Pollution Characteristics Of Heavy Metals Research Articles

Ecological and health risk assessments of heavy metals in surface water sediments from Ifite Ogwari community in Southeastern Nigeria

The hydrosphere becomes contaminated secondarily by accumulated heavy metals in sediments which may be released into the aquatic environment, thereby increasing the risks to human health. To evaluate the pollution characteristics of heavy metals in surface water sediments of Ifite Ogwari, nine sediment samples were collected from surface water sources used by the residents for drinking and other household activities. The concentrations of eight heavy metals: cadmium (Cd), chromium (Cr), copper (Cu), Iron (Fe), manganese (Mn), nickel (Ni), lead (Pb) and zinc (Zn) were analyzed using Atomic Absorption Spectroscopy (AAS). Enrichment Factor (EF), Contamination Factor (CF), Geoaccumulation index (Igeo), Potential Ecological Risk Index (PERI) and Risk Assessment Code (RAC) were conducted. Results of heavy metal concentration indicated that Cu < Cr < Ni < Pb < Cd < Zn < Mn < Fe based on the average metal concentration. Human health assessment showed high cancer risk for children and adults in a ratio of 1 in 10000 population. PERI indicated that sediment samples from Iyiutu and Ahala streams have low potential ecological risk while samples from Ube, Tabasi and Ogbu showed moderate ecological risk whereas samples from Isiachala, Nabaloku and Atammele streams as well as Omambala river sediments were high. RAC shows no ecological risk by Zn, Pb, Ni, Cu and Mn but in Omambala river, Cr and Cd contributed to ecological risk while Fe contributed to ecological risk in all the samples. Consequently, there is need for proper monitoring from health base evaluation and conscious effort to live in a clean environment devoid of any kind of exposure.

Pollution characteristics of heavy metals, antibiotic and antibiotic resistance genes in the crested ibis and their habitat across different lifestyle and geography

Antibacterial resistance in wild animals has been increasingly reported worldwide, even though they are usually not directly exposed to clinically relevant antibiotics. Crested ibis, one of the rarest birds in the world, usually forages in paddy fields and prefer to nest and breed near villages that is greatly influenced by anthropogenic activities. We sampled the feces of crested ibises, as well as their habitat environment samples, to explore the pollution characteristics of heavy metals, antibiotics and antibiotic resistance genes (ARGs). Results showed that the pollution characteristics of heavy metals, antibiotic, ARGs and gut microbiota of crested ibis were more related by host lifestyle and habitats. Captive ibises had higher relative abundances of the total ARGs and tetracycline concentrations compared with feralization and wild ibises, while the heavy metal contents had shown the opposite result. The Characteristics of pollutants in the corresponding environmental samples also exhibited high similarity with the results of fecal samples. The relative abundances of Proteobacteria and Actinobacteria were significantly different between captive and wild individuals, while the abundance of majority bacterial genera was generally higher in wild populations. The concentrations of heavy metals in soil (Cd, Cu and Zn) and water (Cd, Cu, Zn and Cr) were both exceeded the background soil levels or surface water quality standards, suggesting multi-element contamination in the habitat. Ecological risk assessments of soils by Igeo and Er showed that the habitats of wild ibises were heavily and moderately contaminated by Cd, which would possibly pose a threat to the health of ibises. PLS-PM analysis indicated that microbial compositions and residual antibiotics had the most substantial impact on the dynamic changes in ARGs of ibis. Overall, this work provides a comprehensive understanding of the characteristics, risks of those contaminations, and their effects on the ARGs in the habitat of crested ibis.

Spatial and temporal distribution of nitrogen, phosphorus, and heavy metals loads in Guanshan River Basin based on SWAT modeling

ABSTRACT This study takes Guanshan River Basin, a typical inflow river of the Danjiangkou Reservoir, as the research area, and the nonpoint source (NPS) pollution characteristics of nitrogen and phosphorus from 2013 to 2018 were evaluated by establishing a Soil and Water Assessment Tool (SWAT) model. The pollution characteristics of heavy metals were also evaluated by combining the SWAT and simple output coefficient method. The results show that the pollutant load in Guanshan River Basin contributes significantly to the Danjiangkou Reservoir. Temporally, pollutant loads were primarily concentrated in the flood season, which had a significant positive correlation with precipitation, water yield, and sediments in the abundant period. Among them, sediments were the most important driving factor, followed by water yield. Spatially, pollutant loads were mainly concentrated downstream of the basin, where cultivated land is widespread. In this regard, it is suggested that the input of chemical fertilizers, pesticides, and livestock manure in cultivated land should be controlled and soil erosion downstream of the basin should be prevented to mitigate nitrogen, phosphorus, and heavy metal pollution. This research offers a basis for the formulation and implementation of watershed management for the Danjiangkou Reservoir.

Characteristics of Soil Heavy Metal Pollution and Health Risks in Chenzhou City

The objective of this inquiry is to illuminate the attributes of heavy metal contamination and evaluate the potential ecological hazards inherent in the surface soil of Chenzhou City. A comprehensive analysis was conducted on 600 systematically collected soil samples within the study area, utilizing enrichment factors, geo-accumulation indices, comprehensive pollution indices, potential ecological hazard indices, and health risk assessment models to evaluate the degree of heavy metal contamination in the soil, potential ecological risks, and associated health hazards. The findings reveal that the average enrichment factor (EF) for each heavy metal is below 2, with the hierarchy from highest to lowest being Hg &gt; Cd &gt; Cu &gt; Pb &gt; Ni &gt; Zn &gt; Cr &gt; As. Approximately 78.67% of soil samples exhibit no pollution to weak pollution levels based on heavy metal enrichment factors. Moreover, the comprehensive pollution index (IPIN) indicates that 95.17% of soil samples are within safe and pollution-free levels, indicating an overall environmentally secure setting. However, 2.67% of samples display heightened potential ecological risk levels, primarily concentrated in the southwestern region of the study area, influenced by nearby industrial activities. Additionally, it is noteworthy that both the non-carcinogenic and carcinogenic health hazards emanating from soil heavy metals to adult individuals lie within tolerable thresholds. Among these, arsenic (As), chromium (Cr), and lead (Pb) have been discerned as the principal non-carcinogenic agents. It is of particular significance that only a solitary soil specimen, located in the southwestern quadrant of the investigative region, manifests detectable health perils for children.

Distribution Characteristics, Source Analysis and Ecological Risk Assessment of Heavy Metals in the Typical Industry Reclaimed Soil

To further explore the characteristics of heavy metal pollution and the ecological risk of typical industries in reclaimed soil, based on data from 315 different depth profiles of soil samples collected from 49 plots in Jiading District, Shanghai, the geo-accumulation index and potential ecological risk index were used to evaluate the contents and potential ecological risk of seven heavy metals, namely Cd, Pb, Cu, Zn, Ni, Hg, and As. The APCS-MLR receptor model and PMF positive matrix factorization model were employed to analyze the pollution sources. The results showed that:① except for As, the contents of other heavy metals in the soil of the study area exceeded the Shanghai soil background values to varying degrees. The contents of Cd, Pb, Cu, Zn, Ni, and Hg in the surface soil were 3.54, 2.34, 2.91, 1.20, 3.75, and 4.40 times the background values, respectively. The contents of heavy metals in the soil decreased with the increase in depth, and heavy metals were enriched to a certain extent in the surface soil, indicating that human activities had an impact on the distribution of heavy metals in the soil. ② The APCS-MLR and PMF receptor models identified four main sources of soil heavy metals in the study area. Source 1 (Cu, Zn, and Pb) was a mixture of metal products and automobile manufacturing, source 2 (Ni and Cd) was electroplating enterprises, source 3 (Hg) was mainly from chemical enterprises, and source 4 (As) was natural. The combined use of the two receptor models further improved the accuracy and credibility of source identification. ③ The geo-accumulation index in descending order was Hg(1.54)>Ni(1.32)>Cd(1.21)>Cu(0.96)>Pb(0.64)>Zn(-0.33)>As(-1.02). The potential ecological risk index showed that the comprehensive potential ecological risk index RI value in the study area ranged from 32.50 to 4 910.97, with a mean of 321.40, indicating a strong potential ecological risk. The pollution values of heavy metals Hg, Ni, and Cd in industrial site soil deserve further attention for re-development and utilization purposes.

Characteristics and Identification Priority Source of Heavy Metals Pollution in Farmland Soils in the Yellow River Basin

Assessments of the soil environmental quality of farmland and pollution source apportionment are the foundation for ensuring national food security and agricultural sustainable development, as well as an important prerequisite for the pursuit to keep our lands clean. This study evaluated the characteristics of heavy metal pollution in farmland soils in the Yellow River Basin from 2000 to 2023, based on the data of heavy metal contents including As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn, using the geo-accumulation index method. Source apportionment was conducted by employing a positive matrix factorization (PMF) model. The probabilistic health risks were evaluated by coupling Monte Carlo simulation with a human health risk assessment model, and priority pollution sources and elements were identified. The results showed that:① the average content of all heavy metals in farmland soils within the study area was lower than the screening values specified in the soil environment quality risk control standard for soil contamination of agriculture land (GB 15618-2018) (pH>7.5). However, the contents of Cd, As, and Zn in the samples exceeded their screening values, with percentages of 21.69%, 5.56%, and 1.23%, respectively, with Cd having the highest rate of exceedance. ② Hg and Cd were moderately polluted, Cu and Pb were slightly polluted, and the other elements were not polluted. ③ The main sources of heavy metals in farmland soil were traffic-industrial sources, natural-agricultural sources, industrial-natural sources, and agricultural-industrial sources, with contribution rates of 37.04%, 26.69%, 21.72%, and 14.55%, respectively. ④ Heavy metals in farmland soil posed carcinogenic health risks to adults and children but did not have non-carcinogenic risks; As and Cd were priority control elements for human health risks, and industrial-natural sources and agricultural-industrial sources were priority control sources in the study area.

Spatial Distribution, Source Analysis, and Health Risk Assessment of Heavy Metals in the Farmland of Tangwang Village, Huainan City, China

The impacts of heavy metal pollution in arable soil on agricultural production, environmental health, and the wellbeing of urban and rural residents cannot be overlooked. It has become a significant bottleneck in achieving comprehensive rural revitalization. To accurately grasp the characteristics of heavy metal pollution in suburban cultivated soil, Tangwang Village (a suburb of Huainan City) was subjected to scrutiny. The contents of heavy metals (Hg, Cu, Hg, As, Pb, Cr, Cd, and Zn) in the topsoil of cultivated land in this area were detected, and their spatial distribution characteristics were analyzed using inverse distance spatial interpolation. (1) After conducting a comprehensive analysis and thorough examination of the PMF model sources, it was determined that Cu, Cd, and Zn exhibit a direct correlation with agricultural practices, collectively contributing to a cumulative percentage of 21.10%. Meanwhile, Cr is derived from a combination of sources, including both natural parent materials and human activities, accounting for a total proportion of 24.45%. Notably, lead emissions from automobile exhausts constitute a significant source, while arsenic is primarily associated with dispersed factories and their respective operations, contributing to respective proportions of 36.38% and 18.07%. It is evident that agricultural practices, transportation, and industrial activities are the main reasons for heavy metal pollution in arable soil. (2) The evaluation of geological accumulation indicators reveals that the level of soil arsenic accumulation pollution is mild to moderate (1.199). On the other hand, the cumulative pollution level of Cd, Hg, Cr, and Cu was relatively low (0.462→0.186), whereas the levels of Pb and Zn were below the threshold. (3) The assessment of the ecological risk index revealed that the predominant elements posing potential ecological risks in the investigated region were Hg, As, and Cd, with average Ei values of E(Hg) = 86.81, E(As) = 80.67, and E(Cd) = 67.83, respectively. (4) The human health risk assessment revealed significant differences in the single non-carcinogenic risk values of heavy metals generated by different exposure pathways, with oral ingestion &gt; dermal contact &gt; oral nasal inhalation. Children were more susceptible to the toxic effects of heavy metals compared to adults. Both As and Cr caused an increased risk of cancer in both children and adults, which is a matter of great concern. The results of this study contribute to a more accurate description of the sources of heavy metals in farmland soil. This study indicates that the application of PMF for soil source analysis yields clear results that can be further applied. This research also has potential policy significance as it can help to improve the sustainability of ecosystems by coordinating both environmental and human activities.

Pollution Source Apportionment of Heavy Metals in Cultivated Soil Around a Red Mud Yard Based on APCS-MLR and PMF Models

In order to explore the characteristics and sources of heavy metal pollution in cultivated soil around a red mud yard in Chongqing， the content and spatial distribution characteristics of eight heavy metal elements （Cd， Cr， Hg， Ni， Pb， As， Cu， and Zn） in the soil were analyzed， and the single factor pollution index method and Nemerow comprehensive pollution index method were used to evaluate the characteristics of heavy metal pollution in soil. On the basis of correlation analysis， the APCS-MLR and PMF models were used to quantitatively analyze the sources of heavy metals. The results showed that the average contents of the other seven heavy metal elements were higher than the background values of Chongqing soil， except for that of Cr. The heavy metals Cd， Hg， and As were moderately polluted， and Pb， Cu， Ni， and Zn were mildly polluted. The spatial distribution pattern of Cr， Ni， Pb， Cu， and Zn in the soil was similar， and there was a very significant positive correlation between them （P &lt; 0.01）. The spatial distribution characteristics of Cd， Hg， and As were significantly different， and there was no significant correlation between them （P &gt; 0.05）. The source apportionment showed that the sources of heavy metals in the soil in the study area were relatively complex， and the APCS-MLR and PMF models could identify the same four pollution sources， namely red mud yard percolation emission and natural sources， thermal power generation emission sources， agricultural activities and natural sources， and non-ferrous metal smelting emission sources. There was little difference in the results of source apportionment between the two models. The contribution rates of the four pollution sources in the APCS-MLR model were 51.8%， 18.0%， 15.9%， and 14.3%， respectively， whereas those in the PMF model were 45.9%， 12.8%， 21.5%， and 19.8%， respectively.

Spatial Distribution and Pollution Assessment of Heavy Metals in Soils in the Jiefangzha Irrigation Area of the Hetao Irrigation District, China

To explore the characteristics of heavy metal pollution in farmland soils in the Jiefangzha Irrigation Area of the Hetao Irrigation District, Inner Mongolia, 60 samples of the surface soil (0–20 cm) were collected to detect and analyze the content of typical heavy metal elements, Cu, As, and Pb, in the soil. The methods utilized included the single factor index method, the Nemerow index method, the geological accumulation index method, and the potential ecological hazard index method to evaluate their pollution and ecological risks, and these were combined with geostatistical methods using GIS (Geographic Information System) technology to quantitatively analyze their spatial distribution characteristics. The results showed that the average contents of Cu, As, and Pb did not exceed the background values in the Hetao Irrigation Area, and the contents showed a moderate variation, with the order of variation as As > Cu > Pb. The multivariate statistical analysis results showed that the three elements, Cu, As, and Pb, had similar sources, i.e., primarily the use of agrochemicals, such as fertilizers and pesticides. The semi-variance function model fitting results showed that Pb followed a spherical model, and Cu and As followed Gaussian models. Kriging interpolation showed that the contents of As, Pb, and Cu, in general, showed a trend that was higher in the northwest and lower in the southeast, with a change of gradient increasing from the southeast to the northwest. Human activities were the primary factors causing the distribution difference.

Assessment of contamination and potential ecological risks of heavy metals in riverine sediments from gold mining and pristine areas in Ghana

This study explore the characteristics of heavy metal pollution, contamination levels, and potential ecological risks in riverine sediments found in both gold mining and pristine areas. Such investigations are vital for the ongoing monitoring and preservation of water bodies and overall ecosystem health. In total, 44 composite sediment samples were collected from seven pristine environments and four mining sites. These samples underwent preparation, digestion, and analysis for heavy metal content, utilizing the inductively coupled plasma emission mass spectrometer (ICP-MS). Various tools and models, including the geo-accumulation index, enrichment factor, and degree of contamination, were employed to assess the impact of pollution on the environment. Modified ecological risk index were also used to evaluate potential ecological risks. The average concentrations of heavy metals in pristine sites spanned from 0.01±0.01 (Cd) to 73,753.64 ± 388.15 mgkg−1 (Fe), while in mining sites, they ranged from 0.04±0.02 (Cd) to 56,394.25±400.66 mgkg−1 (Fe). Comparing these concentrations against the USEPA Ecological Screening Values, Mean Shales levels, and the Canadian ISQG, it became evident that Pb, Cd, Zn, Ni, Co, and Mn concentrations generally remained below the recommended guideline values in both pristine and mining areas. However, concentrations of Cr, As, Cu, and Hg exceeded the prescribed threshold limits, particularly in the mining regions. Through Principal Component Analysis (PCA) and Geometrical Analysis for Interactive Aid (GAIA) modeling, two primary sources of heavy metals were identified: anthropogenic-related and geogenic-related. GAIA and PCA together explained 78.53 % and 79.40 % of the total variability in heavy metal concentrations, respectively. Overall, the pollution and ecological risk assessment indicated low to moderate contamination levels, with a notable exception of high arsenic contamination in the Nyam river. The findings of this study hold significance for assessing sediment conditions and river quality in mining communities within Ghana and globally. They also provide empirical data to recommend measures for mitigating water contamination in such communities.

Factors controlling the heavy metal ion activity in soil contaminated by microplastics with different mulch durations: Partial least squares path model

Film covers have been widely applied worldwide. However, the effects of long-term plastic film mulching use on heavy metal (HM) activity in soil remain unclear. This study focused on farmland in the upstream part of the Pearl River in China and collected 103 soil samples after 2, 5, and 15 years of plastic film mulching. The main environmental factors controlling microplastics (MPs), plasticizer phthalic acid esters (PAEs), HM pollution characteristics, and HM activity were analyzed. The results showed that Polyethylene (PE) and di(2-ethylhexyl) dicyclohexyl phthalate (DCHP) were the main MPs and PAEs, respectively. The abundance of MPs and the concentrations of free HM ions (Cd, Cu, and Ni) in the soil solution increased with increasing plastic film mulching duration. The Partial Least Squares Path Model (PLS-PM) indicated that after plastic film mulching, soil chemical properties (pH/amorphous Fe) and biological properties (Dissolved organic carbon/ Easily oxidizable carbon/Microbial biomass carbon) were the main controlling factors for free and complexed HM ions (Cd, Pb, Cu, and Ni). These results suggest that, after plastic film mulching, MPs indirectly regulate HM activity by altering soil properties. This study provides a new perspective for the management of MPs and HM activities in agricultural ecosystems.

Health Risk Assessment of Heavy Metals in Agricultural Soils Around the Gangue Heap of Coal Mine Based on Monte Carlo Simulation

To analyze the pollution characteristics of heavy metals in the soil of farmland surrounding the gangue heap of a coal mine in Chongqing, the Nemerow, Muller, and Hakanson indices were used. Meanwhile, to investigate the health risks of heavy metals in soil, a health risk assessment model was employed using Monte Carlo simulation. The results revealed that the average contents of Cd, Hg, As, Pb, Cr, Cu, Ni, and Zn were higher than their soil background values, and the Muller index (Igeo) from high to low was as follows:Cd>Hg>Cu>As>Ni>Zn>Cr>Pb. The Nemerow index (PN) demonstrated that the results of the assessment indicated mainly light pollution (1<PN ≤ 2). The single factor index (Pi) from high to low was as follows:Cd>Cu>Ni>Cr>Zn>As>Pb>Hg. The Hakanson index (RI) demonstrated that the results of the assessment indicated mainly moderate ecological risk (150 ≤ RI<300). The single ecological risk index (Eri) from high to low was as follows:Cd>Hg>As>Cu>Ni>Pb>Cr>Zn. The health risk assessment of heavy metals revealed that the non-carcinogenic health risks of children and adults could be ignored, but carcinogenic health risks existed, with an average total carcinogenic risk index (TCR) of 1.04E-5 and 3.94E-6, respectively. The major carcinogenic factors were As and Cd. Sensitivity analysis of non-carcinogenic health risks revealed that the ingestion rate of soil (Ringest) was the most sensitive, followed by the contents of As. Meanwhile, sensitivity analysis of carcinogenic health risks indicated that the content of As was the most sensitive, followed by the ingestion rate of soil (Ringest). In general, the health risks of children, including non-carcinogenic and carcinogenic risks, were higher than those of adults.

Pollution Characteristics of Heavy Metals in Surface Sediments of the Shuimo River in Urumqi, China

Heavy metal pollution in the surface sediments of urban rivers has a significant influence on the safety of city residents. This study explores the features of heavy metal pollution in the surface sediments of the Shuimo River and provides a theoretical basis for decision makers regarding river management and restoration. This study uses principal component analysis and kriging interpolation to analyse the pH values and pollution characteristics of nine heavy metals (As, Pb, Zn, Cu, Ni, Fe, Mn, Cr, and V) in 23 surface sediments of the Shuimo River. The results showed that the pH value of the surface sediments along the direction of water flow had a quadratic curve trend. Kriging interpolation revealed consistency in the spatial distribution of heavy metals and Fe, and the peak value was from Qidaowan to Weihuliang. There were significant positive correlations (p &lt; 0.05) between Fe and Pb; Mn, Cr, V, Cu, and Zn; and Mn, Cr, and V. The principal component analysis showed that the main heavy metals in the surface sediments of the Shuimo River were Fe, Zn, Cu, and As. The total amount of heavy metals was in the order of Fe &gt; Mn &gt; Zn &gt; V &gt; Cr &gt; Ni &gt; Cu &gt; Pb &gt; As, ranging from 11.27~18,760.97 mg·kg−1. The cluster analysis classified the nine heavy metals into four categories: Zn and Cu in the first category; Ni in the second; As and Pb in the third; and V, Cr, Mn, and Fe in the fourth.

Heavy metal pollution characteristics and systemic risk assessment of the environment around the tailings site

Heavy metal pollution characteristics and systemic risk assessment of the environment around the tailings site

Microbial Community Composition and Diversity in Metal Sulfide Mine Water Systems

To understand the characteristics of heavy metal pollution and physicochemical properties caused by mining activities in mine water systems and the response of the microbial community to habitats with different contamination levels, this study selected different types of water (mining area wastewater, spoil heap area wastewater, dressing area wastewater, mine seepage water, and pond water) as the variables related to the mining activities in the water system of the Shizishan mining area in Tongling, Anhui Province. The pollution characteristics and physicochemical properties were compared, and the relationship between environmental factors and the microbial communities were analyzed. The results showed that the content of heavy metals, the physicochemical properties, and the structure and diversity of the microbial community of different types of water were significantly different in different mine areas, among which the most seriously polluted areas were the mining area, the spoil heap area, and the dressing area. There were significant differences in microbial community structure among different functional types of wastewaters, and the diversity and abundance of the microbial community in DW with the heaviest heavy metal pollution were weaker than those in the other four regions. PcoA analysis showed that samples of similar water types had similar clustering. Spearman correlation heat map analysis and canonical correlation analysis (CCA) indicated that heavy metal pollution, pH, electrical conductivity (EC), SO2-4, and chemical oxygen demand (COD) had the greatest effect on the microbial communities in the mine water systems. Moreover, this study found that Proteobacteria, Euryarchaeota, and Bacteroidetes dominated in mine water systems, and their potential use could be explored in the future. Our results provide a better understanding of the different types of water pollution characteristics in mine water systems and the key factors that determine the microbial community structure.

Source and migration patterns of heavy metals and human health risk assessment of heavy metals in soil-corn straw-flue gas system.

The process of rapid urbanization in Northeast China has resulted in severe heavy metal pollution in the environment. In this study, we investigated the characteristics of heavy metal pollution in soil-corn straw and its combustion flue gas system, and the health risks of heavy metal pollution. The results showed that Cu and Zn in soil were more easily absorbed by corn straw roots. Heavy metals in soil, corn straw and flue gas from corn straw burning all pose some health risk to humans, and are more harmful to children than adults. The concentrations of heavy metals in both soil and flue gas from corn straw burning have reached extremely high ecological risk. The main sources of heavy metal elements in soils are, in order, industrial production, agricultural production activities and metallurgical production. This study highlights the key issues of heavy metal contamination in soil-corn straw and its combustion flue gas system, provides an auxiliary guide for the next step in analyzing the transfer mechanisms, and suggests a rational approach to mitigate heavy metal contamination.

Source Analysis and Pollution Assessment of Soil Heavy Metals in Typical Geological High Background Area in Southeastern Chongqing

In order to understand the pollution characteristics of soil heavy metals in typical geological high background areas in southeastern Chongqing, analyze its pollution sources, and put forward risk management and control suggestions, 211 topsoil samples (0-20 cm) were collected in Xinglong Town and Muye Township in the north of Youyang County, Chongqing City, and the contents of eight heavy metals (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) and the soil pH value in the surface soil were analyzed. Additionally, mathematical statistics, pollution load index (P), potential ecological risk index (RI), correlation analysis, and the positive matrix factorization (PMF) model were used to study the content and spatial distribution characteristics of heavy metals in the topsoil, and pollution assessment and source analysis of heavy metals were carried out. The results showed that the average concentrations of heavy metals in the surface soil all exceeded the soil background value in Chongqing, showing different levels of enrichment. Among them, the proportion of Cd exceeding the screening value in the "soil environmental quality risk control standard for soil contamination of agricultural land" (GB 15618-2018) was as high as 83.41%, the proportion of exceeding the control value was 7.58%, and the potential risk was relatively high. The evaluation results of the pollution load index method showed that the study area was slightly polluted as a whole, and the evaluation results of the potential ecological risk index showed that the overall ecological risk of the study area was relatively high. Among them, the contribution rates of heavy metals Hg, Cd, and As were 50.27%, 28.63%, and 11.70%, respectively. The PMF results showed that there were three main sources of heavy metals in the soil in the study area:natural parent material sources, agricultural sources, and mixed sources of industrial activities and traffic emissions, accounting for 40.49%, 29.12%, and 30.39%, respectively. The quantitative source analysis results of soil heavy metals in the study area have important reference significance for soil heavy metal pollution control in geologically high background areas.

Effects of multi-heavy metal composite pollution on microorganisms around a lead-zinc mine in typical karst areas, southwest China

Heavy metal pollution poses a serious hazard to the soil bacterial community. The purpose of this study is to understand the characteristics of soil heavy metal pollution in lead-zinc mines in karst areas and the response of Pb, Zn, Cd, and As-induced composite pollution to soil microorganisms. This paper selected soil samples from the lead-zinc mining area of Xiangrong Mining Co., Ltd., Puding County, Guizhou Province, China. The soil in the mining area is contaminated by multiple heavy metals such as Pb, Zn, Cd and As. The average levels of Pb, Zn, Cd and As in the Pb-Zn mining soil were 14.5, 7.8, 5.5 and 4.4 times higher than the soil background in this area, respectively. Bacterial community structures and functions were analyzed using 16 S rRNA high-throughput sequencing technology and the PICRUSt method. A total of 19 bacterial phyla, 34 classes and 76 orders were detected in the tested soil. At the phylum level, the Proteobacteria are the dominant flora of the soil in the tailings reservoir area of the lead-zinc mine, respectively GWK1 (49.64%), GWK2 (81.89%), GWK3 (95.16%); and for the surrounding farmland soil, the Proteobacteria, Actinobacteriota, Acidobacteriota, Chloroflexi and Firmicutes are the most abundant in five bacterial groups. RDA analyses revealed that the heavy metal pollution of the lead-zinc mining area has a significant impact on the diversity of soil microorganisms. As the distance from the mining area increased, the heavy metal comprehensive pollution and potential risk value decreased, and the bacterial diversity increased. Additionally, various types of heavy metals have different effects on bacterial communities, and soil heavy metal content will also change the bacterial community structure. Proteobacteria positively related to Pb, Cd, and Zn, therefore, Proteobacteria were highly resistant to heavy metals. PICRUSt analysis suggested that heavy metals significantly affect the metabolic function of microorganisms. Microorganisms might generate resistance and enable themselves to survive by increasing the transport of metal ions and excreting metal ions. These results can be used as a basis for the microbial remediation of heavy metal-contaminated farmland in mining areas.

Source Apportionment and Pollution Assessment of Soil Heavy Metal Pollution Using PMF and RF Model: A Case Study of a Typical Industrial Park in Northwest China

Based on the concentration data of seven heavy metal elements[As, Cd, Cu, Pb, Hg, Ni, and Cr(Ⅵ)] in the surface soil of a typical industrial park in northwest China, the characteristics of heavy metal pollution in the industrial park were analyzed, and the ecological risk and pollution were evaluated using the potential ecological risk index and the index of geo-accumulation. The positive matrix factorization (PMF) model and random forest (RF) model were used for quantitative source analysis, and the emission data of sampling enterprises and empirical data of the source emission component spectrum were combined to identify the characteristic elements and determine the emission source category. The results showed that the heavy metals at all sampling points in the park did not exceed the second-class screening value of construction land in the soil pollution risk control standard for construction land (GB 36600-2018). However, compared with the local soil background values, five elements, excluding As and Cr, were enriched in different degrees, presenting slight pollution and moderate ecological risk (RI=250.04). Cd and Hg were the main risk elements of the park. The results of source analysis showed that the five main sources of pollution were fossil fuel combustion and chemical production sources (33.73%, 9.71%, total source contribution rate of PMF and RF, respectively; the same below), natural sources and waste residue landfill (32.40%, 40.80%), traffic emissions (24.49%, 48.08%), coal burning and non-ferrous metal smelting (5.43%, 0.11%), and electroplating and ore smelting (3.95%, 1.30%). The simulation R2 of the total variable of the two models were above 0.96, indicating that the models could predict heavy metals well. However, considering the actual situation of the number of enterprises in the park and roading density, the main pollution sources of soil heavy metals in the park should be industrial sources, and the simulation results of the PMF model were closer to the actual situation in the park.

Ecological Risk Assessment and Source Apportionment of Heavy Metals in Mineral Resource Base Based on Soil Parent Materials

Mineral resource bases have dual properties, e.g., mineral resources and environmental pollution. The latter could be classified into natural and anthropogenic pollution based on identifying the spatial distribution characteristics and sources of heavy metals in the soil. The Hongqi vanadium titano-magnetite mineral resources base in Luanping County, Luanhe watershed, was taken as the research object. The geo-accumulation index (Igeo), Nemerow comprehensive pollution index (PN), and potential ecological risk (Ei) were utilized to assess the soil heavy metal pollution characteristics, and redundancy analysis (RDA) and positive determinate matrix factorization (PMF) were employed to identify sources of the soil heavy metals. The results revealed that the mean contents of Cr, Cu, and Ni in the parent material of medium-basic hornblende metamorphic rock and medium-basic gneisses metamorphic rock were 1-2 times that in other parent materials in the concentrated area of mineral resources. However, the mean contents of Pb and As were lower. Fluvial alluvial-proluvial parent materials had the highest mean content of Hg, and the mean content of Cd was higher in the parent materials of medium-basic gneisses metamorphic rocks, acid rhyolite volcanic rocks, and fluvial alluvial-proluvial facies. The Igeodecreased in the following order:Cd>Cu>Pb>Ni>Zn>Cr>Hg>As. PN ranged from 0.61 to 18.99, and the sample proportion of moderate and severe pollution reached 10.00% and 8.08% respectively. Pishowed that the contents of Cu, Cd, Cr, and Ni were relatively higher in the parent material of intermediate-basic hornblende metamorphic rocks and intermediate-basic gneiss metamorphic rocks. Ei decreased in the order of Hg(58.06)>Cd(39.72)>As(10.98)>Cu(6.56) >Pb(5.60)>Ni(5.43)>Cr(2.01)>Zn(1.10). Samples whose RI was lower than 150 accounted for 84.27%, showing that the research area was predominantly at a slight potential ecological risk level. The sources of soil heavy metals were dominated by parent material weathering, followed by the mixed sources of agricultural activities and transportation, the exploitation of mining, and fossil burning, which accounted for 41.44%, 31.83%, 22.01%, and 4.73%, respectively. The risks of heavy metal pollution in the mineral resource base were characterized as multi-source instead of the single source from the mining industry. These research results provide the scientific basis for regional green mining development and eco-environmental protection.