Metal Concentrations In Soils Research Articles

Irrigation with water from Beni Haroun reservoir (Algeria) changed soil physicochemical properties and the availability of metallic trace elements in croplands

The Beni Haroun Dam (BHD), situated in the province of Mila, Algeria, stands as the largest dam within the country, facilitating the irrigation of approximately 40,000 ha of agricultural lands characterized by sub-humid and semi-arid climates. Over time, the water within this reservoir has experienced an escalation in contamination, primarily attributed to its role as a major recipient of diverse municipal and industrial effluents, both treated and untreated. Consequently, mounting apprehensions regarding the potential migration of pollutants to irrigated soils have surfaced. The primary aim of this investigation was to assess the levels of contamination by mineral elements and heavy metals present in agricultural soils irrigated by waters originating from BHD. A total of 48 soil samples were systematically collected from 12 distinct sites, comprising 10 irrigated areas and 2 control sites, each spanning depths of 0, 10, 20, and 30 cm. Then subjected to chemical characterization, including the total quantification of minerals (Ca2+, Mg2+, Na+, K+), and heavy metals (Cd2+, Cu2+, Zn2+, Pb2+, Cr3+ and Fe3+). as well as the determination of cation exchange capacity (CEC), exchangeable sodium percentage (ESP), sodium adsorption ratio (SAR) as well as soil texture. This study indicated that irrigating with dam waters increased the soil exchangeable cations in comparison to the control one: Ca2+ (21.99 ± 3.65 meq 100 g−1), Mg2+ (10.53 ± 1.94 meq 100 g−1), Na+ (10.08 ± 1.78 meq 100 g−1), K+ (2.81 ± 0.8 meq 100 g−1), and enhanced soil characteristics: CEC (25.2 ± 5.55), ESP (41.69 ± 11.21) and SAR (2.51 ± 0.43). In terms of percentage of enrichment, the mineral elements are classified as follows: Na+ > Ca2+ > K+ > Mg2+. The metal contents in irrigated soils were also higher but remained less than the recommended international limits. They are classified as follows: Fe3+ > Zn2+ > Pb2+ > Cr3+ > Cu2+ > Cd2+. Consequently, the soils under investigation are deemed susceptible to salinization, sodification, and contamination with prolonged irrigation. Such conditions pose potential risks to human health should vegetable crops absorb these metals. Therefore, it is recommended to implement adequate drainage measures, emphasizing surface drainage, and to conduct regular monitoring for the accumulation of salt and sodium.

Heavy metal concentrations in soil and ecological risk assessment in the vicinity of Tianzhu Industrial Park, Qinghai-Tibet Plateau

Industrial parks in China are centers of intensive chemical manufacturing and other industrial activities, often concentrated in relatively small areas. This concentration increases the risk of soil pollution both within the parks and in surrounding areas. The soils of the Tibetan Plateau, known for their high sensitivity to environmental changes, are particularly vulnerable to human activity. In this study, we examined the concentrations (mg/kg) of 10 metal elements (As, Cd, Cr, Cu, Hg, Mn, Ni, Pb, Se, and Zn) in soils at depths of 0–10 cm, 10–20 cm, and 20–30 cm from the surface at three distances (500 m, 1000 m, and 1500 m from the park boundary) on the east, south, west, and north sides of the Tianzhu Industrial Park on the Qinghai-Tibet Plateau. The concentrations of As, Cr, Mn, and Pb were close to the standard reference values for the Qinghai-Tibet Plateau, while Cu, Ni, Se, and Zn levels were found to be 1.6-2.2 times higher than the reference values. Cd and Hg concentrations were particularly concerning, at 8.0 and 6.5 times higher than reference values, respectively. The potential ecological risk indexes indicated persistent risk levels for Cd and Se across various directions and distances. Variations in soil depth and direction were observed for the concentrations of As, Cd, Hg, Pb, Se, and Zn, underscoring the need for regular or long-term monitoring. Cd, in particular, presents a significant hazard due to its high concentration and its propensity for uptake by plants in the study area.

Advanced Low-Cost Technology for Assessing Metal Accumulation in the Body of a Metropolitan Resident Based on a Neural Network Model

This study is devoted to creating a neural network technology for assessing metal accumulation in the body of a metropolis resident with short-term and long-term intake from anthropogenic sources. Direct assessment of metal retention in the human body is virtually impossible due to the many internal mechanisms that ensure the kinetics of metals and the wide variety of organs, tissues, cellular structures, and secretions that ensure their functional redistribution, transport, and cumulation. We have developed an intelligent multi-neural network model capable of calculating the content of metals in the human body based on data on their environmental content. The model is two interconnected neural networks trained on actual measurement data. Since metals enter the body from the environment, the predictors of the model are metal content in drinking water and soil. In this case, water characterizes the short-term impact on the organism, and drinking water, combined with metal contents in soil, is a depository medium that accumulates metals from anthropogenic sources—the long-term impact. In addition, human physiological characteristics are taken into account in the calculations. Each period of exposure is taken into account by its neural network. Two variants of the model are proposed: open loop, where the calculation is performed by each neural network separately, and closed loop, where neural networks work together. The model built in this way was trained and tested on the data of real laboratory studies of 242 people living in different districts of Kazan. As a result, the accuracy of the neural network block for calculating long-term impact was 90% and higher, and the accuracy of the block for calculating short-term impact was 92% and higher. The closed double-loop model showed an accuracy of at least 96%. Conclusions: Our proposed method of assessing and quantifying metal accumulation in the body has high accuracy and reliability. It does not require expensive laboratory tests and allows quantifying the body’s metal accumulation content based on readily available information. The calculation results can be used as a tool for clinical diagnostics and operational and planned management to reduce the levels of polymetallic contamination in urban areas.

Assessment of the Environmental Impact of Fly Ash on the Concentration of Heavy Metals around Cement Company of Northern Nigeria

This study assessed the impact of Coal Fly Ash on the concentration of Heavy metals in water, soil, and vegetables (moringa and spinach) in the environment of Cement Company of Northern Nigeria. The samples collected were digested, and analysed for heavy metals concentration using Atomic Absorption Spectroscopy. The concentrations of heavy metals obtained in water samples were higher than the WHO/SON permissible limit, except for Cu and Zn which are below the standard limits. The average concentration of Pb, Mn, Cd, and Ni in all plant samples was higher than the permissible limit, except Cd in spinach sample. The roots of the spinach accumulate higher concentrations of heavy metals than the leaves and stem, while leaves of moringa accumulate higher than the roots and stem. The concentration of heavy metals in soil sample was below the WHO limit. Comparatively the plants samples have the highest concentrations of heavy metals than the water and soil samples. The coal fly ash from the Cement Company must have contributed to the significant concentration of Heavy metals in the environment making the water and plants from the study area unfit for human and animal consumption.

Pollution assessment, ecological risk and source identification of heavy metals in paddy soils and rice grains from Salem, South India

The present study investigated concentrations of metals (Cu, Zn, Fe, Mn, Ni, Pb, and Cd) in paddy soils and rice tissues of nine different widely used indica rice varieties in Salem district, India. The order of DTPA soil available metal contents (mg kg-1) were Fe (33.50) > Mn (8.86) > Cu (2.58) > Pb (1.99) > Zn (1.67) > Ni (1.48) > Cd (0.13). Pollution load index (PLI) levels for Cd (1.28) were ‘moderately polluted’, contamination factor (CF) and enrichment factor (EF) values for all metals showed ‘medium contamination’ and ‘less enrichment’ except for Cu and Pb. Ecological risk factor (ERF) and potential ecological risk index (PRI) values of Cd (31.94 and 287.50) showed ‘moderate risk’ and ‘strong ecological risk’. Bio-accumulation factor (BAF) levels of Cd (48.12) and Pb (27.89) are classified as ‘high concentrators’. Translocation factor (TF) values of Pb (2.9), Cd (2.5) and Ni (1.7) were greater than one for roots to plants. Children had higher target hazard quotient (THQ) and hazard index (HI) values for Cd, Pb and Ni than adults. Principal component analysis (PCA) revealed with all parameters that they fell within the two primary factors 1 and 2, with an eigenvalue of 4.69 (33.52% variation) and 3.73 (26.66% variation), respectively. However, cluster analysis (CA) revealed three distinct groups between the metals studied. Although the soil metal contents were within the permissible levels, the grain Cd (6.07 mg kg-1), Pb (56.20 mg kg-1), and Fe (116.11 mg kg-1) contents in all the rice varieties exceeded the prescribed limits of 0.4, 0.2, and 15 mg kg-1, respectively. Our findings will provide important data for metal enrichment in soils to implement more effective measures to reduce the contamination of metals in paddy fields.

Hyperspectral Inversion of Soil Cu Content in Agricultural Land Based on Continuous Wavelet Transform and Stacking Ensemble Learning

Heavy metal pollution in agricultural land poses significant threats to both the ecological environment and human health. Therefore, the rapid and accurate prediction of heavy metal content in agricultural soil is crucial for environmental protection and soil remediation. Acknowledging the limitations of traditional single linear or nonlinear machine learning models in terms of prediction accuracy, this study developed an ensemble learning model that integrates multiple linear or nonlinear learning models with a random forest (RF) model to improve both the prediction accuracy and reliability. In this study, we selected a typical copper (Cu) polluted area in the Pearl River Delta of Guangdong Province as the research site and collected Cu content data and indoor soil reflectance spectral data from 269 surface soil samples. First, the soil spectral data were preprocessed using Savitzky–Golay (SG) smoothing, multiplicative scattering correction (MSC), and continuous wavelet transform (CWT) to reduce noise interference. Next, principal components analysis (PCA) was employed to reduce the dimensionality of the preprocessed spectral data, eliminating redundant features and lowering the computational complexity. Finally, based on the dimensionality-reduced data and Cu content, we established a stacked ensemble learning model, where the base models included SVR, PLSR, BPNN, and XGBoost, with RF serving as the meta-model to estimate the soil heavy metal content. To evaluate the performance of the stacking model, we compared its prediction accuracy with that of individual models. The results indicate that, compared to the traditional machine learning models, the prediction accuracy of the stacking model was superior (R2 = 0.77; RMSE = 7.65 mg/kg; RPD = 2.29). This suggests that the integrated algorithm demonstrates a greater robustness and generalization capability. This study presents a method to improve soil heavy metal content estimation using hyperspectral technology, ensuring a robust model that supports policymakers in making informed decisions about land use, agriculture, and environmental protection.

Contamination and health risk assessment of potentially toxic elements in rice (Oryza sativa) and soil from Ashanti Region.

Anthropogenic activities release potentially toxic elements into the environment, which contaminate the food chain. The main objective of this research was to analyze the concentrations of As, Cd, Cr, Hg, and Pb in rice grains and soils, establish their correlation and transfer factors between soil and rice grains as well as evaluate their human health risk from consumption of rice cultivated in the Asante Akim area. The levels of As, Cd, Cr, Hg, and Pb in soil and rice samples were assayed using an Agilent 7700 Series inductively coupled plasma-mass spectrophotometer. The mean heavy metal content in soil was 7.5, 0.52, 0.47, 1.30, and 8.69mg/kg for As, Cd, Cr, Hg, and Pb, respectively. Mean levels of the potentially toxic elements in rice were 0.082, 0.27, 0.48, 0.028, and 0.14mg/kg for As, Cd, Cr, Hg, and Pb, respectively. Soil pollution indices showed that the soils were unpolluted with the potentially toxic elements studied. The concentrations of the potentially toxic elements in rice were below the maximum allowable concentration (MAC) recommended by the Codex Alimentary Commission except Cd which was marginally higher than the MAC. Dietary exposure to the elements to consumers was assessed by comparing the estimated daily intake (EDI) to the provisional tolerable daily intake (PTDI). The estimated daily intake values for As, Cd, Cr, Hg, and Pb were 1.45 × 10-4, 4.8 × 10-4, 8.5 × 10-4, 4.95 × 10-5, and 2.4 × 10-4, respectively. The HQ for all the potentially toxic elements was less than the permissible value of 1, suggesting that the consumption of rice from the study area constitutes no potential non-carcinogenic health risk to the population. This study is unique because the risk is evaluated from rice that is directly consumed, and this gives a clearer picture of the risk to humans. Regular monitoring studies should be conducted to ascertain the levels of heavy metals in rice cultivated in the area since heavy metals can accumulate and the concentrations could increase to toxic levels with time.

Assessment of heavy metals concentration and health hazard indices in soil and plants from Kokona Local Government Area of Nasarawa State, Nigeria

Human dependence, on the plants grown on soil and the threat posed by contaminated soil to the ecosystem and general public has become a source of concern. The health risks caused by heavy metals concentration to the study area were evaluated. Fifteen (15) plant samples and soil samples each from the study area were collected and analyzed using an Energy Dispersive X-ray Fluorescence Spectroscopy (EDXRF) for Lead (Pb), Cadmium (Cd), Chromium (Cr), Nickel (Ni), Copper (Cu), and Zinc (Zn). The Measured concentrations of these heavy metals were in the order of Cd>Ni>Cu>Zn>Pb>Cr for the plant samples and Cr>Cd>Ni>Cu>Pb for soil samples with Cd and Cr as the highest contributors to cancer risk in term of the carcinogenic risk estimate. The Health Hazard Index value for all pathways were found to be 7.34 x 10-1 making non-carcinogenic risk component less significant to the adult population and in case of children, the Hazard Index value was 1.21, a value greater than unity (1), which present a severe non-carcinogenic risk component to children living in the study area. The carcinogenic risk was found to be 8.68 x 10-6 implying that 1 person in every 5882 adults may be affected and 1 in 2725 children may be affected (9.6 x 10-5) These carcinogenic risk values were both higher than acceptable values.

Exopolysaccharide-Producing Bacteria Regulate Soil Aggregates and Bacterial Communities to Inhibit the Uptake of Cadmium and Lead by Lettuce

The accumulation of heavy metals in the soil not only causes serious damage to the soil ecosystem, but also threatens human health through the food chain. Exopolysaccharides have the functions of adsorbing and chelating heavy metals and reducing their bioavailability in the soil. In our study, exopolysaccharide-producing bacteria with a high efficiency in adsorbing cadmium (Cd) and lead (Pb) were screened from heavy metal-contaminated farmland. Through pot experiments, the influence of functional strains on the size distribution, heavy metal content, and bacterial community structure of soil aggregates in lettuce was studied using high-throughput sequencing technology. The results show that 11 strains secreting exopolysaccharides were initially screened from heavy metal-contaminated soil. Among them, strain Z23 had a removal rate of 88.6% for Cd and 93.2% for Pb. The rate at which Cd was removed by strain Z39 was 92.3%, and the rate at which Pb was removed was 94.4%. Both strains belong to Bacillus sp. Strains Z23 and Z39 induced the formation of Fe2Pb(PO4)2, Cd2(PO4)2, and Pb2O3 in the solution. The pot experiments showed that strains Z23 and Z39 increased (19.1~23.9%) the dry weight and antioxidant enzyme activity of lettuce roots and leaves, while reducing (40.1~61.7%) the content of Cd and Pb. Strains Z23 and Z39 increased the proportion of microaggregates (<0.25 mm) and the content of exopolysaccharides in rhizosphere soil and reduced (38.4–59.7%) the contents of available Cd and Pb in microaggregates, thus inhibiting the absorption of heavy metals by lettuce. In addition, the exopolysaccharide content and the bacterial community associated with heavy metal resistance and nitrogen (N) cycling (Patescibacteria, Saccharimonadales, Microvirga, and Pseudomonas) in microaggregates were key factors affecting the available heavy metal content in soil. These results show that the exopolysaccharide-producing bacteria Z23 and Z39 reduced the absorption of Cd and Pb by lettuce tissues, thus providing strain resources for the safe utilization of soils that exceed heavy metal standards for farmland and for reducing the heavy metal content in vegetables.

Assessment of the Interaction between Pesticide Applications and Heavy Metals Content in Soils and Plants

Assessment of the Interaction between Pesticide Applications and Heavy Metals Content in Soils and Plants

Investigating the Spatial Patterns of Heavy Metals in Topsoil and Asthma in the Western Salt Lake Valley, Utah

Mining activities, particularly in large excavations like the Bingham Canyon Copper Mine in Utah, have been increasingly linked to respiratory conditions due to heavy-metal-enriched waste and dust. Operating continuously since 1906, the Bingham Canyon Copper Mine contributes 4.4% of the Salt Lake Valley PM2.5 pollution. However, the extent of its contributions to larger-sized particulate matter (PM10) dust, soil and water contamination, and human health impacts is largely unknown. Aerosol optical depth data from Sentinel-2 imagery revealed discernible dust clouds downwind of the mine and smelter on non-prevailing-wind days, suggesting potential heavy metal dispersion from this fugitive dust and subsequent deposition to nearby surface soils. Our analysis of topsoils from across the western Salt Lake Valley found mean arsenic, copper, lead, and zinc concentrations to be well above global background concentrations. Also, the minimum values for arsenic and maximum values for lead were well above the US EPA regional screening levels for residential soils. Thus, arsenic is the metal of greatest concern for impacts on human health. Elevated concentrations of all metals were most notable near the mine, smelter, and tailings pond. Our study linked these elevated heavy metal levels to regional asthma outcomes through cluster analysis and distance-related comparison tests. Significant clusters of high asthma rates were observed in regions with elevated topsoil heavy metal concentrations, impacting both low- and high-income neighborhoods. The findings of this preliminary study suggest that the mine, smelter, and recent construction activities, especially on lands reclaimed from former tailings ponds, could be contributing to atmospheric dust containing high levels of heavy metals and exacerbating asthma outcomes for residents. However, the methods used in the study with aggregated health outcome data cannot determine causal links between the heavy metal contents of soil and health outcomes; they can only point to potential links and a need for further investigation. Such further investigation should involve individual-level data and control for potential confounding factors, such as socioeconomic status, access to healthcare, and lifestyle factors, to isolate the effect of metal exposures on asthma outcomes. This study focused on atmospheric deposition as a source of heavy metal enrichment of topsoil. However, future research is also essential to assess levels of heavy metals in subsoil parent materials and local surface and groundwaters to be able to assess the links between the sources or methods of soil contamination and health outcomes.

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.

Utilizing a medicinal plant and soil assays for heavy metal pollution assessment and its impacts in a Turkish Industrial Zone

Due to the worldwide growth in population, agricultural and industrial activities are expanding quickly, which pollutes the air, water, and soil and leads to the buildup of potentially hazardous substances in medicinal plants. The current study sought to determine the concentrations of various metals in Silybum marianum plants and soils in order to highlight the level of pollution in a Turkish Organized Industrial Zone in Dilovasi District, Kocaeli, and to investigate the effects of these heavy metals on plants. In order to determine the concentrations of elements evaluated within the scope of this study inductively coupled plasma optical emission spectroscopy was employed, due to the benefits of ICP that provides few or no organic molecules, few ionization interferences, as well as the ability to analyze many elements sequentially. Furthermore, in order to evaluate elemental analysis in terms of nutritional values, risk assessments using RDA, EDI, THQ, and HI parameters were conducted. The value of heavy metals in co-located soil samples is relatively high. However, except for Co, Mn, and Ni, it has stayed within the World Health Organization’s permitted limits. The evaluation of the co-located soil samples found that the highest contents (mg kg−1) of Al, Ca, Cd, Cr, Cu, Fe, K, Mn, Na, Ni, Pb, and Zn, were recorded as 7825.10, 4365.86, 4768.59, 2.50, 30.45, 38.49, 8352.00, 17452.26, 1495.82, 1495.82, 163.53, 1452.23, 28.67, 136.55 and 125.45, respectively, belonging to Location 1. These findings are in accordance with the Industrial Status Report since the place specified as Location 1 in the current study is characterized by its pronounced industrial activity and the robust electrical plant station with an industrial facility for generating electric power. Furthermore, the hazard index, the estimated daily intake and target hazard quotient for potentially harmful components and recommended daily allowance values for mineral nutrients were computed. Therefore, even though mineral nutritional values in some areas were found to be higher than Buyukada control location, this should be ignored. Consequently, this study warns against using S. marianum plants as food or medicine collected from current regions. As a result, ongoing inspection is necessary to prevent an excessive buildup of metals in the area and other places with similar human life-related features.

Phytoremediation of contaminated urban soils spiked with heavy metals

Urban environments worldwide face toxic heavy metal pollution originating from industrial discharge, municipal waste disposal, vehicular emissions, and atmospheric deposition. Kazakhstan, experiencing accelerated economic growth and extensive mining activities, contends with widespread heavy metal contamination in its soil-plant-air-water ecosystems. This study explores the potential of hyperaccumulating plants for phytoremediation in urban soils of Kazakhstan contaminated with Pb, Cd, and Co. Twelve plant species, including Korean Mint (Lamiaceae), Ornamental Cabbage (Brassica oleracea), Ageratum (Ageratum houstonianum), Coneflower (Echinacea purpurea), Amaranth (Amaranthus Perfect and Amaranthus Emerald), Fescue (Festuca glauca), Burning Bush (Kochia scoparia), Marigold (Tagetes patula nana), White Cabbage (Brassica-Cavolo cappuccino BIANKO), Tepary Bean (Phaseolus acutifolius), and Rapeseed (Brassica napus), were evaluated for growth and biomass production in urban soils spiked with two maximum permissible addition (MPA) treatments of Pb, Co, and Cd. The selected plants demonstrated varied responses to heavy metal stress, with Marigold (8.4 g shoot biomass/plant), Korean mint (10.5 g shoot biomass/plant), Rapeseed (19.9 g/shoot biomass), and Tepary bean (25.9 g shoot biomass/plant) exhibiting resilience or tolerance to Pb, Co, and Cd stresses. The results highlight the significant potential of these plants for efficient phytoremediation, showcasing their unique abilities to absorb and accumulate specific metals. Marigold, particularly, displayed noteworthy Pb accumulation (40.3 mg/kg biomass), resulting in reduced residual Pb concentrations in the soil (74.7 mg/kg). Conversely, White cabbage and Amaranth showed limited efficiency in Cd extraction, while Rapeseed and Tepary bean emerged as promising candidates for Cd phytoremediation. This study emphasizes the critical role of tailored plant species selection in designing effective phytoremediation strategies for specific metal-contaminated urban sites. A comprehensive understanding of the dynamics of metal accumulation and residual concentrations is crucial for the development of sustainable and efficient environmental remediation approaches. Further research is warranted to explore the long-term effects of different plant species on soil metal concentrations, refining and optimizing phytoremediation methods for urban soils grappling with toxic heavy metal contamination.

Vertical distribution and migration of heavy metals in soil of green stormwater infrastructure receiving roof runoff

In order to achieve effective management of urban stormwater runoff, green stormwater infrastructure (GSI) has been widely used worldwide. However, the problem of heavy metal contamination in GSI soils has gradually become a limiting factor for their development. In this paper, concentrations of 6 heavy metals were detected in soils from 0 to 80 cm depth in the GSI receiving roof runoff. The total concentration of the 6 heavy metals in topsoil of the GSI was 395 mg·kg−1, which was significantly higher than that of the control site (p < 0.01). Vertically, heavy metal concentrations in GSI soils decreased with depth. The concentrations of As, Cr, Cu, Pb and Zn in the soils at different depths (0–80 cm) of GSI were higher than those in the soils at the corresponding depths at the control site. This suggests that heavy metals may have migrated below 80 cm. The decrease in Zn/Cu ratios with depth indicated that Zn has a higher initial concentration and more of Zn accumulated in upper layer soil than Cu. Finally, we simulated the vertical migration of dissolved heavy metals in GSI soils by the Hydrus-1D model. Heavy metal concentrations in runoff and soil particle size distributions were examined, while adsorption isotherm experiments were conducted to determine input parameters for the model. The simulation results showed that only dissolved Zn would accumulate in the top soil layer. A short time of infiltration (<60 min) may have little effect on the profile shape of dissolved heavy metal levels in the soil. Substantial increases in infiltration may result in the migration of dissolved heavy metals to deeper depths in the soil.

Stable isotopic evidence of cadmium enrichment in soils of black shale distribution areas

Black shale-derived soils exhibit significant heavy metal enrichment, notably cadmium (Cd) enrichment. This study pioneered the reporting of δ114/110Cd isotopic values within a black shale-soil system, offering novel insights into the geochemical behaviors and enrichment mechanisms of Cd during soil formation processes influenced by weathering. Systematic rock‒soil sampling was conducted on the lower Cambrian Hetang Formation in western Zhejiang, China, which is characterized by Cd-rich black shale. Employing analytical methods, including principal component analysis and multiple linear regression, we investigated the factors influencing heavy metal content in soil, such as element dissolution during weathering, soil pH, and the presence of iron-manganese oxides, sulfides, organic matter, and clay minerals. Our findings revealed a compositional range of δ114/110Cd in black shale (1.93‰–3.31‰) contrasting with that in adjacent soils (0.31‰–1.82‰), illustrating significant Cd isotopic fractionation during weathering, where heavier Cd isotopes are preferentially leached, and lighter isotopes are enriched in the soil in association with iron-manganese oxides. This research not only deepens the understanding of Cd enrichment mechanisms within the rock‒soil system against a black shale geological background but also elucidates the formation processes of soil Cd pollution in areas with a high geochemical background.

Pollution Characteristics and Risk Assessment of Heavy Metals in the Soil of a Municipal Solid Waste Landfill Site

ABSTRACT With the excavation of landfill sites, the disposal and reduction of organic-rich soils with high proportions of heavy metals have become urgent issues. This study focuses on the pollution characteristics and ecological risks associated with heavy metals in the humus soil of a municipal solid waste (MSW) landfill. The results indicate that the concentrations of heavy metals in the humus soil followed the sequence of Cu > Zn > Cr > Pb > Ni > As > Cd > Hg, and Cu and Cd exhibited the highest exceedance multiples. Except for Cr, the concentrations of the heavy metals in the humus soil were higher than those in combustible components, with a strong Hg correlation. Heavy metal forms indicate varying degrees of mobility and stability; Cr, As, Hg, and Pb were stable, while Ni, Cd, Cu, and Zn showed higher mobility. The results of the principal component analysis reveal that heavy metals primarily originate from industrial and agricultural waste. Finally, the geoaccumulation index of the metals indicated that Cu, Zn, Cd, and Pb exhibited severe contamination. Most importantly, Cd posed the greatest environmental risk as it has the highest effective content, bioavailability, and mobility. This study provides a scientific foundation for mitigating heavy metal pollution in the humus soil of landfill sites.

Zinc Accumulation Pattern in Native Cortaderia nitida in High Andes (Ecuador) and Potential for Zinc Phytoremediation in Soil

The aim of this work was to determine the content of heavy metals in soil and, for the first time, in wild Cortaderia nitida, and to discuss its potential as a metal phytoremediator plant. We sampled sediments (bulk and rhizosphere) and C. nitida (roots and shoots) in three nearby spots with different land uses (urban, industrialized and agricultural) along the Chibunga river basin (Ecuador). We analyzed the physico-chemical parameters in soil and heavy metal contents in soil and plants. The agricultural sediments showed the highest conductivity and redox potential, but the lowest pH. Among all the metals analyzed in soil and plants, we only found significant values of Zn and Fe. We observed clear differences in patterns of Zn distribution throughout soil and plants among the three areas sampled, thus suggesting that soil properties played an important role in Zn compartmentalization. Also, C. nitida demonstrated effective Zn translocation from roots to shoots, especially in farmlands (translocation factors between 1.64 and 2.51). Together with the results obtained for other Cortaderia species in metal-polluted areas, this study proposes C. nitida as a candidate to further study its metal phytoremediation potential and encourages this research in heavy metal-enriched soils.

Portable X‐ray fluorescence spectrometry accurately measures metal concentrations in aqueous Mehlich III soil extraction solutions

AbstractAccurate measurement of metal concentrations in soil and water is vital for healthy crop production and decision making for environmental surveys. While there are a multitude of laboratory‐based soil analysis methods, such as inductively coupled plasma‐optical emission spectroscopy (ICP‐OES), flame emission spectrometry, and atomic absorption spectroscopy, most are time and resource intensive. Additionally, there is a lack of information for rapid analysis of elements for aqueous soil extractions. The goal of this research is to establish elemental correlations between portable X‐ray fluorescence (pXRF) measurements of Mehlich III soil extractions and traditional elemental measurements via ICP‐OES. We hypothesize that certain metals can be accurately measured in aqueous soil extraction solutions by pXRF to the same degree as they are measured by ICP‐OES. To test this hypothesis, Mehlich III and 2% nitric acid solutions with known elemental concentrations were analyzed via ICP‐OES and pXRF. Soil samples extracted using Mehlich III were compared between ICP‐OES and pXRF to verify correlations. High correlations were found for As, Ca, Cd, Cr, Cu, Fe, Mn, Mo, Ni, Pb, Se, V, and Zn in both the Mehlich III and 2% nitric acid solutions at concentrations between 5 and 85 mg L−1. P, S, and Si did not show high correlations at concentrations &lt;100 mg L−1. These results indicate that between 5 and 85 mg L−1, pXRF analysis of aqueous solutions and soil extractions is a reliable technique; however, at low concentrations (i.e., &lt;5 mg L−1 for metals and &lt;100 mg L−1 for P and S), pXRF is not well suited.

Assessing soil remediation effect of Cr and Pb based on bioavailability using DGT, BCR and standardized determination method

In the field of soil remediation, the importance of bioavailability of pollutants has not received adequate attention, leading to the excessive application of remediation measures. Therefore, to ensure the safe use of farmland soil, a scientific method is needed to assess labile contaminants and their translocation in plants. To evaluate soil remediation effect based on bioavailability, the concentrations of these heavy metals in soil were analyzed using by the method for total metal content, the Community Bureau of Reference (BCR) extraction, and the diffusive gradients in thin films (DGT) technique. The results reveal that the correlation coefficients between metal concentrations measured by DGT and those accumulated in rice grains are the highest (Cr-R2 = 0.8966, Pb-R2 = 0.9045). However, the capability of method for total metal content to evaluate the remediation effect of heavy metals is very limited. In contrast, although Cr and Pb measured by BCR show a high correlation with HMs in rice plants, the method still falls short in precisely assessing bioavailability. Significantly, DGT proves to be more effective, successfully distinguishing the remediation effects of different treatments. Generally, DGT offers a more accurate and simpler assessment method, underscoring its practical significance for monitoring soil remediation and environmental management.