Soil colloids can significantly enhance spreading of polybromodiphenyl ethers in groundwater by serving as an effective carrier.

Polybromodiphenyl ethers (PBDEs), the widely used flame retardants, are common contaminants in surface soils at e-waste recycling sites. The association of PBDEs with soil colloids has been observed, indicating the potential risk to groundwater due to colloid-facilitated transport. However, the extent to which soil colloids may enhance the spreading of PBDEs in groundwater is largely unknown. Herein, we report the co-transport of decabromodiphenyl ester (BDE-209) and soil colloids in saturated porous media. The colloids released from a soil sample collected at an e-waste recycling site in Tianjin, China, contain high concentration of PBDEs, with BDE-209 being the most abundant conger (320 ± 30 mg/kg). The colloids exhibit relatively high mobility in saturated sand columns, under conditions commonly observed in groundwater environments. Notably, under all the tested conditions (i.e., varying flow velocity, pH, ionic species and ionic strength), the mass of eluted BDE-209 correlates linearly with that of eluted soil colloids, even though the mobility of the colloids varies markedly depending on the specific hydrodynamic and solution chemistry conditions involved. Additionally, the mass of BDE-209 retained in the columns also correlates strongly with the mass of retained colloids. Apparently, the PBDEs remain bound to soil colloids during transport in porous media. Findings in this study indicate that soil colloids may significantly promote the transport of PBDEs in groundwater by serving as an effective carrier. This might be the reason why the highly insoluble and adsorptive PBDEs are found in groundwater at some PBDE-contaminated sites.

Identifying the genetic mechanism of medium-low temperature fluoride-enriched geothermal groundwater by the self-organizing map and evaluating health risk in the Wugongshan area, southeast China.

Fluoride-enriched groundwater is a serious threat for groundwater supply around the world. The medium-low temperature fluoride-enriched geothermal groundwater resource is widely distributed in the circum-Wugongshan area. And the fluoride concentration of all geothermal samples exceeds the WHO permissible limit of 1.5 mg/L. The Self-Organizing Map method, hydrochemical and isotopic analysis are used to decipher the driving factors and genetic mechanism of fluoride-enriched geothermal groundwater. A total of 19 samples collected from the circum-Wugongshan geothermal belt are divided into four clusters by the self-organizing map. Cluster I, Cluster II, Cluster III, and Cluster IV represent the geothermal groundwater with the different degree of fluoride concentration pollution, the different hydrochemical type, and the physicochemical characteristic. The high F- concentration geothermal groundwater is characterized by HCO3-Na with alkalinity environment. The δD and δ18O values indicate that the geothermal groundwater origins from the atmospheric precipitation with the recharge elevation of 1000-2100 m. The dissolution of fluoride-bearing minerals is the main source of fluoride ions in geothermal water. Moreover, groundwater fluoride enrichment is also facilitated by water-rock interaction, cation exchange and alkaline environment. Additionally, the health risk assessment result reveals that the fluorine-enriched geothermal groundwater in the western part of Wugongshan area poses a more serious threat to human health than that of eastern part. The fluoride health risks of geothermal groundwater for different group show differentiation, 100% for children, 94.74% for adult females, and 68.42% for adult males, respectively. Compared with adult females and adult males, children faced the greatest health risks. The results of this study provide scientific evaluation for the utilization of geothermal groundwater and the protection of human health around the Wugongshan area.

Anomaly detection in groundwater monitoring data using LSTM-Autoencoder neural networks.

Groundwater monitoring data can be prone to errors and biases due to various factors like borehole and equipment malfunctions, or human mistakes. These inaccuracies can jeopardize the groundwater system, leading to reduced efficiency and potentially causing partial or complete failures in the monitoring system. Traditional anomaly detection methods, which rely on statistical and time-variant techniques, struggle to handle the complex and dynamic nature of anomalies. With advancements in artificial intelligence and the growing need for effective anomaly detection and prevention across different sectors, artificial neural network methods are emerging as capable of identifying more intricate anomalies by considering both temporal and contextual aspects. Nonetheless, there is still a shortage of comprehensive studies on groundwater anomaly detection. The intricate patterns of sequential data from groundwater present numerous challenges, necessitating sophisticated modeling techniques that combine mathematics, statistics, and machine learning for viable solutions. This paper introduces a model designed for high accuracy and efficient computation in detecting anomalies in groundwater monitoring data through a probabilistic approach. We employed the Monte Carlo method and SEAWAT numerical simulation to ascertain the uncertainty in groundwater salinity. Subsequently, a Long Short-Term Memory (LSTM)-Autoencoder model was trained and evaluated, forming the basis of an anomaly detection framework. Each piece of training data was assessed by the LSTM-Autoencoder using the Negative Log Likelihood (NLL) score and a predefined threshold to determine the data's abnormality percentage. The accuracy evaluation of the proposed LSTM-Autoencoder algorithm revealed that this approach achieved commendable performance, with an accuracy of 98.47% in anomaly detection.

Assessment of the migration characteristics and source-oriented health risks of heavy metals in the soil and groundwater of a legacy contaminated by the chlor-alkali industry in central China.

The chlor-alkali industry (CAI) is crucial for global chemical production; however, its operation has led to widespread heavy metal (HM) contamination at numerous sites, which has not been thoroughly investigated. This study analysed 122 soil and groundwater samples from a typical CAI site in Kaifeng, China. Our aim was to assess the ecological and health risks, identify the sources, and examine the migration characteristics of HMs at this site using Monte Carlo simulation, absolute principal component score-multiple linear regression (APCS-MLR), and the potential environmental risk index (Ei). Our findings revealed that the exceedance rates for Cd, Pb, Hg, and Ni were 71.96%, 45.79%, 49.59%, and 65.42%, respectively. Mercury (Hg) displayed the greatest coefficient of variation across all the soil layers, indicating a significant anthropogenic influence. Cd and Hg were identified as having high and extremely high potential environmental risk levels, respectively. The spatial distributions of the improved Nemerow index (INI), total ecological risk (Ri), and HM content varied considerably, with the most contaminated areas typically associated with the storage of raw and auxiliary materials. Surface aggregation and significant vertical transport were noted for HMs; As and Ni showed substantial accumulation in subsoil layers, severely contaminating the groundwater. Self-organizing maps categorized the samples into two different groups, showing strong positive correlations between Cd, Pb, and Hg. The APCS-MLR model suggested that industrial emissions were the main contributors, accounting for 60.3% of the total HM input. Elevated hazard quotient values for Hg posed significant noncarcinogenic risks, whereas acceptable levels of carcinogenic risk were observed for both adults (96.60%) and children (97.83%). This study significantly enhances historical CAI pollution data and offers valuable insights into ongoing environmental and health challenges.

Chemical characteristics and water stability evaluation of groundwater in the CKDu Zone of Sri Lanka.

Groundwater is the main source of drinking water for the rural population in the chronic kidney disease of unknown etiology (CKDu) zone of the North Central Province (NCP) in Sri Lanka. In this study, a total of 334 groundwater samples (311 dug wells, 21 tube wells and 2 springs) during the wet season from two aquifers in the NCP were collected, and investigated their chemical characteristics and evaluate their water quality, including groundwater chemistry, main ion sources, the corrosion and scaling potential of groundwater. The results showed that the two hydrochemical types of groundwater in the NCP were mainly of the Ca-HCO3, Na·Ca-HCO3 types, with the main HCO3-, Na+ and Ca2+ ions in both types of groundwater originating from silicate and evaporite salt dissolution and influenced by alternating cation adsorption, while the presence of NO3- was mainly anthropogenic. Evaluation of water stability using namely Langelier saturation index (LSI), Ryznar stability index (RSI), Puckorius scaling index (PSI) and Larson-Skold index (LS), indicated that most groundwater presents corrosion potential and has corrosion behavior tendency of metals to some degrees. The water quality of Polonnaruwa was better than that of Anuradhapura in the NCP, and when the groundwater was worse than the "good" grade, which must be properly treated before it is used as drinking water.

Research on the relation between hydro-chemical and geological characteristics in karst area: Case study in Zhong Liang Mountain, Southwest China.

Karst groundwater, which is one of most important drinking water sources, is vulnerable to be polluted as its closed hydraulic relation with surface water. Thus, it is very important to identify the groundwater source to control groundwater pollution. The Pearson correlation coefficient among major ions (Na + K+, Ca2+, Mg2+, HCO3 -, SO4 2-, and Cl-) was employed to deduce the groundwater types in Zhong Liang Mountain, Southwest China. Then, the combined method of principal component analysis and cluster analysis were employed to identify the groundwater sources in a typical karst region of southwest China. The results shown that (1) the high positive correlation between cations and anions indicated the water-rock reaction of Ca-HCO3, Ca-SO4, (Na + K)-Cl, and Mg-SO4. (2) The major two principal components that would represent water-rock reaction of CaSO4 and Ca-HCO3 would, respectively, explain 60.41% and 31.80% of groundwater information. (3) Based on the two principal components, 33 groundwater samples were clustered into eight groups through hierarchical clustering, each group has similar water-rock reaction. The findings would be employed to forecast the surge water, that was an important work for tunnel construction and operation. PRACTITIONER POINTS: The components of groundwater was highly correlated with water-rock reaction. The principal component analysis screens the types of groundwater. The cluster analysis identifies the groundwater sources.

Variation of groundwater and mineral composition of in situ leaching uranium in Bayanwula mining area, China.

The reaction between the lixiviant and the minerals in the aquifer of In-situ uranium leaching (ISL) will result mineral dissolution and precipitation. ISL will cause changes in the chemical composition of groundwater and the porosity and permeability of aquifer, as well as groundwater pollution. Previous studies lack three-dimension numerical simulation that includes a variety of minerals and considers changes in porosity and permeability properties simultaneously. To solve these problems, a three-dimensional reactive transport model (RTM) which considered minerals, main water components and changes in porosity and permeability properties in Bayanwula mine has been established. The results revealed that: (1) Uranium elements were mainly distributed inside the mining area and had a weak trend of migration to the outside. The strong acidity liquid is mainly in the mining area, and the acidity liquid dissolved the minerals during migrating to the outside of the mining area. The concentration front of major metal cations such as K+, Na+, Ca2+ and Mg2+ is about 150m away from the boundary. (2) The main dissolved minerals include feldspar, pyrite, calcite, sodium montmorillonite and calcium montmorillonite. Calcite is the most soluble mineral and one of the sources of gypsum precipitation. Other minerals will dissolve significantly after calcite is dissolved. (3) ISL will cause changes in porosity and permeability of the mining area. Mineral dissolution raises porosity and permeability near the injection well. Mineral precipitation reduced porosity and permeability near the pumping well, which can plugging the pore throat and affect recovery efficiency negatively.

Control of paleoclimate and paleoweathering on chromium contents in a non-ultramafic aquifer hosting high chromium groundwater.

Cr(VI) is a carcinogen with proven mutagenic and genotoxic effects. The effects of the depositional environment (e.g., paleoweathering, paleoclimate, and paleoredox condition) on Cr enrichment in non-ultramafic aquifer solids are unclear. In this study, we presented the sedimentary characteristics of a borehole from a typical non-ultramafic aquifer with high Cr groundwater in Jingbian, central Ordos Basin, China. Chromium was enriched in the K1h sandstone aquifer, especially at depths of 400-500 m, with the highest value of mass transport coefficient (τAl,Cr) up to 92.13% and τAl,Fe up to 33.5%. The provenance of aquifer Cr was predominantly intermediate and felsic igneous rocks with a mafic rock mixture. This mafic source was inferred from Cr-rich granodiorite and mafic/ultramafic rocks in the Yinshan (Daqingshan-Wulashan) Block, northern Ordos Basin. The Cr-rich aquifer in K1h was developed due to a moderate chemical index of alteration (CIA) (mean, 56.7) under relatively warm and humid paleoclimate, as evidenced by high CIA-temperature (CIA-Temp) (mean, 6.79 °C) and paleoclimatic index values (mean, 0.40). Fe-Mn redox cycling in the oxic to suboxic environments contributed to aquifer Cr accumulation. Using path analysis, we identified that paleoclimate created favorable weathering conditions and enrichment of Fe contributed to the formation of high-Cr aquifers. The study reveals the formation of positive Cr anomalies in non-ultramafic aquifers, which is the potential source of groundwater Cr, and highlights the effects of depositional factors on Cr accumulation during aquifer deposition or early diagenesis. It can provide new insights into the natural processes of high-Cr sediments occurring in non-ultramafic aquifers.

Improving groundwater vulnerability assessment in structurally controlled hard rock aquifer: insight from lineament density and land use/land cover pattern.

A comprehensive seasonal assessment of groundwater vulnerability was conducted in the weathered hard rock aquifer of the upper Swarnrekha watershed in Ranchi district, India. Lineament density (Ld) and land use/land cover (LULC) were integrated into the conventional DRASTIC and Pesticide DRASTIC (P-DRASTIC) models and were extensively compared with six modified models, viz. DRASTIC-Ld, DRASTIC-Lu, DRASTIC-LdLu, P-DRASTIC-Ld, P-DRASTIC-Lu, and P-DRASTIC-LdLu, to identify the most optimal model for vulnerability mapping in hard rock terrain of the region. Findings were geochemically validated using NO3- concentrations of 68 wells during pre-monsoon (Pre-M) and post-monsoon (Post-M) 2022. Irrespective of the applied model, groundwater vulnerability shows significant seasonal variation, with > 45% of the region classified as high to very high vulnerability in the pre-M, increasing to Ì´67% in post-M season, highlighting the importance of seasonal vulnerability assessments. Agriculture and industries' dominant southern region showed higher vulnerability, followed by regions with high Ld and thin weathered zone. Incorporating Ld and LULC parameters into DRASTIC-LdLu and P-DRASTIC-LdLu models increases the 'Very High' vulnerability zones to 17.4% and 17.6% for pre-M and 29.4% and 27.9% for post-M, respectively. Similarly, 'High' vulnerable zones increase from 32.5% and 25% in pre-M to 33.8% and 35.3% in post-M for respective models. Model output comparisons suggest that modified DRASTIC-LdLu and P-DRASTIC-LdLu perform better, with accurate estimations of 83.8% and 89.7% for pre-M and post-M, respectively. However, results of geochemical validation suggest that among all the applied modified models, DRASTIC-LdLu performs best, with accurate estimations of 34.4% and 20.6% for pre-M and post-M, respectively.

Bee-inspired insights: Unleashing the potential of artificial bee colony optimized hybrid neural networks for enhanced groundwater level time series prediction.

Analysis of the change in groundwater used as a drinking and irrigation water source is of critical importance in terms of monitoring aquifers, planning water resources, energy production, combating climate change, and agricultural production. Therefore, it is necessary to model groundwater level (GWL) fluctuations to monitor and predict groundwater storage. Artificial intelligence-based models in water resource management have become prevalent due to their proven success in hydrological studies. This study proposed a hybrid model that combines the artificial neural network (ANN) and the artificial bee colony optimization (ABC) algorithm, along with the ensemble empirical mode decomposition (EEMD) and the local mean decomposition (LMD) techniques, to model groundwater levels in Erzurum province, Türkiye. GWL estimation results were evaluated with mean square error (MSE), coefficient of determination (R2), and residual sum of squares (RSS) and visually with violin, scatter, and time series plot. The study results indicated that the EEMD-ABC-ANN hybrid model was superior to other models in estimating GWL, with R2 values ranging from 0.91 to 0.99 and MSE values ranging from 0.004 to 0.07. It has also been revealed that promising GWL predictions can be made with previous GWL data.

Effect of seasonal variations in sea level on residual saltwater removal upstream of subsurface dam in coastal layered heterogeneity aquifers.

Subsurface dams have been recognized as one of the most effective measures for preventing saltwater intrusion. However, it may result in large amounts of residual saltwater being trapped upstream of the dam and take years to decades to remove, which may limit the utilization of fresh groundwater in coastal areas. In this study, field-scale numerical simulations were used to investigate the mechanisms of residual saltwater removal from a typical stratified aquifer, where an intermediate low-permeability layer (LPL) exists between two high-permeability layers, under the effect of seasonal sea level fluctuations. The study quantifies and compares the time of residual saltwater removal (Tre) for constant sea level (CSL) and seasonally varying sea level (FSL) scenarios. The modelling results indicate that, in most cases, seasonal fluctuations in sea level facilitate the dilution of residual saltwater and thus accelerate residual saltwater removal compared to a static sea level scenario. However, accounting for seasonal sea level variations may increase the required critical dam height (the minimum dam height required to achieve complete residual saltwater removal). Sensitivity analyses show that Tre decreases with increasing height of subsurface dam (Hd) under CSL or weaker sea level fluctuation scenarios; however, when the magnitude of sea level fluctuation is large, Tre changes non-monotonically with Hd. Tre decreases with increasing distance between subsurface dam and ocean for both CSL and FSL scenarios. We also found that stratification model had a significant effect on Tre. The increase in LPL thickness for both CSL and FSL scenarios leads to a decrease in Tre and critical dam height. Tre generally shows a non-monotonically decreasing trend as LPL elevation increases. These quantitative analyses provide valuable insights into the design of subsurface dams in complex situations.

Experimental study on migration characteristics of LNAPL in the aquitard under pumping conditions.

Research on the migration behaviors of contaminants in the aquitard has been deficient for an extended period. Clay is commonly employed as an impermeable layer or barrier to stop the migration of contaminants. However, under certain conditions, the clay layer may exhibit permeability to water, thereby allowing contaminants to infiltrate and potentially contaminate adjacent aquifers. Consequently, it holds immense importance to scrutinize and investigate the migration characteristics of light non-aqueous phase liquid (LNAPL) within the aquitard for the purposes of groundwater pollution control and remediation. To evaluate the environmental risk posed by organic contaminants in the aquitard, an experimental model was formulated and devised to monitor the LNAPL concentration in the aquitard under pumping conditions. The correlation between pumping rate and LNAPL concentration was investigated. A self-developed plexiglass sandbox model was used to simulate the migration characteristics of LNAPL in the aquitard under pumping conditions. Four experimental scenarios were designed, varying pumping rates, aquitard thicknesses, and groundwater level changes. The LNAPL concentration curve was derived by systematically tracking and analyzing LNAPL levels at various locations within the aquitard. The results indicated that higher pumping rates corresponded to increased migration of LNAPL, resulting in greater LNAPL ingress into the pumping well during extraction. A thicker aquitard demonstrated a more pronounced inhibitory effect on LNAPL, leading to an extended penetration time of LNAPL within the aquitard. The drawdown within the aquitard exerted a discernible influence on LNAPL migration, with the LNAPL concentration continuing to decrease in tandem with declining water levels during pumping. These research findings can establish a scientific foundation for the control and remediation of contaminants within aquitards.

Prediction of arsenic concentration in groundwater of Chapainawabganj, Bangladesh: machine learning-based approach to spatial modeling.

Groundwater in northwestern parts of Bangladesh, mainly in the Chapainawabganj District, has been contaminated by arsenic. This research documents the geographical distribution of arsenic concentrations utilizing machine learning techniques. The study aims to enhance the accuracy of model predictions by precisely identifying occurrences of groundwater arsenic, enabling effective mitigation actions and yielding more beneficial results. The reductive dissolution of arsenic-rich iron oxides/hydroxides is identified as the primary mechanism responsible for the release of arsenic from sediment into groundwater. The study reveals that in the research region, alongside elevated arsenic concentrations, significant levels of sodium (Na), iron (Fe), manganese (Mn), and calcium (Ca) were present. Statistical analysis was employed for feature selection, identifying pH, electrical conductivity (EC), sulfate (SO4), nitrate (NO3), Fe, Mn, Na, K, Ca, Mg, bicarbonate (HCO3), phosphate (PO4), and As as features closely associated with arsenic mobilization. Subsequently, various machine learning models, including Naïve Bayes, Random Forest, Support Vector Machine, Decision Tree, and logistic regression, were employed. The models utilized normalized arsenic concentrations categorized as high concentration (HC) or low concentration (LC), along with physiochemical properties as features, to predict arsenic occurrences. Among all machine learning models, the logistic regression and support vector machine models demonstrated high performance based on accuracy and confusion matrix analysis. In this study, a spatial distribution prediction map was generated to identify arsenic-prone areas. The prediction map also displays that Baroghoria Union and Rajarampur region under Chapainawabganj municipality are high-risk areas and Maharajpur Union and Baliadanga Union are comparatively low-risk areas of the research area. This map will facilitate researchers and legislators in implementing mitigation strategies. Logistic regression (LR) and support vector machine (SVM) models will be utilized to monitor arsenic concentration values continuously.

Hydrochemical characterization and health risk assessment of different types of water bodies in Fenghuang Mountain Area, Northeast China.

Groundwater, as an essential resource, holds significant importance for human production and livelihoods. With the deterioration of the water environment, the issue of groundwater quality has become an urgent international concern. This study focused on the Fenghuang Mountain Area (FMA) and collected a total of 41 sets of samples including pore groundwater (PGW), fissure groundwater (FGW), karst groundwater (KGW), and river water (RW). Hydrochemical analysis methods were employed to identify the hydrochemical characteristics and controlling factors. The entropy-weighted water quality index (EWQI) and health risk assessment model were utilized to assess the groundwater quality and nitrate health risk, respectively. The results indicated that the dominant anion and cation in both groundwater and surface water in the FMA were HCO3- and Ca2+, respectively, with the main hydrochemical type being HCO3-Ca. Groundwater and surface water in the FMA were primarily controlled by rock weathering process, with ion concentrations influenced mainly by the dissolution of halite, sylvite, carbonates (calcite and dolomite), silicates, and gypsum, as well as by reverse anion exchange process. PGW was significantly affected by agricultural activities, with NO3- concentration closely related to human activities. The water quality of FGW was relatively good, with Class I and Class II water accounting for the highest proportion, reaching 84.62%. The high-value area of EWQI in PGW was influenced by human activities. The impact of nitrate health risk on children was significantly greater than on adults, with FGW having the lowest health risk and PGW having the highest health risk. The research results can provide important guarantees for the rational development and utilization of water resources in the FMA and the sustainable development of the economy in Northeast China.

Spatial variations and health risk assessment of heavy metal levels in groundwater of Qatar.

The present work's objective is to give a comprehensive overview of the quality of groundwater in Qatar in terms of heavy metals content as well as investigating the cause and effect of the elevation in their levels above the WHO/US-EPA standards. The scope of the study included (1) physical and chemical analysis of 82 groundwater samples collected from various locations around Qatar, (2) development of ArcGIS maps depicting the variations in the levels, (3) assessment of the human health risks associated with the existing levels using three of the most used models which are: Hazard index (HI), Nemerow comprehensive pollution index (NCPI) and Incremental Lifetime Cancer Risk (ILCR). There is no extensive study ever reported to assess the health risks linked with the consumption of groundwater characterized with such heavy metals levels in Qatar. The chronic daily intake (CDI) of the investigated heavy metals (Ag, Mn, Cr, V, Mo and Sr) through ingestion and dermal pathways had a range of 1.4 × 10-5-6.7 × 10-1 mg/kg/day while the NCPI's range was reported at 0-4.39. Moreover, the HI and ILCR were found to have a range of 0-3.2 and 5.6 × 10-4-5.5 × 10-2, respectively. The assessment of health risks, conducted in the present work, could be beneficial in building the baseline of heavy metals levels in groundwater in Qatar. This will also help in the determination of any future contamination of groundwater.

Enhancing hydrological insight: isotopic methods revealing groundwater-surface water interactions in the Lower Quang Tri River Group, Vietnam.

The Lower Quang Tri River Group, situated in central Vietnam, faces a myriad of challenges, notably the decline in groundwater levels and the salinisation of both groundwater and surface water, significantly impacting water availability for domestic, agricultural, and industrial purposes. To address these pressing concerns, this study adopts a comprehensive methodology integrating hydrogeological measurements, isotopic techniques, and chemical analyses of various water sources, including local precipitation, surface water bodies, reservoirs, and groundwater samples. Utilising the deuterium and oxygen-18 signatures (δ2H and δ18O) in water molecules as environmental tracers for the assessment of base flow and water sources enables a nuanced understanding of the intricate interaction between surface water and groundwater. Research findings elucidate that during the dry season, groundwater recharge primarily stems from water in the reservoirs over approximately seven months. Base flow contributes between 80 and 85 % of streamflow during the rainy season, escalating to 100 % during the dry season. The mean travelling time of the base flow is estimated at 120 ± 10 days using the sine curve model developed by Rodgers et al. The insights gleaned from this study are poised to play a pivotal role in guiding the local water resources managers in licensing for the exploitation of a right quantities of groundwater as sustainable management strategies in the region.

The permeability evolution mechanism of ore-bearing strata during acid in-situ leaching of uranium: A case study of Bayanwula uranium mine in Inner Mongolia of China.

Uranium mainly comes from ISL of sandstone-type uranium deposits in China. The change of porosity and permeability caused by blockage of ore-bearing strata is one of the most serious problems in acid ISL of uranium. In this paper, the groundwater tracer test was carried out before and 1 year after ISL to explore the pore and permeability evolution characteristics of the ore-bearing layer during ISL. The test results showed that the leaching solution migrated along two seepage channels and the water-bearing medium was isotropic. After 1 year of ISL, the flow rate of the leaching solution decreased obviously. However, the flow rate of the leaching solution in slower channel decreased more than that in the faster channel in all directions, which was caused by the more adequate chemical reactions between the leaching solution and the minerals of the ore-bearing layer and the more corresponding precipitation in the slower channel. In addition, the flow rate along the direction of groundwater flow decreased less than that in the direction of vertical groundwater flow. This was closely related to the transformation of aquifer medium by hydrodynamic field. Initial stage of ISL, the occurrence of plugging is closely related to the precipitation-dissolution process of iron and aluminum minerals under the change of pH, which is accompanied by the continuous precipitation of gypsum.

Hydrogeochemical characteristics, driving factors, and health risk assessment of karst groundwater in Southwest Hubei Province, China.

In South China, karst groundwater is an important water resource for industrial, agricultural, and drinking purposes. However, karst aquifers are highly vulnerable to pollution, leading to deteriorating karst groundwater quality and posing potential health risks to local residents. In this study, 22 groundwater samples were collected from a karst aquifer in the southwestern part of Hubei Province. The hydrogeochemical characteristics and their controlling factors were examined, and the potential health risks associated with groundwater pollutant concentrations in karst groundwater were assessed. The results showed that the groundwater is slightly alkaline with low chemical oxygen demand values, indicating good water quality. The groundwater facies type was identified as HCO3-Ca at most sample spots, showing low total dissolved solids concentrations. Substantial spatial variations in Na+, CO3 2-, and NO2 - concentrations were found, whereas spatial variations in the K+, Ca2+, Cl-, HCO3 -, and F- concentrations were small. In addition, the dissolution of gypsum deposits and magnesium carbonate sedimentary rocks at sampling sites resulted in groundwater facies types of HCO3•SO4-Ca and HCO3-Ca•Mg, with low total dissolved solids concentrations. The karst groundwater chemistry in the study area was mainly controlled by water-rock interactions, as well as by the dissolution of gypsum deposits and magnesium carbonate sedimentary rocks at specific groundwater sampling sites. The groundwater Cl- concentrations were mainly affected by atmospheric precipitation. NO3 - was mainly derived from atmospheric precipitation, domestic sewage, septic tanks, and industrial activities, whereas SO4 2- was derived from atmospheric precipitation, sulfate rock dissolution, and sulfide mineral oxidation. These results highlight the absence of potential human health risks of NO3 - and F- to infants, children, and adults, as their concentrations are below the corresponding regional background values. In contrast, the potential health risks of Cl- cannot be ignored, particularly for infants. This study offers scientific guidelines for protecting and allocating local groundwater resources.

Effects and driving mechanisms of bioremediation on groundwater after the neutral in situ leaching of uranium.

The remediation of groundwater subject to in situ leaching (ISL) for uranium mining has raised extensive concerns in uranium mill and milling. This study conducted bioremediation through biostimulation and bioaugmentation to the groundwater in an area in northern China that was contaminated due to uranium mining using the CO2 + O2 neutral ISL (NISL) technology. It identified the dominant controlling factors and mechanisms driving bioremediation. Findings indicate that microorganisms can reduce the uranium concentration in groundwater subject to NISL uranium mining to its normal level. After 120 days of bioaugmentation, the uranium concentration in the contaminated groundwater fell to 0.36 mg/L, achieving a remediation efficiency of 91.26 %. Compared with biostimulation, bioaugmentation shortened the remediation timeframe by 30 to 60 days while maintaining roughly the same remediation efficiency. For groundwater remediation using indigenous microbial inoculants, initial uranium concentration and low temperatures (below 15 °C) emerge as the dominant factors influencing the bioremediation performance and duration. In settings with high carbonate concentrations, bioremediation involved the coupling of multiple processes including bioreduction, biotransformation, biomineralization, and biosorption, with bioreduction assuming a predominant role. Post-bioremediation, the relative abundances of reducing microbes Desulfosporosinus and Sulfurospirillum in groundwater increased significantly by 10.56 % and 6.91 %, respectively, offering a sustainable, stable biological foundation for further bioremediation of groundwater.

Natural Attenuation of Groundwater Uranium in Post-Neutral-Mining Sites Evidenced from Multiple Isotopes and Dissolved Organic Matter.

Although natural attenuation is an economic remediation strategy for uranium (U) contamination, the role of organic molecules in driving U natural attenuation in postmining aquifers is not well-understood. Groundwaters were sampled to investigate the chemical, isotopic, and dissolved organic matter (DOM) compositions and their relationships to U natural attenuation from production wells and postmining wells in a typical U deposit (the Qianjiadian U deposit) mined by neutral in situ leaching. Results showed that Fe(II) concentrations and δ34SSO4 and δ18OSO4 values increased, but U concentrations decreased significantly from production wells to postmining wells, indicating that Fe(III) reduction and sulfate reduction were the predominant processes contributing to U natural attenuation. Microbial humic-like and protein-like components mediated the reduction of Fe(III) and sulfate, respectively. Organic molecules with H/C > 1.5 were conducive to microbe-mediated reduction of Fe(III) and sulfate and facilitated the natural attenuation of dissolved U. The average U attenuation rate was -1.07 mg/L/yr, with which the U-contaminated groundwater would be naturally attenuated in approximately 11.2 years. The study highlights the specific organic molecules regulating the natural attenuation of groundwater U via the reduction of Fe(III) and sulfate.