Sources Of Heavy Metals Research Articles

Determination of priority control factors for risk management of heavy metal(loid)s in park dust in Mianyang City

In order to determine the priority control elements and sources of heavy metal(loid)s (HMs) pollution in park dust, this study collected dust samples from 25 parks in the urban area of Mianyang City and measured the contents of 10 HMs. Based on Monte Carlo simulation, the probabilistic pollution levels and ecological-health risks of HMs were assessed. We found that the average contents of Zn, Co, Pb, and Cr were much higher than their background values in local soil and were influenced by artificial activities. The pollution assessment found that 5 parks were moderately polluted. The comprehensive pollution of HMs in the dust was mainly caused by Zn and Cr, and industrial source was the main contributor to Zn and Cr pollution. The contribution of As, Co, and Pb to the comprehensive ecological risk was high, accounting for 54.6%. Co, Pb, and As were the priority control HMs of ecological risk, while mixed source and industrial source were the priority control sources. HMs presented potential carcinogenic health risks to both children and adults. The non-carcinogenic risk to adults was within safety level, while some parks showed non-carcinogenic risk to children, which should be paid attention to. The source-specific health risk assessment showed that Cr and As were the priority control HMs for human health, while mixed source and industrial source were the priority control sources.

How Has the Source Apportionment of Heavy Metals in Soil and Water Evolved over the Past 20 Years? A Bibliometric Perspective

Exploring soil heavy metal sources is of great significance for ensuring the safety of ecological environments and agricultural product safety, as well as for guiding pollution control and management policies. This paper retrieved 452 research papers on soil heavy metal source analysis published over the 2004–2024 period from the Web of Science database. The collected literature was subjected to multidimensional bibliometric analysis using the CiteSpace 6.3.R1. The results showed significantly increasing trends in the scientific outputs and the number of papers on heavy metal source analysis in soils and water over the study period. In addition, related research topics have expanded from single to multiple heavy metal elements in environmental media and have increasingly recognized the impact of water pollution on soil contamination. Research methods have also evolved from basic statistical analysis to complex spatial analysis techniques, covering agricultural and urban soils. Previous related studies have focused on heavy metal pollution in different areas, and related research on heavy metal source analysis has now extended from ecological environments to associated human health risks. The present study provides directions for future related research and guidance for ensuring effective source control of heavy metal pollution and safe utilization of land and water resources.

Microbiome divergence across four major Indian riverine water ecosystems impacted by anthropogenic contamination: A comparative metagenomic analysis

Rivers are critical ecosystems that support biodiversity and local livelihoods. This study aimed to evaluate the effects of metal contamination and anthropogenic activities on microbial and phage community dynamics within major Indian river ecosystems, focusing on the Ganga, Narmada, Cauvery, and Gomti rivers -using metagenomic techniques, Biolog, and ICP-MS analysis. Significant variations in microbial communities were observed both within each river and across the four systems, influenced by ecological factors like geography and hydrology, as well as anthropogenic pressures. Downstream sites consistently exhibited higher microbial diversity, with prevalence of Acidobacteria, Actinobacteria, Verrucomicrobia, Firmicutes, and Nitrospirae dominating, while Proteobacteria and Bacteroides declined. The Ganga River showed a higher abundance of bacteriophages compared to other rivers, which gradually reduced with the increment of anthropogenic impact. Functional gene analysis revealed correlations between carbon utilization and metal resistance in contaminated sites. ICP-MS analysis indicates elevated chromium and lead levels in downstream sites of all rivers compared to upstream sites. Interestingly, pristine upstream sites in the Ganga had higher trace element levels than those in Narmada and Cauvery, likely due to its Himalayan origin. Both the Ganga and Cauvery rivers contained numerous metal resistance genes. The Alaknanda was identified as the primary source of microbial communities, bacteriophages, trace elements, and heavy metals in the Ganga. These findings offer new insights into anthropogenic influences on river microbial dynamics and highlight the need for targeted monitoring and management strategies to preserve river health.

Assessment of Heavy Metal Sources and Microplastics in Drainage Deposited Sediments from Highways and Rest Areas

Assessment of Heavy Metal Sources and Microplastics in Drainage Deposited Sediments from Highways and Rest Areas

Study on the source identification and migration and transformation characteristics of heavy metal pollution in sediments of Chaohu Lake Tongyang River Basin.

Heavy metal pollution in soil and groundwater is difficult to detect in time because of its long-term accumulation. This poses a severe hazard to the ecosystem security in polluted areas. Considering the Tongyang River Basin of the Chaohu Lake water system as the research object, various pollution evaluation methods, Geographic Information System (GIS) source analysis models, adsorption and desorption experiments, and mathematical models were used. Based on the data of the heavy metal content in the soil and river sediments in the study area, regional heavy metal pollution evaluation, spatial distribution characteristics, source identification, and lake loss analysis were conducted to evaluate the current situation of environmental pollution, pollution sources, and migration and transformation of heavy metals in the basin. The results show that the heavy metals in the soil of the basin are mainly distributed from the southwest to the northeast and the island distribution to the east of Tongyang Town. The Cd, Cu, Zn, and Pb concentrations are higher in the sediment than in the soil. The Unmix analytical model was established. The natural source of heavy metals in the Tongyang River Basin and the composite pollution source of traffic-production and life showed a high correlation. According to the one-dimensional steady-state model, the concentrations of the heavy metals are in the following descending order: Zn, Cr, Pb, Cu, Ni, and Cd. The amounts of these elements entering the lake annually are 1993.04, 1028.1, 372.47, 301.72, 308.80, and 19.46 kg, respectively (a total of 4023.6 kg).

Pollution of Heavy Metals in Topsoil of Remote Mountainous Areas in Western Yunnan-Guizhou Plateau

Heavy metals from anthropogenic emissions have had a negative impact on the ecological environment in remote regions. A total of 69 topsoil samples were collected from 13 remote mountainous areas in the western Yunnan-Guizhou Plateau at altitudes of 2 563-4 037 m, and the concentrations of ten heavy metals in the samples were determined. Enrichment characteristics and pollution sources of heavy metals in topsoil were discussed by referencing the enrichment factor （EF）, positive matrix factorization （PMF）, and Pb isotopes. The results showed that the average concentrations of Al, Fe, Cu, V, and Zn in the topsoil were lower than the soil background values in Yunnan Province； the average concentrations of Ni and Pb were similar to the background values； and the average concentrations of Cd, Cr, and Hg were 1.8-3.6 times higher than the background values. The average EF values of Pb, Cr, and Ni were 3.8, 3.4, and 2.3, respectively, showing moderate enrichment according to the EF classification criteria； the average EF values of Cd and Hg were 15.2 and 10.0, reflecting significant enrichment； and the average EF values of the other metals ranged from 1.1 to 1.9, displaying none-weak enrichment. Combining the comparisons of heavy metal concentrations and ratios in topsoil and bedrock and the EF and PMF results, Al, Fe, V, Cr, Cu, Ni, and Zn in topsoil were considered primarily from detrital sources, and the spatial concentration variations of the metals should have been mainly regulated by the parent material. Cadmium, Hg, and Pb were obviously polluted by anthropogenic emissions, and the main sources were non-ferrous metal smelting and coal combustion. The areas with relatively high Cd, Hg, and Pb pollution were mainly distributed in the Jiaozi snow mountain, Bitahai watershed, Luoji Mountain, and Laojun Mountain areas. Anthropogenic emissions contributed 23.8% of the accumulation of heavy metals in the topsoil.

Characteristics, Source Apportionment, and Health Risk of Heavy Metals in the Soils of Peri-urban Shanghai Chongming Island.

Heavy metals resulting from human activities pose significant threats to human health and the soil ecosystem. In the current study, 917 soil samples from Chongming Island in Shanghai, China, were examined for eight heavy metals. The sources of contamination were identified by using a Positive Matrix Factorization (PMF) model. Meanwhile, spatial interpolation and Moran's I index were applied to validate the model in terms of spatial linkages. The results revealed that the average concentrations of As, Cd, Hg, Pb, Cr, Cu, Zn, and Ni in the soil were 8.87, 0.19, 0.06, 28.75, 76.01, 37.74, 88.93, and 30.33 mg kg-1, respectively. The PMF analysis proved that heavy metals in the soil of the study area are mainly influenced by traffic sources (Cr and Pb), industrial sources (Zn, Cd, and Cu), station sources (Hg), and natural sources (As and Ni), with contribution rates of 22.23, 26.25, 36.38, and 15.14%, respectively. The combination of Moran's index and the spatial analysis method not only verified the analytical results of the receptor model on the one hand but also served as a supplementary explanation for the sources of heavy metals in the soil. The health risk assessment indicated that noncarcinogenic values were below the threshold values. The total carcinogenic risk (R T) of different heavy metals has a descending order of Cr > As > Ni > Cd. The R T values of multiple heavy metals for children and adults were 5.28 × 10-04 and 4.10 × 10-05, respectively, which were close to the risk threshold. Therefore, attention should be paid to the health risks, especially for children's skin contact, which is the main exposure pathway.

Human and environmental risk assessment and plausible sources of toxic heavy metals at beach placers in southeast Sri Lanka

Beach placers are typically rich in heavy minerals, which are crucial for a wide range of industrial applications. This study investigates the human and environmental risks posed by toxic heavy metals (As, Pb, Zn, Cu, Cr, Fe, V and Mn) in beach placers of southeastern Sri Lanka using 42 X-ray fluorescence data. Risk indicators (EF, Igeo, CF and PLI) indicate the polluted nature of the placers. Correlation analysis (correlation matrix and HCA) identified pollution sources as heavy mineral-rich rocks, agricultural fertilizers, pesticides and municipal wastes. The environmental impact caused by toxic metals is less in placers. The highest non-carcinogenic risks (HI) resulted by Cr (1.69E+00), V (4.29E+00) and Fe (2.06E+00) to children. The total cancer risk of As and Cr in placers is unacceptable (children: 2.60E-04, 2.48E-03, and adults: 3.14E-05, 2.87E-04, respectively). Different strategies are introduced to mitigate the identified risks in source areas and the coastal environment.

Heavy metal contamination assessment and source attribution in the Vicinity of an iron slag pile in Hechi, China: Integrating multi-medium analysis

Heavy metals, such as mercury, cadmium, and nickel, may contaminate human inhabited environments, with critical consequences for human health. This study examines the health impacts of heavy metal pollution from an iron slag pile in Hechi, China, by analyzing heavy metal contamination in water, sediment, soil, and crops. Here, the Nemerow pollution index (NI) indicated severe pollution at most sampling sites, the mean NI of groundwater, and surface water had reached 594.13 and 26.79, respectively. Bioaccumulation of mercury (Hg), cadmium (Cd), and nickel (Ni) was noted in crops, cucumbers showed comparatively lower risk levels. Logarithmic surface water-sediment partition coefficient calculations indicated that heavy metals such as chromium (Cr), ferrum (Fe), zinc (Zn), copper (Cu), Ni, arsenic (As), and lead (Pb) tend to accumulate in sediments. There was a high risk in groundwater (67.48–6590.54) and surface water (13.73–2500.85). Variably influenced by rainfall, these metals can be diluted and mobilized from surface water and sediments, thereby changing the contamination levels and ecological risks. Probabilistic health risk assessments indicated that health risks were higher in children than in adults, the mean total carcinogenic risk values of soil, groundwater, and surface water, were 6.79E-04, 4.20E-06, and 1.15E-6 for children, respectively. Moderate soil pollution is the main health hazard. A Positive Matrix Factorization model attributed over 60% of the pollution to slag stacking. Biotechnologies, solidification/stabilization techniques, field management, and institutional controls, driven by principles of green, low-carbon, and economic efficiency may mitigate. These findings contribute to the management of heavy metal pollution in iron slag pile areas.

Characteristics and health risks assessment of PM2.5-bound heavy metals during winter in urban areas of northern China: A case study in Kaifeng

The health impact of heavy metals in atmospheric PM2.5 has garnered increasingly widespread attention. We have collected PM2.5 samples in a typical city (Kaifeng) within the Central Plains Urban Agglomeration in China during winter and measured the mass concentration of PM2.5-bound heavy metals. The pollution of As and Cr in the urban atmosphere requires significant attention. As PM2.5 concentrations increased, the enrichment factors (EFs) of Mn, Cu, Zn, As, and Pb also rose, suggesting a growing contribution from anthropogenic emissions. The analysis showed that the hazard quotient (HQ) for the non-heating and heating periods (HQ < 1) did not result in a cumulative non-carcinogenic health risk to humans. Regarding carcinogenic effects, As and Cr exhibit significant carcinogenic impacts on both children and adults (ELCR>1 × 10−6), indicating that the carcinogenic risks posed by As and Cr under PM2.5 exposure in Kaifeng could not be overlooked. It was found that industrial and biomass combustion are the primary sources of carcinogenic risk in Kaifeng city. From the non-heating to the heating period, the industrial carcinogenic risk increased from 37.12 % to 43.39 %, while the contribution of biomass burning remained at 25 %. This result was strongly correlated with the high proportions of heavy metal elements such as As, Mn, Pb, and Ni from the metal refinery industry. The results of this study revealed the equally important source of heavy metals, compared to coal combustion in North China Plain. In addition to residential coal combustion, industrial emissions are a major source of PM2.5-bound heavy metals in Kaifeng, contributing significantly to overall air pollution and providing a useful reference to mitigating human health risks in the area.

Determining the priority control sources of heavy metals in the roadside soils in a typical industrial city of North China

Heavy metals (HMs) in roadside soils (RS) are closely related to urban ecosystem and human health, but priority control sources and eco-health risks of HMs remain unclear. We explored pollution sources of HMs using positive matrix factorization (PMF), scanning electron microscopy with energy dispersive spectroscopy (SEM-EDS), and random forest (RF), and assessed their source-specific eco-health risks. The combination of PMF, SEM-EDS and RF indicated that pollution sources of HMs were coal combustion (27.99%), construction materials (30.15%), and traffic emissions (41.86%). SEM-EDS revealed RS particles were identified by a combination of physical (spherical, porous rounded, crustal flake, crustal rounded and irregular particles) and elemental surface characteristics (O, C, Si, Al, Fe, Ca, Mg, K, Zn, Cu, and Mn). RF highlighted road network density, residential density, and industrial density had significant importance influence on pollution sources. Approximately 72.35% of soil samples were at a low ecological risk with traffic emissions being the major contributor. Non-carcinogenic risks had a minimal effect, but carcinogenic risks were at a cautionary level with coal combustion being the highest contributor. Overall, coal combustion and traffic emissions were regarded as priority control sources of HMs. These findings provided effective guidance for soil pollution prevention and risk control.

Quantification of heavy metal contamination and source in urban water sediments using a statistically determined geochemical baseline

Geochemical baselines (GBs) play a crucial role in discerning natural variability from anthropogenic impacts on elemental composition within the environment. However, their applicability in quantifying the contribution of pollution sources to heavy metal contamination in sediments remains understudied. This research aimed to assess the degree of contamination and local pollution source attribution by leveraging geochemical baselines derived from statistical techniques, specifically the relative cumulative frequency (RCF) and 2σ-iterative (2σ-I) methods. In the urban water systems of Ma’anshan City, the major iron ore centre in eastern China, we observed concentration ranges of Cr, Cu, Ni, Pb and Zn in 36 sediment samples ranging from 66.89 to 352.08 mg/kg, 22.01 to 133.37 mg/kg, 22.66 to 50.80 mg/kg, 14.66to 264.37 mg/kg and 73.30 to 2707.46 mg/kg, respectively. RCF and 2σ-I techniques yielded similar GBs with no significant differences (p > 0.05). The geo-accumulation index and contamination factor analysis showed a sediment heavy metal accumulation rank of Zn > Pb > Cr > Cu > Ni. The contribution percentage of pollution sources varied with land functional type of watershed. For industry-influenced sediments, the contribution of local sources to Cr, Cu, Pb and Zn was significant, with shares of 43%–88%. Overall, this study highlights the valuable insights provided by GBs for effective management of urban aquatic environments.

Assessment of soil environmental capacity for heavy metals in Shantou City, Guangdong Province, China: source analysis and enrichment evaluation.

Most studies assessing soil environmental capacity (EC) often overlook the impact of heavy metal sources. Analyzing the sources of heavy metals (HMs) provides a better understanding of regional environmental capacity characteristics and their dynamic changes. The current study focuses on the surface soil of Shantou, using 511 soil samples to assess the soil environmental capacity. Results indicate that the contents of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn in Shantou's surface soil are notable, with lead moderately enriched and other metals lightly enriched. The principal component analysis (PCA) identifies five primary sources of heavy metals: mixed natural and agricultural sources, mixed agricultural and industrial sources, industrial sources, mining sources, and quarrying sources. The primary source contributing significantly to soil HM concentrations in Shantou City is a complex interplay between natural geological processes and extensive agricultural practices. In terms of static environmental capacity, Zn, Cr, Ni, Pb, Cu, As, Hg, and Cd are ranked in descending order. The overall environmental capacity for heavy metals in the soil is at a medium level, influenced by geological backgrounds. However, regions such as Yanhong Town, Guiyu Town, and Chendian Town face lower environmental capacities due to comprehensive human activities, posing certain risks. This study provides a scientific reference for forecasting, controlling soil heavy metal pollution, and improving soil quality and environmental capacity in Shantou City.

Incorporating source apportionment and health risk assessment of heavy metals from indoor dust of an industrial area in Dhaka, Bangladesh

A total of 45 deposited dust samples were collected from the preselected 15 households near an industrial area at Savar, Bangladesh. The concentrations of metals were measured by EDXRF spectroscopy and was found at the following trend: Ca > Fe > K > Ti > Mn > Zr > Sr > Rb > Zn > Cu > Pb > Co. The average concentrations of Cu, Zn, Zr, and Pb were found to be higher than that of the soil background values set by Chinese Environmental Protection Administration (CEPA) and the upper continental crust (UCC), while the average concentrations of K, Ti, Fe, and Rb were found to be higher than that of the background values and lower than that of UCC. Alternately, %RSD for some toxic metals (i.e., Fe, Co, Zn and Pb) in the dust samples were ranged broadly (%RSD: 33.54–86.88 %), which indicates that these trace metals might be present in indoor dust samples due to anthropogenic sources, which is consistent with the ANOVA test. In this study, the contamination levels of metals were assessed based on the enrichment factor (EF), pollution load index (PLI), and geo-accumulation index (Igeo). The two ways ANOVA (Fcal = 3.86 >Fcritic = 1.78, df = 14) for EF data had revealed the heterogeneity of metal enrichment in the study area, whereas PLI values were close to 1.0 or > 1, which indicated that the indoor dust samples in the study area might be deteriorated of site quality by the studied metals. The analysis of Igeo also revealed that these dust samples are slightly to extremely polluted. Conversely Pearson correlation analysis, principal component analysis, and cluster analysis were employed to identify the possible sources of such heavy metals, which suggested that the anthropogenic sources are the main sources of the examined heavy elements. Subsequently, the human health risk assessment strategies were applied to identify the routes of exposures based on the US EPA health risk models. For non-cancer effect, ingestion of dust particles is the main exposure route to both the children and adults. The total hazard index (HI) values indicate that both children and adults are vulnerable to non-carcinogenic effect, but children are more vulnerable than adults (tstat = 1.97 >tcritic = 2.039, p = 0.029) at a 95 % confidence level. Nevertheless, no significant carcinogenic health risk due to the presence of Co was found for both children and adults in the study area. According to sensitivity analysis, the ingestion rate (IR) and the concentration of Co posed the most significant impact (> 79.9 %) on cancer risk estimation.

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

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

Content, Sources, and Ecological Risk Assessment of Heavy Metals in Soil of Typical Karst County

Soil heavy metals in karst areas have obvious high background value characteristics. Conducting county-level soil heavy metal ecological risk assessment and identifying heavy metal sources in karst areas are of great significance for soil pollution control and land resource management. Taking Pingguo City, a typical karst county in Guangxi Province, as the study object, 3 151 surface and deep soil samples were collected using the grid method and combined to form 785 analytical samples. The contents of eight heavy metal elements, including As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn, were determined. The content characteristics and sources of heavy metals were analyzed using statistical analysis, interpolation analysis, factor analysis, and the absolute principal component-multiple linear regression model （APCS-MLR）. Using the content of heavy metal elements in deep soil （150-200 cm） as background values, the ecological risk assessment of heavy metals in surface soil （0-20 cm） in the study area was conducted using the geo-accumulation index （Igeo） and potential ecological risk index （RI） methods. The results showed that the average content of heavy metal elements in the deep soil of the study area was significantly higher than the background value of the C layer soil in Guangxi Province, and the average content of heavy metal elements in the surface soil was significantly higher than the background value of the A layer soil in Guangxi Province. The spatial distribution of soil heavy metal element content generally showed the characteristics of high in karst areas and low in non-karst areas. The main sources of As, Cr, Ni, Pb, and Zn were soil parent materials, with contribution rates of 74.36%, 84.59%, 93.69%, 79.67%, and 78.17%, respectively. The main sources of Cd were soil parent material sources and unknown sources, with contribution rates of 37.33% and 31.05%, respectively. The main sources of Cu were soil parent materials and unknown sources, with contribution rates of 59.07% and 40.23%, respectively. The main sources of Hg were tectonic activity and mineralization, as well as unknown sources, with contribution rates of 52.49% and 30.65%, respectively. The geo-accumulation index （Igeo） showed that the surface soil was mainly polluted by Cd, with mild or above pollution accounting for 47.78%. The potential ecological risk index （RI） showed that the proportion of surface soil heavy metal comprehensive potential ecological hazards with mild, moderate, strong, and very strong levels was 80.78%, 14.97%, 2.51%, and 1.64%, respectively.

Source and Influencing Factor Analysis of Soil Heavy Metals Based on PMF Model and GeoDetector

In Lijiang City, as a typical example, 93 soil samples were collected from the study area, and soil pH； organic matter； and heavy metals arsenic （As）, mercury （Hg）, copper （Cu）, zinc （Zn）, lead （Pb）, cadmium （Cd）, and chromium （Cr） were determined. We explored the sources of heavy metals in the study area by means of Positive Definite Matrix Factorization （PMF） modeling and analyzed the impact of influencing factors by combining seven heavy metals with 13 influencing factors in a GeoDetector. The results showed that the mean values of soil heavy metals ω（As）, ω（Hg）, ω（Cu）, ω（Zn）, ω（Pb）, ω（Cd）, and ω（Cr） in the study area were 17.55, 0.19, 86.75, 164.84, 28.95, 0.39, and 167.87 mg·kg-1, respectively, which were greater than the background values of soils in Yunnan Province （except for As and Pb）. Regarding spatial distribution, the high values of Cu and Cr content were mainly concentrated in Yulong Naxi Autonomous County； the high value areas of As, Hg, Pb, and Cd were mainly concentrated in Ninglang Yi Autonomous County； and the high value of Zn content was mainly concentrated in Huaping County. Correlation analysis and PMF modeling revealed that the main sources of heavy metals As and Hg in the study area were industrial sources, Zn was from transportation pollution sources, Cr and Cu were from natural sources, and Cd and Pb were from agricultural sources. Further, the factor detector of the GeoDetector found that soil pH and organic matter （OC） had strong explanatory power for the content of seven heavy metals, and the interaction detector found that the results following the interaction of different influencing factors were nonlinear enhancement or two-factor enhancement, in which the interaction of OC and pH was the dominant factor for the spatial differentiation of heavy metals. This provides an important scientific basis for the protection of the soil environmental health and sustainable development in Lijiang City.

Pollution Characteristics and Source Apportionment of Heavy Metals in Topsoil of Counties Along the Shandong Section of the Yellow River

The 25 counties along the Shandong section of the Yellow River are the core areas for promoting the ecological protection and high-quality development of the Yellow River in Shandong Province. Moreover, it is of great significance to study the current situation, sources, and potential risks of heavy metal pollution in the topsoil in this region. In this study, 103 soil samples were collected from the 25 counties along the Shandong section of the Yellow River, and the contents of eight heavy metals （As, Cu, Pb, Cr, Zn, Ni, Cd, and Hg） were determined. The pollution characteristics of heavy metals were analyzed and evaluated using the geological accumulation index and potential ecological risk index. Correlation analysis and the positive matrix factorization （PMF） model were used to analyze the sources of heavy metals. The results showed that the average contents of Cu and Cr were lower than that of the background values of soils, whereas the average contents of As, Pb, Zn, Ni, Cd, and Hg were 1.16, 1.42, 1.05, 1.14, 2.29, and 1.85 times higher than that of the background values, respectively, and the average contents of all eight elements were lower than the screening value of soil pollution risk in agricultural land. In terms of different heavy metal variations, the coefficient of variation （CV） of Cu and Cd was higher than 0.500, indicating high variations, whereas As, Pb, Cr, Zn, Ni, and Hg showed moderate variation. Cd and Hg were slightly polluted, whereas the other six elements were not polluted. Cd and Hg had a moderate potential ecological risk level, whereas the other six elements were at a low level. Correlation analysis and PMF model showed that the sources of heavy metals in the study area were influenced by four factors, i.e., agricultural activities, natural sources, industrial emissions, and atmospheric dust from coal combustion and vehicle exhaust emissions, and the relative contribution rates were 32.4%, 34.9%, 16.5%, and 16.2%, respectively.

Pollution Assessment and Source Apportionment of Heavy Metals in the Surrounding Soil of Typical Mining Areas in Tongling, Anhui Province

To study the level of heavy metal pollution and ecological risks in the soil around typical mining areas in Tongling, a total of 150 soil samples were collected from the study area. The content characteristics of 10 elements, namely, As, Cd, Cr, Cu, Hg, Mn, Ni, Pb, Fe, and Zn, in the soils were analyzed. Methods including enrichment factor, the geo-accumulation index, single-factor pollution index, Nemero comprehensive pollution index, and potential ecological risk index were used to evaluate the pollution status of heavy metals in the soil of the study area. The pollution sources of heavy metals in the soil were also analyzed using correlation analysis, cluster analysis, and principal component analysis. The results showed that except for Cr and Fe, the average contents of the other eight heavy metal elements were higher than the soil background values in the study area. Pb, Zn, As, Cu, and Cd had a high degree of variation and were significantly affected by external interference. The spatial distribution showed that both Cr and Ni showed a decreasing trend from the edge to the central region, whereas the other eight heavy metals showed a decreasing trend from the central region to the surrounding areas. The pollution level of Cd and Cu in the soil of the research area was relatively severe. The overall ecological risk was at a medium to low level. Cd and Hg were the main contributing factors. As, Cd, Cu, Fe, Mn, Pb, and Zn mainly came from agricultural, industrial, and transportation sources, whereas Cr and Ni were mainly from natural sources. However, the sources of Hg were relatively complex. The research results can provide a scientific basis for the prevention and control of soil heavy metal pollution in metal mining areas, as well as the remediation of mine pollution.

Chemometric evaluation, source apportionment, and health risk analysis of natural spring water in Murree, outer Himalayas

IntroductionContamination of water is a critical threat to human health at a global level. Water pollutants, such as heavy metals, can have adverse effects on the well-being of humans, animals, and the natural ecosystem of a region. Study AreaMurree is the most visited tourist destination in Pakistan. The rural population of Murree uses natural spring water for drinking, household use, and irrigation. MethodsThis study assessed the elemental concentration of water from 20 natural springs in Murree using Inductively Coupled Plasma Optical Emission Spectroscopy. Source apportionment and spatial distribution of heavy metals were assessed using statistical approaches such as Pearson's correlation coefficient, principal component analysis, and interpolation. The study assessed the quality of water for drinking and irrigation in Murree's natural spring water using the metal index, sodium absorption ratio, magnesium absorption ratio, percentage sodium, Kelly's ratio, and salinity hazard. The health risks associated with heavy metals were assessed by computing Average daily dose, Hazard quotient, Hazard Index, and Cancer Risk. ResultsThe mean concentration of metals in mgL-1 varied in the following order: Ca (51.23) > Na (22.3) > Mg (16.26) > Si (6.51) > K (1.59) > Se (1.17) > Sr (0.48) > Ba (0.209) > Al (0.060) > Li (0.015) > Zn (0.005) > Fe (0.0033) > Ni (0.0032) > Cr (0.001). Metal index was calculated for Al (0.3), Ba (0.29), Cr (0.024), Ni (0.14), Fe (0.004), Zn (0.002), Sr (0.07), Mg (0.32), and Ca (0.25), revealing low levels of metal pollution. The geology of the study area was identified as the primary source of heavy metals in the water. The estimated values of health hazards showed that ingestion is the primary exposure pathway, with children having a higher risk. The health hazards posed by the heavy metal contact from the waters of Murree are not alarming. Quality indices show that the irrigation water sourced from the natural springs is of satisfactory quality. ConclusionThe study concluded that the spring water of Murree has low concentrations of heavy metals; their concentration is dependent upon the geology of the study area and is good for drinking and irrigation.