Metal Pollution In Agricultural Soils 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.

Comprehensive assessment of heavy metal pollution of agricultural soils impacted by the Kalsaka abandoned gold mine and artisanal gold mining in northern Burkina Faso.

In this study, the environmental quality of agricultural soils around the Kalsaka abandoned gold mine was evaluated. A total of 117 samples including industrial mine wastes, topsoil, and control soil were collected in and around the mine, and their heavy metal concentrations were determined using ICP-MS after aqua regia digestion. Except for Zn, the average concentrations of the metals were higher in mine wastes and the agricultural soils than their average upper continental crust (UCC) counterpart, whereas those of Ag, As, and Hg exceeded the UCC in the control soils. The control soils had the lowest contaminations and the lowest pollution levels for all metals except for Hg. Based on the average concentrations and coefficients of variation, it can be concluded that Cr, Ni, and Zn abundance in the agricultural soils was controlled by natural factors, whereas that of Ag, As, Hg, Co, Cu, and Mn was mainly associated with mining. The absence of Hg in industrial mine wastes and its high contents in agricultural and control soils reflected the artisanal gold mining source of this metal. Thus, single and integrated pollution indices showed that ecological risk and toxicity are much higher when Hg is included in the index calculation, suggesting cumulative effects of industrial and artisanal gold mining on the agricultural soil quality. The results also showed that Hg and As are the pollutants of major concern in the Kalsaka abandoned gold mine. Because of its proximity to human settlements, the Kalsaka abandoned gold mine necessitates an immediate rehabilitation.

A meta-analysis and experimental survey of heavy metals pollution in agricultural soils

Heavy metal (HM) pollution in agricultural soils represents a hidden danger to food security worldwide. In this paper, the spatio-temporal trends of heavy metals from eight countries and 50 soil samples from agricultural farmland were evaluated through a combination of field surveys and meta-analysis to provide a comprehensive report on heavy metal pollution. The soil samples were analysed using inductively coupled plasma–mass spectrometry (ICP-MS) (Perkin Elmer Nixon 300Q). The contamination factor (CF) and pollution load index (PLI), and diagnostic tests on the extracted data were calculated. The results of the CF in the soils indicate extreme contamination for Cr, suggesting ecotoxicological effects, while the PLI values range from baseline to moderate pollution for Cd, Hg, Cu, Zn, and Ni, except for Cr, which shows very high pollution, suggesting that the soils have undergone some form of deterioration. The meta-analysis results of the 50 reviewed articles published between 2010 and 2023 showed increasing trends for all the HMs. The weighted mean values of Cd, Cr, Hg, Cu, Zn, As, and Ni were in the range of 0.0-222.7, 0.08-289.2, 0.03-193, 2.94-198.1, 0.0-771.1, 0.0-231, and 1.71-99.75.6 mg/kg, respectively. The mean values of Cd, Hg, Zn and As exceeded two to three times the values of China National Environmental Monitoring Centre (CNEMC) European Union's most cited guideline (MEF), and the rock crust guideline. The results of the correlation matrix heatmap revealed a highly positive correlation between Cr and Ni (R2 = 0.66), suggesting that these elements have the same source and are likely prevalent in agricultural soils. The spatial origin of the publications reveals that 82% of the studies were from China followed by South Africa and Italy accounting for 4% respectively while Nigeria, Egypt, Morocco, Iran, and Turkey account for 2% each. The findings of this study have important implications for environmental regulation on agricultural food protection from heavy metal pollution. Unlike previous meta-analysis studies which often adopt a “silos” method, this study highlights a nexus approach that integrates both meta-analysis and experimental studies which could establish a more comprehensive understanding of heavy metal pollution in agricultural soils.

Worldwide Examination of Magnetic Responses to Heavy Metal Pollution in Agricultural Soils

Over the last decade, a large number of studies have been conducted on heavy metals and magnetic susceptibility (χlf) measurement in soils. Yet, a global understanding of soil contamination and magnetic responses remains elusive due to the limited scope or sampling sites of these studies. Hence, we attempted to explore a pollution proxy on a global scale. Through a meta-analysis of data from 102 published studies, our research aimed to provide a worldwide overview of heavy metal pollution and magnetic responses in agriculture soils. We mapped the geographic distribution of nine heavy metals (Cr, Cu, Zn, Pb, Ni, As, Cd, Mn, and Fe) in agricultural soils and explored their pollution sources and contributions. Since 2011, The accumulation of heavy metals has escalated, with industrial activities (31.5%) being the largest contributor, followed by agricultural inputs (27.1%), atmospheric deposition (22.66%), and natural sources (18.74%). The study reports χlf ranging from 6.45 × 10−8 m3/kg to 319.23 × 10−8 m3/kg and χfd from 0.59% and 12.85%, with the majority of the samples being below 6%, indicating heavy metal influence mainly from human activities. Pearson’s correlation and redundancy analysis show significant positive correlations of Pb, Zn, and Cu with χlf (r = 0.51–0.53) and Mn and Fe with χfd (r = 0.50–0.53), while Pb, Zn, Cu, and As metals were shown to be key factors of variation in magnetic response. The average heavy metal pollution load index of 2.03 suggests moderate global agricultural soil pollution, with higher heavy metal contamination in areas of high χlf. Regression analysis confirms soil is considered to be non-polluted below χlf of 26×10−8 m3/kg and polluted above this threshold, with all contamination factors of metals showing a linear correlation with χlf (R = 0.72), indicating that a significant relationship between χlf and the geochemical properties of soils continues to exist on a global scale. This study provides new insights for large-scale agricultural soil quality assessment and magnetic response.

Zea mays cultivation, biochar, and arbuscular mycorrhizal fungal inoculation influenced lead immobilization.

Plant cultivation can influence the immobilization of heavy metals in soil. However, the roles of soil amendments and microorganisms in crop-based phytoremediation require further exploration. In this study, we evaluated the impact of Zea mays L. cultivation, biochar application, and arbuscular mycorrhizal fungi (AMF) inoculation on soil lead (Pb) immobilization. Our results indicated that biochar addition resulted in a significant, 42.00%, reduction in AMF colonization. Plant cultivation, AMF inoculation, and biochar addition all contributed to enhanced Pb immobilization, as evidenced by decreased levels of diethylenetriaminepentaacetic acid- and CaCl2-extractable Pb in the soil. Furthermore, soil subjected to plant cultivation with AMF and biochar displayed reduced concentrations of bioavailable Pb. Biochar addition altered the distribution of Pb fractions in the soil, transforming the acid-soluble form into the relatively inert reducible and oxidizable forms. Additionally, biochar, AMF, and their combined use promoted maize growth parameters, including height, stem diameter, shoot and root biomass, and phosphorus uptake, while simultaneously reducing the shoot Pb concentration. These findings suggest a synergistic effect in Pb phytostabilization. In summary, despite the adverse impact of biochar on mycorrhizal growth, cultivating maize with the concurrent use of biochar and AMF emerges as a recommended and effective strategy for Pb phytoremediation.IMPORTANCEHeavy metal contamination in soil is a pressing environmental issue, and phytoremediation has emerged as a sustainable approach for mitigating this problem. This study sheds light on the potential of maize cultivation, biochar application, and arbuscular mycorrhizal fungi (AMF) inoculation to enhance the immobilization of Pb in contaminated soil. The findings demonstrate that the combined use of biochar and AMF during maize cultivation can significantly improve Pb immobilization and simultaneously enhance maize growth, offering a promising strategy for sustainable and effective Pb phytoremediation practices. This research contributes valuable insights into the field of phytoremediation and its potential to address heavy metal pollution in agricultural soils.

Spatial and Temporal Distribution and Source Analysis of Heavy Metals in Agricultural Soils of Ningxia, Northwest of China

The spatial and temporal dynamic monitoring of the heavy metal concentration in agricultural soils can help us to understand the extent and changes of regional soil heavy metal pollution, allowing us safeguard food safety and human health and provide basic data for the prevention and control of heavy metal pollution in agricultural soils. The heavy metals’ concentrations, including Cd, Cr, Cu, Hg, Ni, Pb, Zn, and As, were measured in surface (0–20 cm) soil samples collected in 2017 and 2021 from agriculture land to evaluate their pollution levels in the Ningxia Hui Autonomous Region (Hereinafter referred to as Ningxia), northwest of China. A correlation analysis, principal component analysis, and positive matrix factorization were used jointly to identify possible sources. The results showed that, for most soils, the concentrations of As, Cr, Cu, Ni, Pb, and Zn were lower than the contamination thresholds stipulated by the national guideline. The average concentrations of As, Cd, Zn, and Ni in 2021 were significantly lower than the levels in 2017 (p < 0.05), but the average concentration of Cu was significantly higher in 2021 than in 2017 (p < 0.05), and the average concentrations of Cr, Pb, and Hg did not change significantly during the last five years. According to the pollution assessment index (mean Igeo values), Cd and Hg were found to accumulate in the farmland environment and were the major pollutants in the region, and the hotspots with high concentrations of heavy metals were mainly located in the Yellow River irrigation area in Northern Ningxia. Four main sources of heavy metals in the soils were identified: As mainly originated from natural sources; Pb, Cd, and Ni from atmospheric deposition and industrial activities; Cr, Zn, and Cu from agricultural activities; and Hg from the coal-related industrial activities. The concentration of heavy metals from anthropogenic sources accounted for 77.10% in agricultural soils, indicating the strong influence of this source on soil heavy metal accumulation. These findings provide scientific evidence and valuable information to prevent heavy metal contamination and control of farmland.

Assessment of metal pollution in agricultural soils and associated human health risk in Shifang City, China

AbstractMetals in soils exert toxic effects on soil quality and human health. In order to carry out metal contamination assessment and human health risk assessment of agricultural soils, a total of 662 cultivated soil samples were collected from two industrially oriented towns and three agriculturally oriented towns of Shifang City, Southwest China. Various indices were applied to analyze the pollution levels of soils caused by metals (Cr, Fe, Pb, Sr, Ti, V, Zn, and Zr). The relatively high values of the geo‐accumulation index (Igeo) and the enrichment factor (EF) suggested that Sr, V, and Zn had cumulative trends in the soils. The average pollution load index (PLI) values of the industrial towns (1.19 and 0.99) were higher than those of the agricultural towns (0.92, 0.53, and 0.43), demonstrating the contribution of industrial activities to soil metal enrichment. The health risk assessment from the five towns indicated that Cr and V were the dominant contaminants in soils with high potential health risks. Dermal contact was the major pathway of the exposure of children and adults to Cr and V. This study improved the understanding of the pollution levels of metals in Shifang agricultural soils and put forward the necessity of minimizing the health risk of Cr and V in agricultural soil.

The Impacts of Elevated CO2 Levels on Environmental Risk of Heavy Metal Pollution in Agricultural Soils: Applicable Remediation Approaches for Integrated Benefits

Heavy metal pollution in agricultural fields is a serious health concern because of the high bioavailability and persistent toxicity of heavy metals. Much progress has recently been made with respect to elucidating the impacts of climate change (e.g., elevated atmospheric CO2 concentrations) on the environmental behavior of heavy metal pollutants and the associated ecological and health risks. The microbiological responses to elevated CO2 levels are primarily mediated by the C balance in agricultural activities; however, the underlying mechanisms involved in plant–soil–microbe interactions under heavy metal stress are still unclear. Thus, in this study, the challenges and perspectives with regard to controlling heavy metal pollution and optimizing crop yields while reducing greenhouse emissions in agricultural ecosystems responsive to elevated CO2 levels are discussed. Considering the integrated benefits of intensive agriculture and food security under a future changing climate, the summarized findings provided in this study may help to develop applicable remediation approaches for sustainably managing heavy metal polluted soils.

Phosphate solubilizing microorganism: a green measure to effectively control and regulate heavy metal pollution in agricultural soils.

Phosphate solubilizing microorganism: a green measure to effectively control and regulate heavy metal pollution in agricultural soils.

Sustainable phytoextraction of metal-polluted agricultural land used for commercial photovoltaic power generation

Metal pollution of agricultural soils is currently an issue of major concern in China and many soils require remediation. Photovoltaic (PV) power generation is a useful source of renewable energy but solar power plants often require large areas of land. Combining PV power generation with phytoextraction on contaminated arable land is therefore a novel and potential option if these processes can work effectively together. A three-year-long continuous field study was conducted to test the feasibility of phytoextraction using a metal hyperaccumulator species growing under arrays of PV panels. Meteorological data were collected and the growth and cadmium (Cd) and zinc (Zn) uptake of the Cd/Zn hyperaccumulator Sedum plumbizincicola were determined. Shading by the PV panels reduced the annual solar irradiance by 58.4% but this showed no inhibitory effect on plant growth or metal uptake by S. plumbizincicola. Phytoextraction under the PV panels gave high removal efficiencies of Cd and Zn and the hyperaccumulator took up Cd and Zn at rates of 3.40 and 96.2 kg ha−1, respectively, for three seasons. It is concluded that soil phytoextraction and PV electricity generation can be combined to realize soil remediation and energy production.

Combining spatial autocorrelation with artificial intelligence models to estimate spatial distribution and risks of heavy metal pollution in agricultural soils

Information on spatial distribution and potential sources of heavy metals in agricultural lands is very important for human health and food safety. In this study, pollution degree of lead (Pb), cadmium (Cd), and nickel (Ni) in Yüksekova Plain, located on the border in the southeastern part of Turkey, was evaluated by geoaccumulation index (Igeo), modified contamination factor (mCdeg), and Nemerow pollution index (PINemerow) combined with spatial autocorrelation using deep learning algorithms. A total of 304 soil samples were collected from two different depths (0-20 and 20-40cm) in the study area, which covered 17.5 thousand ha land. Covariates were determined for spatial distribution models of Pb, Cd, and Ni by factor analysis (FA). Spatial distribution models for surface soils were developed using pedovariables (silt, sand, clay lime, organic matter, electrical conductivity, pH, Ca, and Na) determined by the FA and Igeo and mCdeg values by artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) models. The estimation success of models for different depths was assessed by root mean square error (RMSE), mean absolute percent error (MAPE), and Taylor diagrams. The RMSE and MAPE values showed a strong correlation between heavy metal contents and the covariates. The RMSE values of ANN-Ni0-20, ANN-Ni20-40, ANN-Pb0-20, ANN-Cd0-20, and ANN-Cd20-40 models (0.01240, 0.07257, 0.0039, 0.00045, 0.00044, and 0.04607, respectively) confirmed the success of the models. Likewise, the MAPE values between 0.2 and 8.5% indicated that all models were very good predictors. In addition, the Taylor diagrams showed that the estimation performance of ANFIS and ANN models are compatible. The IgeoNi and IgeoPb values in both models at both depths indicated that strongly to extremely polluted (4-5) areas are quite high in the study area, while the IgeoCd values revealed that unpolluted areas are widespread. The mCdeg index value showed a moderate to high contamination at the first depth, while very high contamination at the second depth in most of the study area. Spatial distribution of PINemerow revealed that moderate pollution (2-3) is common in both soil depths of the study area. The PINemerow of subsurface layer was between 0.91 and 1 (warning limit class) in a small part of the study area. The results showed that vertical mobility of heavy metals is closely related to pedovariables. In addition, the ANN and ANFIS models are capable of exhibiting the heterogeneity in the spatial distribution pattern of high variation in the data. Thus, the locations with extreme contamination have been accurately determined. The pollution indices calculated considering the commonly used international reference values revealed that heavy metal pollution in some part of the study area reached the detrimental levels for human health and food safety. The results suggested that the pollution indices were more successful than simple heavy metal concentrations in interpreting the pollution risk levels. High-resolution spatial information reported in this study can help policy makers and authorities to reduce heavy metal emissions of pollutants or, if possible, to eliminate the pollution.

Heavy metal pollution in agricultural soils of a typical volcanic area: Risk assessment and source appointment.

Heavy metals are naturally occurring elements with high natural background levels in the volcanic area. Therefore, it is necessary to conduct a risk assessment and identify potential sources of heavy metals. In this study, 4488 soil samples (0-20cm) were collected in Chengmai County, a typical volcanic area in Hainan Province, and analyzed for eight heavy metals and major oxides. Pollution level, ecological risks, and health risks were evaluated by geo-accumulation index (Igeo), pollution index (PI), potential ecological risk index (RI), hazard index (HI), and carcinogenic risks (CR). The positive matrix factorization (PMF) model was further used to determine the priority source of heavy metals. The average values of heavy metal concentrations in soil were 7.06, 0.07, 156.88, 33.43, 0.05, 72.47, 19.48, and 67.51mgkg-1 for As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn, respectively. Except for Pb, the average concentrations of all heavy metals exceeded background concentration in Hainan soils, indicating different degrees of heavy metal enrichment. The Igeo and PI showed that the main pollutant element in volcanic soils was Ni, followed by Cr and Cu. The RI shows that the percentage of soil samples with considerable or worse potential ecological risk was 44.4% of the total samples, with Hg, As, Cd, and Ni causing high ecological risks. The estimated average daily doses of heavy metals were below the tolerable limits and the HI values were below one for both adults and children, indicating that the residents had an acceptable potential non-carcinogenic risk. However, the potential carcinogenic risk of exposure to Cr, Ni, and As was unacceptable for residents, with high CR values exceeding 10-4, especially for children. Based on the PMF, five major sources of heavy metals were found in the study area: Ni, Cu, and Zn mainly from parent materials, As and Pb from daily life and vehicle emissions, Cd from agricultural activities, Hg from industrial activities, and Cr from parent materials under different environmental conditions. Significant positive correlations between Al2O3, TFe2O3, Mn, soil organic carbon (SOC), and heavy metals reflect that aluminium-rich minerals, Fe-Mn oxides, and SOC are the most critical factors affecting heavy metal accumulation in volcanic agricultural soils.

Health Risk Assessment of Some Selected Heavy Metals in Agricultural Soils from Katsina State, North-Western Nigeria

This work contributes to the monitoring of heavy metal pollution of Agricultural soils, Katsina State Nigeria, using Atomic Absorption Spectrophotometry. The heavy metal contamination of the soil samples were analyzed based on the Geoaccumulation index (Igeo), enrichment factor (EF), contamination factor (CF), pollution load index (PLI) and potential ecological risk index (PERI). The health risks of the evaluated heavy metals were estimated using the Hazard Quotient (HQ) and Hazard Index (HI)) to evaluate the possible non-carcinogenic effect and the Incremental Lifetime Cancer Risk (ILCR) for the cancer risk to the population. The results of the study had revealed that in the soil samples all the evaluated heavy metals lie within acceptable limits as set by the regulatory agencies. The evaluated soil samples pollution indices had revealed that the I-geo values for the soil samples were within the range of unpolluted to moderate pollution. Also, the heavy metal enrichment factor (EF) value for the soil samples have indicated that only the heavy metal Fe showed significant enrichment, with the soil samples being moderately contaminated with Fe. The pollution load index (PLI) also indicated unpolluted to moderate pollution. With the potential ecological risk index (PERI) values presenting low ecological risks. The calculated non-cancer risk indices in both the children and adults population for all the heavy metals were less than 1. With the exception of the ILCR for the heavy metal Pb in children from Daura zone that was in limits that environmental and regulatory agencies considered as unacceptable risk, risk values for all the heavy metals falls within the range of the threshold of the safe limit and limits regarded as safe by the regulatory agencies (10-7 to 10-4). The results of pollution indices have indicated that the Agricultural soil samples have low contamination and low health risks by the heavy metals evaluated.

Source analysis and source-oriented risk assessment of heavy metal pollution in agricultural soils of different cultivated land qualities

Heavy metal pollution in soil has received much attention in recent decades. Many studies have analyzed the contamination status, spatial distribution, and pollution sources of heavy metals. Little information is available on the interaction between cultivated land quality and soil heavy metal pollution. Combining soil quality information and intensive heavy metal sampling surveys, this study analyzed heavy metal contamination and the ecological and health risks of various soils with different quality levels. Additionally, through the PMF model and risk assessment techniques, the ecological and health risks of specific pollution sources and their interaction with soil quality were investigated. The results showed that the mean content of the studied elements followed the increasing order of Hg (0.12 mg/kg) < Cd (0.19 mg/kg) < As (6.98 mg/kg) < Pb (25.57 mg/kg) < Cr (72.02 mg/kg). In addition, with increasing soil quality, the concentrations of Pb, Cr and Hg as well as the overall ecological risk increased significantly. Regarding health risks, heavy metal pollution posed a higher risk to children than adults, and ingestion was the main exposure pathway. The total hazard index and carcinogenic risk also increased with increasing soil quality. The PMF analysis showed that Pb and Cr mainly came from industrial activities, As could be attributed to natural sources, Cd was mainly derived from agricultural activities, and Hg pollution was determined by coal combustion. Considering the risks of specific pollution sources, agricultural activities and coal combustion were the major reasons for high ecological risks, whereas industrial activities and coal combustion posed significantly higher risks in suburban high-quality soil. Industrial activities mainly determined the health risk, which contributed more than 50% to the total risk. There was an upward health risk trend with increasing soil quality. Industrial activities in high-quality suburban soil posed the highest health risk to both adults and children. Reasonable and effective policies should be formulated to control industrial pollution and improve the ecological environment in this area.

Distribution Characteristics and Relevance of Heavy Metals in Soils and Colloids Around a Mining Area in Nanjing, China.

Heavy metal pollution in agricultural soils poses a direct threat to food safety and human health. It has been shown that the colloids is the carrier of heavy metal transport in the polluted soil by heavy metals, but the sources of heavy metals in the soil and colloids and their interrelations are not transparent at present. This study aims to investigate the distribution characteristics of heavy metals in agricultural soils near mining areas, and reveal the relevance of heavy metal content in colloids with total content in soils and their chemical species in soils. Results showed that the concentrations of Mn, Zn, and Pb in agricultural soils and colloids were higher than those of other heavy metals. The content of heavy metals in colloids was positively correlated with the total content of heavy metals in soil. Heavy metals in soil could be easily combined by humus-like substances and tryptophan-like protein in the colloids. The primary source of heavy metals in soil and colloids was mining activities. This study provides theoretical support for revealing the pollution characteristics and migration of heavy metals in agricultural soils and colloids around mining areas.

A synthesis framework using machine learning and spatial bivariate analysis to identify drivers and hotspots of heavy metal pollution of agricultural soils

Source apportionment can be an effective tool in mitigating soil pollution but its efficacy is often limited by a lack of information on the factors that influence the accumulation of pollutants at a site. In response to this limitation and focusing on a suite of heavy metals identified as priorities for pollution control, the study established a comprehensive pollution control framework using factor identification coupled with spatial agglomeration for agricultural soils in an industrialized part of Zhejiang Province, China. In addition to elucidating the key role of industrial and traffic activities on heavy metal accumulation through implementing a receptor model, specific influencing factors were identified using a random forest model. The distance from the soil sample location to the nearest likely industrial source was the most important factor in determining cadmium and copper concentrations, while distance to the nearest road was more important for lead and zinc pollution. Soil parent materials, pH, organic matter, and clay particle size were the key factors influencing accumulation of arsenic, chromium, and nickel. Spatial auto-correlation between levels of soil metal pollution and industrial agglomeration can enable a more targeted approach to pollution control measures. Overall, the approach and results provide a basis for improved accuracy in source apportionment, and thus improved soil pollution control, at the regional scale.

Identifying the Source of Heavy Metal Pollution and Apportionment in Agricultural Soils Impacted by Different Smelters in China by the Positive Matrix Factorization Model and the Pb Isotope Ratio Method

In this study, the agricultural soil around Zhuzhou Smelter in Zhuzhou district, Hunan, China and Huludao Zinc Plant in Huludao district, Liaoning, China was selected as the research area to discuss the current situation of heavy metal pollution in the surrounding agricultural soil caused by different smelting plants for soil environmental management and sustainable development of soil resources. Eight elements’ (Cd, Pb, As, Hg, Cr, Ni, Cu, and Zn) contents were measured to assess their pollution risk level and spatial distribution distinction. Correlation analysis, the positive matrix factorization (PMF), and Pb isotope ratio method were employed to analyze the sources of soil heavy metal pollution in the research area. The contents of Cd, Pb, Hg, and Zn in the soil of the two research areas were seriously polluted, and the changes of their spatial content were related to the migration and sedimentation of the smelter waste gas. Four types of pollution sources, including the smelting source, agricultural sources, natural sources, and mixed sources of industrial activity and traffic were identified in both areas by PMF, and the contribution rates of the four pollution sources in both areas were similar. Taking the agricultural soil around Huludao Zinc Plant as an example, the contribution rates of the different pollution sources analyzed by Pb isotope ratio method were the lead smelting source (43.7%), followed by the agricultural source (34.6%), traffic source (14.2%), and natural source (7.5%), which were basically consistent with that of PMF analysis, verifying the reliability of the two methods. The results above showed that the smelters were the main cause of heavy metal pollution in agricultural soils around the two research areas, and the analysis results of element content ratio and smelting source characteristic element contribution rate ratio could provide reference for the analysis of heavy metal pollution in agricultural soil around smelters for soil pollution control decision making.

Enzymatic disturbances of the Egyptian beetle, Blaps polychresta (Forskål, 1775), as environmental indicators of heavy metal pollution of agricultural soils

Heavy metals (HMs) pollution is becoming influential severe trouble in the farming ecosystem, where it causes serious health problems for many living organisms. This study was conducted to estimate the HMs accumulation under different sites from agricultural soil and its effects on enzymatic activities in tissues of the beetle, Blaps polychresta, as an indicator of soil contamination. Beetle and soil samples were collected from three agricultural sites; (A) a reference site, (B) fields located near the River Nile, and (C) fields closed to drainage. The atomic absorption results showed a significant increase in iron (Fe), manganese (Mn), arsenic (As), lead (Pb), chromium (Cr), aluminum (Al), and zinc (Zn) for both soil and beetles from site B & C compared to site A. The highest bioaccumulation (BAF) ratio was observed for nickel (Ni), As, and cadmium (Cd) in site C, while Zn, copper (Cu), and Pb in site B. HMs accumulation in beetle's tissues (gut, fat body, and testis) from site B & C induced the malondialdehyde (MDA) activity. Thus, a significant reduction of the antioxidant enzymes and total protein contents (TPc) were observed in beetle tissues from site C. However, no significant differences in some tissues of site B compared to other sites. A principal component analysis (PCA) and correlation were conducted between HMs concentrations in beetle tissues and antioxidant enzymes, TPc, and MDA. The current results of a principal component analysis (PCA) and the correlation test were used to assist the differences in the decline of the antioxidant enzymes: glutathione (GSH), Superoxide dismutase (SOD), catalase (CAT), glutathione-S-transferase (GST), glutathione peroxidase (GPx), and glutathione reductase (GR) and TPc, while; the elevation in MDA responses in beetle's tissues due to HMs accumulations in response to protect themselves from metals toxicity. The antioxidant defense and oxidative stress were more prominent in the tissues of the beetle's gut and fat bodies comparing to the testis. Accordingly, the HMs accumulation in agricultural soil can be predicted by the enzymatic activities in beetle tissues.

Source Apportionment of Heavy Metal Pollution in Agricultural Soils around the Poyang Lake Region Using UNMIX Model

Rapid urbanization and industrialization have caused the continuous discharge of heavy metals into the soils of China’s Poyang Lake region, where they pose a major threat to human health. Yet, the spatial characteristics of these heavy metals in farmland soils and their pollution sources in this region remain unclear. This study was conducted to document the pollution caused by heavy metals in the Poyang Lake region through sampling that consisted of the collection of 215 soil samples from agricultural fields. The UNMIX model provided identification of the sources causing heavy metal pollution and source contributions to soil pollution. ArcGIS was used to study the spatial distribution of the eleven heavy metals and to validate the apportionment of pollution sources provided by the UNMIX model. Soil concentrations of heavy metals were above the local background concentrations. The average content of eight heavy metals, including Cd, Mo, Zn, Cu, Sb, W, Pb, and Ni, was approximately 1–6 times greater than natural background levels (6.91, 2.0, 1.67, 1.53, 1.23, 1.38, 1.11, and 1.24, respectively), while the average content of V, Cr, and Co was lower than natural background levels. The average contents of Cr, Ni, Cu, Zn, Cd, and Pb were all lower than the screening levels for unacceptable risks in agricultural land soils. The percentage of Cd content exceeded the risk screening value in all sampling sites, up to 55%, indicating that agricultural soils may significantly be affected by cadmium contamination. Five pollution sources of heavy metals were identified: natural sources, copper mine tailings, agricultural activities, atmospheric depositions, and industrial activities. The contribution rates of the pollution sources were 7%, 13%, 20%, 29%, and 31%, respectively. The spatial pattern of heavy metals was closely aligned with the outputs of the UNMIX model. The foregoing supports the utility of the UNMIX model for the identification of pollution sources of heavy metals, apportionment study, and its implementation in agricultural soils in the Poyang Lake region.

Cadmium concentration and its typical input and output fluxes in agricultural soil downstream of a heavy metal sewage irrigation area

Heavy metal pollution of agricultural soils in sewage irrigation areas is a serious environmental issue. Many prior studies have demonstrated that soil around the irrigation area is polluted with heavy metals, even though they had not been irrigated by wastewater. In this study, a paddy field downstream of the Zhangshi Irrigation Area was selected as the study area. The Cd concentrations and their representative input and output fluxes to and from the topsoil were systematically studied. The results showed that 95.5% of soil samples exceeded the screening value of Cd concentration. The Cd input fluxes via irrigation water and atmospheric deposition, accounting for 56.95% and 42.53% of the total input flux, respectively, were the main sources of Cd in soil. Crop harvesting was the main output pathway, accounting for 89.63% of the total output flux. An estimation of the annual mass balance showed that Cd in the studied area was in a state of accumulation, and the annual increase in Cd concentration in topsoil would be 2.46 µg kg−1 if the observed fluxes remain. These results will provide a reference for the development of strategies to control and reduce heavy metal contamination and diffusion in agricultural soils around irrigation areas.