Distribution Of Metals In Soils Research Articles

Heavy Metal Content in the Soil of Baiji Refinery and Surrounding Area, Controlling its Distribution Factors

This study was conducted to analyze the presence of heavy metals within the soil inside and around Baiji Oil Refinery and their factors that control the spatial distribution of metals in soils existed as (organic matter (OM), iron-manganese, pH, clay minerals). In this study, geochemical analysis of Baiji Oil Refinery soil and nearby areas was conducted by Atomic Absorption Spectrophotometer (AAS). Twenty two samples were analysed in which the results showed heavy metal as (Cd, Pb, Cr, Ni, Fe, Mn, Zn and Cu) concentrations that most of these metals were found to be higher than their global limits in the soil, except (Fe, Mn and Zn) found to be within those limits. Controlling factors were conducted for six samples, three of highest concentrations and three of lowest one. The results reveal that the mean concentration of OM in the highest concentrations was 1.64% while the lowest concentrations was 1.59%, the mean concentration of Fe-Mn was in the highest concentrations 23380-359 ppm and in the lowest samples was 11304-114 ppm, respectively. The mean concentration for the pH in the highest concentrations was 8.5 and for the samples within the lowest concentrations was 7.9. However, the mean clay for the samples within the highest concentration were 1.04%, whereas the samples within the lowest concentration were 1.48%. The results showed that the controlling factors did not affect the soil heavy metal distribution of Baiji Oil Refinery and their nearby areas. Therefore, such results indicate the role of industrial processes (oil industries) in increasing the concentration of heavy metals in the soils in addition to the elements inherited from the parent rocks.

A geographically weighted neural network model for digital soil mapping of heavy metal copper in coastal cities

Assessing the spatial distribution of heavy metals in soil is essential for mitigating risks to human health and ensuring the sustainable use of soil resources. This study proposed a geographically weighted neural network (GWNN) model, leveraging deep learning and geographically weighted regression (GWR). The model was designed based on the GWR concept to address the spatial autocorrelation of copper (Cu) in soil and incorporated convolutional neural network (CNN) to capture the nonlinear relationships between Cu and environmental covariates. The GWNN model was compared with GWR, extreme gradient boosting (XGBoost), and artificial neural network (ANN) models. XGBoost was employed to select important environmental covariates and spatial autocorrelation of Cu concentrations was assessed using Moran’s I. The model’s performance was evaluated using 10-fold cross-validation, and prediction uncertainty was quantified with 100 bootstrap models. The results indicated that temperature covariates were the most significant predictors of soil Cu concentrations. The R2 values for Cu prediction accuracy were 0.60 for GWNN, 0.53 for ANN, 0.49 for XGBoost, and 0.32 for GWR. The spatial distribution of Cu showed a trend of higher concentrations in the north and lower concentrations in the south, consistent with spatial clusters identified by local Moran’s I. The mean uncertainty of the 90% confidence interval for GWNN was 16.49%, closely aligning with XGBoost (15.44%) and ANN (16.29%) and significantly outperforming the GWR (18.25%). Overall, the GWNN model demonstrated strong predictive accuracy and low uncertainty, offering an improved approach for digital soil mapping applications.

Accumulation and Distribution of Heavy Metals in Soils and Medicinal Plants in the Impact Zone of Novocherkassk Power Station

Accumulation and Distribution of Heavy Metals in Soils and Medicinal Plants in the Impact Zone of Novocherkassk Power Station

Assessment of heavy metals in soil, leaf litter, and their bioaccumulation in terrestrial macroinvertebrates in Sohag Governorate, Egypt.

The presence of elevated levels of heavy metals in soil poses a significant environmental concern with implications for human health and other organisms. The main objective of our study was to reduce the gap information of seasonal abundance, distribution of heavy metals in soil, leaf litter, and some macroinvertebrates in a citrus orchard (Citrus sinensis) in Sohag Governorate, Egypt. The heavy metals copper (Cu), zinc (Zn), lead (Pb), and cadmium (Cd) were determined by atomic absorption spectrometry. Degree of contamination (DC) was determined for both soil and leaf litter contamination. However, the bioaccumulation factor (BAF) was estimated to determine metal accumulation in the macroinvertebrates including earwigs Anisolabis maritima, chilopoda Scolopendra moristans, spider Dysdera crocata, and earthworm Aporrectodea caliginosa. The study area had clay-loam with varying organic matter, salinity, and pH levels. The degree of contamination varied among seasons, with the highest levels typically observed in autumn in both soil and leaf litter. The soil ranged from low contamination (1.82) to high contamination levels (4.4), while the leaf litter showed extremely high (30.03) to ultra-high (85.92) contamination levels. The mean ecological risk index results indicated that the sampling area had moderate ecological risk levels for Cd (44.3), Zn (42.17), and Pb (80.05), and extremely high levels for Cu (342.5). Heavy metal concentrations in the selected fauna were the highest in autumn, and the bioaccumulation factor varied among species and seasons with some species classified as e-concentrators, micro-concentrators, and macro-concentrators of certain heavy metals. Scolopendra moristans exhibited the highest mean metal concentrations (Cd, Pb, and Zn), while Aporrectodea caliginosa had the lowest. Thus, the differences in heavy metal concentrations found in different soil taxa highlight the significance of taxing a holistic understanding of feeding mechanisms into account when evaluating the potential risk for animals that consume invertebrates.

Pollution Indices, Potential Ecological Risks and Spatial distribution of Heavy Metals in soils around Delta State, Nigeria

Pollution Indices, Potential Ecological Risks and Spatial distribution of Heavy Metals in soils around Delta State, Nigeria

Analysis of the Spatial Distribution of Heavy Metals in Soil of Sewage-Irrigated Agricultural Fields in Arid Regions and Comprehensive Evaluation Methods

Analysis of the Spatial Distribution of Heavy Metals in Soil of Sewage-Irrigated Agricultural Fields in Arid Regions and Comprehensive Evaluation Methods

Mapping soil trace metal distribution using remote sensing and multivariate analysis.

Trace metal soil contamination poses significant risks to human health and ecosystems, necessitating thorough investigation and management strategies. Researchers have increasingly utilized advanced techniques like remote sensing (RS), geographic information systems (GIS), geostatistical analysis, and multivariate analysis to address this issue. RS tools play a crucial role in collecting spectral data aiding in the analysis of trace metal distribution in soil. Spectroscopy offers an effective understanding of environmental contamination by analyzing trace metal distribution in soil. The spatial distribution of trace metals in soil has been a key focus of these studies, with factors influencing this distribution identified as soil type, pH levels, organic matter content, land use patterns, and concentrations of trace metals. While progress has been made, further research is needed to fully recognize the potential of integrated geospatial imaging spectroscopy and multivariate statistical analysis for assessing trace metal distribution in soils. Future directions include mapping multivariate results in GIS, identifying specific anthropogenic sources, analyzing temporal trends, and exploring alternative multivariate analysis tools. In conclusion, this review highlights the significance of integrated GIS and multivariate analysis in addressing trace metal contamination in soils, advocating for continued research to enhance assessment and management strategies.

Effects of drip and flood irrigation on soil heavy metal migration and associated risks in China

BackgroundDifferent irrigation methods have variable effects on the physiochemical properties of soils. The predicted widespread replacement of flood irrigation with drip irrigation will alter the micro-environment of the associated soils in terms of migration, transformation, morphology, and toxicology of heavy metals and pesticides. The dynamics of heavy metals in soil under drip irrigation have only been investigated with regard to the use of sewage and reclaimed water; studies comparing these patterns across different irrigation methods are scarce. PurposeHere, we aimed to investigate the effects of drip and flood irrigation on heavy metal distribution in soil and the related risks in three typical agricultural systems in China. MethodsWe used fixed-point sampling, digestion analytical methods, descriptive analyses, one-way analysis of variance (ANOVA), Nemerow pollution index analyses, and correlation analyses to investigate the different effects of drip and flood irrigation on heavy metals (Cd, Cr, Cu, Pb, and Zn) in soils from Hebei, Xinjiang, and Ningxia Provinces, China. Results and DiscussionAnalyses of soil samples collected from drip-irrigated fields revealed significant differences in the concentrations of soil heavy metals at depths of 0–60 cm. Drip irrigation had a greater effect on heavy metal content in the soil surface than flood irrigation. In addition, heavy metals likely accumulated at the edges of the wetting fronts following prolonged irrigation. In comparison to drip irrigation, flood irrigation elevated pollution levels in the soil. The amount of fertiliser affected the leaching and migration of heavy metals in the soils by altering the physiochemical characteristics of the drip irrigation solution. ConclusionDrip irrigation alters the dynamics of heavy metals in soil by influencing their migration and accumulation patterns. This effect can be attributed to the methods of adding water and fertilisers to the soil under drip irrigation. Altering these variables can impact the level of heavy metals that bioaccumulate in crops. This study provides a scientific basis for reducing heavy metal pollution under drip irrigation.

Risk Assessment of Heavy Metal Distribution in Soil of a Typical Tourist Island in South China

Risk Assessment of Heavy Metal Distribution in Soil of a Typical Tourist Island in South China

Assessment of depth wise distribution, enrichment, contamination, ecological risk and sources of soil heavy metals over an Industrial area in Southern India

Assessing the depth-wise distribution of heavy metals in soil can provide valuable insights into the extent of enrichment, contamination, and the possible sources of pollutants. A study was conducted in parts of Patancheru Industrial areas of Hyderabad, India to assess the vertical distribution of heavy metal content in soil, focusing on enrichment, contamination, and pollutant sources. Sixty soil samples from 15 sites, spanning four depths (0–15 cm, 15–30 cm, 30–50 cm, 50–100 cm) were analyzed for total Fe, Mn, Zn, Cu, Pb, Cr, Co and Ni concentrations. The concentrations of Fe, Mn, Zn, Cu, Pb, Cr, Co, and Ni, regardless of the study depths and sites, range from 2570–10,667, 22.5–439, 11.6–47.2, 3.47–14.2, 5.53–31.7, 36.0–63.1, 2.99–17.5 to 10.5–47.3 mg kg−1respectively. The mean concentrations of all the measured heavy metals showed minor variation across depths, except for Zn and Pb. Moreover, the mean concentration of all the measured heavy metals at various soil depths was within the threshold or target limits except for total Ni. At certain sampling depths and locations, Ni content exceeded the permissible threshold of 35 mg kg−1 in the soil. Surface soils (0–15 cm) exhibited moderate to significant enrichment of Pb, Zn, Cr, and Co. The enrichment factor for the overall Pb concentration varies from 3.02 to 24.73, indicating a range of moderate to very high enrichment throughout the soil depths. Following Pb, Cr exhibits enrichment levels ranging from 2.31 to 9.35, while Co ranges from 1.07 to 5.58.The sites within the study area varied in contamination levels, spanning from moderate contamination to a slight degree of pollution, as assessed by the contamination/pollution index of each element. Principle component analysis and enrichment factor values show that Cu originated primarily from natural sources; while Pb and Cr were likely to be anthropogenic to purely anthropogenic and Zn, Mn, Ni, and Co had both crustal and like to be anthropogenic origins. The maximum and minimum ecological risk index (ERI) values were recorded for Pb and Zn content, respectively. The maximum PERI value of 15.8 was recorded in the study area, indicating a low ecological risk level. However regular monitoring of the heavy metal concentration in soils is recommended over the study area to maintain a low level of ecological risk via reclamation interventions.

Spatial distribution prediction of soil heavy metals based on sparse sampling and multi-source environmental data

Predicting the precise spatial distribution of heavy metals in soil is crucial, especially in the fields of environmental management and remediation. However, achieving accurate spatial predictions of soil heavy metals becomes quite challenging when the number of soil sampling points is relatively limited. To address this challenge, this study proposes a hybrid approach, namely, Light Gradient Boosting Machine plus Ordinary Kriging (LGBK), for predicting the spatial distribution of soil heavy metals. A total of 137 soil samples were collected from the Shengli Coal-mine Base in Inner Mongolia, China, and their heavy metal concentrations were measured. Leveraging environmental covariates and soil heavy metal data, we constructed the predictive model. Experimental results demonstrate that, in comparison to traditional models, LGBK exhibits superior predictive performance. For copper (Cu), zinc (Zn), chromium (Cr), and arsenic (As), the coefficients of determination (R²) from the cross-validation results are 0.65, 0.52, 0.57, and 0.63, respectively. Moreover, the LGBK model excels in capturing intricate spatial features in heavy metal distribution. It accurately forecasts trends in heavy metal distribution that closely align with actual measurements. Environmental ImplicationThis study introduces a novel method, LGBK, for predicting the spatial distribution of soil heavy metals. This method yields higher-precision predictions even with a limited number of sampling points. Furthermore, the study analyzes the spatial distribution characteristics of Cu, Zn, Cr, and As in the grassland coal-mine base, along with the key environmental factors influencing their spatial distribution. This research holds significant importance for the environmental regulation and remediation of heavy metal pollution.

Assessment of iron and heavy metals accumulation in the soils of the combat zone

The object of the study is soils in areas with active military operations. The study is dedicated to assessing the environmental impact of military operations through forecasting. The paper highlights the impact of military conflict on the distribution of heavy metals in soils. An analysis of the distribution and interaction of heavy metals in soil is carried out, which helps to understand the dynamics of pollution in the context of military conflict, and allows to understand the complex processes of the impact of military operations on the environment and the state of soil resources. The complex interrelationships between military operations and environmental pollution are revealed, with an emphasis on the importance of studying the distribution and immobilization of iron and heavy metals in the current conditions of the risk of military operations. It is shown that the most rapidly distributed metals in the soil are: iron (Fe), zinc (Zn), cadmium (Cd), antimony (Sb); the slowest: arsenic (As), lead (Pb), copper (Cu), nickel (Ni), mercury (Hg), manganese (Mn), vanadium (V). It was found that loams and chernozems are more prone to the accumulation of heavy metals and iron than sandy soils. Compared to sandy soil, the rate of metal release in loam decreases from 16.7 % to 69.7 %. In comparison of chernozem to loam, the release rate slows down from 17.85 % to 32.08 %. It was found that the rate of spreading of barium, cobalt, arsenic, lead, mercury, manganese, strontium and titanium does not depend on the type and mechanical parameters of the soil. The practical use of the results will help to predict the mechanism of pollution spread and help to identify the highest risk areas. The results of the study indicate the need to develop scientifically sound strategies for environmental protection and promotion of sustainable development in the area affected by military events

Spatial distribution of heavy metals in soils around cement factory and health risk assessment: a case study of Canakkale-Ezine (NW Turkey).

Sustainable use of agricultural land plays a crucial role in ensuring food security. For sustainable use of soils, it is very important to focus on the pollution status. This study was conducted on the soils in the northern part of the Ezine district in northwestern Turkey. The study aimed to determine the physicochemical properties of the soils in the vicinity of the cement plant, the concentrations of heavy metals, the spatial distribution of heavy metals, and their impact on the health of the local human population. Soil samples were collected from the cement plant in different directions (S,W, N, E, NE, SW) and at different distances (1, 3, 5, and 7km) from 0-10cm depth with three replicates. The soil samples were analyzed for texture, pH, electrical conductivity, lime, and heavy metals such as Cd, Co, Cu, Fe, Mn, Ni, Pb, and Zn. The soils had different textures (loam, sandy clay loam, loam, sandy loam), slightly alkaline pH, low lime content, and moderate organic matter content. Except for Cd and Pb, the average values of the other heavy metals (Co = 1.18 < 19 mg kg-1,Cr = 50.92 < 90 mg kg-1, Cu = 31.21 < 45 mg kg-1, Fe = 16,007 < 47,200 mg kg-1, Mn = 499.68 < 850 mg kg-1, Ni = 41.17 < 68 mg kg-1, Zn = 50.91 < 95 mg kg-1) in the soils were below the normal background level. The heavy metal contents of the soils in the study area are influenced by various sources (geological structure, agrochemicals used in agricultural activities, and vehicle traffic). The prevailing wind direction did not influence the local distribution of heavy metals in soils in the study area. The health risk assessment model studies showed that the hazard quotient values of less than 1 for adults and children indicate that the noncarcinogenic risks were insignificant. People exposed to heavy metals in the soils of the study area contaminated from various sources for a long time could be at carcinogenic risk. Since Cr and Pb exceed the acceptable risk range in children and Cr exceeds the acceptable risk range in adults, geochemical monitoring of soils should be conducted periodically by authorized institutions in the study area.

Elevated temperature induces contrasting transformation of exogenous copper to soil solution and solid phases in an arable soil

Heavy metal contamination of soils has been a global environmental issue over the past decades, threatening food security and human health. Understanding the migration and transformation of heavy metals in soils is critical for restoring an impaired environment and developing sustainable agriculture, particularly in the face of global warming. However, little effort has been devoted to investigating the impact of elevated temperatures on the migration and distribution of exogenous heavy metals in soils. This study experimented with a 180-day incubation at 15 °C, 30 °C, and 45 °C with an arable soil (Alfisol) of Huang-Huai-Hai River Basin, China, which was initially spiked with copper (Cu). A comparison of the results revealed that the percentage of soil water-soluble Cu doubled at 45 °C compared with 15 °C. The percentage of protein-like substances in dissolved organic matter (DOM) was the highest at 45 °C, suggesting that proteinaceous components play a more significant role in controlling the dissolution of Cu into DOM. Moreover, by sequential extraction and micro-X-ray fluorescence (μ-XRF), Cu was facilitatively transformed from exchangeable, and specifically adsorbed fractions, to iron (Fe)/manganese (Mn) oxides bound species by 7.75%23.63% with the elevation of temperature from 15 °C to 45 °C. The conversion of Cu speciation is attributed to the significant release of organic carbon from Fe/Mn oxides, especially the Mn oxide components, which are available for Cu binding. The findings of this work will provide an in-depth understanding of the fate of Cu in soils, which is fundamental for the risk assessment and remediation of Cu-polluted soils in the Huang-Huai-Hai River Basin under the context of global warming.

Enrichment Characteristics, Source Apportionment, and Risk Assessment of Heavy Metals in the Industrial and Mining Area of Northern Guangdong Province

In order to understand the heavy metal pollution of the industrial and mining area in northern Guangdong Province, topsoil samples (0-20 cm) from 209 sites in study area were collected, and the concentrations of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn were analyzed. The source and distribution characteristics of Cd, Cr, Hg, Ni, Pb, As, Cu, and Zn in soil samples were analyzed using the geographic information system (GIS) and principal component analysis (PCA), and the geo-accumulation index and potential ecological hazard index were used to evaluate their pollution status and ecological risk. The results showed that:① Except Ni, all seven heavy metal elements exceeded the national soil background value but were below the pollution risk screening value. The soil environment as a whole was relatively clean. ② The spatial distribution of heavy metals in soil differed. The contents of As and Pb showed northwest-southeast zonal distribution. The contents of Cd, Cu, Hg, and Zn generally decreased from the middle to the surrounding, which was consistent with the industrial and mining enterprise locations. However, the spatial distribution of Cr and Ni had no direct relationship with the location of pollution sources such as industrial enterprises. ③ The eight heavy metals could be identified as three principal components (PCs). PC1 (Cd, Cu, Pb, and Zn) was mainly affected by human activities such as lead-zinc deposit dressing, traffic emissions, and agricultural production. However, PC2 (Cr and Ni) was a natural source, mainly affected by soil parent material. In addition, PC3 (As and Hg) was mainly affected by industrial activities such as non-ferrous metal smelting and thermal power generation. ④ According to the geo-accumulation index method, the risk degree of the eight heavy metals was:Cd>As>Zn>Hg>Pb>Cu>Cr=Ni. The contents of Cr and Ni in soil were at a no-risk level; the contents of As, Cu, Hg, Pb, and Zn were at a low-risk level; and the content of Cd was at a high-risk level. Most potential ecological hazards for single elements in the study area were at a mild risk level. In contrast, a small proportion of the surface soils in areas of intense industrial activity were subject to substantial levels of heavy metal stress and require further attention.

Polypropylene microplastics affect the distribution and bioavailability of cadmium by changing soil components during soil aging.

Compared with the widespread and serious heavy metal contamination in soils, microplastic pollution has gained attention only recently. Little is known about how microplastics affect the distribution of heavy metals in soils, especially across soil components level. In this study, a 180-day soil aging experiment and soil density fractionation were performed to investigate the effect of polypropylene (PP) microplastics on the binding behavior of cadmium (Cd) to solid components, i.e. particulate organic matter, organo-mineral complexes (OMC), and mineral. Results showed addition of 2-10% microplastics in soils induced the decomposition of OMC fraction by 10.88-23.10%. Compared to the control, the content of dissolved organic carbon increased, and pH, humic substances, and soil organic matter decreased with microplastics. After 180d of aging, the content of Cd in OMC fraction increased by 17.92%, while microplastics made Cd contents decline by 10.01-19.75%. The impacts strongly depended on the dose and surface characteristic of microplastics. Overall, PP microplastics increased the concentration of bioavailable Cd in soils via decreasing soil retention of Cd by the OMC fraction. These findings based on the solid components level will provide a new perspective for understanding microplastics effects on soil systems and pollutants.

Accumulation and distribution of heavy metals in soil and food crops in the Pb–Zn mine environ. Case study: Region of Probištip, North Macedonia

The aim of the study was to investigate the exploration and distribution of various chemical elements in soils and vegetables from gardens in the region of Probištip, North Macedonia. This region was exposed to heavy metals pollution from Pb–Zn mining and flotation tailings landfill near the town of Probištip for 70 years. A total of 38 samples of various crops and vegetable products from 19 gardens were analyzed. The analyzes were carried out by ICP-AES (Al, Ba, Ca, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Ni, P, Pb, Sr, V, and Zn) and by ICP-MS (As, Cd, Co, Cr, and Pb). It was found that the content of some potentially toxic elements (As, Cd, Cu, Pb, and Zn) in the soil samples from the gardens, exceeded the target values. From these results, it is clear that the contamination of the soils in this area is due to mining activities and the distribution of flotation wastes from the nearby flotation dump. It was also found that the contaminated soils lead to elevated levels of these elements in some vegetables from the gardens, especially those near the Zletovska River and the flotation waste landfill, exceeding the nationally permissible food content.

Long-term wetland reclamation affects the accumulation and profile distribution of heavy metals in soils

Long-term wetland reclamation affects the accumulation and profile distribution of heavy metals in soils

Peculiarities of profile distribution of metals in soils of geochemically conjugated landscapes of Chelyabinsk city

The article discusses the results of soil-geochemical studies carried out on the territory of the Chelyabinsk urban district. The features of the profile distribution of pollutants within the landscape catena are established. The maximum concentrations of heavy metals are confined to the upper soil horizons of the eluvial position under forest vegetation. The soils of the superaquatic position under moist meadow and swamp vegetation are less polluted. The most polluted soil layer is located at a depth of 4-10 cm from the surface. This may be due to a decrease in heterogeneous emissions from the city’s metallurgical enterprises over the past 30 years.

Distribution of Heavy Metals in Soil of the Temporary Municipal Solid Waste Landfills in the City of Botosani, Romania

Distribution of Heavy Metals in Soil of the Temporary Municipal Solid Waste Landfills in the City of Botosani, Romania