Source-oriented probabilistic health risk assessment of soil potentially toxic elements in a typical mining city

Monte Carlo simulation-based risk assessment of human exposure to multi-mycotoxins in Platycladi semen

Mycotoxin contamination in Platycladi semen has become an increasing concern worldwide due to its significant threat to public health. In this study, a modified QuEChERS-based UPLC-MS/MS method was established to detect multi-mycotoxins in 190 batches of Platycladi semen samples obtained from various channels in China. Out of these samples, 188 tested positive for one or more mycotoxins, with an incidence of 98.95 %. Alternariol monomethyl ether was the most commonly detected with an incidence rate of 92.63 %, followed by fumonisin B2 at 91.58 % and sterigmatocystin at 87.89 %. Notably, the aflatoxin B1 contents in 26 samples and the total aflatoxins contents in 18 samples exceeded their respective official maximum residue limits. Given the toxicity and high contamination levels of mycotoxins, the risk of human exposure to them via the consumption of Platycladi semen was assessed using Monte Carlo simulation-based probabilistic models. The risk assessment using the margin of exposure and hazard quotient approach indicated that Platycladi semen is particularly susceptible to aflatoxins and sterigmatocystin, which pose significant threats to human health. This study provides the regulatory authority with a powerful platform for monitoring multi-mycotoxins in Platycladi semen, offering valuable data to safeguard consumers from potential health risks associated with mycotoxin contamination.

Anthropogenic impacts on regional leaching risks posed by trace metal(loid)s in the soil of an industrial city

The leaching risks associated with trace metal(loid)s (s) in regional soil are complex due to the intricate interplay between pollution levels and soil properties. A Kd-based regional leaching risk assessment method was developed to assess the leaching risks posed by soil TMs. The random forest model was used to identify the effects of the soil environment on the soil Kd and the leaching risks. The reliability of the established method was successfully validated by field monitoring data (R2 = 0.84). The mean total soil groundwater risk was 1.59, the high mobility of Cd contributed the most to total risks. High-risk areas were mainly located in the farmland and forestland around a smelter and areas with severe soil acidification. The high mobility and moderate contamination of TMs resulted in the highest leaching risks. Furthermore, soil acidification and the conversion of farmland to forestland would increase the leaching risk by 33.5 % and 46.4 %, respectively, while urban expansion would reduce the leaching risk by 60.3 %. The Kd-based leaching risk assessment method provided a critical framework for decision-makers to efficiently identify high-risk areas on a regional scale, facilitating a deeper understanding of how anthropogenic activities influenced the leaching risks of TMs in soil.

Spatial and ecological health impacts of potentially toxic elements in road dust from long-term mining activities: A case study of the Bayan Obo deposit

The long-term impacts of mining activities at the Bayan Obo deposit on potentially toxic elements (PTEs) in road dust remain insufficiently understood. This study aims to enrich knowledge in this area by investigating the spatial and eco-health impacts of PTEs in both bulk road dust (BRD) and resuspended road dust (RRD) from mining. An integrated approach combining Monte Carlo simulations with multiple statistical and geostatistical methods was used to quantify mining-related impacts. The findings revealed that Cd was the most polluted element. Concentrations of Cd, Mo, Pb and Zn were notably higher near the mine and decreased with increasing distance, with mining activities directly contributing over 20 % to these PTEs. Moderate and considerable eco-risks were identified for BRD and RRD, respectively, primarily driven by Cd and Mo, with higher risks closer to the mine. While non-carcinogenic risks were negligible, carcinogenic risks for adults required attention. Mining-related sources accounted for over 30 % of eco-risks but less than 10 % of health risks. This research integrates multiple methods, providing a more comprehensive understanding of the spatial and eco-health impacts of mining activities on PTEs in road dust. These findings offer critical insights and guidance for managing similar environmental challenges in other mining regions.

Machine learning-assisted source identification and probabilistic ecological-health risk assessment of heavy metal(loid)s in urban park soils

The accumulation of heavy metal(loid)s (HMs) in the soils of urban parks in industrial cities has raised global concerns because of their environmental and health impacts. However, traditional deterministic assessments commonly overlook uncertainties in pollution evaluation, failing to accurately quantify source-specific contributions and associated risks. This study combines multivariate statistical methods, machine learning techniques, and positive matrix factorization (PMF) with Monte Carlo simulation to investigate HM sources, probabilistic pollution levels, source-based ecological risks, and population-specific health hazards in seven urban parks in a nickel-based mining city in China. Results showed that average concentrations of Cd (0.53 mg/kg), Cr (77.72 mg/kg), Cu (171.15 mg/kg), Hg (0.03 mg/kg), Ni (125.42 mg/kg), Pb (27.13 mg/kg), and Zn (81.97 mg/kg) exceeded their background values, except for As (11.85 mg/kg), particularly for Cd, Cu, and Ni, with exceedance rates of 98.46%, 100.00%, and 100.00%, respectively. Probabilistic assessments revealed that pollution levels were particularly high due to Cd, Cu, and Ni. Source apportionment using PMF, correlation analysis, hierarchical cluster analysis, and super-clustering of self-organizing maps identified fertilizers and pesticides (19.33%), industrial atmospheric deposition (21.13%), mining and agrochemicals (16.41%), and mining and transport activities (43.13%) as the major pollution sources. Probabilistic ecological risk assessments showed significant risks from Cd, Hg, and Cu. Non-carcinogenic risks were negligible, while carcinogenic risks were cautionary, especially for children. Mining and transportation activities were the main contributors to ecological risks, while fertilizers, pesticides, and Ni were the primary health risk factors. This study provides a robust framework to improve the accuracy of risk evaluation and offers valuable guidance for targeted interventions and sustainable management of urban soils.

A novel tiered ecological risk framework linking metal-driven pollution to soil microbial dynamics in a fragile ecosystem

Widespread soil heavy metal (HM) pollution has caused great concerns worldwide. A refined and cost-effective ecological risk assessment (ERA) is critical for managing these risks. Herein, we propose a novel tiered ERA framework to evaluate indigenous pollution-effect associations in contaminated soils. This framework progressively applies source apportionment, spatial regression, deterministic and probabilistic risk characterization, ecological surveys of soil phospholipid fatty acids (PLFAs), and successive multivariable statistics to provide comprehensive ERA evidence, as demonstrated in an ecologically fragile mining area. The risk screening phase identified Zn, Pb, Cd, Cu, and Hg as priority contaminants, and mining activities contributed 86.5 % (Zn), 87.2 % (Pb), 83.3 % (Cd), 64.6 % (Cu), and 52.3 % (Hg) of the total soil concentrations in the study area determined by the positive matrix factorization (PMF) model. The risk quotient of ecological criteria tailored to different land uses exhibited ecologically relevant risk grading. The risk quantification phase determined the overall risk probabilities to be 53.98 %, 11.12 %, 9.69 %, 5.03 % and 1.34 % for Zn, Pb, Cu, Cd and Hg, respectively, and provided adaptive HM priority lists with different risk grades. The risk causeeffect attribution phase confirmed that HMs significantly reduced soil fungal PLFA abundance and indirectly altered the PLFA structure by decreasing the soil pH. The proposed framework offers a cost-effective, refined and feasible technical support for ecological risk management in contaminated areas.

Two-dimensional Monte Carlo simulation coupled with multilinear regression modeling of source-specific health risks from groundwater

Effective protection of groundwater requires an accurate health risk assessment of contaminants; however, the diversity of pollution sources, variability, and uncertainties in exposure parameters present significant challenges in this assessment. In this study, groundwater risk estimates associated with NO3-, and F-, along with fourteen heavy metal(loid)s (V, Cr, Mn, Fe, Ni, Cu, As, Co, Cd, Se, Pb, Hg, Zn, and Al) in an agricultural area were optimized by implementing positive matrix factorization (PMF), multilinear regression, and two-dimensional Monte Carlo simulations to characterize source-specific health risks. Groundwater pollution was analyzed considering regional variations, including differences in elevation, land use and land cover, and soil types. Three pollution sources were identified: agricultural practices, traffic, and natural processes. Moreover, the results revealed NO3- from an agricultural source as the primary control contaminant. Additionally, both adults and children in the study area face significant non-carcinogenic health risks. To mitigate these risks, this study recommends maximum consumption levels of 1.44 L/day for adults and 0.35 L/day for children. Furthermore, adults weighing > 68.1 kg and children weighing > 15.9 kg are likely to be at reduced risk of experiencing adverse health effects. Compared to deterministic health risk assessment and one-dimensional Monte Carlo simulation of health risks, two-dimensional Monte Carlo simulation showed improved performance, providing better accuracy and higher precision in health risk assessment results. Thus, this research is expected to enhance the understanding of health risk assessment related to groundwater and to provide valuable guidance for managing groundwater pollution.

Evaluation of machine learning models for accurate prediction of heavy metals in coal mining region soils in Bangladesh

Coal mining soils are highly susceptible to heavy metal pollution due to the discharge of mine tailings, overburden dumps, and acid mine drainage. Developing a reliable predictive model for heavy metal concentrations in this region has proven to be a significant challenge. This study employed machine learning (ML) techniques to model heavy metal pollution in soils within this critical ecosystem. A total of 91 standardized soil samples were analyzed to predict the accumulation of eight heavy metals using four distinct ML algorithms. Among them, random forest model outer performed in predicting As (0.79), Cd (0.89), Cr (0.63), Ni (0.56), Cu (0.60), and Zn (0.52), achieving notable R squared values. The feature attribute analysis identified As-K, Pb-K, Cd-S, Zn-Fe2O3, Cr- Fe2O3, Ni-Al2O3, Cu-P, and Mn- Fe2O3 relationships resembled with correlation coefficients among them. The developed models revealed that the contamination factor for metals in soils indicated extremely high levels of Pb contamination (CF ≥ 6). In conclusion, this research offers a robust framework for predicting heavy metal pollution in coal mining soils, highlighting critical areas that require immediate conservation efforts. These findings emphasize the necessity for targeted environmental management and mitigation to reduce heavy metal pollution in mining 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.

Historical mining towns: The establishment of 'Soil Planning Areas' for the risk management of contaminated soil

Historical mining towns face financial challenges with the proposed Soil Monitoring Law of the European Union, which will require the management of soil contamination, since remediating soil in densely populated towns and cities is challenging. We compared the environmental impact of sulfide ore mining in the urban area of Outokumpu in Finland with that of other European sites, focusing on soil contamination. Soil sampling revealed that mine tailings were historically used in road construction. The threshold values of Cu, Ni, and Zn were exceeded at several points, with the highest Cu content reaching 2733 mg/kg. Groundwater and surface water contamination was also evident, mainly due to the lack of a proper protective structure in tailings to prevent acid mine drainage. A preliminary risk assessment suggests health risks from unintentional soil ingestion and dust inhalation. However, the issues in many historical mining towns are more severe if they contain high levels of As or Pb which are more toxic than those of concern in Outokumpu. The historical mining town of Freiberg in Saxony, Germany, has been regulated as a 'Soil Planning Area', where limit values have been provided based on land use scenarios. The regional handling and re-use of excavated soil is based on contamination categories, with the tightest restrictions for the areas where the As content exceeds 340 mg/kg. We suggest 'Soil Planning Areas' to be established in historical mining towns facing similar challenges as a first step to mitigate environmental and health risks with reasonable economic resources.

Identifying spatial drivers of soil heavy metal pollution risk integrating positive matrix factorization, machine learning, and multi-scale geographically weighted regression

Soil heavy metal (HMs) contamination poses significant ecological and health risks, yet the spatial drivers of HMs pollution remain poorly understood. This study integrates pollution risk assessment, positive matrix factorization, machine learning, and multi-scale geographically weighted regression to develop a framework for identifying the spatial drivers of soil HMs contamination risk in Yangtze River New City, China. Analysis of 7152 samples revealed that although average HMs concentrations were below national standards, As, Cd, Cr, Cu, Hg, and Ni exceeded local background levels. Four key factors were identified as drivers of HMs contamination: natural sources (30.36 %, influenced by soil type), mixed agricultural and transportation sources (29.56 %, driven by cropland, aquaculture, and road density), human activities (12.68 %, including population density and community activities), and industrial sources (27.42 %, linked to factories and enterprises). Regional variations indicated that industrial activities, transportation, and human activities primarily influenced health risks, while agriculture and natural factors had a greater impact on ecological and environmental capacity risks. These findings underscore the importance of considering spatial heterogeneity in HMs pollution risk assessments and offer insights for developing targeted, region-specific policies to mitigate pollution risks of soil HMs.

Heavy metal enrichment characteristics and synergistic evaluation in soil-crop-human systems of agricultural land with different soil parent materials

Heavy metal (HM) pollution in agricultural areas seriously threatens food security and ecological health. In this study, based on different soil parent materials, the HMs enrichment in the soil-crop systems of two typical eastern Chinese agricultural lands was compared and analyzed. Multivariate linear stepwise regression analysis, influence index of comprehensive quality and HHRA model were used to understand the bioaccumulation and to evaluate the soil-crop-human system. The study showed that HMs exhibited different enrichment characteristics in the two soil parent material areas. Cd faced a higher risk control rate and was a priority pollutant in the soil environment. The acidification soils in the granitic parent material area led to more widespread Ni pollution in wheat grains. The HM absorption model clarifies that driving factors such as the HM content, physicochemical properties and the distance to the river can well explain the enrichment ability of HMs in wheat grains. The synergistic evaluation revealed that only 13.04% of soil and crops were at a clean level. Soil contamination is more prevalent in the metamorphic rocks area, while crop contamination is more severe in the granitic parent material area. Probabilistic health risk assessment indicated that HMs primarily impact health through the ingestion of contaminated wheat, so residents of the granitic parent material area face a slightly higher HI. This information will be crucial for understanding the translocation and accumulation of HMs within soil-crop-human health systems of agricultural land in different soil parent material areas and for developing effective pollution prevention and control programs.

Tracing sources-oriented ecological risks of metal(loid)s in sediments of anthropogenically-affected coastal ecosystem from northeast bay of Bengal

The current study focused on thirty-nine locations in the four islands (i.e., St. Martin, Moheskhali, Kutubdia, and Sonadia) and beach (Innani Beach) along the northeast Bay of Bengal to quantify sources-orientated ecological risks of metal(loid)s. The mean concentrations of As, Mn, Cr, Cd, and Pb are 4.8, 8.7, 1.6, 1.1, and 2 times higher than average shale volume (ASV) values. Key findings revealed that Mn, Cr, Cd, Pb, and As exceed safe levels, particularly on St. Martin and Moheshkhali islands, where tourism and coal mining intensify contamination. Ecological indexes showed moderate to considerable contamination levels, suggesting diverse impacts on aquatic life. Positive matrix factorization (PMF) model-based Nemerow integrated risk index (NIRI) indicated that mixed and coal mining sources posed a moderate risk for 10.26 % and 5.13 % of sediment samples, respectively. This paper serves as a model-based plan for mitigating pollution risks of metal(oid)s in coastal sediments on the northeast coast.

Human Health Risk Assessment of Chlorinated Hydrocarbons in Groundwater Based on Multi-Pathway Analysis

The rapid development of the global chemical industry has led to widespread groundwater contamination, with frequent pollution incidents posing severe threats to water safety. However, there has been insufficient assessment of the health risks posed by chlorinated hydrocarbon contamination in groundwater around chemical industrial parks. This study evaluates the chlorinated hydrocarbon contamination in groundwater at a chemical park and conducts a multi-pathway health risk assessment, identifying the key risk pollutants. In addition, sensitivity analysis of the primary exposure pathways was performed using the Monte Carlo method. The results indicate severe exceedance of pollutant concentrations with widespread diffusion. Carcinogenic risks were mainly driven by vinyl chloride, whose oral cancer slope factor was significantly higher than that of other substances, while non-carcinogenic risks were dominated by trichloro-ethylene, which had the lowest reference dose. Both carcinogenic and non-carcinogenic risks through the drinking water pathway accounted for approximately 90% of the total risk, whereas the risk contribution from dermal contact was negligible. Although boiling water can partially reduce the risks, its effect on high-concentration pollutants is limited. Additionally, sensitivity analysis showed that pollutant concentration was the primary influencing factor for risk values, followed by exposure duration. The findings of this study provide a scientific basis for effectively formulating pollution control measures and ensuring the drinking water safety of nearby residents.

Source to risk receptor transport and spatial hotspots of heavy metals pollution in peri-urban agricultural soils of the largest megacity in China

The traditional concentration-based health risk assessment of heavy metal (HMs) pollution in soil has often overlooked the initial loading and toxicity differences of HMs from various sources. This oversight hinders effective identification of the risky source, complicating precise risk management of soil HMs pollution. This study applied a source-oriented health risk assessment framework that integrates source profiling, exposure risk assessment, and spatial cluster analysis. Taking the Shanghai City, the largest megacity in China as a case, the findings revealed that overall environmental quality of peri-urban agricultural soil in Shanghai remains good, though 3.03 % of Cd concentrations exceeded the national reference standards. Industrial & traffic activities, primarily contributing Hg, Cd, and Pb, accounted for the highest proportion (44.3 %) of total metal concentrations and posed the greatest non-cancer risk (54.6 % for children and 53.1 % for adults). Notably, natural activities, mainly contributing Cr, ranked only third in concentration contribution (26.55 %) but induced the highest cancer risk (58.55 % for children and 57.08 % for adults). These findings suggest that sources with lower concentration contributions may still pose significant health risk. Integrating source apportionment with health risk assessment can more precisely identify the risky source and target areas for mitigating the human health hazards.

Source-oriented health risk assessment and priority control factor analysis of heavy metals in urban soil of Shanghai

The characteristics and ecological risks of heavy metal pollution in urban soils were comprehensively investigated, focusing on 224 typical industries undergoing redevelopment in Shanghai. The PMF (Positive Matrix Factorization) model was used to analyze the sources of soil heavy metals, while the HRA (Health Risk Assessment) model with Monte Carlo simulation assessed health risks to humans. Health risks under different pollution sources were explored, and priority control factors were identified. Results showed that, levels of most heavy metals exceeded Shanghai soil background values. Surface soil concentrations of Cd, Hg, Pb, Cu, Zn, and Ni exceeded the background values of Shanghai's soil to varying degrees, at 5.08, 5.40, 1.81, 1.95, 1.43, and 3.53 times, respectively. Four sources were identified: natural sources (22.23 %), mixed sources from the chemical industry and traffic (26.25 %), metal product sources (36.38 %), and pollution sources from electrical manufacturing and the integrated circuit industry (15.14 %). The HRA model indicated a tolerable carcinogenic risk for adults and children, with negligible non-carcinogenic risk. Potential risk was higher for children than for adult females, and higher for adult females than for adult males, with oral ingestion as the primary exposure pathway. Metal product sources and Ni were identified as primary control factors, suggesting intensified regional control. This study provides theoretical support for urban pollution prevention and control.

A meta-analysis of influencing factors on soil pollution around copper smelting sites

Non-ferrous smelting activities have caused serious heavy metal(loid) pollution in soil which seriously threatens human health globally. A number of studies have been conducted to assess the characteristics and risks of soil heavy metal(loid) pollution around copper (Cu) smelting sites. However, the current research mainly focuses on soil pollution around a single smelter, and the global impact of Cu smelting on soil and its quantitative relationship with related factors need to be further studied. Meta-analysis can integrate a large amount of data and quantitatively analyze the relationship between multiple factors. To investigate the extent to which Cu smelting sites have contributed to heavy metal(loid) pollution in soils, a meta-analysis was conducted on 189 research publications from 1993 to 2023. Furthermore, a single meta regression was used to analyze the relationship between the soil heavy metal(loid)s (HMs) and influencing factors on a global scale. The results of meta-regression analysis showed that compared with the soil background value, Cu smelting significantly increased the concentration of HMs in soil (315%), with the concentration increase for each heavy metal(loid) being: Cu (1012%) > Cd (622%) > As (315%) > Pb (277%) > Zn (188%) > Cr (96%) > Ni (95%) > Mn (45%). Among these, Cu, Cd, and As were the major pollutants in soils around Cu smelting sites. Land use type was a key factor affecting HMs concentrations in surrounding soils, and the influence of non-agricultural land (381%) was greater than that of agricultural land (203%). In addition, the influence of Cu smelting on HMs were negatively correlated with distance (QM=9.86) and positively correlated with latitude (QM=10.7). There was no significant correlation between heavy metal(loid) pollution and soil chemical properties, average annual rainfall and temperature, longitude, or other factors. Our work may be meaningful to the risk control and remediation for Cu smelting sites.

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.

Source identification of heavy metals and metalloids in soil using open-source Tellus database and their impact on ecology and human health

The presence of heavy metals and metalloids (metal(loid)s) in the food chain is a global problem, and thus, metal(loid)s are considered to be Potentially Toxic Elements (PTEs). Arsenic (As), lead (Pb), mercury (Hg), and cadmium (Cd) are identified as prominent hazards related to human health risks throughout the food chain. This study aimed to carry out a source attribution for metal(loid)s in shallow topsoil of north-midlands, northwest, and border counties of the Republic of Ireland, followed by an assessment of the potential ecological and human health risks. The positive Matrix Factorization (PMF) was used for source characterization of PTEs, followed by the Monte Carlo simulation method, used for a probabilistic model to evaluate potential human health risks. The mean concentrations of prioritized metal(loid)s in the topsoil range in the order of Pb (28.83 mg kg-1) > As (7.81 mg kg-1) > Cd (0.51 mg kg-1) > Hg (0.11 mg kg-1) based on the open-source Tellus dataset. This research identified three primary sources of metal(loid) pollution: geogenic sources (36 %), mixed sources of historical mining and natural origin (33 %), and anthropogenic activities (31 %). The ecological risk assessment showed that Ireland's soil exhibits low-moderate pollution levels however, concerns remain for Cd and As levels. All metal(loid)s except Cd showed acceptable non-carcinogenic risk, while Cd and As accounted for high to moderate potential cancer risks. Potato consumption (if grown on land with elevated metal(loid) levels), Cd concentration in soil, and bioaccumulation factor of Cd in potatoes were the three most sensitive parameters. In conclusion, metal(loid)s in Ireland present low to moderate ecological and human health risks. It underscores the need for policies and remedial strategies to monitor metal(loid) levels in agricultural soil regularly and the production of crops with low bioaccumulation in regions with elevated metal(loid) levels.

Source apportionment and ecological risk assessment of antibiotics in Dafeng River Basin using PMF and Monte-Carlo simulation

Antibiotics, prevalent in aquatic ecosystems, pose a grave threat to human health and the ecological well-being. This paper performed a case study on Dafeng River Basin in southern China. Specifically, techniques including positive matrix factorization (PFM) and Monte-Carlo simulation were employed to comprehensively investigate the spatial variations, possible sources, and ecological risks of antibiotics in four groups: sulfonamides (SAs), macrolides (MLs), quinolones (QNs), and tetracyclines (TCs). The major findings were as follows: first, 43 and 39 antibiotics were detected in the surface water and sediments of the basin, respectively, where the respective total content were ND-490.08 ng/L and ND-144.34 μg/kg, and the QNs and TCs were the two dominating groups. Second, the highest antibiotic content in surface water (441.43 ng/L) was observed in the midstream area, whereas the highest concentration in sediments (68.41 μg/kg) was found in the upstream region. Third, the investigation identified five sources of antibiotics discharged to surface water: domestic sewage, agricultural drainage, livestock discharge, sewage treatment plants, and aquaculture; three sources were detected for antibiotics in sediments: aquaculture, sewage treatment plants, and livestock discharge. Fourth, QNs had a significantly higher ecological risk than the other three groups of antibiotics, and livestock discharge (31.4% contribution) and aquaculture (23.4% contribution) were the main sources of risks of antibiotic contamination in Dafeng River Basin. This study is expected to provide some reference for control and risk management of antibiotic pollution in Dafeng River Basin.

Identifying heavy metal sources and health risks in soil-vegetable systems of fragmented vegetable fields based on machine learning, positive matrix factorization model and Monte Carlo simulation

Urban fragmented vegetable fields offer fresh produce but pose a potential risk of heavy metal (HM) exposure. Thus, this study investigated HM sources and health risks in the soil-vegetable systems of Chongqing's central urban area. Results indicated that Cd was the primary pollutant, with 28.33 % of soil samples exceeding the screening value. Amaranth was particularly problematic, exceeding thresholds for Cd, Hg, and Cr, and both amaranth and celery showed significantly higher HM accumulation (p < 0.05). The HM pollution level in the soil-vegetable system was moderate or above. The sources of HMs identified via Positive matrix factorization (PMF) model included agricultural activities (18.19 %), natural soil parent material (25.88 %), mixed metal smelting and transportation (30.72 %), and coal combustion (25.21 %). Furthermore, evaluations using the Random Forest (RF) model revealed an intricate interaction of factors influencing the presence of HMs, where enterprise density, population density, and road density played significant roles in HMs accumulation. Monte Carlo assessments revealed higher non-carcinogenic risks for children (Pb, As) and greater carcinogenic risks for adults (Cd). Therefore, the issue of HM pollution in soils and vegetables from fragmented fields in industrial urban areas need attention, given the potential for elevated health risks with long-term vegetable consumption.

Pollution area identification, receptor model-oriented sources and probabilistic health hazards to prioritize control measures for heavy metal management in soil

Identifying the primary source of heavy metals (HMs) pollution and the key pollutants is crucial for safeguarding eco-health and managing risks in industrial vicinity. For this purpose, this investigation was carried out to investigate the pollution area identification with soil static environmental capacity (QI), receptor model-oriented critical sources, and Monte Carlo simulation (MCS) based probabilistic environmental and human health hazards associated with HMs in agricultural soils of Narayanganj, Bangladesh. The average concentration of Cr, Ni, Cu, Cd, Pb, Co, Zn, and Mn were 98.67, 63.41, 37.39, 1.28, 23.93, 14.48, 125.08, and 467.45 mg/kg, respectively. The geoaccumulation index identified Cd as the dominant metal, indicating heavy to extreme contamination in soils. The QI revealed that over 99% of the areas were polluted for Ni and Cd with less uncertain regions whereas Cr showed a significant portion of areas with uncertain pollution status. The positive matrix factorization (PMF) model identified three major sources: agricultural (29%), vehicular emissions (25%), and industrial (46%). The probabilistic assessment of health hazards indicated that both carcinogenic and non-carcinogenic risks for adult male, adult female, and children were deemed unacceptable. Moreover, children faced a higher health hazard compared to adults. For adult male, adult female, and children, industrial operations contributed 48.4%, 42.7%, and 71.2% of the carcinogenic risks, respectively and these risks were associated with Ni and Cr as the main pollutants of concern. The study emphasizes valuable scientific insights for environmental managers to tackle soil pollution from HMs by effectively managing anthropogenic sources. It could aid in devising strategies for environmental remediation engineering and refining industry standards.

Predictive analysis and risk assessment of potentially toxic elements in Beijing gas station soils using machine learning and two-dimensional Monte Carlo simulations

Gas stations not only serve as sites for oil storage and refueling but also as locations where vehicles frequently brake, significantly enriching the surrounding soil with potentially toxic elements (PTEs). Herein, 117 topsoil samples from gas stations were collected in Beijing to explore the impact of gas stations on PTE accumulation. The analysis revealed that the average Pollution Index (PI) values for Cd, Hg, Pb, Cu, and Zn in the soil samples all exceeded 1. The random forest (RF) model, achieving an AUC score of 0.95, was employed to predict PTE pollution at 372 unsampled gas stations. Additionally, a Positive Matrix Factorization (PMF) model indicated that gas station operations and vehicle emissions were responsible for 70 % of the lead (Pb) enrichment. Probabilistic health risk assessments showed that the carcinogenic risk (CR) and noncarcinogenic risk (NCR) for PTE pollution to adult females were the highest, at 0.451 and 1.61E-05 respectively, but still within acceptable levels. For adult males at contaminated sites, the Pb-associated CR and NCR were approximately twice as high as those at uncontaminated sites, with increases of 107 % and 81 %, respectively. This study provides new insights for managing pollution caused by gas stations.

Systematic assessment of source identification and ecological and probabilistic health risks of potentially toxic elements (PTEs) in soils of a typical coal mining area in Guanzhong region

Mining activities may cause the accumulation of potentially toxic elements (PTEs) in surrounding soils, posing ecological threats and health dangers to the local population. Therefore, a comprehensive assessment using multiple indicators was used to quantify the level of risk in the region. The results showed that the mean values of the nine potentially toxic elements in the study area were lower than the background values only for Cr, and the lowest coefficient of variation was 17.1 % for As, and the spatial distribution characteristics of the elements indicate that they are enriched by different factors. The elements Hg and Cd, which have substantial cumulative features, are the key contributors to ecological risk in the study region, which is overall at moderate risk. APCS-MLR model parses out 4 possible sources: mixed industrial, mining and transportation sources (53.98 %), natural sources (24.56 %), atmospheric deposition sources (12.60 %), and agricultural production sources (8.76 %). The probabilistic health risks show that children are more susceptible to health risks than adults; among children, the safety criteria (HI < 1 and CR < 10-4) were surpassed by 29.29 % of THI and 8.58 % of TCR. According to source-orientated health hazards, the element Ni significantly increases the risk of cancer. Mixed sources from industry, mining, and transportation are important sources of health risks. The results of this research provide some scientific references for the management and decrease of regional ecological and health risks.

Unveiling biochar potential to promote safe crop production in toxic metal(loid) contaminated soil: A meta-analysis

Biochar application emerges as a promising and sustainable solution for the remediation of soils contaminated with potentially toxic metal (loid)s (PTMs), yet its potential to reduce PTM accumulation in crops remains to be fully elucidated. In our study, a hierarchical meta-analysis based on 276 research articles was conducted to quantify the effects of biochar application on crop growth and PTM accumulation. Meanwhile, a machine learning approach was developed to identify the major contributing features. Our findings revealed that biochar application significantly enhanced crop growth, and reduced PTM concentrations in crop tissues, showing a decrease trend of grains (36.1%, 33.6-38.6%) > shoots (31.1%, 29.3-32.8%) > roots (27.5%, 25.7-29.2%). Furthermore, biochar modifications were found to amplify its remediation potential in PTM-contaminated soils. Biochar application was observed to provide favorable conditions for reducing PTM uptake by crops, primarily through decreasing available PTM concentrations and improving overall soil quality. Employing machine learning techniques, we identified biochar properties, such as surface area and C content as a key factor in decreasing PTM bioavailability in soil-crop systems. Furthermore, our study indicated that biochar application could reduce probabilistic health risks associated with of the presence of PTMs in crop grains, thereby contributing to human health protection. These findings highlighted the essential role of biochar in remediating PTM-contaminated lands and offered guidelines for enhancing safe crop production.

Comprehensive analysis of metal(loid)s and associated metal(loid) resistance genes in atmospheric particulate matter

Despite global concerns about metal(loid)s in atmospheric particulate matter (PM), the presence of metal(loid) resistance genes (MRGs) in PM remains unknown. Therefore, we conducted a comprehensive investigation of the metal(loid)s and associated MRGs in PMs in two seasons (summer and winter) in Xiamen, China. According to the geoaccumulation index (Igeo), most metal(loid)s, except for V and Mn, exhibited enrichment in PM, suggesting potential anthropogenic sources. By employing Positive Matrix Factorization (PMF) model, utilizing a dataset encompassing both total and bioaccessible metal(loid)s, along with backward trajectory simulations, traffic emissions were determined to be the primary potential contributor of metal(loid)s in summer, whereas coal combustion was observed to have a dominant contribution in winter. The major contributor to the carcinogenic risk of metal(loid)s in both summer and winter was predominantly attributed to coal combustion, which serves as the main source of bioaccessible Cr. Bacterial communities within PMs showed lower diversity and network complexity in summer than in winter, with Pseudomonadales being the dominant order. Abundant MRGs, including the As(III) S-adenosylmethionine methyltransferase gene (arsM), Cu(I)-translocating P-type ATPase gene (copA), Zn(II)/Cd(II)/Pb(II)-translocating P-type ATPase gene (zntA), and Zn(II)-translocating P-type ATPase gene (ziaA), were detected within the PMs. Seasonal variations were observed for the metal(loid) concentration, bacterial community structure, and MRG abundance. The bacterial community composition and MRG abundance within PMs were primarily influenced by temperature, rather than metal(loid)s. This research offers novel perspectives on the occurrence of metal(loid)s and MRGs in PMs, thereby contributing to the control of air pollution.

Pollution and Health Risk Assessment of Potentially Toxic Elements in Groundwater in the Kǒnqi River Basin (NW China)

Potentially toxic elements (PTEs) pose a significant threat to the groundwater system and human health. Pollution and the potential risks of PTEs in groundwater in the Kǒnqi River Basin (KRB) of the northwest arid zones of China are still unknown. A total of 53 groundwater samples containing eight PTEs (Al, As, Cd, Cu, Mn, Pb, Se, and Zn) were collected from the KRB, and the pollution levels and probabilistic health risks caused by PTEs were assessed based on the Nemerow Index (NI) method and the health risk assessment model. The results revealed that the mean contents of Al, As, and Mn in the groundwater surpassed the Class III threshold of the Standard for Groundwater Quality of China. The overall pollution levels of the investigated PTEs in the groundwater fall into the moderate pollution level. The spatial distributions of contents and pollution levels of different PTEs in the groundwater were different. Health risk assessment indicated that all the investigated PTEs in groundwater in the KRB may pose a probabilistic non-carcinogenic health risk for both adults and children. Moreover, As may pose a non-carcinogenic health risk, whereas the non-carcinogenic health risk posed by the other seven PTEs in groundwater will not have the non-carcinogenic risks. Furthermore, As falls into the low carcinogenic risk level, whereas Cd falls into the very low carcinogenic risk level. Overall, As was confirmed as the dominant pollution factor and health risk factor of groundwater in the KRB. Results of this study provide the scientific basis needed for the prevention and control of PTE pollution in groundwater.

Isotopic insights and integrated analysis for heavy metal levels, ecological risks, and source apportionment in river sediments of the Qinghai-Tibet Plateau

The research was carried out to examine the pollution characteristics, ecological risk, and origins of seven heavy metals (Hg, As, Pb, Cu, Cd, Zn, and Ni) in 51 sediment samples gathered from 8 rivers located on the Qinghai-Tibet Plateau (QTP) in China. The contents of Hg and Cd were 5.0 and 1.1 times higher than their background values, respectively. The mean levels of other measured heavy metals were below those found naturally in the local soil. The enrichment factor showed that the study area exhibited significantly enriched Hg with 70.6% sampling sites. The Cd contents at 19.6% of sampling sites were moderately enriched. The other sampling sites were at a less enriched level. The sediments of all the rivers had a medium level of potential ecological risk. Hg was the major ecological risk factor in all sampling sites, followed by Cd. The findings from the positive matrix factorization (PMF) analysis shown agricultural activities, industrial activities, traffic emissions, and parent material were the major sources. The upper, middle, and low reaches of the Quanji river had different Hg isotope compositions, while sediments near the middle reaches were similar to the δ202Hg of the industrial source. At the upstream sampling sites, the Hg isotope content was very close to the background level. The results of this research can establish a strong scientific sound to improve the safety of the natural circumstances of rivers on the QTP.

Evaluating the protective capacity of soil heavy metals regulation limits on human health: A critical analysis concerning risk assessment - Importance of localization

Heavy metal pollution of agricultural soil is a major global concern, prompting the establishment of maximum allowable limits (MALs) to ensure food safety and protect human health. This study collected and compared MALs for six heavy metals (As, Cd, Hg, Pb, Zn, and Cu) in agricultural soils from representative countries and organizations (EU and WHO/FAO). The research evaluated the critical health risks and efficacy of these MALs under the hypothetical scenario of metals concentrations reaching the maximum allowable level. Safe thresholds for heavy metals were then derived based on maximum acceptable health risk levels. The comparative analysis revealed significant variations in the specific limit values and terms of MALs across countries and organizations, even for the same metal. This suggests that there is no consensus among countries and organizations regarding the level of metal-related health risks. Furthermore, the risk analysis of metal concentrations reaching the maximum level accentuated heightened risks associated with As, suggesting that the current risk of soil As exposure was underestimated, particularly for children. However, soil Cu, Cd, and Zn limits generally resulted in low health risks, implying that the current limits may overestimate their hazard. Overall, the results highlight that the current MALs for soil heavy metals may not fully safeguard human health. There is a critical need to optimize current soil MALs based on localized risks and the actual impact of these metals on human health. It is suggested to appropriately lower the limits of metals (such as As) whose impact on health risks is underestimated, and cautiously increase the limits of metals (such as Cu, Cd, and Zn) that currently pose minor health risks. This approach aims to reduce both over and insufficient protection problems of soil heavy metal MALs, emphasizing the importance of considering the locality in setting these limits.

Integrated assessment of potentially toxic elements in soil of the Kangdian metallogenic province: A two-point machine learning approach

The accumulation of potentially toxic elements in soil poses significant risks to ecosystems and human well-being due to their inherent toxicity, widespread presence, and persistence. The Kangdian metallogenic province, famous for its iron-copper deposits, faces soil pollution challenges due to various potentially toxic elements. This study explored a comprehensive approach that combinescombines the spatial prediction by the two-point machine learning method and ecological-health risk assessment to quantitatively assess the comprehensive potential ecological risk index (PERI), the total hazard index (THI) and the total carcinogenic risk (TCR). The proportions of copper (Cu), cadmium (Cd), manganese (Mn), lead (Pb), zinc (Zn), and arsenic (As) concentrations exceeding the risk screening values (RSVs) were 15.03%, 5.1%, 3.72%, 1.24%, 1.1%, and 0.13%, respectively, across the 725 collected samples. Spatial prediction revealed elevated levels of As, Cd, Cu, Pb, Zn, mercury (Hg), and Mn near the mining sites. Potentially toxic elements exert a slight impact on soil, some regions exhibit moderate to significant ecological risk, particularly in the southwest. Children face higher non-carcinogenic and carcinogenic health risks compared to adults. Mercury poses the highest ecological risk, while chromium (Cr) poses the greatest health hazard for all populations. Oral ingestion represents the highest non-oncogenic and oncogenic risks in all age groups. Adults faced acceptable non-carcinogenic risks. Children in the southwest region confront higher health risks, both non-carcinogenic and carcinogenic, from mining activities. Urgent measures are vital to mitigate Hg and Cr contamination while promoting handwashing practices is essential to minimize health risks.

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

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

Determining priority control toxic metal for different protection targets based on source-oriented ecological and human health risk assessment around gold smelting area

Determining the priority control source and pollutant is the key for the eco-health protection and risk management around gold smelting area. To this end, a case study was conducted to explore the pollution characteristics, source apportionment, ecological risk and human health risk of toxic metals (TMs) in agricultural soils surrounding a gold smelting enterprise. Three effective receptor models, including positive matrix factorization model (PMF), ecological risk assessment (ERA), and probabilistic risk assessment (PRA) have been combined to apportion eco-human risks for different targets. More than 95.0% of samples had a Nemerow pollution index (NPI) > 2 (NPImean=4.27), indicating moderately or highly soil TMs contamination. Four pollution sources including gold smelting activity, mining source, agricultural activity and atmosphere deposition were identified as the major sources, with the contribution rate of 17.52%, 44.16%, 13.91%, and 24.41%, respectively. For ecological risk, atmosphere deposition accounting for 30.8% was the greatest contributor, which was mainly loaded on Hg of 51.35%. The probabilistic health risk assessment revealed that Carcinogenic risks and Non-carcinogenic risks of all population were unacceptable, and children suffered from a greater health risk than adults. Gold smelting activity (69.2%) and mining source (42.0%) were the largest contributors to Carcinogenic risks and Non-carcinogenic risks, respectively, corresponding to As and Cr as the target pollutants. The priority pollution sources and target pollutants were different for the eco-health protection. This work put forward a new perspective for soil risk control and management, which is very beneficial for appropriate soil remediation under limited resources and costs.

Major influencing factors identification and probabilistic health risk assessment of soil potentially toxic elements pollution in coal and metal mines across China: A systematic review

Deposition of potentially toxic elements (PTEs) in soils due to different types of mining activities has been an increasingly important concern worldwide. Quantitative differences of soil PTEs contamination and related health risk among typical mines remain unclear. Herein, data from 110 coal mines and 168 metal mines across China were analyzed based on 265 published literatures to evaluate pollution characteristics, spatial distribution, and probabilistic health risks of soil PTEs. The results showed that PTE levels in soil from both mine types significantly exceeded background values. The geoaccumulation index (Igeo) revealed metal-mine soil pollution levels exceeded those of coal mines, with average Igeo values for Cd, Hg, As, Pb, Cu, and Zn being 3.02-15.60 times higher. Spearman correlation and redundancy analysis identified natural and anthropogenic factors affecting soil PTE contamination in both mine types. Mining activities posed a significant carcinogenic risk, with metal-mine soils showing a total carcinogenic risk an order of magnitude higher than in coal-mine soils. This study provides policymakers a quantitative foundation for developing differentiated strategies for sustainable remediation and risk-based management of PTEs in typical mining soils.

Health risk assessment of heavy metals based on source analysis and Monte Carlo in the downstream basin of the Zishui

In this study, stone coal mines in the lower reaches of the Zijiang River were adopted as the research object. To analyze the spatial distribution, sources, and health risks of heavy metals in the surrounding soil of stone coal mines, 82 topsoil samples were collected in the study area, and the contents of 8 heavy metals including Cd, Hg, As, Cr, Pb, Cu, Ni, and Zn were determined. The spatial distribution of heavy metals was analyzed using ArcGIS, and the pollution sources of heavy metals were identified using Positive matrix factorization (PMF). Then, Monte Carlo and health risk assessment models were used to evaluate the health risks of different populations. The results showed that the average content of heavy metals followed the order of Zn > Cr > Pb > Cu > Ni > As > Cd > Hg, and the contents of all heavy metals were higher than the soil background values of Hunan Province. The high-value areas of heavy metals content were mostly concentrated in the central region close to areas with a notable concentration of stone coal mines. PMF identified four pollution sources, namely, mining activities (26.9%), atmospheric deposition (18.8%), natural sources (32.8%) and agricultural sources (21.5%). The carcinogenic and non-carcinogenic risks for children were higher than those for adults, with As and Cd posing higher carcinogenic risks to children. Based on the source of health risks, it was determined that the health risks could be primarily attributed to agricultural sources, and As was the main heavy metal causing health risks. This study provides theoretical support for treating heavy metal pollution in mining basins.

Characteristics, source analysis, and health risk assessment of potentially toxic elements pollution in soil of dense molybdenum tailing ponds area in central China

The issue of potentially toxic elements (PTEs) contamination of regional soil caused by mining activities and tailings accumulation has attracted wide attention all over the world. The East Qinling is one of the three main molybdenum mines in the world, and the concentration of PTEs such as Hg, Pb and Cu in the slag is high. Quantifying the amount of PTEs contamination in soil and identifying potential sources of contamination is vital for soil environmental management. In the present investigation, the pollution levels of 8 PTEs in the Qinling molybdenum tailings intensive area were quantitatively identified. Additionally, an integrated source-risk method was adopted for resource allocation and risk assessment based on the PMF model, the ecological risk, and the health risk assessment model. The mean concentrations of Cu, Ni, Pb, Cd, Cr, Zn, As, and Hg in the 80 topsoil samples ranged from 0.80 to 13.38 times the corresponding background values; notably high levels were observed for Pb and Hg. The source partitioning results showed that PTEs were mainly affected by four pollution sources: natural and agricultural sources, coal-burning sources, combined transport and mining industry sources, and mining and smelting sources. The health risk assessment results revealed that the risks of soil PTEs for adults are acceptable, while the risks for children exceeded the limit values. The obtained results will help policymakers to obtain the sources of PTEs of tailing ponds intensive area. Moreover, it provides priorities for the governance of subsequent pollution sources and ecological restoration.

Development of a sensitive simultaneous analytical method for 26 targeted mycotoxins in coix seed and Monte Carlo simulation-based exposure risk assessment for local population

Coix seed, a versatile agricultural product, is known for its nutritional and functional components. However, the common contamination with mycotoxins represents a potential risk for human health. A sensitive analytical method was developed and validated to simultaneously determine 26 mycotoxins, including regulated and emerging, using stable-isotope-dilution-assay and LC-MS/MS. The study found co-contamination in 100% of samples from Southeast China, with 8-15 different mycotoxins for each and a total of 20 for all. Probabilistic risk assessments indicated long-term health concerns, with Aflatoxin B1, ochratoxin A, and zearalenone being priority for risk control. Overall, this study appears to be the first to develop a rapid and robust analytical method of 26 mycotoxins and to conduct Monte Carlo simulation-based chronic risk assessments for 12 individual mycotoxins detected in coix seed, which would be of significance for risk communication as well as for regulatory authority in devising effective strategies to minimize exposure health risk.

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.

Incorporating environmental capacity considerations to prioritize control factors for the management of heavy metals in soil

Heavy metals (HMs) pollution threatens food security and human health. While previous studies have evaluated source-oriented health risk assessments, a comprehensive integration of environmental capacity risk assessments with pollution source analysis to prioritize control factors for soil contamination is still lacking. Herein, we collected 837 surface soil samples from agricultural land in the Nansha District of China in 2019. We developed an improved integrated assessment model to analyze the pollution sources, health risks, and environmental capacities of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn. The model graded pollution source impact on environmental capacity risk to prioritize control measures for soil HMs. All HMs except Pb exceeded background values and were sourced primarily from natural, transportation, and industrial activities (31.26%). Approximately 98.92% (children), 97.87% (adult females), and 97.41% (adult males) of carcinogenic values exceeded the acceptable threshold of 1E-6. HM pollution was classified as medium capacity (3.41 kg/hm2) with mild risk (PI = 0.52). Mixed sources of natural backgrounds, transportation, and industrial sources were identified as priority sources, and As a priority element. These findings will help prioritize control factors for soil HMs and direct resources to the most critical pollutants and sources of contamination, particularly when resources are limited.

Exposure risk to rural Residents: Insights into particulate and gas phase pesticides in the Indoor-Outdoor nexus

Rural residents are exposed to both particulate and gaseous pesticides in the indoor-outdoor nexus in their daily routine. However, previous personal exposure assessment mostly focuses on single aspects of the exposure, such as indoor or gaseous exposure, leading to severe cognition bias to evaluate the exposure risks. In this study, residential dust and silicone wristbands (including stationary and personal wearing ones) were used to screen pesticides in different phases and unfold the hidden characteristics of personal exposure via indoor-outdoor nexus in intensive agricultural area. Mento-Carlo Simulation was performed to assess the probabilistic exposure risk by transforming adsorbed pesticides from wristbands into air concentration, which explores a new approach to integrate particulate (dust) and gaseous (silicone wristbands) pesticide exposures in indoor and outdoor environment. The results showed that particulate pesticides were more concentrated in indoor, whereas significantly higher concentrations were detected in stationary outdoor wristbands (p < 0.05). Carbendazim and chlorpyrifos were the most frequently detected pesticides in dust and stationary wristbands. Higher pesticide concentration was found in personal wristbands worn by farmers, with the maximum value of 2048 ng g-1 for difenoconazole. Based on the probabilistic risk assessment, around 7.1 % of farmers and 2.6 % of bystanders in local populations were potentially suffering from chronic health issues. One third of pesticide exposures originated mainly from occupational sources while the rest derived from remoting dissipation. Unexpectedly, 43 % of bystanders suffered the same levels of exposure as farmers under the co-existence of occupational and non-occupational exposures. Differed compositions of pesticides were found between environmental samples and personal pesticide exposure patterns, highlighting the need for holistic personal exposure measurements.

Distribution and transport of contaminants in soil through mining processes and its environmental impact and health hazard assessment: A review of the prospective solutions

Environmental regulations were concerned with support in reaction to the enormous ecological harm caused by mining in the past. Because mining, dumping, and tailings can generate waste and radioactive consequences, society must develop methods for successfully treating mining waste from mine dumps, tailings, and abandoned mines. Strict policies associated with environmental regulations to avoid the possible dangers caused by garbage and radioactivity. Several characteristics, including background contamination from natural sources related to mineral deposits, contamination from industrial activities in three-dimensional subsurface space, a problem with long-term remediation following mine closure, a problem with secondary contaminated areas near mine sites, land use conflicts, and abandoned mines, distinguish it. Reusing and recycling mine waste occasionally results in cost-effective advantages in the mining sector by offsetting natural resource requirements and reducing the volume of garbage materials. These benefits stem from recycling and reusing mining waste, which can lower the amount of garbage that must be managed. This review focuses on realistic strategies for anticipating mining exploration control and attempts to examine those methods in-depth. Management strategies for limiting the environmental impact of mining dumps, stockpiles, and tailings were discussed. The environmental assessment was also mentioned to carry out specific control and take preventive actions.

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.

Prioritization of control factors for heavy metals in groundwater based on a source-oriented health risk assessment model

Heavy metals (HMs) in groundwater seriously threaten ecological safety and human health. To facilitate the effective management of groundwater contamination, priority control factors of HMs in groundwater need to be categorized. A total of 86 groundwater samples were collected from the Huangpi district of Wuhan city, China, during the dry and wet seasons. To determine priority control factors, a source-oriented health risk assessment model was applied to compare the pollution sources and health risks of seven HMs (Cu, Pb, Zn, Cr, Ni, As, and Fe). The results showed that the groundwater had higher As and Fe contents. The sources of HM pollution during the wet period were mainly industrial and agricultural activities and natural sources. During the dry period, origins were more complex due to the addition of domestic discharges, such as sewage wastewater. Industrial activities (74.10% during the wet period), agricultural activities (53.84% during the dry period), and As were identified as the priority control factors for groundwater HMs. The results provide valuable insights for policymakers to coordinate targeted management of HM pollution in groundwater and reduce the cost of HM pollution mitigation.

Spatial response relationship between mining and industrial activities and eco-environmental risks in mineral resource-based areas

Mining and industrial activities in mineral resource-based areas are important sources of potentially toxic elements (PTEs) in the soil, which lead to spatial heterogeneity in regional eco-environmental risks. In this study, we analysed the spatial response relationship between mining and industrial activities and eco-environmental risks using Anselin local Moran's I index and bivariate local Moran's I index. The results showed that the proportions of moderate, moderate to strong, and strong pollution of PTEs in the study area reached 30.9%. The high clusters of PTEs ranged from 5.4 to 13.6%, and were mainly distributed around cities. The influence of different types of metal mines on eco-environmental risks was nonferrous metal mines > precious metal mines > ferrous metal mines. In turn, that of different pollution enterprises was manufacturing industry > other industries > power and thermal industries. Our research demonstrates that there was a significant spatial response relationship between densities of mines and enterprises and eco-environmental risk level. High-density metal mines (5.3/100 km2) and high-density pollution enterprises (10.3/100 km2) resulted in the local high risk. Consequently, this study provides a basis for regional eco-environmental risk management of mineral resource-based areas. With the gradual depletion of mineral resources, high-density pollution enterprise area should be paid more attention to, which would pose a threat not only to the environment but also to population health.

Source-specific risk judgement and environmental impact of potentially toxic elements in fine road dust from an integrated industrial city, North China

The contamination of potentially toxic elements (PTEs) in road dust of large industrial cities is extremely serious. Determining the priority risk control factors of PTE contamination in road dust is critical to enhance the environmental quality of such cities and mitigate the risk of PTE pollution. The Monte Carlo simulation (MCS) method and geographical models were employed to assess the probabilistic pollution levels and eco-health risks of PTEs originating from different sources in fine road dust (FRD) of large industrial cities, and to identify key factors affecting the spatial variability of priority control sources and target PTEs. It was observed that in FRD of Shijiazhuang, a typical large industrial city in China, more than 97% of the samples had an INI > 1 (INI_mean = 1.8), indicating moderately contaminated with PTEs. The eco-risk was at least considerable (NCRI >160) with more than 98% of the samples, mainly caused by Hg (E_{i (mean)} = 367.3). The coal-related industrial source (NCRI_(mean) = 235.1) contributed 70.9% to the overall eco-risk (NCRI_(mean) = 295.5) of source-oriented risks. The non-carcinogenic risk of children and adults are of less importance, but the carcinogenic risk deserves attention. The coal-related industry is a priority control pollution source for human health protection, with As corresponding to the target PTE. The major factors affecting the spatial changes of target PTEs (Hg and As) and coal-related industrial sources were plant distribution, population density, and gross domestic product. The hot spots of coal-related industrial sources in different regions were strongly interfered by various human activities. Our results illustrate spatial changes and key-influencing factors of priority source and target PTEs in Shijiazhuang FRD, which are helpful for environmental protection and control of environmental risks by PTEs.

Spatiotemporal characteristics and dynamic risk assessment of a multi-solvents abandoned pesticide-contaminated site with a long history, in China

With the development of the economy and the adjustment of urban planning and layout, abandoned pesticide sites are widely distributed in major and medium cities in China. Groundwater pollution of a large number of abandoned pesticide-contaminated sites has caused great potential risks to human health. Up to now, few relevant studies concerned the spatiotemporal variation of risks exposure to multi-pollutants in groundwater using probabilistic methods. In our study, the spatiotemporal characteristics of organics contamination and corresponding health risks in the groundwater of a closed pesticide site were systematically assessed. A total of 152 pollutants were targeted for monitoring over a time span up to five years (i.e., June 2016-June 2020). BTEX, phenols, chlorinated aliphatic hydrocarbons, and chlorinated aromatic hydrocarbons were the main contaminants. The metadata was subjected to health risk assessments using the deterministic and probabilistic methods for four age groups, and the results showed that the risks were highly unacceptable. Both methods showed that children (0-5 years old) and adults (19-70 years old) were the age groups with the highest carcinogenic and non-carcinogenic risks, respectively. Compared with inhalation and dermal contact, oral ingestion was the predominant exposure pathway that contributed 98.41%-99.69% of overall health risks. Spatiotemporal analysis further revealed that the overall risks first increased then decreased within five years. The risk contributions of different pollutants were also found to vary substantially with time, indicating that dynamic risk assessment is necessary. Compared with the probabilistic method, the deterministic approach relatively overestimated the true risks of OPs. The results provide a scientific basis and practical experience for scientific management and governance of abandoned pesticide sites.

Effect of Coal Mining on Soil Microorganisms from Stipa krylovii Rhizosphere in Typical Grassland

The environmental changes caused by coal mining activities caused disturbances to the plant, soil, and microbial health in the mining area. Arbuscular mycorrhizal fungi (AMF) play an important role in the ecological restoration of mining areas. However, it is less understood how soil fungal communities with multiple functional groups respond to coal mining, and the quantitative impact and risk of mining disturbance. Therefore, in this study, the effect of coal mining on soil microorganisms' composition and diversity were analyzed near the edge of an opencast coal-mine dump in the Shengli mining area, Xilingol League, Inner Mongolia. The response strategy of soil fungi to coal mining and the stability of arbuscular mycorrhizal fungi (AMF) in the soil fungal community were determined. Our results showed that coal mining affected AMF and soil fungi in areas within 900 m from the coal mine. The abundance of endophytes increased with the distance between sampling sites and the mine dump, whereas the abundance of saprotroph decreased with the distance between sampling sites and the mine dump. Saprotroph was the dominant functional flora near the mining area. The nodes percentage of Septoglomus and Claroideoglomus and AMF phylogenetic diversity near the mining area were highest. AMF responded to the mining disturbance via the variety and evolution strategy of flora. Furthermore, AMF and soil fungal communities were significantly correlated with edaphic properties and parameters. Soil available phosphorus (AP) was the main influencer of soil AMF and fungal communities. These findings evaluated the risk range of coal mining on AMF and soil fungal communities and elucidated the microbial response strategy to mining disturbance.

Pollution Profiles, Source Identification and Health Risk Assessment of Heavy Metals in Soil near a Non-Ferrous Metal Smelting Plant

Heavy metal pollution related to non-ferrous metal smelting may pose a significant threat to human health. This study analyzed 58 surface soils collected from a representative non-ferrous metal smelting area to screen potentially hazardous heavy metals and evaluate their health risk in the studied area. The findings demonstrated that human activity had contributed to the pollution degrees of Cu, Cd, As, Zn, and Pb in the surrounding area of a non-ferrous metal smelting plant (NMSP). Cu, Cd, As, Zn, Pb, Ni, and Co pollution within the NMSP was serious. Combining the spatial distribution and Spearman correlations with principal component analysis (PCA), the primary sources of Cd, As, Pb, and Zn in surrounding areas were related to non-ferrous metal smelting and transportation activities. High non-cancer (THI = 4.76) and cancer risks (TCR = 2.99 × 10^-4) were found for adults in the NMSP. Moreover, heavy metals in the surrounding areas posed a potential cancer risk to children (TCR = 3.62 × 10^-6) and adults (TCR = 1.27 × 10^-5). The significant contributions of As, Pb, and Cd to health risks requires special attention. The construction of a heavy metal pollution management system will benefit from the current study for the non-ferrous metal smelting industry.