Metals In Soils Research Articles

Comprehensive Assessment of Heavy Metal Contamination in Soil-Plant Systems and Health Risks from Wastewater-Irrigated Vegetables

A research study examined the origins, human health impacts, and risks associated with pollutants in vegetables grown in soil irrigated with wastewater. The study analyzed 164 samples from water sources, irrigated soil, and harvested vegetables for eight heavy metals (Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Zn) using atomic absorption spectrophotometry. The focus was on the potential health effects of consuming heavy metal-contaminated vegetables grown in wastewater-irrigated soil. The findings revealed significant accumulation of heavy metals in soil and plants from Mianwali, Pakistan, posing potential health risks to consumers. When compared to vegetables produced with freshwater irrigation, the concentration levels of heavy metals in the soil irrigated with untreated wastewater were significantly greater (P≤0.001) and above the recommended limits set by the World Health Organization (WHO). The results showed that heavy metals in the soil had significantly increased, and crops had subsequently absorbed these metals. Produce raised in soil watered with wastewater showed higher levels of heavy metals than the US Environmental Protection Agency (EPA) and the WHO recommended. Among the veggies, lead (Pb) and cadmium (Cd) were found to have higher Hazardous Quotient Indices (HRIs) than one. This indicates that both adults and children may have been exposed to dangerous levels of these metals. Additionally, for Brassica oleracea, Raphanus sativus, and Spinacia oleracea, nickel (Ni) surpassed HRIs larger than 1, indicating a significant health risk connected to these veggies' ingestion.

Evaluation and risk assessment of heavy metals in wetland soil in the University of Lagos

A study was conducted to evaluate the concentration of heavy metals, and the physicochemical and microbiological properties of wetland soils at the University of Lagos. Soil samples were randomly collected from the Faculty of Science (FSC), Lagoon Front, and Distance Learning Institute areas at depths of 5 cm, 10 cm, 15 cm, and 20 cm using a soil auger. The samples were stored in sterile nylon bags, appropriately labelled, and transported to the University of Lagos Central Research Laboratory for chemical analysis. The physicochemical characteristics measured included soil pH, determined using a pH meter, and moisture content, assessed through the oven-drying method. Heavy metal concentrations were analyzed using an Atomic Absorption Spectrophotometer. Microbial population diversity was examined using the disc diffusion method. Statistical analysis was performed using SPSS version 20, and mean values were evaluated using Tukey’s multiple comparison test at a probability level of P < 0.05. The results revealed that soil pH ranged from 7.20 to 8.81, with the highest value (8.81) recorded near the Faculty of Science (FSC-3). Eight heavy metals, including Pb, Ni, Cr, Cd, Fe, Cu, Mn, and Zn, were analyzed. Lead concentrations ranged from 0.02 to 0.29 ppm, followed by nickel, which ranged from 0.01 to 0.13 ppm. Chromium ranged from 0.0 to 0.25 ppm, cadmium from 0.03 to 0.08 ppm, iron from 1.02 to 2.96 ppm, copper from 3.31 to 4.60 ppm, manganese from 3.31 to 5.16 ppm, and zinc from 1.67 to 9.17 ppm. Lead and zinc concentrations were found to be below the permissible limit at all locations, while chromium and cadmium were within permissible limits. However, Zn, Mn, Cu, Fe, and Ni exceeded the permissible limits. Correlation analysis revealed a significant correlation (P < 0.05) between Pb and Zn, likely due to effluents from human waste and seepage from nearby dumpsites into the lagoon, streams, or beaches. The isolated microbial flora included three bacterial genera, Bacillus megaterium, Bacillus spp, and Enterobacter spp, as well as four fungal genera, Aspergillus, Penicillium, Aspergillus flavus, and Fusarium. Bacterial counts were lower than fungal counts in polluted soils, likely due to the nutrient status of the soil. The isolates were found to be tolerant to slightly alkaline pH and heavy metal pollutants, with microbial variation attributed to the impact of pH and heavy metals on the microbial population.

Assessment of Heavy Metals in Tea Plantation Soil and Their Uptake by Tieguanyin Tea Leaves and Potential Health Risk Assessment in Anxi County in Southeast China

Evaluating heavy metal pollution in tea plantation soil and conducting potential health risk assessments are crucial for ensuring the safety of tea consumers. However, soil heavy metal pollution levels and dietary exposure risk remain poorly understood, and there is no consensus on how soil physicochemical properties affect heavy metal concentrations. In this study, seventy-three soil samples and corresponding tea leaves from main tea-producing regions in Anxi County were analyzed for arsenic (As), chromium (Cr), lead (Pb) and copper (Cu) concentrations. The results showed that mean concentrations of As, Cr, Cu and Pb in the soil did not exceed respective risk screening values in China (GB 15618-2018). The concentrations of As, Cr, Cu and Pb in the tea leaves were within limiting values of the Chinese National Food Safety Standard, and the bioaccumulation factor of heavy metals in descending order was Cu > Pb > As > Cr. The hazard index values of heavy metals indicated no potential human health risk. Soil pH, EAl, EA and AP were the main controlling factors for heavy metal in soil and tea leaves. Cu and Pb concentrations in tea leaves were positively correlated with soil Cu and Pb concentrations. These results provide a scientific basis for effective monitoring and management in tea plantations and for controlling potential risks in tea leaves.

Heavy metals in roadside soil along an expressway connecting two megacities in China: Accumulation characteristics, sources and influencing factors.

Transportation is widely recognized as a significant contributor to heavy metal (HM) pollution in roadside soils. A better understanding of HM pollution in soils near expressways is crucial, particularly given the rapid expansion of expressway transportation in China in recent years. In this study, 329 roadside topsoil samples were collected along the Beijing-Tianjin Expressway, which connects two megacities in China. Chemical analysis showed that HM concentrations in the soil samples were generally below national limits. The mean pollution index (Pi) values for As, Cr, Cu, Ni, Pb, and Zn ranged from 0.94 to 1.01, while Cd and Hg exhibited slightly higher mean Pi values of 1.19 and 1.13, respectively. The Nemerow integrated pollution index values for all samples ranged from 0.71 to 4.97, with a mean of 1.26. This suggests a slight enrichment of HM above natural background levels, especially for Cd and Hg. Source apportionment using positive matrix factorization revealed that natural sources contributed the most to soil HMs (64.51 %), followed by agricultural sources (19.15 %), traffic sources (9.77 %), and industrial sources (6.57 %). The Shapley additive explanation analysis, based on the random forest model, identified soil organic carbon, deep soil HM content, altitude, total soil K2O, urbanization composite impact index, and total soil P as primary influencing factors. This indicates that the impact of transportation on roadside soils along the Beijing-Tianjin Expressway is currently relatively limited. The prominent influence of soil properties and altitude underscored the importance of "transport" and "receptor" in the soil HMs accumulation process at the local scale. These findings provide critical data and a scientific basis for decision-makers to develop policies for expressway design and roadside soil protection.

Arsenic and Heavy Metals in Soils and Plants near Sulfide Mines: Implications for Phytoremediation and Phytomanagement.

The accumulation of heavy metals (i.e., As, Cu, Ni, Pb, and Zn) in soils and native plant species near copper, nickel, and pyrite mines in Vietnam was assessed. The highest soil As, Cu, Ni, Pb, and Zn concentrations recorded in mine soils were 42.3, 1570, 9870, 128, and 462 mg/kg, and those in agricultural soils were 11.4, 453, 94.9, 34.4, and 147 mg/kg, respectively. Pollution index (PI) values indicated heavy pollution (PI = 3.99-13.0) for mine soils, and unpolluted to severely polluted (PI = 0.65-2.84) for agricultural soils. Soil enrichment factors had a wide range, from minimal to extreme enrichment of heavy metals (EF = 0.03-91.4). Arsenic minerals may be the main source of high As concentrations in sulfide mines. The As, Cu, Ni, Pb, and Zn concentrations of 20 native plant species near three mines were in the ranges of 0.05-1150, 3.17-123, 0.47-291, 0.08-6.34, and 6.87-168 mg/kg (dry weight, DW), respectively. Based on the recorded hyperaccumulation levels (1150 mg/kg, DW), bioaccumulation factors (BAF = 2.4-90.0), biomass, and rapid growth, Pteris vittata L. is considered a promising plant for phytoextraction of As in soils. Bidens pilosa L. has potential for phytostabilization of sulfide-bearing soils, given its low concentrations of heavy metals in plant shoots, BAF values of <1, high biomass, and wide distribution. Integrated phytoremediation and phytomanagement are applicable to metal-contaminated soils. Phytomining, energy crops, and vegetation cover should be investigated for the phytomanagement of metal-contaminated soils in mining areas.

Unveiling heavy metal(loid) contamination and migration at an abandoned smelting site: Integrated geophysical and hydrological analyse

The heavy metal contamination at abandoned smelting sites is receiving increasing attention. This study focuses on an abandoned lead–zinc smelting site and uses several methods (such as soil sampling, geophysical exploration, and groundwater monitoring) to systematically investigate the contamination characteristics, distribution patterns, and migration mechanisms of heavy metal(loid) in soil and groundwater. A geological structure model of the study area was established through drilling data and geophysical techniques (Ground penetrating radar (GPR) and Electrical resistivity tomography (ERT)), revealing the relationships among soil resistivity, electromagnetic wave reflection characteristics, and geological structure. This study revealed that heavy metal contamination in soil was concentrated mainly northwest of the site and was closely related to historical smelting activities. The presence of heavy metal(loid)s in groundwater had a complex correlation with soil physicochemical properties and environmental elements, and its distribution was influenced by both hydrogeological conditions and soil properties. This study also investigated the effects of the soil water content (SWC) and soil hydraulic conductivity (Ks) on heavy metal(loid)s migration and reported that high SWC and Ks contribute to the dissolution and migration of heavy metals. In addition, a 3D visualization model of heavy metal contamination plumes was established via Voxler software. This model intuitively demonstrated the migration and diffusion of heavy metal(loid)s in the underground environment, offering a novel perspective on their subsurface behavior. The research results provide important information for understanding the migration of heavy metal(loid)s in soil-groundwater systems.

Source-oriented stochastic health risk assessment of toxic metals in soil via a hybrid model and Monte Carlo simulation

Toxic metal contamination in soils poses significant hazards to the environment and human health; thus, quantitative assessment of the sources and risks of metal contaminants are urgently needed. A hybrid model that integrates the positive matrix factorization (PMF) and random forest (RF) methods was proposed to quantify the sources of toxic metals in soils by combining diverse environmental variables (source proxies) in this study. In addition, a health risk assessment and Monte Carlo simulations were integrated to estimate the source-oriented stochastic health risk. The results suggested that, except for Ni, which exhibited moderate contamination, other toxic metals (As, Cd, Cr, Hg and Pb) presented slight contamination. Four sources (agricultural activities loaded heavily by As, atmospheric deposition loaded heavily by Hg and Pb, natural sources and mining activities loaded heavily by Cr and Ni, and industrial activities loaded heavily by Cd) were defined and explained 23.44 %, 26.65 %, 30.13 % and 19.78 % of the total variance in toxic metals, respectively. The principal route of exposure (i.e., ingestion), the population at highest risk (i.e., children), and the most hazard-inducing metals (i.e., As and Cr) were determined. Agricultural activities and the combination of natural sources and mining activities demonstrated certain degrees of noncarcinogenic risk to children, with exceedance ratios of 2.20 % and 2.56 %, respectively. Additionally, the combination of natural sources and mining activities demonstrated probabilities for significant carcinogenic risk to adults and children of 0.59 % and 3.76 %, respectively. To reduce the health risks of toxic metals in soils and to protect food and ecological safety, strict regulations should be established to control the discharge of waste from mining and agricultural activities.

Quantitative source apportionment and pollution characteristics of heavy metals in agricultural soils surrounding a legacy Pb-Zn mine

Quantitative source apportionment and pollution characteristics of heavy metals in agricultural soils surrounding a legacy Pb-Zn mine

Aqueous and Colloidal Dynamics in Size-Fractionated Paddy Soil Aggregates with Multiple Metal Contaminants under Redox Alternations.

Soil contamination by multiple metals is a significant concern due to the interlinked mobilization processes. The challenges in comprehending this issue arise from the poorly characterized interaction among different metals and the complexities introduced by spatial and temporal heterogeneity in soil systems. We delved into these complexities by incubating size-fractionated paddy soils under both anaerobic and aerobic conditions, utilizing a combination of techniques for aqueous and colloidal analysis. The contaminated paddy soil predominantly consisted of particles measuring <53, 250-53, and 2000-250 μm, with the <53 μm fractions exhibiting the highest concentrations of multiple metals. Interestingly, despite their higher overall content, the <53 μm fractions released less dissolved metal. Furthermore, glucose enhanced the release of arsenic while simultaneously promoting the sequestration of other metals, such as Pb, Zn, and Cu. Utilizing asymmetric flow field-flow fractionation, we unveiled the presence of both fine (0.3-130 kDa) and large (130-450 nm) colloidal pools, each carrying various metals with different affinities for iron minerals and organic matter. Our results highlighted the pivotal role of the <53 μm fraction as a significant reservoir for multiple metal contaminants in paddy soils, in which the colloidal metals were mainly associated with organic matter. These findings illuminated the size-resolved dynamics of soil metal cycling and provided insights for developing remediation strategies for metal-contaminated soil ecosystems.

Investigating the Interactive Effect of Arbuscular Mycorrhizal Fungi and Different Chelating Agents (EDTA and DTPA) with Different Plant Species on Phytoremediation of Contaminated Soil

Heavy metal (HM) contamination in soil poses a severe environmental threat, jeopardizing ecosystem health and potentially entering the food chain through plant uptake. Phytoremediation, a bioremediation technique utilizing plants to remove or immobilize contaminants, offers a sustainable and eco-friendly solution for HM remediation. This study investigated the interactive effects of arbuscular mycorrhizal fungi (AMF) and chelating agents (EDTA and DTPA) on the growth of maize (Zea mays L.) and alfalfa (Medicago sativa L.) cultivated in metal-contaminated soil and their impact on HM uptake by these plants. The findings revealed that AMF and chelating agents have complex interactive effects on plant growth and metal accumulation. Maize (Zea mays L.) shoot dry matter increased with AMF and chelating agents at lower concentrations. Both plants generally showed a significant (p ≤ 0.05) increase in shoot dry matter with amendments, with AMF × EDTA (10 mmol/kg) being the most effective for alfalfa. DTPA and EDTA generally reduced the DTPA-extractable metals in soil, suggesting potential for metal removal. However, the effects of AMF on metal availability were variable. Metal concentrations in maize (Zea mays L.) shoots increased with increasing DTPA and EDTA concentrations, while the effects of AMF were more complex. The alfalfa shoot metal content showed varied responses, with EDTA (5 mmol/kg) effectively reducing the metal uptake. In general, treatments involving chelating agents (DTPA and EDTA) tend to result in higher bioaccumulation factor (BF) values compared to the non-treated controls for most HMs in both plant species. Mycorrhizal fungi (AMF) treatment alone or in combination with chelating agents also showed that varied effects on HM uptake in both the alfalfa and maize treatments with chelating agents, especially at higher concentrations, generally promoted the greater translocation of HMs in both plant species. Both alfalfa and maize responded differently to treatments, with some treatments showing higher translocation factor (TF) values for certain HMs in one species compared to the other. Mycorrhizal fungi (AMF) treatment alone or in combination with chelating agents also showed varied effects on HM uptake and translocation in both alfalfa and maize. Further research is required to optimize remediation strategies that balance plant health and metal mobilization.

WRKY Transcription Factors in Response to Metal Stress in Plants: A Review.

Heavy metals in soil can inflict direct damage on plants growing within it, adversely affecting their growth height, root development, leaf area, and other physiological traits. To counteract the toxic impacts of heavy metals on plant growth and development, plants mitigate heavy metal stress through mechanisms such as metal chelation, vacuolar compartmentalization, regulation of transporters, and enhancement of antioxidant functions. WRKY transcription factors (TFs) play a crucial role in plant growth and development as well as in responses to both biotic and abiotic stresses; notably, heavy metal stress is classified as an abiotic stressor. An increasing number of studies have highlighted the significant role of WRKY proteins in regulating heavy metal stress across various levels. Upon the entry of heavy metal ions into plant root cells, the production of reactive oxygen species (ROS) is triggered, leading to the phosphorylation and activation of WRKY TFs through MAPK cascade signaling. Activated WRKY TFs then modulate various physiological processes by upregulating or downregulating the expression of downstream genes to confer heavy metal tolerance to plants. This review provides an overview of the research advancements regarding WRKY TFs in regulating heavy metal ion stress-including cadmium (Cd), arsenic (As), copper (Cu)-and aluminum (Al) toxicity.

Remediation quantum of organic amendments to immobilize potentially toxic heavy metals in wastewater-contaminated soils through maize cultivation

Wastewater is considered a good reservoir of mineral elements that can be used for agriculture, aquaculture, and some other activities after adopting suitable measures. The gap between supply and demand for water is increasing exponentially because of the abrupt boost to the world’s population. This poses a threat to human life as it has reached alarming levels in some parts of the globe. Normally, wastewater consists of liquid waste produced by commercial or industrial sources for daily use, consumption, and production. It is time to refocus our attention on a kind of circulating water system by reusing municipal wastewater for agricultural purposes, particularly irrigation. The recycled or treated water would be used as an alternative to fresh water. In the current study, the impact of various organic amendments was studied to mitigate the toxic effects of pollutants present in wastewater by cultivating maize as a test crop. The present study comprised five treatments replicated four times with a randomized complete block design under field conditions. In this experiment, the treatments included T1 (treatment 1) = control (wastewater-polluted soil without the application of any amendment), T2 = farmyard manure (FYM) at 2.5 tons ha-1 (hectare-1), T3 = FYM at 5.0 tons ha-1, T4 = compost at 2.5 tons ha-1, and T5 = compost at 5.0 tons ha-1. The application of FYM at 5.0 tons ha-1 (T3) was recorded as being the most effective as the maximum improvement was observed in soil characteristics such as pH, electrical conductivity (EC), sodium adsorption ratio (SAR), and organic matter, and for T3, these were 7.33, 2.22 dS m-1, 8.16, and 0.94%, respectively. T3 remained most superior in reducing the concentration of heavy metals in the soil; for example, lead, cadmium, nickel, and arsenic for T3 were 8.64, 1.34, 10.44, and 2.25 mg kg-1 (milligrams per kg), respectively. Maximum fresh biomass (fodder yield) of 9.98 tons ha-1 was harvested when FYM was applied at 5.0 tons ha-1 to the soil compared to 6.2 tons ha-1 in the control plot. The highest contents of nitrogen (1.20%), phosphorus (0.41%), and potassium (3.97%) were observed in maize plants for T3. In maize plants (T3), the concentration of lead, cadmium, nickel, and arsenic was reduced to levels of 1.92, 0.23, 2.28, and 1.25 mg kg-1, respectively. Therefore, it can be concluded from the findings of the experiment that the application of FYM significantly reduced heavy metal concentrations and improved soil health, along with maize crop growth and productivity.

Heavy metal contamination of the Nigerian environment from e-waste management: A systematic review of exposure pathway and attendant pathophysiological implications

Nigerian environment has become a depository of worrisome levels of toxicants including heavy metals. Electrical and electronic equipment which leads to the generation of e-waste is one of the considerable sources of environmental contaminants in Nigeria. This systematic review deployed Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) method to analyze various empirical and quantitative outputs on heavy metal components of e-waste management sites in Nigeria and investigated the distribution of heavy metals in several environmental matrices such as soil, water, surface dust, plant and blood of e-waste scavengers. Also, the probable environmental multi-transformation that ultimately potentiates the susceptibility of humans to the pathophysiological effects and genetic related disorders of exposure to heavy metal component of e-waste was discussed. The relative abundance of metals in soils due to inappropriate e-waste handling is given as follow: Fe>Cu>Pb>Zn>Mn>Co>Cr>Ni>As>Cd, in underground and surface water: Zn>Fe>Cu>Cr>Mn>Pb>Hg>Ni>Co>Cd>As; in surface dusts: Fe>Zn>Pb>Cu>Mn>Cr>Ni>Cd>Co; in plants: Pb>Cu>Mn>Zn>Ni>Cr>Cd obtained from the Nigerian environment. Moreso, the estimated abundance of heavy metals in the blood of e-waste scavengers is Nigeria is given as Cr>Cd>Hg>Zn>As>Pb>Cu>Mn>Fe. Conclusively, this study does not only show that various matrices of Nigerian environment is contaminated with heavy metal but also that the pattern of abundance differ in the environment and in biological systems with the latter having the abundance of Pb, Cr and Cd and the former having the abundance of Cu, Zn and Fe.

Pollution Characteristics, Risk Assessment, and Source Analysis of Heavy Metals in Soil from a Typical Abandoned Antimony Smelting Factory

Considering the surface soil （0-20 cm） from a typical abandoned antimony smelting factory area in Dachang Town, Qinglong County, Guizhou Province, as a case study, a total of 14 soil samples were systematically collected from both within and outside the smelting factory area. The analysis focused on the pollution status, distribution characteristics, and potential ecological risks of heavy metals such as Sb, As, Cd, Cr, Pb, Cu, Zn, Ni, and V in the soil. Additionally, an evaluation and analysis of pollution sources were conducted. The results showed that the mean concentrations of heavy metals including ω（Sb）, ω（As）, ω（Cd）, ω（Cr）, ω（Pb）, ω（Cu）, ω（Zn）, ω（Ni）, and ω（V） in the surface soil of the abandoned antimony smelting factory ranged from 4.58 to 15 049.33 mg·kg-1. With the exception of Cr and Ni, all values exceeded the background values of soils in Guizhou province. The single factor pollution indices of Sb and As were 83.61 and 7.01, respectively, indicating severe contamination. In contrast, Pb fell within the non-polluted to slightly polluted range. The comprehensive potential ecological risk of soil heavy metals was characterized by severe potential ecological risk levels for Sb, As, and Cd, while the remaining heavy metals fell within a range of moderate to substantial potential ecological risk levels. The assessment of the geoaccumulation index revealed that the soil in the study area was primarily contaminated by Sb and As, predominantly exhibiting contamination levels ranging from moderate to severe. The results from the RAC method suggested that Sb was the dominant focus for remediation in this abandoned smelting factory. The two primary pollutants, Sb and As, exhibited elevated levels in leachate toxicity, acid-soluble fraction, available fraction, gastric phase, and intestinal phase in terms of bioavailable content, indicating a certain potential hazard. Further, correlation analysis indicated a certain correlation between the total amount of heavy metals and leachate toxicity, available fraction, acid-soluble fraction, reducible fraction, oxidizable fraction, gastric phase extractable fraction, and intestinal phase extractable fraction. The APCS-MLR model indicated that the sources of Sb, As, Zn, Cu, and Cd were primarily industrial, while the sources of Cr and V were mainly natural, and Pb originated mainly from mixed sources.

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.

Remediation of Pb and Cd contaminated sediments by wheat straw biochar and microbial community analysis

Wheat straw biochar (BC) or modified wheat straw biochar (MBC) could affect the aggregate structure of soil, effectively adsorb heavy metal and reduce the bioavailability of heavy metals in soil. TGA, BET, FTIR and SEM were used to characterize the surface morphology and structure of BC and MBC. The adsorption properties of BC and MBC on Pb(‌II) and Cd(‌II) in solution systems were investigated by batch experiments, and the remediation performance of Pb and Cd contaminated sediment by BC or MBC were studied by pot experiments. The results showed that MBC had a larger specific surface area of 46.04 m2/g and total pore volume 0.0555 cm3/g; the adsorption isotherms of Pb(II) and Cd(II) for BC and MBC were more suitable for Langmuir model (R2 over 0.91), and the maximum adsorption capacities of Pb(II) and Cd(II) by MBC could reach 71.14 and 115.64 mg/g, respectively. BC or MBC promoted the transformation of Pb and Cd from the extractable acid fraction to the oxidizable and residual fraction, reduced the migration of heavy metals and enhanced the stability of aggregates. Therefore, the results provided a perspective for the dredged contaminated sediments used as planting soil. In addition, BC or MBC, as soil amendments, could improve the abundance of microbial community. At the phylum level, the main dominant bacteria were Proteobacteria and Bacteroidetes.

Sensing at Your Fingertip: On-Glove Electrochemical Sensor for Copper Detection on Vine Leaves

Intensive use of copper-based pesticides in agriculture can impact human health and biodiversity: the accumulation of this metal in soil negatively affects crop yields. There is growing interest in developing new tools that are capable of monitoring copper occurrence in agricultural contexts through the use of quick and user-friendly approaches for non-specialists, e.g., farmers. This work focuses on the development of a glove-based electrochemical sensor, enhanced with gold nanoparticles, for the detection of copper ions on leaves. The developed device proved was capable of detecting copper ions contained in a copper-based pesticide commonly used in agriculture (Cupravit Bio Advanced). The on-glove analytical device was characterized using garden leaf as the model system and subsequently applied to on-site detection of copper ions on vine leaf treated with Cupravit Bio Advanced. The procedure was very facile: sampling was carried out by touching the leaf with the strip and the stripping-voltammetric measurement was performed by adding a few microliters of an acidic solution to the strip. The on-glove approach allowed evaluation of the level of copper-based pesticide used, avoiding complex and time-consuming tasks. Such operation opens up a wide range of possibilities for improving precision agriculture and sustainable development at the point-of-need for the use of non-specialists.

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.

Metals in Soils of the Southern Kuril Islands

Metals in Soils of the Southern Kuril Islands