Determination of priority control factors for the management of soil trace metal(loid)s based on source-oriented health risk assessment

Evaluation of the potentially toxic elements and radionuclides in the soil sample of Novaya Zemlya in the Arctic Circle

The study presented here elucidate the concentrations of radionuclides and potentially toxic elements in the soil samples around the Novaya Zemlya in the Russian Arctic zone, determined using HPGe gamma spectrometry, inductively coupled plasma optical emission spectrometry and direct mercury analyzer. The average detected concentrations for 226Ra, 232Th, 40K, 235U and 137Cs were 36.40, 46.06, 768, 2.06 and 4.71 Bq/kg, respectively. At many sampling sites, the concentrations of potentially toxic elements (Zn, Cu, Pb, Cd, Ni, and Cr) were higher than the natural levels. Positive Matrix Factorization analysis revealed the contribution of oil dumps (32%), natural sources (16%), bird colonies (32%) and atmospheric deposition (20%) for elevated elements content. In the case of radionuclides, the natural occurring contamination (38%) was primary source followed by dumped material (32%) and bird colonies (30%). The radiological risk from radionuclides was relatively high, yet still under permissible levels. For potentially toxic elements, Fe was predominant non-carcinogenic pollutant and Ni emerged as major carcinogenic contaminant. Keeping in view the high content of some elements, future studies are required to keep the human and ecological risk low, and to establish scientific grounds for the contribution of settled bird species. The findings of the study advance the present knowledge about the contamination of the study area and lays the path for further effort.

Deciphering the pollution risks, sources and their links of heavy metals in soils

Heavy metals in soils pose serious ecological and health risks. To make efficient strategies for mitigating the underlying hazards, it is critical to reveal the pollution sources and their links with the risks. Researchers have investigated source identification and risk evaluation of heavy metals in soils, yet few have systematically deciphered the source-sink relationship of soil metals and the links between source apportionment and risk assessment. In the study, an integrated technological framework has been proposed to address the gaps, and applied to characterize the pollution risks, sources and their links of soil metals in a typical coal resource city in China. The assessment using geochemical tool and ecological risk index shows the soils in study area are polluted by Cd, Hg, Cr, As and Pb in varied degrees, and particularly, Cd and Hg present significant ecological risk. Two advanced receptor models (multivariate curve resolution-weighted alternating least-squares and multilinear engine 2) are comparatively applied for apportioning the potential sources of soil metals, and the results suggest the two models have identified similar sources (r2 > 0.90), including agricultural activities, atmospheric depositions and industrial discharges with contributions of 35.5 %-38.3 %, 30.3 %-35.1 %, and 26.6 %-34.1 %, respectively. Then, apportionment results of the two models are jointly employed for evaluating the source-specific health risks of metals in the environment using a probabilistic risk assessment model. The risk levels within the area are overall acceptable or tolerable, and relatively, the industrial discharges present higher contribution on the non-carcinogenic and carcinogenic risks of soil metals to public. Findings will help the managers to design targeted policies for reducing the risks of soil metals, and the framework proposed provides a useful guideline to better understand the source-risk relationship of soil metals in other environments worldwide.

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

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

A comprehensive approach for quantifying source-specific ecological and health risks of potentially toxic elements in agricultural soil

Given the pollution prevalence of potentially hazardous elements (PTEs) in agricultural soils worldwide, it is crucial to establish a comprehensive approach to accurately assess soil contamination, and quantitatively allocate sources and source-specific risks. In the study, soil contamination was assessed through environmental capacity based on the local geochemical baseline established using PTE contents of the subsoil. The sources of PTEs were quantified through positive matrix factorization (PMF) and GIS mapping. Ecological risk (ER) and human health risk (HHR) models based on PMF were used to evaluate source-specific ER and HHR. Taking Jieyang City as an example, obvious contamination of As, Pb, Cd, Zn and Hg was observed in agricultural soils, and 94.40% of sites had high-to-medium capacity for local PTE contamination. Four sources were apportioned including agricultural activities (17.36%), industrial activities (20.49%), natural sources (34.60%) and traffic emissions (27.55%). The study area was at moderate ER level (121.21) with industrial activities contributing the most (41.26%). The carcinogenic risks (3.21E-05 for children and 1.42E-05 for adults) were within the tolerable range, and non-carcinogenic risks (7.08E-01 for children and 7.70E-02 for adults) were not significant. Agricultural activities were the largest source to the carcinogenic (47.17% for children and 46.31% for adults) and non carcinogenic risks (53.55% for children and 53.03% for adults). Therefore, industrial activities and agricultural activities were the priority control sources to reduce ecological risk and protect human health, respectively.

Determining priority control factors for heavy metal management in urban road dust based on source-oriented probabilistic ecological-health risk assessment: A study in Xi'an during peak pollution season

Urban road dust (URD) is essential for transporting heavy metals (HMs), which can be a major danger to both the environment and human health. Moreover, URD has the potential to be carried into bodies of water, leading to contamination of the aquatic ecosystem. A study was conducted in Xi'an, a city in northwestern China known for high air pollution levels, during January 2024 - a period characterized by peak pollution due to frequent low wind speeds and temperature inversions. The research investigated the presence of 10 types of HMs (Cu, Zn, Cd, Cr, Pb, As, Ni, Hg, Co, and Mn) in URD. Findings revealed elevated levels of Cu, Zn, Cd, Cr, Pb, As, and Hg in URD compared to background levels. Hg showed the most significant contamination (moderate to heavy), followed by moderate contamination of Cd, and lower levels of As, Zn, and Cu. The main sources of HMs were traffic (58.2%), mixed natural and industrial (30.3%), and industrial (11.5%). The ecological risk in the area was deemed to be very high, primarily because of Hg and Cd. Based on probabilistic health risk assessments, it was determined that non-carcinogenic risks were deemed acceptable for all groups. Nevertheless, the possibility of carcinogenic risks should not be disregarded. Strategies for controlling ecological-health risks prioritize mixed natural and industrial sources, with a focus on Hg, Cd, and As in URD. The results offer a foundation for policymakers to create specific control strategies.

p-Phenylenediamines and p-phenylenediamine quinone derivatives in rubber consumer products and typical urban dust: Sources, transformation profiles, and health risks

N,N'-Substituted p-phenylenediamines (PPDs) are widely used as antioxidants in the rubber industry and are released into the environment in large quantities during the production and use of rubber products. We quantified PPDs and PPD quinone derivatives (PPD-Qs) in rubber consumer products, including car tires, rubber belts, rubber gloves, rubber cables, and rubber hoses, to obtain information on the degree of weathering over time during their use. Additionally, we investigated the occurrences and sources of PPDs and PPD-Qs in dust samples collected from four typical urban environments (roads, parking lots, automotive repair shops, and residences). The detected compounds included the highly toxic N-(1,3-dimethylbutyl)-N'-phenyl-1,4-phenylenediamine quinone, which can cause acute mortality of coho salmon (Oncorhynchus kisutch). Concentrations of PPDs in the automotive repair shops reached 56.0 μg/g, and were much higher than in the other environments, while the residential samples had the lowest contaminant concentrations. In road and residential samples, N,N'-di-2-naphthyl-p-phenylenediamine accounted for 17 %-30 % of the PPDs, and may have originated from different sources. We preliminarily identified 32 transformation products, and 11 of these were N,N'-di-2-naphthyl-p-phenylenediamine transformation products. The average daily intakes of PPDs and PPD-Qs were calculated to assess the health risks of dust exposure in each environment. Workers had high total intakes of PPD [60.3 ng/(kg day)] and PPD-Qs [20.1 ng/(kg day)], and were at some risk of occupational exposure. These results improve our understanding of the environmental occurrences, sources, transformation, and health risks of PPDs and PPD-Qs.

Determination of soil environmental criteria for high-risk trace metals in urban park soils using improved CLEA model

The trace metals (TMs) accumulated in urban park soils can pose potential threats to human health, making the management of soil quality based on health risks critically important. Based on the human health risk assessment (HHRA) model coupled with Monte Carlo Simulation, this study improved the contaminated land exposure assessment (CLEA) model. Combined with local parameters, the Soil Environmental Criteria (SEC) for high-risk trace metals (TMs) in urban park soils were calculated. Results indicated that all the mean TCR (Total carcinogenic risk) values of seven TMs exceeded the risk threshold of 1E-06, suggesting a higher likelihood of carcinogenic risks for all populations. As and Cr presented the highest potential carcinogenic risks, and were identified as high-risk TMs in the study area. The traditional CLEA model was enhanced by incorporating region-specific data, optimizing exposure parameter calculations, and addressing parameter sensitivity and uncertainty. Using the improved CLEA model, the SEC values for high-risk TMs were calculated, revealing that the SEC values gradually increased from ages 1 to 18, while significantly decreased for individuals over 80 years old. This study effectively addresses issues of parameter uncertainty and sensitivity in the CLEA model, offering new insights for the development of soil environmental quality standards.

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-specific probabilistic health risk assessment of dust PAHs in urban parks based on positive matrix factorization and Monte Carlo simulation

Understanding the health risks of polycyclic aromatic hydrocarbons (PAHs) in dust from city parks and prioritizing sources for control are essential for public health and pollution management. The combination of Source-specific and Monte Carlo not only reduces management costs, but also improves the accuracy of assessments. To evaluate the sources of PAHs in urban park dust and the possible health risks caused by different sources, dust samples from 13 popular parks in Kaifeng City were analyzed for PAHs using gas chromatograph-mass spectrometer (GC-MS). The results showed that the surface dust PAH content in the study area ranged from 332.34 µg·kg-1 to 7823.03 µg·kg-1, with a mean value of 1756.59 µg·kg-1. Nemerow Composite Pollution Index in the study area ranged from 0.32 to 14.41, with a mean of 2.24, indicating that the overall pollution warrants attention. Four pollution sources were identified using the positive matrix factorization (PMF) model: transportation source, transportation-coal and biomass combustion source, coke oven emission source, and petroleum source, with contributions of 33.74%, 25.59%, 22.14%, and 18.54%, respectively. The Monte Carlo cancer risk simulation results indicated that park dust PAHs pose a potential cancer risk to all three populations (children, adult male and adult female). Additionally, the cancer risk for children was generally higher than that for adult males and females, with transportation sources being the main contributor to the carcinogenic risk. Lastly, sensitivity analyses results showed that the toxic equivalent concentration (CS) is the parameter contributing the most to carcinogenic risk, followed by Exposure duration (ED).

Optimizing health risk assessment for soil trace metals under low-precision sampling conditions: A case study of agricultural soil

Cost limitations often lead to the adoption of lower precision grids for soil sampling in large-scale areas, potentially causing deviations in the observed trace metal (TM) concentrations from their true values. Therefore, in this study, an enhanced Health Risk Assessment (HRA) model was developed by combining Monte Carlo simulation (MCS) and Empirical Bayesian kriging (EBK), aiming to improve the accuracy of health risk assessment under low-precision sampling conditions. The results showed that the increased sampling scale led to an overestimation of the non-carcinogenic risk for children, resulting in potential risks (the maximum Hazard index value was 1.08 and 1.64 at the 500 and 1000 m sampling scales, respectively). EBK model was suitable for predicting soil TM concentrations at large sampling scale, and the predicted concentrations were closer to the actual value. Furthermore, we found that the improved HRA model by combining EBK and MCS effectively reduced the possibility of over- or under-estimation of risk levels due to the increasing sampling size, and enhanced the accuracy and robustness of risk assessment. This study provides an important methodology support for health risk assessment of soil TMs under data limitation.

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.

Sources and health risks of heavy metals in kindergarten dust: The role of particle size

Particle size effects significantly impact the concentration and toxicity of heavy metals (HMs) in dust. Nevertheless, the differences in concentrations, sources, and risks of HMs in dust with different particle sizes are unclear. Therefore, guided by the definition of atmospheric particulate matter, dust samples with particle sizes under 1000 μm (DT1000), 100 μm (DT100), and 63 μm (DT63) from Beijing kindergartens were collected. The concentrations of HMs (e.g., Cd, Pb, Zn, Ni, Cr, Ba, Cu, V, Mn, Co, and Ti) in dust samples with different particle sizes were measured. Besides, the differences in HM concentrations, contamination levels, sources, and source-oriented health risks in dust samples of different particle sizes were systematically explored. The results show that the concentrations of Mn, V, Zn, and Cd gradually increase with decreasing dust particle sizes, the concentrations of Ba and Pb show a decreasing trend, and the concentrations of Cr, Cu, Ni, and Co display an increasing and then decreasing trend. The degree of contamination of HMs in dust of different particle sizes varies, with Cd being the most dominant contaminant. Compared with DT1000 and DT63, DT100 is the most polluted. In addition, the sources of HMs in DT1000, DT100, and DT63 become more single with decreasing particle size, which may be mainly due to the particle-size effect inducing the redistribution of HMs in different sources. Notably, the potential health risk is higher in DT100 than in DT1000 and DT63. The highest contribution of industrial sources to the health risk is found in DT100, which is mainly caused by highly toxic chromium (Cr). This work emphasizes the importance of considering particle size in risk assessment and pollution control, which can provide a theoretical basis for precise management of HMs pollution in dust.

Development of an integrated framework for dissecting source-oriented ecological and health risks of heavy metals in soils

Heavy metals (HMs) in soils pose significant risks on ecosystem and human health. To design targeted regulatory measures for mitigating and controlling the risk, it is necessary to accurately identify the pollution sources and environmental risks of soil HMs, as well as to reveal the linkages between them. To date, yet systematic investigation aimed at deciphering the links between source apportionment of soil HMs and their associated environmental risks is still lacking. To fill the gap, an integrated framework has been developed in this study and applied for dissecting the source-sink relationship and source-oriented ecological and health risks of soil HMs in Shanxi, a province with rich coal resource, in which long-term coal mining activities in history has resulted in soil HMs pollution and unavoidably posed environmental risks. Two advanced receptor models, multivariate curve resolution alternating least squares based on maximum likelihood principal component analysis (MCR-ALS/MLPCA) and multilinear engine 2 (ME2), have been employed for apportioning the potential sources, and their apportionment results are jointly incorporated into a modified ecological risk index and a probabilistic health risk assessment model for identifying the source-oriented ecological and health risks posed by soil metals. The results show that the soils in study area have been polluted by HMs (i.e., Cd, Cr, Hg and As) to varying degrees. Industrial activities (35%-35.8%), agricultural activities (11.1%-20.5%), atmospheric deposition (10.5%-13%) and mix source (31.5%-42.6%) are apportioned as the main contributors of soil HMs in the area. The source-oriented ecological risk assessment suggests Hg has presented significant ecological risk and largely contributed by the sources from atmospheric deposition and industrial activities. The source-oriented health risk assessment shows the non-carcinogenic hazard level and carcinogenic risk posed by soil HMs in the study area are acceptable. Relatively, industrial activities and mix source have contributed more on the health risks.

Determination of contamination, source, and risk of potentially toxic metals in fine road dust in a karst region of Southwest China

Understanding the pollution situation of potentially toxic metals (PTMs) in fine road dust (FRD) in emerging industrialized cities and identifying priority control factors is crucial for urban environmental management, resident health protection, and pollution control. This study conducted a comprehensive investigation on PTMs pollution in FRD in Zunyi, a representative emerging industrialized city in the karst region of southwestern China. The average contents of Ni, Cr, Mn, Cu, Zn, Ba, Pb, V, and Co in the FRD were 43.2, 127.0, 1232.1, 134.4, 506.6, 597.8, 76.1, 86.8, and 16.2 mg kg-1, respectively, which were obviously higher than the corresponding background levels of the local soil except for V and Co. The comprehensive pollution level of the determined PTMs in the FRD was very high, primarily caused by Zn and Cu. The sources of PTMs in Zunyi FRD were traffic, industrial, construction, and natural sources, accounting for 38.0, 23.7, 21.9, and 16.4% of the total PTMs content, respectively. The PTMs in Zunyi FRD exhibited a low to moderate overall ecological risk level, mainly contributed by Cu and traffic source. The cancer risks of PTMs in Zunyi FRD were high for all populations. The non-carcinogenic risk of PTMs in Zunyi FRD was acceptable for adults, but cannot be ignored for children. According to the source-specific probabilistic health risk estimation results, the priority control source is industrial source and the priority control PTM is Cr. Local governments need to give more attention to the carcinogenic risks and health hazards posed by PTMs in the FRD.

Source-oriented health risk assessment of groundwater nitrate by using EMMTE coupled with HHRA model

Conventional concentration-oriented approaches for nitrate risk diagnosis only provide overall risk levels without identifying risk values of individual sources or sources accountable for potential health risks. Therefore, a hybrid model combining the end-member mixing model tool on Excel™ (EMMTE) with human health risk assessment (HHRA) was developed to assess the source-oriented health risks for groundwater nitrate, particularly in the Poyang Lake Plain (PLP) region. The results indicated that the EMMTE and the Bayesian stable isotope mixing model (MixSIAR) exhibited remarkable consistency in source apportionment of groundwater nitrate. The source contribution of groundwater nitrate in PLP was related to land use types, hydrogeological conditions, and soil properties. Notably, manure and sewage sources, contributing up to 53.4 %, represented the largest nitrate pollution sources, with a significant contribution of soil nitrogen and nitrogen fertilizers. The non-carcinogenic risk for four potential sources was below the acceptable threshold of 1. Given the factors including rainfall dilution and economic development, attention should be directed towards mitigating the health risks posed by manure and sewage. This study can verify the efficacy of EMMTE in source apportionment and offer valuable insights for decision-makers to regulate the largest sources of nitrate contamination and enhance groundwater management efficiency.

Exploring the environmental risks and seasonal variations of potentially toxic elements (PTEs) in fine road dust in resource-based cities based on Monte Carlo simulation, geo-detector and random forest model

The environmental pollution caused by mineral exploitation and energy consumption poses a serious threat to ecological security and human health, particularly in resource-based cities. To address this issue, a comprehensive investigation was conducted on potentially toxic elements (PTEs) in road dust from different seasons to assess the environmental risks and influencing factors faced by Datong City. Multivariate statistical analysis and absolute principal component score were employed for source identification and quantitative allocation. The geo-accumulation index and improved Nemerow index were utilized to evaluate the pollution levels of PTEs. Monte Carlo simulation was employed to assess the ecological-health risks associated with PTEs content and source orientation. Furthermore, geo-detector and random forest analysis were conducted to examine the key environmental variables and driving factors contributing to the spatiotemporal variation in PTEs content. In all PTEs, Cd, Hg, and Zn exhibited higher levels of content, with an average content/background value of 3.65 to 4.91, 2.53 to 3.34, and 2.15 to 2.89 times, respectively. Seasonal disparities were evident in PTEs contents, with average levels generally showing a pattern of spring (winter) > summer (autumn). PTEs in fine road dust (FRD) were primarily influenced by traffic, natural factors, coal-related industrial activities, and metallurgical activities, contributing 14.9-33.9 %, 41.4-47.5 %, 4.4-8.3 %, and 14.2-29.4 % to the total contents, respectively. The overall pollution and ecological risk of PTEs were categorized as moderate and high, respectively, with the winter season exhibiting the most severe conditions, primarily driven by Hg emissions from coal-related industries. Non-carcinogenic risk of PTEs for adults was within the safe limit, yet children still faced a probability of 4.1 %-16.4 % of unacceptable risks, particularly in summer. Carcinogenic risks were evident across all demographics, with children at the highest risk, mainly due to Cr and smelting industrial sources. Geo-detector and random forest model indicated that spatial disparities in prioritized control elements (Cr and Hg) were primarily influenced by particulate matter (PM10) and anthropogenic activities (industrial and socio-economic factors); variations in particulate matter (PM10 and PM2.5) and meteorological factors (wind speed and precipitation) were the primary controllers of seasonal disparities of Cr and Hg.

Distribution, risk evaluation, and source allocation of cesium and strontium in surface soil in a mining city

Radioactive nuclides cesium (Cs) and strontium (Sr) possess long half-lives, with 135Cs at approximately 2.3 million years and 87Sr at about 49 billion years. Their persistent accumulation can result in long-lasting radioactive contamination of soil ecosystems. This study employed geo-accumulation index (Igeo), pollution load index (PLI), potential ecological risk index (PEPI), health risk assessment model (HRA), and Monte Carlo simulation to evaluate the pollution and health risks of Cs and Sr in the surface soil of different functional areas in a typical mining city in China. Positive matrix factorization (PMF) model was used to elucidate the potential sources of Cs and Sr and the respective contribution rates of natural and anthropogenic sources. The findings indicate that soils in the mining area exhibited significantly higher levels of Cs and Sr pollution compared to smelting factory area, agricultural area, and urban residential area. Strontium did not pose a potential ecological risk in any studied functional area. The non-carcinogenic health risk of Sr to the human body in the study area was relatively low. Because of the lack of parameters for Cs, the potential ecological and human health risks of Cs was not calculated. The primary source of Cs in the soil was identified as the parent material from which the soil developed, while Sr mainly originated from associated contamination caused by mining activities. This research provides data for the control of Cs and Sr pollution in the surface soil of mining city.

Health risk assessment of soil heavy metals in a typical mining town in north China based on Monte Carlo simulation coupled with Positive matrix factorization model

The accumulation of heavy metals (HMs) in soil caused by mineral resource exploitation and its ancillary industrial processes poses a threat to ecology and public health. Effective risk control measures require a quantification of the impacts and contributions to health risks from individual sources of soil HMs. Based on high-density sampling, soil contamination risk indexes, positive matrix factorization (PMF) model, Monte Carlo simulation and human health risk analysis model were applied to investigate the risk of HMs in a typical mining town in North China. The results showed that As was the most dominant soil pollutant factor, Cd and Hg were the most dominant soil ecological risk factors, and Cr and Ni were the most dominant health risk factors in the study area. Overall, both pollution and ecological risks were at low levels, while there were still some higher hazard areas located in the central and south-central part of the region. According to the probabilistic health risk assessment (HRA), children suffered greater health risks than adults, with 21.63% of non-carcinogenic risks and 53.24% of carcinogenic risks exceeding the prescribed thresholds (HI > 1 and TCR>1E-4). The PMF model identified five potential sources: fuel combustion (FC), processing of building materials with limestone as raw materials (PBML), industry source (IS), iron ore mining combined with garbage (IOG), and agriculture source (AS). PBML is the primary source of soil HM contamination, as well as the major anthropogenic source of carcinogenic risk for all populations. Agricultural inputs associated with As are the major source of non-carcinogenic risk. This study offers a good example of probabilistic HRA using specific sources, which can provide a valuable reference for strategy establishment of pollution remediation and risk prevention and control.

A Monte Carlo simulation-based health risk assessment of heavy metals in soils of the tropical region in southern China

The disturbance of ecological stability may take place in tropical regions due to the elevated biomass density resulting from heavy metal and other contaminant pollution. In this study, 62 valid soil samples were collected from Sanya. Source analysis of heavy metals in the area was carried out using absolute principal component-multiple linear regression receptor modelling (APCS-MLR); the comprehensive ecological risk of the study area was assessed based on pollution sources; the Monte-Carlo model was used to accurately predict the health risk of pollution sources in the study area. The results showed that: The average contents of soil heavy metals Cu, Ni and Cd in Sanya were 5.53, 6.56 and 11.66 times higher than the background values of heavy metals. The results of soil geo-accumulation index (Igeo) showed that Cr, Mo, Mn and Zn were unpolluted to moderately polluted, Cu and Ni were moderately polluted, and Cd was moderately polluted to strongly polluted. The main sources of heavy metal pollution were natural sources (57.99%), agricultural sources (38.44%) and traffic sources (3.57%). Natural and agricultural sources were jointly identified as priority control pollution sources and Cd was the priority control pollution element for soil ecological risk. Heavy metal content in Sanya did not pose a non-carcinogenic risk to the population, but there was a carcinogenic risk to children. The element Zn had a high carcinogenic risk to children, and was a priority controlling pollutant element for the risk of human health, with agricultural sources as the priority controlling pollutant source.

Ecological risk assessment of heavy metal(loid)s in riverine sediments along the East China Sea: A large-scale integrated analysis

This study comprehensively assesses spatial distribution, pollution levels, and potential sources of heavy metal(loid)s in surface sediments across multiple river systems along the coastal area of the East China Sea. Copper in Qiantang River and Xiangshan Bay showed higher concentations and exceeded the threshold effect value, while the higher content of Lead was mainly found in the Saijiang River, Oujiang River, and Minjiang River. Heavy metal(loid)s in the alluvium of Qiantang River, Jiaojiang River, and Yangtze River showed low to moderate pollution levels, with Cd posing the highest ecological risk, followed by Hg. Meanwhile, Qiantang River, Jiaojiang River, Yangtze River, and Oujiang River exhibited considerable to moderate ecological risks and low toxic risk. PMF model analysis results reveal that concentrations of Cr, Ni, and As were closely related with natural geogenic input (36.56 %), while industrial and traffic activities (48.77 %) were primary source of Cu, Pb, Zn, and Hg, and main source of Cd was agricultural emissions (14.67 %).

Controlling factors and sources-specific ecological risks associated with toxic metals in core sediments from cascade reservoirs in Southwest China

Toxic metals (TMs) in reservoir sediments pose significant risks to ecosystem security and human safety, yet their presence in the cascade reservoirs of the Lancang River remains understudied. This research examined TMs in core sediments from the Manwan (MW) and Dachaoshan (DCS) cascade reservoirs, aiming to elucidate contamination characteristics, controlling factors, and source-specific ecological risks. The study revealed that the concentrations of As, Cd, Cr, Cu, Hg, Ni, and Zn in the MW Reservoir (37.3, 0.54, 95.1, 44.0, 0.09, 44.8, and 135.7 mg/kg) were notably higher compared to the DCS Reservoir (14.6, 0.30, 82.6, 31.0, 0.08, 36.6, and 108.7 mg/kg). While both reservoirs demonstrated elevated contamination levels of Cd and Hg, the MW Reservoir also exhibited high levels of As, whereas the DCS Reservoir showed relatively high levels of Pb. Mining activities in upstream metal deposits significantly correlated Cd, Hg, and Zn in the MW Reservoir with sulfur. In both reservoir sediments, Cr and Ni displayed a greater affinity for iron oxides, while As, Cd, Cu, Hg, and Zn showed more affinity with manganese oxides. Ecological risk index (RI) values in half of the sediments from the MW Reservoir ranged from 300 to 600, denoting a significant ecological risk. Conversely, in the DCS Reservoir, 93.3 % of the sediments exhibited RI values between 150 and 300, signifying a moderate ecological risk. Source-oriented ecological risks highlighted the need for particular attention to Cd from anthropogenic sources in the MW Reservoir. These findings underscore the importance of implementing measures for TM contamination prevention and control, contributing to strategic planning for sustainable water resource management in the Lancang-Mekong River.

Vertical migration behavior simulation and prediction of Pb and Cd in co-contaminated soil around Pb-Zn smelting slag site

Heavy metal migration in soil poses a serious threat to the soil and groundwater. Understanding the migration pattern of heavy metals (HMs) under different factors could provide a more reasonable position for pollution evaluation and targetoriented treatment of soil heavy metal. In this study, the migration behavior of Pb and Cd in co-contaminated soil under different pH and ionic strength (NaCl concentration) was simulated using convective dispersion equation (CDE). We predicted the migration trends of Pb and Cd in soils after 5, 10, and 20 years via PHREEQC. The results showed that the migration time of Cd in the soil column experiment was about 60 days faster than that of Pb, and the migration trend was much steeper. The CDE was proved to describe the migration behavior of Pb and Cd (R2 > 0.75) in soil. The predicted results showed that Cd migrated to 15-20 cm of soil within 7 years and Pb stayed mainly in the top 0-6 cm of soil within 5 years as the duration of irrigation increased. Overall, our study is expected to provide new insight into the migration of heavy metal in soil ecosystems and guidance for reducing risk of heavy metal in the environment.

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.

Human health risks of heavy metal(loid)s mediated through crop ingestion in a coal mining area in Eastern China

The heavy metal(loid)s (HMs) in soils can be accumulated by crops grown, which is accompanied by crop ingestion into the human body and then causes harm to human health. Hence, the health risks posed by HMs in three crops for different populations were assessed using Health risk assessment (HRA) model coupled with Monte Carlo simulation. Results revealed that Zn had the highest concentration among three crops; while Ni was the main polluting element in maize and soybean, and As in rice. Non-carcinogenic risk for all populations through rice ingestion was at an "unacceptable" level, and teenagers suffered higher risk than adults and children. All populations through ingestion of three crops might suffer Carcinogenic risk, with the similar order of Total carcinogenic risk (TCR): TCRAdults > TCRTeenagers > TCRChildren. As and Ni were identified as priority control HMs in this study area due to their high contribution rates to health risks. According to the HRA results, the human health risk was associated with crop varieties, HM species, and age groups. Our findings suggest that only limiting the Maximum allowable intake rate is not sufficient to prevent health risks caused by crop HMs, thus more risk precautions are needed.

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.

Improving prediction of soil heavy metal(loid) concentration by developing a combined Co-kriging and geographically and temporally weighted regression (GTWR) model

The study of heavy metal(loid) (HM) contamination in soil using extensive data obtained from published literature is an economical and convenient method. However, the uneven distribution of these data in time and space limits their direct applicability. Therefore, based on the concentration data obtained from the published literature (2000-2020), we investigated the relationship between soil HM accumulation and various anthropogenic activities, developed a hybrid model to predict soil HM concentrations, and then evaluated their ecological risks. The results demonstrated that various anthropogenic activities were the main cause of soil HM accumulation using Geographically and temporally weighted regression (GTWR) model. The hybrid Co-kriging + GTWR model, which incorporates two of the most influential auxiliary variables, can improve the accuracy and reliability of predicting HM concentrations. The predicted concentrations of eight HMs all exceeded the background values for soil environment in China. The results of the ecological risk assessment revealed that five HMs accounted for more than 90% of the area at the "High risk" level (RQ ≥ 1), with the descending order of Ni (100%) = Cu (100%) > As (98.73%) > Zn (95.50%) > Pb (94.90%). This study provides a novel approach to environmental pollution research using the published data.

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.

Trophodynamics and potential health risk assessment of heavy metals in the mangrove food web in Yanpu Bay, China

Mangroves are the cradle of coastal water biodiversity and are susceptible to heavy metal pollution. However, the trophic transfer mechanism of heavy metals in the mangrove food web and the resulting human health risks are not fully understood. Heavy metal concentration (Cr, Ni, Cu, Zn, As, Cd, Pb, V, Co) and stable isotope ratios of carbon and nitrogen (δ13C and δ15N) were evaluated in sediments and particulate organic matter, litter, and aquatic organisms (plankton, arthropods, mollusks, omnivorous fish, and carnivorous fish) from the Yanpu Bay mangroves. The results revealed that heavy metals exhibited different trophic transfer patterns. As and Hg were efficiently biomagnified, with trophic magnification factors of 1.17 and 1.42, respectively; while Cr, Ni, Cu, Cd, Pb, V, and Co were efficiently biodiluted. Zn exhibited a trophic magnification factor > 1 and was not significantly correlated with δ15N (p > 0.05), suggesting no biomagnification or biodilution. The heavy metals in the important fishery species (omnivorous fish and carnivorous fish) were below the permissible limits, except for Zn in Ophichthus apicalis. The assessment of probabilistic health risks revealed that fish consumption in adults and children posed an acceptable risk (total target hazard quotient <1).

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.

Accelerated export and transportation of heavy metals in watersheds under high geological backgrounds

The geological background level of metals plays a major role in mineral distribution and watershed diffuse heavy metal (HM) pollution. In this study, field research and a distributed hydrological model were used to analyze the distribution, sources, and pollution risk of watershed HMs in sediments with high geological HM backgrounds. Study showed that the mineral distribution and landcover promoted the transport differences of watershed HMs from upstream to the estuary. And the main sources of Co, Ni, and V in the estuarine sediments were natural sources. Sources of Pb and Zn were dominated by anthropogenic sources, accounting for 76% and 64% of their respective totals. The overall ecological risk of anthropogenically sourced HMs was dominated by Pb (46.6%), while the contributions of Co and Ni were also relatively high, accounting for 35.70% and 33.40%. Moreover, redundancy analysis showed that HM variations in the sediments were most sensitive to soil erosion and mineralizing rock distribution. The spatial patterns of watershed HMs from natural sources were significantly influenced by P loading, precipitation, and forest distribution. This combination of experiments and model improves the understanding of watershed HM variation and provides a new perspective for formulating effective watershed HM management strategies.

Remarkable contamination characteristics, potential hazards and source apportionment of heavy metals in surface dust of kindergartens in a northern megacity of China

It is essential to understand the impact of heavy metals (HMs) present in the surface dust (SD) of kindergartens on children, who are highly sensitive to contaminated dust in cities in their growth stage. A study was conducted on 11 types of HMs present in the SD of 73 kindergartens in Beijing. This study aims to assess the pollution levels and sources of eleven HMs in Beijing's kindergartens surface dust (KSD), and estimate the potential health risks in different populations and sources. The results indicate that Cd has the highest contamination in the KSD, followed by Pb, Zn, Ni, Ba, Cr, and Cu. The sources of these pollutants are identified as industrial sources (23.7%), natural sources (22.1%), traffic sources (30.4%), and construction sources (23.9%). Cancer risk is higher in children (4.02E-06) than in adults (8.93E-06). Notably, Cr is the priority pollutant in the KSD, and industrial and construction activities are the main sources of pollution that need to be controlled. The pollution in the central and surrounding areas is primarily caused by historical legacy industrial sites, transportation, urban development, and climate conditions. This work provides guidance to manage the pollution caused by HMs in the KSD of Beijing. ENVIRONMENTAL IMPLICATION: Children within urban populations are particularly sensitive to pollutants present in SD. Prolonged exposure to contaminated SD significantly heightens the likelihood of childhood illnesses. The pollution status and potential health risks of HMs within SD from urban kindergartens are comprehensively investigated. Additionally, the contributions from four primary sources are identified and quantified. Furthermore, a pollution-source-oriented assessment is adopted to clearly distinguish the diverse impacts of different sources on health risks, and the priority pollutants and sources are determined. This work holds pivotal importance for risk management, decision-making, and environmental control concerning HMs in KSD.

Assessing heavy metal pollution in sediments from the northern margin of Chinese mangrove areas: Sources, ecological risks, and health impacts

With the rapid economic development of coastal cities, the discharge of substantial amounts of heavy metal pollutants poses a serious hazard to mangroves; however, the potential sources of heavy metals and the resulting health risks are not fully understood. In this study, we analyzed the contents, sources, and ecological and health risks of heavy metal contamination in mangrove sediments from the northern margin of China. The accumulation of heavy metals in mangroves was primarily driven by five potential sources, namely agricultural (33.5 %), natural sources (21.3 %), industrial (19.1 %), aquaculture (14.3 %), and traffic (11.8 %). The assessment of health risks using a probabilistic approach demonstrated that noncarcinogenic risks were within acceptable limits for all populations. It was worth noting that both noncarcinogenic and carcinogenic risks were greater in children than in adults. Analysis of source-oriented health risks revealed that agricultural sources and As and Cd were priority sources and elements of pollution requiring attention.

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.

Pollution and source-specific risk analysis of potentially toxic metals in urban soils of an oasis-tourist city in northwest China

Source-specific risk apportionment for soil potentially toxic metals (PTMs) is of great significance for contamination prevention and risk management in urban environments. Eighty-five urban soil samples were obtained from an oasis-tourist city, China and examined for eight PTMs (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn). The pollution levels, sources, and ecological risk of soil PTMs were quantified, and their source-specific ecological and human health effects were also estimated using the multi-proxy approaches. The results demonstrated that accumulation of Cd, Hg, Pb, Cr, Cu, and Zn in soils was observed compared to their background levels, and the soils experienced varying degrees of PTMs pollution, especially at sites with high-intensity anthropogenic activities. Natural sources, atmospheric deposition, industrial sources, vehicular emissions, and comprehensive inputs were the principal sources, with contributions of 29.28%, 25.86%, 20.13%, 16.50%, and 8.23%, respectively. The integrated ecological risks of PTMs in soils were moderate at most sites, with atmospheric deposition being the dominant contributor to ecological risks. Children exhibited pronounced non-cancer risks, but adults had no notable non-cancer risks. Moreover, there were potential carcinogenic risks for both children and adults within the study region. Non-cancer and carcinogenic risks were more significant for children than adults, and traffic emissions were the primary contributor to non-cancer risks (adults: 20.53%, children: 20.49%) and carcinogenic risks (adults: 22.95%, children: 22.08%). The industrial and traffic activities were considered as priority control sources for soil pollution control and risk management, with Hg, Cd, Zn, and Pb corresponding to the priority elements. This study highlights the source-specific ecological and human health effects of PTMs pollution in urban soils, thereby providing valuable information for targeted pollution control and priority source management.

Geochemical characteristics and health risks of heavy metals in agricultural soils and crops from a coal mining area in Anhui province, China

Soil contamination by heavy metals (HMs) in mining areas is a major issue because of its significant impact on the environmental quality and physical health of residents. Mining of minerals used in energy production, particularly coal, has led to HMs entering the surrounding soil through geochemical pathways. In this study, a total of 166 surface soil and 100 wheat grain samples around the Guobei coal mine in southeast China were collected, and trace metal levels were determined via inductively coupled plasma mass spectrometry (ICP-MS). The average HMs (Ni, As, Cr, Cu, Pb, Cd, and Zn) concentrations were lower than the screening values in China (GB 15618-2018) but higher than the soil background values in the Huaibei Bozhou area of Anhui Province (except Zn), indicating HMs enrichment. Based on the geoaccumulation index (Igeo) and ecological risk index (IER), Cd pollution levels were low, while for the other metals the samples were pollution-free, and therefore no ecological risk warning was issued for the mining area. Both Cr and Pb had a higher noncarcinogenic health risks for adults and children. The lifetime carcinogenic risks (LCR) of Cr, Pb, and Cd were within acceptable levels. A positive matrix factorization (PMF) model identified two factors that could explain the HMs sources: factor 1 for Zn, Cd, and Pb, factor 2 for Ni, As, Cr, and Cu. Furthermore, HMs enrichment was observed in surface soil and the Carboniferous-Permian coal seams in the Guobei coal mine, which may suggest that coal mining is an important source for HMs enrichment in surface soil. Overall, this study provides a theoretical basis for undertaking the management and assessment of soil HMs pollution around a coal mine.

Source-sink response analysis of heavy metals and soil pollution assessment in non-ferrous metal industrial agglomeration areas based on decision unit

Soil heavy metals (HMs) pollution is a worldwide concern. In this study, decision units based on "source-sink relationship" were established using multi-source data. The source-sink response of heavy metals in agricultural soils at the regional scale was analyzed using machine learning methods, receptor models, and geospatial analysis. The comprehensive pollution risk score (CRS) was proposed by integrating a variety of key evaluation indicators to evaluate the pollution degree of each decision unit. We divided the study area into 193 decision units, the proportions of sites with concentrations of Cd, Hg, As, Pb, and Cr exceeding the most stringent risk screening values were 16.4 %, 2.2 %, 4.0 %, 7.6 %, and 0.2 %, respectively. Agricultural activities (livestock manure, fertilizer, sewage irrigation), industrial activities (rare earth ore and tungsten‑molybdenum mining and smelting), and soil parent material are the dominant pollution sources of HMs in the study area. The risk of contamination of each element is ranked from largest to smallest according to the CRS as Cd > Hg > Pb > As > Cr. The western and southwestern water pollution decision units are the areas with the highest risk of soil HMs contamination. This quantitative evaluation framework can provide a relatively accurate decision basis for soil pollution management.

Is biomagnetic leaf monitoring still an effective method for monitoring the heavy metal pollution of atmospheric particulate matter in clean cities?

The development of a reasonable method for predicting heavy metals (HMs) pollution in atmospheric particulate matter (PM) remains challenging. This paper presents an elution-filtration method to collect PM from the surface of Osmanthus fragrans in a very clean area (Guiyang, China). The aim is to evaluate the effectiveness of biomagnetic leaf monitoring as a simple and rapid method for assessing HMs pollution in clean cities. For this purpose, we determined the magnetic parameters and concentrations of selected HMs in PM samples to investigate their relationships. The results showed that the magnetic minerals in PM samples were mainly low coercivity ferrimagnetic minerals, with a small amount of high coercivity minerals. The types of magnetic minerals were generally single, and the magnetic domain state was pseudo-single domain (PSD). There was a significant correlation between magnetic parameters and the heavy metal (HM) concentrations in PM. Low-field magnetic susceptibility (χ) could be used as an ideal proxy for determining anthropogenic HM pollution. Traffic emissions were the main atmospheric pollution source in urban Guiyang. Due to the incomplete traffic network and large traffic flow, traffic congestion (TC) often occurred at road intersections in the northwest and southwest corners of the city, resulting in the highest concentration of magnetic minerals and the most severe PM pollution. To mitigate atmospheric PM pollution and protect public health, it is strongly recommended that municipal authorities prioritize urban planning and traffic management to address TC. Measures should be implemented urgently to alleviate stop-and-go traffic.

Human activities contributing to the accumulation of high-risk trace metal(loid)s in soils of China's five major urban agglomerations

Rapid urbanization has accelerated the accumulation of trace metal(loid)s (TMs) in soils, but the relationship between this accumulation and human activities remains largely unknown. Therefore, based on 775 published literatures (2001-2020), this study aimed to identify the influence of human activities on TM accumulation. Results showed that all soil TM concentrations were higher than their corresponding Chinese soil background values. The pollution risk assessment indicated that the soil TMs in the study area were at moderate levels, and the value of Pollution load index was 2.10. According to the assessment of health risks, the non-carcinogenic risks for adults were at the "Negligible risk" level; while the carcinogenic risk was not negligible for all populations, with children being more susceptible than adults. Meanwhile, six high-risk TMs were identified based on the grading of Contaminating factors (CF ≥ 3) and contribution to health risk (≥ 75%), including four high pollution risk TMs (Cd, Hg, Cu, and Pb) and two high health risk TMs (Cr and As) . In addition, in accordance with the results of the Random forest model, the accumulation of soil high-risk TMs was closely related to influencing factors associated with human activities. The accumulation of Hg and Cr among five major urban agglomerations had the same influencing factors (the number of industrial companies and the amount of industrial wastewater discharge for Hg; the amount of pesticide application and highway mileage for Cr). However, there were significant differences in the factors influencing the accumulation of the other four high-risk TMs (including Cd, As, Cu and Pb), due to the different characteristics of each urban agglomeration. Our results provide new insights into the relationship between human activities and soil TM accumulation.

Source-specific probabilistic risk evaluation of potentially toxic metal(loid)s in fine dust of college campuses based on positive matrix factorization and Monte Carlo simulation

Contamination, hazard level and source of 10 widely concerned potentially toxic metal(loid)s (PTMs) Co, As, Pb, Cr, Cu, Zn, Ni, Mn, Ba, and V in fine dust with particle size below 63 μm (FD63) were investigated to assess the environmental quality of college campuses and influencing factors. PTMs sources were qualitatively analyzed using statistical methods and quantitatively apportioned using positive matrix factorization. Probabilistic contamination degrees of PTMs were evaluated using enrichment factor and Nemerow integrated enrichment factor. Eco-health risk levels of content-oriented and source-oriented for PTMs were evaluated using Monte Carlo simulation. Mean levels of Zn (643.8 mg kg-1), Pb (146.0 mg kg-1), Cr (145.9 mg kg-1), Cu (95.5 mg kg-1), and Ba (804.2 mg kg-1) in FD63 were significantly larger than soil background values. The possible sources of the concerned PTMs in FD63 were traffic non-exhaust emissions, natural source, mixed source (auto repair waste, paints and pigments) and traffic exhaust emissions, which accounted for 45.7%, 25.4%, 14.5% and 14.4% of total PTMs contents, respectively. Comprehensive contamination levels of PTMs were very high, mainly caused by Zn pollution and non-exhaust emissions. Combined ecological risk levels of PTMs were low and moderate, chiefly caused by Pb and traffic exhaust emissions. The non-cancer risks of the PTMs in FD63 to college students fell within safety level, while the carcinogenic PTMs in FD63 had a certain cancer risks to college students. The results of source-specific health risk assessment indicated that Cr and As were the priority PTMs, and the mixed source was the priority pollution source of PTMs in FD63 from college campuses, which should be paid attention to by the local government.

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.

An integrated overview of metals contamination, source-specific risks investigation in coal mining vicinity soils

Heavy metals in soil are harmful to natural biodiversity and human health, and it is difficult to estimate the effects accurately. To reduce pollution and manage risk in coal-mining regions, it is essential to evaluate risks for heavy metals in soil. The present study reviews the levels of 21 metals (Nb, Zr, Ag, Ni, Na, K, Mg, Rb, Zn, Ca, Sr, As, Cr, Fe, Pb, Cd, Co, Hg, Cu, Mn and Ti) in soils around Barapukuria coal-mining vicinity, Bangladesh which were reported in literature. An integrated approach for risk assessments with the positive matrix factorization (PMF) model, source-oriented ecological and health hazards were applied for the study. The contents of Rb, Ca, Zn, Pb, As, Ti, Mn, Co, Ag, Zr, and Nb were 1.63, 1.10, 1.97, 14.12, 1.20, 3.13, 1.22, 3.05, 3.85, 5.48, and 7.21 times greater than shale value. About 37%, 67%, 12%, and 85% of sampling sites posed higher risks according to the modified contamination factor, Nemerow pollution index, Nemerow integrated risk index, and mean effect range median quotient, respectively. Five probable metal sources were computed, including industrial activities to coal mining (17%), agricultural activities (33%), atmospheric deposition (19%), traffic emission (16%), and natural sources (15%). Modified Nemerow integrated risk index reported that agricultural activities, industrial coal mining activities, and atmospheric deposition showed moderate risk. Health hazards revealed that cancer risk values computed by the PMF-HHR model with identified sources were higher than the standard value (1.0E-04) for children, adult male, and female. Agricultural activities showed higher cancer risks to adult male (39%) and children (32%) whereas traffic emission contributed to female (25%). These findings highlight the ecological and health issues connected to potential sources of metal contamination and provide useful information to policymakers on how to reduce such risks.

Receptor model-based source-specific health risks of toxic metal(loid)s in coal basin-induced agricultural soil in northwest Bangladesh

Toxic metal(loid)s (TMLs) in agricultural soils cause detrimental effects on ecosystem and human health. Therefore, source-specific health risk apportionment is very crucial for the prevention and control of TMLs in agricultural soils. In this study, 149 surface soil samples were taken from a coal mining region in northwest Bangladesh and analyzed for 12 TMLs (Pb, Cd, Ni, Cr, Mn, Fe, Co, Zn, Cu, As, Se, and Hg). Positive matrix factorization (PMF) and absolute principal component score-multiple linear regression (APCS-MLR) receptor models were employed to quantify the pollution sources of soil TMLs. Both models identified five possible sources of pollution: agrochemical practice, industrial emissions, coal-power-plant, geogenic source, and atmospheric deposition, while the contribution rates of each source were calculated as 28.2%, 17.2%, 19.3%, 19% and 16.3% in APCS-MLR, 22.2%, 13.4%, 24.3%, 15.1% and 25.1% in PMF, respectively. Agrochemical practice was the major source of non-carcinogenic risk (NCR) (adults: 32.37%, children: 31.54%), while atmospheric deposition was the highest source of carcinogenic risk (CR) (adults: 48.83%, children: 50.11%). NCR and CR values for adults were slightly higher than for children. However, the trends in NCR and CR between children and adults were similar. As a result, among the sources of pollution, agrochemical practices and atmospheric deposition have been identified as the primary sources of soil TMLs, so prevention and control strategies should be applied primarily for these pollution sources in order to protect human health.

Connection between health risk and heavy metals in agricultural soils of China: a study based on current field investigations

Heavy metal pollution in agricultural soil is a threat to people's health and sustainable development. However, there is currently no nationwide health risk assessment in China. In this study, we performed a preliminary assessment of heavy metals in agricultural soils of the Chinese mainland, and found obvious carcinogenic risks (total lifetime carcinogenic risk (TLCR) > 1 × 10-5). A similar spatial distribution pattern was found in soil heavy metal and the mortality of esophagus and stomach cancers. Combining the potential carcinogenic risk assessed by LCR for individual heavy metal with Pearson correlation, Geographical Detector (q statistic > 0.75 for TLCR, p < 0.05), and redundancy analysis (RDA), it was found that long-term exposure and intake route of heavy metals exceeding the maximum safety threshold (Health Canada standard) may induce digestive system (esophagus, stomach, liver, and colorectum) cancers in rural populations. Through Partial Least Squares Path Model (PLS-PM), it was also revealed that the LCR of heavy metals was closely related to the soil environmental background (path coefficients = 0.82), which in turn was affected by factors such as economic development and pollution discharge. The current research results highlight the potential carcinogenic risk to the digestive system associated with low-dose and long-term exposure to heavy metals in agricultural soils, and policymakers should propose countermeasures and solutions according to the local conditions.

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

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

New insights into health risk assessment on soil trace metal(loid)s: Model improvement and parameter optimization

Trace metal(loid)s (TMs) in soils may pose potential health risks to humans. Due to model uncertainty and variability of exposure parameters, the traditional health risk assessment (HRA) model may lead to inaccurate risk assessment results. Therefore, this study developed an improved HRA model to assess health risks by combining two-dimensional Monte Carlo simulation (2-D MCS) with a Logistic Chaotic sequence based on published data from 2000 to 2021. The results showed children and adult females were the high-risks populations for Non-carcinogenic risk and Carcinogenic risk, respectively. Meanwhile, children's Ingestion rate (IngR < 160.233 mg/day) and adult females' Skin adherence factor (0.026 mg/(cm2•d) < AF < 0.263 mg/(cm2•d)) were used as recommended exposure to make the health risk within acceptable range. Additionally, when performing risk assessment using actual exposure parameters, priority control TMs were identified, with As being the priority control TM for Southwest China and Inner Mongolia, whereas Cr and Pb for Tibet and Yunnan, respectively. Compared to health risk assessment, improved models increased risk assessment accuracy and provided recommended exposure parameter for high-risk populations. This study will provide new insights for soil-related health risk assessment.

Ascertaining priority control pollution sources and target pollutants in toxic metal risk management of a medium-sized industrial city

Re-suspended surface dust (RSD) often poses higher environmental risks due to its specific physical characteristics. To ascertain the priority pollution sources and pollutants for the risk control of toxic metals (TMs) in RSD of medium-sized industrial cities, this study took Baotou City, a representative medium-sized industrial city in North China, as an example to systematically study TMs pollution in RSD. The levels of Cr (242.6 mg kg-1), Pb (65.7 mg kg-1), Co (54.0 mg kg-1), Ba (1032.4 mg kg-1), Cu (31.8 mg kg-1), Zn (81.7 mg kg-1), and Mn (593.8 mg kg-1) in Baotou RSD exceeded their soil background values. Co and Cr exhibited significant enrichment in 94.0 % and 49.4 % of samples, respectively. The comprehensive pollution of TMs in Baotou RSD was very high, mainly caused by Co and Cr. The main sources of TMs in the study area were industrial emissions, construction, and traffic activities, accounting for 32.5, 25.9, and 41.6 % of the total TMs respectively. The overall ecological risk in the study area was low, but 21.5 % of samples exhibited moderate or higher risk. The carcinogenic risks of TMs in the RSD to local residents and their non-carcinogenic risks to children cannot be ignored. Industrial and construction sources were priority pollution sources for eco-health risks, with Cr and Co being the target TMs. The south, north and west of the study area were the priority control areas for TMs pollution. The probabilistic risk assessment method combining of Monte Carlo simulation and source analysis can effectively identify the priority pollution sources and pollutants. These findings provide scientific basis for TMs pollution control in Baotou and constitute a reference for environmental management and protection of residents' health in other similar medium-sized industrial cities.

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.

Potentially toxic elements in surface fine dust of residence communities in valley industrial cities

A comprehensive analysis of content, pollution characteristics, health hazard, distribution, and source of some broadly concerned potentially toxic elements (PTEs, Pb, V, Mn, Cr, Ba, Zn, Ni, and Cu) in surface fine dust with particle size <63 μm (SFD63) from residence communities in Xi'an, a representative valley industrial city, was conducted in this research to analyze the quality of environment and influencing factors of valley industrial cities in China. The average contents of Ba (794.1 mg kg-1), Cu (61.3 mg kg-1), Pb (99.9 mg kg-1), Zn (408.1 mg kg-1), Cr (110.0 mg kg-1), and Ni (33.4 mg kg-1) in SFD63 of Xi'an residence communities surpassed their background contents of local soil. The high enrichment-value regions of PTEs were chiefly located in the regions with high traffic flow, high population density, and areas around industries. Zn and Pb had moderate enrichment, and the overall pollution level of PTEs was unpolluted-to-moderate and moderate pollution. Three source categories (including natural geogenic source, industrial anthropogenic source, and mixed anthropogenic source of transportation, residential activities, and construction) were identified as the predominant sources for the PTEs pollution in SFD63, with the contribution levels of 29.9%, 32.4%, and 37.7%, respectively. The assessment of health risks according to Monte Carlo simulation revealed that the 95% of the non-cancer risk of PTEs to residents (the elderly, working people, and children) was less than the threshold of 1, while the probability of cancer risk exceeding the acceptable threshold of 1E-6 was 93.76% for children, 68.61% for the elderly, and 67.54% for working people. Industrial source was determined as priority pollution source and Cr was determined as priority pollutant, which should be concerned.

Spatial distribution, sources, and risk assessment of potentially toxic elements in cultivated soils using isotopic tracing techniques and Monte Carlo simulation

Potentially toxic elements (PTEs) in cultivated lands pose serious threats to the environment and human health. Therefore, improving the understanding of their distinct sources and environmental risks by integrating various methods is necessary. This study investigated the distribution, sources, and environmental risks of eight PTEs in cultivated soils in Lishui City, eastern China, using digital soil mapping, positive matrix factorisation (PMF), isotopic tracing, and Monte Carlo simulation. The results showed that Pb and Cd are the main pollutants, which posed higher ecological risks in the study area than the other PTEs. Natural, mining, traffic, and agricultural sources were identified as the four determinants of PTE accumulation via a PMF model combined with Pearson correlation analysis, showing that their contribution rates were 22.6 %, 45.7 %, 15.2 %, and 16.5 %, respectively. Stable isotope analysis further confirmed that local mining activities affected the HM accumulation. Additionally, non-carcinogenic and carcinogenic risk values for children were 3.18 % and 3.75 %, respectively, exceeding their acceptable levels. We also identified that mining activities were the most important sources of human health risks (55.7 % for adults and 58.6 % for children) via Monte Carlo simulations coupled with the PMF model. Overall, this study provides insights into the PTE pollution management and health risk control in cultivated soils.

Quantitative source apportionment and driver identification of soil heavy metals using advanced machine learning techniques

The accurate identification of pollution sources is essential for the prevention and control of possible pollution from soil heavy metals (SHMs). However, the positive matrix factorisation (PMF) model has been widely used as a conventional method for pollution source apportionment, and the classification of source apportionment results mainly relies on existing research and expert experience, which can result in high subjectivity in the source interpretation. To address this limitation, a comprehensive source apportionment framework was developed based on advanced machine learning techniques that combine self-organizing mapping and PMF with a gradient boosting decision tree (GBDT) model. Analysis of Cd, Pb, Zn, Cu, Cr, and Ni in 272 topsoils showed that the average contents of six heavy metals were 1.72-13.79 times greater than corresponding background values, among which Cd pollution was relatively serious, with 66.91 % of the sites having higher values than the specified soil risk screening values. The PMF results revealed that 79.43 % of Pb was related to vehicle emissions and atmospheric deposition, 79.32 % of Cd and 38.84 % of Zn were related to sewage irrigation, and 85.97 % of Cr and 85.50 % of Ni were from natural sources. Moreover, the GBDT detected that industrial network density, water network density, and Fe₂O₃ content were the major drivers influencing each pollution source. Overall, the novelty of this study lies in the development of an improved framework based on advanced machine learning techniques that led to the accurate identification of the sources of SHM pollution, which can provide more detailed support for environmental protection departments to propose targeted control measures for soil pollution.