Distribution Characteristics Of Heavy Metals Research Articles

Pollution level and distribution characteristics of heavy metals and microplastics in the soils from the Qionghai Lake Wetland, Southwest China

Urban wetlands are reported to be ideal habitats for accumulation of HMs and MPs. However, study on combined pollution of HMs and MPs in soil is rare in urban wetland environment. In this study, the characteristics of HMs and MPs in the soils of the Qionghai Lake wetland in southwest China were studied by using ICP–MS, and FTIR. The results showed that the average concentration of HMs in soil ranges from 0.84 to 552.75 (mg/kg). According to the EF and Igeo analysis results, Cd and Cr in the soil were significant enriched (EF=12.64) and moderately enriched (EF=2.09), and were at the moderate to heavy pollution level (Igeo = 2.83) and the unpolluted to moderate pollution level (Igeo = 0.23), and the other elements were at a low level. MPs are emerging micropollutants in the soil environment, and the abundance (pieces/g) of MPs in the soil was 3.90, 7.00, 3.10, 3.40, 14.80, and 1.10 at Stations M1, M2, M3, M4, M8, and M9, respectively, with an average of 5.55 ± 4.92. Films represented the main microplastic shape, accounting for 81.55 %, followed by fibers, accounting for 11.33 %. The proportion of MPs with a particle size of 0.1–0.5 mm is the highest. Black, blue, and green are the predominant colors found in MPs. Polyethylene (PE) and polypropylene (PP) were the main MP materials based on FTIR identification, accounting for 52.16 % and 42.31 % of the total MPs, respectively. The pollution load index (PLI) of MPs was 2.2, which is a level Ⅰ pollution. The research on HMs and MPs in urban wetland soil is still in its preliminary stage. Our aim is to offer a fresh perspective for evaluating the pollution status and risk associated with these two pollutants in urban wetland soil, while also providing a valuable reference for subsequent studies on wetland soil pollutants.

The spatial distribution and source of heavy metals in soil-plant-atmosphere system in a large coal mining area

Due to the lack coupling analysis of heavy metals in soil-plant-atmosphere system, the migration and transformation of heavy metals remains unclear. In this study, 240 surface (0–20 cm) soil samples, 365 plant samples and 168 atmospheric dust samples were collected in a large coal mining area, in which selected heavy metals arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), nickel (Ni), plumbum (Pb), zinc (Zn) were analyzed, to elucidate the spatial distribution and source of heavy metals and their bioavailability. According to the results of ArcGIS mapping analysis, the distribution patterns of Cd, Cu, Pb, and Zn in the three media are similar, while the distribution characteristics of Cr and Ni are highly consistent. The factors contributing to these spatial distribution characteristics of heavy metals could be associated with human activities and the characteristics of the elements. Compared with the background value, Zn, Cr, Pb in soil, Zn, Cr, Cu in plants and Zn, Pb, Cu in atmospheric dust apparently accumulated. The geological accumulation pollution index (Igeo) shows that there exist mild to moderate levels of Cr and Cd pollution in soil, and mild to moderate levels of Cd, Cr, Pb, and Zn pollution in the air. The evaluation of potential risks of heavy metals showed moderate ecological hazards in soil and strong ecological hazards in atmospheric dust. The sources of heavy metals were assessed using principal component analysis (PCA), land use type, and spatial analysis. Anthropogenic factors are the main sources of heavy metal content. Coal-related industrial processes related to coal, sewage irrigation, the use of agricultural chemicals, and vehicle emissions may be anthropogenic sources of heavy metals.

Effects of dissolved organic matter on distribution characteristics of heavy metals and their interactions with microorganisms in soil under long-term exogenous effects

Long-term waste accumulation (LTWA) in soil not only alters its physical and chemical properties but also affects heavy metals and microorganisms in polluted soil through the dissolved organic matter (DOM) it produces. However, research on the impact of DOM from LTWA on heavy metals and microorganisms in polluted soil is limited, which has resulted in an incomplete understanding of the mechanisms involved in LTWA soils remediation. This study focuses on the DOM generated by waste accumulation and analyses the physicochemical properties, microbial community structure, and vertical distribution of heavy metals in four types of LTWA soils at different depths (0–100 cm). A causal analysis is conducted using structural equation modelling. The results indicate that due to the retention effect of the soil and microorganisms, heavy metal pollution is concentrated on the soil surface layer (>30 cm). With increasing depth, there is a decrease in heavy metal concentration and an increase in microbial diversity and abundance. DOM plays a significant role in regulating the concentration of soil heavy metals and the diversity and abundance of microorganisms. The DOM from different soils gradually transforms into substances dominated by tyrosine, tryptophan, and fulvic acid, which sustain the normal life activities and gene expression of microorganisms. Bacteria such as Pseudarthrobacter, Desulfurivibrio, Thiobacillus, and Sulfurimonas, which are involved in energy transformation, along with genes such as water channel protein and YDIF, which enhance heavy metal metabolism, ensure that microbial communities can maintain basic life processes in polluted environments and gradually select for dominant species that are adapted to heavy metal pollution. These novel discoveries illuminate the potential for modulating the composition of DOM to amplify microbial activity, while concurrently offering insights into the migration patterns of various long-term exogenous pollutants. This foundational knowledge provides a foundation for the development of efficacious remediation strategies.

Source Apportionment and Health Risk Assessment of Heavy Metals in Dust Around Bus Stops in Kaifeng City Based on APCS-MLR Model

In order to reveal the influence of urban transportation systems on the quality of urban ecological environment, this study selected surface dust from bus stops, which is strongly disturbed by transportation, as the research object. The contents of eight heavy metals (V, Cr, Co, Ni, Cu, Zn, Cd, and Pb) in the dust were determined through inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma atomic emission spectroscopy (ICP-ASE). The spatial distribution characteristics and pollution levels of the eight heavy metals in the dust were analyzed using the geo-accumulation index method. A combined qualitative (correlation analysis and principal component analysis) and quantitative (absolute principal component scores-multiple linear regression model (APCS-MLR)) method was used to explore the sources of heavy metals in surface dust near bus stops. The spatial distribution characteristics of heavy metals from different sources were elucidated using the Kriging interpolation method. The health risk assessment model proposed by the United States Environmental Protection Agency was used to evaluate the human health risks. The results showed that the average values of ω(V), ω(Cr), ω(Co), ω(Ni), ω(Cu), ω(Zn), ω(Cd), ω(Pb), and ω(As) in the bus stop surface dust were 68.36, 59.73, 5.81, 19.34, 40.10, 208.32, 1.01, and 49.46 mg·kg-1, respectively. The concentrations of heavy metals (Cd, Zn, Pb, Cu, and Cr) in the dust were all higher than the background values in the surrounding dust, exceeding them by 3.37, 2.70, 2.01, 1.95, and 1.28 times, respectively. The order of the geo-accumulation index for the eight heavy metals was Cd > Zn > Pb > Cu > Cr > V > Ni > Co, with Cd, Zn, Cu, and Pb in the dust indicating mild pollution levels and the others showing no pollution. The source analysis results showed that Cr, Co, and Ni were natural sources, whereas Cu, Zn, Pb, and Cd were traffic sources, and V was derived from a combination of industrial and natural sources. The APCS-MLR results indicated that the average contribution rates of the four sources were as follows:natural source (34.17 %), traffic source (29.84 %), industrial-natural mixed source (14.64 %), and unknown source (21.35 %). The spatial distribution map of the contribution rate of the traffic source was consistent with the trends of traffic volume and bus route density distribution. According to the health risk assessment, the cancer risk and non-cancer risk for children were both higher than those for adults. Cr was the main non-cancer factor, and Cd was the main cancer-causing factor. Natural and traffic sources contributed the most to non-cancer risk and cancer risk, respectively.

Health Risk Assessment of Heavy Metals in Soils of a City in Guangdong Province Based on Source Oriented and Monte Carlo Models

Taking a city in Guangdong Province as the research area, the concentration and spatial distribution characteristics of heavy metals in the surface soil were studied to clarify the situation of soil heavy metal pollution and priority control factors, providing basic data for the prevention and control of soil heavy metal pollution in the city. The content characteristics of heavy metals in 221 soil samples in the city were analyzed, and the potential health risk assessment and source analysis were carried out through the Monte Carlo model, the potential health risk assessment (HRA) model, and the PMF receptor model. It was found that heavy metals ω(As), ω(Hg), ω(Cd), ω(Pb), ω(Cr), ω(Cu), ω(Ni), and ω(Zn) in the soil of the city were 18.16, 0.43, 1.46, 68.57, 98.34, 64.19, 26.53, and 257.32 mg·kg-1, respectively, with a moderate to high degree of variation. Except for Ni concentration, the soil concentrations of other heavy metal elements exceeded the background values of soil in Guangdong Province to a certain extent, and the concentrations of Cd and Zn exceeded the national secondary standards, resulting in severe heavy metal pollution; the main sources of heavy metals were industrial sources, and natural parent materials, lead battery manufacturing, transportation, artificial cultivation, and pesticide and fertilizer inputs also had an undeniable impact on the accumulation of heavy metals in the soil. Heavy metals in the soil had a certain degree of tolerable carcinogenic health risk for both children and adults, whereas non-carcinogenic risks could be ignored. The potential health risk of children was greater than that of adults, and the main exposure route was through oral intake. The input sources of pesticides and fertilizers and As should be the main controlling factors for the health risks of heavy metals in the city's soil, followed by mixed sources and Cr. There were differences in the spatial distribution characteristics and relative pollution levels of heavy metals, and it is necessary to deepen zoning monitoring and control, strengthen soil pollution prevention and control, and reduce human input of heavy metals in soil.

Heavy metal content of mountainous agricultural soils and ecological risk assessment in Gadabay district, Azerbaijan

Objective: The objective of this study was to i) investigate the distribution characteristics of heavy metals, ii) examine their relationships with basic soil properties, and iii) characterize their potential sources and ecological risks. Material and Methods: A total of 85 samples were collected from the surface horizon (0-15 cm) of Chernozem soil in a representative agricultural area located in the Lesser Caucasus Mountains (Gadabay district), and heavy metal contents and basic soil properties were determined. Results: The mean of the heavy metals followed a decreasing order: Mn>Zn>Cu>Cr>Ni>Co>Pb>As>Se>Cd and some heavy metals (As, Cd, Se) exhibited a fragmented distribution. Co, Cr, Mn, Se and Zn contents were higher than the background concentration, while others (As, Cd, Co, Cu, Pb and Zn) exceeded the maximum permissible concentration. Conclusion: The spatial distribution of heavy metals was characterized by their typical and element-specific distribution. The noted variability was likely related to geologic features (soil mineralogy), mining history and agricultural practices. Notably, the presence of limestone and clay minerals contributed to the association of Cd, Cu and Se and Mn and Pb, respectively. Sand content influenced the mobility of Cr and Cu. The relations between pH and Cr, Ni and Se was the indication of the influence of the parent material on the distribution of these metals.

Red mud modified phosphogypsum based self-leveling mortar: Hydration mechanism, heavy metal migration law and spatial distribution characteristics

In the production processes of phosphoric acid and alumina, chemical enterprises generate solid waste such as red mud (RM), phosphogypsum (PG), and fly ash (FA). The environmentally friendly utilization of these waste materials is of crucial significance. Therefore, this study focuses on investigating the impact of collaborative modification using diverse solid wastes on the macroscopic properties and internal microstructure of self-leveling mortar. Through a careful selection process, the optimal ratio for red mud and phosphogypsum self-leveling mortar(RPSM) has been identified during the research. This study not only provides substantial support for the effective utilization of solid waste but also contributes to the improvement of overall performance and structural characteristics of the mortar. Based on this, the hydration characteristics, leaching patterns, and spatial distribution characteristics of heavy metals in RPSM were evaluated. The research revealed that the optimal ratios of RM, PG, FA, PC, river sand, and heavy calcium carbonate powder in RPSM were 20.7%, 13.8%, 17.1%, 13.8%, 17.3%, and 17.3%, respectively. Under a water-binder ratio of 0.18, the flexural and compressive strength of the mortar specimens after 14 d of curing can reach 4.3 and 31.6 MPa. Through comprehensive analysis and discussion of the performance, microstructure, and dynamics of the hydration process of RPSM, the main processes of mortar hydration were elucidated. Environmental risk assessments indicated no environmental risks from heavy metals in RPSM. Human health risk assessment suggested carcinogenic risks from Cr and Cd in RPSM through oral exposure, leading to restrictions on the content of characteristic heavy metals in different application scenarios. Furthermore, fitting results of the release kinetics of heavy metals indicated that the leaching of heavy metals in RPSM can be well fitted with kinetic models, allowing the determination of the optimal safe age of RPSM containing harmful heavy metals. Finally, using interpolation and vertical distribution simulation by software such as ArcGIS, the spatial distribution characteristics of heavy metals in RPSM during use were analyzed. The research can supply fundamental academic support for the recycling of solid wastes like RM and the control of environmental risks associated with heavy metal leaching in building materials.

Temporal-spatial characteristics and sources of heavy metals in bulk deposition across China

With the rapid development of industries, agriculture, and urbanization (including transportation and population growth), there has been a significant alteration in the emission and atmospheric deposition of heavy metal pollutants. This has consequently given rise to a range of ecological and environmental health issues. In this study, we conducted a comprehensive two-year investigation on the temporal and spatial distribution characteristics of heavy metals in atmospheric deposition across China based on the Nationwide Nitrogen Deposition Monitoring Network (NNDMN). The atmospheric bulk deposition of Lead (Pb), Arsenic (As), Nickel (Ni), Selenium (Se), Chromium (Cr) and Cadmium (Cd) were 6.32 ± 1.59, 4.49 ± 0.57, 1.31 ± 0.21, 1.05 ± 0.16, 0.60 ± 0.06 and 0.21 ± 0.03 mg m−2 yr−1, respectively, with a large variation among the different regions of China. The order for atmospheric deposition flux was Southwest China > Southeast China > North China > Northeast China > Qinghai-Tibet Plateau and rural area > urban area > background area. The concentrations of heavy metals in bulk deposition exhibit seasonal variation with higher levels observed during winter compared to summer and spring, which are closely associated with anthropogenic activities. The Positive Matrix Factorization (PMF) results indicated that combustion, industrial emissions and traffic are the primary contributors to atmospheric deposition of heavy metals. The single factor pollution index (Pi) of heavy metals is consistently below 1, and the composite pollution index (Ni) is 0.16 across China, indicating that atmospheric heavy metal deposition is at a pollution-free level. The comprehensive potential ecological risk index of heavy metals is 11.8, with Cd exhibiting the highest single factor potential ecological risk index at 7.09, suggesting that more attention should be paid to Cd deposition in China. The present study reveals the spatial-temporal distribution pattern of atmospheric heavy metals deposition in China, identifying regional source characteristics and providing a theoretical foundation and strategies for reducing emissions of atmospheric pollutants.

Spatiotemporal Distribution and Source Analysis of Heavy Metals in Surface Sediments in Lake Ulansuhai Based on PCA-APCS-MLR Model

To explore the spatial and temporal distribution characteristics of heavy metals in the surface sediments of lakes in cold regions during ice-sealing and non-ice-sealing periods, we analyzed the potential ecological risk degree and the pollution sources. A total of 20 sampling sites in Lake Ulansuhai in cold regions were collected from 2020 to 2021, and 120 surface sediment samples were collected during different periods. The contents of As, Cd, Cr, Cu, Ni, Pb, Zn, and Hg were determined. Correlation analysis, principal component analysis, and the absolute factor score-multiple linear regression (APCS-MLR) receptor model were used to trace the source of heavy metal pollution. The results showed that:① the distribution of heavy metals in lake surface sediments was different between the ice-sealing period and the non-ice-sealing period. The distribution of heavy metals during the ice-sealing period was higher in the north and lower in the south. Cd and Hg were mainly distributed in the central and southern lakes during the non-glacial period. ② Hg, Cd, and As were moderately polluted, and Ni was mildly polluted in the surface sediments of the lake. The overall performance was at a high risk level, and the pollution level during the non-ice-sealing period was higher than that during the ice-sealing period. The main environmental risk factors were Hg and Cd, which showed high risk and moderate risk, respectively. ③ The sources of heavy metals in lake surface sediments were mainly industrial sources from mining and transportation, agricultural sources, and natural sources. As, Ni, Pb, and Hg were mainly affected by industrial sources, with contribution rates of 62.67%, 75.31%, 77.47%, and 80.11%, respectively. The main sources of Cu and Zn were natural sources, and Cd was greatly affected by agricultural sources. The contribution rate was 81.57%. The source of Cr was mainly affected by natural factors, and the influence of human activities and unknown sources require further attention.

Prediction of Heavy Metal Pollution in Soil Based on SSA-XGBoost Model and 3D Geological Model

ABSTRACT The problem of soil heavy metal pollution in decommissioned sites has become an environmental threat and challenge faced by countries around the world. Establishing a high-precision 3D model of contaminants is essential for pollution risk assessment and accurate monitoring of contaminated sites. In this study, 3D geological model and SSA-XGBoost model are proposed to predict heavy metal concentration in a site. These models can effectively improve the prediction accuracy of soil heavy metals, and the RMSE of the XGBoost model optimized by the SSA algorithm is reduced by 24.3%-34.3%. Compared with other machine learning models, the SSA-XGBoost model has optimal performance in improving the prediction accuracy of soil heavy metals. It is suitable for the areas with significant spatial heterogeneity of soil heavy metals. Using the SSA-XGBoost model and 3D geological model, the 3D spatial distribution characteristics of heavy metals in contaminated soil are determined. The concentration of soil pollutants ranked as As>Pb>Mo, and the overall pollution degree decreases gradually from top to bottom. The pollutants are mainly distributed in the production workshop area in the southwest of the site, and the miscellaneous fill layer is the main soil layer that needs to be remediated.

Contamination Characteristics and Source Apportionment of Soil Heavy Metals in an Abandoned Pyrite Mining Area of Tongling City, China

To investigate the impact of pyrite mining on the heavy metal pollution in the surrounding soil in Tongling City, 50 surface soil and sediment samples were collected from mining fields, farmland, forests, villages, and the river. The contents of Zn, Cr, Cu, Pb, Ni, Cd, and As in soils and sediments were analyzed. Then, the spatial distribution characteristics of heavy metals in soil were analyzed, and the degree of heavy metal pollution and potential ecological risk level were assessed. Finally, the sources of soil heavy metal pollution were identified. In general, the soil in the study area was weakly acidic (average pH=6.32), and the contents of other heavy metals except Ni exceeded the background values of the soil in Tongling City. Moreover, Ni and Cd were enriched in the river sediments. According to the Nemerow pollution index, Pb and As reached heavy pollution levels, Cu and Cd reached moderate pollution levels, and other elements belonged to light or non-pollution levels. The comprehensive pollution index of different land types was ranked in the order of mining field > river > forest > farmland > village. Mining fields and the river were heavily polluted, forest land was moderately polluted, and farmland and villages were mainly mildly polluted. Pb, As, and Cd belonged to the medium ecological risk category. The contribution rates of the potential ecological risk index were 33.27%, 27.39%, and 20.22%, which were much higher than the other four elements. The ranking results of the potential ecological risk index of different land types was the same as that of the comprehensive pollution index. Mining fields and the river were at a high-risk level, forest land reached moderate risk, and the rest were at a slight risk level. The consistent results of correlation analysis, principal component analysis (PCA), and positive definite matrix factor analysis (PMF) indicated that Zn, Cu, Pb, Cd, and As were mainly derived from pyrite mining activities, Cr mainly came from the parent material and agricultural production, and Ni was mainly affected by soil-forming parent material and pyrite mining activities.

Prediction of heavy metal ion distribution and Pb and Zn ion concentrations in the tailing pond area.

The pollution caused by tailings ponds has resulted in ecological damage, with soil contamination significantly impacting the daily lives of residents in the vicinity of mining areas and the future development of mining areas. This study assesses the transport status of heavy metal pollution in tailings areas and predicts its impact on future pollution levels. This study focused on lead-zinc tailing ponds, exploring the spatial and chemical distribution characteristics of heavy metals based on the distributions of Pb, Zn, As, Cu, Cr, Cd, Hg, and Ge ions. The concentrations of the major heavy metal ions Pb and Zn in tailings ponds were predicted via the exponential smoothing method. ① The total accumulation of Pb and Zn in the mine tailings ranges from 936.74~1212.61 mg/kg and 1611.85~2191.47 mg/kg, much greater than the total accumulation of the remaining six heavy metals. The total accumulation of associated heavy metal Cu was high, and the lowest total heavy metals were Hg and Ge at only 0.19 mg/kg and 1.05 mg/kg. ② The analyses of soil heavy metal chemical forms reveal that the heavy metals Pb and Zn had the highest exchangeable state content and state ratio and the strongest transport activity in the industrial plaza and village soils. Pb and Zn are the heavy metals with the greatest eco-environmental impacts in the mining area. ③ The predicted results show that the soil concentrations of the heavy metals Pb and Zn around the tailings area in 2026 are 1.335 and 1.191 times the predicted time starting values. The concentrations of the heavy metals Pb and Zn at the starting point of the forecast are already 3.34 and 3.02 times the upper limits of the environmental standard (according to environmental standards for gravelly grey calcium soils). These results have significant implications for heavy metal pollution risk management.

Exploring the accumulation capacity of dominant plants based on soil heavy metals forms and assessing heavy metals contamination characteristics near gold tailings ponds

Heavy metal contamination of soil commonly accompanies problems around gold mine tailings ponds. Fully investigating the distribution characteristics of heavy metals and the survival strategies of dominant plants in contaminated soils is crucial for effective pollution management and remediation. This study aims to investigate the contamination characteristics, sources of heavy metals (As, Cd, Pb, Hg, Cu, Zn, Cr, and Ni) in soils around gold mine tailings ponds areas (JHH and WZ) and to clarify the form distribution of heavy metals (As, Cd, Pb, Hg) in contaminated plots as well as their accumulation and translocation in native dominant plants. The results of the study showed that the concentrations of As, Pb, Cd, Cu, and Zn in soil exceeded the national limits at parts of the sampling sites in both study areas. The Nemerow pollution index showed that both study areas reached extreme high pollution levels. Spatial analysis showed that the main areas of contamination were concentrated around metallurgical plants and tailings ponds, with Cd exhibiting the most extensive area of contamination. In the JHH, As (74%), Cd (66%), Pb (77%), Zn (47%) were mainly from tailings releases, and Cu (52%) and Hg (51%) were mainly from gold ore smelting. In the WZ, As (42%), Cd (41%), Pb (73%), Cu (47%), and Zn (41%) were mainly from tailings releases. As, Cd, Pb, and Hg were mostly present in the residue state, and the proportion of water-soluble, ion-exchangeable, and carbonate-bound forms of Cd (19.93%) was significantly higher than that of other heavy metals. Artemisia L. and Amaranthus L. are the primary dominating plants, which exhibited superior accumulation of Cd compared to As, Pb, and Hg, and Artemisia L. demonstrated a robust translocation capacity for As, Pb, and Hg. Compared to the concentrations of other forms of soil heavy metals, the heavy metal content in Artemisia L correlates significantly better with the total soil heavy metal concentration. These results offer additional systematic data support and a deeper theoretical foundation to bolster pollution-control and ecological remediation efforts in mining areas.

Spatial and Temporal Distribution Characteristics of Heavy Metals in Main Rivers Sediments and Ecological Risk Assessment in Kaifeng City

Heavy metal pollution in urban river sediments is an important threat to river ecosystem health. To explore the temporal and spatial distribution characteristics of heavy metals in river sediments of Kaifeng City, the surface sediments of rivers were sampled in 2015 and 2021, respectively, and the contents of Cd, Cr, Cu, Ni, Pb, and Zn in sediments at different periods were compared. The heavy metal pollution in the two periods was evaluated using the indices of geo-accumulation, bio-toxicity risk assessment, and potential ecological risk. The results showed that the content of heavy metals in river sediments of Kaifeng City in 2021 were decreased significantly compared with that in 2015. Cd, Cr, Cu, Ni, Pb, and Zn decreased by 94.42%, 18.4%, 85.7%, 45.19%, 75.61%, and 92.28%, respectively. The heavy metal content in the Huafei River and Huiji River was higher than that in other rivers in both periods. Correlation and principal component analyses showed that the heavy metal pollution sources of river sediments in Kaifeng City were highly similar, and human activities such as industrial layout, road traffic, and land use were the main pollution sources. However, the results showed that the main pollutants were different between the two sampling times. In 2015, Cd, Cr, Pb, and Zn were the main pollutants, and in 2021, Cd, Cu, Pb, and Zn were the main pollutants. The results of the geo-accumulation, bio-toxicity risk assessment, and potential ecological risk indices showed that the temporal and spatial differences in heavy metal pollution in river sediments in Kaifeng City were large. However, the heavy metal pollution of the Huiji River and Huafei River was still serious, with contents in the medium and high pollution levels, especially to Cd. The heavy metal treatment of rivers in Kaifeng City has a long way to go, and it is particularly necessary to strengthen the engineering treatment for key river sections and effectively monitor key pollution elements.

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.

Distribution Characteristics of Heavy Metals in Different Particle Size Fractions of Chinese Paddy Soil Aggregates

In recent years, the migration and transformation of heavy metals (HMs) in soil has become a hot issue. Soil particle size has an important effect on the environmental behavior of HMs in soil. The distribution of HMs in soil is strongly affected by the size of a soil aggregate. In this study, paddy samples in both cultivated and uncultivated soils were collected from Anhui Province, China. The soils were sieved into six particle size fractions (diameters of >4000, 4000–2000, 2000–1000, 1000–250, 250–53, and <53 μm) and the wet digestion method was used to determine the concentrations of Cd, Cr, Pb, and As in the soil aggregates. The results showed that the surface soils were characterized by the largest proportion of coarsest aggregates of >4000 μm particles. Moreover, the concentrations of Cd, Cr, Pb, and As were elevated in cultivated paddy soils compared to uncultivated soils. The accumulation of HMs in all paddy soils increased with decreasing particle size. Although the smallest particle size fractions accounted for only 5.65–17.28%, they provided the highest distribution factor (DF) of Cr (1.35), As (1.25), Cd (1.28), and Pb (1.38). The highest contributions of HMs came from the coarser fractions (>2000 μm); however, for Cr, Pb, Cd, and As, the mass loading of <53 μm particles was up to 15.90%, 14.41%, 15.21%, and 15.70%, respectively. The highest content of HMs was found in the finest aggregate, with a pattern of decreasing with increasing aggregate size. In addition, the leachability behaviors of different HMs in different particle size aggregates were different. The leachability behaviors of Cr and Pb in the coarse particle size fractions were the highest, while the leachability behaviors of As and Cd in the less than 250 μm particle size fractions were 10–100 times higher than those of Cr and Pb. A correlation analysis showed that the particle distributions of Fe, TOC, and Mn had significant influences on the distributions of Pb, Cd, As, and Cr. This study provides a theoretical basis for the prevention, treatment, and remediation of HMs pollution in soil.

Effects of vegetation restoration on distribution characteristics of heavy metals in soil in Karst plateau area of Guizhou.

In southwest China, vegetation restoration is widely used in karst rocky desertification control projects. This technology can effectively fix the easily lost soil, gradually restore the plant community and improve soil fertility. However, the change law of soil heavy metals in the restoration process remains to be further studied. Therefore, in this work, Guizhou Caohai Nature Reserve as a typical karst area was taken as the research object to investigate the influence of vegetation restoration technology on repairing soil heavy metal pollution. The spatial distribution characteristics of soil heavy metals (chromium, nickel, arsenic, zinc, lead) before and after vegetation restoration in karst area were studied by comparative analysis and linear stepwise regression analysis. The main influencing factors and spatial distribution characteristics of heavy metals in karst area were further discussed. The results showed that: (1) heavy metals in karst soils are affected by surface vegetation, root exudates, microorganisms and leaching. Only heavy metals nickel (Ni) and lead (Pb) showed the tendency of surface enrichment and bottom precipitation enrichment in non-karst soils. Path analysis suggested that non-metallic soil factors such as soil bulk density (BD), total nitrogen (TN) and ammonium nitrogen (NH4 +-N) had direct effect on the content of heavy metals in soil. (2) The proportion of 0.25-2 mm aggregates in the surface soil of vegetation restoration belt was more than 40%, and the proportion of surface soil ≤2 mm aggregates in this increased to 83% and 88%, respectively, which could improve the soil structure and properties effectively. (3) Vegetation restoration effectively restored the nutrient elements such as carbon and nitrogen in the soil, and enhanced the soil material circulation. Furthermore the content of heavy metals in the surface soil higher than that in the 10-20 cm soil layer. Plant absorption, biosorption mechanism of microorganisms, coupling of root exudates, dissolution of soil soluble organic carbon and pH make the contents of heavy metals Cr, Ni and Pb in vegetation restoration belt slightly lower than those in karst soil. At the same time, affected by vegetation coverage, residual heavy metals in soil are further leached by surface runoff. Therefore, the content of heavy metals in soil could reduce combined heavy metal enrichment plants for extraction with remediation. This study elucidates the advantages and remedy mechanism of vegetation restoration in the remediation of heavy metal contaminated soils in Caohai area of Guizhou, and this plant activation and enrichment extraction remediation technology would be popularized and applied in the remediation of heavy metal contaminated soils in other karst areas.

Comprehensive distribution characteristics and risks of heavy metals in typical intertidal zones and their relationship with urban economic indicators

Human activities have increased heavy metal pollution in intertidal environments. However, the comprehensive ecological risks of heavy metals in the active zones and their relationship with urban economic indicators are still poorly understood. This study investigated the multiphase distribution characteristics of heavy metals (Cr, Ni, Cu, Zn, Pb, and Cd) in 14 typical intertidal zones in the Guangdong–HongKong–Macao Greater Bay Area. The results showed that the concentrations of heavy metals varied greatly among different cities, and the highest average concentrations in Dongguan city were 695.27, 243.79, 1482.36, 980.24, 66.36 and 4.95 mg.kg−1, respectively. The proportion of bioavailable state Cd was the highest as 54.20%, followed by Zn > Cu > Pb > Ni > Cr. The comprehensive ecological risks (RCER) of the two intertidal zones in Dongguan were 1.45 ∼ 7.70 times higher than those of other sampling areas, indicating a very high ecological risk. Correlation analysis showed that total organic carbon in surface water, ammonia nitrogen in pore water, and solid organic carbon and the proportion of clay in sediments were significantly correlated with RCER values, and the linear regression coefficients were 0.784, 0.919, 0.962 and 0.914, respectively. The modified environmental Kuznets curve (EKC) model was used to describe the relationship between RCER values and urban economic indicators, and an inverted U shaped curve relationship was found, indicating that regional heavy metal pollution seemed to have reached a peak and entered a period of emission reduction. Nevertheless, given the increasing proximity of the intertidal zone to human daily life, long-term follow-up assessments are recommended.

Spatial Distribution Characteristics and Assessment of Heavy Metal Pollution in Cultivated Soil of Agricultural Small Watershed in Typical Mining Area in South China

In order to clarify the spatial distribution characteristics and the present situation of heavy metal pollution in cultivated soil of a typical mining basin in southern China, the contents of Cd, As, Mn, Cu, Zn, and Pb in cultivated soil in the selected small watershed were determined, and the spatial distribution characteristics of heavy metals were analyzed using the spatial interpolation method. Further, the ecological risk was evaluated using the geo-accumulation index and potential ecological risk coefficient (PERC). The results showed that the average contents of Pb, Zn, Cu, As, and Cd in the topsoil (0-20 cm) in the small watershed were approximately 11.9, 3.8, 8.2, 4.7, and 14.2 times that of the background value in Hunan soil, respectively. Compared with the soil risk screening value of agricultural land, the over-standard rates of Pb, Zn, Cu, As, and Cd were approximately 24%, 56%, 75%, 44%, and 48%, respectively. Zn and Mn showed medium variation, whereas Pb, As, Cu, and Cd showed strong variation, which indicated that there was an obvious enrichment of heavy metals in the small watershed. The spatial analysis results showed that there was an obvious consistent characteristic of six heavy metals in the topsoil, that is, there was enrichment in the mining activity area and its downstream and the township streets in the west of the small watershed. Additionally, there were high value points of some heavy metals on both sides of the main river, indicating that the main pollution sources in the study area were mining and metallurgy activities and sewage irrigation. The results of the geo-accumulation index and potential ecological risk index showed that there was compound pollution of heavy metals, in which the degree of Cd pollution was the highest, and the soil of both sides of the river could pose the strongest potential ecological risk.

Spatial Distribution Characteristics and Source Analysis of Heavy Metals in Soil of a Lead Plant in Sanmenxia

At present, a large-scale relocation of industrial enterprises is taking place in major cities in China, and a large number of contaminated relocation sites are being generated, among which the heavy metal pollution is particularly serious. In order to analyze the pollution status, spatial distribution, and sources of heavy metals in the soil of a lead factory in Sanmenxia, the spatial variation and distribution characteristics of heavy metals in the soil were analyzed using geostatistics, and the main sources of heavy metals in the soil were analyzed using a PMF model. The results showed that the average values of As, Cd, Cu, Pb, Hg, and Ni in the soil far exceeded the background values of the soil environment in Henan province; the contents of As, Cd, Pb, and Hg exceeded the screening values of soil pollution risk; and the contents of As, Pb, and Hg exceeded the control values of soil pollution risk. The high-value area was located on the northern part of the slag yard; the Cr, Ni, and Cd high-value area was located in the north and south of the slag yard; the high-value As area was located in the slag yard between the southern area and the living quarters; the Cu and Pb high-value area was relatively scattered, mainly concentrated in the central part of the raw material storage area and furnace area; and Ni and Cd and Cu and Pb had the same spatial distribution characteristics. Based on the PMF model, it can be seen that there were three main sources of the seven heavy metals, and Cd was mainly from waste residue accumulation, with a contributing rate of 87.60%. Cu, Pb, and Hg were mainly soil parent material, with contribution rates of 92.50%, 75.20%, and 95.40%, respectively. Cr, Ni, and As were mainly raw material dust exhaust gas sources, with contribution rates of 80.80%, 83.30%, and 62.00%, respectively.