A comprehensive exploration on the health risk quantification assessment of soil potentially toxic elements from different sources around large-scale smelting area

Spatial interaction and risk zoning of compound pollutants in farmland soils: Insights from heavy metals and polycyclic aromatic hydrocarbons in Hezhang County, China

The accurate identification and assessment of comprehensive risks associated with compound pollution in agricultural ecosystems remain significant challenges due to the complexity of pollution sources, soil heterogeneity, and spatial variability. In this study, bivariate local indicators of spatial association (LISA) were applied to analyze the spatial interaction between heavy metals (HMs) and polycyclic aromatic hydrocarbons (PAHs) in farmland soils in Hezhang County. The results revealed distinct clusters with elevated concentrations of both HMs and PAHs, predominantly in areas affected by long-standing lead-zinc mining and smelting activities. Positive matrix factorization (PMF) was utilized to identify mining and smelting activities, and associated coal consumption as common sources of both pollutants, contributing 53 % and 28 %, respectively. Ecological health risk assessment results indicated that the combined pollution in this area has led to particularly severe ecological and cancer risks, with the pollution coefficient (Pc) exceeding 3.0, and risk values for both adults and children surpassing the threshold of 10-4. Through the integration of advanced bivariate LISA mapping and thorough risk assessment, this study precisely delineated ecological risk zones (33.1 %) and more refined health risk zones (40.1 %) associated with combined pollution. The southwest of Hezhang was identified as a critical hotspot for combined pollution risks, primarily due to intensive mining and smelting activities in the region. Overall, this study underscores the utility of bivariate LISA as a robust approach for delineating spatial clustering patterns caused by combined pollutants. It provides crucial insights for identifying regions with heightened human health and ecological risks in rural settings.

Systematic assessment of source identification and ecological and probabilistic health risks of potentially toxic elements (PTEs) in soils of a typical coal mining area in Guanzhong region

Mining activities may cause the accumulation of potentially toxic elements (PTEs) in surrounding soils, posing ecological threats and health dangers to the local population. Therefore, a comprehensive assessment using multiple indicators was used to quantify the level of risk in the region. The results showed that the mean values of the nine potentially toxic elements in the study area were lower than the background values only for Cr, and the lowest coefficient of variation was 17.1 % for As, and the spatial distribution characteristics of the elements indicate that they are enriched by different factors. The elements Hg and Cd, which have substantial cumulative features, are the key contributors to ecological risk in the study region, which is overall at moderate risk. APCS-MLR model parses out 4 possible sources: mixed industrial, mining and transportation sources (53.98 %), natural sources (24.56 %), atmospheric deposition sources (12.60 %), and agricultural production sources (8.76 %). The probabilistic health risks show that children are more susceptible to health risks than adults; among children, the safety criteria (HI < 1 and CR < 10-4) were surpassed by 29.29 % of THI and 8.58 % of TCR. According to source-orientated health hazards, the element Ni significantly increases the risk of cancer. Mixed sources from industry, mining, and transportation are important sources of health risks. The results of this research provide some scientific references for the management and decrease of regional ecological and health risks.

Levels of potentially toxic and essential elements in Tocantins River sediment: health risks at Brazil's Savanna-Amazon interface

The field study aims to address identified research gaps by providing valuable information on the concentration, spatial distribution, pollution levels, and source apportionment of toxic and essential elements in sediment samples from four sampling sites (P1: Beira Rio (urban area), P2: Bananal (rural area), P3: Embiral (rural area), P4: Cidelândia (rural area) distributed along the middle Tocantins River, Brazil. Samples were collected in 2023 from river sections and analyzed using various contamination índices (geoaccumulation index, contamination factor, enrichment factor, pollution load index, sediment pollution index, potential ecological risk coefficients, and integrated risk index). Results indicated that the levels of aluminum, iron, manganese, and selenium exceeded legal standards in that year. Chromium, nickel, copper, zinc, and lead exceeded guidelines, mainly in section P1 for aluminum and section P3 for nickel and lead. Rainy months showed increased presence, indicating seasonal variability. The geoaccumulation index indicated low pollution levels, with lead and nickel notably present near urban and industrial areas. The enrichment factor highlighted elevated concentrations of lead and zinc in industrial areas. Both PLI and SPI indices raise concerns regarding Pb (P4) and Zn (P3) concentrations at specific times of the year. Overall, potential ecological risks were deemed low for most sites. Continuous monitoring and interventions are crucial to preserve water and environmental quality in the region.

Determination of geochemical baselines and evaluation of potentially toxic elements in agricultural soils of Ramhormoz Plain, Iran

The present study was conducted to investigate the heavy metal pollution status of the agricultural soils in Ramhormoz Plain, Khuzestan province, Iran. A total of 54 samples from the depths (0-20 cm) of the soil were collected from the selected areas in (March) 2021. According to the obtained results, the concentrations of As, Cd, Cr, Cu, Hg, Mn, Ni, Pb, Zn, Al in soil samples were 1.3, 0.68, 60, 10.6, 0.01, 218, 23, 3.65, 14 and 0.58 mg/kg, respectively, in which As showed significant soil contamination and Cu, Hg, Mn, Ni, Pb, Zn and Al moderate contamination according to the calculation of contamination factor (CF). PCA analysis revealed that both anthropogenic and natural sources of pollution like agricultural and transport activities contributed to the enrichment of study area. Investigation of ecological risk indicated that Ramhormoz Plain was categorized as a high risk area.

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.

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.

Spatial variability of heavy metals concentrations in soil of auto-mechanic workshop clusters in Nsukka, Nigeria

The indiscriminate disposal of spent engine oils and other hazardous waste at auto mechanic workshops clusters in Nsukka, Enugu State, Nigeria is an environmental concern. This study examines the concentration of heavy metals in the soil inside the workshop cluster and in the unpolluted soil outside the workshop cluster at approximately 100 m. Ten sampling points were randomly selected from within the cluster and another ten from outside the cluster. Using a hand-held Global Positioning System, the coordinates of the selected points were established and used to create a digital map. Soil samples at depths of 0-30 cm and 30-60 cm, were analyzed for Cu, Fe, Zn, Pb, As and Cd using Spectrophotometer. Moisture content determination and particle size analysis were also done on the samples. Spatial variability of heavy metals concentrations of the studied site was also mapped with ArcGIS 10.2.2 using interpolation methods. Results showed that the soil ranged from sandy loam to sandy clay loam. Cadmium and Zinc had the lowest and highest concentration, respectively, in the studied area. Comparing the concentrations of heavy metals in soils within and outside the auto mechanic cluster revealed notable differences across various depths (0-30 cm and 30-60 cm). The analysis results for soil samples within the cluster exhibited concentration levels (mg/kg) ranging from 0.716-0.751 (Cu), 2.981-3.327 (Fe), 23.464-30.113 (Zn), 1.115-1.21 (Pb), 2.6-2.912 (As), and 0.133-0.365 (Cd) demonstrating a variation pattern in the order of Zn > Fe > As > Pb > Cu > Cd. Conversely, for soil samples outside the cluster, concentration levels (mg/kg) ranged from 0.611-0.618 (Cu), 2.233-2.516 (Fe), 12.841-15.736 (Zn), 0.887-0.903 (Pb), 1.669-1.911 (As), and 0.091-0.091 (Cd). To assess the disparity in heavy metal concentration levels between samples collected within and outside the clusters, ANOVA test was performed. The test showed significant difference in heavy metal concentrations between samples within and outside the auto mechanic cluster (p < 0.05), implying auto mechanic activities significantly impact heavy metal levels within the cluster compared to outside areas. The assessment of soil pollution utilized indices including the Geo-accumulation Index (Igeo), Contamination factor (Cf), and anthropogenic metal concentration (QoC). Zinc, Cadmium, and Arsenic showed the highest contamination factors, indicating significant soil contamination likely due to anthropogenic activities. The concentrations of the metals analyzed were within WHO permissible limits while the metals concentrations were also observed to decrease as depth was increased. Using ArcGIS 10.2.2, spatial maps showing heavy metal distribution were developed, with the Kriging method proving superior. This study suggests that heavy metal levels in the soil at the area be monitored on a regular basis.

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.

Geochemical distribution and environmental assessment of potentially toxic elements in farmland soils, sediments, and tailings from phosphate industrial area (NE Algeria)

This study investigates the extent and spatial distribution of Potentially Toxic Elements (PTEs) in the Djebel Onk phosphate mine area in south-eastern Algeria, as well as the associated risks to human health. Various scales are considered and sampled, including tailing waste (n = 8), surrounding farmland soil (n = 21), and sediments (n = 5). The samples were mineralogically and chemically analyzed using XRD, FTIR, XRF, and ICP-MS techniques. Principal Component Analysis (PCA) was applied after transforming the raw data into centered-log ratios (clr) to identify the dominant factors controlling the distribution of PTEs. Furthermore, pollution assessment was conducted using several indices, including geo-accumulation, pollution load, contamination security indices, and enrichment and contamination factors. The results reveal that the analyzed samples are mostly P-enriched in the mine tailings, farmland soil, and sediments, with P2O5 concentrations ranging from 13.37 wt% to 26.17 wt%, 0.91-21.70 wt%, and 17.04-29.41 wt%, respectively. The spatial distribution of PTEs exhibits clearly a decrease in the contents of CaO, P2O5, Cr, Sr, Cd, and U with increasing distance from the mine discharge site, while other oxides, such as MgO, Al2O3, SiO2, K2O, and Fe2O3, and associated elements (Cu, Co, Pb, and Zn), show an increase. PCA confirms the influence of minerals such as, apatite, dolomite, and silicates on the distribution PTEs. It denoted that the highest contamination level of all PTEs in soils and sediments was observed in the southern part of the plant and mine tailings compared to the northern part. In terms of human health risks, the assessment reveals that the hazard index (HI) values for both non-carcinogenic and carcinogenic risks associated with PTEs in the study area are below 1, suggesting no significant risk. However, regardless of the sample type, the lifetime cancer risk (LCR) values vary from 1.69E-05-2.11E-03 and from 1.03E-04-2.27E-04 for Cr, Ni, As (children) and Cd (adults), respectively, exceeding the safe levels recommended by the United States Environmental Protection Agency. The study highlights that oral ingestion poses the greatest risk, followed by dermal contact and particle inhalation. Importantly, all these indices decrease with increasing distance from the sampling site to the waste discharge point and the factory, which indicates that the phosphate mining activity had caused some extent risks. These findings provide valuable insights for mitigating the adverse health impacts and guiding environmental management efforts.

Integrated pollution analysis, pollution area identification and source apportionment of heavy metal contamination in agricultural soil

Given the global prevalence of soil heavy metal contamination, knowledge concerning of soil environmental quality assessment, pollution area identification and source apportionment is critical for implementation of soil pollution prevention and safe utilization strategies. In this study, soil static environmental capacity (QI) for heavy metals was selected to evaluate pollution risks in agricultural soils of Wenzhou, southeast China. Combined with geostatistical methods, the pollution area was identified along with uncertainty analysis. Potential sources were quantitatively apportioned using a positive matrix factorization model (PMF). Results showed that agricultural soils in this study were mainly contaminated by Cd and Pb based on both Nemerow and QI indices. The environmental capacity assessment found more than 90% areas were identified as polluted soils for Qi-Zn, Qi-Cd and Qi-Pb, with minor uncertain areas. Cu was identified as having a high proportion of uncertain pollution area status, which was similar to the results of the integrated environmental capacity for all metals. PMF results indicated that industrial discharge, agrochemicals and parent material accounted for 32.1%, 32.2% and 35.7% of heavy metal accumulation in soils, respectively. Implementation of strict policies to reduce anthropogenic source emissions and remediate soil pollution are crucial to minimize metal pollution inputs, improve agricultural soil quality and enhance food safety.

Spatial distribution and source identification of metal contaminants in soil and rice grain samples: a study on exploration of soil quality and risk assessment

The present study aims to assess soil quality and potential health risks associated with soil pollution of the Batala region of Punjab, India. Physico-chemical parameters such as pH (6.69-7.43), electrical conductivity (0.17-0.33 mS/cm), and total organic carbon (1.01-5.94%) were observed to be within permissible limits. The maximum mean content (mg/kg) of heavy metals in soil was found as Fe (4060.93), Zn (444.33), Mn (278.5), Pb (23.16), Cu (21.78), Ni (20.16), Co (7.14), and Cd (1.85) which were below the prescribed limits but beyond the geochemical background limits of world soil. For rice grain samples, metal content (mg/kg) was seen as Fe (307.01) > Zn (12.41) > Mn (7.43) > Cu (4.57) and was below the permissible limits. The mean bioaccumulation factor for various metals was in the order as Zn > Cu > Fe > Mn. Single and integrated soil pollution indices revealed that among 18 sites, six were highly contaminated. The ecological risk index (Er) has shown that contamination of soil with Cd, Zn, and Ni was higher than that of other metals studied. The estimated daily intake of metal (EDI), hazard quotient (HQ), and hazard index (HI) were higher for children than those for adults. Spatial variability based on metal pollution load and soil quality was also determined using cluster analysis (CA) and principal component analysis (PCA). During CA, soil samples from 18 sites formed three statistically significant clusters based on the level of metal pollution at the specific site. PCA showed that all variables were reduced into two main components 1 and 2 with eigenvalues as 3.82 (47% variance) and 1.53 (19.7% variance), respectively.

Incorporating environmental capacity considerations to prioritize control factors for the management of heavy metals in soil

Heavy metals (HMs) pollution threatens food security and human health. While previous studies have evaluated source-oriented health risk assessments, a comprehensive integration of environmental capacity risk assessments with pollution source analysis to prioritize control factors for soil contamination is still lacking. Herein, we collected 837 surface soil samples from agricultural land in the Nansha District of China in 2019. We developed an improved integrated assessment model to analyze the pollution sources, health risks, and environmental capacities of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn. The model graded pollution source impact on environmental capacity risk to prioritize control measures for soil HMs. All HMs except Pb exceeded background values and were sourced primarily from natural, transportation, and industrial activities (31.26%). Approximately 98.92% (children), 97.87% (adult females), and 97.41% (adult males) of carcinogenic values exceeded the acceptable threshold of 1E-6. HM pollution was classified as medium capacity (3.41 kg/hm2) with mild risk (PI = 0.52). Mixed sources of natural backgrounds, transportation, and industrial sources were identified as priority sources, and As a priority element. These findings will help prioritize control factors for soil HMs and direct resources to the most critical pollutants and sources of contamination, particularly when resources are limited.

Distribution of potentially toxic elements in soils and sediments in Pearl River Delta, China: Natural versus anthropogenic source discrimination

Although anthropogenic contamination has been regarded as the most important source of potentially toxic elements (PTEs) in soils of large river delta plains, the extent to which human activities affect PTEs in soils is worth exploring. This study used high density geochemical data to distinguish source patterns of PTEs in soils of the Pearl River Delta Economic Zone, a large industrialized and urbanized area in China. Enrichment factor, discriminant analysis, principal components analysis, cumulative distribution function, and positive matrix factorization were used to identify sources of PTEs in soils. The results indicated that parent material was the most significant factor affecting geochemical characteristics of PTEs in soils. Median concentrations of Cd, Cr, Cu, Hg, Pb, and Zn were 0.400, 88.5, 40.5, 0.143, 43.0, and 116.0 mg/kg for stream sediments, 0.333, 75.7, 39.0, 0.121, 42.6, and 98.5 mg/kg for deep soils, and 0.365, 74.0, 45.1, 0.143, 44.6, and 119.5 mg/kg for surface soils, respectively, all of which exceed relevant reference standards. Compared with stream sediments and deep soils, surface soils exhibit substantial concentrations of PTEs. Chemical weathering and erosion of parent materials distributed in the Pearl River Delta were the main sources of PTEs in soils. Diffuse contamination and many small local contamination sources distributed throughout the study area were the most significant anthropogenic sources of PTEs in surface soils. Intensive human activities failed to change the soil geochemical characteristics derived from the parent material at the regional scale. However, it could induce non-point source pollution and local severe PTEs pollution in surface soils.

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

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

Integrating multiple spheres to identify the provenance and risk of urban dust and potentially toxic elements: Case study from central Mexico

This study aims to improve the current method of studying potentially toxic elements (PTEs) in urban dust using direct chemical evidence (from dust, rock, and emission source samples) and robust geochemical methods. The provenance of urban dust was determined using rare earth elements (REEs) and geochemical diagrams (V-Ni-Th*10, TiO2 vs. Zr, and Zr/Ti vs. Nb/Y). The geogenic or anthropogenic source of PTEs was determined using the enrichment factor (EF) and compositional data analysis (CoDA), while a PTE's point emission source was identified using a 3.1*La-1.54*Ce-Zn diagram, mineralogy, and morphology analyses. The spatiotemporal distribution of PTEs was determined using a geographic information system, and their health risk (by inhalation) was estimated using a lung bioaccessibility test and particle size distribution. We collected urban dust (n = 38), rock (n = 4), and zinc concentrate (n = 2) samples and determined PTEs and REEs in a city of 1.25 million inhabitants in central Mexico. Results showed that urban dust derived from the San Miguelito Range. REEs, Sc, and Zr were geogenic, while Mn, Cu, Zn, As, and Pb were anthropogenic. Due to the presente of sphalerite particles, a zinc refinery was identified as the point emission source of Zn, As, and Pb. High concentrations of Zn (5000-20,008 mg/kg), As (120-284 mg/kg), and Pb (350-776 mg/kg) were found in urban dust near the zinc refinery. Additionally, particles of PM2.5 (66-84%), PM5.0 (13-27%), PM10 (3-8%), and PM20 (0-2%) and lung bioaccessibility of Sr (48.5-72.4%), Zn (9.6-28.4%), Cu (10.5-27.0%), Fe (4.5-8.6%), Mn (2.9-9.2%), Cr (38.3%) and Pb (30.6%) demonstrated a latent risk to human health. These approaches improve our understanding of the provenance of urban dust and its PTE emission sources in urban areas.

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

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

Assessment of human health risks of toxic elements in coastal area between Al-Khafji and Al-Jubail, Saudi Arabia

The present work aims to document the distribution of toxic elements (TEs) and assess the human health risk posed by the TEs in the marine sediment of the Arabian Gulf, Saudi Arabia. The descending order of TE averages (μg/g) was as follows: Ni > Cr > V > Zn > Pb > Cu > As > Co. Based on the enrichment factor values, only minor enrichment for Pb, As, Cr, and Ni was noted. The hazard index (HI) values for the non-carcinogenic risk of the TEs were less than 1.0, and the lifetime cancer risk values for carcinogenic Pb, Cr, and As ranged between 2.96 × 10-8 and 5.44 × 10-5, indicating no significant health hazards for the inhabitants of the study area.

A comprehensive approach to quantify the source identification and human health risk assessment of toxic elements in park dust

In this research, enrichment factor (EF) and pollution load index were utilized to explore the contamination characteristics of toxic elements (TEs) in park dust. The results exhibited that park dust in the study area was mainly moderately polluted, and the EF values of dust Cd, Zn, Pb, Cu and Sb were all > 1. The concentrations of Cr, Cu, Zn and Pb increased with the decrease of dust particle size. The investigation results of chemical speciation and bioavailability of TEs showed that Zn had the highest bioavailability. Three sources of TEs were determined by positive matrix factorization model, Pearson correlation analysis and geostatistical analysis, comprising factor 1 mixed sources of industrial and transportation activities (46.62%), factor 2 natural source (25.56%) and factor 3 mixed source of agricultural activities and the aging of park infrastructures (27.82%). Potential ecological risk (PER) and human health risk (HHR) models based on source apportionment were exploited to estimate PER and HHR of TEs from different sources. The mean PER value of TEs in the park dust was 114, indicating that ecological risk in the study area was relatively high. Factor 1 contributed the most to PER, and the pollution of Cd was the most serious. There were no significant carcinogenic and non-carcinogenic risks for children and adults in the study area. And factor 3 was the biggest source of non-carcinogenic risk, and As, Cr and Pb were the chief contributor to non-carcinogenic risk. The primary source of carcinogenic risk was factor 2, and Cr was the cardinal cancer risk element.

Source-oriented ecological and resistome risks associated with geochemical enrichment of heavy metals in river sediments

Heavy metals (HMs) pose ecological and resistome risks to aquatic systems. To efficiently develop targeted risk mitigation strategies, apportioning HM sources and assessing their source-oriented risks are essential. Although many studies have reported risk assessment and source apportionment of HMs, yet few have explored source-specific ecological and resistome risks associated with geochemical enrichment of HMs in aquatic environments. Therefore, this study proposes an integrated technological framework to characterize source-oriented ecological and resistome risks in the sediments of a plain river in China. Several geochemical tools quantitatively showed Cd and Hg had the highest pollution levels in the environment, with 19.7 and 7.5 times higher than their background values, respectively. Positive matrix factorization (PMF) and Unmix were comparatively used to apportion sources of HMs. Essentially, the two models were complementary and identified similar sources including industrial discharges, agricultural activities, atmospheric deposition and natural background, with contributions of 32.3-37.0%, 8.0-9.0%, 12.1-15.9% and 42.8-43.0%, respectively. To analyze source-specific ecological risks, the apportionment results were integratively incorporated into a modified ecological risk index. The results showed anthropogenic sources were the most significant contributors to the ecological risks. Particularly, industrial discharges majorly contributed high- (44%) and extremely high (52%) ecological risk for Cd, while agricultural activities posed a greater percentage of considerable-(36%) and high- (46%) ecological risk for Hg. Furthermore, the high-throughput sequencing metagenomic analysis identified abundant and diverse antibiotic resistance genes (ARGs), including some carbapenem-resistance genes and emerging genes such as mcr-type in the river sediments. Network and statistical analyses displayed significant correlations between ARGs and geochemical enrichment of HMs (ρ > 0.8; P-value <0.01), indicating their important impacts on resistome risks in the environment. This study provides useful insights into risk prevention and pollution control of HMs, and the framework can be made applicable to other rivers facing environmental challenges worldwide.

Soil heavy metal(loid) pollution and health risk assessment of farmlands developed on two different terrains on the Tibetan Plateau, China

The quality of farmland soils on the Tibetan Plateau is important because of the region's ecological vulnerability and their close link with local food security. Investigation on the pollution status of heavy metal (loid)s (HMs) in the farmlands of Lhasa and Nyingchi on the Tibetan Plateau, China revealed that Cu, As, Cd, Tl, and Pb were apparently enriched, with the soil parent materials being the primary sources of the soil HMs. Overall, the farmlands in Lhasa had higher contents of HMs compared to those in the farmlands of Nyingchi, which could be attributed to the fact that the former were mainly developed on river terraces while the latter were mainly developed on the alluvial fans in mountainous areas. As displayed the most apparent enrichment, with the average concentrations in the vegetable field soils and grain field soils of Lhasa being 2.5 and 2.2 times higher compared to those of Nyingchi. The soils of vegetable fields were more heavily polluted than those of grain fields, probably due to the more intensive input of agrochemicals, particularly the use of commercial organic fertilizers. The overall ecological risk of the HMs in the Tibetan farmlands was low, while Cd posed medium ecological risk. Results of health risk assessment show that ingestion of the vegetable field soils could pose elevated health risk, with children facing greater risk than adults. Among all the HMs targeted, Cd had relatively high bioavailability of up to 36.2% and 24.9% in the vegetable field soils of Lhasa and Nyingchi, respectively. Cd also showed the most significant ecological and human health risk. Thus, attention should be paid to minimize further anthropogenic input of Cd to the farmland soils on the Tibetan Plateau.

Quantitative analysis of the contribution of sources, diffusion pathways, and receptor attributes for the spatial distribution of soil heavy metals and their nested structure analysis in China

Investigation of heavy metal pollution degree, pollution sources, and spatial distribution structure is crucial for the country's soil pollution prevention, but relevant research is lacking. In this study, As, Cd, Cr, Cu, Pb and Zn in the national scope are taken as research objects. Among them, Cd has the highest pollution level. Four sources were quantitatively allocated as soil type, mining and dressing industry, GDP, and NDVI, which accounted for 92.93, 97.81, 99.30 and 96.24 % of Cr, Cd, Zn and As contamination, respectively. In addition, according to the geographical detector, the spatial distribution of As was affected by three diffusion pathways, whose influence degree were 0.822-0.947, especially the slope. Cadmium was primarily affected by both receptor attributes and diffusion pathways, with an influence degree of 0.010-0.175, especially soil water content and slope; Cr and Pb were affected by receptor attributes, with an influence degree of 0.886-0.986 and 0.007-0.288, respectively, especially for soil water content and soil organic carbon; Cu and Zn were affected by receptor attributes, with an influence degree of 0.182-0.823 and 0.002-0.150, respectively, especially for soil texture. There are two spatial distribution structures with nested scales in east-west and north-south directions. The large spatial structure has a more significant impact on the spatial distribution of heavy metals, especially in the east-west direction. Overall, the mining and dressing industry is the main source in Hunan, Yunnan, and Liaoning, where many mines exist and mining activities are frequent. GDP was the main source in Shanghai and Zhejiang areas, where the economy is developed. NDVI was the main source in Guangdong and Anhui areas, where agriculture is relatively developed. These results provide a basis for determining remediation and prevention objectives in soil pollution remediation and prevention in the national scope.

Spatiotemporal patterns of soil heavy metal pollution risk and driving forces of increment in a typical industrialized region in central China

Excessive enrichment of soil heavy metals seriously damages human health and soil environment. Exploring the spatiotemporal patterns and detecting the influencing factors are conducive to developing targeted risk management and control. Based on the soil samples of Co, Cr, Cu, Mn, Ni, Pb, Zn, and Cd collected in one typical industrialized region in China from 2016 to 2019, this study analyzed the spatiotemporal pattern of geo-accumulation risk and potential ecological risk based on the spatiotemporal ordinary kriging (STOK) prediction, and probed the driving forces of heavy metal increments with the random forest (RF) regression model. The risk assessment revealed that soils were seriously contaminated by Pb, Cd, and Cu, moderately contaminated by Zn and Mn, and uncontaminated by Co, Cr, and Ni; more than 30% of areas had moderate to high potential ecological risks. From 2016 to 2019, soil heavy metal contents increased in more than 50% of regions and the growth rates of accumulations were ranked as Co (65%) > Ni (56%) > Mn (43%) > Pb (40%) > Cr (36%) > Zn (31%) > Cu (23%) > Cd (3%). High contents and increases of heavy metals in soils near industrial lands are higher. Smelter (24%), mine (20%), and factory (12%) were the major contributing factors for these heavy metal increments, followed by transportation (6%) and population (5%). The results indicated that the management of industrial discharge and contaminated soils should be strengthened to prevent the worsening soil heavy metal pollution in the study area.

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.

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

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

Distribution, sources and health risks of heavy metals in indoor dust across China

The potential effects of heavy metals on human health have attracted increasing attention as most people spend up to 90% of their time indoors. Human exposure to heavy metals in indoor dust have only been characterised for limited regions in China, and full-scale data for different functional areas are not available. Therefore, this review analysed the concentrations, contamination characteristics, and potential health risks of seven heavy metals (including zinc (Zn), lead (Pb), copper (Cu), chromium (Cr), nickel (Ni), arsenic (As), and cadmium (Cd)) in indoor dust at 3392 sampling sites in 55 cities across 27 provincial regions of China based on literature data. Results revealed that the median heavy metal concentrations in indoor dust throughout China decreased in the following order: Zn > Pb > Cu > Cr > Ni > As > Cd. Traffic emissions and decorative materials are the primary sources of heavy metal pollution in indoor dust. No considerable non-carcinogenic risk was found for Zn, Cu, Cr, Ni, and Cd in indoor dust, while Pb and As exhibited potential non-carcinogenic risks to children, primarily distributed in cities across Southern China. Meanwhile, the carcinogenic risks posed by Cr and Ni were higher than those posed by As and Cd, especially in Southern China. Therefore, effective measures in Southern China should prioritised for controlling Pb, Cr, Ni and As pollution in indoor dust to reduce human health risk. This review is useful for policy decision-making and protecting human from exposure to heavy metals in indoor dust across China.

Ecological-health risks assessment and source apportionment of heavy metals in agricultural soils around a super-sized lead-zinc smelter with a long production history, in China

Smelting activities are considered as the primary cause of heavy metal (HM) accumulation in soils, and the human health around the smelter has been a great concern worldwide. In this study, a total of 242 agricultural soil samples were collected around a large scale Pb/Zn smelter in China, and eight HMs (As, Cd, Cr, Cu, Hg, Ni, Pb and Zn) were analyzed to assess HMs status, ecological -health risks, and identify source. Monte Carlo simulation was utilized to evaluate the probabilistic health risks, and positive matrix factorization (PMF) was employed to identify sources. The results revealed the average contents of five heavy metals (Cd 5.28 mg/kg, Pb 203.36 mg/kg, Hg 0.39 mg/kg, Zn 293.45 mg/kg, Cu 37.14 mg/kg) are higher than their background values in Hunan province. Cd had the highest mean pollution index (PI) of 41.8 and the greatest average ecological risk index (E_r) of 1256.34, indicating that Cd was the primary enriched pollutant and had a higher ecological risk than other HMs. The mean hazard index (HI) through exposure to eight HMs was 2.95E-01 and 9.74E-01 for adults and children, respectively, with 35.94% of HI values for children exceeding the risk threshold of 1. Moreover, the mean total cancer risks (TCR) were 2.75E-05 and 2.37E-04 for adults and children, respectively, with 75.48% of TCR values for children exceeding the guideline value of 1E-04. In addition, the positive matrix factorization results showed smelting activities, natural sources, agricultural activities and atmospheric deposition were the three sources in soils, with the contribution rate of 48.62%, 22.35%, and 29.03%, respectively. The uncertainty analysis of the PMF indicated that the three-factor solution is reliable. This work will provide scientific reference for the comprehensive prevention of soil HM pollution adjacent to the large smelter.