Soil heavy metal pollution of industrial legacies in China and health risk assessment

Multi-omics reveals the hepatic metabolic mechanism of neurological symptoms caused by selenium exposure in Przewalski's gazelle (Procapra przewalskii)

Neurological symptoms resulting from selenium(Se) exposure significantly impact the health and conservation of Przewalski's gazelle. In this study, we performed proteomic and metabolomic analyses of the liver in Przewalski's gazelle for the first time, aiming to reveal the hepatic metabolic mechanisms underlying the neurological symptoms caused by Se exposure. We identified 89 differentially expressed proteins and 30 metabolites with altered regulation. Using multi-omics integrated analysis, we identified a neurofunctional regulation network composed of three metabolic pathways, with (S)-3-amino-2-methylpropionate transaminase being the key enzyme in the regulatory network. Molecular docking revealed that the binding of selenocysteine to (S)-3-amino-2-methylpropionate transaminase may act as a key factor in activating this regulatory network. Consequently, these findings provide important insights into the molecular mechanisms of neurological symptoms caused by Se exposure and have significant implications for the conservation in Przewalski's gazelle.

Quantification of an integrated approach to heavy metal source apportionment and probabilistic health risk assessment in the black soil region of central Jilin Province, China

The northeast black soil region is critical for grain production in China but has experienced significant heavy metals (HMs) contamination due to intensive agriculture. This study investigates the levels of Cr, Ni, Cu, Zn, Cd, As, Pb, and Hg in agricultural soils within the black soil region of central Jilin Province. Enrichment factor (EF) and geo-accumulation index (Igeo) indicate that Ni and Cr are significantly affected by human activities, with notable pollution levels. The Positive Matrix Factorization (PMF) model identifies four primary pollution sources: coal combustion, traffic emissions, and soil parent material (24.70 %); fertilizers and pesticides (24.50 %); mining (27.81 %); and organic fertilizers combined with soil parent material (22.99 %). The potential ecological risk assessment results reveal a generally low potential ecological risk in the study area, although Hg and Cd contribute notably to the overall risk. The human health risk assessment (HHRA) results show that non-carcinogenic risk for all populations are below the threshold of 1, while the average carcinogenic risk for all populations exceed the acceptable threshold of 1E-6. Children face higher non-carcinogenic and carcinogenic risks compared to adults. By integrating the PMF results with potential ecological and health risk assessments, it was found that coal combustion and mining activities contribute most significantly to potential ecological and health risks, respectively. This study investigates the pollution characteristics, sources, and ecological and health risks of HMs in agricultural soils in the black soil region. The findings offer valuable insights for policymakers in developing effective environmental management strategies.

Foliar Spray of Cerium Oxide Nanoparticles (CeO2 NPs) Improves Lead (Pb) Resistance in Rice

The widespread use of lead (Pb) has led to serious environmental and human health problems worldwide. The application of oxide nanoparticles (CeO2 NPs) in alleviating abiotic stress in plants has received extensive attention. In this study, 50 mg·L-1 CeO2 NPs can improve Pb resistance and promote rice growth. Specifically, this study observed that CeO2 NPs increased the activity of antioxidant enzymes peroxidase (POD), catalase (CAT), and ascorbate peroxidase (APX), but the difference did not reach a significant level. At the same time, CeO2 NPs upregulated antioxidant metabolites alpha-linolenic acid, linoleic acid, ferulic acid, and kaempferol under Pb stress. In addition, CeO2 NPs upregulated multiple defense response-related genes, such as OsOPR1 and OsPR10a; RPR10a, and improved rice carbon flow and energy supply by upregulating sucrose and D-glucose. The results of this study provided technical support for alleviating Pb stress in rice.

Zinc Mitigates the Combined Neurotoxicity of Binary Metal Mixtures via Mitophagy and Mitochondrial Fusion

Environmental metal mixtures can cause combined neurotoxicity, but the underlying mechanism remains unclear. Mitochondria are crucial for energy metabolism in the nervous system, and their dysfunction leads to neurodegeneration. Zinc (Zn) is a coenzyme of many mitochondrial enzymes that controls mitochondrial function. This study investigated the role of Zn in the neurotoxicity induced by Mn + Pb and Pb + As mixtures. Zn supplementation improved the survival rate and learning ability of Caenorhabditis elegans following their exposure to mixtures of Mn + Pb and Pb + As by enhancing their mitochondrial morphology, membrane potential, and respiratory chain. Similarly, in HT22 cells, Zn mitigated the decrease in cellular activity and increase in apoptosis induced by the Mn + Pb and Pb + As mixtures by improving mitochondrial morphology and function. Mechanistically, Zn activated the PINK1 and MFN-2/OPA-1 pathways, promoting mitophagy and mitochondrial fusion. However, inhibition of mitophagy reversed the protective effect of Zn, indicating its reliance on mitophagy for neuroprotection. Our study demonstrated that Zn alleviates the combined neurotoxicity of Mn + Pb and Pb + As mixtures by enhancing mitophagy and mitochondrial fusion, suggesting that Zn supplementation is a potential treatment for metal-induced neurotoxicity.

Estimating soil cadmium concentration using multi-source UAV imagery and machine learning techniques

Urbanization and industrialization have led to widespread soil heavy metals contamination, posing significant risks to ecosystems and human health. Conventional methods for mapping heavy metal distribution, which rely on soil sampling followed by chemical analysis, are costly and time-consuming. This study proposes a novel approach for estimating soil cadmium (Cd) concentrations by integrating multi-source data captured by Unmanned Aerial Vehicle (UAV), including multispectral images, Digital Elevation Model (DEM), and high-resolution RGB aerial imagery, with machine learning algorithms. Environmental factors such as proximity to pollution sources, terrain attributes, and remote sensing indices were extracted from the UAV multi-source data and used to train machine learning models for soil Cd concentration estimation. Among the tested models, the Gradient Boosting Decision Tree (GBDT) algorithm demonstrated the highest accuracy in estimating soil Cd levels. The proposed method achieves higher predictive accuracy than Kriging interpolation, with Mean Squared Error (MSE) and Mean Absolute Error (MAE) reduced by 37% and 22%, respectively. Additionally, the approach quantified the relative importance of each explanatory variable using feature importance scores derived from machine learning regression models, revealing that proximity to pollution sources was the most influential factor affecting soil Cd concentrations in the study area. This study demonstrates the potential of UAV-based multi-source data, combined with machine learning techniques, as a complementary approach to conventional soil contamination mapping methods. The proposed methodology improves soil contamination assessment efficiency, aiding hotspot detection and targeted remediation. These findings suggest UAV-based remote sensing could support environmental monitoring and land management.

Assessment of ecological and human health risks of heavy metals in soils and Polygonatum sibiricum plants from various cultivation areas in China

In this study, we collected 528 samples from 7 important Polygonatum sibiricum (P. sibiricum) planting areas in China. The P. sibiricum samples were classified into P. sibiricum Red., P. cyrtonema Hua. and P. kiugianum Col.et Hemsl. The content of the Cu, As, Zn, Cd, Pb, and Cr in P. sibiricum and soil were determined using inductively coupled plasma mass spectrometry, and the ecological and health risks were evaluated. The results showed that addition to Cu, the soil exhibits varying degrees of excessive pollution from Zn, As, Pb, Cd, and Cr exceeding permissible levels (GB15618 - 2018, Soil environmental quality-Risk control standard for soil contamination of agricultural land in China). Among them, 31.56% Zn, 22.43% As, and 22.05% Cd in soil exceeded the GB 15618 - 2018 standard. Additionally, three types of P. sibiricum soil have risks, with the risk level being P. cyrtonema Hua. > P. kiugianum Col.et Hemsl. > P. sibiricum Red. It was worth noting that the practice of artificial cultivation management may reduce the amount of As, Cd, and Cr in the soil while increasing the amount of Zn. The order of P. sibiricum bioaccumulating ability in different heavy metals was: Cd > Zn > Cu > Cr > As > Pb, and it had good tolerance to As, Pb, and Cr. In addition, the chronic daily intake, hazard quotient and hazard indexes indicate that the current Cu, Hg, As, Cd and Pb contents of P. sibiricum in China do not pose a health risk to humans. In summary, the impact of Cd in P. sibiricum should be given attention.

Artificial intelligence: A key fulcrum for addressing complex environmental health issues

Environmental health (EH) is a complex and interdisciplinary field dedicated to the examination of environmental behaviours, toxicological effects, health risks, and strategies for mitigating harmful environmental factors. Traditional EH research investigates correlations between risk factors and health outcomes through control variables, but this route is difficult to address complex EH issue. Artificial intelligence (AI) technology not only has accelerated the innovation of the scientific research paradigm but also has become an important tool for solving complex EH problems. However, the in-depth and comprehensive implementation of AI in the field of EH still faces many barriers, such as model generalizability, data privacy protection, algorithm transparency, and regulatory and ethical issues. This review focuses on the compound exposures of EH and explores the potential, challenges, and development directions of AI in four key phases of EH research: (1) data collection, fusion, and management, (2) hazard identification and screening, (3) risk modeling and assessment and (4) EH management. It is not difficult to see that in the future, artificial intelligence technology will inevitably carry out multidimensional simulation of complex exposure factors through multi-mode data fusion, so as to achieve accurate identification of environmental health risks, and eventually become an efficient tool for global environmental health management. This review will help researchers re-examine this strategy and provide a reference for AI to solve complex exposure problems.

Fine-particle separation in heavy metal soil remediation using innovative hydrocyclone technology

Heavy metal pollution in soils poses significant threats to ecosystems and human health. Traditional remediation methods (such as phytoremediation, thermal treatment, and electrokinetic remediation) are frequently limited by high costs and low efficiency. This study presents a novel approach using a small-scale hydrocyclone designed through numerical simulations to effectively separate fine-particle-contaminated soil. While heavy metals primarily adhere to particles smaller than 20 μm, previous studies have focused on rough separation of particles up to 200 μm. Our design innovation focuses specifically on the key particle size range of 20 μm. Using the Reynolds Stress Model (RSM), Volume of Fluid model, and discrete phase model, we investigated the effects of vortex finder diameter on flow field and classification efficiency and analyzed particle trajectories and separation performance. Under optimal conditions (1:25 water-to-soil ratio, 1.1 m3/h flow rate), the <20 μm particle fraction in overflow increased from 76.3 % to 89.2 %, while underflow desorption efficiencies reached 88.7 % (Cu), 84.5 % (Pb), and 80.4 % (Cd). This approach demonstrates significant improvements in fine particle classification and precise reduction of contaminated soil volume. Our findings offer a cost-effective and efficient solution for soil remediation, addressing a major environmental challenge and providing a promising avenue for future research and application in environmental restoration.

Multi-Omics Analysis Reveals That AhNHL Contributes to Melatonin-Mediated Cadmium Tolerance in Peanut Plants

Cadmium (Cd) pollution significantly hampers cleaner production of peanut (Arachis hypogaea L.). Therefore, exploring of tolerance mechanisms to Cd stress and breeding of low-Cd peanut cultivars are urgently needed and require intense efforts. Herein, multi-omics and physiological studies reveal that multiple biological processes, including melatonin (MT) biosynthesis, are involved in the Cd tolerance in peanut plants. Exogenous MT was applied to peanut plants under Cd stress, which decreased Cd accumulation in roots, shoots and seeds for 40%-60%, and promoted the antioxidant capacity. Integrated investigation reveals that MT-mediated Cd tolerance is mainly attributed to the enhanced metabolism of linolenic acid, glutathione (GSH), and phenylpropanoid (lignin), and development of casparian strip in root cell wall. Defense genes, such as non-race-specific disease resistance gene 1/harpininduced gene 1 (NDR1/HIN1)-like in peanut (AhNHL), were also significantly upregulated by MT under Cd stress. Overexpression of the AhNHL gene in tobacco reduced Cd accumulation for 37%-46%, and alleviated photosynthesis-inhibition induced by Cd stress. Transcriptomic analysis suggested that AhNHL confers the Cd tolerance mainly through promoting phenylpropanoid biosynthesis and GSH metabolism. Additionally, exogenous GSH effectively alleviated the Cd stress through improving Cd sequestration and antioxidant capacity in peanut plants, while apply of the GSH biosynthesis inhibitor (buthionine sulfoximine) exacerbated the Cd phytotoxicity. Transcriptomic analysis reveals that exogenous GSH improves Cd tolerance through affecting the expression of genes involved in transcription regulation, and metal ion binding and transport. Our findings provide novel insights into molecular mechanisms underlying Cd tolerance in plants, which would facilitate breeding of low-Cd peanut cultivars.

Exogenous sodium nitroprusside exhibits multiple positive roles in alleviating cadmium toxicity in tobacco (Nicotiana tabacum L.)

As a donor of the gaseous signaling molecule nitric oxide (NO), sodium nitroprusside (SNP) has been shown to play a positive role in enhancing plant resistance to abiotic stress. However, its role in alleviating cadmium (Cd) toxicity in tobacco (Nicotiana tabacum L.) is not fully understood. This study found that Cd stress significantly inhibited tobacco growth. At the same time, 150 μM SNP was the most effective concentration in alleviating Cd toxicity in seedlings, restoring three stress tolerance indicators-MDA, H2O2, and proline-to control levels. Exogenous SNP mitigated Cd-induced oxidative stress by promoting the accumulation of non-enzymatic antioxidants (total phenolics and flavonoids) and activating key antioxidant enzymes (SOD, CAT, POD, APX, and GR) along with their gene expression. SNP also facilitated Cd accumulation in the root cell wall and prevented Cd translocation from roots to shoots. Additionally, SNP altered Cd's subcellular distribution, promoting its sequestration in vacuoles and cell walls, which may be related to the NO-mediated upregulation of the metallothionein gene NtMT2F and the phytochelatin gene NtPCS2. The addition of SNP significantly increased the proportion of Cd in less toxic chemical forms, with the residual Cd fraction in the Cd + SNP group reaching 7.30 %, higher than the 4.86 % in the Cd-only group. Furthermore, exogenous SNP counteracted Cd's inhibition of nitrate reductase (NR) activity, promoting endogenous NO production. This study systematically reveals the positive roles of exogenous SNP in mitigating Cd toxicity in tobacco, offering valuable insights for producing low-Cd tobacco.

Simplified vs extended in vitro methods for the evaluation of bioaccessibility of metals and metalloids present in urban recreational soils

Urban soils may contain different metals and metalloids and they can enter the human body by direct inhalation, ingestion or dermic absorption. According to USEPA, 200 mg·day-1 is the average daily ingested dose of soil for children aged from 1 to 12 years of age. In vitro bioaccessibility tests which are based on human physiology, have been used for the determination of the element fraction in soils that can be absorbed by human digestion. A total of 26 urban soils were collected in recreational areas from San Sebastian to evaluate the bioaccessibility of metals and metalloids (Al, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Cd and Pb) by SBET (Simplified Bioaccessibility Extraction Test) and RIVM (Dutch National Institute for Public Health and Environment) in vitro methodologies. SBET simulates the gastric conditions, while RIVM simulates mouth, gastric and intestinal conditions. ICP-MS was used for the simultaneous determination of the elements. Cd showed the highest percentage of bioaccessibility by both methods and Fe, Al and Cr resulted the least bioaccessible elements. Pb and Zn showed different results in each method. HQ (Hazard Quotient), HI (Hazard Index) and CR (Carcinogenic Risk) values obtained were higher with SBET methodology. According to HI (considering 10 metal(loid)s), non-carcinogenic effects may occur to children with the ingestion of three of the studied children's parks. Regarding CR index, all the studied soils were within the tolerable carcinogenic risk (considering Cr, As and Pb) for children, and the risk was sometimes negligible for adults. Considering the experimental difficulties related to RIVM, SBET method may be used for a simple and conservative first approach of the bioaccessibility of metals and metalloids accumulated in soil samples.

Accumulation, physiological and proteomic analyses of Suaeda salsa under cadmium exposure

Suaeda salsa, the dominant herbaceous plant in the high salinity areas of Asia, can even grow in the heavy metal polluted region. In order to illustrate the mechanisms of Cd (cadmium) tolerance in S. salsa, the accumulation, physiological and proteomic characters under two different concentrations of Cd exposure were investigated in this study. The results showed a significant decrease in root and seedling growth rate, as well as an increase in Cd ion content in all tissues of S. salsa, in response to the increased Cd concentration. Furthermore, it was found that Cd was mainly accumulated in the root compared with the stem and leaf. Further proteomic analysis revealed that in the root of S. salsa under 7-d Cd exposure, 260 and 237 proteins were significantly upregulated in 1 μg/L and 20 μg/L Cd treatment groups, respectively. In addition, Gene Ontology (GO) enrichment analysis showed that cellulose synthase with the function of cell wall organization was upregulated under Cd stress. Moreover, the proteins functioning as the transporters of iron (ATP-binding cassettes protein, metal tolerance proteins, yellow-stripe-like proteins) and organic compounds (oligopeptide transporters, phosphate transporters) were also highly expressed, which indicated that the accumulation of Cd in the root of S. salsa may be mainly regulated through Cd immobilization by the cell wall or transportation into vacuoles. These findings enhance our understanding of the impacts of Cd pollution in S. salsa and may form a basis for future phytoremediation and biomarker studies.

Sources analysis and risk assessment of heavy metals in soil in a polymetallic mining area in southeastern Hubei based on Monte Carlo simulation

This study investigates the pollution characteristics, spatial patterns, causes, and ecological risks of heavy metals in the soils of the southeastern Hubei polymetallic mining areas, specifically the Jilongshan (JLS) and Tonglushan (TLS) regions, located in the middle and lower reaches of the Yangtze River. The main findings are as follows: (1) Among the heavy metals present in the soil, copper (Cu) has the highest average concentration at 278.54 mg/kg, followed by zinc (Zn) at 161.16 mg/kg, chromium (Cr) at 75.23 mg/kg, nickel (Ni) at 30.38 mg/kg, arsenic (As) at 22.53 mg/kg, cadmium (Cd) at 0.76 mg/kg, and mercury (Hg) at 0.14 mg/kg; (2) The distribution of heavy metal concentrations exhibits significant regional variations, with the spatial pattern of pollution indicating that TLS is more affected than JLS, as evidenced by the Pollution Load Index (PLI) values; (3) Three potential sources of heavy metals were identified: natural sources, anthropogenic activities (including industrial production and agricultural practices), and atmospheric deposition (both dry and wet); (4) While severe contamination levels of specific metals such as copper and cadmium are observed in JLS and TLS soils, the overall contamination is mild, suggesting complex contamination dynamics; (5) Cadmium poses a moderate to high ecological risk, being the most sensitive factor in the comprehensive ecological risk assessment with a contribution rate of 65.2 %; (6) The concentrations of heavy metals in the soil present certain health risks, with children being more vulnerable than adults. This study helps to identify the hot spots and pollution patterns of heavy metal pollution in polymetallic mining areas and provides a theoretical basis for the study of local countermeasures against pollution. Based on the research results, management measures and ecological restoration suggestions are proposed, which are important for reducing soil insecurity and coping with climate change.

Migration modeling of metal(loid)s in soil-groundwater systems from an abandoned mine: Based on multimethod integration

Metal(loid)s contamination of mine has been a global environmental challenge. Traditional investigations of metal(loid) distribution patterns and migration behavior in soil-groundwater systems are constrained by the high costs of drilling and sampling limitations, leading to significant uncertainties in contamination assessment. This study presents an integrated approach combining three-dimensional (3D) visualization with Random Forest (RF) modeling and GIS mapping to investigate metal(loid) contamination characteristics and migration behavior in a mining area's soil-groundwater system. We developed an RF model with 1000 decision trees to expand limited drilling data for comprehensive spatial coverage. Model performance was validated using R2 and Root Mean Square Error (RMSE) metrics. The validated predictions were integrated into 3D visualization models and analyzed in conjunction with GIS mapping to characterize spatial patterns. Through analysis of temporal groundwater sampling data across wet, dry, and transitional hydrological periods, combined with RF modeling, we visualized metal(loid) distribution patterns and characterized their migration behavior in the soil-groundwater system. This integrated methodology provides a novel framework for investigating metal(loid) distribution and migration in mine soil-groundwater systems, effectively bridging traditional exploration techniques with advanced numerical simulation.

Systematic bibliographic analysis of heavy metal remediation

Heavy metals pose a significant threat to human health, with contaminated water sources linked to severe conditions, including gastric cancer. Consequently, the effective remediation of heavy metals is crucial. This study employs a bibliographic analysis to examine key methodologies, leading organizations, and prominent countries involved in heavy metal remediation. By systematically reviewing around 1,000 records, the paper identifies the most critical remediation techniques and provides a comprehensive overview of current practices in the field. Additionally, the study explores prospects, emphasizing the potential of emerging technologies such as big data and machine learning to enhance remediation efforts. It highlights recent advancements, identifies significant trends, such as the growing use of bioremediation and nanotechnology, and addresses critical challenges in the remediation landscape, including regulatory hurdles and technological limitations. By making stronger connections between the identified trends and their implications for future research, this comprehensive analysis aims to provide valuable insights and guide the development of improved strategies for mitigating the impact of heavy metal contamination, ultimately safeguarding public health.

Mycoremediation of heavy metals by Curvularia lunata from Buckingham Canal, Neelankarai, Chennai

The spread and mobilization of toxic heavy metals in the environment have increased to a harmful level in recent years as a result of the fast industrialization occurring all over the world to meet the demands of a rising population. This research aims to analyze and evaluate the mycoremediation abilities of fungal strains that exhibit tolerance to heavy metals, gathered from water samples at Buckingham Canal, Neelankarai, Chennai. Water samples were examined for heavy metal analysis, and the highest toxic heavy metals, Zn, Pb, Mn, Cu, and Cr, were recorded. Three fungal strains were isolated and named EBPL1000, EBPL1001, and EBPL1002 were selected by primary screening (100 ppm) for further studies. Out of three fungal isolates, EBPL1000 grew in all five heavy metal concentrations and showed 2100 ppm as the highest Maximum Tolerance Concentration toward Lead, 2000 ppm tolerance in Zinc and Manganese, 1700 ppm in Chromium, and 1500 ppm in copper, respectively. The fungal isolate EBPL1000 was identified as Curvularia lunata with 100% percentage identity and query coverage. The Biosorption result reveals that lead is the highest biosorbed heavy metal with 79.99% at 100 ppm concentration while copper is the lowest biosorbed with 24.11% heavy metal at 500 ppm concentration. The uptake of Manganese by Curvularia lunata biomass was the highest (5.64 mg/g) of all heavy metal's uptake at 100 ppm concentration. The lowest uptake of heavy metals was copper (0.43 mg/g) at 500 ppm concentration, and the growth profile study under heavy metals stress conditions shows the order of Pb > Mn > Zn > Cr > Cu at 60 h of time intervals at 100 ppm concentration. In addition to the research, FTIR analysis and Molecular Docking studies provide credence to the idea that Curvularia lunata has high biosorption potential and uptake or removal of toxic heavy metals at low cost and in an eco-friendly way from the contaminated environment.

Smartphone-assisted colorimetric sensor arrays based on nanozymes for high throughput identification of heavy metal ions in salmon

The rapid, precise, and high-throughput identification of multiple heavy metals ions holds immense importance in ensuring food safety and promoting public health. This study presents a novel smartphone-assisted colorimetric sensor array for the rapid and precise detection of multiple heavy metals ions. The sensor array is based on three signal recognition elements (AuPt@Fe-N-C, AuPt@N-C, and Fe-N-C) and the presence of different heavy metal ions affects the nanozymes-chromogenic substrate (TMB) catalytic color production, enabling the differentiation and quantification of various heavy metal ions. Combined with a smartphone-based RGB mode, the colorimetric sensor array can successfully identify five different heavy metal ions (Hg2+, Pb2+, Co2+, Cr6+, and Fe3+) as low as 0.5 μM and different ratios of binary and ternary mixed heavy metal ions in just 5 min. The sensor array successfully tested seawater and salmon samples with a total heavy metal content of 10 μM in the South China Sea (Haikou and Wenchang). Overall, this study highlights the potential of smartphone-assisted colorimetric sensor arrays for the rapid and precise detection of multiple heavy metal ions, which could significantly contribute to food safety and public health monitoring.

Determination of soil environmental criteria for high-risk trace metals in urban park soils using improved CLEA model

The trace metals (TMs) accumulated in urban park soils can pose potential threats to human health, making the management of soil quality based on health risks critically important. Based on the human health risk assessment (HHRA) model coupled with Monte Carlo Simulation, this study improved the contaminated land exposure assessment (CLEA) model. Combined with local parameters, the Soil Environmental Criteria (SEC) for high-risk trace metals (TMs) in urban park soils were calculated. Results indicated that all the mean TCR (Total carcinogenic risk) values of seven TMs exceeded the risk threshold of 1E-06, suggesting a higher likelihood of carcinogenic risks for all populations. As and Cr presented the highest potential carcinogenic risks, and were identified as high-risk TMs in the study area. The traditional CLEA model was enhanced by incorporating region-specific data, optimizing exposure parameter calculations, and addressing parameter sensitivity and uncertainty. Using the improved CLEA model, the SEC values for high-risk TMs were calculated, revealing that the SEC values gradually increased from ages 1 to 18, while significantly decreased for individuals over 80 years old. This study effectively addresses issues of parameter uncertainty and sensitivity in the CLEA model, offering new insights for the development of soil environmental quality standards.

Migration and availability of Ni and Cd in industrial soils under different leaching conditions: Insights from DGT and DIFS models

Rainfall runoff can mobilize heavy metals in industrial soils, posing environmental risks. The mobility and distribution of heavy metals in different industrial soil layers are often overlooked. This study employed dynamic leaching experiments in layered soil columns with DGT (the diffusive gradients in thin films) measurements and DIFS (DGT-induced fluxes in soils and sediments) model to describe the migration, availability, and resupply ability of metals at different depths in surface and deep soil columns of industrial soils. Results showed significantly higher available concentrations (CDGT and CSoln) of Ni and Cd in surface soils compared to deep soils, likely due to the differences in soil physiochemical properties (contamination, pH, and soil texture). Continuous leaching promoted the migration of available Ni and Cd in surface soils. Maximum values of RNi (0.79-0.91) and RCd (0.75-0.80) were observed in the top layer (0-4 cm) of the surface soil, consistent with the trends of RFe. Combined DGT and DIFS model analysis implied higher potential availability and resupply of Ni and Cd in surface soil columns. These findings highlight the importance of considering dynamic leaching effects on heavy metal transport, availability, and release in industrial soils.

Assessing male reproductive toxicity of environmental pollutant di-ethylhexyl phthalate with network toxicology and molecular docking strategy

Environmental pollutants, especially endocrine-disrupting chemicals (EDCs) like di-ethylhexyl phthalate (DEHP), pose serious threats to human health, with DEHP widely implicated in male reproductive toxicity. However, the complex molecular interactions remain unknown. We employed a network toxicology approach combined with molecular docking analysis to identify potential targets and mechanisms of DEHP's toxic effects. Databases such as ChEMBL, STITCH, OMIM, and GeneCards were utilized to gather data, and Cytoscape software was used to construct protein-protein interaction networks. A total of 51 potential targets were identified, with eight core targets, including PTGS2, CASP3, and ESR1, highlighted for their roles in oxidative stress, apoptosis, and hormonal dysregulation. KEGG pathway enrichment analysis revealed significant associations with pathways in cancer, cytokine-mediated signaling, and the hypothalamic-pituitary-gonadal axis. Additionally, gene expression datasets from the Gene Expression Omnibus (GEO) database were analyzed to identify differentially expressed genes overlapped with DEHP targets in testicular diseases. Molecular docking results confirmed strong binding affinities between DEHP and the core target proteins, suggesting a robust interaction mechanism. This study underscores the need for further investigation into DEHP's toxic mechanisms and its combined effects with other environmental pollutants, paving the way for comprehensive risk assessments and the development of targeted intervention strategies.

Risk hotspots and influencing factors identification of heavy metal(loid)s in agricultural soils using spatial bivariate analysis and random forest

Heavy metal(loid)s (HMs) in agricultural soils not only affect soil function and crop security, but also pose health risks to residents. However, previous concerns have typically focused on only one aspect, neglecting the other. This lack of a comprehensive approach challenges the identification of hotspots and the prioritization of factors for effective management. To address this gap, a novel method incorporating spatial bivariate analysis with random forest was proposed to identify high-risk hotspots and the key influencing factors. A large-scale dataset containing 2995 soil samples and soil HMs (As, Cd, Cr, Cu, Mn, Ni, Pb, Sb, and Zn) was obtained from across Henan province, central China. Spatial bivariate analysis of both health risk and ecological risks revealed risk hotspots. Positive matrix factorization model was initially used to investigate potential sources. Twenty-two environmental variables were selected and input into random forest to further identify the key influencing factors impacting soil accumulation. Results of local Moran's I index indicated high-high HM clusters at the western and northern margins of the province. Hotspots of high ecological and health risk were primarily observed in Xuchang and Nanyang due to the widespread township enterprises with outdated pollution control measures. As concentration and exposure frequency dominated the non-carcinogenic and carcinogenic risks. Anthropogenic activities, particularly vehicular traffic (contributing ∼37.8 % of the total heavy metals accumulation), were the dominant sources of HMs in agricultural soils. Random forest modeling indicated that soil type and PM2.5 concentrations were the most influencing natural and anthropogenic variables, respectively. Based on the above findings, control measures on traffic source should be formulated and implemented provincially; in Xuchang and Nanyang, scattered township enterprises with outdated pollution control measures should be integrated and upgraded to avoid further pollution from these sources.

Multimodel-based quantitative source apportionment and risk assessment of soil heavy metals: A reliable method to achieve regional pollution traceability and management

To strengthen the control of pollution sources and promote soil pollution management of agricultural land, this study constructed a comprehensive source apportionment framework, which significantly improved the reliability of potential source analysis compared with the traditional single model. The spatial distribution pattern of agricultural soil heavy metals (SHMs) content in Lintong, a typical river valley city in China, was determined and the degree of contamination was evaluated. A scientific source apportionment methodological framework was constructed through correlation analysis methods together with multiple source apportionment receptor models. Finally, the Monte Carlo simulation method was used to derive the results of the human health risk assessment (HHRA). The results revealed the following: (1) Agricultural soils were moderately and mildly polluted, accounting for 28.8 % and 71.2 % of the total number of sampling points, respectively. (2) The overall correlation of heavy metals (HMs) was strong according to the coupling analysis of the SHMs, in which a strong correlation (0.8-1) was reached among Cu, Ni, Pb, Cr and Zn, indicating that these HMs were most likely homologous or composite. (3) Multimodel analysis of the SHMs sources revealed that the first and second principal components were agricultural (41.36 %) and industrial (19.69 %) sources, respectively, and the remaining principal components were road traffic, natural factors, and atmospheric deposition or surface runoff, respectively. (4) The average comprehensive noncarcinogenic health risk indices for adults and children were 4.2259E-02 and 1.4194E-01, respectively, which were within the slight risk range, indicating that the risk caused by SHMs to the human body can be almost negligible. This study adopted a mixed method to reveal the risk of SHMs pollution and its sources, which provides some reference and technical support for traceability analysis, zoning control, and health risk studies of regional pollutants and is helpful for formulating scientific management measures and targeting control policies.

Ignoring the food route underestimated human health risk from potentially toxic elements in agricultural environments of Ziyang, Shaanxi, China

Staple food is a crucial exposure route for the human intake of potentially toxic elements (PTEs), but it has been neglected in previous human health risk (HHR) studies. Lack of attention to this issue will lead to an underestimation of HHR caused by PTEs. This study establishes a comprehensive regional identification method for health risk assessment (HRA), namely, soil-maize health risk assessment (SMHRA) and applies it to Ziyang, Shaanxi, which is a typical agricultural county. SMHRA considered the exposure pathway of staple food and utilized Monte Carlo simulation to enhance the accuracy of HRA for PTEs. Results indicated the PTE spatial heterogeneity in a soil-maize system. Introducing staple food exposure pathway would increase HHR values and probabilities 1.57-2.80 and 1.53-5.63 times than that when food route was not considered. Overall, the HHR caused by a single PTE was low, which relatively safe. The introduction of food pathway contributed to accurate estimate the HHR of As and Ni, and the risk probabilities ranged from 0.04% to 12.46%. Few areas had high levels of Ni, which pose health risks: approximately 1.8% for children and higher than 0.5% for adults. Both As and Ni had the highest contribution to HHR among all PTEs, with 33.84%-41.56% TNCR caused by As, and 54.73%-56.90% TCR created by Ni, respectively. For human health risk routes, the staple food exhibited the highest contribution to HHR among all exposure routes, with TNCR of 36.15%-56.73% and the TCR of 44.96%-64.28%. Our research imply that dietary intake of PETs must be considered in the human health risk assessment in agricultural environment, which offers the foundation for subsequent environmental risk prevention and control.

Exploring lead uptake, transport mechanisms in roots of different Sedum alfredii ecotypes as a way of enhancing its hyperaccumulative capacity

Lead (Pb) contamination poses an extensive environmental challenge. Sedum alfredii, as a Zn/Cd co-hyperaccumulator, also exhibits a considerable capability for Pb tolerance and accumulation, which has great potential for phytoremediation of Pb-contaminated soil. However, the mechanisms of Pb uptake and accumulation in Sedum alfredii roots remain opaque. In this study, synchrotron-based micro X-ray fluorescence and X-ray absorption spectroscopy were used to investigate the localization and speciation of Pb in the roots of Pb-accumulating ecotype and non-accumulating ecotype of Sedum alfredii. The results showed that non-accumulating ecotype accumulated large amounts of Pb predominantly in the meristematic and elongation zones of the root tips after treatments of 100 μM Pb for 24 h. Pb-accumulating ecotype accumulated less Pb in roots than non-accumulating ecotype, but transported more Pb to the shoots through the root stele. Moreover, lateral roots, including lateral root primordia, as well as the apexes and bases of emerged lateral roots, were observed to be the hotspots of Pb distribution in both Pb-accumulating ecotype and non-accumulating ecotype roots, indicating their important role in Pb uptake and accumulation. Pb-cell wall complex was found to be the main form of Pb (>65%) in both ecotypes, although the proportion of the Pb-cell wall complex in Pb-accumulating ecotype roots is lower, and a small amount of Pb-GSH complex (8.6%) was observed, which may be engaged with the Pb accumulation and translocation in Pb-accumulating ecotype.

Endophytic Bacteria Improve Bio- and Phytoremediation of Heavy Metals

Currently, the problem of heavy metal pollution in China is becoming increasingly serious, which poses grave threats to the environment and human health. Owing to the non-biodegradability and toxicity of heavy metals, a more sustainable and ecological approach to remediate heavy metal pollution has always been a focus of attention for environmental researchers. In recent years, many scientists have found that phytoremediation aided by endophytes has high potential to remediate heavy metals owing to its low cost, effectiveness, environmental friendliness, and sustainability compared with physical and chemical methods. Indeed, the mechanism of interaction between endophytes, plants, and heavy metals in the soil is pivotal for plants to tolerate metal toxicity and thrive. In this review, we focus on the mechanism of how endophytic bacteria resist heavy metals, and the direct and indirect mechanisms employed by endophytic bacteria to promote the growth of plants and enhance phytoextraction and phytostabilization. Moreover, we also discuss the application of combinations of endophytic bacteria and plants that have been used to remediate heavy metal pollution. Finally, it is pointed out that although there have been many studies on phytoremediation systems that have been assisted by endophytes, large-scale field trials are important to deliver "real" results to evaluate and improve phytoremediation assisted with microorganisms in polluted natural environments.

Association of metals and bisphenols exposure with lipid profiles and dyslipidemia in Chinese adults: Independent, combined and interactive effects

BACKGROUND

Although studies have assessed the association of metals and bisphenols with lipid metabolism, the observed results have been controversial, and limited knowledge exists about the combined and interactive effects of metals and bisphenols exposure on lipid metabolism.

METHODS

Plasma metals and serum bisphenols concentrations were evaluated in 888 participants. Multiple linear regression and logistic regression models were conducted to assess individual associations of 18 metals and 3 bisphenols with 5 lipid profiles and dyslipidemia risk, respectively. The dose-response relationships of targeted contaminants with lipid profiles and dyslipidemia risk were captured by applying a restriction cubic spline (RCS) function. The bayesian kernel machine regression (BKMR) model was used to assess the overall effects of metals and bisphenols mixture on lipid profiles and dyslipidemia risk. The interactive effects of targeted contaminants on interested outcomes were explored by constructing an interaction model.

RESULTS

Single-contaminant analyses revealed that exposure to iron (Fe), nickel (Ni), copper (Cu), arsenic (As), selenium (Se), strontium (Sr), and tin (Sn) was associated with elevated lipid levels. Cobalt (Co) showed a negative association with high density lipoprotein cholesterol (HDL-C). Bisphenol A (BPA) and bisphenol AF (BPAF) were associated with decreased HDL-C levels, with nonlinear associations observed. Vanadium (V), lead (Pb), and silver (Ag) displayed U-shaped dose-response relationships with most lipid profiles. Multi-contaminant analyses indicated positive trends between contaminants mixture and total cholesterol (TC), triglycerides (TG), low density lipoprotein cholesterol (LDL-C), and non-high-density lipoprotein cholesterol (non-HDL-C). The interaction analyses showed that Se-Fe exhibited synergistic effects on LDL-C and non-HDL-C, and Se-Sn showed a synergistic effect on HDL-C.

CONCLUSIONS

Our study suggested that exposure to metals and bisphenols was associated with changes in lipid levels, and demonstrated their combined and interactive effects.

Identifying heavy metal sources and health risks in soil-vegetable systems of fragmented vegetable fields based on machine learning, positive matrix factorization model and Monte Carlo simulation

Urban fragmented vegetable fields offer fresh produce but pose a potential risk of heavy metal (HM) exposure. Thus, this study investigated HM sources and health risks in the soil-vegetable systems of Chongqing's central urban area. Results indicated that Cd was the primary pollutant, with 28.33 % of soil samples exceeding the screening value. Amaranth was particularly problematic, exceeding thresholds for Cd, Hg, and Cr, and both amaranth and celery showed significantly higher HM accumulation (p < 0.05). The HM pollution level in the soil-vegetable system was moderate or above. The sources of HMs identified via Positive matrix factorization (PMF) model included agricultural activities (18.19 %), natural soil parent material (25.88 %), mixed metal smelting and transportation (30.72 %), and coal combustion (25.21 %). Furthermore, evaluations using the Random Forest (RF) model revealed an intricate interaction of factors influencing the presence of HMs, where enterprise density, population density, and road density played significant roles in HMs accumulation. Monte Carlo assessments revealed higher non-carcinogenic risks for children (Pb, As) and greater carcinogenic risks for adults (Cd). Therefore, the issue of HM pollution in soils and vegetables from fragmented fields in industrial urban areas need attention, given the potential for elevated health risks with long-term vegetable consumption.

Pollution characteristics and quantitative source apportionment of heavy metals within a zinc smelting site by GIS-based PMF and APCS-MLR models

The abandoned smelters present a substantial pollution threat to the nearby soil and groundwater. In this study, 63 surface soil samples were collected from a zinc smelter to quantitatively describe the pollution characteristics, ecological risks, and source apportionment of heavy metal(loid)s (HMs). The results revealed that the average contents of Zn, Cd, Pb, As, and Hg were 0.4, 12.2, 3.3, 5.3, and 12.7 times higher than the risk screening values of the construction sites, respectively. Notably, the smelter was accumulated heavily with Cd and Hg, and the contribution of Cd (0.38) and Hg (0.53) to ecological risk was 91.58%. ZZ3 and ZZ7 were the most polluted workshops, accounting for 25.7% and 35.0% of the pollution load and ecological risk, respectively. The influence of soil parent materials on pollution was minor compared to various workshops within the smelter. Combined with PMF, APCS-MLR and GIS analysis, four sources of HMs were identified: P1(25.5%) and A3(18.4%) were atmospheric deposition from the electric defogging workshop and surface runoff from the smelter; P2(32.7%) and A2(20.9%) were surface runoff of As-Pb foul acid; P3(14.5%) and A4(49.8%) were atmospheric deposition from the leach slag drying workshop; P4(27.3%) and A1(10.8%) were the smelting process of zinc products. This paper described the distribution characteristics and specific sources of HMs in different process workshops, providing a new perspective for the precise remediation of the smelter by determining the priority control factors.

Serum metabolic changes link metal mixture exposures to vascular endothelial inflammation in residents living surrounding rivers near abandoned lead-zinc mines

Metal exposure is associated with vascular endothelial inflammation, an early pathological phenotype of atherosclerotic cardiovascular events. However, the underlying mechanism linking exposure, metabolic changes, and outcomes remains unclear. We aimed to investigate the metabolic changes underlying the associations of chronic exposure to metal mixtures with vascular endothelial inflammation. We recruited 960 adults aged 20-75 years from residential areas surrounding rivers near abandoned lead-zinc mine and classified them into river area and non-river area exposure groups. Urine levels of 25 metals, Framingham risk score (FRS), and serum concentrations of intercellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1), as biomarkers of vascular endothelial inflammation, were assessed. A "meet-in-the-middle" approach was applied to identify causal intermediate metabolites and metabolic pathways linking metal exposure to vascular endothelial inflammation in representative metabolic samples from 64 participants. Compared to the non-river area exposure group, the river area exposure group had significantly greater urine concentrations of chromium, copper, cadmium, and lead; lower urine concentrations of selenium; elevated FRS; and increased concentrations of ICAM-1 and VCAM-1. In total, 38 differentially abundant metabolites were identified between the river area and non-river area exposure groups. Among them, 25 metabolites were significantly associated with FRS, 8 metabolites with ICAM-1 expression, and 10 metabolites with VCAM-1 expression. Furthermore, fructose, ornithine, alpha-ketoglutaric acid, urea, and cytidine monophosphate, are potential mediators of the relationship between metal exposure and vascular endothelial inflammation. Additionally, the metabolic changes underlying these effects included changes in arginine and proline metabolism, pyrimidine metabolism, starch and sucrose metabolism, galactose metabolism, arginine biosynthesis, and alanine, aspartate, and glutamate metabolism, suggesting the disturbance of amino acid metabolism, the tricarboxylic acid cycle, nucleotide metabolism, and glycolysis. Overall, our results reveal biomechanisms that may link chronic exposure to multiple metals with vascular endothelial inflammation and elevated cardiovascular risk.

Associations between blood nickel and lung function in young Chinese: An observational study combining epidemiology and metabolomics

Prior research has explored the relationship between occupational exposure to nickel and lung function. Nonetheless, there is limited research examining the correlation between blood nickel levels and lung function among young adults in the general population. The metabolomic changes associated with nickel exposure have not been well elucidated. On August 23, 2019, we enrolled 257 undergraduate participants from the Chinese Undergraduates Cohort to undergo measurements of blood nickel levels and lung function. The follow-up study was conducted in May 2021. A linear mixed-effects model was employed to assess the relationship between blood nickel levels and lung function. We also conducted stratified analyses by home address. In addition, in order to explore the biological mechanism of lung function damage caused by nickel exposure, we performed metabolomic analyses of baseline serum samples (N = 251). Both analysis of variance and mixed linear effect models were utilized to assess the impact of blood nickel exposure on metabolism. Our findings from cross-sectional and cohort analyses revealed a significant association between blood nickel levels and decreased forced expiratory volume in the first second (FEV1) and forced vital capacity (FVC) among young adults in the general population. Furthermore, we found stronger associations in urban areas. In metabolomics analysis, a total of nine metabolites were significantly changed under blood nickel exposure. The changed metabolites were mainly enriched in six pathways including carbohydrate, amino acid, and cofactor vitamin metabolism. These metabolic pathways involve inflammation and oxidative stress, indicating that high concentrations of nickel exposure can cause inflammation and oxidative stress by disrupting the above metabolism of the body.

CDR1, a DUF946 domain containing protein, positively regulates cadmium tolerance in Arabidopsis thaliana by maintaining the stability of OPT3 protein

Industrial and agricultural production processes lead to the accumulation of cadmium (Cd) in soil, resulting in crops absorb Cd from contaminated soil and then transfer it to human body through the food chain, posing a serious threat to human health. Thus, it is necessary to explore novel genes and mechanisms involved in regulating Cd tolerance and detoxification in plants. Here, we found that CDR1, a DUF946 domain containing protein, localizes to the plasma membrane and positively regulates Cd stress tolerance. The cdr1 mutants exhibited Cd sensitivity, accumulated excessive Cd in the seeds and roots, but decreased in leaves. However, CDR1-OE transgenic plants not only showed Cd tolerance but also significantly reduced Cd in seeds and roots. Additionally, both in vitro and in vivo assays demonstrated an interaction between CDR1 and OPT3. Cell free protein degradation and OPT3 protein level determination assays indicated that CDR1 could maintain the stability of OPT3 protein. Moreover, genetic phenotype analysis and Cd content determination showed that CDR1 regulates Cd stress tolerance and affect the distribution of Cd in plants by maintaining the stability of OPT3 protein. Our discoveries provide a key candidate gene for directional breeding to reduce Cd accumulation in edible seeds of crops.

Enhanced Cu2+ and Cd2+ removal by a novel co-pyrolysis biochar derived from sewage sludge and phosphorus tailings: adsorption performance and mechanisms

The reutilization of municipal wastes has always been one of the hottest subjects of sustainable development study. In this study, a novel biochar co-pyrolyzed from municipal sewage sludge and phosphorus tailings was produced to enhance the adsorption performance of the composite on Cu2+ and Cd2+. The maximum Cu2+ and Cd2+ adsorption capacity of SSB-PT were 44.34 and 45.91 mg/g, respectively, which were much higher than that of sewage sludge biochar (5.21 and 4.58 mg/g). Chemisorption dominated the whole adsorption process while multilayer adsorption and indirect interaction were also involved. According to the result of X-ray diffraction (XRD), Fourier transform infrared (FT-IR) spectroscopy and X-ray photoelectron spectrum (XPS), the load of CO32-, Mg2+, and Ca2+ on the surface of SSB-PT enhanced the precipitation and ion exchange effect. Posnjakite and CdCO3 were formed after the adsorption of Cu2+ and Cd2+, respectively. Besides, complexation, and metal-π interaction were also involved during the adsorption process. Therefore, this study offered a promising method to reuse sewage sludge and phosphorus tailings as an effective adsorbent.

Advances in immunology of male reproductive toxicity induced by common environmental pollutants

Humans are exposed to an ever-increasing number of environmental toxicants, some of which have gradually been identified as major risk factors for male reproductive health, even associated with male infertility. Male infertility is usually due to the reproductive system damage, which may be influenced by the exposure to contaminants such as heavy metals, plasticizers, along with genetics and lifestyle. Testicular immune microenvironment (TIM) is important in maintaining normal physiological functions of the testis, whether disturbed TIM after exposure to environmental toxicants could induce reproductive toxicity remains to be explored. Therefore, the current review aims to contribute to the further understanding of exposure and male infertility by characterizing environmental exposures and the effect on TIM. We first summarized the male reproductive toxicity phenotypes induced by common environmental pollutants. Contaminants including heavy metals and plastic additives and fine particulate matter (PM2.5), have been repetitively associated with male infertility, whereas emerging contaminants such as perfluoroalkyl substances and micro(nano)plastics have also been found to disrupt TIM and lead to male reproductive toxicity. We further reviewed the importance of TIM and its homeostasis in maintaining the normal physiological functions of the testis. Most importantly, we discussed the advances in immunology of male reproductive toxicity induced by metals and metalloids, plastic additives, persistent organic pollutants (POPs), micro(nano)plastic and PM2.5 to suggest the importance of reproductive immunotoxicology in the future study of environmental toxicants, but also contribute to the development of effective prevention and treatment strategies for mitigating adverse effects of environmental pollutants on human health.

Comparative assessment of pantothenic, aspartic, ascorbic and tartaric acids assisted Pb-phytoextraction by sunflower (Helianthus annuus L.)

Phytoextraction of lead (Pb) is a challenging task due to its extremely low mobility within soil and plant systems. In this study, we tested the influence of some novel chelating agents for Pb-phytoextraction using sunflower. The Pb was applied at control (0.0278 mM) and 4.826 mM Pb as Pb(NO3)2 through soil-spiking. After 10 days of Pb addition, four different organic ligands (aspartic, ascorbic, tartaric, and pantothenic acids) were added to the soil at 1 mM concentration each. respectively. In the absence of any chelate, sunflower plants grown at 4.826 mM Pb level accumulated Pb concentrations up to 104 µg g-1 DW in roots, whereas 64 µg g-1 DW in shoot. By contrast, tartaric acid promoted significantly Pb accumulation in roots (191 µg g-1 DW; + 45.5%) and shoot (131.6 µg g-1 DW; + 51.3%). Pantothenic acid also resulted in a significant Pb-uptake in the sunflower shoots (123 µg g-1 DW; + 47.9%) and in roots (177.3 µg g-1 DW; + 41.3%). The least effective amongst the chelates tested was aspartic acid, but it still contributed to + 40.1% more Pb accumulation in the sunflower root and shoots. In addition, plant growth, biochemical, and ionomic parameters were positively regulated by the organic chelates used. Especially, an increase in leaf Ca, P, and S was evident in Pb-stressed plants in response to chelates. These results highlight that the use of biocompatible organic chelates positively alters plant physio-biochemical traits contributing to higher Pb-sequestration in sunflower plant parts.

Hazards of toxic metal(loid)s: Exploring the ecological and health risk in soil-crops systems with long-term sewage sludge application

Sewage sludge (SS) is commonly used as agricultural fertilizer worldwide. However, the toxic metal(loid)s in SS raises concerns about soil contamination and the potential risks to human health. This study, conducted since 2007 on the North China Plain, examines the impact of SS use on crops. An experiment was designed with five treatments: conventional fertilization (CK) and four levels of SS application (W1, W2, W3, and W4: 4.5, 9.0, 18.0, and 36.0 t ha-1, respectively). Soil concentrations of eight toxic metal(loid)s (Zn, Cu, Cr, Cd, Ni, Pb, As, and Hg) were analyzed to assess pollution risk using various indices. Health risks associated with maize and wheat grains were also evaluated. Additionally, the impact of long-term SS application on crop yield, soil quality, and human health within a wheat-maize rotation system was examined. SS application increased wheat and maize yields by 5.37 to 19.08 % and 6.97 to 17.94 %, respectively, across treatments W2 to W4. Despite the toxic metal(loid)s in the grains remaining within safe limits, their concentrations showed an upward trend, especially under the W4 treatment. Moreover, SS application significantly increased the soil Zn, Cu, Cr, Cd, Pb, and Hg levels (P < 0.05) without exceeding the national standards. The geo-accumulation index values revealed rising pollution levels for Zn, Cu, Cd, and Hg, which shifted from no contamination to moderate contamination and then to moderate-to-high contamination, yet the overall pollution level remained safe. Soil ecological risks increased from moderate to serious, with Hg posing the greatest risk, particularly under the W4 treatment. Long-term crop intake from the area significantly exposed children and adults to As, contributing 42.12 % and 34.62 % to hazard index (HI), respectively. The HI values for toxic metal(loid)s in these grains surpassed one in both age groups, suggesting health risks from long-term SS cultivated crops.

Bayesian multivariate receptor model and convolutional neural network to identify quantitative sources and spatial distributions of potentially toxic elements in soils: A case study in Qingzhou City, China

Determining sources and spatial distributions of potentially toxic elements (PTEs) is a crucial issue of soil pollution survey. However, uncertainty estimation for source contributions remains lack, and accurate spatial prediction is still challenging. Robust Bayesian multivariate receptor model (RBMRM) was applied to the soil dataset of Qingzhou City (8 PTEs in 429 samples), to calculate source contributions with uncertainties. Multi-task convolutional neural network (MTCNN) was proposed to predict spatial distributions of soil PTEs. RBMRM afforded three sources, consistent with US-EPA positive matrix factorization. Natural source dominated As, Cr, Cu, and Ni contents (78.5 %∼86.1 %), and contributed 37.1 %, 61.0 %, and 65.9 % of Cd, Pb, and Zn, exhibiting low uncertainties with uncertainty index (UI) < 26.7 %. Industrial, traffic, and agricultural sources had significant influences on Cd, Pb, and Zn (30.2 %∼61.9 %), with UI < 39.3 %. Hg originated dominantly from atmosphere deposition (99.1 %), with relatively high uncertainties (UI=87.7 %). MTCNN acquired satisfactory accuracies, with R2 of 0.357-0.896 and nRMSE of 0.092-0.366. Spatial distributions of As, Cd, Cr, Cu, Ni, Pb, and Zn were influenced by parent materials. Cd, Hg, Pb, and Zn showed significant hotspot in urban area. This work conducted a new approach exploration, and practical implications for soil pollution regulation were proposed.

Effects of exogenous copper on microbial metabolic function and carbon use efficiency of Panax notoginseng planting soil

Soil copper (Cu) pollution is a serious environmental risk in the Panax notoginseng planting area. However, the effect of Cu on soil microbial metabolism and nutrient cycling in this area remains unknown. Therefore, Biolog ECO-plate and enzyme stoichiometry methods were utilized in this study to investigate the impact of exogenous Cu (control: 0 mg·kg-1; Cu100: 100 mg·kg-1; Cu400: 400 mg·kg-1; and Cu600: 600 mg·kg-1) on the metabolic function of soil microbial and nutrient limitation in the P. notoginseng soil. The results indicated that Cu100 significantly increased soil organic carbon (SOC), total phosphorus (TP), soil C:N, microbial biomass carbon (MBC), and microbial biomass nitrogen (MBN) 9.89%, 15.65%, 17.91%, 61.87%, and 90.56% higher than the control, respectively. Moreover, the carbon source utilization ratio of carbohydrates, amino acids, and amphiphilic compounds of Cu100 also increased by 7.16%, 25.47%, and 84.68%, respectively, compared with the control. The activities of β-1,4-glucosidase, cellobiohyrolase, leucine amino peptidase, β-1,4-N-acetylglucosaminidase, and phosphatase significantly decreased with increasing Cu concentration. Soil enzyme stoichiometry showed that all treatments were limited by nitrogen (vector angle < 45°; 19.045-22.081). Cu600 led to the lowest carbon limitation (1.798) and highest carbon use efficiency (CUE:0.267). The PLS-SEM model also showed that MBC, MBN, MBP, and microbial diversity positively affected carbon and nitrogen limitation (0.654 and 0.424). Soil carbon, nitrogen, phosphorus, stoichiometric ratio, MBC, MBN, and MBP positively affected CUE (0.527 and 0.589). The microbial diversity index significantly negatively affected CUE (-1.490). Multiple linear stepwise regression analyses showed that CUE was mainly influenced by MBC, AP, C:P, and LAP. Thus, P. notoginseng soil can benefit soil microbial carbon and nitrogen limitations at low Cu concentrations. Clarifying the metabolic activity and nutritional status of microorganisms under Cu stress can provide some theoretical basis for realizing China's comprehensive and effective management and control policies for environmental risks from metals by 2035.

Assessment of the migration characteristics and source-oriented health risks of heavy metals in the soil and groundwater of a legacy contaminated by the chlor-alkali industry in central China

The chlor-alkali industry (CAI) is crucial for global chemical production; however, its operation has led to widespread heavy metal (HM) contamination at numerous sites, which has not been thoroughly investigated. This study analysed 122 soil and groundwater samples from a typical CAI site in Kaifeng, China. Our aim was to assess the ecological and health risks, identify the sources, and examine the migration characteristics of HMs at this site using Monte Carlo simulation, absolute principal component score-multiple linear regression (APCS-MLR), and the potential environmental risk index (Ei). Our findings revealed that the exceedance rates for Cd, Pb, Hg, and Ni were 71.96%, 45.79%, 49.59%, and 65.42%, respectively. Mercury (Hg) displayed the greatest coefficient of variation across all the soil layers, indicating a significant anthropogenic influence. Cd and Hg were identified as having high and extremely high potential environmental risk levels, respectively. The spatial distributions of the improved Nemerow index (INI), total ecological risk (Ri), and HM content varied considerably, with the most contaminated areas typically associated with the storage of raw and auxiliary materials. Surface aggregation and significant vertical transport were noted for HMs; As and Ni showed substantial accumulation in subsoil layers, severely contaminating the groundwater. Self-organizing maps categorized the samples into two different groups, showing strong positive correlations between Cd, Pb, and Hg. The APCS-MLR model suggested that industrial emissions were the main contributors, accounting for 60.3% of the total HM input. Elevated hazard quotient values for Hg posed significant noncarcinogenic risks, whereas acceptable levels of carcinogenic risk were observed for both adults (96.60%) and children (97.83%). This study significantly enhances historical CAI pollution data and offers valuable insights into ongoing environmental and health challenges.

The Cd resistant mechanism of Proteus mirabilis Ch8 through immobilizing and detoxifying

Cadmium (Cd) pollution is a serious global environmental problem, which requires a global concern and practical solutions. Microbial remediation has received widespread attention owing to advantages, such as environmental friendliness and soil amelioration. However, Cd toxicity also severely deteriorates the remediation performance of functional microorganisms. Analyzing the mechanism of bacterial resistance to Cd stress will be beneficial for the application of Cd remediation. In this study, the bacteria strain, up to 1400 mg/L Cd resistance, was employed and identified as Proteus mirabilis Ch8 (Ch8) through whole genome sequence analyses. The results indicated that the multiple pathways of immobilizing and detoxifying Cd maintained the growth of Ch8 under Cd stress, which also possessed high Cd extracellular adsorption. Firstly, the changes in surface morphology and functional groups of Ch8 cells were observed under different Cd conditions through SEM-EDS and FTIR analyses. Under 100 mg/L Cd, Ch8 cells exhibited aggregation and less flagella; the Cd biosorption of Ch8 was predominately by secreting exopolysaccharides (EPS) and no significant change of functional groups. Under 500 mg/L Cd, Ch8 were present irregular polymers on the cell surface, some cells with wrapping around; the Cd biosorption capacity exhibited outstanding effects (38.80 mg/g), which was mainly immobilizing Cd by secreting and interacting with EPS. Then, Ch8 also significantly enhanced the antioxidant enzyme activity and the antioxidant substance content under different Cd conditions. The activities of SOD and CAT, GSH content of Ch8 under 500 mg/L Cd were significantly increased by 245.47%, 179.52%, and 241.81%, compared to normal condition. Additionally, Ch8 significantly induced the expression of Acr A and Tol C (the resistance-nodulation-division (RND) efflux pump), and some antioxidant genes (SodB, SodC, and Tpx) to reduce Cd damage. In particular, the markedly higher expression levels of SodB under Cd stress. The mechanism of Ch8 lays a foundation for its application in solving soil remediation.

Environmental pollution and human health risk due to tailings storage facilities in China

Tailings storage facilities (TSFs) represent an anthropogenic source of pollution, resulting in potential risks to both environmental integrity and human health. To date, the environmental and human health risks from TSFs in China have been under-researched. This study attempts to address this gap by developing, and geo-statistically analyzing two comprehensive databases. The first database (I) focuses on failed TSFs; we supply the statistics of environmental damages from 143 TSF failure incidents. Notably, approximately 75 % of the failure incidents involved tailings flows released into water bodies, resulting in a significant exacerbation of environmental pollution. To better inform ecological and human health risks, we present another database (II) for 147 non-failed TSFs to investigate the soil heavy metal contamination, considering 8 heavy metals. The findings reveal that (i) Cd, Pb, and Hg are the prominent pollutants across the non-failed TSF sites in China; (ii) lead‑zinc and tungsten mine tailings storage sites exhibit the most severe pollution; (iii) Pb, Cd, and Ni present noteworthy non-carcinogenic risks to human health; (iv) >85 % of TSF sites pose carcinogenic risks associated with arsenic; and (v) health risks resulting from dermal absorption surpass ingestion for the majority of heavy metals, with the exception of Pb, where ingestion presents a more pronounced route of exposure. Our study presents a comprehensive evaluation of environmental and human health risks due to TSFs, highlighting the necessity for risk assessment of >14,000 existing TSFs in China.

A Bibliometric Analysis on Research Progress of Earthworms in Soil Ecosystems

The earthworm, as a soil engineer, plays highly important roles in the soil ecosystem for shaping soil structure, promoting soil fertility, regulating microbial community composition and activities and decomposing soil pollutants. However, the research progresses on this important soil fauna have rarely been reviewed so far. Therefore, we conducted a bibliometric analysis of the literature published during 1900-2022, which was collected from the Web of Science Core Collection (WoS). The results showed that three periods (1900-1990, 1991-2005 and 2006-2022) could be identified in terms of the intensity of publications on the topic, and the number of publications kept increasing since 2006. The United States produced the highest publication record at the country scale, whereas Chinese Academy of Sciences was the most productive institution. Chinese institutions and authors played an active and prominent role during 2018-2022. Soil Biology & Biochemistry was the most popular journal for the topic-related research. In these publications, Professor Lavelle P was the most influential author. Based on a citation network of the top 50 cited papers, four hotspots were identified, i.e., the ecological effects of earthworms, the impact of agricultural activities on earthworms, earthworm ecotoxicology and earthworm invasion. Moreover, "impact", "biodiversity", "oxidative stress", "diversity", "response", "Eisenia fetida" and "exposure" were the emerging and active topics in recent years. This study can help us to better understand the relevant subject categories, journals, countries, institutions, authors and articles and identify the research hotspots and emerging trends in the field of soil earthworm research.

Rapid Determination of Cr3+ and Mn2+ in Water Using Laser-Induced Breakdown Spectroscopy Combined with Filter Paper Modified with Gold Nanoclusters

Excessive emissions of heavy metals not only cause environmental pollution but also pose a direct threat to human health. Therefore, rapid and accurate detection of heavy metals in the environment is of great significance. Herein, we propose a method based on laser-induced breakdown spectroscopy (LIBS) combined with filter paper modified with bovine serum albumin-protected gold nanoclusters (LIBS-FP-AuNCs) for the rapid and sensitive detection of Cr3+ and Mn2+. The filter paper modified with AuNCs was used to selectively enrich Cr3+ and Mn2+. Combined with the multi-element detection capability of LIBS, this method achieved the simultaneous rapid detection of Cr3+ and Mn2+. Both elements showed linear ranges for concentrations of 10-1000 μg L-1, with limits of detection of 7.5 and 9.0 μg L-1 for Cr3+ and Mn2+, respectively. This method was successfully applied to the determination of Cr3+ and Mn2+ in real water samples, with satisfactory recoveries ranging from 94.6% to 105.1%. This method has potential application in the analysis of heavy metal pollution.

Effects of remediation agents on rice and soil in toxic metal(loid)s contaminated paddy fields: A global meta-analysis

Toxic metal(loid)s contamination of paddy soil is a nonnegligible issue and threatens food safety considering that it is transmitted via the soil-plant system. Applying remediation agents could effectively inhibit the soil available toxic metal(loid)s and reduce their accumulation in rice. To comprehensively quantify how remediation agents impact the accumulation of Cd/Pb/As in rice, rice growth and yield, the accumulation of available Cd/Pb/As in paddy soil, and soil characteristics, 50 peer-reviewed publications were selected for meta-analysis. Overall, the application of remediation agents exhibited significant positive effects on rice plant length (ES = 0.05, CI = 0.01-0.08), yield (ES = 0.20, CI = 0.13-0.27), peroxidase (ES = 0.56, CI = 0.18-0.31), photosynthetic rate (ES = 0.47, CI = 0.34-0.61), and respiration rate (ES = 0.68, CI = 0.47-0.88). Among the different types of remediation agents, biochar was the most effective in controlling the accumulation of Cd/Pb/As in all portions of rice, and was also superior in inhibiting the accumulation of Pb in rice grains (ES = -0.59, 95 % CI = -1.04-0.13). This study offers an essential contribution for the remediation strategies of toxic metal(loid)s contaminated paddy fields.

Risk-based imprecise post-remediation soil quality objectives

While risk-based contaminated land management is an essential component of sustainable remediation, uncertainty is an unavoidable aspect of risk assessment, since most of the parameters that influence risk are typically affected by uncertainty. Uncertainty may be of different origins; i.e., stochastic or epistemic. Stochastic (or aleatoric) uncertainty arises from random variability related to natural processes, while epistemic uncertainty arises from the incomplete/imprecise nature of available information. But the latter is rarely considered in risk assessments, with the result that risk-based soil quality objectives are almost invariably presented as precise (unique) threshold values. In this paper it is shown: (i) how the joint treatment of stochastic and epistemic uncertainty in risk assessment can lead to soil quality objectives presented as intervals rather than precise values and (ii) how this provides an upper risk-based safeguard for post-remediation monitoring values. The proposed method is illustrated by a real case of soils contaminated by arsenic located in the North-East of France. At this site steel manufacturers have gradually filled up a small valley with slag and dust, over more than a century. These materials are enriched in various metal(loid)s, including arsenic and lead. As the environmental authority has asked for a conversion of the site to other uses that may involve access by the general public, an investigation of human health risk was performed based on a sampling campaign and chemical characterizations including various types of extractions and an analysis of bioaccessibility. While further investigations are required to improve the bioaccessibility model, the human health risk presented herein shows how partial or imprecise information can be incorporated in the analysis while taking into account underlying uncertainties.

Pollution levels and probability risk assessment of potential toxic elements in soil of Pb-Zn smelting areas

Soil pollution around Pb-Zn smelters has attracted widespread attention around the world. In this study, we compiled a database of eight potentially toxic elements (PTEs) Pb, Zn, Cd, As, Cr, Ni, Cu, and Mn in the soil of Pb-Zn smelting areas by screening the published research papers from 2000 to 2023. The pollution assessment and risk screening of eight PTEs were carried out by geo-accumulation index (Igeo), potential ecological risk index (PERI) and health risk assessment model, and Monte Carlo simulation employed to further evaluate the probabilistic health risks. The results suggested that the mean values of the eight PTEs all exceeded the corresponding values in the upper crust, and more than 60% of the study sites had serious Pb and Cd pollution (Igeo > 4), with Brazil, Belgium, China, France and Slovenia having higher levels of pollution than other regions. Besides, PTEs in smelting area caused serious ecological risk (PERI = 10912.12), in which Cd was the main contributor to PREI (86.02%). The average hazard index (HI) of the eight PTEs for adults and children was 7.19 and 9.73, respectively, and the average value of total carcinogenic risk (TCR) was 4.20 × 10-3 and 8.05 × 10-4, respectively. Pb and As are the main contributors to non-carcinogenic risk, while Cu and As are the main contributors to carcinogenic risk. The probability of non-carcinogenic risk in adults and children was 84.05% and 97.57%, while carcinogenic risk was 92.56% and 79.73%, respectively. In summary, there are high ecological and health risks of PTEs in the soil of Pb-Zn smelting areas, and Pb, Cd, As and Cu are the key elements that cause contamination and risk, which need to be paid attention to and controlled. This study is expected to provide guidance for soil remediation in Pb-Zn smelting areas.

Analysis of heavy metal and polycyclic aromatic hydrocarbon pollution characteristics of a typical metal rolling industrial site based on data mining

With the transformation and upgrading of industries, the environmental problems caused by industrial residual contaminated sites are becoming increasingly prominent. Based on actual investigation cases, this study analyzed the soil pollution status of a remaining sites of the copper and zinc rolling industry, and found that the pollutants exceeding the screening values included Cu, Ni, Zn, Pb, total petroleum hydrocarbons and 6 polycyclic aromatic hydrocarbon monomers. Based on traditional analysis methods such as the correlation coefficient and spatial distribution, combined with machine learning methods such as SOM + K-means, it is inferred that the heavy metal Zn/Pb may be mainly related to the production history of zinc rolling. Cu/Ni may be mainly originated from the production history of copper rolling. PAHs are mainly due to the incomplete combustion of fossil fuels in the melting equipment. TPH pollution is speculated to be related to oil leakage during the industrial use period and later period of vehicle parking. The results showed that traditional analysis methods can quickly identify the correlation between site pollutants, while SOM + K-means machine learning methods can further effectively extract complex hidden relationships in data and achieve in-depth mining of site monitoring data.

Integrated assessment of the pollution and risk of heavy metals in soils near chemical industry parks along the middle Yangtze River

Industrialization in riparian areas of critical rivers has caused significant environmental and health impacts. Taking eight industrial parks along the middle Yangtze River as examples, this study proposes a multiple-criteria approach to investigate soil heavy metal pollution and associated ecological and health risks posed by industrial activities. Aiming at seven heavy metals, the results show that nickel (Ni), cadmium (Cd), and copper (Cu) exhibited the most significant accumulation above background levels. The comprehensive findings from Pearson correlation analysis, cluster analysis, principal component analysis, and industrial investigation uncover the primary sources of Cd, arsenic (As), mercury (Hg), and lead (Pb) to be chemical processing, while Ni and chromium (Cr) are predominantly derived from mechanical and electrical equipment manufacturing. In contrast, Cu exhibits a broad range of origins across various industrial processes. Soil heavy metals can cause serious ecological and carcinogenic health risks, of which Cd and Hg contribute to >70 % of the total ecological risk, and As contributes over 80 % of the total health risk. This study highlights the importance of employing multiple mathematical and statistical models in determining and evaluating environmental hazards, and may aid in planning the environmental remediation engineering and optimizing the industry standards.

The leaching behavior of heavy metal from contaminated mining soil: The effect of rainfall conditions and the impact on surrounding agricultural lands

Contaminated mining soils could lead to heavy metal pollution of surrounding farmlands under rainfall conditions. With the aids of sequential extraction, batch leaching, and dynamic leaching experiments, this study was carried out to investigate the characteristics of heavy metals in contaminated mining soils, understand their leaching behavior under different rainfall conditions, and evaluate the potential effects on surrounding farmlands. The results indicated that the concentrations of heavy metals (Cr, Ni, Cu, Zn, As, Cd, and Pb) in the contaminated mining soils were several or even twenty times higher than their corresponding background values, and Cd, Zn, Cu and Pb had considerable proportions (>50 %) in mobile forms. The leaching amounts of heavy metals from the contaminated mining soils had positive correlation with their contents in acid soluble form, and showed strong dependence on rainfall pH conditions. Acid rainfalls (pH = 4.32) can greatly increase the average annual release of Cd, Zn, Cu and Pb from mine soils in the study area, with increments ranging from 72.4 % (Pb) to 85.9 % (Cd) compared to those under alkaline conditions (pH = 7.42). The leaching of heavy metals was well fitted by two-constant, pseudo second-order and parabolic equations, indicating that their multi-layer sorption/desorption behavior on soil surface was dominated by chemical processes and their release was controlled by the diffusion within the soil pore channels. The two-column leaching experiment showed that the metal-rich leachate can lead to obvious increments of heavy metals in non-residual fractions (in particular Cd in acid soluble form) in surrounding farmlands, which would significantly raise the potential ecological risk associated with heavy metals. These findings indicate the importance of contaminated mining soils as a long-term source of heavy metals and the needs for mitigating the releases of toxic elements, especially in areas with heavy acid precipitation.

Inverse vulcanization induced oxygen modified porous polysulfides for efficient sorption of heavy metals

The applications of polysulfides derived from natural plant oil and sulfur via the inverse vulcanization in the removal of heavy metals from aqueous solutions suffered from their low porosity and scarce surface functionality because of their hydrophobic surfaces and bulk characteristics. In this study, polysulfides from sulfur and palm oil (PSPs) with significantly enhanced porosity (13.7-24.1 m2/g) and surface oxygen-containing functional groups (6.9-8.6 wt.%) were synthesized with the optimization of process conditions including reaction time, temperature, and mass ratios of sulfur/palm oil/NaCl/sodium citrate. PSPs were applied as sorbents to remove heavy metals present in aqueous solutions. The integration of porosity and oxygen modification allowed a fast kinetic (4.0 h) and enhanced maximum sorption capacities for Pb(II) (218.5 mg/g), Cu(II) (74.8 mg/g), and Cr(III) (68.4 mg/g) at pH 5.0 and T 298 K comparing with polysulfides made without NaCl/sodium citrate. The sorption behaviors of Pb(II), Cu(II), and Cr(III) on PSPs were highly dependent on the solution pH values and ionic strength. The sorption presented excellent anti-interference capability for the coexisting cations and anions. The sorption processes were endothermic and spontaneous. This work would guide the preparation of porous polysulfides with surface modification as efficient sorbents to remediate heavy metals from aqueous solutions.