Contamination and source-specific risk analysis of soil heavy metals in a typical coal industrial city, central China

Spatial distribution, source apportionment, and health risks assessment of trace elements in pre- and post-monsoon soils in the coal-mining region of North Karanpura basin, India

Coal mining activities in the North Karanpura basin have significantly increased the trace element (TE) concentrations in the soil, resulting in soil pollution and potential health risks. To assess this, 113 soil samples, along with coal, shale, and overburden rocks, were collected from open-cast mining areas during pre-monsoon (Pre-M) and post-monsoon (Post-M) seasons. Seasonal analysis revealed higher TE concentrations in the Post-M period, especially in the SE direction, followed by NE and NW, likely due to surface runoff and deposition, demonstrating temporal variability in TE distribution which corroborated from the spatial distribution maps. Positive matrix factorization (PMF) model identified four factors: mixed sources (F1Pre-M: 37.6 %; F4Post-M: 28.9 %), coal-fired emissions (F2Pre-M: 20.5 %; F3Post-M: 26.0 %), overburden rocks (F3Pre-M: 25.5 %; F2Post-M: 16.7 %), and agricultural and lithogenic origin (F4Pre-M: 16.4 %) during the Pre-M period, attributed to coal mining. Post-M sources were similar, but agricultural and lithogenic origins were replaced by atmospheric deposition (F1Post-M: 28.4 %), enhanced by monsoon effects. Carcinogenic risk assessment revealed that As, Cr, and Ni exceeded acceptable levels for children via ingestion, though adults remained within safe limits. Inhalation and dermal contact were also considered, but ingestion posed the highest risk. The hazard index (HI) via ingestion showed that children had an HI of 1.6 in Pre-M, increasing to 2.66 in Post-M, highlighting their potential vulnerability to non-carcinogenic risks, while adults stayed within safe limits. The expansion of mining areas in the study region led to decrease in vegetative areas which could affect agriculture and local communities, raising a comprehensive environmental and public health issues. These results underline the need for implementing effective biannual soil monitoring and mitigation strategies, such as phytoremediation, bioremediation, rock dust remediation, chemical amendments and improved waste management, to reduce TE contamination.

Spatial heterogeneity: Necessary and feasible for revealing soil trace elements pollution, sources, risks, and their links

The source diversity and health risk of trace elements (TEs) in soil make it necessary to reveal the relationship between pollution, source, and risk. However, neglect of spatial heterogeneity restricts the reliability of existing identification methods. In this study, spatial heterogeneity is proposed as a necessary and feasible factor for accurately dissecting the pollution-source-risk link of soil TEs. A comprehensive framework is developed by integrating positive matrix factorization, Geodetector, and risk evaluation tools, and successfully applied in a mining-intensive city in northern China. Overall, the TEs are derived from natural background (28.5 %), atmospheric deposition (25.6 %), coal mining (21.8 %), and metal industry (24.1 %). The formation mechanism of heterogeneity for high-variance TEs (Se, Hg, Cd) is first systematically deciphered by revealing the heterogeneous source-sink relationship. Specifically, Se is dominated (76.5 %) by heterogeneous coal mining (q=0.187), Hg is determined (92.6 %) by the heterogeneity of metal mining (q=0.183) and smelting (q=0.363), and Cd is caused (50.9 %) by heterogeneous atmospheric deposition (q>0.254) co-influenced by the terrains and soil properties. Highly heterogeneous sources are also noteworthy for their potential to pose extreme risks (THI=1.122) in local areas. This study highlights the necessity of integrating spatial heterogeneity in pollution and risk assessment of soil TEs.

Analysis of driving factors for potential toxic metals in major urban soils of China: a geodetetor-based quantitative study

Potential toxic metal (PTM) is hazardous to human health, but the mechanism of spatial heterogeneity of PTM at a macro-scale remains unclear. This study conducts a meta-analysis on the data of PTM concentrations in the soil of 164 major cities in China from 2006 to 2021. It utilizes spatial analysis methods and geodetector to investigate the spatial distribution characteristics of PTMs. The geographic information systems (GIS) and geodetector were used to investigate the spatial distribution characteristics of PTMs, assess the influence of natural factors (NFs) and anthropogenic factors (AFs) on the spatial heterogeneity of PTMs in urban soils, and identified the potential pollution areas of PTMs. The results indicated that the pollution levels of PTMs in urban soils varied significantly across China, with higher pollution levels in the south than in the north. Cd and Hg were the most severely contaminated elements. The geodetector analysis showed that temperature and precipitation in NFs and land use type in AFs were considered as the main influencing factors, and that both AF and NF together led to the PTM variation. All these factors showed a mutually enhancing pattern which has important implications for urban soil management. PTM high-risk areas were identified to provide early warning of pollution risk under the condition of climate change.

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.

Homology and heterogeneity of soil trace elements of coal power production bases in arid and semi-arid areas of Northwest China

Coal power activities could cause regional fluctuations of trace elements, but the distribution information of these trace elements in arid and semi-arid areas is insufficient. In this study, the soil trace elements (As, B, Be, Cd, Co, Cr, Cu, Fe, Ga, Ge, Mn, Mo, Ni, Pb, Sb, Sn, Sr, Ti, Tl, and Zn) of Ningdong Coal Power Production Base in China were monitored. Results showed that the concentrations of B, Tl, Mn, Pb, Cr, K, Cu, and Co exceeded background values. The maximum risk index reached 265.66, while the trace elements posed a cancer risk to children. Combining correlation analyses (CA), principal component analysis (PCA), and positive matrix factorization (PMF) techniques, it indicated that trace elements were mainly coming from coal combustion (34.15%), livestock farming (17.44%), traffic emissions (12.42%), and natural factors (35.99%). This study reveals the sources and potential ecological risks of soil trace elements in the Ningdong Coal and Power Production Base. It provides a scientific basis for developing targeted environmental management measures and reducing human health risks.

Receptor model-based sources and risk assessment of metals in sediment of the coastal construction-oriented aquatic system in Bangladesh

Metal pollution in sediment from construction areas raises ecological and health concerns, yet source-based sediment pollution in Bangladesh remains understudied. Our investigation focused on fifteen locations in the Kohelia River and the coastal regions near the Matarbari projects (Matarbari Power Plant, Matarbari Deep Seaport), assessing metal concentrations' sources and impacts on ecology and human well-being. Sediment quality indices indicated high Cd and Cr contamination, with sites near Matarbari projects being the most polluted. The positive matrix factorization model identified three anthropogenic sources and mixed sources. Matarbari projects contributed significantly to As (67.9 %), Mn (50.25 %), Cd (48.35 %), and Cr (41.0 %), while ship-breaking yards contributed Fe (58.0 %), Zn (55.5 %), Pb (53.8 %), and Cu (36.1 %). Ecological indices showed different impacts on aquatic life from metal pollution, but cancer risk levels stayed below the threshold set by the US Environmental Protection Agency. These findings underscore the need for targeted measures to address metal pollution.

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.

Spatial and temporal distribution characteristics and risk assessment of heavy metals in groundwater of Pingshuo mining area

Groundwater pollution in the Pingshuo mining area is strongly associated with mining activities, with heavy metals (HMs) representing predominant pollutants. To obtain accurate information about the pollution status and health risks of groundwater, 189 groups of samples were collected from four types of groundwater, during three periods of the year, and analyzed for HMs. The results showed that the concentration of HMs in groundwater was higher near the open pit, waste slag pile, riverfront area, and human settlements. Except for Ordovician groundwater, excessive HMs were found in all investigated groundwater of the mining area, as compared with the standard thresholds. Fe exceeded the threshold in 13-75% of the groundwater samples. Three sources of HMs were identified and quantified by Pearson's correlation analysis and the PMF model, including coal mining activities (68.22%), industrial, agricultural, and residential chemicals residue and leakage (16.91%), and natural sources (14.87%). The Nemerow pollution index revealed that 7.58% and 100% of Quaternary groundwater and mine water samples were polluted. The health risk index for HMs in groundwater showed that the non-carcinogenic health risk ranged from 0.18 to 0.42 for adults, indicating an acceptable level. Additionally, high carcinogenic risks were identified in Quaternary groundwater (95.45%), coal series groundwater (91.67%), and Ordovician groundwater (26.67%). Both carcinogenic and non-carcinogenic risks were greater for children than adults, highlighting their increased vulnerability to HMs in groundwater. This study provides a scientific foundation for managing groundwater quality and ensuring drinking water safety in mining areas.

Urban green space area mitigates the accumulation of heavy metals in urban soils

Despite that the heavy metals in urban soils pose a threat to public health, the critical factors that influence their concentrations in urban soils are not well understood. In this study, we conducted a survey of surface soil samples from urban green spaces in Shanghai, to analyze the concentrations of the key heavy metals. The results showed that Zn was the most abundant metal with an average concentration of 122.99 mg kg-1, followed by Pb (32.72 mg kg-1) and Cd (0.23 mg kg-1). All concentrations were found to be below the risk screening values defined by the National Environmental Quality Standards for soils of development land in China (GB36600-2018), indicating no current risk in Shanghai. However, there was a clear accumulation of heavy metals, as the mean concentrations were significantly higher than the background values. Furthermore, we explored the relationships between key heavy metals with population density, GDP and green space area. Both Spearman correlation and Random Forest analysis indicated that per capita green space area (pGSA) and population density were the most crucial factors influencing the status of heavy metals in urban soils, unlike edaphic factors e.g. SOM content in farmland soils. Specifically, there was a significantly positive linear correlation between heavy metal concentrations and population density, with correlation coefficients ranging from 0.3 to 0.4. However, the correlation with pGSA was found to be non-linear. The nonlinear regression analysis revealed threshold values between heavy metals concentrations and pGSA (e.g Zn 22.22 m2, Pb 24.92 m2, and Cd 25.92 m2), with a sharp reduction in heavy metal concentrations below the threshold and a slow reduction above the threshold. It suggests that an increase in per capita green space area can mitigate the accumulation of heavy metals caused by growing population density, but the effect is limited after the threshold. Our findings not only provide insights into the distribution patterns of heavy metals in the urban soils at the local scale, but also contribute to the urban greening at the global scale and offer guidance for city planning in the face of increasing population densities over the coming decades.

Risk assessment and source apportionment of available atmospheric heavy metal in a typical sandy area reservoir in Inner Mongolia, China

This study evaluated dry and wet deposition of atmospheric heavy metals (HMs) in a sandy area of Inner Mongolia, China, with the Dahekou Reservoir, Xilin Gol League, adopted as the study area. Monthly monitoring of atmospheric HM dry and wet deposition was conducted over one year (2021 to 2022) at 12 monitoring points, producing 144 dry and wet deposition samples, respectively. The sample contents of eight HMs (Cr, Ni, Pb, Cu, Zn, Mn, As, and Cd) were determined to estimate the fluxes of available forms of heavy metal (AHM) in dry and wet deposition. The potential ecological index (Eri), risk assessment coding (RAC), and ratio of secondary phase to primary phase (RSP) were used to evaluate the impact of atmospheric HM dry deposition on ecological security. Correlation analysis, principal component analysis, and the absolute principal component scores-multiple linear regression (APCS-MLR) receptor model were used to quantitatively analyze the sources of AHMs in atmospheric dry and wet deposition. The results showed that the study area experienced annual dry and wet deposition fluxes of AHMs of 1712.59 kg and 534.97 kg, respectively. Atmospheric heavy metal dry deposition over the entire year presented a strong ecological risk, with Cd contributing most to this risk. Risk assessment of HM speciation showed that the greatest risks of migration and transformation were for Cd and Pb. The APCS-MLR receptor model identified five and three sources of dry and wet deposition, respectively, in order of proportion of total contribution of: natural wind and sand > road traffic and coal combustion > mineral mining > other human activities > industrial soot.

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.

Quantitative risk analysis of sediment heavy metals using the positive matrix factorization-based ecological risk index method: a case of the Kuye River, China

Identifying the sources of heavy metals (HMs) in river sediments is crucial to effectively mitigate sediment HM pollution and control its associated ecological risks in coal-mining areas. In this study, ecological risks resulting from different pollution sources were evaluated using an integrated method combining the positive matrix factorization (PMF) and the potential ecological risk index (RI) model. A total of 59 sediment samples were collected from the Kuye River and analyzed for eight HMs (Zn, Cr, Ni, Cu, Pb, As, Cd, and Hg). The obtained results showed that the sediment HM contents were higher than the corresponding soil background values in Shaanxi Province. The average sediment Hg content was 3.42 times higher than the corresponding background value. The PMF results indicated that HMs in the sediments were mainly derived from industrial, traffic, agricultural, and coal-mining sources. The RI values ranged from 26.15 to 483.70. Hg was the major contributor (75%) to the ecological risk in the vicinity of the Yanjiata Industrial Park. According to the PMF-based RI model, coal-mining activities exhibited the strongest impact on the river ecosystem (48.79%), followed, respectively, by traffic (34.41%), industrial (12.70%), and agricultural (4.10%) activities. These results indicated that the major anthropogenic sources contributing to the HM contents in the sediments are not necessarily those posing the greatest ecological risks. The proposed integrated approach in this study was useful in evaluating the ecological risks associated with different anthropogenic sources in the Kuye River, providing valuable suggestions for reducing sediment HM pollution and effectively protecting river ecosystems.

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

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

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-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.

Integrative risk assessment method via combining geostatistical analysis, random forest, and receptor models for potentially toxic elements in selenium-rich soil

Revealing the spatial features and source of associated potentially toxic elements (PTEs) is crucial for the safe use of selenium (Se)-rich soils. An integrative risk assessment (GRRRA) approach based on geostatistical analysis (GA), random forest (RF), and receptor models (RMs) was first established to investigate the spatial distribution, sources, and potential ecological risks (PER) of PTEs in 982 soils from Ziyang City, a typical natural Se-rich area in China. RF combined with multiple RMs supported the source apportionment derived from the RMs and provided accurate results for source identification. Then, quantified source contributions were introduced into the risk assessment. Eighty-three percent of the samples contain Cd at a high PER level in local Se-rich soils. GA based on spatial interpolation and spatial autocorrelation showed that soil PTEs have distinct spatial characteristics, and high values are primarily distributed in this research areas. Absolute principal component score/multiple line regression (APCS/MLR) is more suitable than positive matrix factorization (PMF) for source apportionment in this study. RF combined with RMs more accurately and scientifically extracted four sources of soil PTEs: parent material (48.91%), mining (17.93%), agriculture (8.54%), and atmospheric deposition (24.63%). Monte Carlo simulation (MCS) demonstrates a 47.73% probability of a non-negligible risk (RI > 150) caused by parent material and 3.6% from industrial sources, respectively. Parent material (64.20%, RI = 229.56) and mining (16.49%, RI = 58.96) sources contribute to the highest PER of PTEs. In conclusion, the GRRRA method can comprehensively analyze the distribution and sources of soil PTEs and effectively quantify the source contribution to PER, thus providing the theoretical foundation for the secure utilization of Se-rich soils and environmental management and decision making.

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.

Heavy metals pollution of soil in central plains urban agglomeration (CPUA), China: human health risk assessment based on Monte Carlo simulation

The present study conducted the concentration evaluation, pollution assessment, source analysis, and risk assessment of heavy metals in the soil of the CPUA, China, to contribute to the smooth construction of urban agglomeration. Elevated levels of mean concentrations of cadmium (Cd), chromium (Cr), and copper (Cu) in the soils were shown compared to background values. Cu and zinc (Zn) and also lead (Pb) and Cd exhibited spatial similarity. Manganese (Mn) and Cr exhibited point source characteristics such as the concentrations at a point much higher than the surrounding area. The potential ecological risk in the northern region belonged to the moderate risk level category. Cd contributed over 90% to the potential ecological risk. The health risk among children was higher than that among adults. The major exposure pathways were different for adults and children. Exposure, as shown using Hazard Index (HI), to adults was mainly through the skin contact route, while to children was through both the skin contact and ingestion route. The primary CR (carcinogenic risk) to adults was through the inhalation route, while that to children was through the ingestion route. In both children and adults, Cr was the main contributor to HI and CR. According to the Monte Carlo simulation results, the cumulative probability of exceeding the critical value of HI for children was approximately 2.8-3.0 times that for adults. According to the sensitivity analysis results, non-carcinogenic risk prevention should begin mainly by reducing exposure duration and skin contact. The cancer risk may be reduced primarily by decreasing the exposure duration and controlling ingestion. The PMF (Positive Matrix Factorization) source analysis revealed that Pb mainly came from transportation sources. In addition, Cu, Pb, and Mn were derived mainly from agricultural sources. Cr was derived mostly from a natural source, and Cd originated mainly from an industrial source.

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.

Recent Review on Selected Xenobiotics and Their Impacts on Gut Microbiome and Metabolome

As it is well known, the gut is one of the primary sites in any host for xenobiotics, and the many microbial metabolites responsible for the interactions between the gut microbiome and the host. However, there is a growing concern about the negative impacts on human health induced by toxic xenobiotics. Metabolomics, broadly including lipidomics, is an emerging approach to studying thousands of metabolites in parallel. In this review, we summarized recent advancements in mass spectrometry (MS) technologies in metabolomics. In addition, we reviewed recent applications of MS-based metabolomics for the investigation of toxic effects of xenobiotics on microbial and host metabolism. It was demonstrated that metabolomics, gut microbiome profiling, and their combination have a high potential to identify metabolic and microbial markers of xenobiotic exposure and determine its mechanism. Further, there is increasing evidence supporting that reprogramming the gut microbiome could be a promising approach to the intervention of xenobiotic toxicity.

Method for establishing soil contaminant discharge inventory: An arsenic-contaminated site case study

The existing method to survey site pollution is generally based on soil-groundwater sampling and instrumental analysis, which enables us to access the detailed soil pollution status while lacking quantitative association with industrial activities. It is urgent to understand contaminant discharge modes and establish a discharge inventory for achieving process-targeted pollution control. This study took a 40-year phosphate fertilizer-sulfuric acid site as an example and constructed a contaminant tracing method based on on-site investigations and detailed industrial data. These investigations and data were combined to determine the characteristic pollutant of this site, arsenic. And the calculation process of four-pathway pollution modes (atmospheric deposition, wastewater, solid waste leaching, and storage dripping) is derived from the existing acceptance criteria and risk assessment guidelines. They are set to calculate the arsenic's factory-to-soil discharge flux. The absent process contaminant release information and parameters, such as discharge coefficient, were obtained from soil-groundwater pollution control standards and discharge handbooks. It was found that the high concentration of arsenic (around 1930 mg g^-1) was preponderantly caused by sulfur-iron slag and tailing leaching (96.19%), while the other pathways accounted for only 0.13% (atmospheric deposition), 3.59% (wastewater) and 0.09% (storage tank). Results were verified by the measured arsenic concentration, and the difference was +16.29%, which was acceptable. Finally, a contaminant discharge inventory was established with high-resolution spatial distribution and time-scale (historical discharge) evolution. The innovation of this study lies in the preliminary construction of a method for formulating soil discharge inventory. This study would contribute to the refined management of site pollution and reduction of source contaminants discharge. In addition, it will help infer the pollution condition of sites that are difficult to sample so as to help the government achieve precise source control.

Source apportionment and source-specific risk evaluation of potential toxic elements in oasis agricultural soils of Tarim River Basin

As rapidly developing area of intensive agriculture during the past half century, the oases in the source region of the Tarim River have encountered serious environmental challenges. Therefore, a comparative analysis of soil pollution characteristics and source-specific risks in different oases is an important measure to prevent and control soil pollution and provide guidance for extensive resource management in this area. In this study, the concentration of potential toxic elements (PTEs) was analyzed by collecting soil samples from the four oases in the source region of the Tarim River. The cumulative frequency curve method, pollution index method, positive matrix factorization (PMF) model, geographical detector method and health risk assessment model were used to analyze the pollution status and source-specific risk of potential toxic elements in different oases. The results showed that Cd was the most prominent PTE in the oasis agricultural soil in the source region of the Tarim River. Especially in Hotan Oasis, where 81.25% of the soil samples were moderately contaminated and 18.75% were highly contaminated with Cd. The PTEs in the Hotan Oasis corresponded to a moderate level of risk to the ecological environment, and the noncarcinogenic risk of soil PTEs in the four oases to local children exceeded the threshold (TH > 1), while the carcinogenic risk to local residents was acceptable (1E-06 < TCR < 1E-04). The research results suggested that the Hotan Oasis should be the key area for soil pollution control in the source region of the Tarim River, and agricultural activities and natural sources, industrial sources, and atmospheric dust fall are the priority sources that should be controlled in the Aksu Oasis, Kashgar Oasis and Yarkant River Oasis, respectively. The results of this study provide important decision-making support for the protection and management of regional agricultural soil and the environment.

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.