Source apportionment and ecological health risks assessment from major ions, metalloids and trace elements in multi-aquifer groundwater near the Sunan mine area, Eastern China

Groundwater Safety and Availability Index (GSAI) and its association with salinity indicators

This study assesses the quality of groundwater in the Odra River Basin in Poland, focussing on environmental health risks, temporal variability, and their association with salinity indices. A new indicator, the Groundwater Safety and Availability Index (GSAI), was developed to evaluate groundwater resources by integrating health risk and resource quantity factors, providing a novel tool for ranking water resources and informing environmental and administrative decision-making. Groundwater samples were collected between 2005 and 2021 and analysed in accordance with national standards. The results demonstrate an improvement in groundwater quality over time, indicated by a reduction in Health Index (HI) values, particularly in Lower Silesia, Lubusz, and Silesia. Significant correlations were found between HI and NO₃- (τ-Kendall = 0.40) and arsenic (τ-Kendall = 0.55). GSAI values varied across regions, with West Pomerania showing the highest groundwater safety and availability, while Silesia had the lowest. Elevated concentrations of contaminants such as arsenic and nitrates were found to significantly impact water safety, particularly during hydrogeological droughts. These findings support the need for region-specific management strategies to ensure sustainable groundwater use and mitigate health risks, with the GSAI serving as a valuable tool for policymakers and environmental planners.

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.

Identification of hydrogeochemical processes in shallow groundwater using multivariate statistical analysis and inverse geochemical modeling

Identifying key factors that control the chemical evolution of groundwater along groundwater flow direction is essential in ensuring the safety of groundwater resources in upper watersheds and lower plains. In this study, the ion ratio, multivariate statistics, and inverse geochemical modeling were used to investigate and explore the chemical characteristics of groundwater and factors driving the formation of groundwater components in the plain area of Deyang City, China. The chemical type of groundwater in the area was dominated by the HCO3-Ca type, and the variation in groundwater chemical composition was mainly affected by water-rock interaction and human interference. The water-rock interaction process includes carbonate dissolution, oxidation-reduction reactions, and cation exchange. Furthermore, inverse geochemical modeling revealed that the dissolution of evaporite minerals, dissolution/precipitation of carbonate minerals, and weathering of silicate minerals play a key role in the hydrogeochemical evolution of groundwater. Owing to dissimilar geological and hydrological conditions, hydrogeochemical evolution processes differ along different and similar paths. Overall, this study not only provides a conceptual framework for hydrochemical evolution in plains but also has important implications for the sustainable management of groundwater resources in other basins within plains.

Unravelling integrated groundwater management in pollution-prone agricultural cities: A synergistic approach combining probabilistic risk, source apportionment and artificial intelligence

Groundwater is vital for agricultural cities, but intensive farming and fertilizer use have increased contamination risks, particularly for non-carcinogenic health hazards. This study reveals the sources of contaminants in groundwater, their health impacts, and targeted strategies in such cities. The study analyzed 115 groundwater samples, with the main groundwater chemical type being HCO₃-Na·Ca. Significant exceedances were found in Mg²⁺, HCO₃-, F-, total hardness (TH), and Mn, with HCO₃- and Mg²⁺ surpassing standards in nearly all samples. The average Comprehensive Environmental Water Quality Index (CEWQI) was 100.68, indicating that overall groundwater quality in the study area is good. High-quality water is mainly found near reservoirs and rivers, while urban and eastern regions have relatively poorer water quality. The proportion of groundwater unsuitable for drinking is low. Monte Carlo risk assessments revealed that F- and NO₃- pose non-carcinogenic risks to both adults and children, with NO₃- presenting a higher potential health risk. The Positive Matrix Factorization (PMF) model identified that groundwater pollution primarily results from natural geological processes and human activities, with agriculture being the major anthropogenic factor. AI-based zoning strategies highlighted industrial areas and high-fluoride zones as critical areas requiring enhanced prevention and control measures.

Simultaneous removal of groundwater manganese and ammonia nitrogen based on high-flux gravity driven ceramic membrane (HF-GDCM) coupled with aerated fluidized birnessite

High concentrations of manganese ion (Mn2+) and ammonia nitrogen (NH3-N) in groundwater are indicative of a critical environmental issue that necessitates immediate attention. The gravity-driven ceramic membrane (GDCM) technology has shown great potential for groundwater treatment in rural communities, owing to its low energy demand and user-friendly operation. Active manganese oxide (MnOx) is extensively used for the concurrent removal of Mn2+ and NH3-N, leveraging its large specific surface area and abundant adsorption sites. Our research group has developed a GDCM-MnOx coupled system to address this challenge. However, membrane fouling, manifested as a reduction in flux or an increase in transmembrane pressure, has been a significant barrier to its widespread adoption. To address this challenge, we have implemented a continuous aeration system in conjunction with GDCM to fluidize birnessite to achieve the higher membrane flux, which has also proven effective in mitigating fouling while maintaining high water purification performance. Over a period of 100 days or more, the high membrane flux in the high-flux GDCM system (HF-GDCM) enhanced with aerated fluidized birnessite has been consistently maintained at approximately 34 L/(m2·h) at a water head of 1 m. Moreover, the HF-GDCM system efficiently removed manganese and NH3-N from groundwater under a hydraulic retention time (HRT) of less than 2.5 h, while also improving membrane permeability. The involvement of manganese oxidizing bacteria (MnOB) and ammonium-oxidizing bacteria (AOB) of Hypomicrobium and Nocardioides in the removal processes within the HF-GDCM system was confirmed. Additionally, XPS analysis confirmed the predominant oxidation state of MnOx to be Mn(III). The MnOx, deposited on powdered activated carbon (PAC) particles in a flower-like configuration, progressively formed a birnessite-like functional layer as the manganese ion content increased over time. Consequently, the HF-GDCM coupled with aerated fluidized birnessite is deemed suitable for water purification in small-scale rural or reservoir settings.

Source-oriented health risk assessment of groundwater based on hydrochemistry and two-dimensional Monte Carlo simulation

Accurately assessing the health risks posed by major contaminants is essential for protecting groundwater. However, the complexity of pollution sources and the uncertainty of parameters pose challenges for quantitative health risk assessment. In this study, a source-oriented groundwater risk evaluation process was improved by screening key pollutants, employing a combined hydrochemical and positive matrix factorization (PMF) approach for source apportionment, and incorporating two-dimensional Monte Carlo simulation for risk characterization. The application of this process to groundwater assessment in Central Jiangxi Province identified NO3-, F-, Se and Mn as the key pollutants. The pollution sources were anthropogenic activities, rock dissolution, regional geological processes, and ion exchange. Anthropogenic sources contributed 36.8 % and 28.8 % of the pollution during the wet season and dry season, respectively, and accounted for more than half of the health risks. NO3- from anthropogenic sources was the primary controlling pollutant. Additionally, the risk assessment indicated that children were at the highest health risk during the dry season, with ingestion rate suggested to be controlled below 1.062 L·day-1 to make the health risk within an acceptable range. The improved assessment methodology could provide more accurate results and recommended intakes.

Natural background level, source apportionment and health risk assessment of potentially toxic elements in multi-layer aquifers of arid area in Northwest China

Groundwater contaminated by potentially toxic elements has become an increasing global concern for human health. Therefore, it is crucial to identify the sources and health risks of potentially toxic elements, especially in arid areas. Despite the necessity, there is a notable research gap concerning the sources and risks of these elements within multi-layer aquifers in such regions. To address this gap, 54 phreatic and 24 confined groundwater samples were collected from an arid area in Northwest China. This study aimed to trace the sources and evaluate the human health risks of potentially toxic elements by natural background level (NBL), positive matrix factorization (PMF) model, and health risk model. Findings revealed exceeding levels of potentially toxic elements existed in phreatic and confined aquifers. Source apportionment and NBL results indicated that mineral dissolution, evaporation, redox reactions, and human activities were the main factors for elevated concentrations of potentially toxic elements. High Fe and Mn concentrations were attributed to reduction environments, while F accumulation resulted from slow runoff, and irrigation from the Yellow River. Due to high F levels, more than one-third of groundwater samples (phreatic: 33.14 %, confined: 56.22 %) posed non-carcinogenic health risks to population groups. Adults displayed higher carcinogenic risks (phreatic: 19.47 %, confined: 34.16 %) than infants (phreatic: 0 %, confined: 0 %) and children (phreatic: 1.26 %, confined: 7.97 %) owing to the toxic elements of Cr. The confined aquifer presented greater health risks than the phreatic aquifer. Consequently, controlling the levels of F and Cr in multi-layered aquifers is key to reducing health risks. These findings provide valuable insights into protecting groundwater from contamination by potentially toxic elements in multi-layered aquifers worldwide.

Perfluoroalkyl compounds in groundwater alter the spatial pattern of health risk in an arsenic‑cadmium contaminated region

Integrated health risk assessment strategies for emerging organic pollutants and heavy metals that coexist in water/soil media are lacking. Contents of perfluoroalkyl compounds and potentially toxic elements in multiple media were determined by investigating a county where a landfill and a tungsten mine coexist. The spatial characteristics and sources of contaminants were predicted by Geostatistics-based and multivariate statistical analysis, and their comprehensive health risks were assessed. The average contents of perfluorooctane acid, perfluorooctanesulfonic acid, arsenic, and cadmium in groundwater were 3.21, 0.77, 1.69, and 0.14 μg L-1, respectively; the maximum content of cadmium in soils and rice highly reached 2.12 and 1.52 mg kg-1, respectively. In soils, the contribution of mine lag to cadmium was 99 %, and fertilizer and pesticide to arsenic was 59.4 %. While in groundwater, arsenic, cadmium and perfluoroalkyl compounds near the landfill mainly came from leachate leakage. Significant correlations were found between arsenic in groundwater and arsenic and cadmium in soils, as well as perfluoroalkyl compounds in groundwater and pH and sulfate. Based on these correlations, the geographically optimal similarity model predicted high-level arsenic in groundwater near the tungsten mine and cadmium/perfluoroalkyl compounds around the landfill. The combination of analytic network process, entropy weighting method and game theory-based trade-off method with risk assessment model can assess the comprehensive risks of multiple pollutants. Using this approach, a high health-risk zone located around the landfill, which was mainly attributed to the presence of arsenic, cadmium and perfluorooctanesulfonic acid, was found. Overall, perfluoroalkyl compounds in groundwater altered the spatial pattern of health risks in an arsenic‑cadmium contaminated area.

Occupational, environmental, and toxicological health risks of mining metals for lithium-ion batteries: a narrative review of the Pubmed database

BACKGROUND

The global market for lithium-ion batteries (LIBs) is growing exponentially, resulting in an increase in mining activities for the metals needed for manufacturing LIBs. Cobalt, lithium, manganese, and nickel are four of the metals most used in the construction of LIBs, and each has known toxicological risks associated with exposure. Mining for these metals poses potential human health risks via occupational and environmental exposures; however, there is a paucity of data surrounding the risks of increasing mining activity. The objective of this review was to characterize these risks.

METHODS

We conducted a review of the literature via a systematic search of the PubMed database on the health effects of mining for cobalt, lithium, manganese, and nickel. We included articles that (1) reported original research, (2) reported outcomes directly related to human health, (3) assessed exposure to mining for cobalt, lithium, manganese, or nickel, and (4) had an available English translation. We excluded all other articles. Our search identified 183 relevant articles.

RESULTS

Toxicological hazards were reported in 110 studies. Exposure to cobalt and nickel mining were most associated with respiratory toxicity, while exposure to manganese mining was most associated with neurologic toxicity. Notably, no articles were identified that assessed lithium toxicity associated with mining exposure. Traumatic hazards were reported in six studies. Three articles reported infectious disease hazards, while six studies reported effects on mental health. Several studies reported increased health risks in children compared to adults.

CONCLUSIONS

The results of this review suggest that occupational and environmental exposure to mining metals used in LIBs presents significant risks to human health that result in both acute and chronic toxicities. Further research is needed to better characterize these risks, particularly regarding lithium mining.

Natural background levels, source apportionment and health risks of potentially toxic elements in groundwater of highly urbanized area

Identifying the natural background levels (NBLs), threshold values (TVs), sources and health risks of potentially toxic elements in groundwater is crucial for ensuring the water security of residents in highly urbanized areas. In this study, 96 groundwater samples were collected in urban area of Sichuan Basin, SW China. The concentrations of potentially toxic elements (Li, Fe, Cu, Zn, Al, Pb, B, Ba and Ni) were analyzed for investigating the NBLs, TVs, sources and health risks. The potentially toxic elements followed the concentration order of Fe > Ba > B > Al > Zn > Li > Cu > Ni > Pb. The NBLs and TVs indicated the contamination of potentially toxic elements mainly occurred in the northern and central parts of the study area. The Positive Matrix Factorization (PMF) model identified elevated concentrations of Fe, Al, Li, and B were found to determine groundwater quality. The primary sources of Fe, Al, Pb, and Ni were attributed to the dissolution of oxidation products, with Fe additionally affected by anthropogenic reduction environments. Li and B were determined to be originated from the weathering of tourmaline. High levels of Ni and Cu concentrations were derived from electronic waste leakage, while excessive Ba and Zn were linked to factory emissions and tire wear. The reasonable maximum exposure (RME) of hazard index (HI) was higher than safety standard and reveal the potential health risks in the southwestern study area. Sensitivity analysis demonstrated the Li concentrations possessed the highest weight contributing to health risk. This study provides a valuable information for source-specific risk assessments of potentially toxic elements in groundwater associated with urban areas.

Determination of high-risk factors and related spatially influencing variables of heavy metals in groundwater

Identifying high-risk factors (heavy metals (HMs) and pollution sources) by coupling receptor models and health risk assessment model (HRA) is a novel approach within the field of risk assessment. However, this coupled model ignores the contribution of spatial differentiation to high-risk factors, resulting in the assessment being subjective. Taking Dongting Plain (DTP) as an example, a coupling framework by jointly using the positive matrix factorization model (PMF), HRA, Monte Carlo simulation, and geo-detector was developed, aiming to identify high-risk factors in groundwater, and further explore key environmental variables influencing the spatial heterogeneity of high-risk factors. The results showed that at least 82.86 % of non-carcinogenic risks and 97.41 % of carcinogenic risks were unacceptable for people of all ages, especially infants and children. According to the relationships among HMs, pollution sources, and health risks, As and natural sources were defined as high-risk HMs and sources, respectively. The interactions among Holocene thickness, oxidation-reduction potential, and dissolved organic carbon emerged as the primary drivers of spatial variability in high-risk factors, with their combined explanatory power reaching up to 74%. This proposed framework provides a scientific reference for future studies and a practical reference for environmental authorities in developing effective pollution management measures.

Using unsupervised machine learning models to drive groundwater chemistry and associated health risks in Indo-Bangla Sundarban region

Groundwater is an essential resource in the Sundarban regions of India and Bangladesh, but its quality is deteriorating due to anthropogenic impacts. However, the integrated factors affecting groundwater chemistry, source distribution, and health risk are poorly understood along the Indo-Bangla coastal border. The goal of this study is to assess groundwater chemistry, associated driving factors, source contributions, and potential non-carcinogenic health risks (PN-CHR) using unsupervised machine learning models such as a self-organizing map (SOM), positive matrix factorization (PMF), ion ratios, and Monte Carlo simulation. For the Sundarban part of Bangladesh, the SOM clustering approach yielded six clusters, while it yielded five for the Indian Sundarbans. The SOM results showed high correlations among Ca2+, Mg2+, and K+, indicating a common origin. In the Bangladesh Sundarbans, mixed water predominated in all clusters except for cluster 3, whereas in the Indian Sundarbans, Cl--Na+ and mixed water dominated in clusters 1 and 2, and both water types dominated the remaining clusters. Coupling of SOM, PMF, and ionic ratios identified rock weathering as a driving factor for groundwater chemistry. Clusters 1 and 3 were found to be influenced by mineral dissolution and geogenic inputs (overall contribution of 47.7%), while agricultural and industrial effluents dominated clusters 4 and 5 (contribution of 52.7%) in the Bangladesh Sundarbans. Industrial effluents and agricultural activities were associated with clusters 3, 4, and 5 (contributions of 29.5% and 25.4%, respectively) and geogenic sources (contributions of 23 and 22.1% in clusters 1 and 2) in Indian Sundarbans. The probabilistic health risk assessment showed that NO3- poses a higher PN-CHR risk to human health than F- and As, and that potential risk to children is more evident in the Bangladesh Sundarban area than in the Indian Sundarbans. Local authorities must take urgent action to control NO3- emissions in the Indo-Bangla Sundarbans region.

Multiple stable isotopes and geochemical approaches to elucidate groundwater reactive transport paths in mining cities: A case from the northern Anhui, China

Mining cities are ecotone areas where human and natural components interact. Indeed, the negative effects of mining activities on drinking water quality have become a serious public concern worldwide. To elucidate groundwater genesis and reactive transport path controlling the water pollution, a multi-bodies system in the Sunan Mine area in China was considered in this study. The results of the mineral phase characterizations, hydrochemical analysis, and multiple stable isotopes (δ2H/δ18O, δ34S and 87Sr/86Sr) indicated that calcite, dolomite, gypsum, quartz, halite, organic carbon, and gases (O2, CO2 and H2O) were the primary reactants in the aquifer system, accompanied by dissolution and precipitation of minerals, cation exchange, desulfation, and evaporation. An inverse hydrogeochemical model was employed to identify three paths, Path 1 demonstrated that mine water mainly originated from the Quaternary loose aquifer water (QLA), Permian fractured sandstone aquifer water (PFA), and Carbonifer fractured limestone aquifer water (CFA), accompanied by high K++Na+ and HCO3- concentrations due to the carbonate dissolution, halite dissolution, and cation exchange processes. Path 2 showed that the recharge of the CFA and Ordovician fractured limestone aquifer (OFA) occurred from the shallow recharge zone to the deeper OFA water through faults and fractures, mainly involving halite dissolution, carbonate dissolution, and gypsum dissolution. Path 3 demonstrated the interaction between the Hui River, collapsed pond water, and QLA, accompanied by gypsum dissolution, calcite dissolution, and cation exchange. Although the shallow QLA quality met the WHO drinking water standards, the pollution risk from the surface collapse pit water cannot be ignored. Therefore, effective approaches need to be considered in the study area to reduce the connection between the collapse pit water and QLA. The study results can help decision makers to predict water quality of complex water systems in ecotone areas and other similar regions worldwide.

Groundwater pollution source identification and health risk assessment in the North Anhui Plain, eastern China: Insights from positive matrix factorization and Monte Carlo simulation

Groundwater contaminants from natural and anthropogenic sources pose a serious threat to the ecological environment and public health. In this study, 30 groundwater samples were collected from shallow wells at a large central water source in the North Anhui Plain, eastern China. Hydrogeochemical methods, positive matrix factorization (PMF) model, and Monte Carlo simulation were used to determine the characteristics, sources, and human health risks of inorganic and organic analytes in groundwater. The groundwater was weakly alkaline with high total hardness and was dominated by HCO3-Mg·Ca, HCO3-Ca·Mg, and HCO3-Ca·Mg·Na hydrochemical facies. The concentration of naphthalene was at a safe level, while the concentrations of F-, NO3- and Mn in 16.7 %, 26.7 % and 40 % of the samples, respectively, exceeded threshold risk-based values based on Chinese groundwater quality standards. Hydrogeochemical methods revealed that water-rock interactions (including weathering of silicate minerals, dissolution of carbonates, and cation exchange), acidity, and runoff conditions control the migration and enrichment of these analytes in groundwater. The PMF model indicated that local geogenic processes, hydrogeochemical evolution, agricultural activities, and petroleum-related industrial sources were the main factors affecting groundwater quality, with contributions of 38.2 %, 33.7 %, 17.8 %, and 10.3 %, respectively. A health risk evaluation model based on Monte Carlo simulation indicated that 77.9 % of children were exposed to a total noncarcinogenic risk above safe thresholds, about 3.4 times higher than the risk to adults. The main contributor to human health risk was F- originating from geogenic processes; thus, F- was identified as a priority for control. This study demonstrates the feasibility and reliability of combining source apportionment techniques and health risk assessment to evaluate groundwater quality.

Characterization of trace and heavy metal concentration in groundwater: A case study from a tropical river basin of southern India

This study investigates the hydrogeochemistry of groundwater samples collected from the Shiriya River Basin (SRB), a tropical watershed located in Kasaragod, Kerala, southern India, with a special focus on trace elements. Fifty-four groundwater samples were collected from deep aquifers, which constitute weathered and fractured granitoids and mafic rocks, and the groundwater is tapped by bore wells from a fractured zone at a depth range of 60-100 m. Concentrations of Sr, Li, Ba, Al, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Cd, Ag, Au, Te, Pb, Re, and PGEs in groundwater were determined by using Q-ICPMS. Out of the 25 analysed trace elements in groundwater, only Sr (489.6 μg/L), Ba (226 μg/L), Li (11.76 μg/L) Mn (396.8 μg/L), Ni (68 μg/L) and Fe (2438.5 μg/L) show anomalous values. The PGEs and the majority of trace elements show values within the permissible limit. Raman spectral studies reveal the presence of celsian in aquifer rocks and are the source of Ba in groundwater. Further, XRF data of the rocks show a high enrichment of Fe and Mn in mafic dyke, basalt, and syenite, and Ba and Sr in granite, pegmatite, and granitic gneiss. Therefore, this study proved that the source of these elements is geogenic, i.e., they are released from the crystalline aquifer through rock-water interaction under alkaline conditions. The results of this study show that the groundwater of the basin has enough metals such as Na, K, Mg, Ca, Mn, Fe, Co, Cu, and Zn, which are good for health. Nevertheless, a few metals (Fe, Mn, Ba, Sr, Li, Ni) that may exert toxic effects on humans are also present in the groundwater of the SRB. As groundwater is found to be a dependable source of drinking water in such watersheds, a comprehensive study on the hydrogeochemistry of all watersheds in tropical regions is recommended.

Hydrothermal alkaline synthesis and release properties of silicon compound fertiliser using high-ash coal slime

High-ash coal slime is difficult to utilise as a boiler fuel, and its accumulation results in environmental pollution. In this study, we describe a new method for the preparation of high-ash coal slime silica compound fertiliser (HASF) using CaO-KOH mixed hydrothermal method to optimize the utilization of this industrial waste and relieve the pressure on the fertiliser industry. The coal slime (D0) used in this study and its dry basis ash content by 1 mol/L and 4 mol/L sulfuric acid pre-activation (D1, D4) were greater than 85%. The effective silicon content of D0, D1, and D4 silica compound fertilisers reached 30.24%, 31.24%, and 17.35%, respectively, and the sums of effective silica-calcium-potassium oxides were 57.28%, 58.87%, and 48.16%, respectively, under the optimal reaction conditions of 230 °C, 15 h, and 1 mol/L KOH, which met the market requirements, as determined using single-factor experiments. We used XRD, FTIR, and SEM-EDS analysis techniques to demonstrate that tobermorite and leucite were the main mineral phases of the compound fertiliser, and activated coal slime D4, which contains only quartz single crystals, required more demanding reaction conditions in the synthesis reaction. Subsequently, the cumulative release pattern of HASF silica was well described by the power function equation via repeated extraction and dissolution experiments, with the dissolution rate following D4 > D1 ≈ D0. Furthermore, 4 mol/L sulfuric acid pre-activation resulted in the enrichment of HASF combined with organic matter and increased the slow-release rate of HASF silica. Thus, the synthesized HASF could have potential application prospects in soil improvement and fertilisation.

Anthropogenic processes drive heterogeneous distributions of toxic elements in shallow groundwater around a smelting site

Smelting activities have a far-reaching influence on the quality of soil and groundwater, while most studies have neglected the information on the pollution characteristics of groundwater. The hydrochemical parameters of shallow groundwater and the spatial distributions of toxic elements were investigated in this study. Correlations analysis and groundwater evolution revealed that the major ions were primarily determined by silicate weathering and calcite dissolution process, and anthropogenic processes had a significant effect on groundwater hydrochemistry. Almost 79%, 71%, 57%, 89%, 100%, and 78.6% of samples exceeded the standards of Cd, Zn, Pb, As, SO₄^2-, and NO₃^-, and their distribution is closely related to the production process. Analysis of soil geochemistry indicated that the relatively mobile forms of toxic elements strongly influence the origin and concentration in shallow groundwater. Besides, rainfall with high magnitude would lead to a decrease of toxic elements in shallow groundwater, whereas the area once stacked waste residue was the opposite. It is recommended to strengthen risk management of the limited mobility fraction while devising a plan for waste residue treatment in accordance with the local pollution conditions. The research on controlling the mechanism of toxic elements in shallow groundwater, along with sustainable development in the study area and other smelting zones may benefit from this study.

Characterizing spatial dependence of boron, arsenic, and other trace elements for Permian groundwater in Northern Anhui plain coal mining area, China, using spatial autocorrelation index and geostatistics

Anthropogenic and geological factors play an essential role in the variability of groundwater quality, resulting in a weak spatial dependence of groundwater trace elements. Thus, it is an essential study to investigate the factors affecting groundwater quality and its spatial abundance of trace elements (including As, B, and other metalloids). In this study, samples are obtained from a Permian sandstone fracture aquifer in a coal mining area. A multivariate statistical analysis, hydrogeochemistry modeling, and spatial autocorrelation analysis were used to analyze the data. The results showed that Moran index was positive for all trace elements, which had good spatial autocorrelation. The Local indicators of spatial association (LISA) indicated that trace elements were clustered. The hydrogeochemical modeling results indicated that the precipitation and stability of iron-phase minerals, such as rhodochrosite and arsenic (As) absorption on the surface of iron-phase minerals in the aquifer, may limit concentrations in the southern region. The spatial autocorrelations of both As and Boron (B) were positive (high-high) in the western areas, indicating that As contamination occurred from both natural geological causes and human coal mining activities. In contrast, B contamination was mainly linked to the influence of human agricultural or industrial activities. Over 96% of the groundwater concentrations of As (10 μg/L) and B (300 μg/L) in the study area exceeded World Health Organization (WHO) limits. Overall, the results of this work could help decision-makers involved in regional water quality management visualize disperse zones where specific anthropogenic and geological processes may threaten groundwater quality.