As. The analysis results were evaluated together with GIS and Water Quality Index (WQI) methods. In the evaluations with the WQI method, 76% of the samples were in the "poor water" class. The groundwater in the study area is polluted by both geogenic and anthropogenic sources. For this reason, health risk assessment was performed due to the use of groundwater in the region by the local people in different areas, especially as drinking water, and the negative effects of water quality. Accordingly, there are non-carcinogenic negative effects on health in terms of NO₃, As, Pb and Fe parameters from the use of groundwater by children. In addition, Pb and As concentrations are at carcinogenic levels for both children and adults in all groundwater samples collected from the study area. Therefore, it is not recommended to use groundwater as drinking water without treatment.

The risk assessment of arsenic contamination in the urbanized coastal aquifer of Rayong groundwater basin, Thailand using the machine learning approach

The rapid expansion of urbanization has resulted in an insufficient of groundwater resource. In order to use groundwater more efficiently, a risk assessment of groundwater pollution should be proposed. The present study used machine learning with three algorithms consisting of Random Forest (RF), Support Vector Machine (SVM), and Artificial Neural Network (ANN) to locate risk areas of arsenic contamination in Rayong coastal aquifers, Thailand and selected the suitable model based on model performance and uncertainty for risk assessment. The parameters of 653 groundwater wells (Deep=236, Shallow=417) were selected based on the correlation of each hydrochemical parameters with arsenic concentration in deep and shallow aquifer environments. The models were validated with arsenic concentration collected from 27 well data in the field. The model's performance indicated that the RF algorithm has the highest performance as compared to those of SVM and ANN in both deep and shallow aquifers (Deep: AUC=0.72, Recall=0.61, F1 =0.69; Shallow: AUC=0.81, Recall=0.79, F1 =0.68). In addition, the uncertainty from the quantile regression of each model confirmed that the RF algorithm has the lowest uncertainty (Deep: PICP=0.20; Shallow: PICP=0.34). The result of the risk map obtained from the RF reveals that the deep aquifer, in the northern part of the Rayong basin has a higher risk for people to expose to As. In contrast, the shallow aquifer revealed that the southern part of the basin has a higher risk, which is also supported by the location of the landfill and industrial estates in the area. Therefore, health surveillance is important in monitoring the toxic effects on the residents who use groundwater from these contaminated wells. The outcome of this study can help policymakers in regions to manage the quality of groundwater resources and enhance the sustainable use of groundwater resources. The novelty process of this research can be used to further study other groundwater aquifers contaminated and increase the effectiveness of groundwater quality management.

The influence mechanism of hydrogeochemical environment and sulfur and nitrogen cycle on arsenic enrichment in groundwater: A case study of Hasuhai basin, China

Hydro-biogeochemical processes control the formation and evolution of high arsenic (As) groundwater. However, the effects of nitrogen and sulfur cycles in groundwater on As migration and transformation are not well understood. Thus, twenty-one groundwater samples were collected from the Hasuhai basin. Hydrochemistry and geochemical modeling were used to analyze the geochemical processes associated with nitrogen and sulfur cycles. An arsenic speciation model (AM) and a sulfide-As model (SAM) were constructed to verify the existence of As species and the formation mechanism of thioarsenate. A hydrous ferric oxide (Hfo)-As adsorption model (HAM) and a competitive adsorption model (CAM) were used to reveal the adsorption and desorption mechanisms of As. The results showed that high arsenic groundwater (As > 10 μg/L) was mainly distributed under reductive conditions, and the highest concentration was 231.5 μg/L. The modeling results revealed that sulfides were widely involved in the geochemical cycle of As, with H₃AsO₃ and H₂AsO₃^- accounting for >70 % of the total As, and thioarsenate accounting for 30 %. S/As < 2.5 and S/Fe < l control the formation of thioarsenate. With the high correlation of NH₄⁺, TFe, sulfide, and TAs, the co-mobilization of N and S cycles may facilitate As enrichment in groundwater. A weak alkaline reduction environment triggered by the decomposition of organic matter was the main factor leading to the transfer of As from the aquifer to the groundwater. This research contributes to the development of high-As groundwater, and the findings are of general significance for drinking water in the Hasuhai Basin.

Formation mechanism of hydrogeochemical characterization of mineral water in Antu County, Changbai Mountain area

Antu County in the Changbai Mountains is an important source of mineral water, but there is a lack of research on the source of groundwater characteristic components, affecting the protection of water resources. This study obtained hydrochemical and isotopic data (28 groups in total, April and September in 2019) by summarizing research and sampling data in order to identify the formation process of characteristics. The formation mechanism of the characteristic components was revealed using geostatistical, isotopic, and hydrogeochemical inversion simulations. The results show that the metasilicic acid is a common component of groundwater water chemistry in the study area. The water body primarily receives stable recharge from low-mineralized precipitation with ages ranging from 27.7 to 38.4 years and recharge elevations ranging from 1160 to 2393 m, providing ample time for water-rock interaction. The dissolution of olivine, pyroxene, albite, and other siliceous minerals is the source of characteristic components, and deep faults and deep basalt heat flow are the key conditions for the formation of metasilicic acid. When low-mineralized precipitation recharges the underground aquifer, it dissolves the silica-aluminate and silicon-containing minerals in the surrounding rocks through the water-rock action under the effect of CO₂, causing a large amount of metasilic acid to dissolve into the groundwater and forming metasilic acid-type mineral water.

Acid mine drainage potential of waste rocks in a gold mine (Thailand): application of a weathering cell test and multivariate statistical analysis

In the process of gold mining, large amounts of broken waste rocks are produced and left at the surface under atmospheric conditions, which may generate acid mine drainage (AMD). This study aimed to predict the AMD generation potential and determine the concentrations of potentially toxic metals at three dump sites for a gold mine in Thailand. The AMD generation potentials of waste rock samples collected from the oxide, transition and sulfide dump sites was determined using the weathering cell test. The kinetic test had a 7-d cycle and was run for ~ 21 cycles; the effluent pH, conductivity, redox potential and levels of sulfate, and major and trace metals (i.e., As, Co, Cu, Fe, Mn, Pb and Zn) present in each cycle were measured. Some samples generated significant amounts of AMD, especially the massive sulfide samples from the transition and sulfide dump sites. The effluent water pH in the oxide and sulfide dump sites was neutral to slightly alkaline (pH ~ 6-9), while it was acidic to neutral (pH ~ 3-7) in the transition dump site. The transition dump site samples generated significantly higher acidity and sulfate levels than those from the oxide and sulfide dump sites. Furthermore, some waste rock samples, including the massive sulfide from the transition dump site, released relatively high amounts of heavy metals; in addition, sulfate reached levels (9.48 mg kg^-1 of waste rock) high enough to pose a risk to ecosystems. The long-term acid generation suggested that some waste rock samples from sulfide dump site and transition dump site will continue to generate acid for long periods. Based on data from the weathering cell test and multivariate statistical analysis, the transition dump site potentially generates a lower pH leachate than other waste rock dumps.

Aqueous Arsenic Speciation with Hydrogeochemical Modeling and Correlation with Fluorine in Groundwater in a Semiarid Region of Mexico

In arid and semiarid regions, groundwater becomes the main source to meet the drinking water needs of large cities, food production, and industrial activities. For this reason, necessary studies must be carried out to estimate its quantity and quality, always seeking sustainable management, thus avoiding social conflicts or a decrease in the productive activities of humanity. This research explains the behavior of groundwater quality concerning arsenic speciation and its relationship with fluoride. The average total arsenic concentration of 19.95 µg/L and 20.29 µg/L is reported for the study period from 2015 to 2020, respectively, according to the Mexican standard. If the population drinks water directly, it is exposed to possible damage to health. The predominant arsenic species is As (V), with 95% and As (III) with 5%, this finding will allow us to define in greater detail the type of remediation that is required to reduce the content of this element in the water. Regarding the relationship between arsenic and fluorine, very small Pearson correlation coefficients of the order of 0.3241 and 0.3186 were found. The estimation of the space–time variation made it possible to identify the areas with the highest concentration of arsenic and fluorine, allowing the definition of the operating policies of these wells, thereby protecting the health of the inhabitants who consume this water.

Exploration of Hydrogeochemical Characterization and Assessment of Organic Pollution Characteristics of Shallow Groundwater near a Chemical Plant That Discharged Sewage Illegally

Groundwater plays a significant role in domestic use and agricultural irrigation in rural areas of northern China. The untreated wastewater from the chemical plant was directly discharged into a seepage well, resulting in the pollution of groundwater. Assessing characteristics of groundwater organic pollution and identifying evolutionary mechanisms of hydrogeochemistry are beneficial for groundwater protection and sustainable management. Statistical methods (correlation analysis (CA) and principal component analysis (PCA)) combined with hydrogeochemical methods including Piper, Gibbs, Gaillardet, and ions binary diagrams and the chloride alkalinity index were employed to explore hydrogeochemical characteristics and evolutionary mechanisms. The results showed that cations were predominantly located at the Ca2+ end and anions were mostly close to the SO42− and Cl− end. The ion concentrations of groundwater were mainly affected by water–rock interactions. The weathering or dissolution of silicate (i.e., aluminosilicate minerals), evaporite (i.e., halite and gypsum), carbonate minerals (i.e., calcite and dolomite), cation exchange, and anthropogenic activities contribute to the chemical compositions of groundwater. Based on CA and PCA, the dissolution of halide minerals and the use of pesticides and fertilizers were the main factors controlling water chemistry. Additionally, the dissolution of sulfur-bearing minerals and gypsum was the key factor controlling the concentrations of Ca2+ and Mg2+. Application of mathematical statistical methods characterized that the exceedance rate of seven organic compounds with high detection rates were as follows: carbon tetrachloride (39.83%) > 1,1,2-trichloroethane (28.81%) > chloroform (10.17%) > trichloroethene (6.78%) > 1,1,2,2-tetrachloroethane (5.93%) > perchloroethylene (5.08%) > trichlorofluoromethane (0.85%). Simultaneously, pollution under the influence of volatilization and diffusion was significantly less than that in the direction of groundwater runoff.

Hydrogeochemistry, identification of hydrogeochemical evolution mechanisms, and assessment of groundwater quality in the southwestern Ordos Basin, China

Understanding the evolution process of hydrogeochemistry and groundwater quality is essential for water supply and health in the southwestern Ordos Basin, where groundwater is a vital source for drinking. This study systematically illustrates the hydrogeochemical characteristics and evolution mechanism based on the groundwater samples (n = 67) collected from Loess area by integrating multivariate statistical methods and hydrogeochemical methods. Furthermore, the entropy water quality index (EWQI) and water quality indices combined with spatial analysis were employed to evaluate the suitability of groundwater for drinking and irrigation purposes and analyze the spatial variation of water quality. The hierarchical cluster analysis and principal component analysis classified groundwater dataset into four clusters and four components which were examined using a Piper diagram and Gibbs diagram, representing different hydrogeochemical characteristics and controlling factors. Based on results, the groundwater chemistry was characterized by representative water types: freshwater (cluster 1, cluster 2), low salinity (half of cluster 3), high salinity (half of cluster 3, cluster 4), and the main controlling factors of hydrogeochemistry revealed by Gibbs diagram were evaporation crystallization (cluster 3, cluster 4) and water-rock interactions (cluster 1, cluster 2). Moreover, the Gaillardet diagram, chloro-alkaline indices, binary diagram, and saturation index further comprehensively illustrate that the silicate and evaporite weathering, ion exchange, dissolution of halite, gypsum, and anhydrite are responsible for hydrogeochemical process. Based on EWQI and ArcGIS, the groundwater quality is categorized as excellent (47.0%), good (31.8%), medium (4.5%), poor (6.1%), and extremely poor (10.6%) types, and the quality in the south of the study area is better than north. Additionally, the USSL diagram shows that most of samples belong to C3S1 (high-salinity hazard and low-sodium hazard) and C2S1 (medium-salinity hazard and low-sodium hazard), and Wilcox diagram shows that 77.2% of samples are suitable for irrigation.

Hydrogeochemical Assessment of Groundwater and Suitability Analysis for Domestic and Agricultural Utility in Southern Punjab, Pakistan

Groundwater is a critical water supply for safe drinking water, agriculture, and industry worldwide. In the Khanewal district of Punjab, Pakistan, groundwater has severely deteriorated during the last few decades due to environmental changes and anthropogenic activities. Therefore, 68 groundwater samples were collected and analyzed for their main ions and trace elements to investigate the suitability of groundwater sources for drinking and agricultural purposes. Principal component analysis (PCA) and cluster analysis (CA) were employed to determine the major factors influencing groundwater quality. To assess the groundwater’s appropriateness for drinking and irrigation, drinking and agricultural indices were used. The pH of the groundwater samples ranged from 6.9 to 9.2, indicating that the aquifers were slightly acidic to alkaline. The major cations were distributed as follows: Na+ > Ca2+ > Mg2+ > K+. Meanwhile, the anions are distributed as follows: HCO3− > SO42− > Cl− > F−. The main hydrochemical facies were identified as a mixed type; however, a mixed magnesium, calcium, and chloride pattern was observed. The reverse ion exchange process helps in exchanging Na+ with Ca2+ and Mg2+ ions in the groundwater system. Rock weathering processes, such as the dissolution of calcite, dolomite, and gypsum minerals, dominated the groundwater hydrochemistry. According to the Weight Arithmetic Water Quality Index (WAWQI), 50% of the water samples were unsafe for drinking. The Wilcox diagram, USSL diagram, and some other agricultural indices resulted in around 32% of the groundwater samples being unsuitable for irrigation purposes. The Khanewal’s groundwater quality was vulnerable due to geology and the influence of anthropogenic activities. For groundwater sustainability in Khanewal, management strategies and policies are required.

Shallow groundwater environmental investigation at northeastern Cairo, Egypt: quality and photo-treatment evaluation

Groundwater represents the primary source of freshwater for more than 35% of world people, and its contamination became a worldwide challenge. Egypt is suffering from water quantity and quality, especially in desert areas. El Obour city and environs Northeast Cairo face waterlogging owing to the elevated-shallow groundwater table. In the present research work, the water quality of the shallow groundwater aquifer was studied. The remediation efficiency of polluted water using photocatalytic treatment technique in the presence of modified nano-titania and solar radiation has also been investigated. Twenty-eight representative samples have been collected from different locations, and their microbial, physical, and chemical characteristics were determined. The average contents of Pb (214.96 µg/L), As (1517 µg/L), Cd (8.79 µg/L), total bacterial count (2.22 × 10⁵ CFU/ml), and bacterial indicators (MPN-index/100 ml): total coliform (497.4), fecal coliform (358.3), and fecal streptococci (115.9) were higher than WHO permissible limits for drinking water, possibly due to higher industrialization, agricultural, and urbanization rates. The organic pollutants reached critical concentrations (chemical oxygen demand up to 960.8 mg O₂/L). Most of the studied samples contained acceptable concentrations of the major ions, (e.g., K⁺, Mg²⁺, HCO₃^-), for drinking and irrigation purposes. The statistical analyses (e.g., principal component analysis and cluster analysis) pointed out the control of water-rock interaction and anthropogenic activities in water composition. The hydrochemical data show that most of the water samples (96.4%) are Na₂SO₄ and NaHCO₃ type, indicating its meteoric origin. The contamination with human and animal fecal substances, NO₃^¯, and NH₄⁺ was identified in all samples, which pointed out the control of anthropogenic activities in water pollution. The photocatalytic technique efficiently eliminated more than 82-95% of organic contents and microbial pollutants, respectively, but it was inefficient in reducing heavy metal levels. According to the current results, shallow groundwater injection into the deep aquifer must be constrained and reusable after treatment. Finally, more studies are imperative to disseminate the applied treatment techniques to elude bacteria and organic pollutants from water at a pilot scale.

Human biomarkers associated with low concentrations of arsenic (As) and lead (Pb) in groundwater in agricultural areas of Thailand

Human biomarkers were used to evaluate the lead (Pb) and arsenic (As) exposure of local people who lived in an agricultural area with intense agrochemical usage and who consumed groundwater. Although the heavy metals/metalloids in the groundwater were at low concentrations, they could cause adverse effects due to a high daily water intake rate over the long term. Biomarkers (hair, fingernails and urine) were collected from 100 subjects along with the local shallow groundwater and tap water, which is the treated deep groundwater, and investigated for the concentrations of As and Pb. Shallow groundwater had an average pH of 5.21 ± 1.90, ranging from 3.77 to 8.34, with average concentrations of As and Pb of 1.311 µg/L and 6.882 µg/L, respectively. Tap water had an average pH of 5.24 ± 1.63, ranging from 3.86 to 8.89, with the average concentrations of As and Pb of 0.77 µg/L and 0.004 µg/L, respectively. The levels of both As and Pb in the hair, fingernails and urine of shallow groundwater-consuming residents were greater than those in the hair, fingernails and urine of tap water-consuming residents. Interestingly, the As level in urine showed a linear relationship with the As concentration in groundwater (R2 = 0.91). The average water consumption rate was approximately two-fold higher than the standard; thus, its consumption posed a health risk even at the low As and Pb levels in the groundwater. The hazard index (HI) ranged from 0.01 to 16.34 (average of 1.20 ± 2.50), which was higher than the acceptable level. Finally, the concomitant factors for As and Pb in the urine, hair and nails from both binary logistic regression and odds ratio (OR) analysis indicated that groundwater consumption was the major concomitant risk factor. This study suggested that direct consumption of this groundwater should be avoided and that the groundwater should be treated, especially before consumption. In conclusion, urine is suggested to be a biomarker of daily exposure to As and Pb, while for long-term exposure to these metals, fingernails are suggested as a better biomarker than hair.

Effects of Arsenic and Iron on the Community and Abundance of Arsenite-Oxidizing Bacteria in an Arsenic-Affected Groundwater Aquifer

Arsenic (As) contamination of groundwater aquifers is a global environmental problem, especially in South and Southeast Asian regions, and poses a risk to human health. Arsenite-oxidizing bacteria that transform As(III) to less toxic As(V) can be potentially used as a groundwater As remediation strategy. This study aimed to examine the community and abundance of arsenite-oxidizing bacteria in groundwater with various As concentrations from Rayong Province, Thailand using PCR-cloning-sequencing and quantitative PCR (qPCR) of catalytic subunit of arsenite oxidase gene (aioA). Key factors influencing their community and abundance were also identified. The results demonstrated that arsenite-oxidizing bacteria retrieved from groundwater were phylogenetically related to Betaproteobacteria and Alphaproteobacteria. The aioA gene abundances ranged from 8.6 × 10¹ to 1.1 × 10⁴ copies per ng of genomic DNA, accounting for 0.16-1.37% of the total 16S rRNA bacterial gene copies. Although the abundance of arsenite-oxidizing bacteria in groundwater was low, groundwater with As(III) dominance likely promoted their abundance which possibly played an important role in chemolithoautotrophic oxidation of As(III) to As(V). Fe and As(III) were the major environmental factors influencing the community and abundance of arsenite-oxidizing bacteria. The knowledge gained from this study can be used to further contribute to the development of bioremediation strategies for As removal from groundwater resources.

Microbial community structure in aquifers associated with arsenic: analysis of 16S rRNA and arsenite oxidase genes

The microbiomes of deep and shallow aquifers located in an agricultural area, impacted by an old tin mine, were explored to understand spatial variation in microbial community structures and identify environmental factors influencing microbial distribution patterns through the analysis of 16S rRNA and aioA genes. Although Proteobacteria, Cyanobacteria, Actinobacteria, Patescibacteria, Bacteroidetes, and Epsilonbacteraeota were widespread across the analyzed aquifers, the dominant taxa found in each aquifer were unique. The co-dominance of Burkholderiaceae and Gallionellaceae potentially controlled arsenic immobilization in the aquifers. Analysis of the aioA gene suggested that arsenite-oxidizing bacteria phylogenetically associated with Alpha-, Beta-, and Gamma proteobacteria were present at low abundance (0.85 to 37.13%) and were more prevalent in shallow aquifers and surface water. The concentrations of dissolved oxygen and total phosphorus significantly governed the microbiomes analyzed in this study, while the combination of NO₃ ^--N concentration and oxidation-reduction potential significantly influenced the diversity and abundance of arsenite-oxidizing bacteria in the aquifers. The knowledge of microbial community structures and functions in relation to deep and shallow aquifers is required for further development of sustainable aquifer management.