Spatial distribution, contamination characteristics and ecological-health risk assessment of toxic heavy metals in soils near a smelting area

Distinguishing the contributions of different smelting emissions to the spatial risk footprints of toxic elements in soil using PMF, Bayesian isotope mixing models, and distance-based regression

Toxic element pollution of soils emanating from smelting operations is an escalating global concern due to its severe impact on ecosystems and human health. In this study, soil samples were collected and analyzed to quantify the risk contributions and delineate the spatial risk footprints from smelting emissions for 8 toxic elements. A comprehensive health risk contribution and delineation framework was utilized, consisting of Positive matrix factorization (PMF), spatial interpolation, an advanced Bayesian isotope mixing model via Mixing Stable Isotope Analysis in R (MixSIAR), and distance-based regression. The results showed that the mean concentrations of As, Cd, Cu, Hg, Pb, and Zn exceeded the background levels, indicating substantial contamination. Three sources were identified using the PMF model and confirmed by spatial interpolation and MixSIAR, with contributions ranked as follows: industrial wastewater discharge and slag runoff from the smelter site (48.9 %) > natural geogenic inputs from soil parent materials (26.7 %) > atmospheric deposition of dust particles from smelting operations (24.5 %). Among the identified sources, smelter runoff posed the most significant risk, accounting for 97.9 % of the non-carcinogenic risk (NCR) and 59.9 % of the carcinogenic risk (CR). Runoff also drove NCR and CR exceedances at 7.8 % and 4.7 % of sites near the smelter, respectively. However, atmospheric deposition from smelting emissions affected soils across a larger 0.8 km radius. Although it posed lower risks, contributing just 1.1 % to NCR and 22.6 % to CR due to the limited elevation of toxic elements, deposition reached more distant soils. Spatial interpolation and distance-based regression delineated high NCR and CR exposure hotspots within 1.4 km for runoff and 0.8 km for deposition, with exponentially diminishing risks at further distances. These findings highlight the need for pathway-specific interventions that prioritize localized wastewater containment and drainage controls near the smelter while implementing broader regional air pollution mitigation measures.

Ecological and health risk assessments of heavy metals and their accumulation in a peanut-soil system

Heavy metals pollution is a notable threat to environment and human health. This study evaluated the potential ecological and health risks of heavy metals (Cu, Cr, Cd, Pb, Zn, Ni, and As) and their accumulation in a peanut-soil system based on 34 soil and peanut kernel paired samples across China. Soil As and Cd posed the greatest pollution risk with 47.1% and 17.6% of soil samples exceeding the risk screen levels, respectively, with 26.5% and 20.6% of the soil sites at relatively strong potential ecological risk level, respectively, and with the geo-accumulation levels at several soil sites in the uncontaminated to moderately contaminated categories. About 35.29% and 2.94% of soil sites were moderately and severely polluted based on Nemerow comprehensive pollution index, respectively, and a total of 32.4% of samples were at moderate ecological hazard level based on comprehensive potential ecological risk index values. The Cd, Cr, Ni, and Cu contents exceeded the standard in 11.76, 8.82, 11.76 and 5.88% of the peanut kernel samples, respectively. Soil metals posed more health risks to children than adults in the order As > Ni > Cr > Cu > Pb > Zn > Cd for non-carcinogenic health risks and Ni > Cr ≫ Cd > As > Pb for carcinogenic health risks. The soil As non-cancer risk index for children was greater than the permitted limits at 14 sites, and soil Ni and Cr posed the greatest carcinogenic risk to adults and children at many soil sites. The metals in peanut did not pose a non-carcinogenic risk according to standard. Peanut kernels had strong enrichment ability for Cd with an average bio-concentration factor (BCF) of 1.62. Soil metals contents and significant soil properties accounted for 35-74% of the variation in the BCF values of metals based on empirical prediction models.

Co-pyrolysis of alkali-fused fly ash and corn stover to synthesize biochar composites for remediating lead-contaminated soil

Fly ash (FA) is mainly composed of silica, alumina, and other metal oxide components, and has a positive stabilizing effect on soil heavy metals. Biochar composites produced from FA and corn stover (CS) can improve its remediation performance. Therefore, a batch of biochar composites (alkali-fused FA-CS biochars, ABs), synthesized via co-pyrolysis of CS and alkali-fused FA (AFFA) at different temperatures of 300, 500, and 700 °C (AB300-1, AB500-1, and AB700-1) and CS to AFFA mass ratios of 10:1, 10:2, and 10:5 (AB500-1, AB500-2, and AB500-5), was used to remediate lead (Pb)-contaminated soil. Compared with pristine biochars (BCs), ABs were enriched with oxygen-containing functional groups (Si-O-Si and Si-O) and aromatic structures. The ABs prepared at lower pyrolytic temperature (≤500 °C) and lower ratio of CS to AFFA (10:1) showed higher yield and stability. The contents of Toxicity Characteristic Leaching Procedure (TCLP)-extractable Pb and DTPA-CaCl2-triethanolamine (DTPA)-extractable Pb were generally lower in the soils amended with ABs than BCs. Compared with other ABs such as AB300-1, AB500-2, AB500-5, and AB700-1, the soil amended with AB500-1 had lower contents of TCLP and DTPA-extractable Pb (24% reduction), exhibiting superior performance in stabilizing Pb in the soil. The gradual decrease of DTPA-extractable Pb content in the soil with increasing dosage of AB500-1 amendments suggests that AB500-1 facilitated the conversion of bioavailable Pb to the stable and less toxic residual fractions. Specifically, the highest percentage of residual fraction of Pb in soil amended with AB500-1 was 14%. Correlation analyses showed that the soil DTPA-extractable Pb content decreased with the increase of soil pH and cation-exchange capacity (CEC) value. ABs stabilize Pb in the soils mainly via electrostatic attraction, precipitation, cation-π interaction, cation exchange, and complexation. These findings provide insights for producing functionalized biochar composites from industrial waste like FA and biomass waste for remediating the soils polluted by heavy metals.

Different "nongrain" activities affect the accumulation of heavy metals and their source-oriented health risks on cultivated lands

"Nongrain" production on cultivated land is one of the primary environmental issues in China. Different "nongrain" activities may introduce different pollution sources to the local environment, leading to variations in heavy metal contents in soil, which can profoundly impact national food security. In this study, three typical "nongrain" regions (Nanxun (NX), Xiaoshan (XS) and Lin'an (LA)) with intensive aquaculture, tea planting and flower (seedling) growth on cultivated land around the Hangzhou metropolitan area were selected to address the spatial heterogeneity of accumulation levels, sources and source-oriented health risks of heavy metals in soil. The results showed that Hg was the main pollutant in NX and XS, while Cd and As were the major contaminants in LA. Aquiculture and sericultural industries (37.43%), natural sources (23.59%) and industrial activities (38.99%) were the major sources in NX; atmospheric deposition (37.73%), flower and seedling planting (23.49%) and metal-related industries (35.16%) were the major sources in XS; and atmospheric deposition (28.06%), excessive application of fertilizers and pesticides during tea planting (43.47%) and natural sources (28.47%) were the major sources in LA. The major risk population, area, exposure route and hazardous elements were children, LA, ingestion and As and Cr, respectively. From the perspective of source-based health risk assessment, in addition to natural sources that are difficult to intervene in, industrial activities, especially leather and wood process industries, metal-related industries and excessive fertilizer and pesticide application during tea planting contributed the most to the total health risk, which explained 67%, 41% and 42%, respectively, of the total risk in NX, XS and LA. High health risks are present in sources with heavy loadings of hazardous heavy metals (As and Cr); thus, to protect human health, the corresponding high-risk anthropogenic pollution sources in different "nongrain" areas need to be controlled.

Potentially toxic elements (PTEs) and ecological risk at waste disposal sites: An analysis of sanitary landfills

This study presents an analysis of soil contamination caused by Ni, Zn, Cd, Cu, and Pb at municipal solid waste (MSW) landfills, with a focus on ecological risk assessment. The approach aims to assess how different landfill practices and environmental conditions affect soil contamination with potentially toxic elements (PTEs) and associated environmental risks. Soil samples were collected from MSW landfills in Poland and the Czech Republic. The research included a comprehensive assessment of PTEs in soils in the context of global environmental regulations. The degree of soil contamination by PTEs was assessed using indices: Geoaccumulation Index (Igeo), Single Pollution Index (Pi), Nemerow Pollution Index (PN), and Load Capacity of a Pollutant (PLI). The ecological risk was determined using the Risk of PTEs (ERi) and Sum of Individual Potential Risk Factors (ERI). The maximum values of the indicators observed for the Radiowo landfill were as follows: Igeo = 4.04 for Cd, Pi = 24.80 for Cd, PN = 18.22 for Cd, PLI = 2.66, ERi = 744 for Cd, ERI = 771.80. The maximum values of the indicators observed for the Zdounky landfill were as follows: Igeo = 1.04 for Cu, Pi = 3.10 for Cu, PN = 2.52 for Cu, PLI = 0.27, ERi = 25 for Cd, ERI = 41.86. The soils of the tested landfills were considered to be non-saline, with electrical conductivity (EC) values less than 2,000 μS/cm. Varying levels of PTEs were observed, and geostatistical analysis highlighted hotspots indicating pollution sources. Elevated concentrations of Cd in the soil indicated potential ecological risks. Concentrations of Cu and lead Pb were well below the thresholds set by the environmental legislation in several countries. In addition, Ni concentrations in the soils of both landfills indicated that the average levels were within acceptable limits. Principal Component Analysis (PCA) revealed common sources of PTEs. The identification of specific risk points at the Radiowo and Zdounky sites contributes to a better understanding of potential hazards in landfill environments. By establishing buffer zones and implementing regular maintenance programs, emerging environmental problems can be addressed in a timely manner.

Lead exposure in Chinese children: Urbanization lowers children's blood lead levels (BLLs)

Lead is a toxic metal that can pose a huge threat to children's health. China has experienced rapid urbanization since the reform in 1978; however, there has been no examination of the potential influence of this urbanization on children's blood lead levels (BLLs). This study is the initial investigation to explore the correlation between urbanization and BLLs in Chinese children. Five windows of time are considered: pre-2000, 2001-2005, 2006-2010, 2011-2015 and 2016-2021. The results show that urbanization affected lead distribution in urban soil and agricultural soil during the above periods, especially in northern China. The higher non-carcinogenic risk of lead for children is consistent with the lead pollution in soil (3 < Igeo ≤ 4). Urban children's BLLs are slightly higher than those of rural children in 2001-2010, but rural children's BLLs in 2011-2021 are higher than those of urban children during China's urbanization. The areas of rural decline and the areas of urban growth increased across all the window periods. However, the BLLs decrease in all rural and urban areas during all window periods, especially in urban areas. Children's BLLs have a significantly negative correlation with urban areas (p < 0.01). Therefore, China's urbanization has a significant effect on the decrease in children's BLLs. The significance of this study is to provide a fresh perspective and innovative strategy for policymaking in order to reduce children's BLLs and prevent lead exposure. This can be achieved by transforming their external living environment from a rural lifestyle to an urban one, while also ensuring access to well education and maintaining a balanced nutrient intake.

Potential risk assessment and occurrence characteristic of heavy metals based on artificial neural network model along the Yangtze River Estuary, China

Pollution from heavy metals in estuaries poses potential risks to the aquatic environment and public health. The complexity of the estuarine water environment limits the accurate understanding of its pollution prediction. Field observations were conducted at seven sampling sites along the Yangtze River Estuary (YRE) during summer, autumn, and winter 2021 to analyze the concentrations of seven heavy metals (As, Cd, Cr, Pb, Cu, Ni, Zn) in water and surface sediments. The order of heavy metal concentrations in water samples from highest to lowest was Zn > As > Cu > Ni > Cr > Pb > Cd, while that in surface sediments samples was Zn > Cr > As > Ni > Pb > Cu > Cd. Human health risk assessment of the heavy metals in water samples indicated a chronic and carcinogenic risk associated with As. The risks of heavy metals in surface sediments were evaluated using the geo-accumulation index (Igeo) and potential ecological risk index (RI). Among the seven heavy metals, As and Cd were highly polluted, with Cd being the main contributor to potential ecological risks. Principal component analysis (PCA) was employed to identify the sources of the different heavy metals, revealing that As originated primarily from anthropogenic emissions, while Cd was primarily from atmospheric deposition. To further analyze the influence of water quality indicators on heavy metal pollution, an artificial neural network (ANN) model was utilized. A modified model was proposed, incorporating biochemical parameters to predict the level of heavy metal pollution, achieving an accuracy of 95.1%. This accuracy was 22.5% higher than that of the traditional model and particularly effective in predicting the maximum 20% of values. Results in this paper highlight the pollution of As and Cd along the YRE, and the proposed model provides valuable information for estimating heavy metal pollution in estuarine water environments, facilitating pollution prevention efforts.

Effects of arbuscular mycorrhizal fungi on the reduction of arsenic accumulation in plants: a meta-analysis

Arsenic (As) accumulation in plants is a global concern. Although the application of arbuscular mycorrhizal fungi (AMF) has been suggested as a potential solution to decrease As concentration in plants, there is currently a gap in a comprehensive, quantitative assessment of the abiotic and biotic factors influencing As accumulation. A meta-analysis was performed to quantitatively investigate the findings of 76 publications on the impacts of AMF, plant properties, and soil on As accumulation in plants. Results showed a significant dose-dependent As reduction with higher mycorrhizal infection rates, leading to a 19.3% decrease in As concentration. AMF reduced As(V) by 19.4% but increased dimethylarsenic acid (DMA) by 50.8%. AMF significantly decreased grain As concentration by 34.1%. AMF also improved plant P concentration and dry biomass by 33.0% and 62.0%, respectively. The most significant reducing effects of As on AMF properties were seen in single inoculation and experiments with intermediate durations. Additionally, the benefits of AMF were significantly enhanced when soil texture, soil organic carbon (SOC), pH level, Olsen-P, and DTPA-As were sandy soil, 0.8%-1.5%, ≥7.5, ≥9.1 mg/kg, and 30-60 mg/kg, respectively. AMF increased easily extractable glomalin-related soil protein (EE-GRSP) and total glomalin-related soil protein (T-GRSP) by 23.0% and 28.0%, respectively. Overall, the investigated factors had significant implications in developing AMF-based methods for alleviating the negative effects of As stress on plants.

Cadmium and copper-induced metabolic and proteomic changes in the root tip during early maize growth

In this study, the metabolic adjustments performed by maize (Zea mays L.) seminal roots exposed to 25 µM Cd2+ or 25 µM Cu2+ at pre-emergence are compared, focusing on the proteomic changes after metal exposure. Root width was increased, and root length was decreased after 72 h of metal treatment. Both metals induced H2O2 accumulation and lipid peroxidation in the root tip. These changes were accompanied by increases in lipoxygenase activity and 4-hydroxy-2-nonenal content. NMR spectroscopy revealed that the abundance of 38 water-soluble metabolites was significantly modified by Cd and Cu exposure; this set of metabolites comprised carboxylic acids, amino acids, carbohydrates, and unidentified phenolic compounds. Linoleic acid content significantly decreased in Cu-treated samples. The total amount of proteins detected in maize root apexes was 2,171. Gene ontology enrichment analysis of the differentially accumulated proteins was performed to detect pathways probably affected by metal additions. Both metals altered redox homeostasis, up-regulated oxylipins biosynthetic process, and shifted metabolism towards the oxidative pentose-phosphate in the root apexes. However, the methionine salvage pathway appears as a key metabolic module only under Cd stress. The integrative analysis carried out in this study suggests that most molecular features behind the reprogramming of maize root tips to cope with cadmium and copper toxicity are common, but some are not.

Preliminary construction of a microecological evaluation model for uranium-contaminated soil

With the extensive development of nuclear energy, soil uranium contamination has become an increasingly prominent problem. The development of evaluation systems for various uranium contamination levels and soil microhabitats is critical. In this study, the effects of uranium contamination on the carbon source metabolic capacity and microbial community structure of soil microbial communities were investigated using Biolog microplate technology and high-throughput sequencing, and the responses of soil biochemical properties to uranium were also analyzed. Then, ten key biological indicators as reliable input variables, including arylsulfatase, biomass nitrogen, metabolic entropy, microbial entropy, Simpson, Shannon, McIntosh, Nocardioides, Lysobacter, and Mycoleptodisus, were screened by random forest (RF), Boruta, and grey relational analysis (GRA). The optimal uranium-contaminated soil microbiological evaluation model was obtained by comparing the performance of three evaluation methods: partial least squares regression (PLS), support vector regression (SVR), and improved particle algorithm (IPSO-SVR). Consequently, partial least squares regression (PLS) has a higher R2 (0.932) and a lower RMSE value (0.214) compared to the other. This research provides a new evaluation method to describe the relationship between soil ecological effects and biological indicators under nuclear contamination.

Source-oriented risk assessment of heavy metal(loid)s in agricultural soils around a multimetal smelting area near the Yellow River, China

Heavy metal(loid) (HM) contamination in agricultural soils, particularly in areas severely impacted by smelting industries, has attracted worldwide attention. In this study, agricultural soils were collected in a flourishing multimetal smelting area near the Yellow River in central China. By an integrated approach encompassing the positive matrix factorization model, ordinary kriging interpolation and hierarchical clustering analysis (PMF-OK-HC), a total of four major sources and their mass contributions were identified, namely, soil parent material (56.6%), industrial waste and Mo smelting (24.0%), metal smelting and traffic emissions (12.8%), and coal combustion (6.7%). On this basis, the health risk of HMs was evaluated by Monte Carlo simulations and showed that a higher risk, with a higher proportion of exceeding-thresholds risk, was observed for children than for adults in terms of both noncarcinogenic and carcinogenic risks. Exposure pathways of oral ingestion in children could result in a higher attributed risk than other pathways. Furthermore, source-oriented risk assessment (SORA) revealed that the sources of coal combustion, industrial waste and Mo smelting had the highest contributions to noncarcinogenic and carcinogenic risks. Overall, for effective environmental management in agricultural soil, the framework of SORA was verified as an effective tool in the identification of the priority control of HMs and their sources.

Source-specific probabilistic contamination risk and health risk assessment of soil heavy metals in a typical ancient mining area

Heavy metal pollution (HMP) from mining operations severely threatens soil ecosystems and human health. Identifying the sources of soil heavy metals (HMs) and assessing source-specific risks are critical for developing effective risk mitigation strategies. In this study, a combination of methodologies including PMF, Monte Carlo analysis, soil pollution risk index, and a human health risk assessment model were utilized to investigate soil HM risks in a typical ancient mining area in Daye City, China, considering both environmental pollution and human health impacts. Cu emerged as the most significant soil pollution risk, whereas As posing the highest health risk. About 48.44 % of the multi-element integrated soil pollution risk has escalated to the heavy level. Furthermore, around 22.42 % of the non-carcinogenic risk (NCR) and 9.53 % of the carcinogenic risk (CR) exceeded unacceptable thresholds (THI > 1 for NCR and TCR > 1E-4 for CR). The PMF model identified four distinct sources: the smelting industry, traffic emissions, a combination of agricultural and natural factors, and mining activities. The mixed agricultural and natural source significantly impacted health risks, contributing 42.17 % to NCR and 53.88 % to CR, followed by the mining source, contributing 31.67 % to NCR and 24.07 % to CR. Interestingly, the mining source contributed the highest soil pollution risk at 42.45 %, while the mixed agricultural and natural source exhibited the lowest at 16.33 %. Furthermore, the study explored source-specific risk components by evaluating the contributions of different sources to specific elements. The mining source was identified as the focus for soil HMP control, followed by the mixed agricultural and natural source. Overall, this study provided an in-depth analysis of soil heavy metal risks in mining areas from the source apportionment perspective, which broadened the research framework of soil heavy metal source analysis and risk assessment, potentially providing scientific guidance for managing regional soil HMP.

Impacts of land use/cover and slope on the spatial distribution and ecological risk of trace metals in soils affected by smelting emissions

The soil contamination around smelting sites shows high spatial heterogeneity. This study investigated the impacts of distance, land use/cover types, land slopes, wind direction, and soil properties on the distribution and ecological risk of trace metals in the soil around a copper smelter. The results demonstrated that the average concentrations of As, Cd, Cu, Pb, and Zn were 248.0, 16.8, 502.4, 885.6, and 250.2 g mg kg-1, respectively, higher than their background values. The hotspots of trace metals were primarily distributed in the soil of smelting production areas, runoff pollution areas, and areas in the dominant wind direction. The concentrations of trace metals decreased with the distance to the smelting production area. An exponential decay regression revealed that, depending on the metal species, the influence distances of smelting emissions on trace metals in soil ranged from 450 to 1000 m. Land use/cover types and land slopes significantly affected trace element concentrations in the soil around the smelter. High concentrations of trace metals were observed in farmland, grassland, and flatland areas. The average concentrations of trace metals in the soil decreased in the order of flat land > gentle slope > steep slope. Soil pH values were significantly positively correlated with Cd, Cu, Pb, Zn, and As, and SOM was significantly positively correlated with Cd, Pb, and Zn in the soil. Trace metals in the soil of the study area posed a significant ecological risk. The primary factors influencing the distribution of ecological risk, as determined by the Ctree analysis, were land slope, soil pH, and distance to the source. These results can support the rapid identification of high-risk sites and facilitate risk prevention and control around smelting sites.

Spatial distribution, ecological risk and health risk assessment of heavy metals in agricultural soil from Ankang basin, Shaanxi Province

In order to assess the heavy metal pollution features, ecological dangers, and health risk status posed to human beings by soils in the Ankang Basin, a study was conducted. This involved the collection of 38 surface soil samples, followed by the determination of elemental levels of arsenic, mercury, copper, cadmium, lead, chromium, nickel, and zinc. The concentrations of arsenic, mercury, copper, cadmium, lead, chromium, nickel, and zinc were quantified through the collection of 38 surface soil samples. The data obtained from the study was subjected to analysis and evaluation utilizing various academic methodologies, including the geo-accumulation index method, potential ecological risk assessment method, human health risk assessment model, and Monte Carlo simulation method. The findings indicated that the concentrations of the eight heavy metals in the soil above the background levels, with only Cadmium (Cd) marginally surpassing the threshold set for controlling soil pollution risks. The ground accumulation index revealed a higher degree of soil pollution with mercury, cadmium, copper, and zinc components. According to the possible ecological risk index, the presence of mercury and cadmium elements poses significant ecological hazards. The geographical distribution analysis suggests that these risks mostly stem from the combined impacts of human activities and the topographical and geomorphological characteristics of the river valley. The findings of the human health risk assessment indicated that the non-carcinogenic risk fell within acceptable limits. Additionally, it was observed that the carcinogenic risk associated with arsenic, mercury, cadmium, and nickel was comparatively greater for children as compared to adults. The results of the Monte Carlo simulations indicate that the non-carcinogenic hazards have a negligible effect on human health. However, it was seen that arsenic and nickel have a greater likelihood of presenting a substantial carcinogenic risk to humans, particularly in relation to the pediatric population, hence exerting a more pronounced impact on their health. In general, it is observed that conventional deterministic risk assessments tend to overstate the potential health risks associated with a given situation. Conversely, the utilization of Monte Carlo simulations has been found to effectively mitigate uncertainties in health risk assessments. It has been observed that children exhibit a higher vulnerability to both carcinogenic and non-carcinogenic health impacts resulting from exposure to heavy metals present in soil, in comparison to adults. It is recommended that residents prioritize the surveillance of soil heavy metals in relation to potential impacts on human health.

Heavy metals contamination, receptor model-based sources identification, sources-specific ecological and health risks in road dust of a highly developed city

The present study quantified Ni, Cu, Cr, Pb, Cd, As, Zn, and Fe levels in road dust collected from a variety of sites in Tangail, Bangladesh. The goal of this study was to use a matrix factorization model to identify the specific origin of these components and to evaluate the ecological and health hazards associated with each potential origin. The inductively coupled plasma mass spectrometry was used to determine the concentrations of Cu, Ni, Cr, Pb, As, Zn, Cd, and Fe. The average concentrations of these elements were found to be 30.77 ± 8.80, 25.17 ± 6.78, 39.49 ± 12.53, 28.74 ± 7.84, 1.90 ± 0.79, 158.30 ± 28.25, 2.42 ± 0.69, and 18,185.53 ± 4215.61 mg/kg, respectively. Compared to the top continental crust, the mean values of Cu, Pb, Zn, and Cd were 1.09, 1.69, 2.36, and 26.88 times higher, respectively. According to the Nemerow integrated pollution index (NIPI), pollution load index (PLI), Nemerow integrated risk index (NIRI), and potential ecological risk (PER), 84%, 42%, 30%, and 16% of sampling areas, respectively, which possessed severe contamination. PMF model revealed that Cu (43%), Fe (69.3%), and Cd (69.2%) were mainly released from mixed sources, natural sources, and traffic emission, respectively. Traffic emission posed high and moderate risks for modified NIRI and potential ecological risks. The calculated PMF model-based health hazards indicated that the cancer risk value for traffic emission, natural, and mixed sources had been greater than (1.0E-04), indicating probable cancer risks and that traffic emission posed 38% risk to adult males where 37% for both adult females and children.

The Patterns of Migration of Potentially Toxic Elements from Coal Mining Subsidence Areas and Associated Soils to Waterlogged Areas

It is crucial for effectively controlling potentially toxic element (PTE) pollution to understand the pollution situation, ecological risks, health risks, and migration patterns of PTEs. However, currently, no research has been conducted on the migration patterns of soil PTEs from coal mining subsidence areas to waterlogged areas under different restoration modes. In this study, a total of 15 sediment samples and 60 soil samples were collected from landscaped wetlands, aquaculture wetland, fish-photovoltaic complementary wetland, photovoltaic wetland, and waterlogged areas with untreated coal mining subsidence. The PTE pollution status, ecological risks, health risks, migration patterns, and the important factors influencing the migration were analyzed. The results indicated that the comprehensive pollution level of PTEs in waterlogged areas with coal mining subsidence can be reduced by developing them into landscaped wetlands, aquaculture wetlands, fish-photovoltaic complementary wetlands, and photovoltaic wetlands. Additionally, the closer to the waterlogged area, the higher the Cu content in the subsidence area soil is, reaching its peak in the waterlogged area. The Cd was influenced positively by SOC and pH. The research results were of great significance for formulating reclamation plans for waterlogged areas and controlling PTE pollution.

Genetic programming-based predictive model for the Cr removal effect of in-situ electrokinetic remediation in contaminated soil

Soil electrokinetic remediation is an emerging and efficient in-situ remediation technology for reducing environmental risks. Promoting the dissolution and migration of Cr in soil under the electric field is crucial to decrease soil toxicity and ecological influences. However, it is difficult to establish strong relationships between soil treatment and impact factors and to quantify their contributions. Machine learning can help establish pollutant migration models, but it is challenging to derive predictive formulas to improve remediation efficiency, describe the predictive model construction process, and reflect the importance of the predictors for better regulation. Therefore, this paper established a predictive model for the electrokinetic remediation of Cr-contaminated soil using genetic programming (GP) after determining the characteristic parameters which influenced the remediation effect, described the model's adaptive optimization process through the algorithm's function, and identified the sensitivity factors affecting the Cr removal effect. Results showed that the Cr(VI) and total Cr concentrations predicted by GP were in satisfactory agreement with the experimental values, 92% of the training data and 90% of the validation data achieved errors within 1%, and could fully reflect the target ions' content variation in different soil layers. By substituting the above prediction formulas into Sobol sensitivity analysis, it was determined that conductivity, pH, current, and moisture content dramatically affected the Cr content variation in distinguished regions. For overall contaminated area, the system current and soil pH were the most sensitive factors for Cr(VI) and total Cr contents. Remediation efforts throughout the contaminated area should focus on the role of current versus soil pH. GP and sensitivity analysis can provide decision support and operational guidance for in-situ soil electrokinetic treatment by establishing a remediation effect prediction model, expediting the development and innovation of electrokinetic technology.

Multi-technological integration in a smelting site: Visualizing pollution characteristics and migration pattern

Heavy metal(loid)s pollution of industrial legacies has become a severe environmental issue worldwide. Linking soil pollution to groundwater contaminant plumes would make invisible pollution features visible across the site, but related studies are lacking and require the convergence of multiple technologies. This study uniformly managed the soil and groundwater data in a 3D visualization model to pellucidly assess the spatial distribution of critical contaminants beyond simple drilling information. The distribution of Pb, Zn, As, and Cd in soil-groundwater system has a strong correlation to historical production, substance type, soil property, and groundwater flow direction. Over 2600 measurements of High-density electrical resistivity tomography (ERT) data were used to guarantee the exactness of soil structures. Hydraulic conductivity showed a strongest correlation (R2 = 0.86), yielding a calibrated model to reveal the anisotropic and contaminant transport in the region, with the consequent minimize the drilling tests. This study provides a template for the description of a verifiable scenario of hydrogeological conditions and pollution characteristics at smelting sites, coupled with traditional exploration and non-invasive techniques. The findings highlight the significance of visualizing the internal state of the soil-groundwater system under consideration, thus providing a basis for targeted control measures against site contamination.

Spatial distribution, source apportionment and potential ecological risk assessment of trace metals in surface soils in the upstream region of the Guanzhong Basin, China

The health of ecosystems and safety of agricultural products are correlated with trace metal pollutionin in the soil, which eventually affects mankind. For this research, topsoil (0-20 cm) was sampled from 51 locations in the upstream area of the Guanzhong Basin to determine the level of pollution, spatial distribution characteristics and origins of 15 trace metals (V, Cr, Mn, Fe, Ni, Cu, Zn, As, Se, Rb, Sr, Y, Zr, Cd, Pb). The pollution index and potential ecological risk index were adopted for the accurate analyses of contamination degree and ecological risk that trace elements cause. The identification of potential sources of trace metals pollution was carried out using the APCS-MLR model and multivariate statistical analysis. Findings demonstrated that the most contaminated elements in the topsoil of the designated areas were Cr, Cu, Cd and Pb, and the average levels of all trace metal elements exceeded their respective local background values. However, most of the sampling points showed slight pollution, and a few demonstrated moderate and severe pollution. The southern, south-western and eastern parts in the research zone were relatively seriously contaminated, especially near Baoji City and Wugong County. Fe, Cu, Zn, Ni, Se were mainly caused by combination of agricultural and industrial production, the primary sources of Mn, Y, and Zr were the process of mining and industrial production, Cd and Pb originated mainly from traffic emission and agricultural pollution, and Cr mainly came from mining and metal smelting processes. Meanwhlie, some unknown pollution sources were also disclosed. This study has a reliable reference value for determining the source of trace metals in this region. To further determine the pollution sources of trace elements, long-term monitoring and management is necessary.

Spatial and temporal distribution of heavy metals pollution and risk indices in surface sediments of Gomal Zam Dam Basin, Pakistan

Sediments were considered a sink and potential source of heavy metals in the aquatic system. For this purpose, the present study examined surface sediments for spatial and temporal variation of heavy metals pollution and risk indices in the Gomal Zam Dam Basin (GZDB), Pakistan. Sediment samples (n = 20) were collected from the GZDB, i.e., Gomal Zam Dam, its inlets, and outlets in the winter and summer seasons of 2020, and examined for heavy metals such as zinc (Zn), nickel (Ni), manganese (Mn), lead (Pb), chromium (Cr), copper (Cu), iron (Fe), and cobalt (Co) concentrations. Among GZDB, results showed that the Zhob River Inlet had a higher levels of heavy metals in both seasons. The results revealed that pollution load index values were < 1, observing no pollution in the aquatic system. The risk indices values revealed that sampling sites showed no or very low risk during the summer, 84% of samples showed no or very low risk during the winter, and the rest noted with reasonable risks. Winter season showed higher average values of contamination and risk indices than summer. Statistical analyses revealed that the heavy metals contaminations were mainly due to geogenic sources of rock weathering and ore deposits, with minor contributions from anthropic activities. This study recommends regular monitoring of temporal studies on heavy metals contamination in the water of the GZDB.

Biochar applications for treating potentially toxic elements (PTEs) contaminated soils and water: a review

Environmental pollution with potentially toxic elements (PTEs) has become one of the critical and pressing issues worldwide. Although these pollutants occur naturally in the environment, their concentrations are continuously increasing, probably as a consequence of anthropic activities. They are very toxic even at very low concentrations and hence cause undesirable ecological impacts. Thus, the cleanup of polluted soils and water has become an obligation to ensure the safe handling of the available natural resources. Several remediation technologies can be followed to attain successful remediation, i.e., chemical, physical, and biological procedures; yet many of these techniques are expensive and/or may have negative impacts on the surroundings. Recycling agricultural wastes still represents the most promising economical, safe, and successful approach to achieving a healthy and sustainable environment. Briefly, biochar acts as an efficient biosorbent for many PTEs in soils and waters. Furthermore, biochar can considerably reduce concentrations of herbicides in solutions. This review article explains the main reasons for the increasing levels of potentially toxic elements in the environment and their negative impacts on the ecosystem. Moreover, it briefly describes the advantages and disadvantages of using conventional methods for soil and water remediation then clarifies the reasons for using biochar in the clean-up practice of polluted soils and waters, either solely or in combination with other methods such as phytoremediation and soil washing technologies to attain more efficient remediation protocols for the removal of some PTEs, e.g., Cr and As from soils and water.

A hydrochemical and isotopic approach for source identification and health risk assessment of groundwater arsenic pollution in the central Yinchuan basin

Arsenic contamination of groundwater is becoming a major global issue as it can severely affect the safety of drinking water and human health. In this paper, 448 water samples were investigated to study the spatiotemporal distribution, source identification and human health risk of groundwater arsenic pollution in the central Yinchuan basin by applying a hydrochemical and isotopic approach. The results showed that arsenic concentrations in groundwater ranged from 0.7 μg/L to 26 μg/L with a mean of 2.19 μg/L, and 5.9% of samples were above 5 μg/L, indicating the arsenic pollution of groundwater in the study area. High arsenic groundwater was mainly distributed in the northern and eastern areas along the Yellow river. The main hydrochemistry type of high arsenic groundwater was HCO3·SO4-Na·Mg, and the dissolution of arsenic-bearing minerals in sediment, irrigation water infiltration and aquifer recharge from the Yellow river were the main sources of arsenic in groundwater. The arsenic enrichment was dominantly controlled by the TMn redox reaction and the competitive adsorption of HCO3-, and the influence of anthropogenic activities was limited. The health risk assessment suggested that the carcinogenic risk of As for children and adults greatly exceeded the acceptable risk threshold of 1E-6, displaying a high carcer risk, while the non-carcinogenic risks of As, F-, TFe, TMn and NO3- in 2019 were largely higher than the acceptable risk threshold (HQ > 1). The present study provides insight into the occurrence, hydrochemical processes and potential health risk of arsenic pollution in groundwater.

A global meta-analysis of the correlation between soil physicochemical properties and lead bioaccessibility

Soil physiochemical properties play a vital role in bioaccessibility-based health risk assessment as it can determine the bioaccessibility and the true risk of potentially toxic elements in soil. However, the effects of soil properties on bioaccessibility still remains unclear. In this paper, 17 of the 1454 literatures with 474 samples were identified, screened and reviewed for exploring the correlation between soil physicochemical properties and lead bioaccessibility (BAc_Pb) through a meta-analysis approach. Five soil physicochemical parameters including pH, SOM, Clay, CEC and T-Pb were systematically analyzed using Principal component analysis, Pearson correlation analysis and survival analysis. The results showed that pH of simulated gastric juice is a major source of heterogeneity of the correlation between soil pH and BAc_Pb. In the gastric phase, the effect of alkaline soil on high BAc_Pb (BAc >50%) is more sensitive, and the effect of acidic soil on low BAc_Pb (BAc <50%) is more sensitive. However, in the small intestinal phase, soil pH displays little impacts on BAc_Pb in acidic, alkaline and neutral soils. Although three principal components explained 66.2% and 64.9% of the total variance of the urban, agricultural, and mining soils in gastric and small intestinal phases, respectively, there was no strong evidence that soil type can influence the BAc_Pb. The results of present study provide insights into the correlation between soil properties and BAc_Pb, and prediction of the bioaccessibility and bioavailability of Pb in different types of soil.