Environmental Geochemistry and Health最新文献

{"title":"Entropy-based groundwater quality evaluation with multivariate analysis and Sobol sensitivity for non-carcinogenic health risks in mid-Gangetic plains, India.","authors":"Amit Kumar, Anshuman Singh","doi":"10.1007/s10653-025-02495-9","DOIUrl":"https://doi.org/10.1007/s10653-025-02495-9","url":null,"abstract":"<p><p>This study assessed the quality and pollution status of the groundwater in an agricultural and densely populated area of Mid-Gangetic Plain Utilizing Principal Component Analysis (PCA), Spearman's correlation analysis, and Entropy water quality index (EWQI) and evaluated the public health hazard resulting due to nitrate and fluoride exposure using USEPA-based Health risk model and Sobol sensitivity analysis (SSA) on the basis of collected groundwater samples. The analysis revealed that several water quality parameters surpassed the permissible levels established by the Bureau of Indian Standards (BIS). Based on the third quartile values the sequence of ionic dominance in the groundwater was observed as: HCO₃^- > Ca²⁺ > Mg²⁺ > Cl^- > SO₄^2- > NO₃^- > PO₄^3- > F^-. Approximately 10% of groundwater samples exceeded the desirable fluoride level of 1 mg/l, and 12% of samples surpassed the BIS permissible nitrate limit of 45 mg/l. Correlation analysis suggested key factors driving groundwater chemistry, including agricultural runoff, wastewater discharge, and geological activities. PCA reduced 12 variables to 4 significant components, explaining 68.074% of the variation, identifying both geogenic and anthropogenic interventions on the groundwater quality, and highlighting the complex interplay of these factors in the study area. Groundwater quality, measured by EWQI, ranged from 36.30 to 234 revealing about 85% of samples falling in excellent to fair quality, suitable for drinking. Notedly, there was some overlap in the distribution pattern of poor water quality samples and those with high nitrate, phosphate, and magnesium levels. Health risk assessment revealed that nitrate and fluoride pollution pose a significant non-carcinogenic threat. The total hazard index ranging 0.328-2.77 for children, 0.26-2.23 for females, and 0.22-1.89 for males, with 56.10% of samples exceeding the safe threshold for children, signifying a potential health risk for children than adults. SSA revealed that concentration and intake rate are the most influential variables of nitrate and fluoride exposure, which causes health risks to residents. To ensure public health and safety, the study advises residents to rely on treated water from underground sources. Additionally, it stresses the need for ongoing monitoring of groundwater resources to guide the development of effective pollution mitigation strategies and maintain a safe and reliable water supply.</p>","PeriodicalId":11759,"journal":{"name":"Environmental Geochemistry and Health","volume":"47 6","pages":"186"},"PeriodicalIF":3.2,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143985197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of risk to human health associated with the consumption of contaminated groundwater in the Western Brazilian Amazon.","authors":"Josilena de Jesus Laureano, Elisabete Lourdes do Nascimento, Caryne Ferreira Ramos, Daíse da Silva Lopes, Luiza Fernanda Silva Pavanello, Tiago de Oliveira Lima, Alan Gomes Mendonça, Ana Lúcia Denardin da Rosa, Walkimar Aleixo da Costa Junior, Maria Cristina N do N Recktenvald, Wanderley Rodrigues Bastos","doi":"10.1007/s10653-025-02491-z","DOIUrl":"https://doi.org/10.1007/s10653-025-02491-z","url":null,"abstract":"<p><p>The present study evaluates the risk to human health associated with the consumption of groundwater in municipalities in the Western Brazilian Amazon (Jaru, Ouro Preto do Oeste, Ji-Paraná and Presidente Médici, all in the state of Rondônia). Water was collected directly from wells with an underground collector and PET bottles between 2017 and 2019, in periods (low water, high water, Transition high water/low water). Nitrite and nitrate analyses were carried out using spectrophotometry (APHA, Standard methods for the examination of water and wastewater, Washington, 2017; EPA, Technical Resource Document, EPA/600/4-79/020 Disponívelem, 1971). Trace elements were detected by inductively coupled plasma-optical emission spectrometry. The hazard quotient was obtained from the ratio between the exposure level and the acceptable level for each substance present in the samples, and the hazard index resulted from the sum of the hazard quotients found for each substance. We found that the groundwater in the study areas is improper for human consumption in accordance with Brazilian regulations. Concentrations were found above the maximum values permitted by the Edict on Potability of Water for Human Consumption (PRC Edict 5/2017, as amended by GM/MS Edict 888/2021), and the World health organization standard for 2017 for Al (< 200 µg L^-1), As (< 10 µg L^-1), Ba (< 700 µg L^-1), Fe (< 300 µg L^-1), Mn (< 100 µg L^-1), Pb (< 10 µg L^-1), Zn (< 5,000 µg L^-1), and nitrate (< 10,000 µg L^-1). The results of the risk assessment indicated that the values were above the recommended levels (< 1) in 75.3% of the samples analyzed, meaning that people in the areas studied are highly exposed to contaminants that are harmful to human health.</p>","PeriodicalId":11759,"journal":{"name":"Environmental Geochemistry and Health","volume":"47 5","pages":"185"},"PeriodicalIF":3.2,"publicationDate":"2025-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143998285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multisource remote sensing and ensemble learning for multidimensional monitoring of heavy metals on mine surfaces.","authors":"Yanru Li, Keming Yang, Xinru Gu, Lishun Peng, Xinyang Chen","doi":"10.1007/s10653-025-02493-x","DOIUrl":"https://doi.org/10.1007/s10653-025-02493-x","url":null,"abstract":"<p><p>This study aims to establish monitoring models for surface heavy metals in mining areas by utilizing multi-source remote sensing data and ensemble learning algorithms. By collecting heavy metal content data from soil and crop leaves within the study area, and combining it with data obtained from the Google Earth Engine platform, including Landsat 8, Sentinel-2 spectral data, vegetation indices, and VV and VH polarization information from Sentinel-1, along with terrain factors derived from the Digital Elevation Model such as elevation, hillshade, slope, and aspect, a total of 43 feature indicators were consolidated. Feature importance ranking (FI) and the successive projections algorithm (SPA) feature selection method were employed to filter feature factors, selecting different features for each type of heavy metal. In the soil, the optimal model for predicting Cr and Cd content is AdaBoost-MT, while the optimal model for inverting Zn, As, Hg, and Pb content is FISPA-AdaBoost-MT. In the crops, the optimal model for predicting the content of all six heavy metals is FISPA-AdaBoost-MT. This indicates that the combination of FI and SPA features effectively evaluates the heavy metal content in both soil and crops. Utilizing these multidimensional features, this study combines ensemble learning algorithms with multi-target regression techniques to construct inversion models for six types of heavy metals (Cr, Zn, As, Cd, Hg, and Pb) simultaneously. Based on the optimal prediction models, distribution maps of heavy metals in soil and crops within the study area were generated, achieving comprehensive, multidimensional monitoring of surface heavy metals in mining areas through overlay display.</p>","PeriodicalId":11759,"journal":{"name":"Environmental Geochemistry and Health","volume":"47 5","pages":"184"},"PeriodicalIF":3.2,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143968625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distribution of synthetic antioxidants in outdoor and educational indoor dusts and assessment of human exposure.","authors":"Yiyu Wang, Huijun Su, Ning Liu, Naiwang Yang, Pingqiang Gao","doi":"10.1007/s10653-025-02496-8","DOIUrl":"https://doi.org/10.1007/s10653-025-02496-8","url":null,"abstract":"<p><p>Antioxidants have been received recognized as contaminants in the environmental field due to the reports of adverse effects. In this study, a total of 35 outdoor dusts and 20 educational indoor dusts were sampled to investigated the occurrence and spatial distribution of antioxidants, and eight antioxidants were positively found in dusts. For the indoor dusts, the total antioxidant concentrations (Σ₈Ant) were in the range of 15.7-5282 ng/g, 2,6-di-tert-butyl-4-methylphenol (BHT) was the dominate compound which constituted of 46.4% in the total concentrations of detected antioxidants. The composition profiles of antioxidants (67.9%) in outdoor dusts were different from that in indoor dusts, N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine (6PPD) was the main component of all the identified antioxidants. Various microenvironments exhibited different contamination characteristics of antioxidants, the rank order of Σ₈Ant was following as: campus roads (average concentration: 35.4 ng/g) < pedestrian streets (59.1 ng/g) < urban roads (92.9 ng/g) < teaching buildings (105 ng/g) < laboratory buildings (530 ng/g) < dormitories (1652 ng/g). Based on the measured Σ₈Ant in dusts, we estimated daily intake via dust ingestion to be 3.90e^-2 to 9.55e^-2 ng/kg BW/day for adults under high exposure scenario. Overall, the occurrence and spatial distribution of antioxidants in outdoor and educational indoor spaces were investigated and the potential risks of detected antioxidants exposure in toddlers and adults were assessed in the present study.</p>","PeriodicalId":11759,"journal":{"name":"Environmental Geochemistry and Health","volume":"47 5","pages":"183"},"PeriodicalIF":3.2,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143975716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: Provenance and distribution of potentially toxic elements (PTEs) in stream sediments from the eastern Hg-district of Mt. Amiata (central Italy).","authors":"Federica Meloni, Enrico Dinelli, Jacopo Cabassi, Barbara Nisi, Giordano Montegrossi, Daniele Rappuoli, Orlando Vaselli","doi":"10.1007/s10653-025-02499-5","DOIUrl":"https://doi.org/10.1007/s10653-025-02499-5","url":null,"abstract":"","PeriodicalId":11759,"journal":{"name":"Environmental Geochemistry and Health","volume":"47 5","pages":"182"},"PeriodicalIF":3.2,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12018484/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143975266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of machine learning models for accurate prediction of heavy metals in coal mining region soils in Bangladesh.","authors":"Ram Proshad, Krishno Chandra, Maksudul Islam, Dil Khurram, Md Abdur Rahim, Maksudur Rahman Asif, Abubakr M Idris","doi":"10.1007/s10653-025-02489-7","DOIUrl":"https://doi.org/10.1007/s10653-025-02489-7","url":null,"abstract":"<p><p>Coal mining soils are highly susceptible to heavy metal pollution due to the discharge of mine tailings, overburden dumps, and acid mine drainage. Developing a reliable predictive model for heavy metal concentrations in this region has proven to be a significant challenge. This study employed machine learning (ML) techniques to model heavy metal pollution in soils within this critical ecosystem. A total of 91 standardized soil samples were analyzed to predict the accumulation of eight heavy metals using four distinct ML algorithms. Among them, random forest model outer performed in predicting As (0.79), Cd (0.89), Cr (0.63), Ni (0.56), Cu (0.60), and Zn (0.52), achieving notable R squared values. The feature attribute analysis identified As-K, Pb-K, Cd-S, Zn-Fe₂O₃, Cr- Fe₂O₃, Ni-Al₂O₃, Cu-P, and Mn- Fe₂O₃ relationships resembled with correlation coefficients among them. The developed models revealed that the contamination factor for metals in soils indicated extremely high levels of Pb contamination (CF ≥ 6). In conclusion, this research offers a robust framework for predicting heavy metal pollution in coal mining soils, highlighting critical areas that require immediate conservation efforts. These findings emphasize the necessity for targeted environmental management and mitigation to reduce heavy metal pollution in mining sites.</p>","PeriodicalId":11759,"journal":{"name":"Environmental Geochemistry and Health","volume":"47 5","pages":"181"},"PeriodicalIF":3.2,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143996031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Centennial-scale sediment record and source traceability of heavy metals in Laizhou Bay, Bohai Sea, China.","authors":"Fang Tang, Ziyang Zhang, Jingjing Li, Yue Wang, Yang Yang, Xiaolei Wang, Hong Wang, Min Xu","doi":"10.1007/s10653-025-02488-8","DOIUrl":"https://doi.org/10.1007/s10653-025-02488-8","url":null,"abstract":"<p><p>The accumulation of heavy metals in marine sediments poses a significant threat to marine ecosystems. This study utilized a ²¹⁰Pb-dated sediment core from Laizhou Bay to reconstruct historical sediment variability, trace heavy metal sources, and evaluate their contamination at a centennial timescale. By intergrating Self-Organizing Map, Principal Component Analysis and Positive Matrix Factorization, we conducted a comprehensive analysis of the sources of heavy metal pollution in Laizhou Bay. Our results revealed four distinct periods of heavy metal distribution into: 1906-1930, 1930-1976, 1976-2000, and 2000-2020, corresponding to shifts in human activities and changes in the Yellow River course over the past century. This study is the first to introduce the SOM algorithm into the field of heavy metal source analysis in Laizhou Bay, exhibiting better classification robustness for non-linearly coupled combinations like Co-Cr-Ni-V. By combined with PMF, we identified four primary sources of heavy metals: natural sources, mixed anthropogenic and natural sources, agricultural activities, and industrial production, with contribution rate of 28.37, 28.86, 14.03 and 28.74%, respectively. Notably, Cadmium (Cd) was identified as the most enriched pollutant, demonstrating pronounced anthropogenic amplification. These results provide valuable insights for targeted pollution mitigation strategies, emphasizing the need for source-specific management approaches in coastal zones under increasing anthropogenic pressure.</p>","PeriodicalId":11759,"journal":{"name":"Environmental Geochemistry and Health","volume":"47 5","pages":"180"},"PeriodicalIF":3.2,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143996264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ecological risk assessment of emerging contaminants on soil and terrestrial ecosystems (2005-2024): a bibliometric and scientometric review.","authors":"Wen Ma, Qi Wang, Erastus Mak-Mensah, Xiaole Zhao, Wenjia Qi, Jinhui Zhu, Rizwan Azim, Xujiao Zhou, Dengkui Zhang, Bing Liu, Qinglin Liu, Xuchun Li","doi":"10.1007/s10653-025-02486-w","DOIUrl":"https://doi.org/10.1007/s10653-025-02486-w","url":null,"abstract":"<p><p>Growing awareness exists regarding the dangers posed by emerging contaminants (ECs) to terrestrial ecosystems and human health. This study reviewed ecological risk assessment studies on ECs, emphasizing their environmental presence, toxicological effects, behavior, and potential negative impacts on soil and terrestrial ecosystems. The work aims to identify key trends, research hotspots, and gaps to provide policy recommendations, inform regulatory frameworks, and suggest future research directions for the sustainable management of ECs in terrestrial environments. A systematic literature review was conducted using the Web of Science database, selecting studies from the past decade related to ECs, soil, terrestrial ecosystems, and ecological risk assessment. A total of 450 documents were analyzed using VOSviewer and CiteSpace to visualize key research patterns. Results indicate a 26.26% annual growth in publications, highlighting increasing scholarly interest. Citation analysis identifies China, the USA, and Italy as leading contributors, with Switzerland exhibiting the highest citation impact per article. Co-authorship network analysis reveals key researchers and collaboration clusters, though cross-group interactions remain limited. Institutional analysis underscores the dominance of the Chinese Academy of Sciences, with notable global partnerships from CSIC (Spain) and King Saud University. Journal analysis highlights Environmental Toxicology and Chemistry and Journal of Environmental Monitoring as highly influential sources. Temporal keyword trends indicate a shift toward ecological risk assessment and contaminant interactions. The study underscores the need for advanced monitoring techniques to manage ECs. Understanding broader ecological impacts, including ecosystem responses and bioaccumulation, is crucial for informed environmental management and policy-making. The findings have significant implications for environmental policy, management strategies, and mitigation measures to protect ecosystem and human health.</p>","PeriodicalId":11759,"journal":{"name":"Environmental Geochemistry and Health","volume":"47 5","pages":"179"},"PeriodicalIF":3.2,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143997620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative analysis of the short-term germination and metal accumulation patterns of two Sorghum hybrids.","authors":"Dávid Tőzsér, Jennifer Damilola Osazuwa, John Sule Elias, Deborah Osariemen Idehen, Daniela Isabel Gutiérrez Pérez, Ágota Zsófia Ragyák, Zsófi Sajtos, Tibor Magura","doi":"10.1007/s10653-025-02485-x","DOIUrl":"https://doi.org/10.1007/s10653-025-02485-x","url":null,"abstract":"<p><p>Metal contamination poses a high risk for organisms, especially those with extensive food chain relevancy. Thus, elevated concentration of metals is considered a major cause for concern in crops. This study aimed to evaluate the short-term responses of sorghum and Sudan grass to different Cd/Zn doses in a complex germination test by assessing growth parameters, tissue metal concentrations, and metal interaction accountant for the ecophysiological and elemental alterations. To do so, radicle and hypocotyl length were measured, and Ca, K, Mg, Cd, Cu, Fe, and Zn concentrations were determined after 24, 72, and 120 h. Our results indicated significant (p < 0.05) differences in the radicle and hypocotyl length by species, contaminant dose, and exposure time. Further, the applied doses along the exposure time gradient significantly and variously affected tissue concentrations. Out of the comparisons involving single metal doses, two significant interactions were revealed: the concentrations of both Cu and Fe were significantly reduced by the increase in Cd concentration in Sudan grass tissues. It was concluded that both species have an excellent potential to indicate metal contamination and accumulate metals in the short term, however, with differences in their responses along the exposure gradient. Additionally, this study filled a literature gap by revealing major patterns and limitations in growth and metal accumulation for sorghum and Sudan grass, thereby supporting further research and practical implications.</p>","PeriodicalId":11759,"journal":{"name":"Environmental Geochemistry and Health","volume":"47 5","pages":"178"},"PeriodicalIF":3.2,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12011658/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143987112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating spatial heterogeneity and speciation dynamics in source apportionment of toxic metal(loid)s at an abandoned hydrometallurgical zinc smelting site.","authors":"Hengbo Liu, Xu Cao, Zhiyue Gao, Yi Wu, Yongfang Sa, Qinying Yao, Jianzhou Han, Jinyan Yang, Jiang Hou, Tao Xing","doi":"10.1007/s10653-025-02469-x","DOIUrl":"https://doi.org/10.1007/s10653-025-02469-x","url":null,"abstract":"<p><p>Zinc hydrometallurgy sites are critical hotspots for combined toxic metal(loid)s (TMs) pollution, yet the integration of spatial heterogeneity and migration dynamics into source apportionment remains underexplored. This study investigated the concentrations, speciation, and spatial distribution of nine TMs (As, Cd, Cu, Hg, Mn, Ni, Pb, Sb, Zn) in soils at an abandoned zinc smelter in southwest China. Multivariate statistical methods and the Positive matrix factorization (PMF) model were applied to disentangle primary sources and secondary redistribution. Spatial analysis revealed that As, Cd, Cu, Pb, Sb, and Zn shared similar contamination patterns, concentrated in slag storage and comprehensive recovery areas, whereas Hg and Mn exhibited distinct hotspots near sulfuric acid production and electrolysis zones. Vertical migration was most pronounced for Cd and Zn (> 8 m depth), followed by Hg and Mn (4-8 m), while As, Cu, Pb, and Sb were restricted to 0-4 m due to adsorption in clay-rich layers. Speciation analysis indicated high mobility of Cd and Zn (acid-soluble fraction: 66.96 and 52.10%, respectively), contrasting with reducible Pb and Mn (51.59 and 48.32%) and residual As, Hg, Ni, Sb (60.74-76.64%). The results from PMF model identified aqueous-phase (Cd, Zn, Mn) and solid-phase (As, Cu, Pb, Sb) migration pathways, validated by spatial correlations with topography and functional zones. Aqueous-phase contributions dominated low-lying areas, while solid-phase contributions aligned with elevated regions, reflecting topography-driven redistribution. This study advances source apportionment of TM in soil by unifying spatial heterogeneity, speciation dynamics, and receptor modeling, offering a framework for targeted risk assessment and remediation of industrial sites.</p>","PeriodicalId":11759,"journal":{"name":"Environmental Geochemistry and Health","volume":"47 5","pages":"177"},"PeriodicalIF":3.2,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143957377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}