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.

Impact of coking plant to heavy metal characteristics in groundwater of surrounding areas: Spatial distribution, source apportionment and risk assessments.

Coking industry is a potential source of heavy metals (HMs) pollution. However, its impacts to the groundwater of surrounding residential areas have not been well understood. This study investigated the pollution characteristics and health risks of HMs in groundwater nearby a typical coking plant. Nine HMs including Fe, Zn, Mo, As, Cu, Ni, Cr, Pb and Cd were analyzed. The average concentration of total HMs was higher in the nearby area (244.27 µg/L) than that of remote area away the coking plant (89.15 µg/L). The spatial distribution of pollution indices including heavy metal pollution index (HPI), Nemerow index (NI) and contamination degree (CD), all demonstrated higher values at the nearby residential areas, suggesting coking activity could significantly impact the HMs distribution characteristics. Four sources of HMs were identified by Positive Matrix Factorization (PMF) model, which indicated coal washing and coking emission were the dominant sources, accounted for 40.4%, and 31.0%, respectively. Oral ingestion was found to be the dominant exposure pathway with higher exposure dose to children than adults. Hazard quotient (HQ) values were below 1.0, suggesting negligible non-carcinogenic health risks, while potential carcinogenic risks were from Pb and Ni with cancer risk (CR) values > 10-6. Monte Carlo simulation matched well with the calculated results with HMs concentrations to be the most sensitive parameters. This study provides insights into understanding how the industrial coking activities can impact the HMs pollution characteristics in groundwater, thus facilitating the implement of HMs regulation in coking industries.

Effect of clayey sediment compression on fluoride enrichment in the Quaternary groundwater system of Cangzhou Plain, China.

The effect of clay layer compression on the enrichment of groundwater fluoride remains unknown. Quaternary groundwater with high fluoride levels at the Cangzhou Plain, which has a long history of land subsidence caused by clay layer compression, poses a potential health risk. The spatial distribution and enrichment mechanisms of groundwater fluoride are identified by sample collection, hydrochemical analysis, and geochemical inverse modeling. The results revealed that fluoride concentrations in 82 % of the 122 groundwater samples above the limit in drinking water as 1.0 mg/L in China. Fluoride in shallow groundwater (depth <20 m, ∼average = 2.08 mg/L) was mainly originated from fluorite dissolution and influenced by groundwater HCO3-, pH, and cation exchange levels. Below ∼200 m, the main source of groundwater fluoride (∼average = 3.12 mg/L) was the compression-release of clay pore water with high F- concentration, which was generated by complex water-rock interaction. Based on hydrochemical inverse simulation and end-member mixing models, the pore water released from clayey sediments supplied 53 %-56 % of deep groundwater (>200 m) and contributed 2.07 -2.87 mg/L to F- concentration. The findings of this study provide a theoretical basis for future research on prevention of high fluoride groundwater induced by clayey sediment compression.

Assessing drinking water quality in Eloued, south-East Algeria, using the groundwater pollution index (GPI) and the synthetic pollution index (SPI) model.

Groundwater quality degradation is a significant environmental issue worldwide, with potentially severe economic consequences and harm to ecosystems and biodiversity. This can directly affect human health, particularly in developing countries where rapid and uncontrolled urbanization is on the rise. Groundwater is the primary resource for meeting the water needs of the Eloued region, located in southeastern Algeria. Water is considered unfit for human consumption if its physico-chemical elements exceed national or international standards or guidelines. We used the GPI and SPI indices to evaluate the quality of groundwater suited for drinking. Groundwater samples were obtained from 22 wells at depths of more than 250 m. Standard analytical procedures were used to determine the physicochemical characteristics of the collected samples, which included pH, EC, TDS, Na+, Ca+2, Mg+2, K+, Cl-, HCO3-, SO4-2, NO3-, NO2-, NH4+ and PO4-3. Multivariate statistical analysis and GIS techniques were used to process the results. The results of the selected physicochemical parameters were compared with World Health Organization (WHO) guidelines to determine the quality of drinking water. The findings indicate that the waters of the terminal complex aquifer are salty and contain medium to high quantities of main ions that surpass the established drinking water limits. The primary ions' relative abundance is Cl- > SO4-2 > HCO3- > NO3 for anions and Na+ > Ca+2 > Mg+2 > K+ for cations. Groundwater chemical types were dominated by Na+, Ca+2, Cl-, and SO4-2. Principal Component Analysis (PCA) showed that alteration and dissolution of carbonates, evaporates, salts, partly silicates, and evaporation, are the main reasons affecting the chemical composition of water in Eloued. The GPI results show that 18.18%, 54.54%, and 27.27% of the water samples were classed as lightly polluted, moderately polluted, or substantially polluted for drinking purposes, respectively. According to the SPI study, 9.09%, 36.36%, 36.36%, and 18.18% were considered drinkable, mildly contaminated, moderately polluted, and seriously polluted for drinking purposes, respectively. According to the GPI and SPI models' geographical distribution maps, potable water is generally scarce and concentrated in the northeastern section of the research area, near the town of Ourmes.

Assessment of groundwater quality for irrigation purpose in aquifers of the Upper Brahmaputra floodplains of Assam, India.

Groundwater is an essential natural resource for mankind. Due to various geogenic and anthropogenic causes, groundwater quality has raised serious concern over the years. In this study, groundwater quality was evaluated for its suitability for irrigation in the Jorhat and Golaghat Districts of Assam, India. A total of 100 groundwater samples were collected from shallow aquifers (< 35 m) from different locations during the pre-monsoon season (March-April 2022). Groundwater in the study area is slightly alkaline in nature (mean pH value of 7.44). The average cations and anions chemistry are in the order of Na+ > Ca2+ > Mg2+ > K+ and HCO3- > Cl- > SO42- > CO32-, respectively. Ca-Mg-HCO3 followed by Na-Ca-HCO3-Cl are the primary water types in the study area. Pearson's correlation matrix showed a positive correlation between TDS and EC (r = 0.78) and sodium showed a positive correlation with TDS and bicarbonate (r = 0.62 and r = 0.65), respectively. Gibbs plot indicated that rock-water interaction is the dominant factor that controls the chemistry of the groundwater of the area. Irrigation parameters like Sodium Absorption Ratio (SAR), Permeability Index (PI), Magnesium Absorption Ratio (MAR), Kelly's Ratio (KR), and Irrigation Water Quality Index (IWQI) indicated that groundwater is overall suitable for irrigation. USSL diagram illustrated that most of the samples fell into the C2 (medium salinity) and S1 (low sodium hazard) categories. Wilcox plot showed the samples fell in excellent to good categories indicating fitness of groundwater for irrigation in the area.

Evaluation of intensive remediation using simulation-optimization modeling based on long-term monitoring at a DNAPL contaminated site.

Simulation-optimization modeling is extensively used to identify optimal remediation designs. However, verifying these optimal solutions often remains unclear. In this study, we determine optimal groundwater remediation strategies using simulation-optimization modeling and assess the effectiveness of previous remediation efforts by validating optimized results through 14 years of long-term monitoring of trichloroethylene (TCE) contamination. The study site is the Road Administrative Office (RAO) in Wonju, Korea, where significant TCE contamination has occurred, and long-term in-situ remediation and monitoring have been conducted. We employ MODFLOW for simulating groundwater flow and MT3D for modeling dissolved TCE concentration distribution. The Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is applied to derive optimal groundwater remediation designs. Initial simulation results effectively predicted long-term TCE contamination trends and the impact of short-term in-situ remediation. Our evaluation involved comparing these optimal designs with field test outcomes, leading to the integration of continuous intensive pump-and-treat with in-situ remediation strategies. By comparing various modeling scenarios against long-term TCE contamination trends, we confirmed the effectiveness of previous remediation efforts and demonstrated that the optimal remediation design substantially minimized TCE concentrations at the main source zone. This study highlights successful strategies in historical contamination and remediation trend assessments, proposing an optimal design for pump-and-treat with reduced pumping stress to manage remaining TCE contamination at the site effectively.

Continuous and funnel-gate configurations of a permeable reactive barrier for reclamation of groundwater laden with tetracycline: experimental and simulation approaches.

The current study investigates removing tetracycline from water using batch, column, and tank experiments with statistical modelling using ANN for continuous tests. An artificial neural network (ANN) using the Levenberg-Marquardt back-propagation (LMA) training algorithm is constructed to compare the effectiveness of Tetracycline removal from aqueous solution using the sorption technique with prepared adsorbent. Several characterization analyses XRD, FT-IR, and SEM are employed for prepared Brownmillerite (Ca2Fe2O5)-Na alginate beads. The operating conditions of batch tests involved, contact time (0.1-3 h), initial of tetracycline (Co) of (100-250 mg/L), pH (3-12), agitation speed (50-250) rpm and dosage of adsorbent (0.2-1.2 g/50 mL). The outcomes of experiments have demonstrated that the optimum conditions for the batch test to achieve the maximum adsorbent capacity (qmax =7.845 mg/g) are achieved at pH 7, contact time 1.5 h, adsorbent dose 1.2 g/50 mL, agitation speed of 200 rpm, and initial concentration of TC 100 mg/L. Minimum mean square error (MSE) values of 7.09E-04 for 30 hidden neurons and 0.0029 for 59 hidden neurons in the 1D and 2D systems are accomplished, respectively. The artificial neural network model has exhibited excellent performance with correlation coefficients exceeding 0.980 for the operating variables, demonstrating its accuracy and effectiveness in predicting the experimental outcomes. According to sensitivity analysis, the influential parameter in the column test (1D) is the flow rate (mL/min), with a relative importance of 32.769%. However, in the tank test (2D), time (day) is signified as an influential parameter with a relative importance of 31.207%.

Groundwater geochemistry using modified integrated water quality index (IWQI) and health indices with special emphasis on nitrates and heavy metals in southern parts of Tirupati, South India.

Groundwater is particularly vulnerable to pollution in places with a high population density and extensive human usage of the land, especially in southern parts of Tirupati, India. To assess this, 60 bore-well samples were obtained and assessed for physical specifications, ion chemistry, and heavy metals during the pre- and post-monsoon seasons 2022. The current investigation employed a modified integrated water quality index (IWQI), conventional graphical and human health risk assessment (HHRA) of nitrates and heavy metals to know the groundwater chemistry and its detrimental health effects on humans. The major ions were analyzed using American public health association (APHA) standards, whereas heavy metals were analyzed using inductively coupled plasma optical emission spectrometry (ICP-OES). Additionally, pH Redox Equilibrium and C (PHREEQC), a geochemical model written in C programming language was employed to determine the saturation indices of mineral facies and ArcGIS 10.3.1 was used for spatial distribution patterns of IWQI. Then, the HHRA of nitrates and heavy metals was performed using United States environmental protection agency (US EPA) guidelines. The noteworthy outcomes include elevated levels of Ca2+, Mg2+, Cl-, NO3-, Cu, Fe, Mn, and Pb, demonstrating rock-water interaction, silicate weathering, Ca-Mg-HCO3 followed by mixed water facies, dissolution/precipitation, reverse exchange, and anthropogenic contamination are the major controlling processes in groundwater of southern Tirupati, India. The modified IWQI reveals that most groundwater samples (38%) fall under the bad quality class, with (47%) in the poor quality class and only (15%) classified as medium quality class in pre- and post-monsoon seasons. Elevated IWQI were observed in all directions except in the east, which is suitable for drinking. Moreover, the major hazard quotient (HQ) and hazard index (HI) for nitrates (NO3-) and heavy metals like copper (Cu), iron (Fe), manganese (Mn), lead (Pb) and zinc (Zn) are above the critical value of 1, revealing potential risk to humans, especially infants, followed by children and adults, entailing the instantaneous implementation of proper remedial measures and stringent policies to reduce the risk associated with groundwater pollution in the southern parts of Tirupati.

Microscale δ34S and δ18O variations of barite as an archive for fluid mixing and microbial sulphur metabolisms in igneous rock aquifers.

The stable isotope compositions of sulphur (δ34S) and oxygen (δ18O) in barite are frequently used as proxies for microbial sulphate reduction (MSR) in diverse environments, such as in relation to anaerobic oxidation of methane in marine cold seeps. There, isotopically heavy barite is used as a marker for MSR from a sulphate pool that has undergone semi-closed system conditions. Closed-system MSR is also a commonly observed feature in igneous rock hosted fracture aquifers, as shown by extremely 34S-enriched pyrite. What is less well-constrained is whether δ34S in barite can be used as a proxy for MSR in such systems. Here we explore the microscale heterogeneity of δ34S and δ18O via secondary ion mass spectrometry and the trace element Sr via LA-ICP-MS maps in barite precipitated in granite-hosted boreholes during a 17-year experiment, at Äspö, Sweden. We compare it with δ18Osulfate, δ34Ssulfate, and δ34Ssulfide of the fracture fluids and with paragenetic pyrite with δ34S values reflecting closed system MSR. The δ18O values in barite (+9.4 to +16.9 ‰) represent two generations of barite, one with low values and one with high values. The latter are likely impacted by sulphur disproportionating or -oxidizing bacteria. The barite reflects a much smaller span in δ34S (+14.5 to +28.6 ‰) than the pyrite (-47.2 to +53.3 ‰). This lack of extremely high δ34Sbarite values is proposed to be due to that barite saturation only occurred in the early parts of the Rayleigh cycle. Additionally, fluid migration has affected the δ34S values to lower values, accompanied by higher Sr concentrations. Taken together, barite δ34S values cannot be regarded as a reliable independent proxy for MSR in deep sulphate-poor igneous rock hosted aquifers. However, the relation between the δ34S values of coeval barite and pyrite is regarded as a useful proxy for MSR-related fractionation during early stages of MSR.

Visual MODFLOW, solute transport modeling, and remote sensing techniques for adapting aquifer potentiality under reclamation and climate change impacts in coastal aquifer.

Global environmental changes, such as climate change and reclamation alterations, significantly influence hydrological processes, leading to hydrologic nonstationarity and challenges in managing water availability and distribution. This study introduces a conceptual underpinning for the rational development and sustainability of groundwater resources. As one of the areas intended for the development projects within the Egyptian national plan for the reclamation of one and a half million acres; hundreds of pumping wells were constructed in the Moghra area to fulfill the reclamation demand. This study investigates the long-term impacts of exploiting the drilled pumping wells under climate change. The approach is to monitor the groundwater levels and the salinity values in the Moghra aquifer with various operational strategies and present proposed sustainable development scenarios. The impact of global warming and climate change is estimated for a prediction period of 30 years by using satellite data, time series geographical analysis, and statistical modeling. Using MODFLOW and Solute Transport (MT3DMS) modules of Visual MODFLOW USGS 2005 software, a three-dimensional (3D) finite-difference model is created to simulate groundwater flow and salinity distribution in the Moghra aquifer with the input of forecast downscaling (2020-2050) of main climatic parameters (PPT, ET, and Temp). The optimal adaptation-integrated scenario to cope with long-term groundwater withdrawal and climate change impacts is achieved when the Ministry of Irrigation and Water Resources (MWRI) recommends that the maximum drawdown shouldn't be more significant than 1.0 m/ year. In this scenario, 1,500 pumping wells are distributed with an equal space of 500 m, a pumping rate of 1,200 m3/day and input the forecast of the most significant climatic parameters after 30 years. The output results of this scenario revealed a drawdown level of 42 m and a groundwater salinity value of 16,000 mg/l. Climate change has an evident impact on groundwater quantity and quality, particularly in the unconfined coastal aquifer, which is vulnerable to saltwater intrusion and pollution of drinking water resources. The relationship between climate change and the hydrologic cycle is crucial for predicting future water availability and addressing water-related issues.

Pipe experiment elucidates biochar application depth affects nitrogen leaching under crop present condition.

Nitrogen leaching, resulting from the inefficient use of fertilizers, pollutes the environment, such as groundwater. Biochar can be applied to farmlands to mitigate nitrogen leaching. The effect depends on the application depth. However, the effect has not been examined under crop-farming conditions. Evaluating the interactions between biochar application depth and crop growth is indispensable for considering depth in the actual field. To address this, we conducted a pipe experiment with four treatments, no biochar (control), surface (0-5 cm), plow layer (0-30 cm), and subsurface (25-30 cm) applications, and compared the results with no-crop conditions from a previous study. Biochar application depth affected soil NO3--N and NH4+-N absorption ability and also influenced soil-water stress conditions, affecting crop growth. Surface biochar application improved nitrogen absorption and reduced soil-water stress, improving crop growth. The NO3--N leaching was reduced to 87.7%. Plow layer application worsened nitrogen absorption and resulted in frequent dry stress in the shallow-soil layer, preventing root growth in this layer. The NO3--N and NH4+-N leaching increased 106.4% and 264.1%, respectively. The effects of subsurface application were similar to those in the control. Selecting an appropriate application depth can simultaneously improve crop growth and reduce nitrogen leaching.

Assessment of groundwater quality in the eastern part of tehran plain: Implications for human health.

Groundwater quality is a critical concern for human health, particularly in urban areas like the eastern part of Tehran Plain, where geological features and anthropogenic activities contribute to contamination risks. This study aimed to assess the quality of groundwater in this region, focusing on its implications for public health. The objectives of the study were to identify factors influencing hydrogeochemistry, evaluate environmental risk based on metal(loid)s using water quality indices, and conduct a health risk assessment. Groundwater samples were collected and analyzed for chemistry, water quality, heavy metal contamination, and associated health risks. The results indicated a relatively stable pH condition and a wide variation in the concentration of dissolved solids. The Water Quality Index (WQI) was employed to evaluate the overall water quality, revealing that approximately 50% of the samples fell into the poor and very poor quality categories, with two samples deemed unsuitable for drinking. Heavy metal contamination varied across different metals, with some indicating low levels while others showed moderate to very high levels. Priority pollutants such as mercury and arsenic were identified as having a greater potential impact on water quality deterioration. Exposure and health risk assessments indicated a negligible risk associated with aluminum exposure but high risks associated with arsenic, chromium, and mercury exposure. Carcinogenic risk assessments for arsenic, chromium, and mercury exceeded acceptable thresholds, emphasizing the urgent need for further investigation into contamination sources and strategies for mitigation. These findings highlight the importance of continuous monitoring and sustainable groundwater management practices, providing valuable insights for other regions facing similar challenges in groundwater quality and public health.

Metaproteogenomics resolution of a high-CO2 aquifer community reveals a complex cellular adaptation of groundwater Gracilibacteria to a host-dependent lifestyle.

BACKGROUND: Bacteria of the candidate phyla radiation (CPR), constituting about 25% of the bacterial biodiversity, are characterized by small cell size and patchy genomes without complete key metabolic pathways, suggesting a symbiotic lifestyle. Gracilibacteria (BD1-5), which are part of the CPR branch, possess alternate coded genomes and have not yet been cultivated. The lifestyle of Gracilibacteria, their temporal dynamics, and activity in natural ecosystems, particularly in groundwater, has remained largely unexplored. Here, we aimed to investigate Gracilibacteria activity in situ and to discern their lifestyle based on expressed genes, using the metaproteogenome of Gracilibacteria as a function of time in the cold-water geyser Wallender Born in the Volcanic Eifel region in Germany. RESULTS: We coupled genome-resolved metagenomics and metaproteomics to investigate a cold-water geyser microbial community enriched in Gracilibacteria across a 12-day time-series. Groundwater was collected and sequentially filtered to fraction CPR and other bacteria. Based on 725 Gbps of metagenomic data, 1129 different ribosomal protein S3 marker genes, and 751 high-quality genomes (123 population genomes after dereplication), we identified dominant bacteria belonging to Gallionellales and Gracilibacteria along with keystone microbes, which were low in genomic abundance but substantially contributing to proteomic abundance. Seven high-quality Gracilibacteria genomes showed typical limitations, such as limited amino acid or nucleotide synthesis, in their central metabolism but no co-occurrence with potential hosts. The genomes of these Gracilibacteria were encoded for a high number of proteins involved in cell to cell interaction, supporting the previously surmised host-dependent lifestyle, e.g., type IV and type II secretion system subunits, transporters, and features related to cell motility, which were also detected on protein level. CONCLUSIONS: We here identified microbial keystone taxa in a high-CO2 aquifer, and revealed microbial dynamics of Gracilibacteria. Although Gracilibacteria in this ecosystem did not appear to target specific organisms in this ecosystem due to lack of co-occurrence despite enrichment on 0.2-µm filter fraction, we provide proteomic evidence for the complex machinery behind the host-dependent lifestyle of groundwater Gracilibacteria. Video Abstract.

Simulation of bench-scale CO2 injection using a coupled continuum-discrete approach.

Unintended releases of CO2 from carbon capture and storage operations presents the risk of atmospheric emissions and groundwater or surface water quality impacts. Given the potential impacts, it is valuable to have tools capable of predicting groundwater concentrations and likely pathways of CO2 migration in the subsurface. Traditional multiphase flow models struggle to simulate the discontinuous flow expected at leakage sites. This work applied a coupled continuum-discrete model, ET-MIP, to simulate a bench-scale injection of CO2. Results demonstrate the capability of ET-MIP to accurately capture gas fingering behaviour, and the complexity of multicomponent mass transfer observed in the experiment. Simulations were computationally efficient, allowing for the use of multiple displacement pressure realizations. CO2 migration in the subsurface was shown to be sensitive to mass transfer, as i) increased groundwater velocity can dissolve leaked CO2 prior to reaching the surface and ii) background dissolved gases in the subsurface can impact the rate of upwards gas movement, gas distribution, and the composition and persistence of the gas phase. The sensitivity to mass transfer suggests it may be preferable to monitor for low-solubility gases in the source mixture rather than CO2. These findings are applicable to other gases in the subsurface, such as hydrogen or methane migrating from geoenergy wells.

Hydrogeochemical dynamics under saltwater-freshwater mixing in a mangrove wetland over tidal cycles.

Seawater and groundwater interactions shape the hydrogeochemical profile of mangrove aquifers, revealing how biogeochemical processes adapt to saline-freshwater mixing via the fluctuating patterns of key hydrochemical indicators and primary biogenic elements. This study, utilizing a multi-level monitoring profile spanning the entire submerged aquifer within a mangrove wetland, analyzed the spatiotemporal dynamics of DO, ORP, pH, alkalinity and biogenic elements (C, N, S). The results revealed that among the basic hydrochemical parameters, total alkalinity showed the most stable spatiotemporal distribution and was positively correlated with salinity. pH demonstrated a significant negative correlation with salinity, whereas the correlations of ORP and DO with salinity were not substantial. The discharge of terrestrial freshwater into the mangrove wetland is marked by hydrogeochemical reactions favoring the input of Mg2+ and DIC, with potential iron mineral precipitation within the aquifer. Spatial distribution of biogenic elements in the groundwater showed no apparent pattern across sampling periods. DOC concentrations ranged from 0.3 to 1.3 mmol/L. Three components of dissolved organic matter were identified using three-dimensional fluorescence spectroscopy, with high molecular weight components (C1 + C2) accounting for an average of 47 to 73 %. Both elevated DOC concentrations and high molecular weight component ratios were primarily found in shallow layers of dense mangrove areas, decreasing with depth. Concentrations of ammonia, nitrite, and nitrate varied dynamically, reflecting active biochemical processes in the shallow to mid-layers of the aquifer. Furthermore, sulfate and sulfide concentrations, ranging from 0 to 26 mmol/L and 0.4 to 576.8 µmol/L, respectively, underscore the interplay of biogeochemical reactions, especially sulfate reduction. These findings highlight valuable insights into the complex biogeochemical processes within mangrove aquifers and provide theoretical guidance for protecting the ecological health of mangrove wetlands.

Metabarcoding reveals ecologically distinct fungal assemblages in river and groundwater along an Austrian alpine to lowland gradient.

Biodiversity, the source of origin, and ecological roles of fungi in groundwater are to this day a largely neglected field in fungal and freshwater ecology. We used DNA-based Illumina high-throughput sequence analysis of both fungal gene markers 5.8S and internal transcribed spacers region 2 (ITS2), improving taxonomic classification. This study focused on the groundwater and river mycobiome along an altitudinal and longitudinal transect of a pre-alpine valley in Austria in two seasons. Using Bayesian network modeling approaches, we identified patterns in fungal community assemblages that were mostly shaped by differences in landscape (climatic, topological, geological), and environmental conditions. While river fungi were comparatively more diverse, unique fungal assemblages could be recovered from groundwater, including typical aquatic lineages such as Rozellomycota and Olpidiomycota. The most specious assemblages in groundwater were not linked to the input of organic material from the surface, and as such, seems to be sustained by characteristic groundwater conditions. Based on what is known from closely related fungi, our results suggest that the present fungal communities potentially contribute to mineral weathering, carbon cycling and denitrification in groundwater. Furthermore, we were able to observe the effects of varying land cover due to agricultural practices on fungal biodiversity in groundwater ecosystems. This study contributes to improving our understanding of fungi in the subsurface aquatic biogeosphere.

The use of E. coli phylogrouping and microbial source tracking (non-species specific, human-specific, bovine-specific bacteroidales markers) to elucidate hydro(geo)logical contamination mechanisms in southeastern Ontario, Canada.

In Ontario, monitoring, maintenance, and treatment of private drinking systems (e.g. wells) are the responsibility of the well owner. Fecal contamination of drinking water threatens public health, particularly in rural communities which are often fully reliant on unregulated private groundwater as a primary drinking water source. Private well users face a higher risk of acute gastrointestinal illness compared to those served by municipally operated systems (Murphy et al., 2016). Accordingly, the current study sought to characterize the fecal indicator, E. coli, isolated from southeastern Ontario private groundwater wells, including phylogroups and host source. Results were examined in the context of antecedent climate and local hydrogeological setting to elucidate likely contaminant sources and pathways. A total of 737 E. coli isolates from 260 private wells were assigned to phylogroups using the Clermont PCR phylotyping method, with likely host source determined using host-specific Bacteroidales 16S rRNA RT qPCR assays. Multivariate models were developed for the main E. coli phylogroups (A, B1, B2, and D) and all microbial source tracking markers. Models were coupled for interpretation where possible, based on associations between phylogroups and MST markers. Preferential subsurface flow, and to a lesser degree, overland flow, were likely mechanisms of contamination across all models. Distinct temporal associations were found based on the fecal source. Multiple models were developed and will be discussed, in an attempt to elucidate source-specific contamination mechanisms, in support of risk assessment and appropriate protective actions.

Evaluation of potential human health risks associated with Li and their relationship with Na, K, Mg, and Ca in Romania's nationwide drinking water.

Background: Increasing lithium (Li) demand worldwide due to its properties and role in renewable energy will raise water reservoir pollution and side effects on human health. Divergent results regarding Li concentration in water and affective disorders are found in the literature, which is why regional reports are expected. Objective: The present study evaluated the occurrence and human health risks resulting from oral exposure, respectively, and the relationship between alkali metals (Li, Na, and K) and minerals (Mg, Ca) in balanced purified water (bottled) and spring water. Methods: The ICP-MS technique was used to measure a national database with 53 bottled and 42 spring water samples randomly selected. One-way ANOVA, Pearson correlation, and HCA analysis were applied to assess the possible relationship between metals in water. The possible side effects of Li poisoning of water resources on human health have been evaluated using the Estimated Daily Intake Index (EDI) and Total Hazard Quotient (THQ). Results: The toxic metals (As, Hg, and Pb) were measured, and the results indicate values above the detection limit of 22.3% of samples in the case of lead but not exceeding the safety limits. Depending on the water sources, such as bottled and spring water, the Li concentration varied between 0.06-1,557 and 0.09-984% µg/L. We found a strong positive correlation between Li and Na and Mg, varying between bottled and spring waters (p% <%0.001). Li exceeded the limit set by the Health-Based Screening Level (HBSL) in 41.37 and 19% of bottled and spring water samples. The oral reference doses (p-RfDs) for the noncancer assessment of daily oral exposure effects for a human lifetime exceeded threshold values. The THQ index shows potential adverse health effects, requiring further investigations and remedial actions in 27.58% of approved bottled waters and 2.38% of spring waters. Conclusion: We can conclude that water is safe based on the Li concentration found in drinking water and supported by a gap in strict regulations regarding human Li ingestion. The present study can serve decision-makers and represent a starting database with metals of interest for further clinical studies. Decision-makers can also use it to find solutions for sustainable management of clean and safe drinking water.

High-risk nuclide screening and parameter sensitivity analysis based on numerical simulation and machine learning.

During nuclear accidents, large quantities of radionuclides will be released into the environment, posing serious health hazards to local residents. The screening of high-risk nuclides is critical for the development of subsequent nuclear emergency response measures. In order to overcome the shortcomings of traditional screening methods, a machine learning method was proposed to screen high-risk nuclides and predict their contamination to groundwater more effectively. The performances of Support Vector Machine (SVM), Random Forest (RF) and Back Propagation Neural Network (BPNN) algorithms were compared, and sensitivity analyses of the initial leakage concentration ratio (C0/Cp), distribution coefficient (Kd) and decay coefficient (λ) on the model outputs were performed. Results showed that RF classification model achieved the highest prediction accuracy for screening high-risk nuclides. The contribution of the input parameters ranked as Kd > λ > C0/Cp. BPNN regression model was found to be the best for predicting when high-risk nuclides would pollute groundwater. The output was negatively correlated with C0/Cp and positively correlated with Kd and λ, with the parameter influence ranking as Kd > C0/Cp > λ. The contribution of Kd mainly came from itself, and the contribution of C0/Cp and λ mainly due to their interaction with other parameters.

Appraisal of contamination, hydrogeochemistry, and Monte Carlo simulation of health risks of groundwater in a lithium-rich ore area.

This study incorporated hydrogeochemical facies, the entropy-weighted water quality index (EWQI), multivariate statistics, and probabilistic human exposure assessment to investigate hydrogeochemistry, analyze groundwater quality, and estimate potential risks to human health in a lithium-rich ore area (Jadar River basin, Serbia). The findings designated the Ca·Mg-HCO3 hydrogeochemical type as the predominant type of groundwater, in which rock weathering and evaporation control the major ion chemistry. Due to the weathering of a lithium-rich mineral (Jadarite), the lithium content in the groundwater was very high, up to 567 mg/L, with a median value of 4.3 mg/L. According to the calculated EWQI, 86.4% of the samples belong to poor and extremely poor quality water for drinking. Geospatial mapping of the studied area uncovered several hotspots of severely contaminated groundwater. The risk assessment results show that groundwater contaminants pose significant non-carcinogenic and carcinogenic human health risks to residents, with most samples exceeding the allowable limits for the hazard index (HI) and the incremental lifetime cancer risk (ILCR). The ingestion exposure pathway has been identified as a critical contaminant route. Monte Carlo risk simulation made apparent that the likelihood of developing cancerous diseases is very high for both age groups. Sensitivity analysis highlighted ingestion rate and human body weight as the two most influential exposure factors on the variability of health risk assessment outcomes.