Pollution Status Of Heavy Metals Research Articles

Assessment of microplastic and heavy metal pollution in agricultural soils of Ernakulam District, Kerala, India.

Microplastics (MPs) and heavy metal pollution pose significant environmental threat, potentially leading to agroecosystem toxicity and jeopardizing food security. Therefore, this study aims to evaluate the abundance and risk assessment of these pollutants in five different farmlands of Ernakulam district, India. Results showed that MPs content in agricultural fields near commercialized areas such as Kakkanad Nedungapuzha, Nedumbassery, and Kadamakuddy was dominant compared to Nechoor, a rural area. The average microplastic abundance was found to be 45.6 ± 26.4 items kg⁻1 dw. Polypropylene (PP) and polyethylene (PE) were the dominant polymers found in the soil samples, constituting 45% and 25% of the microplastic content, respectively. The pollution load index of MPs indicates that the sampling sites are considered to be polluted as PLI > 1 with hazard level I. The heavy metal pollution status follows the order: Cu (80.3 to 724mg/kg) > Zn (77 to 543.5mg/kg) > Cr (171.65 to 334.65mg/kg) > As (10.25 to 79.5mg/kg) > Pb (2.05 to 30.3mg/kg) > Cd (0.3 to 14.35mg/kg). Calculated pollution load index (PLI) geo-accumulation index (Igeo), ecological risk assessment values indicate that commercialized regions exhibit high levels of trace metals, namely Cu, Zn, As, Cd, and Cr, posing a significant concern for the agricultural ecosystem. Our results indicate heightened microplastics and heavy metals prevalence in farmlands adjacent to commercial zones, necessitating immediate preventive action to mitigate increasing concentrations.

Distribution characteristics and ecological risk assessment of heavy metal pollution in seawater near the Yellow River Estuary of Laizhou Bay

To understand the characteristics and pollution status of heavy metals in the intersection areas of Laizhou Bay and the Yellow River Estuary in Shandong Province, the contents of various heavy metals in surface seawater samples collected from this area in August 2022 were detected. The spatial distributions of the heavy metals were analysed, which exhibits a general decreasing trend in the concentrations of Hg, As, Cr, and Pb from west to east, while Cd, Zn, and Cu show the opposite trend. The average single-factor index P values decrease in the following order Pb > Zn > Hg > Cu > As > Cd > Cr, among which Pb, Zn, Hg, and Cu caused pollution in this area. The potential ecological risk index values indicate that the main heavy metal pollutants in study area are Hg and Pb, with Hg having the highest value, accounting for 74.7%, and being the main potential ecological risk factor. Correlation analysis shows that the most significant environmental factor affecting heavy metal content is salinity. According to the interactive heatmap between cluster analysis and station classification, the heavy metals have originated from industrial, agricultural, and domestic sewage discharge, surface runoff, river inputs, seawater aquaculture, maritime transportation, and fuel exhaust emissions. This research hopes to provide some reference value for the protection of marine and estuarine ecosystems.

Machine learning-assisted risk evaluation of heavy metals in the Hainan gold mining region, China.

This study employed machine learning (ML) to thoroughly investigate the impact of informal mining activities on the distribution and pollution status of heavy metals in soils near private gold mines in Hainan Province, southern China, a region known for its ecological sensitivity and economic importance. By systematically collecting surface soil samples and samples at depths of 0.5-1m from 175 drilling sites, a comprehensive quantitative analysis was conducted on major heavy metal elements, including lead (Pb), copper (Cu), cadmium (Cd), nickel (Ni), mercury (Hg), chromium (Cr), arsenic (As), and zinc (Zn). Combined with evaluation methods such as the Pollution Load Index (PLI), Normalized Pollution Index (NIPI), and Ecological Risk Index (ERI), the study revealed a high level of soil pollution at informal mining sites. The findings indicated that the average concentrations of Pb, Cd, Hg, As, and Zn in surface soils significantly exceeded the background values for soils in China, with a pronounced positive correlation observed between these heavy metal elements in both surface and deep soil profiles (r > 0.5). Furthermore, leveraging the heavy metal content in surface soils and the constructed environmental indicators, the predictive accuracy for metal content in deep soils was found to range from R2 = 0.27 to 0.68, suggesting that informal mining activities have led to substantial variations in metal content across different soil profiles. Through the application of a random forest model for predictive analysis of the PLI, NIPI, and ERI, high prediction accuracy was achieved (R2 = 0.78, 0.86, and 0.60, respectively). The study demonstrates that informal mining activities not only elevate the risk of soil pollution but also alter the distribution patterns of heavy metals. Also, this study provides a crucial foundation for the scientific assessment of soil quality and potential environmental hazards, while also affirming the efficacy of ML techniques in forecasting soil quality parameters.

Analysis and probabilistic health risk assessment of vertical heavy metal pollution in the water environment of reservoir in the west coast new area of Qingdao, China

The West Coast New Area is a typical city in China where water supply is predominantly sourced from reservoirs. Heavy metal pollution in these reservoirs directly impacts the safety of drinking water and human health. Therefore, this study comprehensively evaluated the status of heavy metal pollution in the water environment and sediment of the main water supply reservoir in the study area, revealing the interaction relationship and pollution sources, as well as assessing the probabilistic health risks to human beings. The results show that there are different degrees of pollution in the main water supply reservoirs in the study area, and the pollution increases with the increase of water depth. The heavy metal pollution index was up to 2681, indicating heavily pollution. The main polluting elements were Mn and Fe, and the maximum contents were 4.11 mg L−1 and 0.68 mg L−1, respectively, which far exceeded the Class III standard limit of drinking water in China. The main source of pollution is human activities, and Mn release from sediment aggravates deep water pollution. The non-carcinogenic risk index of heavy metals in the reservoir, ranging from 4% to 14%, is higher than 1, indicating a potential non-carcinogenic threat. Furthermore, heavy metals have a much greater impact on children compared to adults, among which Mn is the main contributor to human non-carcinogenic risk, contributing more than 60%. Therefore, controlling the content of Mn and Fe can effectively reduce the heavy metal pollution of reservoir and human health risk. The research results are of great significance for the utilization of reservoir water resources and the protection of the ecological environment in the study area.

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.

Heavy metals distribution and their ecological risk in the surface sediments of Haizhou Bay, China

A comprehensive analysis of heavy metal concentrations, sources, and pollution status was conducted on thirty surface sediment samples collected from Haizhou Bay, China in 2020. The spatial distributions of Cu, Pb, Zn, Cr, Cd, and total organic carbon (TOC) were found to be analogous. Noteworthy, sporadic pollution effects from Cu, Cr, and As were detected, although heavy metal concentrations remained below the probable effect level (PEL). A suite of analytical methods, including Pearson's correlation coefficient, geoaccumulation index, sediment quality guidelines, potential ecological risk index, and principal component analysis, was employed to elucidate the sources and assess the pollution risks. The results indicated that Hg emerged as the predominant heavy metal pollutant in Haizhou Bay sediments, with several stations showing high pollution levels that require attention. Other heavy metals were mainly of natural origin, indicating no significant pollution in the study area.

Meta-analysis of Heavy Metal Pollution in Soil-crop Systems in China's Urban-Rural Fringe

Owing to the influence of human activities, the issue of heavy metal pollution in farmland soil at the urban-rural fringe has become increasingly prominent. An accurate understanding of the characteristics of soil-crop heavy metal pollution in these areas is of great significance for ensuring food safety and promoting social sustainable development. Most of the existing studies rely on small-scale field monitoring, but research at the national level has not effectively captured the unique pollution dynamics of this urban-rural interface. Based on the published literature, the present study investigated the status of heavy metal pollution in the soil-crop system within China's urban-rural fringe through Meta-analysis. On this basis, the study evaluated the risks to human health associated with heavy metals in major crops in a given region. The results showed that heavy metals were accumulated in farmland soil in the urban-rural fringe of China, especially in Cd （Igeo = 0.89） pollution, and its distinct spatial heterogeneity patterns emerged. When considering different types of cultivated land, paddy fields and irrigated land exhibited a higher tendency of heavy metal accumulation. From the varying urbanization levels, the accumulation of heavy metals in soils of small and medium-sized cities was more obvious. For crops in the urban-rural fringe, Cd and Pb had the highest exceedance rate in rice （28.25% and 39.64%） and wheat （27.72% and 42.72%）. The health risk assessment results of heavy metals in crops showed that Cd was the main element that posed human health risks, which had some degree of non-carcinogenic risk and unacceptable carcinogenic risk to both children and adults.

Assessment and Source Analysis of Heavy Metal Pollution in Farmland Soil Around Tin Mine

Studying the status and source analysis of heavy metal pollution in farmland in typical mining and processing areas is an important prerequisite for promoting farmland soil ecological restoration and farmland protection in concentrated mining areas. In this study, the heavy metal content of farmland soil around a mining area in southwest China was detected, and the pollution status, distribution law, health risks, and sources of heavy metals were studied by using the land accumulation index method, comprehensive pollution index method, kriging interpolation method, health risk assessment method, and PMF receptor model on the sampling data. The results showed that the mean values of eight heavy metals in farmland soil except Ni exceeded the local soil background values, and the results of the ground accumulation index evaluation showed that Cd and Hg were extremely polluted； Pb and As showed medium pollution-heavy pollution； and Cr, Zn, Ni, and Cu were lightly polluted. In the health risk assessment, oral ingestion was the main exposure route posing a health risk to the human body； the main element that constituted non-carcinogenic health risks was As, and the carcinogenic risks were from As and Cd. PMF model analysis showed that the contribution rate of weathering natural sources of iron-bearing ore was 28.02%, and the main factors were Ca and Fe. The contribution rate of agricultural sources was 3.02%, and the main factors were Pb and As. The contribution rate of industrial and atmospheric deposition composite sources was 33.09%, and the main factor was Hg. The contribution rate of the parent material source was 17.27%, and the main factor was Ca. The contribution rate of mining activities such as mining and smelting was 18.60%, and the main factors were Zn and Cd.

Identification Priority Source of Heavy Metals in Urban Soils Based on Source-specific Ecological Risk Analysis in a Typical Tourist City

To understand the pollution status, distribution characteristics, and pollution sources of soil heavy metals in tourist cities in northwest China, the soil content of heavy metals As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn in the main areas of Dunhuang City was collected and analyzed. The soil heavy metal pollution level was quantitatively evaluated by the methods of the geo-accumulation index and improved Nemerow pollution index, and the sources of heavy metal pollution were quantitatively analyzed using cluster analysis and the positive matrix factorization （PMF） model. The contribution rate of each pollution source to ecological risk was determined by combining the PMF model and comprehensive ecological risk index. The results showed that except for the mean contents of As and Ni, the mean contents of Cd, Cr, Cu, Hg, Pb, and Zn were all higher than the background values in Gansu Province. However, the average content of the eight elements was lower than the screening value of construction land in the Standard for Soil Pollution Risk Control of Soil Environmental Quality Construction Land （trial） （GB 36600-2018）. Among them, the enrichment of Cd, Pb, and Hg was more serious, and the exceedance rate was higher than 90%. The results of the geo-accumulation index indicated that urban soils were mainly polluted by Hg in the study area, and Cd, Cr, Cu, Pb, and Zn pollution also existed in different degrees. The improved Nemerow pollution index illustrated that the comprehensive pollution degree of the soil was clean to moderate pollution, and the overall pollution was light pollution. Based on the PMF model, we could conclude that soil heavy metals in the study area were affected by natural sources, industrial deposition sources, industrial sources, traffic sources, and comprehensive sources, and the contribution rates were 29.28%, 25.86%, 20.13%, 16.5%, and 8.23%, respectively. The specific source-integrated ecological risk assessment model found that the industrial deposition source contributed the most to the ecological risk in the study area and could be regarded as the priority control pollution source, and Hg was considered to be the priority control pollution element for ecological risk.

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

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

Soil Heavy Metal(loid) Pollution Evaluation, Risk Assessment, and Source Analysis of a Mineral Processing Plant

Yunnan Province is rich in mineral resources. Early mining, processing, metallurgy, and other mining activities produce three industrial wastes (waste water, waste gas, and waste residue) causing environmental pollution. Considering the legacy site of a mineral processing plant in Yunnan as the research object, 21 sampling points in the study area and 12 control sampling points in the periphery were set up to determine the contents of the heavy metal(loid)s As, Hg, Cd, Cu, Ni, Pb, and Cr in the soil. The spatial distribution of heavy metal(loid)s was interpolated and analyzed using Arcmap10.8, and combined with the single-factor index, Nemero Comprehensive Pollution Index, and the health risk assessment method for the heavy metal(loid) pollution status and health risk of the soil were evaluated. The soil in the study area was acidic, with the largest average value of elemental As and the largest percentages of control and screening values. The results of the single-factor and Nemero composite pollution index showed the following trend: As > Pb > Cd > Cu > Ni > Hg. Cd, Cu, and Pb mainly originate from mining and metallurgy and Hg from the combustion of fossil fuels, while soil-forming substrates are the main sources of Ni. Pollution by As was the most prominent element, whereas pollution by Cd, Cu, and Pb in some areas also cannot be ignored to prevent negative impacts on residents. It is recommended to remediate and treat the soil on site for public events; therefore, this study fills the gap in studying potential ecological risks, human health risk assessments, and sources of exposure (oral ingestion, respiratory ingestion, dermal contact).

Distribution Characteristics and Assessment of Heavy Metal Pollution in Sediments of Fengyuan River, Guangdong

Mining activities and industrial production discharges often generate heavy metal pollution and pose serious environmental impacts. It is of great significance to study the pollution status and sources of heavy metals in polluted rivers for environmental pollution control. This paper determines the concentration of 34 heavy metals, including As, Cd, Cr, Cu, Ni, Pb, and Zn, in the Fengyuan River and tailing pond in Yunfu City, Guangdong Province. The potential ecological risk index (RI) and integrated pollution index (IPI) were used to evaluate the spatial distribution and pollution levels of heavy metals, and the possible source and enrichment of heavy metal were identified and assessed using enrichment factor (EF). The results showed that Cd and Tl in the slag of the tailings pond were the most serious; The potential ecological risk index indicates that Cd in the sediment of the Fengyuan River is a very severe ecological risk, As and Pb caused heavy and moderate ecological risk, respectively, while, Co, Cr, Cu, Mn, Ni, V, and Zn constituted mild ecological risks; The integrated pollution index shows that all the sampling sites are above high pollution. The average enrichment factor of Cd in surface sediments reached 28.11. The EF values of As, Cu, Mn, Pb, and Zn were all greater than 1. The RI, IPI, and EF produced similar levels of heavy metal pollution in sediments, thereby confirming each other’s results, indicating that the Fengyuan River is heavily contaminated, and As, Cd, Mn, Pb, and Zn were likely to have an effect on the aquatic ecosystem. According to principal component and hierarchical cluster analyses, the Fengyuan River may contain heavy metals from a variety of sources, such as tailings ponds, industrial parks, chemical effluent, and more. In addition, correlation analysis indicates that total organic carbon is significantly correlated with the concentrations of As and Cr, respectively, and combining EF suggests that cluster 1 containing As, Mn, and Pb and cluster 2 containing Cd and Zn may be derived from similar anthropogenic sources. This study can provide meaningful basic information for environmental development planning and decision-making associated with human health in the region.

Seasonal Evaluation of Physicochemical Parameters, Heavy Metals Levels and Pollution Status in Leachate from Ikhueniro Open Solid Waste Dumpsite located in Benin City, Edo State, Nigeria

Seasonal Evaluation of Physicochemical Parameters, Heavy Metals Levels and Pollution Status in Leachate from Ikhueniro Open Solid Waste Dumpsite located in Benin City, Edo State, Nigeria

Heavy Metal Concentration Estimation for Different Farmland Soils Based on Projection Pursuit and LightGBM with Hyperspectral Images.

Heavy metal pollution in farmland soil threatens soil environmental quality. It is an important task to quickly grasp the status of heavy metal pollution in farmland soil in a region. Hyperspectral remote sensing technology has been widely used in soil heavy metal concentration monitoring. How to improve the accuracy and reliability of its estimation model is a hot topic. This study analyzed 440 soil samples from Sihe Town and the surrounding agricultural areas in Yushu City, Jilin Province. Considering the differences between different types of soils, a local regression model of heavy metal concentrations (As and Cu) was established based on projection pursuit (PP) and light gradient boosting machine (LightGBM) algorithms. Based on the estimations, a spatial distribution map of soil heavy metals in the region was drawn. The findings of this study showed that considering the differences between different soils to construct a local regression estimation model of soil heavy metal concentration improved the estimation accuracy. Specifically, the relative percent difference (RPD) of As and Cu element estimations in black soil increased the most, by 0.30 and 0.26, respectively. The regional spatial distribution map of heavy metal concentration derived from local regression showed high spatial variability. The number of characteristic bands screened by the PP method accounted for 10-13% of the total spectral bands, effectively reducing the model complexity. Compared with the traditional machine model, the LightGBM model showed better estimation ability, and the highest determination coefficients (R2) of different soil validation sets reached 0.73 (As) and 0.75 (Cu), respectively. In this study, the constructed PP-LightGBM estimation model takes into account the differences in soil types, which effectively improves the accuracy and reliability of hyperspectral image estimation of soil heavy metal concentration and provides a reference for drawing large-scale spatial distributions of heavy metals from hyperspectral images and mastering soil environmental quality.

Heavy Metal Pollution Status in The Main Surface Waters of The N'djili River Basin in Kinshasa, Democratic Republic of Congo: A Review with Application and Evaluation of Pollution Indices Evaluation

The aim of this study was to assess heavy metal pollution in the surface waters of the N'djili river watershed, as well as to determine the main sources of this pollution and their impact on water quality. Five sampling sites were selected in the watershed, representing a variety of urban and industrial influences. In these samples, trace metals such as lead (Pb), cadmium (Cd) and arsenic (As) were measured by atomic absorption spectrometry. The respective mean concentrations of lead (Pb), cadmium (Cd) and arsenic (As) in the surface waters of the N'djili basin are 0.066 mg/L, 0.006 mg/L and 0.310 mg/L. The mean value of the degree of contamination (Dc) in the surface waters of the N'djili basin is greater than 3, indicating heavy contamination of these waters (Lukaya river, Matete river, N'djili river, Ntshuenge river, Ngwele river). The average values of for the trace metal pollution index (HPI) are below the threshold value of 100, so overall, these waters are not very polluted. Nevertheless, particularly high concentrations were observed in the waters of the Matete River, with values exceeding 100, indicating severe localized pollution. Correlation analysis between trace metals and HPI indicates that lead and cadmium are the main contributors to surface water toxicity in the N'djili basin. These results highlight the urgent need to develop targeted strategies to reduce pollution in order to preserve public health and aquatic ecosystems.

Geochemical characteristics and sources of heavy metal elements in the southern and western surface soils of Fengdu County, Chongqing

In order to explore the current situation and sources of heavy metal element pollution in the surface soil of the southern and western parts of Fengdu County, Chongqing. In this paper, the test and analysis results of 2955 surface soil samples collected from the project of "Chongqing Jiaoshi Dam Width, Liziwan Width, etc. a total of five 1:50,000 Land Quality Geological Survey" project were carried out. The single pollution index method and the land accumulation index method were used to evaluate the current status of heavy metal pollution in crops and soil. At the same time, correlation analysis and principal component analysis were performed. The results show that: (1) Compared with the soil heavy metal background in the Three Gorges Reservoir area, the average values of As, Cd, Cr, Cu, Hg, Ni, Pb and Zn in the study area are enriched to different degrees, except that the average content of Cr is lower than the background value. Among them, As, Cd and Hg elements were obviously enriched. (2) The calculation results of the single index of heavy metals in the surface soil showed that Cd pollution was the main in the area. Cu was only slightly to slightly polluted, and the number of lightly polluted samples accounted for only 0.07%. (3) The average Igeo trend of heavy metals in surface soil in the region was Cd>Hg>As>Pb>Zn>Cu>Ni>Cr. As, Pb, Zn, Cu, Ni and Cr were mainly non-slightly polluted. Cd and Hg elements were heavily polluted, but the sample accounted for a small proportion. The overall display area is dominated by Cd element pollution. (4) The source analysis results show that As, Cu, Pb, Ni, Zn and Cr in the study area are mainly derived from the earth's crust. Its content is related to the geological setting. The pollution of Hg and Cd is likely to be affected by human activities, mainly from atmospheric deposition.

Heavy Metal Pollution Status and Potential Ecological Risk Assessment in Farmland Surface Soil Along River in Jiaozuo Area

A total of 41 surface soil samples were collected from the farmlands along Guangliji River and Jianggou River in Jiaozuo area, and 7 heavy metals such As Cr, Cu, Zn, AS, Cd, Pb and Ni were determined by ICP-MS (Varian-820).The soil accumulation index method, single factor pollution index method, Nemerow comprehensive pollution index method and potential ecological risk index method were used to evaluate the pollution status and potential ecological risk of heavy metals in the study area. The results showed that compared with the risk screening value (pH>7.5) given in the "Soil Quality Standard for Soil Pollution Risk Control of Agricultural Land" (GB15618-2018), Cd in farmland soil along the two rivers exceeded the screening value by 5.7 times and 1.5 times, respectively, and was the main local pollutant. The Nemero comprehensive pollution index of the farmland along Guangliji River and Jianggou River was 9.71 and 1.88, respectively, which were in the level of heavy pollution and light pollution. The comprehensive potential ecological risk index of farmland along the two rivers is 417.65 and 85.79, with strong ecological risk and slight ecological risk respectively. The comprehensive evaluation shows that there is a certain degree of heavy metal pollution in the farmland soil along the river in Jiaozuo area, especially Cd pollution, and the ecological risk in some areas has exceeded the acceptable level, which should arouse the attention of the local government and relevant departments.

Status and risk assessment of heavy metal pollution in farmland soil in the southern suburbs of Jiaozuo City

A farmland in the southern suburb of Jiaozuo City was selected As the research area, 36 surface soil samples were collected, and the contents of heavy metals (Cd, Cr, Zn, Ni, Cu, Pb and As) in soil were determined. The ecological risk of heavy metals in soil was assessed by single factor pollution index method, Nemerow comprehensive pollution index method and potential ecological risk index method. The results showed that the average contents of Cd, Cr, Zn, Ni, Cu, Pb and As in the soil were 1.25, 62.96, 79.00, 28.91, 22.60, 11.02 and 42.25mg/kg, respectively. Cd and As in soil exceeded the standard, and the exceedance rate was 92.75% and 83.5%. The single factor pollution index was Cd>As>Cr>Zn>Cu>Ni>Pb from large to small, and Cd reached the moderate pollution level. The results of Nemerow comprehensive pollution index showed that Cd reached the level of severe pollution, and As was the level of severe pollution. The evaluation results of potential ecological risk index showed that Cd was at the moderate risk level, As was at the slight risk level, and other heavy metals were at the slight risk level. The comprehensive potential ecological risk index RI value was 13.87-266.80, which was at the slight to moderate risk level. Cd and As were the main risk sources of soil heavy metals, and their contribution rates to the comprehensive potential ecological risk index were 79% and 18%, respectively.

Ecotoxicological risks of heavy metals in floodplain sediments: Linking current conditions to future threats

Given increasing concerns about the environmental impact of heavy metal pollution, assessing the level of contamination in floodplain suspended sediments is an important task. Effective environmental management and the preservation of an ecosystem depend on understanding existing pollution levels and potential concerns in the future. For this reason, floodplain-suspended sediments from major industrialized cities in Southeast Nigeria were sampled and analyzed for heavy metal contents. The investigation was conducted to evaluate the immediate and long-term bioavailability and pollution status of heavy metals in receptor organisms. A five-step sequential extraction procedure was adopted to fractionate iron, manganese, copper, zinc, nickel, lead, cadmium, and chromium to determine the geochemical phases in which they were distributed. Generally, the heavy metals were partitioned in the following order: residual >> oxidizable > carbonate > reducible > exchangeable. This indicates that a significant portion of the metals were tightly bound to the soil matrix, rendering them not readily bioavailable to the biota, except over an extended period. The levels of heavy metals, except for lead and cadmium in specific areas, were below the saturation point in terms of their bioavailability. Furthermore, the pollution assessment indices, such as the geo-accumulation index, reflected high levels of cadmium, copper, and lead contamination. This suggests a potential ecotoxicological risk to organisms near the sampling sites. The sites were classified as moderate and high risk in terms of immediate and future risk assessment, respectively. This research has established connections between current conditions and future threats and contributed valuable insights for understanding and mitigating potential environmental hazards. Proper cleaning methods and potential site reclamation are imperative to minimize or contain these heavy metals in stable forms within urban areas to prevent bioaccumulation.

Pollution status and health risk assessment of heavy metals in the soil of Sahibzada Ajit Singh (SAS) Nagar district of Punjab, India and its source apportionment

The threat of heavy metals in soil due to rapid urbanization, intensive agricultural practices, vehicular emission, and industry-related activities is increasing day by day, causing high risk to environmental health. The present study assessed the heavy metal pollution (Cr, Co, Ni, Co, Zn, As, Cd, and Pb) in the soil of Sahibzada Ajit Singh Nagar District, Punjab, India, through the index of geoaccumulation (Igeo), contamination factors (CF), degree of contamination (DC), pollution load index (PLI), ecological risk factor (Er) and potential ecological risk indices (PRI). The results showed the concentration of heavy metals in the soil in the order of Pb > Zn > Ni > Cr > Cu > As > Co > Cd. The pollution risk assessment indices: Igeo, CF, and Er indicated that most soil samples were moderately contaminated with Pb. The village Majra showed considerable contamination as evidenced by the Cd. The multivariate statistical analysis revealed the anthropogenic sources (agricultural practices and discharges from micro, small and medium enterprises (MSME) industries) to be the possible sources of Cr, Co, Ni, Cu, Zn, and Pb. The health risk assessment studies indicated that carcinogenic risks were higher for children than the adults. The cancer risk (CR) for all heavy metals in decreasing order is As > Cr > Pb > Ni > Cd. Likewise, the non-carcinogenic risks calculated as HQ followed the order of Pb > As > Cr > Cd > Ni > Cu > Co > Zn. The significant disparities in heavy metal concentrations underscore the necessity of establishing appropriate baseline levels for toxic trace metals in soils.