Pollution characteristics and source identification of soil metal(loid)s at an abandoned arsenic-containing mine, China

Distribution and biotransfer of potentially toxic elements in a terrestrial ecosystem from an abandoned realgar mine

The present study was conducted to examine the trophic transfer of potentially toxic elements (PTEs) in a closed arsenic mine. Eight PTEs in a soil-plant-leaf litter-earthworm-top predators (free-range local chicken and wild passerine bird) system were analyzed for nitrogen and carbon stable isotopes, PTE concentrations, bioaccumulation factors (BAFs), and transfer factors (TFs). The PTE concentrations in soils from mining areas were generally higher than a adjacent controlled area, with As and Cd in soils showing the prominent compared to other six PTEs, as seen for the indices of geo-accumulation index (Igeo), pollution index (PI) and potential ecological risk index (RI). The relatively high BAF and TF values suggested a distinct biotransfer of PTEs along the soil-plant-leaf litter-earthworm system. BAFs were mostly <1 except in earthworms, indicating that earthworms had a strong capacity to take up these metals. The TFs varied both among PTEs and organism's species, e.g., the transfer capacities of As in Pteris vittata and Pteris cretica, Cd in Miscanthus sinensis, and Pb, Cr and Mn in moss were the highest. For local free-range chicken and wild passerine bird, the concentrations of PTEs were higher in gastric contents and feather than in internal tissue (stomach, liver and heart), with lower contents in muscle and egg. Bioaccumulation of PTEs generally decreased from decomposer earthworms, to primary producer plants, to top predator, indicating a potential bio-dilution tendency in higher trophic levels in the terrestrial food chain.

Accurate prediction of spatial distribution of soil heavy metal in complex mining terrain using an improved machine learning method

Accurate prediction of heavy metals (HMs) spatial distribution in mining areas is crucial for pollution management. However, predicting the spatial distribution of HMs remains a significant challenge in mining areas with complex terrain and variable contaminant transport pathways. This study aims to optimize the spatial prediction of arsenic (As) distribution in the Shimen realgar mining area, the largest in Asia, by integrating machine learning models with kriging interpolation and feature selection techniques. The results show that the Random Forest (RF) model achieved the best performance in predicting soil As concentration, with an R2 of 0.84 for the test data. Incorporating environmental variables improved the spatial prediction accuracy, with RF (R2 = 0.76, RMSE = 24.68 mg/kg) and Random Forest Regression Kriging (RFRK) (R2 = 0.78, RMSE = 23.46 mg/kg) outperforming ordinary kriging and geographically weighted regression kriging. Importance analysis and recursive feature elimination further optimized the model, leading to a 5 % increase in R2 and a reduction of RMSE by 8 %-12.4 %. The optimized RFRK model accurately captured the spatial distribution of As in the mining area, revealing the outward diffusion pattern of As from the smelting plant. The findings highlight the critical role of feature selection in improving prediction accuracy in highly polluted and complex terrain regions, an aspect that has often been overlooked in previous studies. This study provides a practical framework for spatial prediction of contaminants in similar areas, enhancing the understanding of pollution distribution.

The role of SLC7A11 in arsenite-induced oncogenic phenotypes of human bronchial epithelial cells: A metabolic perspective

Chronic arsenic exposure enhances the probability of lung cancer with the underlying mechanisms remain unknown. Glutamine-driven synthetic metabolism, including nucleotide synthesis, amino acid production, TCA cycle replenishment, glutathione synthesis, and lipid biosynthesis, is crucial for both cancer initiation and progression. This study demonstrated that chronic exposure to 0.1 μM arsenite for as long as 36 weeks induced malignant transformation in human bronchial epithelial cells (BEAS-2B). Metabolomics were used to systematically disclose metabolic characteristics in arsenic-transformed malignant (As-TM) cells. Significantly changed metabolites were enriched in alanine, aspartate and glutamate metabolism, arginine biosynthesis, glutamine and glutamate metabolism, glutathione metabolism, butanoate metabolism, TCA cycle, and arginine and proline metabolism. It is worth noting that glutamate located at the intersection of the enriched metabolism pathways. Glutamine deprivation attenuated the oncogenic phenotypes, including capacity of wound healing and proliferation, in As-TM cells. And the expression levels of mRNA and proteins associated with glutamine metabolism-related transporters and enzymes, including SLC7A11, GCLM, and GCLC, were significantly increased, with SLC7A11 exhibiting the most substantial increase. Moreover, arsenite transformation progressively elevated SLC7A11 mRNA and protein levels over time. The SLC7A11 inhibitor sulfasalazine remarkably attenuated arsenite-induced oncogenic phenotypes. Collectively, our data suggest that chronic arsenite exposure enhances glutamine metabolism through upregulation of SLC7A11, thereby promoting cell proliferation and malignant transformation. These results provide new insights for preventive and therapeutic strategies for lung cancer linked to arsenic exposure.

Application of machine learning in soil heavy metals pollution assessment in the southeastern Tibetan plateau

The Tibetan Plateau, a globally significant ecological region, is experiencing escalating pollution from heavy metals (HMs). This study applies a machine learning approach based on the self-organizing map hyper-clustering, alongside advanced methodologies such as Positive Matrix Factorization (PMF), Incremental Spatial Autocorrelation, and Bivariate Local Indicators of Spatial Association (BiLISA), to analyze the ecological risk of soil HMs in representative watersheds of the southeastern Tibetan Plateau, focusing on spatial pattern clustering, pollutant source identification, and interaction risk assessment. The results indicated higher HMs concentrations in the middle and downstream areas. A comprehensive ecological risk assessment integrating the Improved Potential Ecological Risk Index, Enrichment Factor, Contamination Factor, and Geo-accumulation Index identified Cd, Pb, and As as the primary pollutants of concern. By combining PMF with Mantel analysis, pollution was attributed to geological background, agricultural activities, traffic emissions, and atmospheric deposition. The BiLISA method revealed significant spatial interactions among HMs, with the composite pollution of As and Cd occupying the largest proportion in High (As)-High (Cd) aggregation zones, underscoring the need for integrated management strategies. This study offers novel insights into the spatial pollution patterns and source apportionment of soil HMs, providing an advanced analytical framework for their precise control and ecological restoration.

Integrating spatial heterogeneity and speciation dynamics in source apportionment of toxic metal(loid)s at an abandoned hydrometallurgical zinc smelting site

Zinc hydrometallurgy sites are critical hotspots for combined toxic metal(loid)s (TMs) pollution, yet the integration of spatial heterogeneity and migration dynamics into source apportionment remains underexplored. This study investigated the concentrations, speciation, and spatial distribution of nine TMs (As, Cd, Cu, Hg, Mn, Ni, Pb, Sb, Zn) in soils at an abandoned zinc smelter in southwest China. Multivariate statistical methods and the Positive matrix factorization (PMF) model were applied to disentangle primary sources and secondary redistribution. Spatial analysis revealed that As, Cd, Cu, Pb, Sb, and Zn shared similar contamination patterns, concentrated in slag storage and comprehensive recovery areas, whereas Hg and Mn exhibited distinct hotspots near sulfuric acid production and electrolysis zones. Vertical migration was most pronounced for Cd and Zn (> 8 m depth), followed by Hg and Mn (4-8 m), while As, Cu, Pb, and Sb were restricted to 0-4 m due to adsorption in clay-rich layers. Speciation analysis indicated high mobility of Cd and Zn (acid-soluble fraction: 66.96 and 52.10%, respectively), contrasting with reducible Pb and Mn (51.59 and 48.32%) and residual As, Hg, Ni, Sb (60.74-76.64%). The results from PMF model identified aqueous-phase (Cd, Zn, Mn) and solid-phase (As, Cu, Pb, Sb) migration pathways, validated by spatial correlations with topography and functional zones. Aqueous-phase contributions dominated low-lying areas, while solid-phase contributions aligned with elevated regions, reflecting topography-driven redistribution. This study advances source apportionment of TM in soil by unifying spatial heterogeneity, speciation dynamics, and receptor modeling, offering a framework for targeted risk assessment and remediation of industrial sites.

Source-specific soil heavy metal risk assessment in arsenic waste mine site of Yunnan: Integrating environmental and biological factors

This study quantified heavy metal (HM) pollution risks in mining site soils to provide targeted solutions for environmental remediation. Focusing on As waste mine sites in Yunnan, we utilised multiple indices and a positive matrix factorisation model to assess and quantify ecological health risks. Our ecological risk assessment distinguished between environmental and biological factors. This study demonstrated that As and Pb are the most impactful contaminants in environmental and biological contexts, respectively. Notably, the quantification of ecological risk sources indicated that agricultural sources were the main environmental influencers, accounting for 58.45 % of the total impact. Consequently, Cu from agricultural sources has become a primary environmental HM target, replacing As. In the quantification of health risk sources, mining and smelting activities predominantly contributed to health risks, contributing 23 % and 39.81 % of the Non-Carcinogenic Risk and 47.98 % and 42.96 % of the Carcinogenic Risk, respectively. The representative pollution source elements As and Cd were consistent with the health risk assessment results. This study refined the ecological risk assessment framework by distinguishing between environmental and biological factors, providing crucial insights into the rehabilitation of mine sites and formulation of effective environmental management strategies.

pH induced incongruent-dissolution impacts Al-ferrihydrite transformations and As mobilization

This study investigated the role of Al and As fate during the transformation process of ferrihydrite influenced by different pH values under oxic conditions. The results indicate that the Al doping greatly enhanced the transformation of ferrihydrite (Fh) to Al-substituted goethite at all acidic or alkaline pH values under oxic conditions by promoting the incongruent dissolution and reprecipitation reactions of Al-substituted ferrihydrite (AlFh). Under acidic conditions, the preferential dissolution of structural Fe (4.73 mg/L) from AlFh occurs, whereas under alkaline conditions, the preferential dissolution of structural Al (1.25 mg/L) takes place. In contrast, under neutral conditions, the low solubility of Fh and AlFh induces the significant particle assembly, with Fe/Al minerals primarily transforming into goethite through oriented aggregation. As predominantly remains in an adsorbed state at all pH values during the transformation of Fh and AlFh, with the highest proportion of adsorbed As (86.9-96.7%) observed under neutral conditions. During the aging process, the adsorbed As gradually transforms into non-extractable As, and the changes in As speciation within Fe/Al minerals are closely coupled with the transformation of AlFh and Fh. Under alkaline and acidic conditions, the proportion of non-extractable As in the transformation products of Fh and AlFh increases by 14.02-19.72% and 12.27-16.28%, respectively, while under neutral conditions, it increases only by 12-13.02%. Therefore, regulating soil pH can partially modify As speciation and mitigate its environmental impact by altering the mineral transformation process. The results of this study facilitate better understanding of the role of Al substitution in the transformation of Fh and the cycling of As in the environment.

Novel insight into deriving remediation goals of arsenic contaminated sites with multi-media-equivalent dose and local exposure parameters

The remediation goal (RG) for arsenic (As) calculated by the traditional method is approximately 0.45 mg·kg-1, significantly lower than the background values. This poses significant challenges for the management of As-contaminated sites. The present study focused on a typical glassworks site with an As contamination level of up to 298 mg·kg-1, predominantly existing as As (III), with a carcinogenic risk level as high as 8.6 × 10-5. We developed a novel method known as multi-media-equivalent dose (MMED), incorporating local exposure parameters, and investigated the impacts of site-specific bioaccessibility (from 6.9 % to 51.5 %) on the results. The RG of arsenic calculated via MMED was 34.4 mg·kg-1 and 54 mg·kg-1 when bioaccessibility was considered. Integrating with five exposure parameters across 31 provinces, the provincial remediation goals (PRGs) ranged from 15.1 to 31.7 mg·kg-1. The RG calculated using the new method were more aligned with the practical conditions of managing As-contaminated sites, with potential for broader implementation across various provinces.

Migration modeling of metal(loid)s in soil-groundwater systems from an abandoned mine: Based on multimethod integration

Metal(loid)s contamination of mine has been a global environmental challenge. Traditional investigations of metal(loid) distribution patterns and migration behavior in soil-groundwater systems are constrained by the high costs of drilling and sampling limitations, leading to significant uncertainties in contamination assessment. This study presents an integrated approach combining three-dimensional (3D) visualization with Random Forest (RF) modeling and GIS mapping to investigate metal(loid) contamination characteristics and migration behavior in a mining area's soil-groundwater system. We developed an RF model with 1000 decision trees to expand limited drilling data for comprehensive spatial coverage. Model performance was validated using R2 and Root Mean Square Error (RMSE) metrics. The validated predictions were integrated into 3D visualization models and analyzed in conjunction with GIS mapping to characterize spatial patterns. Through analysis of temporal groundwater sampling data across wet, dry, and transitional hydrological periods, combined with RF modeling, we visualized metal(loid) distribution patterns and characterized their migration behavior in the soil-groundwater system. This integrated methodology provides a novel framework for investigating metal(loid) distribution and migration in mine soil-groundwater systems, effectively bridging traditional exploration techniques with advanced numerical simulation.

Evaluating the influence of alternating flooding and drainage on antimony speciation and translocation in a soil-rice system

The quantitative evaluation of antimony (Sb) accumulation in rice has garnered significant attention due to the potential risks to human health. A pot experiment was conducted to investigate the essential nodes of Sb transfer in soil-rice system. Seven step extract results showed that during the flooding period, organic matter releasing was the primary factor contributing 14.1 % to the increase in Sb availability, while weakly crystallized Fe-Mn oxides and sulfides respectively accounted for 6.9 % and 1.42 %. During the drainage period, a notable increase in active Sb was observed, coinciding with decrease in Fe-Mn oxides and sulfides bond Sb. The migration rate constant of Sb from the root to the above-ground parts increased dramatically during the early flooding stage, being 2000 times higher than that in the mid-to-late stage. The shoot-to-grain migration rate constant remained low, at 1.07 × 10-2 d-1 and 3.52 × 10-3 d-1 during the flooding and drainage periods, respectively. Consequently, Sb accumulation amount in the grain (11.5 μg) was 2.2 times and 6.24 times lower than that in the roots and shoots, respectively. This study quantitatively evaluates the key processes controlling Sb transformation, uptake and translocation throughout different growth stages of the rice plant.

Novel Photoelectron-Assisted Microbial Reduction of Arsenate Driven by Photosensitive Dissolved Organic Matter in Mine Stream Sediments

The microbial reduction of arsenate (As(V)) significantly contributes to arsenic migration in mine stream sediment, primarily driven by heterotrophic microorganisms using dissolved organic matter (DOM) as a carbon source. This study reveals a novel reduction pathway in sediments that photosensitive DOM generates photoelectrons to stimulate diverse nonphototrophic microorganisms to reduce As(V). This microbial photoelectrophic As(V) reduction (PEAsR) was investigated using microcosm incubation, which showed the transfer of photoelectrons from DOM to indigenous sediment microorganisms, thereby leading to a 50% higher microbial reduction rate of As(V). The abundance of two marker genes for As(V) reduction, arrA and arsC, increased substantially, confirming the microbial nature of PEAsR rather than a photoelectrochemical process. Photoelectron ion is unlikely to stimulate photolithoautotrophic growth. Instead, diverse nonphototrophic genera, e.g., Cupriavidus, Sphingopyxis, Mycobacterium, and Bradyrhizobium, spanning 13 orders became enriched by 10-50 folds. Metagenomic binning revealed their genetic potential to mediate the photoelectron-assisted reduction of As(V). These microorganisms contain essential genes involved in respiratory As(V) reduction, detoxification As(V) reduction, dimethyl sulfoxide reductase family, c-type cytochromes, and multiple heavy-metal resistance but lack a complete photosynthesis system. The novel microbial PEAsR pathway offers new insights into the interaction between photoelectron utilization and nonphototrophic As(V)-reducing microorganisms, which may have profound implications for arsenic pollution transportation in mine stream sediment.

Identification of priority factors for risk control of trace toxic elements in surface resuspended dust of university campuses

The surface resuspended dust (SRD) that accumulates trace toxic elements (TTEs) can be suspended in the atmosphere and can be transported to other areas, such as campuses, through airflow. The risks and sources of TTEs in university campus SRD have not been thoroughly explored, especially the priority factors for TTEs pollution and risk control in the SRD. Taking Xi'an as a case, this study quantitatively apportioned the sources of TTEs in the SRD of university campuses using positive matrix factorization method, evaluated the ecological and health risks of the specific-source TTEs in the SRD using Monte Carlo simulation method, and determined the priority factors for risk control of TTEs in the SRD. We found that the pollution of Zn, Pb, and Cu in the SRD was severe, with significantly high to very high enrichment levels. The comprehensive pollution of TTEs in the SRD was high to extremely high levels, with Pb and Zn as the main contributors. The four sources of TTEs identified in the SRD were traffic exhaust, traffic non-exhaust, mixed, and natural sources, accounting for 19.1%, 43.3%, 11.2%, and 26.3% of the total TTE concentrations, respectively. The ecological risk of TTEs was quite serious, mainly caused by traffic exhaust Pb. TTEs in the SRD had a certain cancer risk to college students, mainly contributed by traffic exhaust. Traffic exhaust source is the main factor that needs to be controlled.

Ignoring the food route underestimated human health risk from potentially toxic elements in agricultural environments of Ziyang, Shaanxi, China

Staple food is a crucial exposure route for the human intake of potentially toxic elements (PTEs), but it has been neglected in previous human health risk (HHR) studies. Lack of attention to this issue will lead to an underestimation of HHR caused by PTEs. This study establishes a comprehensive regional identification method for health risk assessment (HRA), namely, soil-maize health risk assessment (SMHRA) and applies it to Ziyang, Shaanxi, which is a typical agricultural county. SMHRA considered the exposure pathway of staple food and utilized Monte Carlo simulation to enhance the accuracy of HRA for PTEs. Results indicated the PTE spatial heterogeneity in a soil-maize system. Introducing staple food exposure pathway would increase HHR values and probabilities 1.57-2.80 and 1.53-5.63 times than that when food route was not considered. Overall, the HHR caused by a single PTE was low, which relatively safe. The introduction of food pathway contributed to accurate estimate the HHR of As and Ni, and the risk probabilities ranged from 0.04% to 12.46%. Few areas had high levels of Ni, which pose health risks: approximately 1.8% for children and higher than 0.5% for adults. Both As and Ni had the highest contribution to HHR among all PTEs, with 33.84%-41.56% TNCR caused by As, and 54.73%-56.90% TCR created by Ni, respectively. For human health risk routes, the staple food exhibited the highest contribution to HHR among all exposure routes, with TNCR of 36.15%-56.73% and the TCR of 44.96%-64.28%. Our research imply that dietary intake of PETs must be considered in the human health risk assessment in agricultural environment, which offers the foundation for subsequent environmental risk prevention and control.

A comprehensive study of source apportionment, spatial distribution, and health risks assessment of heavy metal(loid)s in the surface soils of a semi-arid mining region in Matehuala, Mexico

BACKGROUND

This study investigates the contamination level, spatial distribution, pollution sources, potential ecological risks, and human health risks associated with heavy metal(loid)s (i.e., arsenic (As), copper (Cu), iron (Fe), manganese (Mn), lead (Pb), and zinc (Zn)) in surface soils within the mining region of Matehuala, located in central Mexico.

OBJECTIVES

The primary objectives are to estimate the contamination level of heavy metal(loid)s, identify pollution sources, assess potential ecological risks, and evaluate human health risks associated with heavy metal(loid) contamination.

METHODS

Soil samples from the study area were analysed using various indices including Igeo, Cf, PLI, mCd, EF, and PERI to evaluate contamination levels. Source apportionment of heavy metal(loid)s was conducted using the APCS-MLR and PMF receptor models. Spatial distribution patterns were determined using the most efficient interpolation technique among five different approaches. The total carcinogenic risk index (TCR) and total non-carcinogenic index (THI) were used in this study to assess the potential carcinogenic and non-carcinogenic hazards posed by heavy metal(loid)s in surface soil to human health.

RESULTS

The study reveals a high contamination level of heavy metal(loid)s in the surface soil, posing considerable ecological risks. As was identified as a priority metal for regulatory control measures. Mining and smelting activities were identified as the primary factors influencing heavy metal(loid) distributions. Based on spatial distribution mapping, concentrations were higher in the northern, western, and central regions of the study area. As and Fe were found to pose considerable and moderate ecological risks, respectively. Health risk evaluation indicated significant levels of carcinogenic risks for both adults and children, with higher risks for children.

CONCLUSION

This study highlights the urgent need for monitoring heavy metal(loid) contamination in Matehuala's soils, particularly in regions experiencing strong economic growth, to mitigate potential human health and ecological risks associated with heavy metal(loid) pollution.

A remote sensing analysis method for soil heavy metal pollution sources at site scale considering source-sink relationships

Conventional methods for identifying soil heavy metal (HM) pollution sources are limited to area scale, failing to accurately pinpoint sources at specific sites due to the spatial heterogeneity of HMs in mining areas. Furthermore, these methods primarily focus on existing solid waste polluted dumps, defined as "direct pollution sources", while neglecting existing HM pollution hotspots generated by historical anthropogenic activities (e.g., mineral development, industrial discharges), defined as "potential pollution sources". Addressing this gap, a novel remote sensing analysis method is proposed to identify both direct and potential pollution sources at site scale, considering source-sink relationships. Direct pollution sources are extracted using a supervised classification algorithm on high-resolution multispectral imagery. Potential pollution sources depend on the spatial distribution of HM pollution, mapped using a machine learning model with hyperspectral imagery. Additionally, a source identification algorithm is developed for gridded pollution source analysis. Validated through a case study in a cadmium (Cd)-polluted mine area, the proposed method successfully extracted 21 solid waste polluted dumps with an overall accuracy approaching 90 % and a Kappa coefficient of 0.80. Simultaneously, 4167 HM pollution hotspots were identified, achieving optimal inversion accuracy for Cd (Rv2 = 0.91, RMSEv = 4.27, and RPDv = 3.02). Notably, the spatial distribution patterns of these identified sources exhibited a high degree of similarity. Further analysis employing the identification algorithm indicated that 3 polluted dumps and 258 pollution hotspots were pollution sources for a selected high-value point of Cd content. This innovative method provides a valuable methodological reference for precise prevention and control of soil HM pollution.

Machine learning-assisted risk evaluation of heavy metals in the Hainan gold mining region, China

This study employed machine learning (ML) to thoroughly investigate the impact of informal mining activities on the distribution and pollution status of heavy metals in soils near private gold mines in Hainan Province, southern China, a region known for its ecological sensitivity and economic importance. By systematically collecting surface soil samples and samples at depths of 0.5-1 m from 175 drilling sites, a comprehensive quantitative analysis was conducted on major heavy metal elements, including lead (Pb), copper (Cu), cadmium (Cd), nickel (Ni), mercury (Hg), chromium (Cr), arsenic (As), and zinc (Zn). Combined with evaluation methods such as the Pollution Load Index (PLI), Normalized Pollution Index (NIPI), and Ecological Risk Index (ERI), the study revealed a high level of soil pollution at informal mining sites. The findings indicated that the average concentrations of Pb, Cd, Hg, As, and Zn in surface soils significantly exceeded the background values for soils in China, with a pronounced positive correlation observed between these heavy metal elements in both surface and deep soil profiles (r > 0.5). Furthermore, leveraging the heavy metal content in surface soils and the constructed environmental indicators, the predictive accuracy for metal content in deep soils was found to range from R2 = 0.27 to 0.68, suggesting that informal mining activities have led to substantial variations in metal content across different soil profiles. Through the application of a random forest model for predictive analysis of the PLI, NIPI, and ERI, high prediction accuracy was achieved (R2 = 0.78, 0.86, and 0.60, respectively). The study demonstrates that informal mining activities not only elevate the risk of soil pollution but also alter the distribution patterns of heavy metals. Also, this study provides a crucial foundation for the scientific assessment of soil quality and potential environmental hazards, while also affirming the efficacy of ML techniques in forecasting soil quality parameters.

Pollution characteristics and quantitative source apportionment of heavy metals within a zinc smelting site by GIS-based PMF and APCS-MLR models

The abandoned smelters present a substantial pollution threat to the nearby soil and groundwater. In this study, 63 surface soil samples were collected from a zinc smelter to quantitatively describe the pollution characteristics, ecological risks, and source apportionment of heavy metal(loid)s (HMs). The results revealed that the average contents of Zn, Cd, Pb, As, and Hg were 0.4, 12.2, 3.3, 5.3, and 12.7 times higher than the risk screening values of the construction sites, respectively. Notably, the smelter was accumulated heavily with Cd and Hg, and the contribution of Cd (0.38) and Hg (0.53) to ecological risk was 91.58%. ZZ3 and ZZ7 were the most polluted workshops, accounting for 25.7% and 35.0% of the pollution load and ecological risk, respectively. The influence of soil parent materials on pollution was minor compared to various workshops within the smelter. Combined with PMF, APCS-MLR and GIS analysis, four sources of HMs were identified: P1(25.5%) and A3(18.4%) were atmospheric deposition from the electric defogging workshop and surface runoff from the smelter; P2(32.7%) and A2(20.9%) were surface runoff of As-Pb foul acid; P3(14.5%) and A4(49.8%) were atmospheric deposition from the leach slag drying workshop; P4(27.3%) and A1(10.8%) were the smelting process of zinc products. This paper described the distribution characteristics and specific sources of HMs in different process workshops, providing a new perspective for the precise remediation of the smelter by determining the priority control factors.

Multistage stabilization of Cd, Pb, Zn, Cu and As in contaminated soil by phosphorus-coated nZVI layered composite materials: characteristics, process and mechanism

This study developed a shell-like slow-release material, PF@ST/Fe-0.5, by encapsulating nanoscale zero-valent iron composites (NZC) with phosphate fertilizer (PF) and a starch binder (ST). The material dissolved in soil in stages, first releasing P and Ca to increase the soil pH from 4.95 to 7.14. This was followed by the formation of phosphates and hydroxides precipitates with Pb, Cu, Zn, and Cd in soil, reducing their bioavailable forms by 81.73 %, 79.58 %, 91.05 %, and 86.47 %, respectively. The process also involved the competitive adsorption between PO43-/HPO42- and arsenate/arsenite led to the release of specifically adsorbed arsenic, increasing the probability of reaction with the material. Afterwards, the exposure of the NZC core reacted with arsenate/arsenite to form ferric arsenates, thus reducing the content of bioavailable arsenic in the soil by 73.57 %. Excess PO43- and alkali metal cations were captured and mineralized by the iron (hydro) oxides and reactive silicates in NZC, enhancing the remediation effect. Furthermore, the wet-dry alternation test had demonstrated the adaptability of PF@ST/Fe-0.5 to the rainy dry-wet soil environment in Yunnan, which enabled the bioavailable content of As, Pb, Cu, Zn, and Cd decreased by 71.2 %, 94.8 %, 84.1 %, 79.8 %, and 83.9 %, respectively. The layered structure minimized internal reactive substance consumption and protected the internal nZVI from oxidation. The phased release of phosphate and Fe0 stabilized Pb, Cu, Zn, and Cd, enhancing As stabilization and providing a new perspective for the synchronous stabilization of soil contaminated.

Discarded substrates from soilless hydroponic horticulture as potential amendments for metal-contaminated soils

Soil contamination with metals is a major threat for the environment and public health since most metals are toxic to humans and to non-human biota, even at low concentrations. Thus, new sustainable remediation approaches are currently needed to immobilize metals in soils to decrease their mobility and bioavailability. In this work, we explore the application of discarded substrates from hydroponic cultivation, namely coconut shell and a mixture of coconut shell and pine bark, for immobilization of metals (Cd, Cr, Ni, Cu, Pb, Hg, Sb and As) in a naturally contaminated soil from a mining region in Portugal. The immobilization capacity of substrates (added to the soil at 5% mass ratio) was assessed both individually and also combined with other traditional agriculture soil additives (limestone and gypsum, at 2% mass ratio) and nanoparticles of zero-valent iron (nZVI) at 1-3% mass ratio. The overall results obtained after a 30-d incubation showed that the discarded substrates are a viable, economic, and environmental-friendly solution for metal remediation in soils, with the capacity of immobilization ranging from 20 to 91% for the metals and metalloids studied. Furthermore, they showed the capacity to reduce the soil toxicity (EC50 ∼ 6000 mg/L) to non-toxic levels (EC50 > 10000 mg/L) to the bacteria Aliivrio fischeri.

Health Risk Assessment of Heavy Metals in Agricultural Soils Based on Multi-Receptor Modeling Combined with Monte Carlo Simulation

The spatial characteristics, pollution sources, and risks of soil heavy metals were analyzed on Hainan Island. The results showed that the heavily polluted points accounted for 0.56%, and the number of mildly and above polluted points accounted for 15.27%, respectively, which were mainly distributed in the northern part of the study area. The principal component analysis-absolute principal component score-multiple linear regression (APCS-MLR) and the positive matrix factorization (PMF) revealed four sources of heavy metals: agricultural pollution sources for cadmium, (Cd), industrial and mining pollution sources for arsenic, (As), transportation pollution sources for zinc and lead (Zn and Pb), and natural pollution sources for chromium, nickel, and copper (Cr, Ni, and Cu). The human health risk assessment indicated that the average non-carcinogenic risk (HI) for both adults and children was within the safe threshold (<1), whereas Cr and Ni posed a carcinogenic risk (CR) to human health. In addition, the total non-carcinogenic risk (THI) indicated that heavy metals posed a potential non-carcinogenic risk to children, while the total carcinogenic risk (TCR) remained relatively high, mainly in the northern part of the study area. The results of the Monte Carlo simulation showed that the non-carcinogenic risk (HI) for all heavy metals was <1, but the total non-carcinogenic risk index (THI) for children was >1, indicating a potential health risk above the safe threshold. Meanwhile, nearly 100% and 99.94% of the TCR values exceeded 1 × 10-4 for children and adults, indicating that Cr and Ni are priority heavy metals for control. The research results provide the necessary scientific basis for the prevention and control of heavy metals in agricultural soils.

Nanoconfined Fe(II) releaser for long-term arsenic immobilization and its sustainability assessment

Ferrous (Fe(II))-based oxygen activation for pollutant abatements in soil and groundwater has attracted great attention, while the low utilization and insufficient longevity of electron donors are the primary challenges to hinder its practical applications. Herein, we propose a nanoconfined Fe(II) releasing strategy that enables stable long-term electron donation for oxygen activation and efficient arsenic (As) immobilization under oxic conditions, by encapsulating zero-valent iron in biomass-derived carbon shell (ZVI@porous carbon composites; ZVI@PC). This strategy effectively enhances the generation of reactive oxygen species, enabling efficient oxidation and subsequent immobilization of As(III) in soils. Importantly, this Fe(II) releaser exhibits strong anti-interference capability against complex soil matrices, and the accompanying generation of Fe(III) enables As immobilization in soils, effectively lowering soil As bioavailability. Soil fixed-bed column experiments demonstrate a 79.5 % reduction of the total As in effluent with a simulated rainfall input for 10 years, indicating the excellent long-term stability for As immobilization in soil. Life cycle assessment results show that this Fe(II) releaser can substantially mitigate the negative environmental impacts. This work offers new insights into developing green and sustainable technologies for environmental remediation.

Assessment of toxic effects of thallium on the earthworm Eisenia fetida using the biomarker response index

Thallium (Tl), though not essential for biological systems, is widely used in industrial activities, resulting in soil pollution and adverse effects on soil biota. Systematic toxicological studies on Tl, especially concerning soil organisms, are relatively rare. This research evaluates the toxic effects of Tl on earthworms by measuring oxidative stress biomarkers, such as superoxide dismutase (SOD), catalase (CAT), glutathione S-transferase (GST), malondialdehyde (MDA), and 8-hydroxydeoxyguanosine (8-OHdG), and by assessing the expression of functional genes, such as heat shock protein 70 (Hsp70), metallothionein (MT), and annetocin (ANN). Additionally, this study employs the Biomarker Response Index (BRI) and two-way ANOVA to comprehensively assess the cumulative toxicity of Tl in earthworms. The findings indicate that Tl exposure significantly exacerbates oxidative stress and cellular damage in earthworms, particularly under conditions of high concentration and prolonged exposure. BRI results demonstrate a continuous decline in the physiological state of earthworms with increasing Tl concentration and exposure duration. Two-way ANOVA reveals significant dose-responsive increases in SOD and CAT activities, as well as in ANN gene expression. Apart from GST activity, other biomarkers significantly increased over time, and the changes in biomarkers such as SOD, CAT, MDA, and 8-OHdG were significantly influenced by dose and time. LSD post hoc tests show significant effects of dose, time, and their interactions on all biomarkers except for GST. These findings are valuable for gaining a deeper understanding of the ecological risks of Tl in soil environments and its potential threats to soil biota, aiding in the management of ecological risks associated with Tl-contaminated soils.

Considering the bioavailability and bioaccessibility of metal(loid)s for risk assessment of soils affected by different non-ferrous metal activities in Southwest China

Toxic metal(loid)s released into the soil by non-ferrous metal mining and smelting activities pose a serious threat to residents and the surrounding ecosystem. Considering only total metal(loid) concentrations likely overestimates routine (eco)toxicological risk assessment of soil. We hypothesize that considering metal(loid) bioavailability/accessibility will improve the accuracy of risk assessment. To test this hypothesis, four mining areas in Southwest China, including mining and surrounding sites, were studied. Bioavailability was determined considering metal(loid)s leached by a simulated strong acid rain (SSAR) treatment. In the four areas, the mining site showed higher cumulative releases of metal(loid)s under SSAR treatment than the agricultural field located in the surrounding sites. Thus, the bioavailable metal(loid)s contents were continuously being released during SSAR treatment and likely increased the environmental risk. Ecological and health risk assessment of soil, calculated using total metal(loid)s content, was corrected considering bioavailable/accessible metal(loid)s, which was determined by the heavy metal(loid)s forms and in vitro simulated intestinal stages. Although the corrected indices indicated that the risk of metal(loid)s-contaminated soil was reduced, unfavorable ecological and health risks remained in the four areas. Our study provides new perspectives to better predict the risk of bioavailable/accessible metal(loid)s in non-ferrous metal contaminated and surrounding soils.

Sources apportionments of heavy metal(loid)s in the farmland soils close to industrial parks: Integrated application of positive matrix factorization (PMF) and cadmium isotopic fractionation

Understanding the source identification and distribution of heavy metal(loid)s in soil is essential for risk management. The sources of heavy metal(loid)s in farmland soil, especially in areas with rapid economic development, were complicated and need to be explored urgently. This study combined geographic information system (GIS) mapping, positive matrix factorization (PMF) model and cadmium (Cd) isotope fingerprinting methods to identify heavy metal(loid) sources in a typical town in the economically developed Yangtze River Delta region of China. Cd, As, Cu, Zn, Pb, Ni and Co in different samples were detected. The results showed that Cd was the most severely contaminated element, with an exceedance rate of 78.0 %. GIS mapping results indicated that the hotspot area was located in the northeastern area with prolonged operational histories of electroplating and non-ferrous metal smelting industries. The PMF model analysis also identified emissions from smelting and electroplating enterprises as the main sources of Cd in the soil, counted for 49.28 %, followed by traffic (25.66 %) and agricultural (25.06 %) sources. Through further isotopic analysis, it was found that in soil samples near the industrial park, the contribution of electroplating and non-ferrous metal smelting enterprises to cadmium pollution was significantly higher than other regions. The integrated use of various methodologies allows for precise analysis of sources and input pathways, offering valuable insights for future pollution control and soil remediation endeavors.

Contrasting response strategies of sulfate-reducing bacteria in a microbial consortium to As3+ stress under anaerobic and aerobic environments

The sulfate-reducing efficiency of sulfate-reducing bacteria (SRB) is strongly influenced by the presence of oxygen, but little is known about the oxygen tolerance mechanism of SRB and the effect of oxygen on the metalliferous immobilization by SRB. The performance evaluation, identification of bioprecipitates, and microbial and metabolic process analyses were used here to investigate the As3+ immobilization mechanisms and survival strategies of the SRB1 consortium under different oxygen-containing environments. Results indicated that the sulfate reduction efficiency was significantly decreased under aerobic (47.37%) compared with anaerobic conditions (66.72%). SEM analysis showed that under anaerobic and aerobic conditions, the morphologies of mineral particles were different, whereas XRD and XPS analyses showed that the most of As3+ bioprecipitates under both conditions were arsenic minerals such as AsS and As4S4. The abundances of Clostridium_sensu_stricto_1, Desulfovibrio, and Thiomonas anaerobic bacteria were significantly higher under anaerobic than aerobic conditions, whereas the aerobic Pseudomonas showed an opposite trend. Network analysis revealed that Desulfovibrio was positively correlated with Pseudomonas. Metabolic process analysis confirmed that under aerobic conditions the SRB1 consortium generated additional extracellular polymeric substances (rich in functionalities such as Fe-O, SO, CO, and -OH) and the anti-oxidative enzyme superoxide dismutase to resist As3+ stress and oxygen toxicity. New insights are provided here into the oxygen tolerance and detoxification mechanism of SRB and provide a basis for the future remediation of heavy metal(loid)-contaminated environments.

Source identification and exposure risk management for soil arsenic in urban reclamation areas with high background levels: A case study in a coastal reclamation site from the Pearl River Delta, China

Urbanization involving the excavation and reuse of arsenic-bearing geological materials may pose human health risks. We investigated the distribution and sources of soil arsenic at a coastal reclamation site in the Pearl River Delta, China, and proposed risk management strategies. Analysis of 899 soil samples revealed an average of 58.97 mg/kg arsenic, with a maximum of 1450 mg/kg, mainly in fill material obtained from a local island. Integrative analysis combining reclamation history, regional geology, and bedrock mineralogy conclusively identified hydrothermally altered arsenic-bearing sulfide minerals within extensively fractured bedrock as the primary source of arsenic. Physical weathering and anthropogenic rock blasting produced discrete arsenic-rich particles that were directly transported into soils during land reclamation and accumulated to potential hazardous levels. Oral, dermal, and inhalation pathways were identified as primary exposures for future populations. Integrated engineering and institutional controls, coupled with long-term monitoring, were recommended to mitigate risks. The results highlight the importance of identifying specific geogenic and anthropogenic sources that contribute to heavy metal enrichment of soils in reclaimed areas where native bedrock naturally contains elevated level of metals, supporting evidence-based best practices for risk management and future land use.

Influence of biochar on the arsenic phytoextraction potential of Pteris vittata in soils from an abandoned arsenic mining site

Biochar (BC) has a strong potential for activating arsenic (As) in soil; thus, the phytoremediation efficiency of As-polluted soils is enhanced with Pteris vittata L. A pot experiment was conducted to investigate the potential of BC to assist in phytoremediation with P. vittata. The effects of BC on physicochemical properties, available As, enzyme activities, and the bacterial community in the rhizosphere soil were investigated, and the biomass, physiology, and As uptake of P. vittata were analyzed. The results indicated that applying BC facilitated available As in the P. vittata rhizosphere soil, and the phytoremediation efficiency percentage increased in the As-polluted soils, such as 3.80% and 8.01% under the 2% and 5% BC treatments compared to the control, respectively. Phytoremediation with P. vittata and BC significantly improved soil organic matter content, available N, P, and K, enzyme activities, and the bacterial community. BC promoted Streptomyces (26.6-54.2%) and Sphingomonas (12.3-30.8%) abundance which regulated the growth and As uptake by P. vittata. Moreover, applying BC increased the biomass, and As uptake by P. vittata. Overall, BC strengthened the phytoremediation of As-polluted soils by improving soil pH, nutrient concentrations, enzyme activities, bacterial community structure, and soil arsenic activation, growth, and absorption by P. vittata.

Comprehensive distribution characteristics and factors affecting the migration of chromium in a typical chromium slag-contaminated site with a long history in China

The contamination of abandoned chromium slag-contaminated sites poses serious threats to human health and the environment. Therefore, improving the understanding of their distribution characteristics and health risks by multiple information is necessary. This study explored the distribution, accumulation characteristic, and the role in the migration process of chromium. The results showed that the contents of total Cr and Cr (VI) ranged from 12.00 to 7400.00 mg/kg, and 0.25 to 2160.00 mg/kg, respectively. The average contents of both total Cr and Cr (VI) reached the highest value at the depth of 7-9 m, where the silt layer retaining total Cr and Cr (VI) was. The spatial distribution analysis revealed that the total contamination area percentages of total Cr and Cr (VI) reached 7.87% and 90.02% in the mixed fill layer, and reduced to 1.21% and 34.53% in the silty layer, and the same heavily polluted areas were located in the open chromium residue storage. Soil pH and moisture content were the major factors controlling the migration of total Cr and Cr(VI) in soils. Results of probabilistic health risk assessment revealed that carcinogenic risk was negligible for adults and children, and the sensitive analysis implied that the content of Cr(VI) was the predominant contributor to carcinogenic risk. The combination of chemical reduction and microbial remediation could be the feasible remediation strategy for soil Cr(VI) pollution. Overall, this study provides scientific information into the chromium post-remediation and pollution management for various similar chromium-contaminated sites.

Effects of three plant growth-promoting bacterial symbiosis with ryegrass for remediation of Cd, Pb, and Zn soil in a mining area

The quality of soil containing heavy metals (HMs) around nonferrous metal mining areas is often not favorable for plant growth. Three types of plant growth promoting rhizobacteria (PGPR)-assisted ryegrass were examined here to treat Cd, Pb, and Zn contaminated soil collected from a nonferrous metal smelting facility. The effects of PGPR-assisted plants on soil quality, plant growth, and the migration and transformation of HMs were evaluated. Results showed that inter-root inoculation of PGPR to ryegrass increased soil redox potential, urease, sucrase and acid phosphatase activities, microbial calorimetry, and bioavailable P, Si, and K content. Inoculation with PGPR also increased aboveground parts and root length, P, Si, and K contents, and antioxidant enzyme activities. The most significant effect was that the simultaneous inoculation of all three PGPRs increased the ryegrass extraction (%) of Cd (59.04-79.02), Pb (105.56-157.13), and Zn (27.71-40.79), compared to CK control (without fungi). Correspondingly, the inter-root soil contents (%) of total Cd (39.94-57.52), Pb (37.59-42.17), and Zn (34.05-37.28) were decreased compared to the CK1 control (without fungi and plants), whereas their bioavailability was increased. Results suggest that PGPR can improve soil quality in mining areas, promote plant growth, transform the fraction of HMs in soil, and increase the extraction of Cd, Pb, and Zn by ryegrass. PGPR is a promising microbe-assisted phytoremediation strategy that can promote the re-greening of vegetation in the mining area while remediating HMs pollution.

Spatial distribution and source identification of potentially toxic elements in Yellow River Delta soils, China: An interpretable machine-learning approach

Identifying the driving factors and quantifying the sources of potentially toxic elements (PTEs) are essential for protecting the ecological environment of the Yellow River Delta. In this study, data from 201 surface soil samples and 16 environmental variables were collected, and the random forest (RF) and Shapley additive explanations (SHAP) methods were then combined to explore the key factors affecting soil PTEs. An innovative t-distributed random neighbor embedding-RF-SHAP model was then constructed, based on the absolute principal component score and multivariate linear regression model, to quantitatively determine PTE sources. Although average PTE concentrations did not exceed the risk control values, PTE distributions exhibited significant differences. It was found that sodium, soil organic matter, and phosphorus contents were the three most important factors affecting PTEs, and human activities and natural environmental factors both influence PTE contents by altering the soil properties. The proposed model successfully determined PTE sources in the soil, outperforming the original linear regression model with a significantly lower RMSE. Source analysis revealed that the parent material was the main contributor to soil PTEs, accounting for more than half of the total PTE content. Industrial and agricultural activities also contributed to an increase in soil PTEs, with average contributions of 19.91 % and 17.44 %, respectively. Unknown sources accounted for 10.83 % of the total PTE content. Thus, the proposed model provides innovative perspectives on source parsing. These findings provide valuable scientific insights for policymakers seeking to develop effective environmental protection measures and improve the quality of saline-alkali land in the Yellow River Delta.

Risk assessment and source identification of soil heavy metals: a case study of farmland soil along a river in the southeast of a mining area in Southwest China

To investigate the heavy metals (HMs) contamination of surface farmland soil along the river in the southeast of a mining area in southwest China and identify the contamination sources, 54 topsoil samples were collected and the concentrations of seven elements (Zn, Ni, Pb, Cu, Hg, Cr, and Co) were determined by inductively coupled plasma optical emission spectrometry (ICP-OES) and atomic fluorescence spectrometry (AFS). The geo-accumulation index ([Formula: see text]) and comprehensive potential ecological risk index ([Formula: see text]) were used for analysis to determine the pollution degree of HMs and the risk level of the study area. Meanwhile, the Positive Matrix Factorization (PMF) model was combined with a variety of statistical methods to determine the sources of HMs. To explore the influence of the river flowing through the mining area on the concentrations of HMs in the farmland soil, 15 water samples were collected and the concentrations of the above seven elements were determined. The results showed that the concentrations of Pb, Cu, and Zn in soil all exceeded the risk screening value, and Pb in soil of some sampling sites exceeded control value of "Agricultural Land Soil Pollution Risk Control Standard".[Formula: see text] showed that Pb was heavily contaminated, while Cu and Zn were moderately contaminated. RI showed that the study area was at moderate risk. PMF and various statistical methods showed that the main source of HMs was the industrial source. In the short term, the river flowing through the mine has no significant influence on the concentration of HMs in the soil. The results provide a reference for the local government to control contamination and identify the sources of HMs.

Leptolyngbya sp. XZMQ and Bacillus XZM co-inoculation reduced sunflower arsenic toxicity by regulating rhizosphere microbial structure and enzyme activity

Microorganisms are of great significance for arsenic (As) toxicity amelioration in plants as soil fertility is directly affected by microbes. In this study, we innovatively explored the effects of indigenous cyanobacteria (Leptolyngbya sp. XZMQ) and plant growth-promoting bacteria (PGPB) (Bacillus XZM) on the growth and As absorption of sunflower plants from As-contaminated soil. Results showed that single inoculation and co-inoculation stimulated the growth of sunflower plants (Helianthus annuus L.), enhanced enzyme activities, and reduced As contents. In comparison to the control group, single innoculation of microalgae and bacteria in the rhizosphere increased extracellular polymeric substances (EPS) by 21.99% and 14.36%, respectively, whereas co-inoculation increased them by 35%. Compared with the non-inoculated group, As concentration in the roots, stems and leaves of sunflower plants decreased by 38%, 70% and 41%, respectively, under co-inoculation conditions. Inoculation of Leptolyngbya sp. XZMQ significantly increased the abundance of nifH in soil, while co-inoculation of cyanobacteria and Bacillus XZM significantly increased the abundance of cbbL, indicating that the coupling of Leptolyngbya sp. XZMQ and Bacillus XZM could stimulate the activity of nitrogen-fixing and carbon-fixing microorganisms and increased soil fertility. Moreover, this co-inoculation increased the enzyme activities (catalase, sucrase, urease) in the rhizosphere soil of sunflower and reduced the toxic effect of As on plant. Among these, the activities of catalase, peroxidase, and superoxide dismutase decreased. Meanwhile, co-inoculation enables cyanobacteria and bacteria to attach and entangle in the root area of the plant and develop as symbiotic association, which reduced As toxicity. Co-inoculation increased the abundance of aioA, arrA, arsC, and arsM genes in soil, especially the abundance of microorganisms with aioA and arsM, which reduced the mobility and bioavailability of As in soil, hence, reduced the absorption of As by plants. This study provides a theoretical basis for soil microbial remediation in mining areas.

Treatment of wastewater containing thallium(I) by long-term operated manganese sand filter: Synergistic action of MnOx and MnOM

The long-term and stable removal of thallium (Tl) from industrial wastewater generated by mining and smelting operations remains challenging. While sand filters are commonly applied for the simultaneous removal of Mn(II) and other heavy metals, they have limited efficacy in treating Tl-contaminated wastewater. To address this gap, we operated a lab-scale Mn sand filter (MF) without added microorganisms to investigate the efficiency and mechanisms of Mn(II) and Tl(I) removal. Trends in effluent Mn(II) and Tl(I) concentrations indicated three operational stages: start-up, developing and maturation. Over time, the removal efficiency of Tl(I) gradually improved, plateauing at approximately 80 % eventually. Throughout operation, Tl(I) was sequestrated via surface complexation and ion exchange. Besides, enrichment of Sphingobium and other typical manganese oxidizing microorganisms (MnOM) during operation facilitated Mn(II) and Tl(I) oxidation and sequestration by generating biogenic manganese oxides (BioMnOx). Additionally, the accurate control of water quality and operating conditions during operation could also enhance removal efficiency. In summary, physicochemical actions of Mn oxides and biochemical actions of microorganisms synergistically contributed to the sequestration of Mn(II) and Tl(I). These findings provided a novel and sustainable method for the long-term and stable treatment of industrial wastewater containing thallium.

Evaluation of metal pollution characteristics using water and moss in the Luanchuan molybdenum mining area, China

Luanchuan is rich in molybdenum resources, and mining activities are frequent, but over-mining can cause serious metal pollution to the local environment. To explore the degree of metal pollution caused by mining activities, the content characteristics and spatial distribution of metals in mining areas were studied by measuring the concentrations of Fe, Mn, Zn, Ba, Mo, Cu, Cr, Co, V, and W in surface water and mosses of mining areas. In addition, the metal pollution index (HPI), contamination factor (CF), and pollution load index (PLI) were used to evaluate metal pollution, and factor analysis was used to analyze the sources of metals. The results of the analysis of surface water at the mine site indicate the most abundant element in surface water, with a maximum concentration of 3713.8 μg/L, and its content far exceeds the water quality standard of Class III of the Environmental Quality Standard for Surface Water. The results of the HPI analysis showed that nearly 90% of the surface water was moderately contaminated (HPI ≥ 15). The results of the analysis of atmospheric deposition at the mine site confirm that the metal elements with a high threat to the atmospheric environment are Mo and W. The results of PLI indicate that the level of atmospheric deposition pollution in the study area is severe (PLI > 4). Factor analysis indicated that rock weathering and mining activities were the main sources of metals. This study provides a theoretical basis for the investigation and control of metal pollution in similar metal mining areas.

The concentration and prevalence of potentially toxic elements (PTEs) in cheese: a global systematic review and meta-analysis

The present study aimed to systematically review the concentration of different PTEs, including Arsenic (As), Mercury (Hg), Lead (Pb), and Cadmium (Cd) in cheese among some databases between 2000 and 2021 (from 57 included studies). Estimated concentrations of 160.78 (95% CI = 119.24-202.28), 15.68 (95% CI = 11.88-19.48), 16.94 (95% CI = 13.29-20.59), and 2.47 (95% CI = 1.70-3.23) µg/kg were calculated for As, Pb, Cd, and Hg, respectively. Most of the studies for PTEs are related to Pb, about 40% of the studies, compared to As, which has fewer studies. The results showed that As and Hg concentrations were lower than the Codex Alimentarius Commission standard limits. Nevertheless, Cd and Pb concentrations were higher than the standard limit values. Results showed that cheese making, the ripening period, fat content, and texture are influential factors in a high level of Pb and Cd in cheese samples.

Synthesis of organic-solvent-soluble cellulose and preparation of fluorescent polyurethanes for the detection and removal of Hg+ ions

Modifying cellulose to obtain materials with favorable processing properties and functions is highly significant, especially, for the detection and removal of heavy metal ions. In this study, fluorescent cellulose-based polyurethane (PU) films containing naphthalimide fluorophore were synthesized and could use for the convenient detection and removal of Hg+ ions. Firstly, the microcrystalline cellulose was treated with SOCl2 to convert some -OH groups into -Cl. Simultaneously, a naphthalimide derivative (NAN) with -NH- groups was synthesized. Subsequently, a fluorescent cellulose-based probe (Cel-NAN) was prepared by utilizing the substitution reaction between -Cl on cellulose and -NH- on NAN. Finally, two cellulose-based fluorescent PU films (Cel-NAN-PU1 and Cel-NAN-PU2) were successfully synthesized by reacting the unreacted -OH groups on Cel-NAN with PEG-1000 and HDI/IPDI. These as-prepared PU films could serve as portable fluorescence test papers to Hg+ ions in aqueous solutions. Upon contact with Hg+ ions, the fluorescence was quenched, acting as a "turn-off" probe. Simultaneously, these films could serve as adsorbents for the removal of Hg+ ions from aqueous systems. Cel-NAN-PU1 film exhibited a removal efficiency over 80 % and an adsorption capacity of 8.4 mg·cm-2 for Hg+. These cellulose-based fluorescent PU films possess promising potential in the field of mercury pollution control.

Source apportionment and migration characteristics of heavy metal(loid)s in soil and groundwater of contaminated site

The rapid industrial growth has generated heavy metal(loid)s contamination in the soil, which poses a serious threat to the ecology and human health. In this study, 580 samples were collected in Henan Province, China, for source apportionment, migration characterization and health risk evaluation using self-organizing map, positive matrix factorization and multivariate risk assessment methods. The results showed that samples were classified into four groups and pollution sources included chromium slag dump, soil parent rock and abandoned factory. The contents of Cr, Pb, As and Hg were low in Group 1. Group 2 was characterized by total Cr, Cr(Ⅵ) and pH. The enrichment of total Cr and Cr(Ⅵ) in soil was mainly attributed to chromium slag dump, accounting for more than 84.0%. Group 3 was dominated by Hg and Pb. Hg and Pb were primarily attributed to abandoned factory, accounting for 84.7% and 70.0%, respectively. Group 4 was characterized by As. The occurrence of As was not limited to one individual region. The contribution of soil parent rock reached 83.0%. Furthermore, the vertical migration of As, Hg, Pb and Cr(Ⅵ) in soil was mainly influenced by medium permeability, pH and organic matter content. The trends of As, Pb, and Hg with depth were basically consistent with the trends of organic matter with depth, and were negatively correlated with the change in pH with depth. The trends of Cr(Ⅵ) with depth were basically consistent with the changes in pH with the depth. The content of Cr(Ⅵ) in the deep soil did not exceed the detection limits and Cr(Ⅵ) contamination occurred in the deep aquifer, suggesting that Cr(Ⅵ) in the deep groundwater originated from the leakage of shallow groundwater. The assessment indicated that the non-carcinogenic and carcinogenic risks for children and adults could not be neglected. Moreover, children were more susceptible than adults.

Assessment of effectiveness in stabilization/solidification of arsenic-contaminated soil: long-term leaching test and geophysical measurement

This study focused on evaluating the effectiveness of stabilizer/binding agents in immobilizing arsenic (As) in contaminated soil using both geochemical and geophysical monitoring methods. The effluent from the stabilizer/binding agent's application and control columns was analyzed, and the status of the columns was monitored using electrical resistivity (ER) and induced polarization (IP) methods. As stabilizers/binder, acid mine drainage sludge (AMDS) and steel slag (SS) were used, which delayed As and Ca leaching time and significantly reduced As leaching amount. Determination coefficients for As and Fe leaching exhibited elevated values (control column, R2 = 0.955; AMDS column, R2 = 0.908; and SS column, R2 = 0.833). A discernible decline in the concentration of leached Fe was accompanied by a corresponding reduction in IP. The determination coefficients correlating IP and Fe leaching remained substantial (control column, R2 = 0.768; AMDS column, R2 = 0.807; and SS column, R2 = 0.818). Such IP measurements manifest as instrumental tools in monitoring and assessing the retention capacity of applied stabilizer/binding agents in As-affected soils, thereby furnishing crucial data for the enduring surveillance of stabilization/solidification locales. This research posits a swift and continuous monitoring method for solidification/stabilization locales in situ.

An integrated approach to identify the source apportionment of potentially toxic metals in shale gas exploitation area soil, and the associated ecological and human health risks

Public awareness of the potential environmental risks of shale gas extraction has increased in recent years. However, the status and environmental risks of potentially toxic metals (PTMs) in shale gas field soil remain unclear. A total of 96 topsoil samples were collected from the first shale gas exploitation area in China. The sources of nine PTMs in the soils were identified using positive matrix factorization and correlation analysis, and the ecological and human health risks of toxic metals from different sources under the two land use types were calculated. The results showed that mean pollution load index (PLI) values for farmland (1.18) and woodland (1.40) indicated moderate pollution, As, Cd and Ni were the most serious contaminants among all nine PTMs. The following four sources were identified: shale gas extraction activities (43.90%), nature sources (31.90%), agricultural and traffic activities (17.55%) and industrial activities (6.55%). For ecological risk, the mean ecological risk index (RI) values for farmlands (161.95) and woodlands (185.27) reaching considerable risk. The contribution ratio of shale gas extraction activities for farmlands and woodlands were 5.70% and 8.90%, respectively. Regarding human health risk, noncarcinogenic risks for adults in farmlands and woodlands were negligible. Industrial activities, agricultural and traffic activities were estimated to be the important sources of health risks. Overall, shale gas extraction activities had little impact on the ecological and human health risk. This study provides scientific evidence regarding the soil contamination potential of shale gas development activities.

Identifying the potential soil pollution areas derived from the metal mining industry in China using MaxEnt with mine reserve scales (MaxEnt_MRS)

Identifying the potential soil pollution areas derived from the metal mining industry usually requires extensive field investigation and laboratory analysis. Moreover, the previous studies mainly focused on a single or a few mining areas, and thus couldn't provide effective spatial decision support for controlling soil pollution derived from the metal mining industry at the national scale. This study first conducted a literature investigation and web crawler for the relevant information on the metal mining areas in China. Next, MaxEnt with mine reserve scales (MaxEnt_MRS) was proposed for spatially predicting the probabilities of soil pollution derived from the metal mining industry in China. Then, MaxEnt_MRS was compared with the basic MaxEnt. Last, the potential soil pollution areas were identified based on the pollution probabilities, and the relationships between the soil pollution probabilities and the main environmental factors were quantitatively assessed. The results showed that: (i) MaxEnt_MRS (AUC = 0.822) obtained a better prediction effect than the basic MaxEnt (AUC = 0.807); (ii) the areas with the soil pollution probabilities higher than 54% were mainly scattered in the eastern, south-western, and south-central parts of China; (iii) GDP (45.7%), population density (30.1%), soil types (15.5%), average annual precipitation (3.9%), and land-use types (3.1%) contributed the most to the prediction of the soil pollution probabilities; and (iv) the soil pollution probabilities in the areas with all the following conditions were higher than 54%: GDP, 7600-2612670 thousand yuan/km²; population density, 152-551 people/km²; precipitation, 924-2869 mm/year; soil types, Ferralisols or Luvisols; and land-use types, townland, mines, and industrial areas. The above-mentioned results provided effective spatial decision support for controlling soil pollution derived from the metal mining industry at the national scale.

Source apportionment and quantitative risk assessment of heavy metals at an abandoned zinc smelting site based on GIS and PMF models

The abandoned smelters have caused serious hazards to the surrounding environment and residents. Taking an abandoned zinc smelter in southern China as an example, a total of 245 soil samples were collected to study spatial heterogeneity, source apportionment, and source-derived risk assessment of heavy metal(loid)s (HMs) in the region. The results showed that the mean values of all HMs concentrations were higher than the local background values, with Zn, Cd, Pb, and As contamination being the most serious and their plume penetrating to the bottom layer. Four sources were identified by principal component analysis and positive matrix factorization, with their contributions to the HMs contents ranked as: surface runoff (F2, 63.2%) > surface solid waste (F1, 22.2%) > atmospheric deposition (F3, 8.5%) > parent material (F4, 6.1%). Among these, F1 was a determinant source of human health risk with a contribution rate of 60%. Therefore, F1 was considered to be the priority control factor, but it only accounted for 22.2% of HMs contents contribution. Hg dominated the ecological risk with a contribution of 91.1%. Pb (25.7%) and As (32.9%) accounted for the non-carcinogenic risk, while As (95%) dominated the carcinogenic effect. The spatial characteristics of human health risk values derived from F1 indicated that high-risk areas were mainly distributed in the casting finished products area, electrolysis area, leaching-concentration area, and fluidization roasting area. The findings highlight the significance of priority control factors (including HMs, pollution sources and functional areas) for consideration in the integrated management of this region, thus saving costs for effective soil remediation.

Cooperative effect of slow-release ferrous and phosphate for simultaneous stabilization of As, Cd and Pb in soil

The different chemical behavior of anionic As and cationic Cd and Pb makes the simultaneous stabilization of soils contaminated with arsenic (As), cadmium (Cd), and lead (Pb) challenging. The use of soluble, insoluble phosphate materials and iron compounds cannot simultaneously stabilize As, Cd, and Pb in soil effectively due to the easy re-activation of heavy metals and poor migration. Herein, we propose a new strategy of "cooperatively stabilizing Cd, Pb, and As with slow-release ferrous and phosphate". To very this theory, we developed ferrous and phosphate slow-release materials to simultaneously stabilize As, Cd, and Pb in soil. The stabilization efficiency of water-soluble As, Cd and Pb reached 99% within 7d, and the stabilization efficiencies of NaHCO₃-extractable As, DTPA-extractable Cd and Pb reached 92.60%, 57.79% and 62.81%, respectively. The chemical speciation analysis revealed that soil As, Cd and Pb were transformed into more stable states with the reaction time. The proportion of residual fraction of As, Cd, and Pb increased from 58.01% to 93.82%, 25.69 to 47.86%, 5.58 to 48.54% after 56 d, respectively. Using ferrihydrite as a representative soil component, the beneficial interactions of phosphate and slow-release ferrous material in stabilizing Pb, Cd, and As were demonstrated. The slow-release ferrous and phosphate material reacted with As and Cd/Pb to form stable ferrous arsenic and Cd/Pb phosphate. Furthermore, the slow-release phosphate converted the adsorbed As into dissolved As, then the dissolved As reacted with released ferrous to form a more stable form. Concurrently, As, Cd and Pb were structurally incorporated into the crystalline iron oxides during the ferrous ions-catalyzed transformation of amorphous iron (hydrogen) oxides. The results demonstrates that the use of slow-release ferrous and phosphate materials can aid in the simultaneous stabilization of As, Cd, and Pb in soil.

Evaluation of heavy metals contamination in cereals, vegetables and fruits with probabilistic health hazard in a highly polluted megacity

Heavy metals (HMs) contamination in foodstuffs could pose serious health issues for public health and humans are continually exposed to HMs through the consumption of cereals, fruits, and vegetables. The present study was conducted to assess 11 HMs in foodstuffs to investigate pollution levels and health risks to children and adults. The mean contents of Cd, Cr, Cu, Ni, Zn, Fe, Pb, Co, As, Mn and Ba in foodstuffs were 0.69, 2.73, 10.56, 6.60, 14.50, 9.63, 2.75, 0.50, 0.94, 15.39 and 0.43 mg/kg, respectively and the concentration of Cd, Cr, Cu, Ni and Pb were higher than maximum permissible concentrations (MPCs) showing that these foods may be contaminated with metals and constitute a danger to consumers. Vegetables had relatively higher metal contents followed by cereals and fruits. The average value of the Nemerrow composite pollution index (NCPI) for cereals, fruits, and vegetables were 3.99, 6.53, and 11.34, respectively indicating cereal and fruits were moderately contaminated whereas vegetables were heavily contaminated by the studied metals. The total estimated daily and weekly intakes for all studied metals were higher than the maximum tolerable daily intake (MTDI) and provisional tolerance weekly intake (PTWI) recommended by FAO/WHO. The target hazard quotients and hazard index of all studied metals exceeded the standard limit for adults and children suggesting significant non-carcinogenic health hazards. The total cancer risk value of Cd, Cr, Ni, Pb, and As from food intake exceeded the threshold range (1.0E-04), suggesting potential carcinogenic risks. Based on practical and sensible evaluation techniques, the current work will assist policymakers in controlling metal contamination in foodstuffs.

Analytical study on heavy metal output fluxes and source apportionment of a non-ferrous smelter in southwest China

Abandoned Pb/Zn smelters are often accompanied by a large amount of smelting slag, which is a serious environmental problem. Previous studies have demonstrated that slag deposits pose an environmental threat even if the smelters are shut down. Herein, a Pb/Zn smelter and its impacted zone in GeJiu, Yunnan, China were selected as the study area. The risk and source apportionment of heavy metals (HMs) in the soil of the impacted zone were systematically studied. Based on the hydrogeological features, the migration path and output fluxes of the HMs released from smelting slag to the impacted zone were investigated. The HM contents (Cd, As, Zn, Pb, and Cu) in the soil substantially exceeded the screening values of the Chinese soil standard (GB15618-2018). Based on the results of the Pb isotopic and statistical analyses for source apportionment, the contaminated sites and agricultural irrigation water had a large impact on the HMs of soil. The hydrological analysis results showed that runoff, as an HM migration path under rainfall, continued to affect the environment. The water balance calculations using the Hydrologic Evaluation of Landfill Performance model showed that the rainfall was distributed on site as follows: evaporation (57.35%), runoff (32.63%), and infiltration (10.02%). Finally, the output fluxes were calculated in combination with the leaching experiment. As, Zn, Cd, Pb, and Cu runoff had the output fluxes of 6.1 × 10^-3, 4.2 × 10^-3, 4.1, 1.4 × 10^-2, and 7.2 × 10^-4 mg/kg/y, and infiltration of 1.9 × 10^-3, 1.3 × 10^-3, 1.3, 4.0 × 10^-4, and 2.2 × 10^-4 mg/kg/y, respectively. Therefore, this study offers theoretical and scientific recommendations for effective environmental management and engineering remediation.

Heavy metals in influent and effluent from 146 drinking water treatment plants across China: Occurrence, explanatory factors, probabilistic health risk, and removal efficiency

Heavy metals (HMs) in drinking water have drawn worldwide attention due to their risks to public health; however, a systematic assessment of the occurrence of HMs in drinking water treatment plants (DWTPs) at a large geographical scale across China and the removal efficiency, human health risks, and the correlation with environmental factors have yet to be established. Therefore, this study characterised the occurrence patterns of nine conventional dissolved HMs in the influent and effluent water samples from 146 typical DWTPs in seven major river basins across China (which consist of the Yangtze River, the Yellow River, the Songhua River, the Pearl River, the Huaihe River, the Liaohe River and the Haihe River) for the first time and removal efficiency, probabilistic health risks, and the correlation with water quality. According to the findings, a total of eight HMs (beryllium (Be), antimony (Sb), barium (Ba), molybdenum (Mo), nickel (Ni), vanadium (V), cobalt (Co) and titanium (Ti)) were detected, with detection frequencies in influent and effluent water ranging from 2.90 (Mo) to 99.30% (Ba) and 1.40 (Ti) to 97.90% (Ba), respectively. The average concentration range was 0.41 (Be)- 77.36 (Sb) μg/L. Among them, Sb (exceeding standard rate 8%), Ba (2.89%), Ni (21.43%), and V (1.33%) were exceeded the national standard (GB5749-2022). By combining Spearman's results and redundancy analysis, our results revealed a close correlation among pH, turbidity (TURB), potassium permanganate index (COD_Mn), and total nitrogen (TN) along with the concentration and composition of HMs. In addition, the concentration of HMs in finished water was strongly affected by the concentration of HMs in raw water, as evidenced by the fact that HMs in surface water poses a risk to the quality of finished water. Metal concentration was the primary factor in assessing the health risk of a single metal, and the carcinogenic risk of Ba, Mo, Ni, and Sb should be paid attention to. In DWTPs, the removal efficiencies of various HMs also vary greatly, with an average removal rate ranging from 16.30% to 95.64%. In summary, our findings provide insights into the water quality and health risks caused by HMs in drinking water.

Environmental and human health risks of potentially harmful elements in mining-impacted soils: A case study of the Angouran Zn-Pb Mine, Iran

The soil pollution status, levels of exposure, and potential ecological and health risks to workers and residents by potentially harmful elements (PHEs) in the Angouran mining area (Iran), the biggest Zn-Pb mine in the Middle East, were studied. To this aim, topsoil (0-5 cm) samples (n = 63) from different land-uses were analyzed for their total PHEs concentrations. Mine worker's blood analysis and in vitro digestion extractions were applied in conjunction with human health risk assessment (HHRA) to assess the potential health impacts by exposure to PHEs. The maximum PHEs total concentrations were found in the soils near the waste rock dumps. HHRA indicated that ingestion of soils may induce a non-carcinogenic risk due to As and Pb (for both age groups of children and adults), while dermal contact for children may induce the same type of risk due to Cd, and Pb. The carcinogenic risks (CR_s) of As, Cd, Cr, and Ni through ingestion route were above the acceptable value of 1 × 10^-4, and children may face greater health risks. The average blood Zn, Pb, and Cd levels in the mine workers largely exceeded the safe concentration for adults, while 30% of the workers were tested positive for As in blood. In vitro digestion extractions indicated that the highest bioaccessible contents of As, Cd, Pb, Ni and Zn were found for the industrial-residential and mine soils in the area, while those of Cr and Cu were observed in the agricultural use soils. This study illustrates that a combination of techniques, including geochemical analysis, in vitro bioaccessibility extractions, HHRA, and blood analysis, is a workable integrated approach for evaluating pollution and health risks in mining districts.

Rhizosphere effect on the relationship between dissolved organic matter and functional genes in contaminated soil

Arsenic contamination in a mining area is a potential threat to the local population. In the context of one-health, biological pollution in contaminated soil should be known and understandable. This study was conducted to clarify the effects of amendments on arsenic species and potential threat factors (e.g., arsenic-related genes (AMGs), antibiotic resistance genes (ARGs) and heavy-metal resistance genes (MRGs)). Ten groups (control (CK), T1, T2, T3, T4, T5, T6, T7, T8, and T9) were set up by adding different ratio of organic fertilizer, biochar, hydroxyapatite and plant ash. The maize crop was grown in each treatment. Compared with CK, the bioavailability of arsenic was reduced by 16.2%-71.8% in the rhizosphere soil treatments, and 22.4%-69.2% in the bulk soil treatments, except for T8. The component 2 (C2), component 3 (C3) and component 5 (C5) of dissolved organic matter (DOM) increased by 22.6%-72.6%, 16.8%-38.1%, 18.4%-37.1%, respectively, relative to CK in rhizosphere soil. A total of 17 AMGs, 713 AGRs and 492 MRGs were detected in remediated soil. The humidification of DOM might directly correlate with MRGs in both soils, while it was influenced directly on ARGs in bulk soil. This may be caused by the rhizosphere effect, which affects the interaction between microbial functional genes and DOM. These findings provide a theoretical basis for regulating soil ecosystem function from the perspective of arsenic contaminated soil.

Spatial heterogeneity and source apportionment of soil metal(loid)s in an abandoned lead/zinc smelter

Metal smelting have brought severe metal(loid)s contamination to the soil. Spatial distribution and pollution source analysis for soil metal(loid)s in an abandoned lead/zinc smelter were studied. The results showed that soil was contaminated heavily with metal(loid)s. The mean of lead (Pb), arsenic (As), cadmium (Cd), mercury (Hg) and antimony (Sb) content in topsoil is 9.7, 8.2, 5.0, 2.3, and 1.2 times higher than the risk screening value for soil contamination of development land of China (GB36600-2018), respectively. Cd is mainly enriched in the 0-6 m depth of site soil while As and Pb mainly deposited in the 0-4 m layer. The spatial distribution of soil metal(loid)s is significantly correlated with the pollution source in the different functional areas of smelter. As, Hg, Sb, Pb and copper (Cu) were mainly distributed in pyrometallurgical area, while Cd, thallium (Tl) and zinc (Zn) was mainly existed in both hydrometallurgical area and raw material storage area. Soil metal(loid)s pollution sources in the abandoned smelter are mainly contributed to the anthropogenic sources, accounting for 84.5%. Specifically, Pb, Tl, As, Hg, Sb and Cu mainly from atmospheric deposition (55.9%), Cd and Zn mainly from surface runoff (28.6%), While nickel (Ni) mainly comes from parent material (15.5%). The results clarified the spatial distribution and their sources in different functional areas of the smelter, providing a new thought for the risk prevention and control of metal(loid)s in polluted site soil.

Pollution characteristics and source identification of farmland soils in Pb-Zn mining areas through an integrated approach

Long-term mining activities have caused serious heavy metals contamination of farmland soils. In this study, we investigated the concentrations, distributions, accumulations, potential ecological risk, and sources of eight heavy metals in farmland soils of Pb-Zn mining areas. According to the soil standard GB15618-2018, Cd was the most contaminated, followed by Pb and Zn. The geo-accumulation index showed that Pb, Zn, Cd, and Hg accumulated seriously. The potential risk index indicated that Cd, Hg, and Pb were the main environmental risk elements. An integrated approach combining multivariate statistical analysis, PMF, and GIS mapping was used to analyze the sources of heavy metals. Four main sources were identified and quantified: (1) mining activities source, the main source of Cd (71.09%) and Zn (61.88%); (2) agricultural activities source, dominated by Hg (73.01%); (3) atmospheric deposition sources, with Pb (85.11%) as the main contributor; (4) natural source, characterized by Cr (72.96%), Ni (66.04%), As (55.98%) and Cu (37.70%). This study would help us understand the pollution characteristics and sources of farmland soils in mining areas and provide basic information for the next step of pollution control and remediation.

Risk source identification and diffusion trends of metal(loid)s in stream sediments from an abandoned arsenic-containing mine

Stream sediments from mine area are a converging source of water and soil pollution. The risk and development trends of metal(loid)s pollution in sediments from an abandoned arsenic-containing mine were studied using modelling techniques. The results showed that the combined techniques of geographic information system (GIS), random forest (RF), and numerical simulation (NS) could identify risk sources and diffusion trends of metal(loid)s in mine sediments. The median values of As, Cd, Hg, and Sb in sediments were 5.01, 3.02, 5.67, and 3.20 times of the background values of stream sediments in China, respectively. As (14.09%) and Hg (18.64%) pollution in mine stream sediments were severe while As is the main potential risk source with a strong spatial correlation. High-risk blocks were concentrated in the landfill area, with the surrounding pollution shows a decreasing trend of "step-type" pollution. The risk correlation between Hg and As (55.37%) in the landfill area is high. As a case of arsenic, the diffusion capacity of As within 500m is strong and stabilizes at 1 km when driven by the flows of 0.05, 0.5, and 5 m³/s, respectively. With the worst-case scenario flow (86 m³/s), it would take only 147 days for the waters within 3 km to become highly polluted. The high pollution levels in a stream under forecast of different distance intervals (500, 1500, 2000 m) within 6.5 km is arrived at approximate 344, 357, and 384 days, respectively. The study suggested the combined technique of GIS, RF, and NS can serve the risk source identification of contaminated sites and risk forecast of toxic element diffusion in emergency situations.