Source-specific health risks apportionment of soil potential toxicity elements combining multiple receptor models with Monte Carlo simulation

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.

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

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

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.

Concentration, speciation and risk effects of multiple environmentally sensitive trace elements in respirable fine-grained fly ash

Respirable fine-grained fly ash (RFA) is captured very inefficiently by existing air purification devices of power plant, leading to increasing concerns regarding their migration and subsequent interaction with body due to fine particle size and its complex toxic composition. Trace elements of RFA in three groups with five different sizes between 8-13 µm were analyzed in terms of available concentration, speciation and risk effects. The concentration, pollution level and ecological risk level of elements in RFA were related to particle sizes. Chronic non-carcinogenic effect risk (NER) and carcinogenic effect risk (CER) were negatively correlated with particle size. The individual weight of exposed subjects, corresponding trace elements concentration and ingestion rate in RFA were three significant variables influencing CER. NER and CER had a tenfold exaggerated effect when calculated using total element concentration of RFA. In addition to individual differences and exposure conditions, trace element properties, speciation and available concentration were the dominant factor responsible for ecological and environmental effects of trace elements in RFA, following the order As>Ni, Mn>Cr>Pb>Cu>Zn. Results of this work highlight the effects and differences of trace elements in RFA on ecology and health, and provide a basis for further pollution control and human health warning.

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.

Risk assessment of heavy metals in agricultural soil based on the coupling model of Monte Carlo simulation-triangular fuzzy number

Soils in areas wherein agriculture and mining coexist are experiencing serious heavy metal contamination, posing a great threat to the ecological environment and human health. In this study, heavy metals (As, Cd, Cr, Cu, Ni, Pb, and Zn) in agricultural soil samples from mining areas were analyzed to explore pollution status, bioavailability, potential sources, and ecological/health risks. Particularly, the coupling model of Monte Carlo simulation-triangular fuzzy number (MCS-TFN) was established to quantify ecological/health risks accurately. Results showed that Cd was heavily enriched in soil and had the highest bioavailability based on both geo-accumulation index (Igeo) and chemical speciation analysis. Pollution sources apportioned with the absolute principal component score-multiple linear regression (APCS-MLR) model demonstrated that heavy metals were mainly derived from agricultural activities, followed by mining activities and natural sources. The MCS-TFN ecological risk assessment classified Cd into the high-risk category with a probability of 40.96%, whereas other heavy metals were categorized as the low risk. Cd was regarded as the major pollutant for the ecosystem. Moreover, the MCS-TFN health risk assessment indicated that As showed high noncarcinogenic risk (0.07% probability) and moderate carcinogenic risk (1.87% probability), and Cd presented low carcinogenic risk (80.19% probability). As and Cd were identified as the main heavy metals that pose a threat to human health. The MCS-TFN risk assessment is superior to the traditional deterministic risk assessment since it can obtain the risk level and the corresponding probability, and significantly reduce the uncertainty in risk assessment.

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.

Bioavailability and health risk of pollutants around a controlled landfill in Morocco: Synergistic effects of landfilling and intensive agriculture

Toxic contamination of agricultural soils by trace metal(oid)s can pose detrimental effects on human health and agroecological systems. In this view, the current research explored total and available metal(oid)s in surface soils and assessed the associated hazards using pollution indices, PMF modeling, PCA, and Montecarlo probabilistic human risk assessment with 10,000 repetitions. The mean concentrations of Cd, Pb, As, Cr, Ni, Cu, Zn, and Fe were 0.89, 24.86, 1.81, 19.10, 25.44, 7.98, 49.12 and 6183.32 mg kg-1 dry weight, respectively. These findings highlighted that the concentration of pollutants exceeded the values measured in the geochemical background. Soil enrichment by heavy metal (oid)s was confirmed by analyzing available fractions using DTPA ,CaCl2 and enrichment factor (EF). Additionally, pollution indicators (Igeo, PLI, and PERI) displayed significant contamination levels, with a higher ecological risk. Matrix Factorization (PMF) receptor and multivariate statistical analysis reflected that anthropogenic activities, particularly landfilling and agricultural practices were the main causes of the contamination. Furthermore, probabilistic and deterministic human risk assessments showed that carcinogenic risks exceeded the threshold values (10-4) set by the USEPA. Consequently, it is crucial to implement continuous monitoring and supervision of landfill sites to prevent additional pollution. These measures should be integrated into the management plans for waste management.

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.

Uncertainty Evaluation of Soil Heavy Metal(loid) Pollution and Health Risk in Hunan Province: A Geographic Detector with Monte Carlo Simulation

Research on soil heavy metal(loid) pollution and health risk assessment is extensive, but a notable gap exists in systematically examining uncertainty in this process. We employ the Nemerow index, the health risk assessment model, and the geographic detector model (GDM) to analyze soil heavy metal(loid) pollution, assess health risks, and identify driving factors in Hunan Province, China. Furthermore, the Monte Carlo simulation (MCS) method is utilized to quantitatively evaluate the uncertainties associated with the sampling point positions, model parameters, and classification boundaries of the driving factors in these processes. The experimental findings reveal the following key insights: (1) Regions with high levels of heavy metal(loid) pollution, accompanied by low uncertainty, are identified in Chenzhou and Hengyang Cities in Hunan Province. (2) Arsenic (As) and chromium (Cr) are identified as the primary contributors to health risks. (3) The GDM results highlight strong nonlinear enhanced interactions among lithology and other factors. (4) The input GDM factors, such as temperature, river distance, and gross domestic product (GDP), show high uncertainty on the influencing degree of soil heavy metal(loid) pollution. This study thoroughly assesses high heavy metal(loid) pollution in Hunan Province, China, emphasizing uncertainty and offering a scientific foundation for land management and pollution remediation.

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.

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.

Comprehensive model development based on Dempster-Shafer evidence theory for pollution source analysis in chemical parks

Pollution source analysis is an effective method that can help chemical park managers accurately understand the characteristics and contributions of pollution sources in the park. However, as more receptor models are being used in this field, it has become difficult for managers to find the best interpretable and reasonable model among many source analysis models. Here, we present a case study of pollution source analysis in a southern chemical park using the D-S evidence theory approach to combine the source analysis results of different receptor models for comprehensive consideration. Receptor models were used to analyse the pollution sources via positive definite matrix decomposition, principal component analysis-multiple linear regression, and Unmix models. The results demonstrated that source analysis was greatly influenced by the uniqueness of pollutant characteristics and model receptor differences. Furthermore, incomparable analysis results and low fineness were observed. The D-S evidence theory model proposed in this study solved the above-mentioned problem to some extent and successfully extracted the four primary pollution sources in the study area, of which 45.73 % came from the metal processing industry (F1), whose primary pollutants were Cr, Ni, Zn, Cr(VI), and Cu, and 25.12 % came from the electronics manufacturing industry (F2), whose primary pollutants were Pb, Cr(VI), Cu, and Zn. 15.62 % of the contamination came from the production of chemical agents (F3), whose primary pollutant was TEHP, and 13.53 % came from the use of oil-containing auxiliary materials (F4), whose primary pollutant was TPH. The D-S evidence theory model used in this study provides a reference for the management of chemical parks.

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.

Contamination and source apportionment of metals in urban road dust (Jinan, China) integrating the enrichment factor, receptor models (FA-NNC and PMF), local Moran's index, Pb isotopes and source-oriented health risk

Contamination and source identifications of metals in urban road dust are critical for remediation and health protection. Receptor models are commonly used for metal source identification, whereas the results are usually subjective and not verified by other indicators. Here we present and discuss a comprehensive approach to study metal contamination and sources in urban road dust (Jinan) in spring and winter by integrating the enrichment factor (EF), receptor models (positive matrix factorization (PMF) and factor analysis with nonnegative constraints (FA-NNC)), local Moran's index, traffic factors and Pb isotopes. Cadmium, Cr, Cu, Pb, Sb, Sn and Zn were the main contaminants, with mean EFs of 2.0-7.1. The EFs were 1.0-1.6 times higher in winter than in spring but exhibited similar spatial trends. Chromium contamination hotspots occurred in the northern area, with other metal contamination hotspots in the central, southeastern and eastern areas. The FA-NNC results indicated Cr contamination primarily resulting from industrial sources and other metal contamination primarily originating from traffic emissions during the two seasons. Coal burning emissions also contributed to Cd, Pb and Zn contamination in winter. FA-NNC model-identified metal sources were verified via traffic factors, atmospheric monitoring and Pb isotopes. The PMF model failed to differentiate Cr contamination from other detrital metals and the above anthropogenic sources, largely due to the model grouping metals by emphasizing hotspots. Considering the FA-NNC results, industrial and traffic sources accounted for 28.5 % (23.3 %) and 44.7 % (28.4 %), respectively, of the metal concentrations in spring (winter), and coal burning emissions contributed 34.3 % in winter. Industrial emissions primarily contributed to the health risks of metals due to the high Cr loading factor, but traffic emissions dominated metal contamination. Through Monte Carlo simulations, Cr had 4.8 % and 0.4 % possibilities posing noncarcinogenic and 18.8 % and 8.2 % possibilities posing carcinogenic risks for children in spring and winter, respectively.

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.

Heavy metal fraction, pollution, and source-oriented risk assessment in biofilms on a river system polluted by mining activities

The Lanping Pb-Zn mine is the largest source of Pb and Zn ores in China, thus posing a great threat to local ecosystems and human health. A total of seven heavy metals (Zn, Pb, Ni, Cu, Cr, Cd, and As) in the Bijiang River near the Pb-Zn mine were measured in winter and summer to assess their spatial-temporal enrichment, ecological risk, and source-oriented health risk in periphytic biofilms. Positive matrix factorization (PMF) receptor model and clustering analysis were used to quantitatively identify pollution sources. The results of PMF were then imported into the health risk assessment to further determine the carcinogenic and noncarcinogenic risks of various pollution sources. The results indicated distinct seasonal patterns in metal concentrations, with much higher concentrations in winter. Sites near the Pb-Zn mine tailing reservoir exhibited higher metal contamination levels than other sites. A strong correlation between the enrichment factor and the levels of nonresidual fraction suggested that anthropogenic inputs were the main source of these metals. Mining industries (Cd, Zn, and Pb), natural sources (As, Ni, and Cu), and agricultural activities (Cr) were the primary sources of heavy metal pollution in biofilms, accounting for 44.43%, 33.32%, and 22.26% of the total metal accumulation, respectively. Moreover, the carcinogenic and noncarcinogenic risks via dermal contact of the studied elements in biofilms were typically acceptable. Notably, as concentration was the main factor influencing these risks in children and adults. This study provides evidence that natural epilithic periphyton may be a potential metal biomonitor in aquatic systems and provide supporting information for effective source regulation.

A comprehensive method of source apportionment and ecological risk assessment of soil heavy metals: A case study in Qingyuan city, China

The study combined multiple models to provide a deeper understanding to soil heavy metal contamination and source information, which are essential for controlling pollution and reducing human health risks. In this study, the agricultural soils were collected from the Qingyuan City of China as an example. The multiple models (APCS/MLR, PMF, and GDM) were used to identify and quantitatively apportion the main sources of heavy metal pollution in the area. The results showed that Cu (56.4 %), Ni (70.9 %), B (44.5 %), and Cr (72.8 %) were associated with natural sources, such as soil parent material and soil-forming processes. However, Pb (41.2 %), Zn (61.8 %), Hg (67.0 %), and Cd (69.6 %) were associated with agricultural activities, atmospheric deposition, vehicle exhaust emissions, and vehicle tires, while Mo, Se, and Mn were possibly derived from natural sources, including rock weathering and soil parent materials. Additionally, the network of environmental analysis revealed that soil microbes are far more sensitive to soil heavy metal pollution than herbivores, vegetation, and carnivores. This study can serve as a guideline for reducing the ecological and health risks associated with heavy metals in soil by controlling their preferential sources. Environmental implication Combining multiple models is more effective approach to wide understanding of heavy metal contamination and source information, which is essential for controlling pollution and reducing human health risks. Based on multiple models (APCS/MLR, PMF, and GDM) and network environ analysis, a comprehensive method for apportioning soil heavy metal sources and assessing ecological risk had been provided. Further, the present study can be a guideline for reducing ecological and health risks by heavy metals in soil by controlling preferential sources.

Contamination characteristics and source analysis of potentially toxic elements in dustfall-soil-crop systems near non-ferrous mining areas of Yunnan, southwestern China

Potentially toxic elements (PTEs) in the dustfall-soil-crop system pose a serious threat to the ecological environment and agricultural production. However, there is still a knowledge gap in terms of better understanding the distinctive sources of PTEs by integrating various models and technologies. In this study, we comprehensively investigated the concentrations, distribution, and sources of seven PTEs in a dustfall-soil-crop system (424 samples in total) near a typical non-ferrous mining area, using absolute principal component score/multiple linear regression (APCS/MLR) combined with X-ray diffraction (XRD) and microscopy techniques. Our results showed that the mean values of As, Cd, Cr, Cu, Ni, Pb, and Zn in the soils were 211, 14, 105, 91, 65, 232, and 325 mg/kg, respectively. These values were significantly higher than the background soil values in Yunnan. Except for Ni and Cr, all elements in the soil were significantly higher than the screening values of agricultural lands in China. The spatial distribution of PTE concentrations was similar among the three media. The ACPS/MLR, XRD, and microscopy analyses further indicated that soil PTEs mainly originated from industrial activities (37 %), vehicle emissions and agricultural activities (29 %), respectively. Dustfall PTEs mainly originated from vehicle emissions and industrial activities, accounting for 40 % and 37 %, respectively. Crop PTEs mainly originated from vehicle emissions and soil (57 %), and agricultural activities (11 %), respectively. PTEs seriously threaten the safety of agricultural products and the ecological environment once they settle from the atmosphere to soil and crop leaves, further accumulate in crops, and spread through the food chain. Therefore, our study provides scientific evidence for government regulators to control PTE pollution and reduce their environmental risks in dustfall-soil-crop systems.

Distribution and accumulation of cadmium in soil under wheat-cultivation system and human health risk assessment in coal mining area of China

The soil contamination caused by the discharge of cadmium (Cd) from coal mining activities has aroused continuous attention due to the detrimental effects on the human health. This study aimed to investigate the characteristics on distribution of Cd in soils and its accumulation in wheat grains under wheat-cultivation system, and further assess the human health risks to adults and children. 58 soils and wheat samples in pairs from Linhuan coal mining area, Anhui Province were collected and analyzed. Results showed that the concentrations of Cd in 17.24% of soil samples exceeded the limit value established by the Ministry of Ecology and Environment. The ordinary kriging interpolation displayed that the spatial variability of Cd concentrations in soils was mainly influenced by coal mining activities. The transfer capacity of Cd from soils to wheat roots was greater than that from the wheat roots to grains. Multiple linear regression model clarified that soil pH and exchangeable Cd fraction in soils were the critical factors affecting the Cd accumulation in wheat grains. The carcinogenic risk of Cd levels in our studied wheat grains was a concern but still within the acceptable range, while their non-carcinogenic hazard was negligible for adults and children. The calculation results were in accord with the uncertainty analysis conclusion based on Monte Carlo simulation. The study was expected to promote the source management and control strategy of reducing tailing discharge, and providing scientific references for current soil remediation and land degradation prevention.

Quantitative Source Apportionment of Potentially Toxic Elements in Baoshan Soils Employing Combined Receptor Models

Arable soils are crucial for national development and food security; therefore, contamination of agricultural soils from potentially toxic elements (PTEs) is a global concern. In this study, we collected 152 soil samples for evaluation. Considering the contamination factors and using the cumulative index and geostatistical methods, we investigated the contamination levels of PTEs in Baoshan City, China. Using principal component analysis, absolute principal component score-multivariate linear regression, positive matrix factorization, and UNMIX, we analyzed the sources and quantitatively estimated their contributions. The average Cd, As, Pb, Cu, and Zn concentrations were 0.28, 31.42, 47.59, 100.46, and 12.36 mg/kg, respectively. The Cd, Cu, and Zn concentrations exceeded the corresponding background values for Yunnan Province. The combined receptor models showed that natural and agricultural sources contributed primarily to Cd and Cu and As and Pb inputs, accounting for 35.23 and 7.67% pollution, respectively. Industrial and traffic sources contributed primarily to Pb and Zn inputs (47.12%). Anthropogenic activities and natural causes accounted for 64.76 and 35.23% of soil pollution, respectively. Industrial and traffic sources contributed 47.12% to pollution from anthropogenic activities. Accordingly, the control of industrial PTE pollution emissions should be strengthened, and awareness should be raised to protect arable land around roads.

Soil heavy metal pollution from Pb/Zn smelting regions in China and the remediation potential of biomineralization

Smelting activities pose serious environmental problems due to the local and regional heavy metal pollution in soils they cause. It is therefore important to understand the pollution situation and its source in the contaminated soils. In this paper, data on heavy metal pollution in soils resulting from Pb/Zn smelting (published in the last 10 years) in China was summarized. The heavy metal pollution was analyzed from a macroscopic point of view. The results indicated that Pb, Zn, As and Cd were common contaminants that were present in soils with extremely high concentrations. Because of the extreme carcinogenicity, genotoxicity and neurotoxicity that heavy metals pose, remediation of the soils contaminated by smelting is urgently required. The primary anthropogenic activities contributing to soil pollution in smelting areas and the progressive development of accurate source identification were performed. Due to the advantages of biominerals, the potential of biomineralization for heavy metal contaminated soils was introduced. Furthermore, the prospects of geochemical fraction analysis, combined source identification methods as well as several optimization methods for biomineralization are presented, to provide a reference for pollution investigation and remediation in smelting contaminated soils in the future.

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

Identifying potential sources of soil potentially toxic elements (PTEs) and developing source-oriented health risk assessments in typical mining cities are key for pollution prevention and risk management. To this end, a case study was conducted to explore the pollution characteristics, potential sources, and human health risks of PTEs in Daye City, China. Indices, including the pollution factor (PF), pollution load index (PLI), and geo-accumulation index (I_geo), were applied to assess PTE pollution. Cd had the highest value among the detected PTEs, and 82.93% of the sampling sites had moderate pollution levels, with the highest mean I_geo value for Cd (2.30). Four potential sources were determined. Cr and Ni originated mainly from natural sources. Zn (91.5%) was exclusively and then Cd (33.1%) was moderately derived from industrial activities. The mixed source of various mineral exploitation smelting, and coal-fired traffic emissions leaded to the accumulation of As, Cd, and Pb. Cu was associated with Cu-related mining and smelting activities. The probabilistic health risk assessment indicated that the non-carcinogenic risks for populations were negligible. Overall, this work provides scientific information for environmental managers to manage soil PTE pollution through the effective management of anthropogenic sources with limited resources and costs.

Pollution characteristics and probabilistic health risk of potentially hazardous elements in soils near a typical coal mine in Panzhihua City, Southwest China

This study first assessed the pollution characteristics and probabilistic health risks of potentially hazardous elements (PHEs) in soils from the Dabaoding coal mining area in southwest China using Monte Carlo simulation. Experimental results showed that Cd was moderately enriched in soils, while Ni, Cr, and V were slightly enriched. However, the geoaccumulation index (I_geo) illustrated that the coal mining area had a low level of Cd pollution. PHEs produced a very high ecological risk to soils in the coal mining area, whereas Cd showed the highest contribution (82.56%). The mean hazard index of all soil PHEs was 7.45E - 02 and 4.18E - 01 for local adults and children, respectively, all of which were obviously lower than the maximum acceptable level of 1.0. However, Monte Carlo simulation analysis indicated that 1.08% of noncarcinogenic risk values for local children still exceeded the maximum acceptable level. Additionally, 10.84% and 18.40% of the total carcinogenic risk values for local adults and children, respectively, exceeded the threshold of 1E - 04. Indeed, Cr and Ni had the highest contributions to noncarcinogenic and carcinogenic risks, respectively. These findings suggest that Cd, Cr, and Ni should be identified as priority pollutants in coal mining areas. This study also provides valuable implications for policy-makers and environmental engineers, proposing efficient policies for better soil pollution control and remediation strategies in coal mining areas.

Speciation, bioaccessibility and human health risk assessment of chromium in solid wastes from an ultra-low emission coal-fired power plant, China

Chromium (Cr) in solid wastes from ultra-low emission (ULE) coal-fired power plants (CFPPs) could engender adverse effects on environment and human health. Hence, solid waste samples containing bottom ash, fly ash, gypsum and sludge were collected from a typical ULE CFPP in China to study the distribution, speciation, bioaccessibility and human health risk of Cr. The results showed that Cr was depleted in gypsum, whereas significantly enriched in bottom ash, fly ash and sludge comparing with feed coal. The ratios of Cr(VI) to total Cr in solid wastes were relatively low, but the increase of flow fractions in Cr chemical binding forms implied the deterioration of environmental stability. Based on the in vitro simulated digestion methods of solubility bioavailability research consortium (SBRC) and physiologically based extraction test (PBET), the bioaccessibility of Cr in the gastric and intestinal phases reached the highest values in either gypsum or sludge. After incorporating bioaccessibility in human health risk assessment, the carcinogenic risk (CR) within acceptable limits of Cr in solid wastes to adults and children was concluded, with the non-carcinogenic hazard quotient (HQ) was all within the safety threshold. The Monte Carlo model was applied to evaluate the uncertainty analysis of human health risk assessment at 5% and 95% confidence interval, and the fitting results were consistent with the calculation results of the carcinogenic and non-carcinogenic risk for adults and children. This study is expected to provide insights for the integration of bioaccessibility into the health risk assessment of Cr in solid wastes from ULE CFPPs, thus is conducive to the disposal of solid wastes and human health protection.

Editorial for the Special Issue "Potentially Toxic Elements Pollution in Urban and Suburban Environments"

Pollution by potentially toxic elements (PTEs) is becoming a serious and widespread issue in all environmental matrices because of accelerated population growth rate, rapid industrialization and urbanization, and other changes which have occurred in most parts of the world in the last few decades [...].

Integrated review of the nexus between toxic elements in the environment and human health

Emerging pollutants in the environment due to economic development have become a global challenge for environmental and human health management. Potentially toxic elements (PTEs), a major group of pollutants, have been detected in soil, air, water and food crops. Humans are exposed to PTEs through soil ingestion, consumption of water, uptake of food crop products originating from polluted fields, breathing of dust and fumes, and direct contact of the skin with contaminated soil and water. The dose absorbed by humans, the exposure route and the duration (i.e., acute or chronic) determine the toxicity of PTEs. Poisoning by PTEs can lead to excessive damage to health as a consequence of oxidative stress produced by the formation of free radicals and, as a consequence, to various disorders. The toxicity of certain organs includes neurotoxicity, nephrotoxicity, hepatotoxicity, skin toxicity, and cardiovascular toxicity. In the treatment of PTE toxicity, synthetic chelating agents and symptomatic supportive procedures have been conventionally used. In addition, there are new insights concerning natural products which may be a powerful option to treat several adverse consequences. Health policy implications need to include monitoring air, water, soil, food products, and individuals at risk, as well as environmental manipulation of soil, water, and sewage. The overall goal of this review is to present an integrated view of human exposure, risk assessment, clinical effects, as well as therapy, including new treatment options, related to highly toxic PTEs.

Source appointment of potentially toxic elements (PTEs) at an abandoned realgar mine: Combination of multivariate statistical analysis and three common receptor models

Identifying pollution sources and quantifying their contributions are of great importance for proposing management and control strategies of potentially toxic elements (PTEs) in soil. In this study, multivariate statistical analysis and receptor models were combined to identify potential pollution sources and apportion their contributions at an abandoned realgar mine. Principal component analysis (PCA) result shows that three factors are responsible for PTEs, which is also supported by cluster analysis (CA). Correlation analysis and spatial analysis also show that the heavy metals from the same pollution source are of higher correlation coefficients and similar spatial distribution. Three receptor models were combined to apportion contributions of pollution sources. Three pollution sources were detected by absolute principal component analysis-multiple linear regression (APCA-MLR). In contrast, four sources were identified by positive matrix factorization (PMF) and UNMIX. Soil parent material was heavily loaded on Cr, Cu, Ni and Zn, occupying the largest average contribution (30%-43%). Cadmium was mainly derived from agricultural activities with contribution higher than 60%. Arsenic accumulation was mainly associated with mining and smelting activity with contribution higher than 80%. PMF and UNMIX models showed that more than half of Pb concentrations were influenced by industrial activities. Comparatively speaking, APCA-MLR was a well-performing model for all PTEs even though it only detected three pollution sources. The study showed that it was a good choice to apply multiple receptor models in order to achieve more reliable and objective conclusions of source appointment.

Bioavailability and health risk of toxic heavy metals (As, Hg, Pb and Cd) in urban soils: A Monte Carlo simulation approach

Toxic heavy metals pollution in urban soil has become a major global issue due to its adverse effects on the environment and human health. In this paper, 26 soil samples were analyzed to assess the speciation, bioavailability and human health risk of Arsenic (As), Mercury (Hg), Lead (Pb) and Cadmium (Cd) in urban soils of a heavy industrial city in NE China by using a Monte Carlo simulation approach. The results showed that As, Hg, Pb and Cd concentrations in the soil all exceed the corresponding background value of study area. Mercury displays the highest value of geo-accumulation index (Igeo), followed by Cd, Pb and As. The pollution load index (PLI) value (>2) indicates a moderate pollution level in the study area. The chemical speciation of HMs mainly exists in residual fraction except Cd. The probabilistic health risk assessment demonstrated that the mean values of Total Carcinogenic Risk (TCR) and Hazard Index (HI) calculated with total concentration are at the unacceptable level, with a higher risk to children than adults. However, the mean values calculated with bioavailable fraction are all within the acceptable level. The mean value of TCR and HI obtained by bioavailable fraction is about 96% and 95% lower than that obtained by total concentration, respectively. Thus, this study suggested that the bioavailable fraction of HMs is a more reliable parameter for health risk assessment, while the total concentration of HMs can overestimate the true risk. The results of this study provide some insight into the speciation, bioavailability and health risks of toxic heavy metals in urban soils in those heavy industrial cities.

Contamination, Source Apportionment, and Health Risk Assessment of Heavy Metals in Farmland Soils Surrounding a Typical Copper Tailings Pond

Tailings resulting from mining and smelting activities may cause soil heavy-metal pollution and harm human health. To evaluate the environmental impact of heavy metals from tailings on farmland soils in the surrounding area, heavy metals (As, Cd, Cr, Cu, Ni, Pb, and Zn) in tailings and farmland soils in the vicinity of a typical copper tailings pond were analyzed. Contamination status, potential sources, and health risks for farmland soils were investigated. The results showed that the tailings contained a high concentration of Cu (1136.23 mg/kg). The concentrations of Cd and Cu in the farmland soils exceeded the soil quality standard. The geoaccumulation index (I_geo) indicated that the soils were moderately polluted by Cu and Cd, and slightly polluted by Ni, Cr, and Zn. The absolute principal component scores-multiple linear regression (APCS-MLR) model was applied for source apportionment. The results showed that tailings release is the main source of soil heavy-metals contamination, accounting for 35.81%, followed by agricultural activities (19.41%) and traffic emission (16.31%). The health risk assessment suggested that the children in the study region were exposed to non-carcinogenic risks caused by As, while the non-carcinogenic risk to adults and the carcinogenic risk to both adults and children were at acceptable levels. It is necessary to take effective measures to control heavy-metal contamination from tailings releases to protect humans, especially children, from adverse health risks.

Probabilistic risk assessment of heavy metals in urban farmland soils of a typical oasis city in northwest China

Previous studies lacked quantitative evaluation studies of the probability of ecology and human health risks from soil heavy metals. This study assessed heavy metal risk level by collecting topsoil samples from a typical oasis city (Wuwei) in northwest China and then quantitatively evaluating the ecological risk from heavy metals by incorporating the uncertainty of health risk model parameters into the risk assessment. This study found that anthropogenic activities have influenced the accumulation of heavy metals in the study area and that the risk of contamination of soil heavy metals was characterized as light to moderate contamination and low ecological risk. On this basis, the species sensitivity distribution curves of heavy metals were constructed using species acute toxicity data, the predicted no effect concentrations of heavy metals were derived, and a probabilistic ecological risk evaluation was conducted. The results show that the current soil environmental quality standards in China are not effective in protecting species diversity. In addition, the probability of ecological risk for Cr, Ni and As in the study area was 63.3%, 23.8% and 7.1%, however, traditional pollution assessment methods underestimate the hazard of Cr. Monte Carlo simulations have shown that the probability of the carcinogenic risk of Cr (adults: 79.4%; children: 94.5%) and As (adults: 78.9%; children: 94.0%) is high, the probability of the total carcinogenic risk exceeding 1E-06 is 99.0%, the probability of the non-carcinogenic risk is low, and the slope factor and reference dose can significantly affect the evaluation of human health risks.