Heavy metal(loid)s in the topsoil of urban parks in Beijing, China: Concentrations, potential sources, and risk assessment

​Quantitative assessment of heavy metal concentrations, pollution levels, and sources apportionment in one of China's top 10 most livable cities

Urban topsoil is not only an essential part of the urban ecosystem, but also a powerful carrier of pollutants in the urban environment. In this paper, 130 topsoil samples from urban area of Xinyang in central-eastern China were selected, the aim is to quantitatively investigate the concentrations, pollution levels, and sources apportionment of 8 heavy metals (HMs, encompassing arsenic (As), cobalt (Co), copper (Cu), chromium (Cr), lead (Pb), nickel (Ni), vanadium (V), and zinc (Zn)) via geochemical method. The main conclusions are as follows. (1) The eight HMs in the topsoil have been artificially enriched to varying degrees, which are lower than the street dust levels sampled in pairs. (2) Cu, Zn, and Pb were significantly contaminated, and As, Co, Ni, Cr, and V were relatively low levels of contamination. Overall, comprehensive pollution levels were particularly severe, with 30.0%, 39.2%, and 30.8% for slight, moderate, and serious pollution, respectively. (3) Co, Ni, V, and Cr predominantly originated from natural sources, the percentage contribution of which is 6.3%; Pb, As, Cu, and Zn were predominantly derived from traffic-derived sources, with a percentage contribution of 93.7%. Thus, the first-order source of HMs in the topsoil originates from traffic-induced activities, similar to the case of street dust. Our findings can be beneficial in providing local governments with a reference to formulate environmental pollution controls, and also provide a case study for environmental pollution control in the other livable cities in China.

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

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

A novel spatial prediction method for soil heavy metal based on unbiased conditional kernel density estimation

Soil contamination by heavy metals has emerged as a significant global problem. Accurately mapping the spatial distribution of soil heavy metal pollutant concentrations is indispensable for effective agriculture and environmental management. Nevertheless, challenges arise in obtaining comprehensive data at all desired locations, due to limitations in measuring equipment capacity and the associated capital costs. To obtain soil heavy metal maps efficiently and accurately, this paper proposes a nonparametric spatial prediction method, based on unbiased conditional kernel density estimation (UCKDE). The proposed method incorporates the advantages of both geostatistics and machine learning, including stability, adaptability, and the ability to account for various types of auxiliary information. Additionally, it can directly predict the probabilistic density function (PDF) of soil heavy metal content at the target location based on sampling data without complex parameter settings, providing both a deterministic single value and a probabilistic prediction interval. The proposed method and ordinary kriging (OK) were implemented for the spatial prediction of the six heavy metals (As, Cd, Cu, Hg, Mn, and Sb) with the greatest coefficients of variation (CV = 0.53, 1.14, 0.66, 1.05, 0.81 and 0.74, respectively) in Qingxi Town, Chongqing, China. The results showed that the predictive capability of the proposed method (with RMSE values of 5.82, 0.61, 14.76, 0.15, 383.84, and 0.85, respectively) is superior to that of OK (with RMSE values of 5.29, 0.87, 16.37, 0.22, 493.22, and 1.58, respectively) in most cases, particularly when the CV value is high. Besides, the prediction accuracy of the proposed method can be further enhanced by incorporating parent material, resulting in RMSE values of 3.02, 0.51, 8.98, 0.08, 194.16, and 0.56, respectively. The results affirm the reliability of the proposed method and suggest its effectiveness as a tool for soil heavy metal pollution prediction in practical applications.

Trachemys dorbigni as a metal(loid) bioindicator: a study in rural and urban areas

Metals and metalloids are persistent environmental pollutants with the potential for bioaccumulation, posing significant health risks, including genotoxicity. These contaminants are prevalent in industrial and agricultural runoff. This study utilizes Trachemys dorbigni, an aquatic reptile, as a bioindicator to assess environmental contamination by metals and metalloids in both rural and urban settings in Pelotas, Rio Grande do Sul, Brazil. We captured specimens using pit-type traps with barriers (fyke nets), dividing them into two groups: 15 from a rural area and 15 from an urban area. Each animal underwent physical evaluations, and biometric data (weight, total carapace length and width) were recorded to calculate body condition indices. Biological samples were collected via manual restraint, with blood samples drawn from the supraoccipital venous sinus and linear carapace fragments obtained through manual scraping. Water samples from each location were also analyzed. Using atomic absorption spectrophotometry, concentrations of Al, As, Cd, Cr, Cu, Fe, Hg, Mn, Ni, Pb and Zn were measured in the water, carapace fragments, and blood samples. Cellular damage was assessed through flow cytometry and microscopy, examining erythrocyte disruption, reactive oxygen species, membrane fluidity, DNA fragmentation and micronucleus formation. Urban area samples showed concentrations of As, Cd, Cu, Fe, Hg and Ni exceeding national standards set by the Conselho Nacional do Meio Ambiente (CONAMA), with rural areas also showing elevated levels of As, Cd, Hg and Ni. Biometric analysis revealed that rural reptiles had significantly higher weight and carapace dimensions, whereas urban tortoises displayed a higher body condition index and significantly elevated blood levels of Al, Cr, Ni, Pb and Zn. The urban tortoises also exhibited higher concentrations of all tested metal(loid) in carapace samples (p < 0.05) and more pronounced cellular damage (p < 0.05), highlighting severe bioaccumulation and associated deleterious effects. Elevated reactive oxygen species levels were noted in rural specimens. This study underscores the impact of water degradation and metal(loid) pollution in urban environments on T. dorbigni, suggesting that carapace tissue analysis can serve as a chronic exposure indicator to these harmful contaminants.

Advancing source apportionment of soil potentially toxic elements using a hybrid model: a case study in urban parks, Beijing, China

Identifying the source-specific health risks of potentially toxic elements (PTE) in urban park soils is essential for human health protection. However, previous studies have mostly focused on the deterministic source-specific health risks, ignoring the health risk assessment from a probabilistic perspective. To fill this gap, we developed a hybrid model that incorporated machine learning (ML) interpretability into positive matrix factorization (PMF) and probability health risk assessment (PHRA) based on the Monte Carlo simulation. The results indicated that concentrations of soil PTEs except for Mn and Sb were significantly higher than their corresponding background values. Random forest (RF) was regarded as the best ML model to identify key drivers for As, Cd, Cr, Cu, Ni, Pb, and Zn, with R2 > 0.60, but was less effective for other soil PTEs (R2 < 0.49). Specifically, the contributions of the four potential pollution sources were mixed sources, traffic emission, fuel combustion, and building materials, with contribution rate of 24.88%, 30.56%, 28.99%, and 15.56%, respectively. Fuel combustion contributed the most to non-carcinogenic for children (39.45%), male (43.84%), and female (43.76%), and the non-carcinogenic risk could be considered negligible for human. However, building materials was the major contributor to carcinogenic risk for children (36.1%), male (44.9%), and female (43.2%). The integration of the RF model with PMF and PHRA improved the accuracy of the results by identifying and quantifying the specific sources of each soil PTE using the relative importance analysis from the RF model. The results of this study assisted in providing efficient strategies for risk management and control of soil PTEs in Beijing parks.

Hazard profiles, distribution trends, and sources tracing of rare earth elements in dust of kindergartens in Beijing

Children, the most vulnerable group in urban populations, are susceptible to the effects of pollution in urban environments. It is significant to evaluate the influence of rare earth elements (REEs) from kindergartens dust (KD) in Beijing on children's health. This study collected surface dust from 73 kindergartens in 16 districts of the mega-city of Beijing, and the concentrations of 14 REEs in KD, including La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, and Lu, were detected. The contamination levels, source apportionment, and health exposure risk of REEs were comprehensively investigated. The results indicate that the contamination levels of 14 REEs are within the acceptable range. Nevertheless, Eu, Ce, La, Pr, Nd, Gd, and Sm show high enrichment due to anthropogenic influence. Besides, KD is rich in light rare earth elements (LREEs) (90.97 mg kg-1) compared to heavy rare earth elements (HREEs) (8.65 mg kg-1). The distribution parameter patterns of REEs suggest that complicated anthropogenic sources influence the enrichment of REEs in KD. The main sources of REEs in KD include natural sources (40.64%), mixed high-tech industries and construction (33.89%), and mixed coal-fired, historical industrial, and transportation sources (26.47%). The primary pathway for daily intake of REEs in children is through ingestion, which presents a low but not negligible health risk. This study provides guidance for the effective risk management of REEs in KD.

Source Apportionment and Risk Assessment of Potentially Toxic Elements Based on PCA and PMF Model in Black Soil Area of Hailun City, Northeast China

This study assessed the presence of potentially toxic elements (PTEs) in China's northeastern black soil belt, an area with limited prior research. We collected 304 soil samples (0-20 cm) from Gonghe Town, Hailun City, and analyzed the PTE contamination degree using the single-factor pollution index and Nemerow pollution index. The results demonstrated that the mean concentrations of arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb), and zinc (Zn) were 11.16, 0.11, 65.29, 22.56, 0.03, 27.07, 26.09, and 66.01 mg/kg, respectively. Source apportionment was conducted via correlation analysis, principal component analysis, and positive matrix factorization, identifying four main sources: natural (33.2%), irrigation (29.5%), fuel (23.4%), and fertilizer (13.2%). The ecological risk index indicated a slight ecological risk, while the human health risk showed that non-carcinogenic risks were negligible and carcinogenic risks were acceptable. Our findings emphasize the need to prioritize controlling PTEs from fertilizer, particularly cadmium, and to a lesser extent, irrigation and fuel sources, focusing on As, Pband Hg. This research provides critical insights for policymakers aiming to manage PTE contamination in black soils.

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

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

Analysis of heavy metal and arsenic sources in mangrove surface sediments at Wulishan Port on Leizhou Peninsula, China, using the APCS-MLR model

Mangrove forests are sources and sinks for various pollutants. This study analyzed the current status of heavy metal and arsenic (As) pollution in mangrove surface sediments in rapidly industrializing and urbanizing port cities. Surface sediments of mangroves at Wulishan Port on the Leizhou Peninsula, China, were analyzed using inductively coupled plasma emission spectrometry (ICP-AES) and inductively coupled plasma mass spectrometry (ICP-MS) for the presence of Cr, Pb, Ni, Zn, Cd, Cu, As, and Hg. The Pollution load index, Nemerow pollution index, and Potential ecological risk index were employed to evaluate the pollutant. Multivariate statistical methods were applied for the qualitative analysis of pollutant sources, and the APCS-MLR receptor model was used for quantification. This study indicated the following results: (1) The average content of eight pollutants surpassed the local background level but did not exceed the Marine Sediment Quality standard. The pollution levels across the four sampling areas were ranked as Ⅲ > Ⅳ > Ⅰ > Ⅱ. The area Ⅱ exhibited relatively lower pollution levels with the grain size of the sediments dominated by sand, which was not conducive to pollutant adsorption and enrichment. (2) The factor analysis and cluster analyses identified three primary sources of contamination. As, Cr, Ni, and Pb originated from nearby industrial activities and their associated wastewater, suggesting that the primary source was the industrial source. Cd, Cu, and Zn stem from the cement columns utilized in oyster farming, alongside discharges from mariculture and pig farming, establishing a secondary agricultural source. Hg originated from ship exhaust burning oil and vehicle emissions in the vicinity, representing the third traffic source. (3) The APCS-MLR receptor model results demonstrated industrial, agricultural, and traffic sources contributing 47.19 %, 33.13 %, and 13.03 %, respectively, with 6.65 % attributed to unidentified sources.

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

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

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.

A New Approach Refined Probabilistic Health Risk Assessment of Shaoguan Smelter Based on Microenvironment - Guangdong Province, China, 2021

Introduction

This study introduces a novel method for developing an advanced exposure conceptual model tailored for health risk assessment, focusing on microenvironments.

Methods

The research was conducted at a major smelter in China to assess the health risks associated with trace metals (TMs) pollutants in the facility and the surrounding soil.

Results

Deterministic risk assessment indicated that cobalt, cadmium, antimony, manganese, arsenic, plumbum, and mercury (Co, Cd, Sb, Mn, As, Pb, and Hg) necessitated further evaluation through probabilistic risk assessment to assess potential health risks to residents. The 95% quantile concentrations of other TMs were found to be within acceptable health risk limits. For the probabilistic risk assessment, exposure parameters such as body weight, respiration rate, and exposure duration were collected using a questionnaire. This targeted assessment of the residential microenvironment revealed it as the site of the highest carcinogenic (CR) and non-carcinogenic risks (NCR), with values ranging from 2.84×10-5 to 6.7×10-5 and 1.59 to 5.57, respectively.

Conclusion

The primary contaminants posing the greatest health risks in residential and industrial areas have been identified as As, Pb, and Mn. The probabilistic health risk model, which focuses on microenvironmental factors, yields more precise results and offers a valuable tool for managing soil health risks.

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

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

New insights into assembly processes and driving factors of urban soil microbial community under environmental stress in Beijing

Rapid urbanization leads to drastic environmental changes, directly or indirectly affecting the structure and function of soil microbial communities. However, the ecological response of soil microbes to environmental stresses has not yet been fully explored. In this study, we used high-throughput sequencing to analyze the assembly mechanism and driving factors of soil microbial community under environmental stresses. The results indicated that environmental stresses significantly affected soil properties and the levels of beryllium, cobalt, antimony, and vanadium contamination in soil generally increased from the suburban areas toward the city core. The composition and distribution of soil microbial communities demonstrated clear differences under different levels of environmental stress, but there was no significant difference in microbial diversity. Random forest and partial least squares structural equation modeling results suggested that multiple factors influenced microbial diversity, but antimony was the key driver. The influence of environmental stress led to deterministic processes dominating microbial community assembly processes, which promoted the regional homogenization of soil microbes. Therefore, this study provides new insights into urban soil microbial management under environmental stresses.

Assessment of the migration characteristics and source-oriented health risks of heavy metals in the soil and groundwater of a legacy contaminated by the chlor-alkali industry in central China

The chlor-alkali industry (CAI) is crucial for global chemical production; however, its operation has led to widespread heavy metal (HM) contamination at numerous sites, which has not been thoroughly investigated. This study analysed 122 soil and groundwater samples from a typical CAI site in Kaifeng, China. Our aim was to assess the ecological and health risks, identify the sources, and examine the migration characteristics of HMs at this site using Monte Carlo simulation, absolute principal component score-multiple linear regression (APCS-MLR), and the potential environmental risk index (Ei). Our findings revealed that the exceedance rates for Cd, Pb, Hg, and Ni were 71.96%, 45.79%, 49.59%, and 65.42%, respectively. Mercury (Hg) displayed the greatest coefficient of variation across all the soil layers, indicating a significant anthropogenic influence. Cd and Hg were identified as having high and extremely high potential environmental risk levels, respectively. The spatial distributions of the improved Nemerow index (INI), total ecological risk (Ri), and HM content varied considerably, with the most contaminated areas typically associated with the storage of raw and auxiliary materials. Surface aggregation and significant vertical transport were noted for HMs; As and Ni showed substantial accumulation in subsoil layers, severely contaminating the groundwater. Self-organizing maps categorized the samples into two different groups, showing strong positive correlations between Cd, Pb, and Hg. The APCS-MLR model suggested that industrial emissions were the main contributors, accounting for 60.3% of the total HM input. Elevated hazard quotient values for Hg posed significant noncarcinogenic risks, whereas acceptable levels of carcinogenic risk were observed for both adults (96.60%) and children (97.83%). This study significantly enhances historical CAI pollution data and offers valuable insights into ongoing environmental and health challenges.

Characteristics and correlation analysis of heavy metal distribution in China's freshwater aquaculture pond sediments

The concentration of heavy metals (HMs) in aquaculture pond sediments significantly affects aquatic food safety and environmental quality. The contamination characteristics, drivers and potential sources of HMs in typical bulk freshwater aquaculture pond sediments in major provinces of China were systematically investigated using a variety of methods and models. Specifically, 130 surface sediment samples were collected from the study area, and the geoaccumulation index (Igeo) and potential ecological risk index (RI) were used to jointly evaluate the characteristics of the HMs. Spearman's correlation and redundancy analysis revealed the main drivers of the HMs. Additionally, the positive matrix factorization (PMF) model and absolute principal component score-multiple linear regression (APCS-MLR) model were used to identify the sources of HMs. The results revealed that the pond sediments were safe for fish culture in most of the study areas. Aquafeed protein content is an important driver of HM concentrations in sediments. The total organic carbon (TOC) content, percentage of clay particles, and pH of the aquaculture pond sediments determined the sediment HMs enrichment abilities as 13.6 %, 52 %, and 9.8 %, respectively. Cd, a significantly enriched pollutant, posed a greater ecological risk than the other five HMs (Cr, Cu, Zn, As, and Pb). Three sources of HMs were identified, including agricultural activity (e.g., aquafeeds, pesticides, and fertilizers), industrial production, and natural sources, with contributions of 44.29 %, 36.66 %, and 19.05 %, respectively. This study provides a scientific basis for minimizing the input and accumulation of HMs in freshwater aquaculture pond sediments, and this can provide insights into the prevention and control of the ecological risks posed by HMs.

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

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

Source-sink relationships of anthropogenic metal(loid)s from urban catchment to waterway in relation to spatial pattern of urban green infrastructures

Surface sediment in urban waterways originates from fine topsoil particles within catchments via surface erosion, often bonded with non-degradable metal(loid)s. This study posited that urban green infrastructures (UGIs) can influence anthropogenic metal(loid) transport from catchment topsoil to waterway sediment by retaining moveable particles. In multiply channeled downtown Suzhou, China, UGIs' spatial patterns were examined in relations to metal(loid)s source (catchment topsoil) - sink (waterway surface sediment) dynamics. Anthropogenic metal(loid)s - As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn - were spatially quantified in sediment at 144 waterway points and in topsoil at 154 UGIs' points across 7 subwatersheds. Integrated metal(loid) loads revealed significantly higher sediment loads (except for As) than topsoil, varying with element specificity and spatial unmatching across the subwatersheds. Loads of metal(loid)s in topsoil showed no significant differences among UGI types, but sediment loads of As, Cr, and Ni correlated positively with topsoil loads in roadside and public facility UGIs within 100 m- and 200 m-wide riparian buffer zones. However, waterfront UGIs negatively impacted on these correlations for Cr, Hg, and Ni loads within the riparian buffer zones. These findings highlight metal(loid) specificity and UGIs' spatial pattern effects on anthropogenic metal(loid) loads between catchment topsoil (source) and waterway surface sediment (sink), offering valuable guidelines for UGIs' design and implementation.

Quantitative assessment of ecological risk from pollution source based on geostatistical analysis and APCS-MLR model

The safety of human health and agricultural production depends on the quality of farmland soil. Risk assessment of heavy metal pollution sources could effectively reduce the hazard of soil pollution from various sources. This study has identified and quantitatively analyzed pollution sources with geostatistical analysis and the APCS-MLR model. The potential ecological risk index was combined with the APCS-MLR model which has quantitatively calculated the source contribution. The results revealed that As, Cr, Cd, Pb, Zn, and Cu were enriched in soil. Geostatistical analysis and the APCS-MLR model have apportioned four pollution sources. The Mn and Ni were attributed to natural sources; As and Cr were from agricultural activities; Cu and Zn were originated from natural sources; Cd and Pb were derived from atmospheric deposition. Atmospheric deposition and agricultural activities were the largest contributors to ecological risk of heavy metals in soil, which accounted for 56.21% and 36.01% respectively. Atmospheric deposition and agricultural activities are classified as priority sources of pollution. The combination of source analysis receptor model and risk assessment is an effective method to quantify source contribution. This study has quantified the ecological risks of soil heavy metals from different sources, which will provide a reliable method for the identification of primary harmfulness sources of pollution for future studies.

Phytoremediation by trees as a nature-based solution for mitigating metal contamination in urban soils

Trace metals in the environment are important pollutants affecting human health, particularly in urban areas worldwide. Phytoremediation as a nature-based solution (NBS) and environmentally friendly technology may decrease high concentrations of trace metals in urban soils, protecting public health (especially children) and contributing to urban sustainability. This study examined trace metal contamination of urban soils and trees in six cities in the Republic of Srpska (RS), Bosnia and Herzegovina (BiH) and investigated the potential of selected tree species for phytoremediation as a NBS for metal-polluted urban soils. Contamination of urban soils was assessed by quantifying the concentrations of 11 trace metals (B, Ba, Cd, Co, Cr, Cu, Mn, Mo, Ni, Pb, and Zn). To estimate phytoremediation potential of urban tree species, concentration and bioconcentration factor of the 11 metals were quantified in leaves of three common and abundant tree species: Aesculus hippocastanum L. (horse chestnut), Platanus acerifolia Willd. (plane), and Tilia sp. (lime). The results showed that trace metal concentrations in leaf samples did not exceed toxicity threshold guideline values. Further assessments are needed to establish the true potential of the three species as NBS for urban soils.

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.

Ecological pollution features and health risk exposure to heavy metals via street dust and topsoil from Nkpor and Onitsha in Anambra, Nigeria

The manuscript presents the investigation results on the pollution and risk of metal mines, and it is considered an important report on environmental pollution near mines in Nigeria, with archival value. The research involved soil sampling and heavy metal analysis for about 12 months in three metal mines. Based on these results, the paper provides information on pollution levels and hazards using well-known methods like pollution and ecological risk indexes. The increasing population in urban communities attracted by various industrial, economic and social activities causes contamination of atmospheric environment that can affect human health. We investigated heavy metal distributions, correlation coefficient among elements, ecological indices and probable health risk assessment in street dust and topsoil from Nkpor and Onitsha urban suburb, Nigeria. The mean concentration of heavy metals in car dust from Onitsha and Nkpor suburb follows thus: Fe > Mn > Cu > As > Pb > Ni > Cr. The decreasing trend of heavy metal in rooftop dust from both area: Fe > Mn > Cu > Pb > As > Ni > Cr whereas metal contents in topsoil were: Fe > Mn > Cu > Pb > Ni > Cr > As for both areas. The degree of pollution indices was characterized by contamination factor (CF), geo-accumulation factor (I-geo), pollution load index (PLI), Nemerow (PN), ecological and potential ecological risk index (ER and PERI) which indicated low pollution in the urban street environment. The results of Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) showed that the estimated heavy metals displayed sources from atmospheric deposition, natural origin and anthropogenic sources. Risk assessment revealed that ingestion of dust and soil was the significant route for heavy metals exposure to the populace followed by inhalation, then dermal contact. Considering all factors, non-cancer risk was more prominent in children than adults and no significant health hazard could be attributed to both aged groups as of the period of study except for As and Ni that needs constant monitoring to avoid exceeding organ damaging threshold limit of 1 × 10-4.

Ecological and human health hazards of soil heavy metals after wildfire: A case study of Liangshan Yi autonomous prefecture, China

Soil samples were collected in at different depths from the conflagration area in Liangshan Yi Autonomous Region, China, to investigate the distribution characteristics and ecological and human health risks of heavy metals after a wildfire. The samples collected comprise wildfire ash (WA) above the soil surface, ash soil (AS) 0-5 cm, and plain soil (PS) 5-15 cm below the soil surface. Additionally, reference soil (RS) was collected from a nearby unburned area at the same latitude as the conflagration area. The results showed that the concentrations of zinc (Zn), copper (Cu), lead (Pb), and cadmium (Cd) in the WA and AS were significantly higher than in reference soil (RS) (p < 0.05). Concentrations of Pb in the PS were 2.52 times higher than that in RS (17.9 mg kg-1) (p < 0.05). The AS and WA had the highest Index of potential ecological risks (RI > 600). In addition, The Cd in AS and WA contributed the most to the highest Improved nemerow index (INI) and RI with a contribution of more than 80%. The concentration of heavy metals was used to establish non-carcinogenic effects and cancer risks in humans via three exposure pathways: accident ingestion of soil, dermal contact with soil, and inhalation of soil particles. Hazard index (HI) values of each sample were all less than 1, indicating the non-carcinogenic risk was within the acceptable range and would not adversely affect the local population's health. The Cancer risk (CR) values of Cr, As, Cd, and Ni were all below 1 × 10-6, indicating that heavy metal pollution from this wildfire did not pose a cancer risk to residents.

Assessment of sources and health risks of heavy metals in metropolitan household dust among preschool children: The LEAPP-HIT study

The most common construction material used in Taiwan is concrete, potentially contaminated by geologic heavy metals (HMs). Younger children spend much time indoors, increasing HM exposure risks from household dust owing to their behaviors. We evaluated arsenic (As), cadmium (Cd), and lead (Pb) concentrations in fingernails among 280 preschoolers between 2017 and 2023. We also analyzed HM concentrations, including As, Cd, Pb, chromium (Cr), nickel (Ni), copper (Cu), zinc (Zn), iron (Fe), and manganese (Mn), in 90 household dust and 50 road dust samples from a residential area where children lived between 2019 and 2021 to deepen the understanding of sources and health risks of exposure to HMs from household dust. The average As, Cd, and Pb concentrations in fingernails were 0.12 ± 0.06, 0.05 ± 0.05, and 0.95 ± 0.77 μg/g, respectively. Soil parent materials, indoor construction activities, vehicle emissions, and mixed indoor combustion were the pollution sources of HMs in household dust. Higher Cr and Pb levels in household dust may pose non-carcinogenic risks to preschoolers. Addressing indoor construction and soil parent materials sources is vital for children's health. The finding of the present survey can be used for indoor environmental management to reduce the risks of HM exposure and avoid potential adverse health effects for younger children.

Health risk assessment of heavy metals in wild fish and seasonal variation and source identification of heavy metals in sediments: a case study of typical urban river in Xi'an, China

In order to determine the status of heavy metal pollution in river sediments and wild fish in Xi'an, concentrations of heavy metals (Cr, Ni, Cu, Zn, As, and Pb) were collected and analyzed in sediments and wild fish during dry season (October-November 2020) and wet season (June-July 2021). This study aimed to investigate the spatial and temporal variations of heavy metals in urban rivers of Xi'an, China. Their distribution characteristics and sources as well their pollution levels and health risks were assessed. The findings revealed that influenced by human activities, the heavy metal content in sediments (mg·kg-1 dry weight) in wet season was ranked as follows: Cr (73.09) > Zn (63.73) > Pb (40.31) > Ni (31.52) > Cu (24.86) > As (6.83); in the dry season: Zn (94.07) > Cr (69.59) > Cu (34.24) > Ni (33.60) > Pb (32.87) > As (7.60). Moreover, 32 fish samples from six species indicated an average metal content trend (mg·kg-1 wet weight) of Zn (8.70) > Cr (0.57) > Pb (0.28) > Ni (0.27) > Cu (0.24) > As (0.05). The potential ecological risk indices for sediment heavy metal concentrations in both seasons were well below the thresholds, which indicates that the aquatic environment is in safe level. The analysis of the potential ecological risk of sediment heavy metal concentrations indicates that the aquatic environment is safe for the time being. Based on the estimated daily intake (EDI), target risk quotient (THQ), total target risk quotient (TTHQ), cancer risk (CR), total cancer risk (TCR), and the permissible safety limits set by the agencies, the consumption of the fish examined is safe for human health. However, the presence of Cr and As in wild fish should still be a concern for human health, especially for children. The cumulative effect of heavy metals and the bioconcentration factor (BCF) suggest that sediment and heavy metals in fish are closely related, with higher concentrations in fish living in the bottom layer of the water column than in other water layers, and increasing with increasing predator levels. Correlation analysis and PMF modeling identified and determined four comparable categories of potential sources, namely, (1) atmospheric deposition and traffic sources, (2) agricultural sources, (3) industrial sources, and (4) natural sources.

Mineralogy and Geochemistry of Iron Tailings from Yeshan Iron Deposit, Southwest Jiangsu, China: Implications for Potential Utilization

In this work, twenty-one core samples of tailings wastes were collected from Yeshan iron tailings pond in Jiangsu Province, China. The mineralogical-chemical properties of Yeshan iron ore tailings (IOTs) were investigated to explore potential utilization. Mineralogical investigations and mineral liberation analysis indicated that the iron tailings have complex texture and incomplete mineral liberation, suggesting further grinding can improve higher recovery. Yeshan IOTs accumulated much higher MgO originating from dolomite, therefore, it could be infeasible to utilize a large quantity of Yeshan IOTs as alternative raw meals for cement clinker or replace aggregates in concrete. 2D vertical distribution profiles created with the ordinary kriging method presented heterogeneous distributions of major elements, and the variation trends were inconsistent. The results obtained in this work provide insight for exploiting and reducing Yeshan IOTs.

Development of a new method framework to estimate the nonlinear and interaction relationship between environmental factors and soil heavy metals

The intricate and multifaceted nature of soil system profoundly influences the highly complex and often nonlinear changes that soil heavy metals (HM) undergo. Spatial heterogeneity, location and scale variability, and the interaction and superposition among environmental drivers challenged researchers to determine the sophisticated nature of soil HMs changes at the regional scale. This study aims to develop a new method framework and selects Ningbo as the case study to apportion the environmental factors responsible for soil HMs pollution that include Cd, Cr, Pb, Hg, As, Cu, Zn and Ni, focusing on nonlinearity and interaction. We harnessed the Random Forest model to apportion the environmental drivers of soil HM change. The directionality and shape of the nonlinear relationship between HMs and their individual contributors were derived by Partial Dependence Plots. The interactions of multiple drivers were quantitatively assessed by the Conditional Inference Tree. Our results demonstrated that soil HMs in the study area varied spatially. Soil HMs pollution was mitigated by natural factors and anthropogenic factors. The main influencing factors were pH, soil parent material type, enterprise activities, and agricultural application. The effects of some factors on soil HMs showed a monotonic linear trend, but some have apparent threshold effects. The direction of influence on soil HMs will shift when pH and phosphate fertilizer reach a specific value. The addition of enterprises in the area would rarely have an impact on the HMs pollution once it reached around 2 per km2 because of the industrial agglomeration. Soil HM concentrations were mainly from multi-pollutants and were governed by a combination of environmental factors. Our study provided managers and policymakers with site-specific and definite guidelines for preventing and controlling soil HM pollution.

Impacts of land use/cover and slope on the spatial distribution and ecological risk of trace metals in soils affected by smelting emissions

The soil contamination around smelting sites shows high spatial heterogeneity. This study investigated the impacts of distance, land use/cover types, land slopes, wind direction, and soil properties on the distribution and ecological risk of trace metals in the soil around a copper smelter. The results demonstrated that the average concentrations of As, Cd, Cu, Pb, and Zn were 248.0, 16.8, 502.4, 885.6, and 250.2 g mg kg-1, respectively, higher than their background values. The hotspots of trace metals were primarily distributed in the soil of smelting production areas, runoff pollution areas, and areas in the dominant wind direction. The concentrations of trace metals decreased with the distance to the smelting production area. An exponential decay regression revealed that, depending on the metal species, the influence distances of smelting emissions on trace metals in soil ranged from 450 to 1000 m. Land use/cover types and land slopes significantly affected trace element concentrations in the soil around the smelter. High concentrations of trace metals were observed in farmland, grassland, and flatland areas. The average concentrations of trace metals in the soil decreased in the order of flat land > gentle slope > steep slope. Soil pH values were significantly positively correlated with Cd, Cu, Pb, Zn, and As, and SOM was significantly positively correlated with Cd, Pb, and Zn in the soil. Trace metals in the soil of the study area posed a significant ecological risk. The primary factors influencing the distribution of ecological risk, as determined by the Ctree analysis, were land slope, soil pH, and distance to the source. These results can support the rapid identification of high-risk sites and facilitate risk prevention and control around smelting sites.

Source apportionment and migration characteristics of heavy metal(loid)s in soil and groundwater of contaminated site

The rapid industrial growth has generated heavy metal(loid)s contamination in the soil, which poses a serious threat to the ecology and human health. In this study, 580 samples were collected in Henan Province, China, for source apportionment, migration characterization and health risk evaluation using self-organizing map, positive matrix factorization and multivariate risk assessment methods. The results showed that samples were classified into four groups and pollution sources included chromium slag dump, soil parent rock and abandoned factory. The contents of Cr, Pb, As and Hg were low in Group 1. Group 2 was characterized by total Cr, Cr(Ⅵ) and pH. The enrichment of total Cr and Cr(Ⅵ) in soil was mainly attributed to chromium slag dump, accounting for more than 84.0%. Group 3 was dominated by Hg and Pb. Hg and Pb were primarily attributed to abandoned factory, accounting for 84.7% and 70.0%, respectively. Group 4 was characterized by As. The occurrence of As was not limited to one individual region. The contribution of soil parent rock reached 83.0%. Furthermore, the vertical migration of As, Hg, Pb and Cr(Ⅵ) in soil was mainly influenced by medium permeability, pH and organic matter content. The trends of As, Pb, and Hg with depth were basically consistent with the trends of organic matter with depth, and were negatively correlated with the change in pH with depth. The trends of Cr(Ⅵ) with depth were basically consistent with the changes in pH with the depth. The content of Cr(Ⅵ) in the deep soil did not exceed the detection limits and Cr(Ⅵ) contamination occurred in the deep aquifer, suggesting that Cr(Ⅵ) in the deep groundwater originated from the leakage of shallow groundwater. The assessment indicated that the non-carcinogenic and carcinogenic risks for children and adults could not be neglected. Moreover, children were more susceptible than adults.

Human health risk assessment of potentially toxic elements in soil and air particulate matter of automobile hub environments in Kumasi, Ghana

Rapid urbanization and uncontrolled industrial activities in developing countries have raised concerns about potentially toxic metal contamination of the environment. This study assessed the levels of potentially toxic elements in soil and airborne particulate matter in the Suame and Asafo areas in the Kumasi metropolis, characterized by a high concentration of auto mechanic workshops and residential settlements. X-ray fluorescence analysis and inductively coupled plasma-mass spectrometry were used to determine the metal concentrations in the samples. The results showed high concentrations of potentially toxic elements in the soil and air samples, indicating contamination from automotive activities. Metals such as Co, Ni, Pb, and Zn were found to be present at concentrations (13.42-6101.58 mg/kg and 14.15-11.74 mg/kg for Suame and Asafo respectively) that pose potential health risks to exposed populations. Mathematical models such as pollution indices were used to assess the extent of contamination and determine the potential sources of the metals - the automotive repairs. The findings highlight the urgent need for environmental management and remediation strategies to mitigate the health risks of exposure to potentially toxic elements in the Kumasi metropolis automotive hub.

Machine learning combined with Geodetector quantifies the synergistic effect of environmental factors on soil heavy metal pollution

The critical prerequisite for the prevention and control of soil heavy metal (HM) pollution is the identification of factors that influence soil HM accumulation. The dominant factors have been individually identified and apportioned in existing studies. However, the accumulation of soil HMs results from a combination of multiple factors, and the influence of a single factor is less than the interaction of multiple parameters on soil HM pollution. In this study, we employed Geodetector to delve into the interaction effect of the influencing factors on the variations of soil HMs. We performed partial dependence plot to depict how these factors interact with each other to affect the HM content. We found that both individually and interactively, pH and agricultural activities significantly impact soil HM content. Except for Hg and Cu, the pairs with the most significant interaction effects all involve pH. For Pb, As and Zn, interaction with pH has the most significant driving force compared to the other factors. For Cu, Hg, and Ni, all environmental factor interactions increased their explanatory power, while for Cr, the single most significant driver decreased its driving power when interacting with other factors. Additionally, the study area exhibited a widespread prevalence of changes in HM concentration being governed by the synergistic effect of two factors. For the response of HMs to the interaction of pH and fertilizer, soil HM concentration was sensitive to pH, while fertilizer had less effect. These results provide a dependable method of investigating the interaction of environmental factors on soil HM content and put forth efficacious and potent tactical measures for soil HM pollution prevention and control based on the interaction type.

Assessment of source-oriented health risk associated with the oral ingestion of heavy metals in dust within an iron/steel smelting-affected area of the North China Plain

Heavy metals (HMs) from iron/steel smelting activities pose notable risks to human health, especially to those living around industrial facilities of North China Plain, the base of China's steel production. In this study, 78 outdoor windowsill dust samples were collected around a large-scale iron/steel smelter with more than 65 years of production history in the western North China Plain. Nine HMs were analysed to comprehensively assess the health risks by integrating Monte Carlo simulation, oral bioaccessibility, and source apportionment. Results showed serious pollution with Cd, Pb, and Zn based on their geo-accumulation index values and concentrations. Four potential sources including industrial sources (49.85%), traffic sources (21.78%), natural sources (20.58%), and coal combustion (7.79%) were quantitatively identified by multivariate statistical analysis. The oral bioaccessibilities of HMs determined by the physiologically based extraction test ranged from 0.02% to 65.16%. Zn, Mn, Cd, and Pb had higher bioaccessibilities than other HMs. After incorporating oral bioavailability adjustments, noncarcinogenic and carcinogenic risks were significantly reduced, especially for adults. The mean hazard index (HI) for children and adults was below the safety threshold (1.0), whereas the mean of the total carcinogenic risk (TCR) based on HM bioaccessibilities in the gastric phase remained above the acceptable level (1.0E-06) (children: 5.20E-06; adults: 1.16E-06). Traffic sources warranted increased concern as it substantially increased TCR. Cd was identified as the priority pollution in iron/steel smelting areas. Assessing source-oriented health risks associated with oral ingestion exposure can guide the management and control of HM contamination within iron/steel smelting-affected areas.

Contamination, ecological-health risks, and sources of potentially toxic elements in road-dust sediments and soils of the largest urban riverfront scenic park in China

Identifying the contamination and sources of potentially toxic elements (PTEs) in road-dust sediment (RDS) and the surrounding greenspace soil of urban environments and understanding their ecological-health risks are important for pollution management and public health. The contamination characteristics, ecological and probabilistic health risks, and source apportionment of eight PTEs (Cd, Pb, Cr, Cu, Ni, As, Zn, and Hg) in the Yellow River Custom Tourist Line of Lanzhou, which is the largest open urban riverfront scenic park in China, were investigated. The results showed that all the RDS PTE mean concentrations exceeded their soil background values, whereas for the surrounding greenspace soils, the concentrations of the PTEs, except for Cr and Ni, were also higher than their local background levels. Moreover, the RDS-soil system was mainly contaminated by Cd, Zn, Pb, Cu, and Hg to varying degrees, and the integrated ecological risks of PTEs in the RDS and soil were high and considerable at most sites, respectively. The probabilistic health risk assessment results demonstrated that the non-carcinogenic hazard risk for humans was negligible, but the total carcinogenic risks should be considered. Source apportionment using a positive matrix factorization model combined with multivariate statistical analyses revealed that Cr, Ni, and As in the RDS-soil system were from natural and industrial sources, Cd, Pb, Zn, Cu came from vehicle emissions and pesticide and fertilizer applications, and Hg was from natural and industrial sources and utilization of pesticides with fertilizers. This work provides scientific evidence for urban planning and human health protection in urban environments.

Spatial distribution, source apportionment and potential ecological risk assessment of trace metals in surface soils in the upstream region of the Guanzhong Basin, China

The health of ecosystems and safety of agricultural products are correlated with trace metal pollutionin in the soil, which eventually affects mankind. For this research, topsoil (0-20 cm) was sampled from 51 locations in the upstream area of the Guanzhong Basin to determine the level of pollution, spatial distribution characteristics and origins of 15 trace metals (V, Cr, Mn, Fe, Ni, Cu, Zn, As, Se, Rb, Sr, Y, Zr, Cd, Pb). The pollution index and potential ecological risk index were adopted for the accurate analyses of contamination degree and ecological risk that trace elements cause. The identification of potential sources of trace metals pollution was carried out using the APCS-MLR model and multivariate statistical analysis. Findings demonstrated that the most contaminated elements in the topsoil of the designated areas were Cr, Cu, Cd and Pb, and the average levels of all trace metal elements exceeded their respective local background values. However, most of the sampling points showed slight pollution, and a few demonstrated moderate and severe pollution. The southern, south-western and eastern parts in the research zone were relatively seriously contaminated, especially near Baoji City and Wugong County. Fe, Cu, Zn, Ni, Se were mainly caused by combination of agricultural and industrial production, the primary sources of Mn, Y, and Zr were the process of mining and industrial production, Cd and Pb originated mainly from traffic emission and agricultural pollution, and Cr mainly came from mining and metal smelting processes. Meanwhlie, some unknown pollution sources were also disclosed. This study has a reliable reference value for determining the source of trace metals in this region. To further determine the pollution sources of trace elements, long-term monitoring and management is necessary.

Distribution, source investigation, and risk assessment of topsoil heavy metals in areas with intensive anthropogenic activities using the positive matrix factorization (PMF) model coupled with self-organizing map (SOM)

Over the past decade, heavy metal (HMs) contamination in soil environments has become severe worldwide. However, their resulting ecological and health risks remained elusive across a variety of soil ecosystems due to the complicated distributions and sources. This study investigated the HMs (Cr, As, Cu, Pb, Zn, Ni, Cd, and Hg) in areas with multi-mineral resources and intensive agricultural activities to study their distribution and source apportionment using a positive matrix factorization (PMF) model coupled with self-organizing map (SOM). The potential ecological and health risks were assessed in terms of distinct sources of HMs. The results disclosed that the spatial distribution of HM contaminations in the topsoil was region-dependent, primarily located in areas with high population intensity. The geo‑accumulation index (Igeo) and enrichment factor (EF) values collectively displayed that the topsoils were severely contaminated by Hg, Cu, and Pb, particularly in residential farmland areas. The comprehensive analysis combined with PMF and SOM identified both geogenic and anthropogenic sources of HMs including natural, agricultural, mining, and mixed sources (caused by multi-anthropogenic factors), accounting for 24.9%, 22.6%, 45.9%, and 6.6% contribution rates, respectively. The potential ecological risk was predominantly due to the enrichment of Hg, followed by Cd. The non-carcinogenic risks were mostly below the acceptable risk level, while the potential carcinogenic health risks caused by As and Cr should be paid prime attention to, particularly for children. In addition to the 40% geogenic sources, agricultural activities contributed to 30% of the non-carcinogenic risk, whereas mining activities contributed to nearly half of the carcinogenic health risks.

Assessing pollution and health risks from chromite mine tailings contaminated soils in India by employing synergistic statistical approaches

Potentially toxic elements (PTEs) contamination in the agricultural soil can generate a detrimental effect on the ecosystem and poses a threat to human health. The present work evaluates the PTEs concentration, source identification, probabilistic assessment of health hazards, and dietary risk analysis due to PTEs pollution in the region of the chromite-asbestos mine, India. To evaluate the health risks associated with PTEs in soil, soil tailings and rice grains were collected and studied. The results revealed that the PTEs concentration (mainly Cr and Ni) of total, DTPA-bioavailable, and rice grain was significantly above the permissible limit in site 1 (tailings) and site 2 (contaminated) as compared with site 3 (uncontaminated). The Free ion activity model (FIAM) was applied to detect the solubility of PTEs in polluted soil and their probable transfer from soil to rice grain. The hazard quotient values were significantly higher than the safe (FIAM-HQ < 0.5) for Cr (1.50E+00), Ni (1.32E+00), and, Pb (5.55E+00) except for Cd (1.43E-03), Cu (5.82E-02). Severity adjustment margin of exposure (SAMOE) results denote that the PTEs contaminated raw rice grain has high health risk [Cr_SAMOE: 0.001; Ni_SAMOE: 0.002; Cd_SAMOE: 0.007; Pb_SAMOE: 0.008] for humans except for Cu. The Positive matrix factorization (PMF) along with correlation used to apportion the source. Self-organizing map (SOM) and PMF analysis identified the source of pollution mainly from mines in this region. Monte Carlo simulation (MCS) revealed that TCR (total carcinogenic risk) cannot be insignificant and children were the maximum sufferers relative to adults via ingestion-pathway. In the spatial distribution map, the region nearer to mine is highly prone to ecological risk with respect to PTEs pollution. Based on appropriate and reasonable evaluation methods, this work will help environmental scientists and policymakers' control PTEs pollution in agricultural soils near the vicinity of mines.

Organophosphate esters in soils of Beijing urban parks: Occurrence, potential sources, and probabilistic health risks

Organophosphate esters (OPEs) are an emerging contaminant widely distributed in the soil. OPEs have drawn increasing attention for their biological toxicity and possible threat to human health. This research investigated the pollution characteristics of two typical OPEs, organophosphate triesters (tri-OPEs) and organophosphate diesters (di-OPEs), in soils of 104 urban parks in Beijing. The median concentrations of Σ₁₁tri-OPEs and Σ₈di-OPEs were 157 and 17.9 ng/g dw, respectively. Tris(2-chloroisopropyl) phosphate and bis(2-ethylhexyl) phosphate were the dominant tri-OPE and di-OPE, respectively. Consumer materials (such as building insulation and decorative materials), traffic emissions, and reclaimed water irrigation may be critical sources of tri-OPEs in urban park soils. Di-OPEs mainly originated from the degradation of parent compounds and industrial applications. Machine learning models were employed to determine the influencing factors of OPEs and predict changes in their concentrations. The predicted OPEs concentrations in Beijing urban park soils in 2025 and 2030 are three times and five times those in 2018, respectively. According to probabilistic health risk assessment, non-carcinogenic and carcinogenic risks of OPEs can be negligible for children and adults. Our results could inform measures for preventing and controlling OPEs pollution in urban park soils.

Unraveling the complexities of beryllium contamination in agricultural soils: The case of Qingcheng District, Qingyuan City

Metal contamination in agricultural soils has received widespread attention; however, the status of beryllium (Be) contamination in agricultural soils has been inadequately studied. This research was conducted to determine the enrichment level and major sources of Be contamination in the agricultural soil in Qingcheng District, Qingyuan City, and to quantify the potential ecological risk and human health risk (PER and HHR) of Be by integrating geological mineral and remote-sensing image maps. The results of principal component analysis followed by multiple linear regression (PCA-MLR) suggest that Be, Sn, Zn, Pb, As, and Cd are mainly derived from anthropogenic activities; V, Ti, Sc, Cr, and Co are mainly derived from medium acidic granites; Al and Si are mainly derived from geological sources; and K and Na are mainly derived from calcium-alkaline materials. Anthropogenic activities are priority material sources owing to the highest contribution. Be contamination poses a slight PER, and the PER level of agricultural soil was moderate. The HHR caused by Be is negligible. The results of this study can serve as the basis for promoting agricultural soil protection and developing and implementing agricultural policies to reduce environmental pollution in the study area.

Spatial prediction and influencing factors identification of potential toxic element contamination in soil of different karst landform regions using integration model

The prediction of contamination distribution of potentially toxic elements (PTEs) in soils of Guangxi province, China and the identification of their controlling factors pose great challenges due to diverse bedrock types, intense leaching and weathering, and discontinuous terrain distributions. Herein, we integrated the random forest (RF) and empirical Bayesian kriging (EBK) to interpret and predict complex PTEs contamination distribution from three different karst landform regions (fenglin, fengcong, isolated peak plain) in Guangxi province. The modeling results are compared with the commonly used ordinary kriging and regression-kriging. In this study, our developed RF-EBK model combines the advantages of the RF and EBK model to promote the prediction accurately and efficiently. In this study, it was shown that the integration RF-EBK model exhibited desirable for Cd and As concentrations, with R² of 0.89 and 0.83, respectively. The average RMSE and MAE of integration RF-EBK model decreased by 39% and 44%, respectively, relative to the regression-kriging with the second highest accuracy. Furthermore, the modeling results showed that approximately 41.96% and 18.96% of total area was classified as Cd and As polluted and above regions (I_geo >0) in Guangxi province, respectively. Higher Cd concentration was observed in the soil of fenglin and fengcong regions than that in isolated peak plain region due to the secondary enrichment and parent rock inheritance, while the As concentration exhibited no significant difference among the three regions. The modeling results indicated that the elevated Cd concentration might be associated with soil CaO concentration and alkaline soil environment, whereas As concentration tended to be increased with the elevating Fe₂O₃ concentrations in weakly acidic soil environment. This result confirmed the applicability and effectiveness of integration model in predicting complex spatial patterns of soil PTEs and identifying their controlling factors.

Biomonitoring trace metal contamination in Guangzhou urban parks using Asian tramp snails (Bradybaena similaris)

Anthropogenic activities have caused environmental metal contamination in urban areas. Biomonitoring using organisms such as invertebrates can evaluate metal pollution, supplementing chemical monitoring, which cannot comprehensively reflect how metals influence organisms in the urban environment. To assess metal contamination in Guangzhou urban parks and its source, Asian tramp snails (Bradybaena similaris) were collected from ten parks in Guangzhou in 2021. The metal concentrations (Al, Cd, Cu, Fe, Mn, Pb, and Zn) were measured by ICP-AES and ICP-MS. We evaluated the metal distribution characteristics and correlations among metals. The probable sources of metals were determined by the positive matrix factorization (PMF) model. The metal pollution levels were analysed using the pollution index and the Nemerow comprehensive pollution index. The mean metal concentrations were ranked Al > Fe > Zn > Cu > Mn > Cd > Pb; metal accumulation in the snails was ranked Al > Mn > CuFe > Cd > Zn > Pb. Pb-Zn-Al-Fe-Mn and Cd-Cu-Zn were positively correlated in all samples. Six major metal sources were identified: an Al-Fe factor corresponding to crustal rock and dust, an Al factor related to Al-containing products, a Pb factor indicative of traffic and industries, a Cu-Zn-Cd factor dominated by the electroplating industry and vehicle sources, an Mn factor reflecting fossil fuel combustion, and a Cd-Zn factor related to agricultural product use. The pollution evaluation suggested heavy Al pollution, moderate Mn pollution, and light Cd, Cu, Fe, Pb, and Zn pollution in the snails. Dafushan Forest Park was heavily polluted; Chentian Garden and Huadu Lake National Wetland Park were not widely contaminated. The results indicated that B. similaris snails can be used as effective biomarkers for monitoring and evaluating environmental metal pollution in megacity urban areas. The findings show that snail biomonitoring provides a valuable understanding of the migration and accumulation pathways of anthropogenic metal pollutants in soil‒plant-snail food chains.

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.

A novel regional-scale human health risk assessment model for soil heavy metal(loid) pollution based on empirical Bayesian kriging

Soil heavy metal(loid)s contamination caused by rapid urbanization and industrialization seriously affects human health and hinders the global sustainable development goals (SDGs). Currently, there is a lack of comprehensive human health risk assessment (HHRA) studies for multiple land use types at the regional scale. We propose a practical risk assessment framework that integrates empirical Bayesian kriging (EBK), pollution level analyses, and modified HHRA modeling. The concentrations of copper industry-related metals (Cu, Ni, Cd, As, and Hg) in 332 topsoil samples from the south bank of the Yangtze River in Tongling were investigated. Obvious enrichment of Cu, Cd, As, and Hg was detected, and the average concentration of Cu was 5.24 times higher than the background values. The distribution of heavy metal(loid) pollution was typically high in the south and east, and low in the north and west. The mean errors of interpolation for Cu, Ni, and Hg were 0.84, 1.29, and 0, respectively, and the root mean square errors of interpolation for Cd and As were 1.29 and 0.86, respectively. Non-carcinogenic risks of soil heavy metal(loid)s were assessed as acceptable throughout the studied area. The hazard index decreased in the order As (0.448) > Ni (0.0729) > Cd (0.0136) > Hg (9.04 ×10^-4) > Cu (6.41 ×10^-4). Nevertheless, the carcinogenic risks of Ni, Cd, and As in 70-80% of the administrative units (AUs) were between 10^-6 to 10^-4, considered an unacceptable level. Exposure through the oral ingestion route accounted for 88.0-99.2% of the total three exposure routes. It is worth noting that four AUs were considered to be the priority control units, and Ni and As were identified as the priority control soil heavy metal(loid)s. This case demonstrates the feasibility and scientific validity of the new EBK-HHRA framework, which confirms that EBK can effectively predict the spatial distribution patterns of soil heavy metal(loid)s and that modified HHRA models are conducive to risk integration at the regional scale. The EBK-HHRA approach is generic and provides substantial support for risk source identification and risk management of soil heavy metal(loid)s contamination at the regional scale.

Health risk assessment of the heavy metals at wastewater discharge points of textile industries in Tongi, Shitalakkhya, and Dhaleshwari, Bangladesh

Pollution of industry-adjacent surface water bodies has become a major threat to the environment in Bangladesh. This study examined the health risks of concentrated heavy metals in Tongi, Shitalakkhya, and Dhaleshwari, which receive effluents from wastewater treatment plants. Samples were analyzed for heavy metals such as lead, cadmium, iron, magnesium, manganese, zinc, copper, chromium, and nickel. At all the locations, only Zn, Cu, and Ni did not exceed the Bangladesh standard for drinking water. The health risk was estimated using the hazard quotient (HQ) technique. There was a threat of health risks resulting from the exposure through ingestion, with Pb, Cd, Fe, Mg, and Cr being the main contributors. The orders of decreasing values of mean HQ were Mg > Pb > Fe > Cr > Cd, Mg > Fe > Pb > Cr > Cd, and Cr > Mg > Pb > Fe > Cd via oral intake for both adults and children at Tongi, Shitalakkhya, and Dhaleshwari, respectively. For dermal intake, the mean HQ for only chromium at Dhaleshwari exceeded the limit for both groups. The results emphasize the need for enhancement, proper operation, and maintenance of wastewater treatment facilities in order to meet the discharge quality standard.

Necessity of introducing particle size distribution of hand-adhered soil on the estimation of oral exposure to metals in soil: Comparison with the traditional method

This study aimed to systematically investigate the relationship between children exposure possibility, metal concentration, metal bioaccessibility and soil particle size. fifty Children aged 3-8 years were recruited for the collection of hand-adhered soil, environmental soil, and blood samples. The mass distribution of hand-adhered soil with particle size were analyzed. Based on it, environmental soil samples were divided into five fractions to evaluate the effect of soil particle size on the total contents and bioaccessibilities of toxic metals. Then, a refined soil oral exposure model based on the particle size distribution of hand-adhered soil was established, and the estimation was compared with the typical traditional method. We found that finer particles were preferentially adhered to hand. The highest metal concentrations and bioaccessibilities occurred in the finest fraction, with values decreasing with increasing particle size. The exposure levels using the refined model were 2.0-3.4 times higher than those with the traditional method. In addition, Pb exposure level calculated using the refined model exhibited stronger and more significant correlation with blood Pb than those of the traditional soil. The construction of a refined exposure scenario based on hand-adhered soil could more exactly reflect the real exposure level and the difference among individuals.

An integrated approach for quantifying source apportionment and source-oriented health risk of heavy metals in soils near an old industrial area

Soil contamination of heavy metals (HMs) caused by the long-term industrial activities has become a major environmental issue due to its adverse effects on human health and ecosystem. In this paper, 50 soil samples were analyzed to evaluate the contamination characteristics, source apportionment and source-oriented health risk of HMs in soils near an old industrial area in NE China by applying an integrated approach of Pearson correlation analysis, Positive matrix factorization (PMF) model and Monte Carlo simulation. The results showed that the mean concentrations of all HMs greatly exceeded the soil background values (SBV), and the surface soils in the study area were heavily polluted with HMs, displaying a very high ecological risk. The toxic HMs emitted from the bullet production were identified as the primary source of HMs contamination in soils, with a contribution rate of 33.3%. The human health risk assessment (HHRA) suggested that the Hazard quotient (HQ) values of all HMs for children and adults are within the acceptable risk level (HQ < 1). The carcinogenic risk (CR) values of HMs for children and adults significantly exceeded the acceptable threshold of 1E-6 with a basic trend: As > Pb > Cr > Co > Ni, indicating a high cancer risk. For source-oriented health risk, the CR of four pollution sources for children and adults shows a same trend: Factor 4 > Factor 3 > Factor 2 > Factor 1. Among those, the source of HMs pollution from bullet production is the largest contributor to cancer risk, and As and Pb are the most important HMs pollutants that cause cancer risk to humans. The present study sheds some light on the contamination characteristics, source apportionment and source-health risk assessment of HMs in industrially contaminated soils, which helps improve the management of environmental risk control, prevention and remediation.

Characteristics of Soil Heavy Metal Pollution and Health Risk Assessment in Urban Parks at a Megacity of Central China

In this study, we compared the concentrations of the heavy metals Cd, Cr, Cu, Zn, Ni, and Pb in the surface soils of urban parks in Wuhan, Hubei Province, with those in the surface soils of urban parks worldwide. The soil contamination data were assessed using enrichment factors and spatial analysis of heavy metals using inverse distance weighting and quantitative analysis of heavy metal sources with a positive definite matrix factor (PMF) receptor model. Further, a probabilistic health risk assessment of children and adults using Monte Carlo simulation was performed. The average Cd, Cr, Cu, Zn, Ni, and Pb concentrations in the surface soils of urban parks were 2.52, 58.74, 31.39, 186.28, 27.00, and 34.89 mg·kg^-1, respectively, which exceeded the average soil background values in Hubei. From the inverse distance spatial interpolation map, heavy metal contamination was primarily observed to be present to the southwest of the main urban area. The PMF model resolved four sources: mixed traffic and industrial emission, natural, agricultural, and traffic sources, with relative contributions of 23.9%, 19.3%, 23.4%, and 33.4%, respectively. The Monte Carlo health risk evaluation model demonstrated negligible noncancer risks for both adult and child populations, whereas the health effects of Cd and Cr on children were a concern for cancer risks.

The function of "Cambi® thermal hydrolysis + anaerobic digestion" on heavy metal behavior and risks in a full-scale sludge treatment plant based on four seasons investigation

The environmental risk of heavy metals in sewage sludge from a full-scale "Cambi® thermal hydrolysis + anaerobic digestion" sludge treatment plant was discussed based on four seasons' data. Results showed that the order of heavy metal concentration in sludge was Zn > Cu > Cr > Ni > As > Pb > Hg > Cd, which all increased significantly due to the "enrichment effect" caused by the degradation of organics. Nevertheless, the mass of heavy metals except for Cd decreased. Chemical fractions of different heavy metals in raw sludge varied greatly. The proportion of their residual fraction all increased slightly after treatment. Thermal hydrolysis and anaerobic digestion led to the transformation of some heavy metal fractions. Deep dehydration process reduced the mass of heavy metals from sludge (less than 10%). Potential ecological risk of heavy metals was low (RI <150) when sludge is applied 0.75 kg/m² to soil according to GB 4284-2018, in which the risk of Hg and Cd was highest. Furthermore, the accumulation amounts of heavy metals in test soil and rural soil with the annual sludge application amount of 0.75 kg/m² for 15 years were calculated, which did not exceed GB 36600-2018 and GB 15618-2018 respectively.

Source, environmental behavior and potential health risk of rare earth elements in Beijing urban park soils

Rare earth elements (REEs) have been increasingly diffused to the environment due to their extensive use and application in industries, agriculture, and high-tech devices, which have been regarded as emerge pollutants. However, the study concerning REEs in urban soils is still limited. Therefore, the objectives of this study were to investigate the potential source and risk of REEs in urban environment. We analyzed the concentration and distribution of REEs in urban park soils, and performed a combination of micro geochemical method and random forest method to characterize the pollution sources of REEs. The results showed that the ΣREE concentrations in Beijing urban park soils ranged from 117.19 to 198.09 mg/kg. Spatial distribution indicated that the high concentrations of REEs were mainly concentrated in the west of Beijing near an industrial area. The geochemical parameters, micro spherules and random forest results confirmed the anthropogenic pollution sources from industry and traffic. Risk assessment showed that the average daily doses of total REEs for children and adults were far below the reference threshold with values of 0.08 and 0.02 µg/kg/day, respectively. Our study has exhibited that though the reconstruction of parks from abandoned industrial sites showed an accumulation of REEs, the health risk of REEs for human beings are negligible.

Health risk assessment of heavy metals in road dust from the fourth-tier industrial city in central China based on Monte Carlo simulation and bioaccessibility

Health risks caused by heavy metal (HM) exposure in road dust has attracted extensive attention, but few studies have focused on the health risks of residents living in small- and medium-sized cities with rapid industrialization and urbanization. Thus, 140 road dust samples were collected across Anyang, a typical fourth-tier industrial city in central China, which were analysed for 10 different HMs (Mn, Zn, Pb, V, Cr, As, Cd, Ni, Cu and Co). Monte Carlo simulation and bioaccessibility were used to quantify the health risks of heavy metals comprehensively in road dust. Results revealed a remarkable accumulation of Mn, Zn, Pb, Cd and Cu. According to the Geo-accumulation index and potential ecological risk index, Cd was priority control pollutant. Moreover, 55.0% of the road dust samples reached heavily polluted level, and 52.86% of the samples were at high ecological risk levels. These results illustrated that HM contamination was serious and universal in the road dust of Anyang. The occurrences of HMs were allocated to traffic emissions, natural sources, industrial activities and agricultural activities with contribution rates of 35.4%, 6.0%, 41.6% and 17.0%, respectively. Except for Zn in the gastric phase, all other HMs had relatively low bioaccessibilities in the gastrointestinal system, usually less than 20%. The bioaccessibilities of most HMs were higher in the gastric phase, except for Cr, Ni and Cu, which remained higher in the intestinal phase. The non-carcinogenic risk and carcinogenic risk were remarkably reduced when considering the HM bioaccessibilities in the gastrointestinal system, especially for adults. The outcomes of this paper are valuable for understanding HM contamination in road dust and highlight the importance of risk assessment for populations living in the fourth- and fifth-tier cities.

Contamination Assessment and Potential Human Health Risks of Heavy Metals in Urban Soils from Grand Forks, North Dakota, USA

Heavy metal (HM) pollution of soil is an increasingly serious problem worldwide. The current study assessed the metal levels and ecological and human health risk associated with HMs in Grand Forks urban soils. A total 40 composite surface soil samples were investigated for Mn, Fe, Co, Ni, Cu, Zn, As, Pb, Hg, Cr, Cd and Tl using microwave-assisted HNO3-HCl acid digestion and inductively coupled plasma mass spectrometry (ICP-MS) analysis. The enrichment factor (EF), contamination factor (CF), geoaccumulation index (Igeo), ecological risk and potential ecological risk index were used for ecological risk assessment. The park soils revealed the following decreasing trend for metal levels: Fe > Mn > Zn > Cr > Ni > Cu > Pb > As > Co > Cd > Tl > Hg. Based on mean levels, all the studied HMs except As and Cr were lower than guideline limits set by international agencies. Principal component analysis (PCA) indicated that Mn, Fe, Co, Ni, Cu, Zn, As, Cd, Pb, Cr and Tl may originate from natural sources, while Hg, Pb, As and Cd may come from anthropogenic/mixed sources. The Igeo results showed that the soil was moderately polluted by As and Cd and, based on EF results, As and Cd exhibited significant enrichment. The contamination factor analysis revealed that Zn and Pb showed moderate contamination, Hg exhibited low to moderate contamination and As and Cd showed high contamination in the soil. Comparatively higher risk was noted for children over adults and, overall, As was the major contributor (>50%), followed by Cr (>13%), in the non-carcinogenic risk assessment. Carcinogenic risk assessment revealed that As and Cr pose significant risks to the populations associated with this urban soil. Lastly, this study showed that the soil was moderately contaminated by As, Cd, Pb and Hg and should be regularly monitored for metal contamination.