Quantitative source apportionment, risk assessment and distribution of heavy metals in agricultural soils from southern Shandong Peninsula of China

Multivariate analysis of potentially toxic metal contents in soil and vegetables: Enrichment, bioconcentration, translocation from soil to vegetables, and assessment of human health toxicity

The excessive accumulation of metals in agricultural soils can profoundly impact the quality of vegetables grown in contaminated soil. Understanding the bioaccumulation of these metals in vegetables is essential for assessing human exposure risks. The present study aimed to investigate the concentration of potentially toxic metals (PTMs: Fe, Mn, Cu, Zn, Al, As, Cr, Cd, and Pb) in agricultural soil and some commonly consumed vegetables (carrot, reddish, cauliflower, pumpkin, and spinach). The samples were collected from agrarian farmlands near the industrial area of Multan Road, Kasur-Pakistan. The mean contents of all metals in soil, root, and shoot samples were within the limits set by the EU, WHO, FAO, and US EPA, except for Cr in soil and Cr, Cd, and Pb in root samples. Across all analyzed vegetables, the bioconcentration factors (BCFroot and BCFshoot < 1, except As) and translocation factor (TF < 1) for all metals suggested that while these vegetables absorb metals, they generally do not accumulate or translocate them. Multivariate analysis indicated that both natural and anthropogenic activities contribute to metal contamination. The calculated hazard index (HI > 1) and cumulative cancer risk (CCR >1 × 10-3) values indicated the probability of non-carcinogenic and carcinogenic health risks for adults and children associated with the consumption of these vegetables. The findings provide critical insights for policymakers, agricultural regulators, and public health authorities to mitigate metal contamination risks and promote food safety.

Ecological Risk Assessment and Source Identification of Potential Toxic Elements in Farmland Soil of Nanyang Basin, China

This study investigated spatial distribution features and ecological risks of eight potential toxic elements (Cr, Ni, Cu, Zn, Pb, As, Cd, and Hg) in surface soil samples (0-20 cm) collected from farmland in the Nanyang Basin, China. This research also aimed to analyze the sources of these elements. Its findings revealed that the mean contents of Cr, Ni, Cu, Zn, Pb, As, Cd, and Hg were 54.35, 26.57, 25.20, 82.09, 22.17, 8.27, 0.17, and 0.13 mg·kg-1, respectively, all of which were lower than their corresponding risk screening values. However, the mean contents of Cu, Zn, Cd, and Hg exceeded the background values of Henan Province. Spatial distribution analysis revealed that Cr and Ni exhibited similar patterns, with high contents primarily observed in the western part of the research area. Generally speaking, Cu, Zn, and Pb contents were higher in the south and lower in the north, whereas Hg, As, and Cd displayed a scattered distribution of high-value areas. Ecological risk assessment indicated that Hg and Cd posed relatively high risks, with their comprehensive ecological risk indexes (RIs) predominantly classified as moderate. Source identification suggested that As primarily originates from agriculture, Cd from industry sources, Hg from coal combustion, and the remaining elements from mixed sources, including parent material, transportation, and agriculture.

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

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

Uncovering soil heavy metal pollution hotspots and influencing mechanisms through machine learning and spatial analysis

Soil heavy metal (HM) pollution is a significant and widespread environmental issue in China, highlighting the need to quantify influencing factors and identify priority concern areas for effective prevention and management. Based on published literature data of soil HM concentrations from 2000 to 2022, this study investigated the pollution characteristics and spatial distribution of eight soil HMs in China, and identified the hotspot areas of HM pollution and related influencing factors. The main findings were as follows: (1) The average concentrations of all eight HMs all exceeded their respective background values, with Cd (Igeo = 1.41) and Hg (Igeo = 0.85) showing the most serious pollution. (2) The Random forest-SHapley Additive exPlanations (RF-SHAP) model revealed that transportation and agriculture activities dominantly contribute to soil HM accumulation in China. (3) Bivariate local indicators of spatial association (LISA) based on Moran's I identified industry and transportation activities as primary drivers of HM pollution in the Yangtze River Delta and Pearl River Delta, whereas a combination of agriculture and industry activities was the main cause of pollution in Central China. This study offers valuable insights for the control and management of soil HM pollution and provides a critical reference for shaping comprehensive policies aimed at addressing HM pollution on a regional or national scale.

Spatial Distribution and Quantitative Source Identification of Heavy Metals in Soil of a Typical Industrial Park, East of China

In order to illustrate the contamination, spatial distribution and sources identification of heavy metals in Bohai New Urban District (BHNUD), a total of 333 surface soil (< 0.5 m) and 159 core soil samples (0.5-2 m) were collected. Results showed that, the mean concentrations of Cu, Ni, Pb, Cd, As and Hg in soil were 8.00-45.00 mg/kg, 10-58.00 mg/kg, 7.40-92.10 mg/kg, 0.02-0.35 mg/kg, 3.02-18.00 mg/kg and 0.002-0.21 mg/kg, respectively. The concentrations of the six heavy metals were higher than their background values to different extent, indicating the accumulation of heavy metals in this area. Cu, Cd and Ni were mainly distributed in the agricultural region; As and Hg were mainly distributed in the northeast part of the industrial area; Pb had a randomized distribution across the study area. The source identification was quantitatively carried out with the positive matrix factorization (PMF) receptor model. It showed that Pb in this area was most influenced by traffic, followed by agricultural and industrial activities. Cu and Ni in this area were mainly associated with agricultural and industrial activities; Hg was predominantly due to atmospheric deposition; As was mainly affected by industrial activities; and Cd was mainly a consequence of agricultural activities. The results will underpin the development of appropriate methods for the soil pollution control and remediation in the future.

Assessing blood metal levels in house sparrows (Passer domesticus) across urban and rural habitats in Meknes

This study investigates the concentration of heavy metals lead (Pb), cadmium (Cd), and zinc (Zn) in the blood of house sparrows (Passer domesticus) across various urban habitats in Meknes, Morocco. Fifty adult sparrows were captured from five distinct sites, including industrial, high-traffic, and rural areas. Blood samples were specifically analyzed for Pb, Cd, and Zn using Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-AES). Significant variations in metal concentrations were observed across the different sites, with the highest levels found in the industrial zone: lead (Pb) at 336.02 µg/L, cadmium (Cd) at 12.28 µg/L, and zinc (Zn) at 1736.09 µg/L. Principal component analysis (PCA) and K-means clustering identified three distinct pollution clusters: Cluster 0 (high Zn, low Pb and Cd), Cluster 1 (moderate levels of all metals), and Cluster 2 (high levels of all metals). These findings emphasize the ecological and health risks posed by urban pollution, and demonstrate the value of house sparrows as effective bioindicators.

Heavy metals in roadside soil along an expressway connecting two megacities in China: Accumulation characteristics, sources and influencing factors

Transportation is widely recognized as a significant contributor to heavy metal (HM) pollution in roadside soils. A better understanding of HM pollution in soils near expressways is crucial, particularly given the rapid expansion of expressway transportation in China in recent years. In this study, 329 roadside topsoil samples were collected along the Beijing-Tianjin Expressway, which connects two megacities in China. Chemical analysis showed that HM concentrations in the soil samples were generally below national limits. The mean pollution index (Pi) values for As, Cr, Cu, Ni, Pb, and Zn ranged from 0.94 to 1.01, while Cd and Hg exhibited slightly higher mean Pi values of 1.19 and 1.13, respectively. The Nemerow integrated pollution index values for all samples ranged from 0.71 to 4.97, with a mean of 1.26. This suggests a slight enrichment of HM above natural background levels, especially for Cd and Hg. Source apportionment using positive matrix factorization revealed that natural sources contributed the most to soil HMs (64.51 %), followed by agricultural sources (19.15 %), traffic sources (9.77 %), and industrial sources (6.57 %). The Shapley additive explanation analysis, based on the random forest model, identified soil organic carbon, deep soil HM content, altitude, total soil K2O, urbanization composite impact index, and total soil P as primary influencing factors. This indicates that the impact of transportation on roadside soils along the Beijing-Tianjin Expressway is currently relatively limited. The prominent influence of soil properties and altitude underscored the importance of "transport" and "receptor" in the soil HMs accumulation process at the local scale. These findings provide critical data and a scientific basis for decision-makers to develop policies for expressway design and roadside soil protection.

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

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

Distribution, assessment, and causality analysis of soil heavy metals pollution in complex contaminated sites: a case study of a chemical plant

To effectively prevent and control pollution from heavy metals (HMs) in urban soils, it is essential to thoroughly understand the contamination status of contaminated sites. In this study, the contamination status and sources of six HMs (As, Cu, Cr, Ni, Pb, Cd) in the soil of a decommissioned chemical plant in southern China were comprehensively analyzed. The results indicated that the average concentration of HMs followed the sequence: Cr > Pb > Cu > Ni > As > Cd. Heavy metal accumulation in the upper soil layer was predominantly observed in industrial zones and low-lying areas, with notable variations in concentration along the vertical profile. Certain sections of the site exhibited severe HM contamination, particularly with Cu levels exceeding the background value by 46.77 times. Cd presented significant ecological risks in specific areas, with an average Ecological Index of 96.09. Carcinogenic and non-carcinogenic risks were identified at three and six sampling points, respectively, with sampling point S103 demonstrating both types of risks. The causes of HM contamination were primarily attributed to anthropogenic activities. Horizontal dispersion was mainly influenced by production operations and topographical features, while vertical distribution was predominantly affected by the permeability characteristics of the strata. The causality analysis incorporating production activities and topographical factors provides novel perspectives for understanding sources of contamination at contaminated sites. The study outcomes can offer guidance for the assessment and surveying of urban industrial pollution sites.

Multimodel-based quantitative source apportionment and risk assessment of soil heavy metals: A reliable method to achieve regional pollution traceability and management

To strengthen the control of pollution sources and promote soil pollution management of agricultural land, this study constructed a comprehensive source apportionment framework, which significantly improved the reliability of potential source analysis compared with the traditional single model. The spatial distribution pattern of agricultural soil heavy metals (SHMs) content in Lintong, a typical river valley city in China, was determined and the degree of contamination was evaluated. A scientific source apportionment methodological framework was constructed through correlation analysis methods together with multiple source apportionment receptor models. Finally, the Monte Carlo simulation method was used to derive the results of the human health risk assessment (HHRA). The results revealed the following: (1) Agricultural soils were moderately and mildly polluted, accounting for 28.8 % and 71.2 % of the total number of sampling points, respectively. (2) The overall correlation of heavy metals (HMs) was strong according to the coupling analysis of the SHMs, in which a strong correlation (0.8-1) was reached among Cu, Ni, Pb, Cr and Zn, indicating that these HMs were most likely homologous or composite. (3) Multimodel analysis of the SHMs sources revealed that the first and second principal components were agricultural (41.36 %) and industrial (19.69 %) sources, respectively, and the remaining principal components were road traffic, natural factors, and atmospheric deposition or surface runoff, respectively. (4) The average comprehensive noncarcinogenic health risk indices for adults and children were 4.2259E-02 and 1.4194E-01, respectively, which were within the slight risk range, indicating that the risk caused by SHMs to the human body can be almost negligible. This study adopted a mixed method to reveal the risk of SHMs pollution and its sources, which provides some reference and technical support for traceability analysis, zoning control, and health risk studies of regional pollutants and is helpful for formulating scientific management measures and targeting control policies.

Source-oriented stochastic health risk assessment of toxic metals in soil via a hybrid model and Monte Carlo simulation

Toxic metal contamination in soils poses significant hazards to the environment and human health; thus, quantitative assessment of the sources and risks of metal contaminants are urgently needed. A hybrid model that integrates the positive matrix factorization (PMF) and random forest (RF) methods was proposed to quantify the sources of toxic metals in soils by combining diverse environmental variables (source proxies) in this study. In addition, a health risk assessment and Monte Carlo simulations were integrated to estimate the source-oriented stochastic health risk. The results suggested that, except for Ni, which exhibited moderate contamination, other toxic metals (As, Cd, Cr, Hg and Pb) presented slight contamination. Four sources (agricultural activities loaded heavily by As, atmospheric deposition loaded heavily by Hg and Pb, natural sources and mining activities loaded heavily by Cr and Ni, and industrial activities loaded heavily by Cd) were defined and explained 23.44 %, 26.65 %, 30.13 % and 19.78 % of the total variance in toxic metals, respectively. The principal route of exposure (i.e., ingestion), the population at highest risk (i.e., children), and the most hazard-inducing metals (i.e., As and Cr) were determined. Agricultural activities and the combination of natural sources and mining activities demonstrated certain degrees of noncarcinogenic risk to children, with exceedance ratios of 2.20 % and 2.56 %, respectively. Additionally, the combination of natural sources and mining activities demonstrated probabilities for significant carcinogenic risk to adults and children of 0.59 % and 3.76 %, respectively. To reduce the health risks of toxic metals in soils and to protect food and ecological safety, strict regulations should be established to control the discharge of waste from mining and agricultural activities.

Spatial pattern, source apportionment, and source-oriented health risk quantifying of heavy metals in farmland soils of southern China

The contamination of heavy metal has permeated many parts of China, especially in densely populated and industrialized southern China. This study focused on the degree of pollution in farmland soil heavy metals (HMs), and its spatial distribution characteristics and source apportionment. Meanwhile, we conducted an evaluation of the health risks attributed to soil HMs and analyzed the factors that impact them. We found that the distribution of five heavy metals is mainly concentrated in the east-central and southern parts of the study area. Specifically, Cd and Hg have high levels of pollution and present potential ecological risks. The pollution sources of five HMs were analyzed utilizing positive matrix factorization. The results revealed that the contribution of different sources keeps the following order: natural source (42.42%), agricultural activities (29.93%), industrial pollution source (20.49%), and atmospheric deposition pollution (7.16%). The non-carcinogenic risks to residents were acceptable, whereas the carcinogenic risks were relatively high. Children and the elderly are more vulnerable to the negative effects of Cr, As. Using structural equation modeling, we found soil property is a vital factor affecting soil contamination, with the soil organic matter and cation exchange capacity having a relatively greater impact on heavy metals pollution. Our study provides some data reference and guidance for soil ecological protection and restoration.

Assessment of heavy metal pollution in soils of Jebba Area, Nigeria: Concentrations, source analysis and implications for ecological and human health risks

This comprehensive research investigates heavy metal contamination in the rapidly developing town of Jebba in north-central Nigeria, which is essential to the nation's economy due to its agro-allied and non-agro-allied businesses. The research focuses on soil samples, collecting and analyzing 137 surface soil samples to assess the presence of 25 distinct metals. After statistical analysis and simple mathematical models are applied to the data, the amounts of harmful metals and their probable causes are revealed. The study identifies geogenic and anthropogenic origins of toxic metals, with some elements exceeding average crustal concentrations. Non-homogeneous metal dispersion is shown in the region by spatial distribution maps. The geo-accumulation index reflects various amounts of contamination, with particular metals posing significant threats to the ecosystem. Additionally, the study compares results with worldwide studies, revealing distinct pollution patterns in Jebba. The research delves into weathering processes, employing chemical indices to quantify the level of soil weathering and uncovering a prominent role of geogenic activities in metal release. Bivariate correlation and principal component analysis indicate links and possibly common sources among heavy metals, emphasizing anthropogenic contributions. In addition, assessments of ecological and medical risks are conducted, indicating possible threats to human wellness and the ecosystem. Children, in particular, are regarded as especially vulnerable to non-carcinogenic health concerns, with various heavy metals posing potential threats through diverse exposure routes. The study emphasizes the need to implement remediation procedures to address the risks to public health and the environment related to metal pollution.

Assessment of health risks based on different populations and sources of heavy metals on agricultural lane in Tengzhou City by APCS-MLR models

To identify the sources of heavy metals in local soils and their risks to human health. This study quantified the concentrations of eight heavy metals in 504 soil samples collected in Tengzhou, China. The ecological risks of a single heavy metal (EI), a comprehensive ecological risk index (RI), and a health risk assessment model were used to evaluate the level of contamination in the city. The results of the research study indicate that there are different levels of heavy metal pollution in rural and urban agricultural areas in Tengzhou. Moreover, the spatial variability of mercury (Hg) is considerable, reaching 0.96, indicating a significant impact of anthropogenic activities. For the ecological risk, the heavy metal element with the highest EI value was mercury with a mean value of 67.22 and a peak value of 776.00. The heavy metal with the lowest mean EI value was Zn with only 1.03. Meanwhile, the average RI is only 128.59, but some areas have an RI as high as 842.2. The sources of heavy metals were identified using principal component analysis, correlation analysis, and an absolute principal component score multiple linear regression model (APCS-MLR). The non-carcinogenic risk for children, the carcinogenic risk for children, and the carcinogenic risk for adults were 1.23, 2.42×10-4 and 1.00×10-4, respectively, and these values exceeded their respective recommended values, and As and Cr had some carcinogenic hazards. Heavy metals in the soil come from natural, industrial, traffic and agricultural sources and represent 39.59%, 29.48%, 25.17% and 5.77%, respectively. The main source of heavy metals in local agricultural soils is the geological background, and the government needs to strengthen the monitoring of As and Cr in drinking water resources, as well as reduce traffic pollution and factory waste emissions to reduce Hg in soils.

Prospective Study on the Association Between Blood Heavy Metal Levels and Pulmonary Function in University Students from a Medical College in Shandong Province, China

Background

This study aimed to examine the blood concentrations of selected heavy metals, their corresponding pulmonary functions, and their interrelationship with university students.

Methods

This prospective study, conducted from September 2019 to September 2020, encompassed 593 university students. Participants completed self-administered questionnaires regarding demographic factors and underwent lung function testing and blood mercury analysis at two distinct intervals: an initial assessment and a follow-up examination. Pulmonary function was assessed using Forced Vital Capacity, Forced Expiratory Volume in one second, and Peak Expiratory Flow. The blood concentrations of various heavy metals were determined through inductively coupled plasma mass spectrometry.

Results

Notable disparities in pulmonary function emerged among university students when categorized by gender, Body Mass Index, physical activity, and seafood consumption frequency, all showing statistical significance (p<0.05). Blood levels of Pb, Mn, Co, and Ni exhibited diverse patterns and extents of correlation with pulmonary function (p<0.05 in each instance). Specifically, a positive correlation was observed with blood Pb levels, while Mn, Co, and Ni levels were inversely correlated with pulmonary function (p<0.01 for both observations).

Conclusion

This study uncovered significant and complex relationships between the blood concentrations of individual heavy metals and pulmonary function in university students. These findings highlight the need for further research to elucidate these associations in greater detail.

Geochemical baseline establishment and accumulation characteristics of soil heavy metals in Sabaochaqu watershed at the source of Yangtze River, Qinghai-Tibet Plateau

The establishment of soil geochemical baseline and heavy metal pollution assessment in the Qinghai-Tibet Plateau is of great significance for guiding environmental management in the high-cold and high-altitude regions. A total of 126 topsoil samples (0-20 cm) were collected and the contents of Cu, Pb, Zn, Ni, Cr, Cd, As and Hg were determined in the Sabaochaqu basin of the Tuotuo River, the source of the Yangtze River, in the Tibetan Plateau. The baseline values of 8 heavy metals were determined by mathematical statistics, iterative 2times standard deviation method, cumulative frequency and reference element standardization, and the soil heavy metal pollution in the study area was assessed by enrichment factor method and pollution index method. The results showed that the average contents of As, Cd, Cr, Cu, Hg, Ni, Pb and Zn were 31.84, 0.29, 66.07, 17.35, 0.021, 27.86, 49.35 and 88.56 mg/kg, respectively. Baseline values were 22.24, 0.217, 64.16, 15.69, 0.0191, 26.46, 34.91, and 68.62 mg/kg, respectively. There is a great difference between the baseline value of soil heavy metals in study area and the Xizang soil background value, especially the baseline value of Cd was 2.68 times of its background value. The results of the pollution evaluation based on the baseline values showed that the 8 heavy metals were slightly enriched, and the overall pollution status was light pollution, and measures should be taken to control and manage them. The research results can provide a reference value for the evaluation of soil heavy metal pollution in the source region of the Yangtze River, and also provide a theoretical basis for the construction of soil heavy metal baseline values in similar high-cold and high-altitude regions.

Health Risk Assessment of Heavy Metals in Agricultural Soils Based on Multi-Receptor Modeling Combined with Monte Carlo Simulation

The spatial characteristics, pollution sources, and risks of soil heavy metals were analyzed on Hainan Island. The results showed that the heavily polluted points accounted for 0.56%, and the number of mildly and above polluted points accounted for 15.27%, respectively, which were mainly distributed in the northern part of the study area. The principal component analysis-absolute principal component score-multiple linear regression (APCS-MLR) and the positive matrix factorization (PMF) revealed four sources of heavy metals: agricultural pollution sources for cadmium, (Cd), industrial and mining pollution sources for arsenic, (As), transportation pollution sources for zinc and lead (Zn and Pb), and natural pollution sources for chromium, nickel, and copper (Cr, Ni, and Cu). The human health risk assessment indicated that the average non-carcinogenic risk (HI) for both adults and children was within the safe threshold (<1), whereas Cr and Ni posed a carcinogenic risk (CR) to human health. In addition, the total non-carcinogenic risk (THI) indicated that heavy metals posed a potential non-carcinogenic risk to children, while the total carcinogenic risk (TCR) remained relatively high, mainly in the northern part of the study area. The results of the Monte Carlo simulation showed that the non-carcinogenic risk (HI) for all heavy metals was <1, but the total non-carcinogenic risk index (THI) for children was >1, indicating a potential health risk above the safe threshold. Meanwhile, nearly 100% and 99.94% of the TCR values exceeded 1 × 10-4 for children and adults, indicating that Cr and Ni are priority heavy metals for control. The research results provide the necessary scientific basis for the prevention and control of heavy metals in agricultural soils.

Cumulative characteristics and ecological risk source analysis of soil potentially toxic elements in the northern margin of the Tibetan Plateau

To understand the soil toxic and hazardous elements content, pollution level, and ecological risk status in the northern margin of the Tibetan Plateau, we collected and analyzed 8273 sets of surface soil samples. Evaluations were conducted using the single-factor pollution index, geo-accumulation, pollution load, and potential ecological risk indices, and source identification correlation and principal component analysis. The results revealed that, compared with the background levels in China, the accumulation of soil arsenic, cadmium, nickel, and chromium was greater in the surface soil of the study area. Additionally, in comparison with Qinghai Province, more mercury accumulated in the surface soil of the study area and owing to the influence of anthropogenic activities. Benchmarking against soil environmental quality standards, the study area exhibited pollution control zones primarily dominated by arsenic and cadmium (3.9%). The spatial distribution revealed distinct zones: a ridge mountain type characterized by arsenic-cadmium-chromium-nickel, a Daban mountain type with solely cadmium presence, and a Longyangxia-Jianzha South type dominated by arsenic. Compared with the Qinghai Province soil background values, evaluations using the Pollution loading index, Geological Cumulative Index, and Potential Ecological Risk Index methods revealed varying degrees of potentially toxic element content exceedance. From an ecological risk perspective, the individual element with the highest potential ecological risk coefficients were mercury, followed by cadmium and arsenic; however, the region's overall ecological risk index was classified as low. Three distinct sources were identified: natural sources leading to high background levels of chromium, nickel, copper, zinc, and mercury; mixed natural and industrial/agricultural sources contributing to elevated cadmium levels; and human activity-related mercury enrichment. Based on the evaluation results, synergistic monitoring of soil and biota in naturally occurring risk zones is recommended to ensure the safety of agricultural and pastoral products. Additionally, ecological impact assessments and pollution source mitigation studies should be conducted in regions influenced by human activities to curb the further degradation of soil ecological quality.

Source identification and migration fate of heavy metals of soil-groundwater system in a thousand-year cultivation region

Pollution of farmland by heavy metals threatens food security and human health. In addition, heavy metals in soil could infiltrate into groundwater to influence the water quality and safety of drinking water. However, the relationship between heavy metal pollution in soil and groundwater is still not clear. In this study, we investigated the soil and groundwater in the Guanzhong Plain region, which is a significant grain production base in China, and determined the spatial distributions, ecological risk, sources, and migration fates of heavy metals (As, Cd, Cr, Cu, Ni, Pb, and Zn). The results showed that the mean values (0-20 cm) in the soil were 19.57 mg kg-1 for As, 0.71 mg kg-1 for Cd, 69.65 mg kg-1 for Cr, 21.97 mg kg-1 for Cu, 28.67 mg kg-1 for Ni, 17.54 mg kg-1 for Pb, and 73.77 mg kg-1 for Zn, and the corresponding mean values in groundwater were 1.2, 0.04, 4.69, 0.15, 0.07, 0.3, and 3.6 μg L-1, respectively. The mean values for As, Cd, Cr, Pb, and Zn in soil exceeded the background values, and the mean values for As, Cd and Pb exceeded those in groundwater. Positive matrix factorization models identified five sources (fertilizers and organic fertilizers, natural sources, pesticides and herbicides, industrial activities, and sedimentation caused by transportation) for heavy metal pollution in soil and four sources (industry activity, atmospheric sedimentation caused by transportation, natural sources, and agriculture) for heavy metal pollution in groundwater. The soil particle composition and soil organic carbon content were important factors that affected the vertical distribution of heavy metals in the soil. The migration modes (convection and diffusion) were not found for all heavy metals. These results help to understand the relationships between heavy metals in soil and groundwater in farmland ecosystems regionally.

Source-specific ecological risk analysis and critical source identification of heavy metal(loid)s in the soil of typical abandoned coal mining area

Long-term coal mining activities in abandoned coal mining areas have resulted in the migration of large quantities of heavy metals into the surrounding soil environment, posing a threat to the regional ecological environment. This study focuses on the surface soil collected from a typical abandoned coal mining area. Methods such as the pollution index (PI) and potential ecological risk index (RI) were used to comprehensively evaluate the pollution levels and ecological risks of soil heavy metals. Geostatistical analysis and the APCS-MLR model were used to quantify the sources of soil heavy metals, and Nemerow integrated ecological risk (NIRI) model was coupled to apportion the ecological risks from different pollution sources. The results indicate that the average concentrations of Cd, As, and Zn are 4.58, 2.44, and 1.67 times the soil background values, respectively, while the concentrations of other heavy metals are below the soil background values. The soil of study area is strongly polluted by heavy metals, with the pollution level and ecological risk of Cd being significantly higher than those of other heavy metals. The NIRI calculation results show that the overall comprehensive ecological risk level is considerable, with sample points classified as relatively considerable, moderate, and low at 60.53 %, 36.84 %, and 2.63 %, respectively. The sources of soil heavy metals can be categorized into four types: traffic activities, natural sources, coal gangue accumulation, and a combined source of coal mining and agricultural activities, with contribution rates of 35.3 %, 36.1 %, 19.5 %, and 9.1 %, respectively. The specific source ecological risk assessment results indicate that coal gangue accumulation contributes the most to ecological risk (36.4 %) and should be prioritized for pollution control, with Cd being the priority control element for ecological risk. The findings provide theoretical support for the refined management of soil heavy metal pollution in abandoned coal mining areas.

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

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

High-efficiency combination washing agents with eco-friendliness simultaneously removing Cd, Cu and Ni from soil of e-waste recycling site: A lab-scale experiment

Soil washing technology plays an important role in the removal of heavy metals, and the efficacy of this process depends on the washing agent used. Due to the difficulty in treating soils contaminated by multiple heavy metals, there is still a need for further exploration of efficient washing agents with low environmental impact. Although single washing agents, such as chelators, can also effectively remove heavy metals from soil, combining efficient washing agents and determining their optimal washing conditions can effectively improve their removal efficiency for multiple heavy metals in soil simultaneously. Based on the previous research, the present study was carried out to combine different types of washing agents to remediate contaminated soils at a commonly e-waste recycling site. The objectives were to investigate their efficient washing conditions and assess the impact of the washing process on the speciation distribution and pollution level associated with heavy metals in soil. The results showed that the combination of HEDP (1-hydroxyethylidene-1,1-diphosphonic acid) and FeCl3 at a ratio of 6:4 exhibited the most effective removal of Cd, Cu and Ni from the contaminated soil at an e-waste recycling site. Under optimal washing conditions, with a soil-to-liquid ratio of 1:20 and a washing time of 48 h, the removal rates of Cd, Cu and Ni were 96.72%, 69.91% and 76.08%, respectively. It needed to be emphasized that the combination washing agents were able to remove most of the acid-soluble, reducible and oxidizable fractions of heavy metals, and even the removal rates of the stable residual fraction (e.g., of Cd) was at a relatively high level. In addition, the washing process significantly reduced the pollution level associated with heavy metals in soil. This study aid in the development of combined efficient washing agents and explores optimal washing strategies for the remediation of Cd, Cu, and Ni-contaminated soil at e-waste recycling sites. The findings may play a role in enhancing the remediation capabilities for soils contaminated with multiple heavy metals, due to its characteristics of and high-efficiency and environmental friendliness.

Spatial distribution, compositional pattern, and source apportionment of colloidal trace metals in the coastal water of Shandong Peninsula, northeastern China

The Shandong Peninsula (SP) is the largest peninsula in China hosting rich economic and agricultural activities. In this study, we investigated the behavior of dissolved Mn, Fe, Cu, Zn, Cd, and Pb and their colloidal phases in the coastal and estuarine areas of SP. Pb and Zn had the highest contamination factors of 0.22-10.15 and 0.90-4.41, respectively. The <1 kDa accounted for 23-57 % of the total dissolved phase. Mn, Fe, Cu, Zn, Cd, and Pb were more likely to bind to 100 kDa-0.45 μm colloids (21-57 %). For colloidal Fe and Cu, the adsorption-release behavior had more significant effects on their dynamics. In contrast, the changes in colloidal Mn, Cd, and Pb were mainly controlled by the combined influence of temperature, dissolved oxygen, and microbial activity. However, the 1-3 kDa Zn exhibited a greater pH-dependent dispersion and was significantly positively correlated with it.

Heavy metal spatial distribution, source analysis, and ecological risks in the central hilly area of Hainan Island, China: results from a high-density soil survey

The presence of heavy metals in soil has gained considerable attention due to their potential risks to ecosystems and human health. In this study, a thorough soil investigation was performed in the hilly region of central Hainan, which was formerly regarded as an area with the highest ecological environmental quality. A total of 7094 soil samples were systematically collected with high density over a large area. Simultaneously, a detailed investigation was conducted on the surrounding environment of each sampling point, including environmental factors such as soil, land use and crop types. The soil samples were analysed for heavy metals, pH, organic matter, and other parameters. The soil heavy metal pollution level, ecological risk and health risk were evaluated using the geo-accumulation index and the potential ecological risk index. The findings showed that the average contents of the heavy metals As, Cd, Cr, Cu, Hg, Ni, Pb and Zn in the soil were 1.68, 0.042, 24.2, 6.49, 0.0319, 7.06, 29.6 and 49.8 mg·kg-1 respectively. Except for Hg, the mean values of the other heavy metals were either lower than or similar to the background values of Hainan. Also, only a few localised areas showed contamination by heavy metals. The primary sources of heavy metals, identified by a positive matrix factorisation model, could be categorised into four types: natural sources related to the soil formation process from acidic intrusive rocks (such as granite); natural sources primarily influenced by atmospheric deposition; anthropogenic sources associated with agricultural activities; and natural sources related to the soil formation process from middle-mafic intrusive rocks and black shales. The correlation analysis and variance analysis findings suggested that the content of heavy metals in the soil was primarily associated with the parent rock. The study area generally had low heavy metal levels and was not significantly polluted. However, agricultural activities still affected the enrichment of heavy metals. Therefore, it is imperative to remain vigilant about the ecological risks linked to soil heavy metals while continuing land development and expanding agricultural activities in the future. These findings indicate that conducting high-density soil surveys can enhance our understanding of regional soil heavy metals and enable reliable recommendations for agricultural planning. Whether in areas with low pollution risk or potential pollution risk, it is recommended that high-density soil surveys be conducted provide scientific guidance for further agricultural development.

Pollution sources and risk assessment of potentially toxic elements in soils of multiple land use types in the arid zone of Northwest China based on Monte Carlo simulation

The concentration of potentially toxic elements (PTEs) in soils of different land-use types varies depending on climatic conditions and human. Topsoil samples were collected in Northwest China to investigate PTE pollution and risk in different land uses, and thereby estimate the risk of various pollution sources. The results showed that human activity had an impact on PTE concentrations in the study area across all land use types, with farmland, grassland, woodland, and the gobi at moderate pollution levels and the desert at light pollution levels. Different PTE sources pose different risks depending on the land-use type. Apart from deserts, children are exposed to carcinogenic risk from a variety of sources. A mixed natural and agricultural source was the main source of public health risk in the study area, contributing 38.7% and 39.0% of the non-carcinogenic and 40.7% and 35.5% of the carcinogenic risks, respectively. Monte Carlo simulations showed children were at a higher health risk from PTEs than adult s under all land uses, which ranked in severity as farmland > woodland > grassland > gobi > desert. As and Ni has a higher probability of posing both a non-carcinogenic and a carcinogenic risk to children. Sensitivity analysis showed that the contribution of parameters to the assessment model of PTEs exhibited the following contribution pattern: concentration > average body weight > ingestion rate > other parameters. The PTEs affecting the risk assessment model were not common among different land use types, where the importance distribution pattern of each parameter was basically the same in woodland, grassland, and farmland, and Ni contributed the most to carcinogenic risk. However, Cr contributed the most to the carcinogenic risk in the desert and gobi.

Ecological risk and spatial distribution, sources of heavy metals in typical purple soils, southwest China

The identification and quantification of the ecological risks, sources and distribution of heavy metals in purple soils are essential for regional pollution control and management. In this study, geo-accumulation index (Igeo), enrichment factor (EF), pollution index (PI), potential ecological risk index (RI), principal component analysis (PCA) model and geographical detector (GD) were combined to evaluate the status, ecological risk, and sources of heavy metals (HMs) in soils from a typical purple soil areas of Sichuan province. The results showed that the average contents of As, Cd, Cr, Cu, Hg, Ni, Pb and Zn in purple soil were 7.77, 0.19, 69.5, 27.9, 0.077, 30.9, 26.5 mg/kg and 76.8 mg/kg, and the Igeo, EF and RI of topsoil Hg and Cd in designated area was the highest, and the average contents of Hg and Cd in topsoil were obviously greater than respective soil background value in Sichuan province and purple soil. The hot spots for the spatial distribution of 8 HMs were mainly focused in the southwest and northeast of the designated area, and there were also significant differences for 8 HMs distribution characteristics in the profile soil. Cu comes from both anthropogenic and natural sources, Zn, Ni and Cr mainly come from natural sources, but As, Pb, Hg and Cd mainly derived from human activities. GD results showed that soil texture (X18), altitude (X4), total nitrogen (TN), clay content (X3), sand content (X2) and silt content (X1) had the greatest explanatory power to 8 HMs spatial differentiation.This study provides a reference for understanding the status and influencing factors of HM pollution in typical purple soil, and lays a theoretical foundation for the environmental treatment of purple soil in China.

Heavy Metal(oid)s Contamination and Potential Ecological Risk Assessment in Agricultural Soils

Soil pollution caused by heavy metal(oid)s has generated great concern worldwide due to their toxicity, persistence, and bio-accumulation properties. To assess the baseline data, the heavy metal(oid)s, including manganese (Mn), iron (Fe), Cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), arsenic (As), lead (Pb), mercury (Hg), chromium (Cr), and cadmium (Cd), were evaluated in surface soil samples collected from the farmlands of Grand Forks County, North Dakota. Samples were digested via acid mixture and analyzed via inductively coupled plasma mass spectrometry (ICP MS) analysis to assess the levels, ecological risks, and possible sources. The heavy metal(oid) median levels exhibited the following decreasing trend: Fe > Mn > Zn > Ni > Cr > Cu > Pb > Co > As > Cd > Hg. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) suggested the main lithogenic source for the studied metal(oid)s. Metal(oid) levels in the current investigation, except Mn, are lower than most of the guideline values set by international agencies. The contamination factor (Cf), geo accumulation index (Igeo) and enrichment factor (EF) showed considerable contamination, moderate contamination, and significant enrichment, respectively, for As and Cd on median value basis. Ecological risk factor (Er) results exhibited low ecological risk for all studied metal(oid)s except Cd, which showed considerable ecological risk. The potential ecological risk index (PERI) levels indicated low ecological risk to considerable risk. Overall, the results indicate the accumulation of As and Cd in the study area. The high nutrients of the soils potentially affect their accumulation in crops and impact on consumers' health. This drives the impetus for continued environmental monitoring programs.

Source identification and driving factor apportionment for soil potentially toxic elements via combining APCS-MLR, UNMIX, PMF and GDM

The contamination and quantification of soil potentially toxic elements (PTEs) contamination sources and the determination of driving factors are the premise of soil contamination control. In our study, 788 soil samples from the National Agricultural Park in Chengdu, Sichuan Province were used to evaluate the contamination degree of soil PTEs by pollution factors and pollution load index. The source identification of soil PTEs was performed using positive matrix decomposition (PMF), edge analysis (UNMIX) and absolute principal component score-multiple line regression (APCS-MLR). The geo-detector method (GDM) was used to analysis drivers of soil PTEs pollution sources to help interpret pollution sources derived from receptor models. Result shows that soil Cu, Pb, Zn, Cr, Ni, Cd, As and Hg average content were 35.2, 32.3, 108.9, 91.9, 37.1, 0.22, 9.76 and 0.15 mg/kg in this study area. Except for As, all are higher than the corresponding soil background values in Sichuan Province. The best performance of APCS-MLR was determined by comparison, and APCS-MLR was considered as the preferred receptor model for soil PTEs source distribution in the study area. ACPS-MLR results showed that 82.70% of Cu, 61.6% of Pb, 75.3% of Zn, 91.9% of Cr and 89.4% of Ni came from traffic-industrial emission sources, 60.9% of Hg came from domestic-transportation emission sources, 57.7% of Cd came from agricultural sources, and 89.5% of As came from natural sources. The GDM results showed that distance from first grade highway, population, land utilization and total potassium (TK) content were the main driving factors affecting these four sources, with q values of 0.064, 0.048, 0.069 and 0.058, respectively. The results can provide reference for reducing PTEs contamination in farmland soil.

Differentiating anthropogenic effects from natural metal(loid) levels in residential soil near a zinc smelter in South Korea

Metal(loid)s pose a significant hazard due to inherent toxicity. Individuals are particularly exposed to metal(loid)s in soil through direct or indirect contact. Identifying metal(loid) sources in soil is required for exposure mitigation to anthropogenic metal(loid)s, while metal(loid)s are natural constitutes of soil. Metal(loid) concentrations and Pb isotopes were determined in residential soil profiles impacted by a Zn smelter to distinguish the anthropogenic effect from natural levels. One hundred sixty-nine core soil samples were collected from depths down to 5.5 m below ground level at 19 sites and were divided into Zn-Cd-As- and As-contaminated groups based on the worrisome level (WL) of soil contamination. The Zn-Cd-As-contaminated group (n = 62) was observed at depths < 1 m, showed high Zn levels (mean of 1168 mg/kg) and Cd and As frequently exceeding WLs, and had low 206Pb/207Pb ratios close to the Zn smelter. In contrast, the As-contaminated group (n = 96) was observed at depths > 1 m, did not have other metals exceeding WLs, and showed a wide range of 206Pb/207Pb ratios far away from the Zn smelter. The results indicated that the pollution sources of Zn-Cd-As- and As-contaminated soils were fugitive dust emissions from smelter stacks and geology, respectively. The metal(loid)s in host rock set geochemical baselines in soil profiles, while smelting activities affected the upper layers over 50 years. This study demonstrated the effectiveness of utilizing the vertical distribution of metal(loid) concentrations and Pb isotopes in soil profiles for distinguishing between anthropogenic and geogenic origins, in combination with baseline assessment.

Spatial distribution characteristics of soil heavy metals in Sabao Chaqu watershed of Tuotuo river, Qinghai-Tibet Plateau based on geographic detector

The Qinghai-Tibet Plateau belongs to the area of extremely fragile environment and sensitive to human activities. In recent years, more and more human interference has been detected in this area. In this study, 128 surface soil samples were collected from the Sabao Chaqu watershed of the Tuotuo river at the source of the Yangtze River on the Qinghai-Tibet Plateau. The soil pollution status and spatial distribution characteristics of Cd, Hg, As, Cu, Pb, Cr, Zn and Ni were evaluated by soil accumulation index, enrichment factor, pollution index and geographical detector. The results showed that the average contents of As, Cd, Pb and Zn in the study area were 1.2-3.64 times higher than soil background values of Tibet, while the contents of Hg, Cr, Cu and Ni were lower than the background values, while the average content of As was higher than the soil pollution risk screening value (GB15618-2018), and the pollution index showed that As was in a low pollution state, while the other 7 heavy metals were in a safe state. There were significant differences in the spatial distribution of 8 heavy metals and there was a significant correlation with soil properties and distance factors. Factor detection showed that natural factors had the strongest explanatory power to the contents of As, Cd, Cr, Cu and Ni, distance from the lake and soil Sc content had the strongest explanatory power to Hg content, and anthropogenic factors had the strongest explanatory power to Pb content. Interaction detection revealed that the q values of the strongest interaction explanatory power for As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn were 2.81, 4.30, 1.26, 2.47, 2.33, 1.59, 6.37, and 5.08 times higher than their strongest factor detection explanatory power, respectively. The interaction between anthropogenic factors and other factors has an important influence on the spatial differentiation of heavy metals in the study area. Risk detection showed that the average contents of As, Cd, Cr, Cu, Hg, Ni, Pb and Zn were the highest in the subregions of MgO, TS, Sc, X6, X13, MgO, TN and X4, respectively. Comprehensive study shows that the spatial differentiation of As, Cd, Cr, Cu, Ni and Zn is mainly affected by natural factors, but there are also some anthropogenic factors, the spatial differentiation of Hg is affected by both natural factors and atmospheric deposition, and the spatial distribution characteristics of Pb are mainly affected by anthropogenic factors.

Assessing metal(loid)s-Induced long-term spatiotemporal health risks in Coastal Regions, Bay of Bengal: A chemometric study

Despite sporadic and irregular studies on heavy metal(loid)s health risks in water, fish, and soil in the coastal areas of the Bay of Bengal, no chemometric approaches have been applied to assess the human health risks comprehensively. This review aims to employ chemometric analysis to evaluate the long-term spatiotemporal health risks of metal(loid)s e.g., Fe, Mn, Zn, Cd, As, Cr, Pb, Cu, and Ni in coastal water, fish, and soils from 2003 to 2023. Across coastal parts, studies on metal(loid)s were distributed with 40% in the southeast, 28% in the south-central, and 32% in the southwest regions. The southeastern area exhibited the highest contamination levels, primarily due to elevated Zn content (156.8 to 147.2 mg/L for Mn in water, 15.3 to 13.2 mg/kg for Cu in fish, and 50.6 to 46.4 mg/kg for Ni in soil), except for a few sites in the south-central region. Health risks associated with the ingestion of Fe, As, and Cd (water), Ni, Cr, and Pb (fish), and Cd, Cr, and Pb (soil) were identified, with non-carcinogenic risks existing exclusively through this route. Moreover, As, Cr, and Ni pose cancer risks for adults and children via ingestion in the southeastern region. Overall non-carcinogenic risks emphasized a significantly higher risk for children compared to adults, with six, two-, and six-times higher health risks through ingestion of water, fish, and soils along the southeastern coast. The study offers innovative sustainable management strategies and remediation policies aimed at reducing metal(loid)s contamination in various environmental media along coastal Bangladesh.

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

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

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

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

The adsorption-diffusion model and biomimetic simulation reveal the switchable roles of silicon in regulating toxic metal uptake in rice roots

Soil contamination by heavy metals has become a serious threat to global food security. The application of silicon (Si)-based materials is a simple and economical method for producing safe crops in contaminated soil. However, the impact of silicon on the heavy-metal concentration in plant roots, which are the first line in the chain of heavy-metal entering plants and causing stress and the main site of heavy-metal deposition in plants, remains puzzling. We proposed a process-based model (adsorption-diffusion model) to explain the results of a collection of 28 experiments on alleviating toxic metal stress in plants by Si. Then we evaluated the applicability of the model in Si-mitigated trivalent chromium (Cr[III]) stress in rice, taking into account variations in experimental conditions such as Cr(III) concentration, stress duration, and Si concentration. It was found that the adsorption-diffusion model fitted the experimental data well (R2 > 0.9). We also verified the binding interaction between Si and Cr in the cell wall using SEM-EDS and XPS. In addition, we designed a simplified biomimetic device that simulated the Si in cell wall to analyze the dual-action switch of Si from increasing Cr(III) adsorption to blocking Cr(III) diffusion. We found that the adsorption of Cr(III) by Si decreased from 58% to 7% as the total amount of Cr(III) increased, and finally the diffusion blocking effect of Si dominated. This study deepens our understanding of the role of Si in mitigating toxic metal stress in plants and is instructive for the research and use of Si-based materials to improve food security.

An integrated framework for source apportionment and spatial distribution of mercury in agricultural soil near a primary ore mining site

Mercury (Hg) is a global environmental concern that affects both humans and ecosystem. The comprehensive understanding of sources and dynamics is crucial for facilitating targeted and effective control strategies. Herein, a robust approach integrating Multivariate Statistics, Geostatistics, and Positive Matrix Factorization (PMF) was employed to quantitatively elucidate the distribution and sources of Hg in agricultural lands. Results indicated elevated Hg concentrations in the land with 74.46% of soils, including 84.85% of topsoil, 69.70% of subsoil, and 67.31% of deepsoil, exceeding risk screening value. Geoaccumulation Index of Hg in soil surpassed level Ⅱ with more than 50% of Hg in the residual fraction regardless of the layer or location. The levels of Hg in surface water for irrigation exhibited a negative correlation with the distance from the mine and a positive correlation with that in sediment (R2>0.78, p < 0.01), suggesting the downstream migration and remobilization from sediment. Source apportion revealed that human activities as primary contributors despite high variability across locations and soil layers. Contributions to downstream soil Hg from Natural Background (NB), Primary Ore Mining (OM), Agricultural Practices (AP), and Wastewater Irrigation (WI) were 15.5%, 83.1%, 1.3%, and 0.1%, respectively. A reliable approach for source apportionment of Hg in soil was suggested, demonstrating potential applicability in the risk management of Hg-contaminated sites.

Integrated assessment of the pollution and risk of heavy metals in soils near chemical industry parks along the middle Yangtze River

Industrialization in riparian areas of critical rivers has caused significant environmental and health impacts. Taking eight industrial parks along the middle Yangtze River as examples, this study proposes a multiple-criteria approach to investigate soil heavy metal pollution and associated ecological and health risks posed by industrial activities. Aiming at seven heavy metals, the results show that nickel (Ni), cadmium (Cd), and copper (Cu) exhibited the most significant accumulation above background levels. The comprehensive findings from Pearson correlation analysis, cluster analysis, principal component analysis, and industrial investigation uncover the primary sources of Cd, arsenic (As), mercury (Hg), and lead (Pb) to be chemical processing, while Ni and chromium (Cr) are predominantly derived from mechanical and electrical equipment manufacturing. In contrast, Cu exhibits a broad range of origins across various industrial processes. Soil heavy metals can cause serious ecological and carcinogenic health risks, of which Cd and Hg contribute to >70 % of the total ecological risk, and As contributes over 80 % of the total health risk. This study highlights the importance of employing multiple mathematical and statistical models in determining and evaluating environmental hazards, and may aid in planning the environmental remediation engineering and optimizing the industry standards.

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

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

WITHDRAWN: Trace metals translocation from soil to plants: Health risk assessment via consumption of vegetables in the urban sprawl of a developing country

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Optimizing the development of contaminated land in China: Exploring machine-learning to identify risk markers

Often available for use, previously developed land, which includes residential and commercial/industrial areas, presents a significant challenge due to the risk to human health. China's 2018 release of health risk assessment standards for land reuse aimed to bridge this gap in soil quality standards. Despite this, the absence of representative indicators strains risk managers economically and operationally. We improved China's land redevelopment approach by leveraging a dataset of 297,275 soil samples from 352 contaminated sites, employing machine learning. Our method incorporating soil quality standards from seven countries to discern patterns for establishing a cost-effective evaluative framework. Our research findings demonstrated that detection costs could be curtailed by 60% while maintaining consistency with international soil standards (prediction accuracy = 90-98%). Our findings deepen insights into soil pollution, proposing a more efficient risk assessment system for land redevelopment, addressing the current dearth of expertise in evaluating land development in China.

Uncovering the impact of mega-scale shipbreaking yards on soil and crop quality in Bangladesh: A spatiotemporal dynamics and associated health risks of metal/loid contamination

The uncontrolled release of harmful metal/loids from mega-scale shipbreaking activities in Bangladesh is a significant concern. This study investigated the impact of shipbreaking activities on soil and crop quality and human health in relation to metal/loid contamination. This work covered an area of 1221 km2 surrounding the shipbreaking yards in Chittagong during the wet and dry seasons between 2019 and 2020. Amongst the sixteen elements measured, the concentrations of Pb, Cd, As, V, Cr, Mn, Cu, Zn, Fe, Co, Ni, and Sn in the soil, rice, and vegetables from the four exposure sites were significantly higher compared to the control site in both seasons. Soil pollution indices indicated moderate to higher contamination levels of Pb, Zn, Cd, As, and Se in 30-50% of soil, supporting their accumulation in food crops. Source apportionment analysis identified uncontrolled shipwrecking operations as the primary anthropogenic activity mainly contributing to metal/loid pollution. Health risk analysis showed inorganic arsenic (estimated), Cd, and Pb in food crops could pose potential health threats to the general population. Spinach leaf and gourd were identified as the highest-risk contributing vegetables in the dry and wet seasons. These findings help to inform management strategies to protect agroecosystems and public health.

Health Risk Assessment of Lead, Cadmium, and Arsenic in Leafy Vegetables in Tehran, Iran: the Concentration Data Study

Absorption of heavy and toxic metals causes their accumulation in the edible parts of vegetables. Pollutants such as heavy metals have directly affected the health of society and contributed to emerging diseases in recent years. The current study aimed to detect heavy metals (Pb, Cd, As) in highly consumed leafy vegetables provided from the Tehran market. Four types of vegetables, including dill, parsley, cress, and coriander were selected and 64 samples were randomly collected from fruit and vegetable markets in different regions of Tehran in August and September 2022. Then, samples were analyzed by the ICP-OES system, and health risk assessment was conducted using non-carcinogenic and carcinogenic approach. The range of Pb concentration was 54-314, < LOQ-289, < LOQ-230, and < LOQ-183 μg/kg for dill, cress, parsley, and coriander, respectively. The high mean concentrations of Pb belong to the dill (161.43 ± 77.3 μg/kg) and cress (154.75 ± 72.9 μg/kg). In some samples of dill (37.5% of samples), cress (18.75% of samples), and parsley (12.5% of samples), the Pb content was above the national allowable limit (200 μg/kg). The range of Cd concentration was < LOQ-42, < LOQ-41, < LOQ-30, and < LOQ-38 μg/kg for dill, cress, parsley, and coriander, respectively. In none of the samples, the concentration of Cd was higher than the Iranian national limit (50 μg/kg). The As occurrence was observed in all cress samples with a mean of 165.19 ± 64.83 μg/kg. The range of As concentration was < LOQ-71, < LOQ-256, 58-273, and < LOQ-75 μg/kg for parsley, dill, cress, and coriander, respectively. The THQ and HI values were higher than 1, and either ILCR value was higher than 10-4 for all tested heavy metals, it can be concluded that higher levels of heavy metals than the standard limits in some samples may raise the warning alarm and should come to the attention of the authorities.

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.

Differentiating environmental scenarios to establish geochemical baseline values for heavy metals in soil: A case study of Hainan Island, China

Soil heavy metal distributions exhibit regional heterogeneity due to the complex characteristics of parent materials and soil formation processes, emphasizing the need for appropriate regional standards prior to assessing soil risks. This study focuses on Hainan Island and employs the Multi-purpose Regional Geochemical Survey dataset to establish heavy metal geochemical baseline and background values for soil using an iterative method. Geographical detector analysis reveals that parent materials are the primary factor influencing heavy metal distribution, followed by soil types and land use. Heavy metal geochemical baseline values are established for the island's three environments and administrative regions. Notably, a universal geochemical baseline value cannot adequately represent regional variations in heavy metal distribution, with parent materials playing a crucial role in various scenarios. Locally applicable values based on parent material are the most representative for Hainan Island. This study provides a reference framework for developing region-specific environmental baseline values for soil heavy metal assessments.

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.

Source-oriented risks apportionment of toxic metals in river sediments of Bangladesh: a national wide application of PMF model and pollution indices

Intense human activities, particularly industrial and agricultural output, has enriched metal(loid)s in riverine sediment and endangered aquatic ecosystems and human health. Promoting proper river management requires an assessment of the possible ecological hazards and pollution posed by metal(loid)s in sediments. However, there are limited large-scale risk assessments of metal(loid)s contamination in riverine sediment in heavily populated nations like Bangladesh. This study compiled data on sediment metal(loid)s, for example, Cd, As, Cu, Ni, Cr, Pb, Mn, and Zn, from 24 major rivers located across Bangladesh between 2011 and 2022 and applied positive matrix factorization (PMF) to identify the critical metal(loid)s sources and PMF model-based ecological risks. Based on studied metal(loid)s, 12-78% of rivers posed higher contents than the upper continental crust and 8% of the river sediments for Cr and Ni, whereas 4% for Cd and As exceeded probable effect concentration. Cr and Ni in the sum of toxic units (STU), whereas Mn, As and Cd in potential ecological risk (PER) posed the highest contribution to contaminate sediments. In the studied rivers, sediment contaminant Mn derived from natural sources; Zn and Ni originated from mixed sources; Cr and Cu were released from the tannery and industrial emissions and Cd originated from agricultural practices. Source-based PER and NIRI indicated that mixed source (4% rivers) and tannery and industrial emission (4% rivers) posed very high risks in sediments. For the creation of macroscale policies and the restoration of contaminated rivers, our national-scale comprehensive study offers helpful references.

The spatial distribution, health risk, and cytotoxicity of metal(loid)s in contaminated field soils: The role of Cd in human gastric cells damage

The spatial distribution and pollution level of heavy metal(loid)s in soil (0-6 m) from a typical industrial region in Jiangmen City, Southeast China was investigated. Their bioaccessibility, health risk, and human gastric cytotoxicity in topsoil were also evaluated using an in vitro digestion/human cell model. The average concentrations of Cd (87.52 mg/kg), Co (106.9 mg/kg), and Ni (1007 mg/kg) exceeded the risk screening values. The distribution profiles of metal(loid)s showed a downward migration trend to reach a depth of 2 m. The highest contamination was found in topsoil (0-0.5 m), with the concentrations of As, Cd, Co, and Ni being 46.98, 348.28, 317.44, and 2395.60 mg/kg, respectively, while Cd showed the highest bioaccessibility in the gastric phase (72.80 %), followed by Co (21.08 %), Ni (18.27 %), and As (5.26 %) and unacceptable carcinogenic risk. Moreover, the gastric digesta of topsoil suppressed the cell viability and triggered cell apoptosis, evidenced by disruption of mitochondrial transmembrane potential and increase of Cytochrome c (Cyt c) and Caspases 3/9 mRNA expression. Bioaccessible Cd in topsoil was responsible for those adverse effects. Our data suggest the importance to reduce Cd in the soil to decrease its adverse impacts on the human stomach.

Green remediation of Ni, Zn, and Cu in an electroplating contaminated site by wood vinegar with optimization and risk assessment

Wood vinegar (WV) is a renewable organic compound, possessing characteristics such as high oxygenated compound content and low negative impact on soil. Based on its weak acid properties and complexing ability to potentially toxic elements (PTEs), WV was used to leach Ni, Zn, and Cu contaminated soil in electroplating sites. In addition, the response surface methodology (RSM) based on the Box-Behnken design (BBD) was established to clarify the interaction between each single factor, and finally completed the risk assessment of the soil. The amounts of PTEs leached from the soil climbed with the increase of WV concentration, liquid-solid ratio, and leaching time, while they surged with the decrease of pH. Under optimal leaching circumstances (the concentration of WV= 100 %; washing time= 919 min; pH= 1.00), the removal rates of Ni, Zn, and Cu could reach 91.7 %, 57.8 %, and 65.0 %, respectively, and the WV-extracted PTEs were mainly from the Fe-Mn oxides fraction. After leaching, the Nemerow integrated pollution index (NIPI) decreased from an initial value of 7.08 (indicating severe pollution) to 0.450 (indicating no pollution). The potential ecological risk index (RI) dropped from 274 (medium level) to 39.1 (low level). Additionally, the potential carcinogenic risk (CR) values reduced by 93.9 % for both adults and children. The results revealed that the washing process significantly reduced the pollution level, potential ecological risk, and health risk. Coupled with FTIR and SEM-EDS analysis, the mechanism of WV removal of PTEs could be explained from three aspects: acid activation, H⁺ ion exchange, and functional group complexation. In summary, WV is an eco-friendly and high-efficiency leaching material for the remediation of PTEs polluted sites, which will maintain soil function and protect human health.

Analytical study on heavy metal output fluxes and source apportionment of a non-ferrous smelter in southwest China

Abandoned Pb/Zn smelters are often accompanied by a large amount of smelting slag, which is a serious environmental problem. Previous studies have demonstrated that slag deposits pose an environmental threat even if the smelters are shut down. Herein, a Pb/Zn smelter and its impacted zone in GeJiu, Yunnan, China were selected as the study area. The risk and source apportionment of heavy metals (HMs) in the soil of the impacted zone were systematically studied. Based on the hydrogeological features, the migration path and output fluxes of the HMs released from smelting slag to the impacted zone were investigated. The HM contents (Cd, As, Zn, Pb, and Cu) in the soil substantially exceeded the screening values of the Chinese soil standard (GB15618-2018). Based on the results of the Pb isotopic and statistical analyses for source apportionment, the contaminated sites and agricultural irrigation water had a large impact on the HMs of soil. The hydrological analysis results showed that runoff, as an HM migration path under rainfall, continued to affect the environment. The water balance calculations using the Hydrologic Evaluation of Landfill Performance model showed that the rainfall was distributed on site as follows: evaporation (57.35%), runoff (32.63%), and infiltration (10.02%). Finally, the output fluxes were calculated in combination with the leaching experiment. As, Zn, Cd, Pb, and Cu runoff had the output fluxes of 6.1 × 10^-3, 4.2 × 10^-3, 4.1, 1.4 × 10^-2, and 7.2 × 10^-4 mg/kg/y, and infiltration of 1.9 × 10^-3, 1.3 × 10^-3, 1.3, 4.0 × 10^-4, and 2.2 × 10^-4 mg/kg/y, respectively. Therefore, this study offers theoretical and scientific recommendations for effective environmental management and engineering remediation.

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

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

Comparing cadmium uptake kinetics, xylem translocation, chemical forms, and subcellular distribution of two tobacco (Nicotiana tabacum L.) cultivars

Tobacco (Nicotiana tabacum L.) is a potential phytoremediator that can reduce soil cadmium (Cd) contamination. Pot and hydroponic experiments were conducted to investigate the difference in absorption kinetics, translocation patterns, accumulation capacity, and extraction amounts between two leading tobacco cultivars in China. We studied the chemical forms and subcellular distribution of Cd in the plants to understand the diversity of the detoxification mechanism of the cultivars. The concentration-dependent kinetics of Cd accumulation in leaves, stems, roots, and xylem sap for cultivars Zhongyan 100 (ZY100) and K326, fitted well with the Michaelis-Menten equation. K326 exhibited high biomass, Cd tolerance, Cd translocation, and phytoextraction abilities. The acetic acid, sodium chloride, and water-extractable fractions accounted for > 90% of Cd in all ZY100 tissues but only in K326 roots and stems. Moreover, the acetic acid and NaCl fractions were the predominant storage forms, while the water fraction was the transport form. The ethanol fraction also contributed significantly to Cd storage in K326 leaves. As the Cd treatment increased, more NaCl and water fractions were found in K326 leaves, while only NaCl fractions increased in ZY100 leaves. For subcellular distribution, > 93% Cd proportions were primarily stored in both cultivars' soluble or cell wall fraction. The proportion of Cd in the cell wall fraction of ZY100 roots was less than that of K326, while that proportion in the soluble fraction in ZY100 leaves was higher than in K326 leaves. These findings demonstrate that Cd accumulation patterns, detoxification, and storage strategies differ between the cultivars, providing a deeper understanding of Cd tolerance and accumulation mechanism in tobacco plants. It also guides the screening of germplasm resources or gene modification to improve the Cd phytoextraction efficiency of tobacco.