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

Soil quality, risk assessment and source identification of heavy metals in native and improved paddy soil and rice grains from Tamil Nadu, India

The present study aims to assess the soil quality, source analysis, and risk assessment of heavy metals in native and improved rice paddies in Tamil Nadu, India. The mean values of DTPA-extractable heavy metal levels in native paddy soil were 0.06, 0.52, 2.61, 3.15, 0.48, 39.48, 97.61 mg kg-1, while improved paddy soil had values of 0.11, 1.98, 0.91, 3.21, 1.54, 20.30, 7.78 mg kg-1 for Cd, Pb, Ni, Cu, Zn, Fe and Mn. These levels were below the acceptable limits set by Indian and European Union soil quality guidelines. All native rice varieties had grain Pb concentration ranging from 0.71 to 1.34 mg kg-1, but all improved rice varieties had higher levels of Cd, Pb, and Fe then prescribed limits. Nemerow pollution index (NPI) level of Ni indicated high pollution in native soil. Potential ecological risk index (RI) values of Cd indicated moderate risk in improved soil. Based on the EF and TF values, the paddy fields and rice plants are classified as 'severe enrichment' and 'accumulator' of heavy metals (Cd and Pb), respectively. The HI and THQ levels (Ni, Cd and Pb) were > 1 for both adults and children. Principal component analysis (PCA) found that PC1 eigenvalue of 5.63 (40.21%) and 6.91 (49.37%) and PC2 with 4.84 eigenvalue of 5.63 (34.56%) and 3.97 (28.37%) for native and improved soil, respectively, while cluster analysis (CA) revealed three distinct groups between the metals studied.

Physiological Adaptations of Vigna radiata to Heavy Metal Stress: Soluble Sugar Accumulation and Biomass Enhancement

BACKGROUND

Heavy metal contamination significantly threatens crop growth and global food security. Understanding plant responses to such stress is crucial to developing stress-tolerant crops. This study explores the physiological and biochemical responses of Vigna radiata (L.) R. Wilczek to mercury, lead, and copper stress, focusing on the role of soluble sugar accumulation and biomass enhancement in conferring heavy metal tolerance.

METHODS

Commercially available V. radiata seeds were exposed to varying concentrations (50, 150, and 300 mg/L) of mercurous nitrate, lead nitrate, and copper chloride under controlled conditions. The germination rates, seedling growth, and physiological parameters such as the soluble sugar and protein content were analyzed using spectrophotometry and statistical methods, including ANOVA.

RESULTS

The results demonstrated that lead ion stress significantly increased the seedling dry weight, while all the tested heavy metals promoted soluble sugar accumulation. Although the heavy metals inhibited germination and growth at higher concentrations, Vigna radiata exhibited strong tolerance at moderate stress levels.

CONCLUSION

This study highlights the adaptive strategies of V. radiata, including soluble-sugar-mediated osmotic adjustment and enhanced biomass allocation, which contribute to its resilience under heavy metal stress. These findings provide insights for breeding stress-resistant crops and managing heavy-metal-contaminated environments.

Machine learning-supported determination for site-specific natural background values of soil heavy metals

Heavy metal natural background values play a crucial role in distinguishing anthropogenic sources from natural sources to assess human impacts in polluted areas, thereby accurately formulating environmental policies. However, due to limitations imposed by human activities, research methods, and regional constraints, the determination of heavy metal background values, particularly on site or profile scale, is often challenging, highlighting the urgent need for new methodologies. To establish a comprehensive dataset containing heavy metal concentrations and soil properties, the study systematically collected and screened 82 soil profiles from areas minimally affected by human activities, resulting in a total of 2185 data sets. Using soil depth, pH, organic matter, weathering indices (SAF, BA), Fe2O3, MgO, Na2O, CaO, and K2O as model input variables, the predictive performance for site-specific background levels of Cd, Cr, Cu, Ni, Pb, and Zn was compared across four advanced machine learning models (RF (random forest), XGBoost (extreme gradient boosting), ANN (artificial neural network), SVR (support vector regression)). The results indicated that the optimal model for predicting background values of Cd, Cr, and Ni was XGBoost (MAE = 0.14 - 0.17; MSE = 0.04 - 0.06; R² = 0.82 - 0.87), while RF was used for Cu, Pb, and Zn (MAE = 0.01 - 0.18; MSE = 0.02 - 0.06; R² = 0.89 - 0.95). Importance assessments using RF and SHAP revealed that pH is a key controlling factor for Cd and Ni, Fe2O3 significantly impacts Cr, Cu, and Zn background levels, and K2O is the main controlling factor for Pb. The machine learning models developed can effectively predict the background levels of these six heavy metals based on major elemental and soil physicochemical properties, particularly achieving accurate predictions for Cu and Zn using just two input variables. This machine learning prediction framework is based on major elemental compositions and the physical/chemical properties of soil, enables precise and cost-effective point-to-point environmental assessments, thereby offering significant potential for practical applications.

Exploring environmental risk in soils: Leveraging open data for non-sampling assessment?

Soil contamination by heavy metals (HM) is a critical area of research. Traditional methods involving sample collection and lab analysis are effective but costly and time-consuming. This study explores whether geostatistical analysis with GIS and open data can provide a faster, more precise, and cost-effective alternative for HM contamination assessment without extensive sampling. Concentrations of nine HMs (Cu, Pb, Ni, Co, Mn, As, Cd, Sb, Cr) were analysed from 498 soil samples collected in two mining areas in Portugal: the Panasqueira and Aljustrel mines. Corresponding data were extracted from the Lucas TOPSOIL 1 km raster maps. Several contamination indices, Contamination Factor (Cf), Modified Contamination Degree (mCd), Geoaccumulation Index (Igeo), Nemerow Pollution Index (Pn), Potential Ecological Risk Index (PERI), and Pollution Load Index (PLI) were calculated for both datasets. A confusion matrix was used to evaluate the percentage of correct classifications, while a concordance analysis assessed the alignment of accurately classified points between the two data sources. In the soil samples, very high contamination levels for As were observed in 42% of the samples, according to the Cf, with high levels for Sb found in approximately 30% of the samples. The mCd revealed that approximately 11% of soil samples exhibited very high levels of contamination, while the Pn indicated that 78.9% of the soil samples fell within the seriously polluted domain. Similar contamination trends were observed for the other indices. In contrast, the results for the LUCAS points showed significant discrepancies. No high contamination levels were found for any metal. The misclassification rates for mCd, Pn, PERI, and PLI were 84.25%, 97.55%, 95%, and 82%, respectively, when compared to the field data. This study concludes that while open data raster maps offer rapid overviews, they fall short of providing the detailed precision required for reliable contamination assessments. The significant misclassification rates observed highlight the limitations of relying solely on these tools for critical environmental decisions. Consequently, traditional sampling and laboratory analysis remain indispensable for accurate risk assessments of HM contamination, ensuring a more reliable foundation for decision-making and environmental management.

Evidence of eared doves consumption and the potential toxic exposure during the Regional Development period in Quito-Ecuador

Throughout history, food has played a fundamental role in the development of societies. An understanding of the diets of different cultures and their impact on health can provide valuable insights into their lifestyle. The identification of the animal remains found within two vessels is reported and, in addition, an assessment of whether the diet and soil composition of the period may be associated with toxic elements was carried out. The animal bones retrieved from the settlement, which dated from 25 to 203 cal AD, were identified as belonging to Zenaida cf. auriculata, commonly known as eared dove. Ancient starch was discovered in the sediments inside the vessels. These sediments, along with the pre-Hispanic soil collected in the study zone, showed moderate pollution, suggesting potential environmental contamination. For the first time, evidence that eared doves were part of the diet of the ancient inhabitants of Quito is presented, as shown by the occurrence of their bones within food processing utensils. Furthermore, the study highlights the possibility of environmental contamination due to volcanic eruptions that occurred during the Regional Development period from 500 BC to AD 500. These results can contribute to a better understanding of the living conditions of the early inhabitants of Quito and similar regions.

Source identification of heavy metals and metalloids in soil using open-source Tellus database and their impact on ecology and human health

The presence of heavy metals and metalloids (metal(loid)s) in the food chain is a global problem, and thus, metal(loid)s are considered to be Potentially Toxic Elements (PTEs). Arsenic (As), lead (Pb), mercury (Hg), and cadmium (Cd) are identified as prominent hazards related to human health risks throughout the food chain. This study aimed to carry out a source attribution for metal(loid)s in shallow topsoil of north-midlands, northwest, and border counties of the Republic of Ireland, followed by an assessment of the potential ecological and human health risks. The positive Matrix Factorization (PMF) was used for source characterization of PTEs, followed by the Monte Carlo simulation method, used for a probabilistic model to evaluate potential human health risks. The mean concentrations of prioritized metal(loid)s in the topsoil range in the order of Pb (28.83 mg kg-1) > As (7.81 mg kg-1) > Cd (0.51 mg kg-1) > Hg (0.11 mg kg-1) based on the open-source Tellus dataset. This research identified three primary sources of metal(loid) pollution: geogenic sources (36 %), mixed sources of historical mining and natural origin (33 %), and anthropogenic activities (31 %). The ecological risk assessment showed that Ireland's soil exhibits low-moderate pollution levels however, concerns remain for Cd and As levels. All metal(loid)s except Cd showed acceptable non-carcinogenic risk, while Cd and As accounted for high to moderate potential cancer risks. Potato consumption (if grown on land with elevated metal(loid) levels), Cd concentration in soil, and bioaccumulation factor of Cd in potatoes were the three most sensitive parameters. In conclusion, metal(loid)s in Ireland present low to moderate ecological and human health risks. It underscores the need for policies and remedial strategies to monitor metal(loid) levels in agricultural soil regularly and the production of crops with low bioaccumulation in regions with elevated metal(loid) levels.

Regional disparities and technological approaches in heavy metal remediation: A comprehensive analysis of soil contamination in Asia

Rapid industrialization and urbanization in Asia have significantly increased heavy metal emissions, leading to severe challenges in soil contamination. This review critically examines the diverse sources of heavy metal pollution, regional disparities in contamination levels, and various remediation strategies across Asia. The connections between pollution sources and the resulting heavy metal contamination are explored, with a focus on individual assessments of pollution status in East Asia, South Asia, Southeast Asia, Central Asia, and West Asia. These assessments consider human, geographical, policy, and economic factors. The advantages and limitations of physical, chemical, and biological remediation techniques, as well as their combined applications, are analyzed. Additionally, the importance of regulatory measures, sustainable practices, and public awareness is emphasized for ensuring the long-term health and sustainability of Asian soils. This review aims to contribute to the sustainable development of Asian soils by providing region-specific strategies for the effective remediation of heavy metal contamination.

Analysis of heavy metal and arsenic sources in mangrove surface sediments at Wulishan Port on Leizhou Peninsula, China, using the APCS-MLR model

Mangrove forests are sources and sinks for various pollutants. This study analyzed the current status of heavy metal and arsenic (As) pollution in mangrove surface sediments in rapidly industrializing and urbanizing port cities. Surface sediments of mangroves at Wulishan Port on the Leizhou Peninsula, China, were analyzed using inductively coupled plasma emission spectrometry (ICP-AES) and inductively coupled plasma mass spectrometry (ICP-MS) for the presence of Cr, Pb, Ni, Zn, Cd, Cu, As, and Hg. The Pollution load index, Nemerow pollution index, and Potential ecological risk index were employed to evaluate the pollutant. Multivariate statistical methods were applied for the qualitative analysis of pollutant sources, and the APCS-MLR receptor model was used for quantification. This study indicated the following results: (1) The average content of eight pollutants surpassed the local background level but did not exceed the Marine Sediment Quality standard. The pollution levels across the four sampling areas were ranked as Ⅲ > Ⅳ > Ⅰ > Ⅱ. The area Ⅱ exhibited relatively lower pollution levels with the grain size of the sediments dominated by sand, which was not conducive to pollutant adsorption and enrichment. (2) The factor analysis and cluster analyses identified three primary sources of contamination. As, Cr, Ni, and Pb originated from nearby industrial activities and their associated wastewater, suggesting that the primary source was the industrial source. Cd, Cu, and Zn stem from the cement columns utilized in oyster farming, alongside discharges from mariculture and pig farming, establishing a secondary agricultural source. Hg originated from ship exhaust burning oil and vehicle emissions in the vicinity, representing the third traffic source. (3) The APCS-MLR receptor model results demonstrated industrial, agricultural, and traffic sources contributing 47.19 %, 33.13 %, and 13.03 %, respectively, with 6.65 % attributed to unidentified sources.

Health Risk Assessment of Heavy Metals in Agricultural Soils Based on Multi-Receptor Modeling Combined with Monte Carlo Simulation

The spatial characteristics, pollution sources, and risks of soil heavy metals were analyzed on Hainan Island. The results showed that the heavily polluted points accounted for 0.56%, and the number of mildly and above polluted points accounted for 15.27%, respectively, which were mainly distributed in the northern part of the study area. The principal component analysis-absolute principal component score-multiple linear regression (APCS-MLR) and the positive matrix factorization (PMF) revealed four sources of heavy metals: agricultural pollution sources for cadmium, (Cd), industrial and mining pollution sources for arsenic, (As), transportation pollution sources for zinc and lead (Zn and Pb), and natural pollution sources for chromium, nickel, and copper (Cr, Ni, and Cu). The human health risk assessment indicated that the average non-carcinogenic risk (HI) for both adults and children was within the safe threshold (<1), whereas Cr and Ni posed a carcinogenic risk (CR) to human health. In addition, the total non-carcinogenic risk (THI) indicated that heavy metals posed a potential non-carcinogenic risk to children, while the total carcinogenic risk (TCR) remained relatively high, mainly in the northern part of the study area. The results of the Monte Carlo simulation showed that the non-carcinogenic risk (HI) for all heavy metals was <1, but the total non-carcinogenic risk index (THI) for children was >1, indicating a potential health risk above the safe threshold. Meanwhile, nearly 100% and 99.94% of the TCR values exceeded 1 × 10-4 for children and adults, indicating that Cr and Ni are priority heavy metals for control. The research results provide the necessary scientific basis for the prevention and control of heavy metals in agricultural soils.

High-density sampling of soil heavy metals in the upper Bailang River basin: contamination characteristics, sources, and source-oriented health risk assessment

Heavy metals (HMs) seriously harm soil environment and threaten crop quality and human health. The aim of the study was to investigate the characteristics, quantify the sources and assess the risks of HMs in soil of upper Bailang River Basin (UBRB). The results indicated that the soils in UBRB were at a non-polluted level and posed a low ecological risk to the environment as a whole. The main pollutants were Ni and Cr obtained by indices Pi and Igeo. Based on the consideration of toxicity, the fuzzy comprehensive evaluation model and Ei index revealed that Hg and Cd were dominating pollutants and ecological risk factors of soil in UBRB. The positive matrix factorization model ascertained five potential sources of soil HMs, namely, plastic processing, energy activities, parent material, transportation and agriculture mixed source and industrial manufacturing, with contribution rates of 17%, 7%, 15%, 29% and 32%, respectively. Natural source primarily determined the non-carcinogenic risk for all populations, accounting for about 43% of the total risk. Industrial manufacturing mainly determined the carcinogenic risk, accounting for about 45%. For adults, the risk was acceptable for most of the sample points. For children, potential non-carcinogenic risks were present in 13.19% of the sample sites, which were mainly located in the west, and unacceptable carcinogenic risks were present in 57.21% of the sample sites, which were mainly concentrated in the western and central parts.

Identifying interactive effects of spatial drivers in soil heavy metal pollutants using interpretable machine learning models

The accurate identification of spatial drivers is crucial for effectively managing soil heavy metals (SHM). However, understanding the complex and diverse spatial drivers of SHM and their interactive effects remains a significant challenge. In this study, we present a comprehensive analysis framework that integrates Geodetector, CatBoost, and SHapley Additive exPlanations (SHAP) techniques to identify and elucidate the interactive effects of spatial drivers in SHM within the Pearl River Delta (PRD) region of China. Our investigation incorporated fourteen environmental factors and focused on the pollution levels of three prominent heavy metals: Hg, Cd, and Zn. These findings provide several key insights: (1) The distribution of SHM is influenced by the combined effects of various individual factors and interactions within the source-flow-sink process. (2) Compared with the spatial interpretation of individual factors, the interaction between Hg and Cd exhibited enhanced spatial explanatory power. Similarly, interactions involving Zn mainly demonstrated increased spatial explanatory power, but there was one exception in which a weakening was observed. (3) Spatial heterogeneity plays a crucial role in determining the contributions of environmental factors to soil heavy metal concentrations. Although individual factors generally promote metal accumulation, their effects fluctuate when interactions are considered. (4) The SHAP interpretable method effectively addresses the limitations associated with machine-learning models by providing understandable insights into heavy metal pollution. This enables a comparison of the importance of environmental factors and elucidates their directional impacts, thereby aiding in the understanding of interaction mechanisms. The methods and findings presented in this study offer valuable insights into the spatial heterogeneity of heavy metal pollution in soil. By focusing on the effects of interactive factors, we aimed to develop more accurate strategies for managing SHM pollution.

A multivariate analysis of microplastics in soils along the headwaters of Yangtze river on the Tibetan Plateau

Microplastics (MPs) are among the most widespread anthropogenic pollutants of natural environments, while limited research has focused on the fate of MPs in soils along the Plateau rivers. In this study, we investigated MPs in soils along the source areas of the Yangtze River on the Qinghai-Tibet Plateau. The results showed mean MP abundance values of (89.4 ± 51.0) and (64.4 ± 24.5) items/kg of dry soils around the tributary and mainstream areas, respectively. Film, transparent colors, and polyethylene were common shape, color, and compositions, respectively. The correlation analysis and PCA revealed that MP abundance was related to soil heavy metals (Cr and Ni) and nutrients (TOC and TP) (p < 0.05). Structural equation modeling also revealed that population density was the dominant driving factor contributing to MPs, with a total effect coefficient of 0.45. In addition, the conditional fragmentation model further distinguished the differences in MP sources from upstream to downstream along the Jinsha River. The significant sources of MPs in the bare land and grasslands from the upper reaches of the Jinsha River included traffic, tourism, and atmospheric transport. In contrast, MP transport during farming activities mainly contributed to MPs in the agricultural soil in the lower reaches.

Heavy metal spatial distribution, source analysis, and ecological risks in the central hilly area of Hainan Island, China: results from a high-density soil survey

The presence of heavy metals in soil has gained considerable attention due to their potential risks to ecosystems and human health. In this study, a thorough soil investigation was performed in the hilly region of central Hainan, which was formerly regarded as an area with the highest ecological environmental quality. A total of 7094 soil samples were systematically collected with high density over a large area. Simultaneously, a detailed investigation was conducted on the surrounding environment of each sampling point, including environmental factors such as soil, land use and crop types. The soil samples were analysed for heavy metals, pH, organic matter, and other parameters. The soil heavy metal pollution level, ecological risk and health risk were evaluated using the geo-accumulation index and the potential ecological risk index. The findings showed that the average contents of the heavy metals As, Cd, Cr, Cu, Hg, Ni, Pb and Zn in the soil were 1.68, 0.042, 24.2, 6.49, 0.0319, 7.06, 29.6 and 49.8 mg·kg-1 respectively. Except for Hg, the mean values of the other heavy metals were either lower than or similar to the background values of Hainan. Also, only a few localised areas showed contamination by heavy metals. The primary sources of heavy metals, identified by a positive matrix factorisation model, could be categorised into four types: natural sources related to the soil formation process from acidic intrusive rocks (such as granite); natural sources primarily influenced by atmospheric deposition; anthropogenic sources associated with agricultural activities; and natural sources related to the soil formation process from middle-mafic intrusive rocks and black shales. The correlation analysis and variance analysis findings suggested that the content of heavy metals in the soil was primarily associated with the parent rock. The study area generally had low heavy metal levels and was not significantly polluted. However, agricultural activities still affected the enrichment of heavy metals. Therefore, it is imperative to remain vigilant about the ecological risks linked to soil heavy metals while continuing land development and expanding agricultural activities in the future. These findings indicate that conducting high-density soil surveys can enhance our understanding of regional soil heavy metals and enable reliable recommendations for agricultural planning. Whether in areas with low pollution risk or potential pollution risk, it is recommended that high-density soil surveys be conducted provide scientific guidance for further agricultural development.

Preliminary construction of a microecological evaluation model for uranium-contaminated soil

With the extensive development of nuclear energy, soil uranium contamination has become an increasingly prominent problem. The development of evaluation systems for various uranium contamination levels and soil microhabitats is critical. In this study, the effects of uranium contamination on the carbon source metabolic capacity and microbial community structure of soil microbial communities were investigated using Biolog microplate technology and high-throughput sequencing, and the responses of soil biochemical properties to uranium were also analyzed. Then, ten key biological indicators as reliable input variables, including arylsulfatase, biomass nitrogen, metabolic entropy, microbial entropy, Simpson, Shannon, McIntosh, Nocardioides, Lysobacter, and Mycoleptodisus, were screened by random forest (RF), Boruta, and grey relational analysis (GRA). The optimal uranium-contaminated soil microbiological evaluation model was obtained by comparing the performance of three evaluation methods: partial least squares regression (PLS), support vector regression (SVR), and improved particle algorithm (IPSO-SVR). Consequently, partial least squares regression (PLS) has a higher R2 (0.932) and a lower RMSE value (0.214) compared to the other. This research provides a new evaluation method to describe the relationship between soil ecological effects and biological indicators under nuclear contamination.

Screening of cadmium-chromium-tolerant strains and synergistic remediation of heavy metal-contaminated soil using king grass combined with highly efficient microbial strains

The present study involved the isolation of two cadmium (Cd) and chromium (Cr) resistant strains, identified as Staphylococcus cohnii L1-N1 and Bacillus cereus CKN12, from heavy metal contaminated soils. S. cohnii L1-N1 exhibited a reduction of 24.4 % in Cr6+ and an adsorption rate of 6.43 % for Cd over a period of 5 days. These results were achieved under optimal conditions of pH (7.0), temperature (35 °C), shaking speed (200 rpm), and inoculum volume (8 %). B. cereus strain CKN12 exhibited complete reduction of Cr6+ within a span of 48 h, while it demonstrated a 57.3 % adsorption capacity for Cd over a period of 120 h. These results were achieved under conditions of optimal pH (8.0), temperature (40 °C), shaking speed (150 rpm), and inoculum volume (2-3 %). Additionally, microcharacterization and ICP-MS analysis revealed that Cr and Cd were accumulated on the cell surface, whereas Cr6+ was mainly reduced extracellularly. Subsequently, a series of pot experiments were conducted to provide evidence that the inclusion of S. cohnii L1-N1 or B. cereus CKN12 into the system resulted in a notable enhancement in both the plant height and biomass of king grass. In particular, it was observed that the presence of S. cohnii L1-N1 or B. cereus CKN12 in king grass led to a significant reduction in the levels of Cd and Cr in the soils (36.0 % and 27.8 %, or 72.9 % and 47.4 %, respectively). Thus, the results of this study indicate that the combined use of two bacterial strains can effectively aid in the remediation of tropical soils contaminated with moderate to light levels of Cd and Cr.

Heavy metals contamination and ecological risks in agricultural soils of Uşak, western Türkiye: a geostatistical and multivariate analysis

This research aimed to determine and evaluate the concentrations of As, Cu, Hg, Ni, and Pb, and the physicochemical properties of 48 agricultural soil samples, to identify potential ecological risks and their sources associated with heavy metals contamination in Usak, western Türkiye. Various methods were used to assess ecological risks, including geoaccumulation index (Igeo), enrichment factor (EF), degree of contamination (Cdeg), potential ecological risk (RI), and pollution load index (PLI). The heavy metals concentrations ranged from 4 to 61 mg/kg for As, 8-48 mg/kg for Cu, 0.01-0.06 mg/kg for Hg, 30-813 mg/kg for Ni, and 4-30 mg/kg for Pb. The mean As and Ni concentrations were much greater than Earth's crustal average, the world's mean values, and mean values from many other emerging countries. Igeo and EF values for As, Ni, and Pb indicate various degrees of contamination. Cdeg values show that 96% of the study area is affected to some degree by contamination. For RI values, 38% indicate ecological risks ranging from moderate to considerable degrees. PLI values show that 75% of the agricultural soils are moderately polluted. Spatial distribution maps of Cdeg, RI, and PLI show that the northeastern and southwestern parts of the study area have been polluted to different levels by As, Ni, and Pb. Industrial activities and excessive use of fertilizers, pesticides, fungicides, and herbicides were identified as major sources of heavy metals contamination in the agricultural soils of Uşak.

Pollution and source-specific risk analysis of potentially toxic metals in urban soils of an oasis-tourist city in northwest China

Source-specific risk apportionment for soil potentially toxic metals (PTMs) is of great significance for contamination prevention and risk management in urban environments. Eighty-five urban soil samples were obtained from an oasis-tourist city, China and examined for eight PTMs (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn). The pollution levels, sources, and ecological risk of soil PTMs were quantified, and their source-specific ecological and human health effects were also estimated using the multi-proxy approaches. The results demonstrated that accumulation of Cd, Hg, Pb, Cr, Cu, and Zn in soils was observed compared to their background levels, and the soils experienced varying degrees of PTMs pollution, especially at sites with high-intensity anthropogenic activities. Natural sources, atmospheric deposition, industrial sources, vehicular emissions, and comprehensive inputs were the principal sources, with contributions of 29.28%, 25.86%, 20.13%, 16.50%, and 8.23%, respectively. The integrated ecological risks of PTMs in soils were moderate at most sites, with atmospheric deposition being the dominant contributor to ecological risks. Children exhibited pronounced non-cancer risks, but adults had no notable non-cancer risks. Moreover, there were potential carcinogenic risks for both children and adults within the study region. Non-cancer and carcinogenic risks were more significant for children than adults, and traffic emissions were the primary contributor to non-cancer risks (adults: 20.53%, children: 20.49%) and carcinogenic risks (adults: 22.95%, children: 22.08%). The industrial and traffic activities were considered as priority control sources for soil pollution control and risk management, with Hg, Cd, Zn, and Pb corresponding to the priority elements. This study highlights the source-specific ecological and human health effects of PTMs pollution in urban soils, thereby providing valuable information for targeted pollution control and priority source management.

Bioavailability and health risk of pollutants around a controlled landfill in Morocco: Synergistic effects of landfilling and intensive agriculture

Toxic contamination of agricultural soils by trace metal(oid)s can pose detrimental effects on human health and agroecological systems. In this view, the current research explored total and available metal(oid)s in surface soils and assessed the associated hazards using pollution indices, PMF modeling, PCA, and Montecarlo probabilistic human risk assessment with 10,000 repetitions. The mean concentrations of Cd, Pb, As, Cr, Ni, Cu, Zn, and Fe were 0.89, 24.86, 1.81, 19.10, 25.44, 7.98, 49.12 and 6183.32 mg kg-1 dry weight, respectively. These findings highlighted that the concentration of pollutants exceeded the values measured in the geochemical background. Soil enrichment by heavy metal (oid)s was confirmed by analyzing available fractions using DTPA ,CaCl2 and enrichment factor (EF). Additionally, pollution indicators (Igeo, PLI, and PERI) displayed significant contamination levels, with a higher ecological risk. Matrix Factorization (PMF) receptor and multivariate statistical analysis reflected that anthropogenic activities, particularly landfilling and agricultural practices were the main causes of the contamination. Furthermore, probabilistic and deterministic human risk assessments showed that carcinogenic risks exceeded the threshold values (10-4) set by the USEPA. Consequently, it is crucial to implement continuous monitoring and supervision of landfill sites to prevent additional pollution. These measures should be integrated into the management plans for waste management.

Ecological risk assessment and transmission of soil heavy metals in pastoral areas of the Tibetan plateau based on network environment analysis

The Qinghai-Tibet Plateau is distinguished by its diverse ecosystems and biodiversity, which are highly dependent on their soil. In this study, a comprehensive analysis was conducted to assess the ecological risks in Maqin County, located on the Qinghai-Tibet Plateau, along with the local background values of soil elements, level of element enrichment, and source appointment of soil elements. The findings show that the background soil element levels in Maqin County were greater than the average soil content values in China. The soils in the study area exhibited pollution levels ranging from weak to moderate. The positive matrix factorization (PMF) model was employed to successfully categorized soil elements into four sources: F1 (natural sources), F2 (grazing sources), F3 (volcanic and rock fracture sources), and F4 (intrusive and deep rock source). Based on the characteristics of the ecological communities and the network environmental analysis model, ecological risks were directly introduced through vegetation and soil microorganisms, with subsequent transmission to other components of the ecosystem through the food chain. The integrated risks associated with vegetation, herbivores, soil microorganisms, and carnivores were 0.0106, 0.00193, 0.0282, and 0.00132, respectively. Notably, soil microorganisms were found to be the primary contributors to the total ecological risk in the study area. Furthermore, network environmental analysis and human health risk models revealed that F1, F2, F3, and F4 accounted for 16.85 %, 8.90 %, 21.76 %, and 52.49 % of the input risk of vegetation and soil microorganisms, respectively. Particularly, F4 emerged as the largest contributor to human health risks. This study provides valuable information for the preservation of the ecological environment in pastoral areas, contributing to the global promotion of sustainable ecological practices.

Differentiating environmental scenarios to establish geochemical baseline values for heavy metals in soil: A case study of Hainan Island, China

Soil heavy metal distributions exhibit regional heterogeneity due to the complex characteristics of parent materials and soil formation processes, emphasizing the need for appropriate regional standards prior to assessing soil risks. This study focuses on Hainan Island and employs the Multi-purpose Regional Geochemical Survey dataset to establish heavy metal geochemical baseline and background values for soil using an iterative method. Geographical detector analysis reveals that parent materials are the primary factor influencing heavy metal distribution, followed by soil types and land use. Heavy metal geochemical baseline values are established for the island's three environments and administrative regions. Notably, a universal geochemical baseline value cannot adequately represent regional variations in heavy metal distribution, with parent materials playing a crucial role in various scenarios. Locally applicable values based on parent material are the most representative for Hainan Island. This study provides a reference framework for developing region-specific environmental baseline values for soil heavy metal assessments.

An integrated overview of metals contamination, source-specific risks investigation in coal mining vicinity soils

Heavy metals in soil are harmful to natural biodiversity and human health, and it is difficult to estimate the effects accurately. To reduce pollution and manage risk in coal-mining regions, it is essential to evaluate risks for heavy metals in soil. The present study reviews the levels of 21 metals (Nb, Zr, Ag, Ni, Na, K, Mg, Rb, Zn, Ca, Sr, As, Cr, Fe, Pb, Cd, Co, Hg, Cu, Mn and Ti) in soils around Barapukuria coal-mining vicinity, Bangladesh which were reported in literature. An integrated approach for risk assessments with the positive matrix factorization (PMF) model, source-oriented ecological and health hazards were applied for the study. The contents of Rb, Ca, Zn, Pb, As, Ti, Mn, Co, Ag, Zr, and Nb were 1.63, 1.10, 1.97, 14.12, 1.20, 3.13, 1.22, 3.05, 3.85, 5.48, and 7.21 times greater than shale value. About 37%, 67%, 12%, and 85% of sampling sites posed higher risks according to the modified contamination factor, Nemerow pollution index, Nemerow integrated risk index, and mean effect range median quotient, respectively. Five probable metal sources were computed, including industrial activities to coal mining (17%), agricultural activities (33%), atmospheric deposition (19%), traffic emission (16%), and natural sources (15%). Modified Nemerow integrated risk index reported that agricultural activities, industrial coal mining activities, and atmospheric deposition showed moderate risk. Health hazards revealed that cancer risk values computed by the PMF-HHR model with identified sources were higher than the standard value (1.0E-04) for children, adult male, and female. Agricultural activities showed higher cancer risks to adult male (39%) and children (32%) whereas traffic emission contributed to female (25%). These findings highlight the ecological and health issues connected to potential sources of metal contamination and provide useful information to policymakers on how to reduce such risks.

Metallothionein expression in the central nervous system in response to chronic heavy metal exposure: possible neuroprotective mechanism

It has been reported that volcanoes release several tonnes of mercury per year among other heavy metals through eruptions, fumaroles, or diffuse soil degassing. Since a high percentage of the world's population lives in the vicinity of an active volcano, the aim of this study is to evaluate the accumulation of these metals in the central nervous system and the presence of cellular mechanisms of heavy metal detoxification such as metallothioneins. To carry out this study, wild mice (Mus musculus) chronically exposed to an active volcanic environment were captured in Furnas village (Azores, Portugal) and compared with those trapped in a reference area (Rabo de Peixe, Azores, Portugal). On the one hand, the heavy metal load has been evaluated by analyzing brain and cerebellum using ICP-MS and a mercury analyzer and on the other hand, the presence of metallothionein 2A has been studied by immunofluorescence assays. Our results show a higher load of metals such as mercury, cadmium and lead in the central nervous system of exposed mice compared to non-exposed individuals and, in addition, a higher immunoreactivity for metallothionein 2A in different areas of the cerebrum and cerebellum indicating a possible neuroprotection process.

Connection between health risk and heavy metals in agricultural soils of China: a study based on current field investigations

Heavy metal pollution in agricultural soil is a threat to people's health and sustainable development. However, there is currently no nationwide health risk assessment in China. In this study, we performed a preliminary assessment of heavy metals in agricultural soils of the Chinese mainland, and found obvious carcinogenic risks (total lifetime carcinogenic risk (TLCR) > 1 × 10-5). A similar spatial distribution pattern was found in soil heavy metal and the mortality of esophagus and stomach cancers. Combining the potential carcinogenic risk assessed by LCR for individual heavy metal with Pearson correlation, Geographical Detector (q statistic > 0.75 for TLCR, p < 0.05), and redundancy analysis (RDA), it was found that long-term exposure and intake route of heavy metals exceeding the maximum safety threshold (Health Canada standard) may induce digestive system (esophagus, stomach, liver, and colorectum) cancers in rural populations. Through Partial Least Squares Path Model (PLS-PM), it was also revealed that the LCR of heavy metals was closely related to the soil environmental background (path coefficients = 0.82), which in turn was affected by factors such as economic development and pollution discharge. The current research results highlight the potential carcinogenic risk to the digestive system associated with low-dose and long-term exposure to heavy metals in agricultural soils, and policymakers should propose countermeasures and solutions according to the local conditions.

De-novo exposure assessment of heavy metals in commercially important fresh and dried seafood: Safe for human consumption

The heavy metals (HMs) in seafood are alarming due to their biomagnification in the food chain. The concentrations of As, Cd, Hg, Pb, Cr, and Ni in both fresh and dried fish were quantified, and the potential exposure and safe intake levels for human consumption were assessed by the European Commission (EC) and the Food Safety Standard Authority of India (FSSAI). HMs concentrations ranged from 0.003 mg/kg (Cr) to 2.08 mg/kg for (As) and 0.007 mg/kg (Hg) to 2.76 mg/kg (As). Cd, Hg, and Pb levels in fresh and dried fish were below the maximum residue limits (MRLs) set by the EC and FSSAI, which were 0.1 mg/kg, 0.5 mg/kg, and 0.3 mg/kg, respectively. Cr and As concentrations were also below the MRLs of 12 mg/kg and 76 mg/kg for aquatic products specified by FSSAI. The concentration of HMs in fresh and dried fish was found in the order of As > Cr > Ni > Pb > Cd > Hg and As > Cd > Cr > Ni > Pb > Hg, while the fresh and dried fishes contained HMs in the following order: E. areolatus > S. longiceps > L.lentjen > S. barracuda > E. affinis > S. javus and DA > DS > DR > DB > DSF. The metal pollution index (MPI) validates seafood is HMs free, while the single (Pi) and Nemerow integrated pollution index (Pnw) indicate that concentrations of Cd and As in fresh and dried fish have exceeded the threshold value. The target hazard quotient (THQ<1), hazard index (HI < 1), and target cancer risk (TCR<10-4) indicate that there are no non-carcinogenic and carcinogenic risks through the consumption of seafood and seafood products collected from the Tuticorin coast and marketed at the domestic and international levels. The preliminary findings emphasize the importance of formulating domestic legislation/government initiatives to promote seafood and its consumption. The attainment of this objective shall be facilitated by examining the levels of persistent organic pollutants (POPs) in seafood and evaluating its potential risk to consumers.

Receptor model-based source apportionment and ecological risk assessment of metals in sediment of river Ganga, India

Ganga river surface sediment was sampled from 11 locations, which revealed average concentrations (mg/kg) of metals in the order Mn (296.93) > Zn (61.94) > Cr (54.82) > Cu (30.19) > Pb (24.42) > Cd (0.36). Sediment quality guidelines showed metals rarely to occasionally exhibit adverse biological effects. Indices like potential ecological risk, contamination security index, hazard quotients, multiple probable effect concentrations quality, mean probable effects level quotients, mean effects range median quotient suggest nil to a very low level of pollution with low ecological risk. Contamination factor, geo accumulation index, enrichment factor, quantification of contamination revealed that Pb and Cd originated from anthropogenic activities. APCS-MLR model revealed that metals contributed from natural sources (Zn, Mn, Cr; 20.18 %), industrial-agricultural (Cd; 21.35 %); and discharge of paints, Pb batteries, fossil fuel (Pb; 8.49 %). Present findings will serve as an effective guideline for managing and ameliorating pollution in the river system.

Coastal sediment heavy metal(loid) pollution under multifaceted anthropogenic stress: Insights based on geochemical baselines and source-related risks

Contamination and risk assessments generally ignore the potential bias in results caused by the variation of background values at different spatial scales due to the spatial heterogeneity of sediments. This study aims to perform quantitative source-ecological risk assessment via establishing geochemical baselines values (GBVs) of heavy metal(loid)s (HMs) in Daya Bay, China. Cumulative frequency distribution (CFD) curves determined the GBVs of 12.44 (Cu), 30.88 (Pb), 69.89 (Zn), 0.06 (Cd), 47.85 (Cr), 6.80 (As), and 0.056 mg kg-1 (Hg), which were comparable to the background values of Guangdong Province surface soils, and implied a potential terrestrial origin of the coastal sediments. Principal component analysis (PCA) and positive matrix factorization (PMF) identified three sources (F1: natural processes; F2: anthropogenic impacts; F3: specific sources) with contributions of 51.7%, 29.2%, and 19.1%, respectively. The source-specific risk assessment revealed an ecological risk contribution potential of 73.8% for the mixed anthropogenic sources (F2 + F3) and only 26.2% for natural processes. Cd and Hg were the priority management of metallic elements, occupying 63.5% and 72.5% of the contribution weights of F2 and F3, respectively, which showed multi-level pollution potentials and ecological risk levels. The spatial distribution patterns demonstrated the hotspot features of HM pollution, and priority concerns should be given to the management of marine traffic and industrial point source pollution in Daya Bay. The results of the study provide a scientific approach and perspective for pollution treatment and risk management in the coastal environment.

Heavy metals distribution characteristics, source analysis, and risk evaluation of soils around mines, quarries, and other special areas in a region of northwestern Yunnan, China

In this study, based on the assessment of soil heavy metals (HMs) pollution using relevant indices, a comprehensive approach combined network environ analysis (NEA), human health risk assessment (HHRA) method and positive definite matrix factor (PMF) model to quantify the risks among ecological communities in a special environment around mining area in northwest Yunnan, calculated the risk to human health caused by HMs in soil, and analyzed the pollution sources of HMs. The integrated risks for soil microorganisms, vegetations, herbivores, and carnivores were 2.336, 0.876, 0.114, and 0.082, respectively, indicating that soil microorganisms were the largest risk receptors. The total hazard indexes (HI_T) for males, females, and children were 0.542, 0.591, and 1.970, respectively, revealing a relatively high and non-negligible non-carcinogenic risks (NCR) for children. The total cancer risks (TCR) for both females and children exceeded 1.00E-04, indicating that soil HMs posed carcinogenic risks (CR) to them. Comparatively, Pb was the high-risk metal, accounting for 53.76%, 57.90%, and 68.09% of HI_T in males, females, and children, respectively. PMF analysis yielded five sources of pollution, F1 (industry), F2 (agriculture), F3 (domesticity), F4 (nature), and F5 (traffic).

Translocation pattern of heavy metals in soil-rice systems at different growth stages: A case study in the Taihu region, Eastern China

Rice production is crucial for human nutrition and food safety globally. However, it has been a significant sink for potentially harmful metals because of intensive anthropogenic activities. The study was conducted to characterize heavy metal translocation from soil to rice at the filling, doughing and maturing stages, and influencing factors of their accumulation in rice. The distribution and accumulation patterns varied for metal species and growth stages. Cd and Pb accumulation mainly occurred in roots, Cu and Zn were readily transported to stems. Cd, Cu, and Zn accumulation in grains had a descending order of filling > doughing > maturing. Soil heavy metals, TN, EC, and pH exerted important impacts on heavy metals uptake by roots during the period from filling stage to maturing stage. Concentrations of heavy metals in grains were positively correlated with the translocation factors TF_stem-grain (from stem to grain) and TF_leaf-grain (from leaf to grain). Grain Cd exhibited significant correlations with total Cd and DTPA-Cd in the soil at each of the three growth stages. Moreover, Cd in maturing grain could be effectively predicted by soil pH and DTPA-Cd at the filling stage.

Bismuth-based metal-organic framework peroxidase-mimic nanozyme: Preparation and mechanism for colorimetric-converted ultra-trace electrochemical sensing of chromium ion

A colorimetric-electrochemical dual-mode analytical method based on bismuth metal-organic framework nanozyme was developed for label-free and trace/ultra-trace Cr⁶⁺ detection. 3D ball-flower shaped bismuth oxide formate (BiOCOOH) was used as the precursor and template to facilely construct the metal-organic framework nanozyme BiO-BDC-NH₂, which possesses intrinsic peroxidase-mimic activity to effectively catalyze the colorless 3,3',5,5'-tetramethylbenzidine into blue oxidation products in the presence of hydrogen peroxide. Based on Cr⁶⁺ to promote the peroxide-mimic activity of BiO-BDC-NH₂ nanozyme, a colorimetric method for Cr⁶⁺ detection was developed with the detection limit of 0.44 ng mL^-1. Cr⁶⁺ can be electrochemically reduced to Cr³⁺ that would specifically inhibit the peroxidase-mimic activity of BiO-BDC-NH₂ nanozyme. Thus, the colorimetric system for Cr⁶⁺ detection was converted into a low-toxic and signal-off electrochemical sensor. The electrochemical model showed upgraded sensitivity and a lower detection limit of 9.00 pg mL^-1. The dual-model method was developed for selective appropriate sensing instruments in different detection scenarios, which can provide built-in correction for environmental effects, as well as the development and utilization of dual-signal sensing platforms for trace to ultra-trace Cr⁶⁺ rapid assay.

Green remediation of Ni, Zn, and Cu in an electroplating contaminated site by wood vinegar with optimization and risk assessment

Wood vinegar (WV) is a renewable organic compound, possessing characteristics such as high oxygenated compound content and low negative impact on soil. Based on its weak acid properties and complexing ability to potentially toxic elements (PTEs), WV was used to leach Ni, Zn, and Cu contaminated soil in electroplating sites. In addition, the response surface methodology (RSM) based on the Box-Behnken design (BBD) was established to clarify the interaction between each single factor, and finally completed the risk assessment of the soil. The amounts of PTEs leached from the soil climbed with the increase of WV concentration, liquid-solid ratio, and leaching time, while they surged with the decrease of pH. Under optimal leaching circumstances (the concentration of WV= 100 %; washing time= 919 min; pH= 1.00), the removal rates of Ni, Zn, and Cu could reach 91.7 %, 57.8 %, and 65.0 %, respectively, and the WV-extracted PTEs were mainly from the Fe-Mn oxides fraction. After leaching, the Nemerow integrated pollution index (NIPI) decreased from an initial value of 7.08 (indicating severe pollution) to 0.450 (indicating no pollution). The potential ecological risk index (RI) dropped from 274 (medium level) to 39.1 (low level). Additionally, the potential carcinogenic risk (CR) values reduced by 93.9 % for both adults and children. The results revealed that the washing process significantly reduced the pollution level, potential ecological risk, and health risk. Coupled with FTIR and SEM-EDS analysis, the mechanism of WV removal of PTEs could be explained from three aspects: acid activation, H⁺ ion exchange, and functional group complexation. In summary, WV is an eco-friendly and high-efficiency leaching material for the remediation of PTEs polluted sites, which will maintain soil function and protect human health.

High-resolution risk mapping of heavy metals in soil with an integrated static-dynamic interaction model: A case study in an industrial agglomeration area in China

Heavy metal pollution of soils in industrial agglomeration areas is an increasing concern worldwide. In this study, we traced the sources of heavy metal emissions using a positive matrix factorization (PMF) model. Accordingly, we proposed a novel static-dynamic risk interaction model incorporating multiple risk-related factors to quantify the spatial interaction of emission sources and the probability of accumulation of heavy metals on a large scale. This model was further classified using the Jenks optimization technique to predict the spatial distribution of high-risk hotspots. Our results determined four primary emission sources of heavy metals: industrial (35.01 %), natural (28.61 %), agricultural (26.07 %), and traffic (10.31 %) sources. Five levels were classified by the integrated risk coefficient (IRC), namely, from extremely high to extremely low risk. The extremely high- and high-risk hotspots constituting 41.52 % of the total area of the Zhenhai District, with IRC values ranging from 0.221 to 0.413, were mainly generated by multiple sources linked to PMF-based factors. This quantitative evaluation framework can generate a high-resolution spatially distributed pollution risk map at the grid scale (1 km), which can provide a relatively precise basis for policymaking for point-to-point soil pollution management.

Mapping of trace elements in topsoil of arid areas and assessment of ecological and human health risks in Qatar

Soil is the incubator of human activities. Mapping of soil contaminants needs to be constantly updated. It is fragile in arid regions, especially if it accompanies dramatic and successive industrial and urban activities in addition to the climate change. Contaminants affecting soil are changing due to natural and anthropogenic influences. Sources, transport and impacts of trace elements including toxic heavy metals need continuous investigations. We sampled soil in accessible sites in the State of Qatar. An inductively coupled plasma-optical emission spectrometry (ICP-OES) and an inductively coupled plasma-mass spectrometry (ICP-MS) were used to determine the concentrations of Ag, Al, As, Ba, C, Ca, Ce, Cd, Co, Cr, Cu, Dy, Er, Eu, Fe, Gd, Ho, K, La, Lu, Mg, Mn, Mo, Na, Nd, Ni, Pb, Pr, S, Se, Sm, Sr, Tb, Tm, U, V, Yb and Zn. The study also presents new maps for the spatial distribution of these elements using the World Geodetic System 1984 (projected on UTM Zone 39N) which is based on socio-economic development and land use planning. The study assessed the ecological risks and human health risks of these elements in soil. The calculations showed no ecological risks associated with the tested elements in soil. However, the contamination factor (CF) for Sr (CF > 6) in two sampling locations calls for further investigations. More important, human health risks were not detected for population living in Qatar and the results were within the acceptable range of the international standards (hazard quotient HQ < 1 and Cancer risk between 10^-5 and 10^-6). Soil remains a critical component with water and food nexus. In Qatar and arid regions, fresh water is absent and soil is very poor. Our findings enhance the establishment of scientific strategies for investigating soil pollution and potential risks to achieve food security.

Spatial distribution and source apportionment of DTPA-extractable metals in soils surrounding the largest Serbian steel production plant

Despite presenting a practical approach for the characterization of the environmental risk of potentially toxic elements (PTEs) derived from steel production facilities, the analysis of the spatial distribution of bioavailable PTEs concentrations in the soil is frequently overlooked in the management of polluted sites. In this study, the diethylenetriaminepentaacetic acid (DTPA)-extractable forms of PTEs were investigated in soils surrounding the largest Serbian steel production plant. The correlation and geostatistical analysis indicated their pronounced variability suggesting the anthropogenic origin of most investigated elements, apparently from the steel production facility. The detailed visualization of variables and observations derived by self-organizing maps (SOMs) revealed the homologies in PTEs' distribution patterns, implying the common origin of some elements. These observations were confirmed by principal component analysis (PCA) and positive matrix factorization (PMF). The аpplied approach supports a comprehensive assessment of contaminated sites' ecological and health risks and provides a basis for soil remediation.

Effects of mowing on Pb accumulation and transport in Cynodon dactylon (L.) Pers

Bermudagrass is a perennial herb with the potential to remediate Pb pollution in soils, and it has mechanical resistance to shearing. However, the effects of mowing on Pb absorption and accumulation in bermudagrass are still unclear. In this study, we investigated the effects of different quantities (0, 1, 2, 4 applications) of mowing treatments under 200 mg L^-1 Pb application on Pb accumulation and transport in bermudagrass and explored the related mechanisms. Compared to the Pb treatment, all of the mowing treatments greatly decreased root Pb concentration/accumulation, significantly enhanced Pb concentrations/accumulations in stubble stems and stubble leaves, and ultimately promoted Pb enrichment and transport. Of the treatments in this study, two applications of mowing best promoted Pb enrichment, and four applications of mowing best promoted Pb transport efficiency. Furthermore, mowing mediated the microdistribution and physiological patterns of Pb in bermudagrass and affected the Pb transport by changing the subcellar distribution patterns and chemical forms of Pb in various tissues. Additionally, mowing promoted the transport of all mineral elements and showed a synergistic relationship with Pb absorption and transport. The change in mineral element metabolism patterns may be an important reason why mowing promoted Pb accumulation in bermudagrass. Our study provides the first comprehensive evidence regarding mowing facilitating the absorption, accumulation and transport of Pb in bermudagrass. Moderate mowing may be an effective strategy to assist in soil Pb remediation using bermudagrass.

Distribution, Risk Assessment and Source of Heavy Metals in Mangrove Wetland Sediments of Dongzhai Harbor, South China

Heavy metals are common environmental contaminants that are toxic, non-biodegradable, and bioaccumulative. They can bioaccumulate through the food chain and present a risk to both public health and ecology. Therefore, this study takes the mangrove wetland of Dongzhai Harbor as an example. The concentrations of heavy metals such as As, Cd, Cr, Cu, Ni, Pb, and Zn in the surface sediments of mangrove wetlands were measured to reveal their distribution, the contamination level was assessed, and the sources of contamination were analyzed. The distribution of Cr, Zn, Ni, Pb, Cu, and Cd concentrations are: Yanfeng East River > Sanjiang River > Yanzhou River > Yanfeng West River, while the As concentration in the Yanfeng West River is greater than that in the Yanfeng East River. According to the correlation analysis, the concentrations of Cr, Zn, Ni, Cu, and Cd are significantly and positively correlated with total organic carbon (TOC), total phosphorus (TP), total nitrogen (TN), and salinity (SAL) and shared a significantly negative correlation with pH. There is moderate contamination risk of As and slight contamination risk of Cd, Cr, Cu, Ni, Pb, and Zn in most regions within the study area. Cd, Cr, Cu, Ni, Pb, and Zn exhibit the same sources, which are mainly influenced by human sources such as aquaculture, agricultural cultivation, and livestock farming, while the source of As comes from aquaculture.

Application of nano remediation of mine polluted in acid mine drainage water using machine learning model

Acid mine drainage (AMD) is the term used to describe drainage from coal mines with high sulfur-bearing rocks. The oxidative weathering of metal sulfides leads to AMD. The acidic environment corrodes more harmful compounds in the soil, which is spread throughout the working area. One such significant metal is copper, which is extracted in massive quantities from ores rich in sulfide. A copper-extraction resin might be created by combining diatomaceous earth (DE) particles with polyethyleneimine (PEI), which is shown to have great selectivity and affinity for copper. In this effort, PEI-DE particles' copper absorption level was examined by using synthetic and actual acid mine drainage samples at varied pH values. The findings of the copper uptake particles have been examined through the Support Vector Machine (SVM) model. Using the n-fold 14 cross-validation approach, the quantities of parameters and C are estimated to be 0.001 and 0.01, respectively. The SVM analysis was correct, and the findings indicated that copper could bind to the material efficiently and preferentially at pH 4. Subsequent water elution studies at a pH value of 1 confirmed the pH-reliant interaction between dissolved Cu and PEI by demonstrating full release of the adsorbed Cu. In this research, the copper absorption of PEI-DE particles from synthetic and genuine AMD specimens was studied based on several pH conditions. The findings suggest that copper may attach to the material effectively and preferentially at pH 4. Studies of filtering water at pH1 later confirmed that all of the adsorbed Cu was released. This shows that the interaction between PEI and dissolved Cu depends on PH.

Vertical distribution and major influencing factors of soil selenium in tropical climate: A case study of Chengmai County, Hainan Island

Soil selenium is of great significance to human health. Soil-forming parent rocks are the most critical factor that influences soil Se levels. Chengmai County, Hainan Island, has a tropical climate and diverse types of parent rocks, in which soil Se content is high. This study investigated the vertical distribution of soil Se from various parent rock substrates under tropical climatic conditions, and the factors that influence these soil Se contents, with 69 vertical soil profiles covering Chengmai County. The vertical distribution of soil Se and correlations with CIA (chemical alteration index), Al₂O₃, TFe₂O₃ (total iron oxide expressed as Fe₂O₃), total iodine, SOC (soil organic carbon), and pH were analysed. As per the results, the mean ± standard error of Se content in the A, B, and C horizons was 0.88 ± 0.13 mg/kg, 0.77 ± 0.08 mg/kg and 0.45 ± 0.05 mg/kg, respectively. The parent rock strictly controlled the horizon distribution of Se in the A-horizon. Soil Se showed A-B-horizons-enrichment in the vertical profile, especially in soil profiles overlying granite and basalt. It is hypothesised that the Se enriched in soils developed from the Tuolie Formation due to the release of Se from the weathering process of Se-rich rocks. Meanwhile, Se in soils developed from granite and basalt is more closely associated with exogenous input. Another crucial factor for the high level of Se in Chengmai County is the tropical climate, which has led the rocks to generally undergo intense chemical weathering. This results in soils rich in clay minerals and Fe/Al oxyhydroxides, which easily absorb and retain Se. Furthermore, the Se content of the B-horizon was generally higher than that of the A-horizon due to leaching. These results provide further knowledge and understanding of the geochemical behaviour of soil Se and guide the evaluation of Se-rich land resources under tropical climatic conditions.

Heterogeneous catalysis mediated by light, electricity and enzyme via machine learning: Paradigms, applications and prospects

Energy crisis and environmental pollution have become the bottleneck of human sustainable development. Therefore, there is an urgent need to develop new catalysts for energy production and environmental remediation. Due to the high cost caused by blind screening and limited valuable computing resources, the traditional experimental methods and theoretical calculations are difficult to meet with the requirements. In the past decades, computer science has made great progress, especially in the field of machine learning (ML). As a new research paradigm, ML greatly accelerates the theoretical calculation methods represented by first principal calculation and molecular dynamics, and establish the physical picture of heterogeneous catalytic processes for energy and environment. This review firstly summarized the general research paradigms of ML in the discovery of catalysts. Then, the latest progresses of ML in light-, electricity- and enzyme-mediated heterogeneous catalysis were reviewed from the perspective of catalytic performance, operating conditions and reaction mechanism. The general guidelines of ML for heterogeneous catalysis were proposed. Finally, the existing problems and future development trend of ML in heterogeneous catalysis mediated by light, electricity and enzyme were summarized. We highly expect that this review will facilitate the interaction between ML and heterogeneous catalysis, and illuminate the development prospect of heterogeneous catalysis.

Heavy Metal Pollution and Source Contributions in Agricultural Soils Developed from Karst Landform in the Southwestern Region of China

Heavy metal pollution of soil in agricultural areas is the most prominent environmental pollution problem in China, seriously affecting human health and food security. It has become one of the environmental problems to which all sectors of society attach great importance. Soil heavy metals in the weathering area of hazardous geological bodies in southwest China have naturally high background attributes. Therefore, ecological risk assessment and analysis of potential sources of soil heavy metals in southwest China is of great significance for soil health management, soil heavy metal pollution control and territorial spatial planning. In this study, we collected 787 soil samples (0-20 cm) in Xuanwei County in China and analyzed the concentrations of As, Cd, Cr, Cu, Hg, Ni, Pb and Zn in soils. Igeo, RI, HI and CR were used to calculate the pollution levels, ecological risks and human health risks. Additionally, the PMF model and one-way ANOVA were used to identify the potential sources and discuss the factors affecting the enrichment of heavy metals. The results showed that the mean contents of the surface soils were 1.190 (Cd), 139.4 (Cr), 96.74 (Cu), 0.081 (Hg), 56.97 (Ni), 46.66 (Pb) and 130.1 (Zn) mg/kg. All heavy metals exceeded the background values of the A layer soil in Yunnan Province. The I_geo showed that Cd was the most hazardous element in the study area, followed by Cu, Cr, As, Ni and Pb. The RI showed that low ecological risks, moderate ecological risks, considerable ecological risks and strong ecological risks accounted for 3.81%, 55.27%, 37.74% and 3.18%, respectively, of the total samples, and Cd was the main dominant element. The HI values of the As element in children were greater than 1, indicating a non-carcinogenic risk, and other elements' risks were acceptable. The CR values of Cr and Ni were higher than their limits (1 × 10^-4), and both had carcinogenic risks in children and adults, as did As in children. According to the PMF model, four heavy metals sources were identified: geological sources (32%), sources from mining activities (19.38%), atmospheric deposition sources (17.57%) and agricultural sources (31.05%). Thereinto, As and Pb were mainly derived from agricultural sources, Cd and Cr were mainly associated with geological sources, Cu was largely from mining activity sources, Hg was mainly from atmospheric deposition sources and Ni and Zn were mainly from geological sources, mining activities and agricultural activities. The parent material has a significant influence on the enrichment of heavy metals in the soil, and the heavy metals are significantly enriched in the carbonate parent material and quaternary parent material. Topography also plays a role in heavy metal accumulation; Cd, Cr, Cu, Ni and Zn gradually decreased with the increase in altitude, and As and Pb increased with the increase in altitude. Mn-oxide played a crucial part in the enrichment of Cu and Zn, while SOC, K₂O and pH had little influence on the accumulation of heavy metals.

Characteristics, Health Risk Assessment, and Transfer Model of Heavy Metals in the Soil-Food Chain in Cultivated Land in Karst

Heavy metal(loid) contamination of farmland is a crucial agri−environmental problem that threatens food safety and human health. In this study, we examined the contamination levels of heavy metals (As, Pb, Cd, Hg, Cr) in farmland and foods (rice, maize, and cabbage) in the core of Asia’s largest karst region and assessed the potential health risks of consumption of these three foods. In addition, we developed a predictive transfer model of heavy metals in the soil−food chain through multiple regression equations. The results reveal that the soil heavy metals in the study area showed high accumulation characteristics, and the average concentration exceeded the national background value by 1.6−130 times, among which Cd pollution was the most serious. The order of contamination of the three soils in the study area was cabbage land > maize land > rice land. The order of potential risk of toxic elements in all three soils was Cd > Hg > As > Pb > Cr. The results of the risk assessment of agricultural consumption indicated a high carcinogenic and noncarcinogenic risk for the local population. The top contributor to carcinogenic risk was Cr, followed by As. Cd is the major noncarcinogenic contributor in maize and cabbage, and the noncarcinogenic contribution in rice is mainly caused by As. The risk was higher in children than in adults and was the highest for rice consumption. In addition, the predictive transfer model showed that the Cd levels in the three foods showed sufficient predictability and reasonable simulations of Cd concentrations in rice, maize, and cabbage throughout the study area. It could allow decision-making on the need for remediation strategies to reduce the risk of metal contamination of agricultural land in potentially high−risk areas of karst.

Contamination and source of metals in surface sediments from the Nandu River of Hainan Island, China

Concentrations of eight metals, organic carbon (Corg), and eight oxides were measured in 33 river sediment samples from the Nandu River. Sediment quality guidelines (SQGs) showed no severe pollution at all stations. However, according to the geo-accumulation index (Igeo), enrichment factor (EF), and potential ecological risk index (EI and RI), As and Cd were the primary pollutants in the survey area and caused low to moderate potential ecological risk. The positive correlations between Al₂O₃, TFe₂O₃, Mn, Corg, and metals indicated that clay, FeMn oxides, and organic carbon content were the main factors for metal accumulation in the study area. From the results of correlation (CA) and principal component analysis (PCA), we inferred that Cr, Ni, Cu, and Zn were mainly from natural sources, while As, Cd, Hg, and Pb were from anthropogenic activities in the Nandu River basin. This was the first study of metal pollution in the surface sediments of the Nandu River, which will serve as a reference for future research.

Preparation of Three-Dimensional MF/Ti3C2Tx/PmPD by Interfacial Polymerization for Efficient Hexavalent Chromium Removal

Heavy metal pollution is a serious threat to human health and the ecological environment, but adsorption technology based on nano adsorbents can effectively treat the crisis. However, due to the nanoscale effect, nano adsorbents have some crucial shortcomings, such as recycling difficulty and the loss of nanoparticles, which seriously limit their application. The feasible assembly of nano adsorbents is an accessible technology in urgent need of a breakthrough. In this study, three-dimensional (3D) adsorbent (MF/Ti3C2Tx/PmPD) with excellent performance and favorable recyclability was prepared by interfacial polymerization with melamine foam (MF) as the framework, two-dimensional (2D) titanium carbide (Ti3C2Tx) as the bridge and Poly (m-Phenylenediamine) (PmPD) as the active nano component. The morphology, structure, mechanical property of MF/Ti3C2Tx/PmPD and reference MF/PmPD were investigated through a scanning electron microscope (SEM), Fourier transformed infrared spectra (FT-IR), Raman scattering spectra and a pressure-stress test, respectively. Owning to the regulation of Ti3C2Tx on the morphology and structure of PmPD, MF/Ti3C2Tx/PmPD showed excellent adsorption capacity (352.15 mg/g) and favorable cycling performance. R-P and pseudo-second-order kinetics models could well describe the adsorption phenomenon, indicating that the adsorption process involved a composite process of single-layer and multi-layer adsorption and was dominated by chemical adsorption. In this research, the preparation mechanism of MF/Ti3C2Tx/PmPD and the adsorption process of Cr(VI) were systematically investigated, which provided a feasible approach for the feasible assembly and application of nano adsorbents in the environmental field.