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Liu L, Li Y, Gu X, Tulcan RXS, Yan L, Lin C, Pan J. Priority sources identification and risks assessment of heavy metal(loid)s in agricultural soils of a typical antimony mining watershed. J Environ Sci (China) 2025; 147:153-164. [PMID: 39003036 DOI: 10.1016/j.jes.2023.11.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 11/13/2023] [Accepted: 11/13/2023] [Indexed: 07/15/2024]
Abstract
Heavy metal(loid) (HM) pollution in agricultural soils has become an environmental concern in antimony (Sb) mining areas. However, priority pollution sources identification and deep understanding of environmental risks of HMs face great challenges due to multiple and complex pollution sources coexist. Herein, an integrated approach was conducted to distinguish pollution sources and assess human health risk (HHR) and ecological risk (ER) in a typical Sb mining watershed in Southern China. This approach combines absolute principal component score-multiple linear regression (APCS-MLR) and positive matrix factorization (PMF) models with ER and HHR assessments. Four pollution sources were distinguished for both models, and APCS-MLR model was more accurate and plausible. Predominant HM concentration source was natural source (39.1%), followed by industrial and agricultural activities (23.0%), unknown sources (21.5%) and Sb mining and smelting activities (16.4%). Although natural source contributed the most to HM concentrations, it did not pose a significant ER. Industrial and agricultural activities predominantly contributed to ER, and attention should be paid to Cd and Sb. Sb mining and smelting activities were primary anthropogenic sources of HHR, particularly Sb and As contaminations. Considering ER and HHR assessments, Sb mining and smelting, and industrial and agricultural activities are critical sources, causing serious ecological and health threats. This study showed the advantages of multiple receptor model application in obtaining reliable source identification and providing better source-oriented risk assessments. HM pollution management, such as regulating mining and smelting and implementing soil remediation in polluted agricultural soils, is strongly recommended for protecting ecosystems and humans.
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Affiliation(s)
- Lianhua Liu
- Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - You Li
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
| | - Xiang Gu
- School of Environment, Beijing Normal University, Beijing 100875, China
| | | | - Lingling Yan
- Yiyang Academy of Agricultural Sciences, Yiyang 413099, China
| | - Chunye Lin
- School of Environment, Beijing Normal University, Beijing 100875, China
| | - Junting Pan
- Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
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2
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Liu Y, Xu F, Wang H, Huang X, Wang D, Fan Z. Optimizing health risk assessment for soil trace metals under low-precision sampling conditions: A case study of agricultural soil. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 944:173797. [PMID: 38862037 DOI: 10.1016/j.scitotenv.2024.173797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 05/24/2024] [Accepted: 06/03/2024] [Indexed: 06/13/2024]
Abstract
Cost limitations often lead to the adoption of lower precision grids for soil sampling in large-scale areas, potentially causing deviations in the observed trace metal (TM) concentrations from their true values. Therefore, in this study, an enhanced Health Risk Assessment (HRA) model was developed by combining Monte Carlo simulation (MCS) and Empirical Bayesian kriging (EBK), aiming to improve the accuracy of health risk assessment under low-precision sampling conditions. The results showed that the increased sampling scale led to an overestimation of the non-carcinogenic risk for children, resulting in potential risks (the maximum Hazard index value was 1.08 and 1.64 at the 500 and 1000 m sampling scales, respectively). EBK model was suitable for predicting soil TM concentrations at large sampling scale, and the predicted concentrations were closer to the actual value. Furthermore, we found that the improved HRA model by combining EBK and MCS effectively reduced the possibility of over- or under-estimation of risk levels due to the increasing sampling size, and enhanced the accuracy and robustness of risk assessment. This study provides an important methodology support for health risk assessment of soil TMs under data limitation.
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Affiliation(s)
- Yafeng Liu
- School of Resources and Environment, Anqing Normal University, Anqing 246133. China
| | - Feng Xu
- School of Resources and Environment, Anqing Normal University, Anqing 246133. China
| | - Huijuan Wang
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Xinmiao Huang
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Dejin Wang
- School of Resources and Environment, Anqing Normal University, Anqing 246133. China.
| | - Zhengqiu Fan
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China.
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3
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Wu C, Huang F, Wei L, Yi S, Wu Y, Huang Z, Yi M, Li F. Do the residual metals in multiple environmental media surrounding mines pose ecological and health risks? A case of an abandoned mining area in central south China. ENVIRONMENTAL RESEARCH 2024; 257:119279. [PMID: 38821461 DOI: 10.1016/j.envres.2024.119279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Revised: 05/27/2024] [Accepted: 05/29/2024] [Indexed: 06/02/2024]
Abstract
Despite effective mining environmental regulations, residual metal pollution persists, leading to significant ecological harm and posing substantial risks to human well-being. This study employed multiple-criteria methods to investigate the ecological and health risks caused by metals in multiple environmental media (e.g., arable soil, indoor dust, PM10, homegrown vegetables, and rice) around abandoned mine areas (MA) in central south China. The study also aimed to identify predominant risk factors and the main exposure pathway. The findings revealed that metal levels and risks in the environmental media surrounding the MA were significantly higher than those in the control areas (away from abandoned mines, CA). This indicates that the accumulation of metals in the environmental media surrounding the MA was attributed to the previous mining activities. Variations in metal content were observed among different environmental media in MA, with Cd from mining source being the primary pollutant in arable soil, indoor dust, PM10, and vegetables, while As from agricultural source was the main pollutant in rice. Additionally, the consumption of Cd-contaminated vegetables and As-contaminated rice emerged as the primary routes of health hazards for the local population, leading to significant non-carcinogenic and carcinogenic risks. Consequently, it is imperative for the government and mining companies to promptly establish risk control and remedial strategies for mitigating residual metal levels in multiple environmental media surrounding the MA.
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Affiliation(s)
- Chen Wu
- College of Environment and Resources, Xiangtan University, Xiangtan, 411105, China; Hunan Provincial University Key Laboratory for Environmental and Ecological Health, Xiangtan, 411105, China; The Experimental Teaching Center in College of Environment and Resources, Xiangtan University, Xiangtan, 411105, China
| | - Fenglian Huang
- State Environmental Protection Key Laboratory of Monitoring for Heavy Metal Pollutants, Changsha, 410014, China; Changsha Environmental Protection Vocational College, Changsha, 410004, China
| | - Lanlan Wei
- College of Environment and Resources, Xiangtan University, Xiangtan, 411105, China; Hunan Provincial University Key Laboratory for Environmental and Ecological Health, Xiangtan, 411105, China; The Experimental Teaching Center in College of Environment and Resources, Xiangtan University, Xiangtan, 411105, China
| | - Shengwei Yi
- College of Environment and Resources, Xiangtan University, Xiangtan, 411105, China; Hunan Provincial University Key Laboratory for Environmental and Ecological Health, Xiangtan, 411105, China; The Experimental Teaching Center in College of Environment and Resources, Xiangtan University, Xiangtan, 411105, China
| | - Yujun Wu
- College of Environment and Resources, Xiangtan University, Xiangtan, 411105, China; Hunan Provincial University Key Laboratory for Environmental and Ecological Health, Xiangtan, 411105, China; The Experimental Teaching Center in College of Environment and Resources, Xiangtan University, Xiangtan, 411105, China
| | - Zhongting Huang
- Changsha Environmental Protection Vocational College, Changsha, 410004, China
| | - Min Yi
- Hunan Ecological and Environmental Monitoring Center, Changsha, 410014, China
| | - Feng Li
- College of Environment and Resources, Xiangtan University, Xiangtan, 411105, China; Hunan Provincial University Key Laboratory for Environmental and Ecological Health, Xiangtan, 411105, China; The Experimental Teaching Center in College of Environment and Resources, Xiangtan University, Xiangtan, 411105, China.
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Lu S, Wang J, Wang B, Xin M, Lin C, Gu X, Lian M, Li Y. Spatiotemporal variations and risk assessment of estrogens in the water of the southern Bohai Sea: A comprehensive investigation spanning three years. JOURNAL OF HAZARDOUS MATERIALS 2024; 474:134754. [PMID: 38820750 DOI: 10.1016/j.jhazmat.2024.134754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 05/08/2024] [Accepted: 05/27/2024] [Indexed: 06/02/2024]
Abstract
The ubiquitous and adverse effects of estrogens have aroused global concerns. Natural and synthetic estrogens in 255 water samples from the southern Bohai Sea were analyzed over three years. Total estrogen concentrations were 11.0-268 ng/L in river water and 1.98-99.7 ng/L in seawater, with bisphenol A (BPA) and 17α-ethynylestradiol (EE2) being the predominant estrogens, respectively. Estrogen showed the highest concentrations in summer 2018, followed by spring 2021 and spring 2019, which was consistent with the higher estrogen flux from rivers during summer. Higher estrogen concentrations in 2021 than in 2019 were driven by the higher level of BPA, an additive used in personal protective equipment. Estrogen exhibited higher concentrations in the southern coast of the Yellow River Delta and the northeastern coast of Laizhou bay due to the riverine input and aquaculture. Estrogens could disturb the normal endocrine activities of organisms and edict high ecological risks (90th simulated RQT > 1.0) to aquatic organisms, especially to fish. EE2 was the main contributor of estrogenic potency and ecological risk, which requires special concern. This is the first comprehensive study of estrogen spatiotemporal variations and risks in the Bohai Sea, providing insights into the environmental behavior of estrogens in coastal regions.
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Affiliation(s)
- Shuang Lu
- School of Environmental and Material Engineering, Yantai University, Yantai 264005, China; Beijing Normal University, Beijing 100875, China
| | - Jing Wang
- Beijing Normal University, Beijing 100875, China.
| | - Baodong Wang
- First Institute of Oceanography, Ministry in of Natural Resources, Qingdao 266061, China
| | - Ming Xin
- First Institute of Oceanography, Ministry in of Natural Resources, Qingdao 266061, China
| | - Chunye Lin
- Beijing Normal University, Beijing 100875, China
| | - Xiang Gu
- Beijing Normal University, Beijing 100875, China
| | - Maoshan Lian
- Beijing Normal University, Beijing 100875, China
| | - Yun Li
- Beijing Normal University, Beijing 100875, China
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Shi H, Du Y, Xiong Y, Deng Y, Li Q. Source-oriented health risk assessment of groundwater nitrate by using EMMTE coupled with HHRA model. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 934:173283. [PMID: 38759927 DOI: 10.1016/j.scitotenv.2024.173283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Revised: 04/20/2024] [Accepted: 05/13/2024] [Indexed: 05/19/2024]
Abstract
Conventional concentration-oriented approaches for nitrate risk diagnosis only provide overall risk levels without identifying risk values of individual sources or sources accountable for potential health risks. Therefore, a hybrid model combining the end-member mixing model tool on Excel™ (EMMTE) with human health risk assessment (HHRA) was developed to assess the source-oriented health risks for groundwater nitrate, particularly in the Poyang Lake Plain (PLP) region. The results indicated that the EMMTE and the Bayesian stable isotope mixing model (MixSIAR) exhibited remarkable consistency in source apportionment of groundwater nitrate. The source contribution of groundwater nitrate in PLP was related to land use types, hydrogeological conditions, and soil properties. Notably, manure and sewage sources, contributing up to 53.4 %, represented the largest nitrate pollution sources, with a significant contribution of soil nitrogen and nitrogen fertilizers. The non-carcinogenic risk for four potential sources was below the acceptable threshold of 1. Given the factors including rainfall dilution and economic development, attention should be directed towards mitigating the health risks posed by manure and sewage. This study can verify the efficacy of EMMTE in source apportionment and offer valuable insights for decision-makers to regulate the largest sources of nitrate contamination and enhance groundwater management efficiency.
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Affiliation(s)
- Huanhuan Shi
- MOE Key Laboratory of Groundwater Quality and Health, China University of Geosciences, Wuhan, 430078, China; State Environmental Protection Key Laboratory of Source Apportionment and Control of Aquatic Pollution, China University of Geosciences, Wuhan, 430078, China; School of Environmental Studies, State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430078, China
| | - Yao Du
- MOE Key Laboratory of Groundwater Quality and Health, China University of Geosciences, Wuhan, 430078, China; State Environmental Protection Key Laboratory of Source Apportionment and Control of Aquatic Pollution, China University of Geosciences, Wuhan, 430078, China; School of Environmental Studies, State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430078, China.
| | - Yaojin Xiong
- MOE Key Laboratory of Groundwater Quality and Health, China University of Geosciences, Wuhan, 430078, China; State Environmental Protection Key Laboratory of Source Apportionment and Control of Aquatic Pollution, China University of Geosciences, Wuhan, 430078, China; School of Environmental Studies, State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430078, China
| | - Yamin Deng
- MOE Key Laboratory of Groundwater Quality and Health, China University of Geosciences, Wuhan, 430078, China; State Environmental Protection Key Laboratory of Source Apportionment and Control of Aquatic Pollution, China University of Geosciences, Wuhan, 430078, China; School of Environmental Studies, State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430078, China
| | - Qinghua Li
- Wuhan Center of China Geological Survey, Wuhan 430205, China.
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Yang Y, Lu X, Yu B, Wang Z, Wang L, Lei K, Zuo L, Fan P, Liang T. Exploring the environmental risks and seasonal variations of potentially toxic elements (PTEs) in fine road dust in resource-based cities based on Monte Carlo simulation, geo-detector and random forest model. JOURNAL OF HAZARDOUS MATERIALS 2024; 473:134708. [PMID: 38795490 DOI: 10.1016/j.jhazmat.2024.134708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Revised: 05/13/2024] [Accepted: 05/22/2024] [Indexed: 05/28/2024]
Abstract
The environmental pollution caused by mineral exploitation and energy consumption poses a serious threat to ecological security and human health, particularly in resource-based cities. To address this issue, a comprehensive investigation was conducted on potentially toxic elements (PTEs) in road dust from different seasons to assess the environmental risks and influencing factors faced by Datong City. Multivariate statistical analysis and absolute principal component score were employed for source identification and quantitative allocation. The geo-accumulation index and improved Nemerow index were utilized to evaluate the pollution levels of PTEs. Monte Carlo simulation was employed to assess the ecological-health risks associated with PTEs content and source orientation. Furthermore, geo-detector and random forest analysis were conducted to examine the key environmental variables and driving factors contributing to the spatiotemporal variation in PTEs content. In all PTEs, Cd, Hg, and Zn exhibited higher levels of content, with an average content/background value of 3.65 to 4.91, 2.53 to 3.34, and 2.15 to 2.89 times, respectively. Seasonal disparities were evident in PTEs contents, with average levels generally showing a pattern of spring (winter) > summer (autumn). PTEs in fine road dust (FRD) were primarily influenced by traffic, natural factors, coal-related industrial activities, and metallurgical activities, contributing 14.9-33.9 %, 41.4-47.5 %, 4.4-8.3 %, and 14.2-29.4 % to the total contents, respectively. The overall pollution and ecological risk of PTEs were categorized as moderate and high, respectively, with the winter season exhibiting the most severe conditions, primarily driven by Hg emissions from coal-related industries. Non-carcinogenic risk of PTEs for adults was within the safe limit, yet children still faced a probability of 4.1 %-16.4 % of unacceptable risks, particularly in summer. Carcinogenic risks were evident across all demographics, with children at the highest risk, mainly due to Cr and smelting industrial sources. Geo-detector and random forest model indicated that spatial disparities in prioritized control elements (Cr and Hg) were primarily influenced by particulate matter (PM10) and anthropogenic activities (industrial and socio-economic factors); variations in particulate matter (PM10 and PM2.5) and meteorological factors (wind speed and precipitation) were the primary controllers of seasonal disparities of Cr and Hg.
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Affiliation(s)
- Yufan Yang
- Department of Environmental Science, School of Geography and Tourism, Shaanxi Normal University, Xi'an 710119, China
| | - Xinwei Lu
- Department of Environmental Science, School of Geography and Tourism, Shaanxi Normal University, Xi'an 710119, China.
| | - Bo Yu
- Department of Environmental Science, School of Geography and Tourism, Shaanxi Normal University, Xi'an 710119, China
| | - Zhenze Wang
- Department of Environmental Science, School of Geography and Tourism, Shaanxi Normal University, Xi'an 710119, China
| | - Lingqing Wang
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
| | - Kai Lei
- School of Biological and Environmental Engineering, Xi'an University, Xi'an 710065, China
| | - Ling Zuo
- Department of Environmental Science, School of Geography and Tourism, Shaanxi Normal University, Xi'an 710119, China
| | - Peng Fan
- Department of Environmental Science, School of Geography and Tourism, Shaanxi Normal University, Xi'an 710119, China
| | - Tao Liang
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
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Ma W, Wang M, Wang M, Tao L, Li Y, Yang S, Zhang F, Sui S, Jia L. Assessment of the migration characteristics and source-oriented health risks of heavy metals in the soil and groundwater of a legacy contaminated by the chlor-alkali industry in central China. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2024; 46:280. [PMID: 38963449 DOI: 10.1007/s10653-024-02037-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Accepted: 05/17/2024] [Indexed: 07/05/2024]
Abstract
The chlor-alkali industry (CAI) is crucial for global chemical production; however, its operation has led to widespread heavy metal (HM) contamination at numerous sites, which has not been thoroughly investigated. This study analysed 122 soil and groundwater samples from a typical CAI site in Kaifeng, China. Our aim was to assess the ecological and health risks, identify the sources, and examine the migration characteristics of HMs at this site using Monte Carlo simulation, absolute principal component score-multiple linear regression (APCS-MLR), and the potential environmental risk index (Ei). Our findings revealed that the exceedance rates for Cd, Pb, Hg, and Ni were 71.96%, 45.79%, 49.59%, and 65.42%, respectively. Mercury (Hg) displayed the greatest coefficient of variation across all the soil layers, indicating a significant anthropogenic influence. Cd and Hg were identified as having high and extremely high potential environmental risk levels, respectively. The spatial distributions of the improved Nemerow index (INI), total ecological risk (Ri), and HM content varied considerably, with the most contaminated areas typically associated with the storage of raw and auxiliary materials. Surface aggregation and significant vertical transport were noted for HMs; As and Ni showed substantial accumulation in subsoil layers, severely contaminating the groundwater. Self-organizing maps categorized the samples into two different groups, showing strong positive correlations between Cd, Pb, and Hg. The APCS-MLR model suggested that industrial emissions were the main contributors, accounting for 60.3% of the total HM input. Elevated hazard quotient values for Hg posed significant noncarcinogenic risks, whereas acceptable levels of carcinogenic risk were observed for both adults (96.60%) and children (97.83%). This study significantly enhances historical CAI pollution data and offers valuable insights into ongoing environmental and health challenges.
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Affiliation(s)
- Wanqi Ma
- College of Resource and Environment, Henan Polytechnic University, Jiaozuo, 454003, China
| | - Mingya Wang
- College of Resource and Environment, Henan Polytechnic University, Jiaozuo, 454003, China
| | - Mingshi Wang
- College of Resource and Environment, Henan Polytechnic University, Jiaozuo, 454003, China.
| | - Lu Tao
- Jiaozuo Environmental Monitoring Station, Jiaozuo, 454003, China
| | - Yuanhang Li
- Henan Non-Ferrous Geotechnical Engineering Company, Zhengzhou, 450003, China
| | - Shili Yang
- College of Resource and Environment, Henan Polytechnic University, Jiaozuo, 454003, China
| | - Fan Zhang
- College of Resource and Environment, Henan Polytechnic University, Jiaozuo, 454003, China
| | - Shaobo Sui
- College of Resource and Environment, Henan Polytechnic University, Jiaozuo, 454003, China
| | - Luhao Jia
- College of Resource and Environment, Henan Polytechnic University, Jiaozuo, 454003, China
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Zhang Y, Ji J, Su B, Xu M, Wang Y, Jiao H, Li N, Zhang H, Li S, Wu J, Gao C. Fate and potential ecological risk of rare earth elements in 3000-year reclaimed soil chronosequences. JOURNAL OF HAZARDOUS MATERIALS 2024; 476:135076. [PMID: 38991636 DOI: 10.1016/j.jhazmat.2024.135076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Revised: 06/05/2024] [Accepted: 06/28/2024] [Indexed: 07/13/2024]
Abstract
The introduction of anthropogenic inputs into natural systems may lead to enduring alterations in the innate characteristics of Rare Earth Elements (REEs). Against this backdrop, the evolutionary processes and environmental drivers of REEs in soil remain uncertain. A 3000-year soil chronosequence with uniform parent material was established in reclaimed farmland along the Yangtze River, reconstructing, for the first time, the dynamic processes of REE accumulation and fractionation over a long-time scale. Analysis of 122 soil samples showed REE concentrations ranging from 146.00 to 216.56 μg/g. Based on reclamation duration, three significant stages of REE evolution were identified: natural leaching, rapid accumulation, and stable accumulation with differentiation. Reclaimed soil after 3000 years exhibited a 14.1 % increase in REE concentrations compared to fresh sediments, attributed to anthro -pedogenic processes. Moreover, Heavy Rare Earth Elements (HREEs) accumulated faster than Light Rare Earth Elements (LREEs), particularly in deeper soils (60-100 cm), where HREE concentrations rose by 34.3 %, mainly due to acidic environments promoting HREE fixation. Additionally, the potential ecological risk posed by REEs heightened with reclamation duration, with HREEs exhibiting a sensitivity of 83 % to 94 %. Our findings stress the urgency of carefully monitoring exogenous REEs introduced through anthropogenic activities, particularly HREEs.
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Affiliation(s)
- Yalu Zhang
- School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
| | - Jiachen Ji
- School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
| | - Baowei Su
- School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
| | - Mingxu Xu
- School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
| | - Yonghong Wang
- School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
| | - He Jiao
- School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
| | - Ning Li
- School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
| | - Huan Zhang
- School of Marine Science and Engineering, Nanjing Normal University, Nanjing 210023, China
| | - Shengfeng Li
- School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
| | - Jingtao Wu
- School of Geography and Planning, Huaiyin Normal University, Huaian 223300, China
| | - Chao Gao
- School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China.
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9
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Su C, Yang Y, Jia M, Yan Y. Integrated framework to assess soil potentially toxic element contamination through 3D pollution analysis in a typical mining city. CHEMOSPHERE 2024; 359:142378. [PMID: 38763392 DOI: 10.1016/j.chemosphere.2024.142378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 05/16/2024] [Accepted: 05/17/2024] [Indexed: 05/21/2024]
Abstract
Soil potentially toxic elements (PTEs) pollution of contaminated sites has become a global environmental issue. However, given that previous studies mostly focused on pollution assessment in surface soils, the current status and environmental risks of potentially toxic elements in deeper soils remain unclear. The present study aims to cognize distribution characteristics and spatial autocorrelation, pollution levels, and risk assessment in a stereoscopic environment for soil PTEs through 3D visualization techniques. Pollution levels were assessed in an integrated manner by combining the geoaccumulation index (Igeo), the integrated influence index of soil quality (IICQs), and potential ecological hazard index. Results showed that soil environment at the site was seriously threatened by PTEs, and Cu and Cd were ubiquitous and the predominant pollutants in the study area. The stratigraphic models and pollution plume simulation revealed that pollutants show a decreasing trend with the deepening of the soil layer. The ranking of contamination soil volume is as follows: Cu > Cd > Zn > As > Pb > Cr > Ni. According to the IICQs evaluation, this region was subject to multiple PTE contamination, with more than 60% of the area becoming seriously and highly polluted. In addition, the ecological hazard model revealed the existence of substantial ecological hazards in the soils of the site. The integrated potential ecological risk index (RI) indicated that 45.7%, 10.13%, and 4.15% of the stereoscopic areas were in considerable, high, and very high risks, respectively. The findings could be used as a theoretical reference for applying multiple methods to integrate evaluation through 3D visualization analysis in the assessment and remediation of PTE-contaminated soils.
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Affiliation(s)
- Chuanghong Su
- College of Resources and Environment, Huazhong Agricultural University, Wuhan, 430070, China; Hubei Key Laboratory of Soil Environment and Pollution Remediation, China; Key Laboratory of Arable Land Conservation (Middle and Lower Reaches of Yangtze River), Ministry of Agriculture, China.
| | - Yong Yang
- College of Resources and Environment, Huazhong Agricultural University, Wuhan, 430070, China; Hubei Key Laboratory of Soil Environment and Pollution Remediation, China; Key Laboratory of Arable Land Conservation (Middle and Lower Reaches of Yangtze River), Ministry of Agriculture, China.
| | - Mengyao Jia
- College of Resources and Environment, Huazhong Agricultural University, Wuhan, 430070, China; Hubei Key Laboratory of Soil Environment and Pollution Remediation, China; Key Laboratory of Arable Land Conservation (Middle and Lower Reaches of Yangtze River), Ministry of Agriculture, China
| | - Yibo Yan
- College of Resources and Environment, Huazhong Agricultural University, Wuhan, 430070, China; Hubei Key Laboratory of Soil Environment and Pollution Remediation, China; Key Laboratory of Arable Land Conservation (Middle and Lower Reaches of Yangtze River), Ministry of Agriculture, China
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10
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Liu S, Wu K, Yao L, Li Y, Chen R, Zhang L, Wu Z, Zhou Q. Characteristics and correlation analysis of heavy metal distribution in China's freshwater aquaculture pond sediments. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 931:172909. [PMID: 38703834 DOI: 10.1016/j.scitotenv.2024.172909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 04/28/2024] [Accepted: 04/29/2024] [Indexed: 05/06/2024]
Abstract
The concentration of heavy metals (HMs) in aquaculture pond sediments significantly affects aquatic food safety and environmental quality. The contamination characteristics, drivers and potential sources of HMs in typical bulk freshwater aquaculture pond sediments in major provinces of China were systematically investigated using a variety of methods and models. Specifically, 130 surface sediment samples were collected from the study area, and the geoaccumulation index (Igeo) and potential ecological risk index (RI) were used to jointly evaluate the characteristics of the HMs. Spearman's correlation and redundancy analysis revealed the main drivers of the HMs. Additionally, the positive matrix factorization (PMF) model and absolute principal component score-multiple linear regression (APCS-MLR) model were used to identify the sources of HMs. The results revealed that the pond sediments were safe for fish culture in most of the study areas. Aquafeed protein content is an important driver of HM concentrations in sediments. The total organic carbon (TOC) content, percentage of clay particles, and pH of the aquaculture pond sediments determined the sediment HMs enrichment abilities as 13.6 %, 52 %, and 9.8 %, respectively. Cd, a significantly enriched pollutant, posed a greater ecological risk than the other five HMs (Cr, Cu, Zn, As, and Pb). Three sources of HMs were identified, including agricultural activity (e.g., aquafeeds, pesticides, and fertilizers), industrial production, and natural sources, with contributions of 44.29 %, 36.66 %, and 19.05 %, respectively. This study provides a scientific basis for minimizing the input and accumulation of HMs in freshwater aquaculture pond sediments, and this can provide insights into the prevention and control of the ecological risks posed by HMs.
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Affiliation(s)
- Shouzhuang Liu
- Key laboratory of Lake and Watershed Science for Water Security, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China; China University of Geosciences, Wuhan 430074, China
| | - Kaixuan Wu
- Key laboratory of Lake and Watershed Science for Water Security, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lu Yao
- Key laboratory of Lake and Watershed Science for Water Security, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China
| | - Yahua Li
- China University of Geosciences, Wuhan 430074, China
| | - Ruonan Chen
- Key laboratory of Lake and Watershed Science for Water Security, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China; China University of Geosciences, Wuhan 430074, China
| | - Liping Zhang
- Key laboratory of Lake and Watershed Science for Water Security, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China
| | - Zhenbin Wu
- Key laboratory of Lake and Watershed Science for Water Security, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China
| | - Qiaohong Zhou
- Key laboratory of Lake and Watershed Science for Water Security, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China.
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11
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Hu J, Wang P, Li J, Zhang Q, Tian L, Liu T, Ma W, Zheng H. Hazard profiles, distribution trends, and sources tracing of rare earth elements in dust of kindergartens in Beijing. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 358:124374. [PMID: 38906400 DOI: 10.1016/j.envpol.2024.124374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Revised: 05/30/2024] [Accepted: 06/13/2024] [Indexed: 06/23/2024]
Abstract
Children, the most vulnerable group in urban populations, are susceptible to the effects of pollution in urban environments. It is significant to evaluate the influence of rare earth elements (REEs) from kindergartens dust (KD) in Beijing on children's health. This study collected surface dust from 73 kindergartens in 16 districts of the mega-city of Beijing, and the concentrations of 14 REEs in KD, including La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, and Lu, were detected. The contamination levels, source apportionment, and health exposure risk of REEs were comprehensively investigated. The results indicate that the contamination levels of 14 REEs are within the acceptable range. Nevertheless, Eu, Ce, La, Pr, Nd, Gd, and Sm show high enrichment due to anthropogenic influence. Besides, KD is rich in light rare earth elements (LREEs) (90.97 mg kg-1) compared to heavy rare earth elements (HREEs) (8.65 mg kg-1). The distribution parameter patterns of REEs suggest that complicated anthropogenic sources influence the enrichment of REEs in KD. The main sources of REEs in KD include natural sources (40.64%), mixed high-tech industries and construction (33.89%), and mixed coal-fired, historical industrial, and transportation sources (26.47%). The primary pathway for daily intake of REEs in children is through ingestion, which presents a low but not negligible health risk. This study provides guidance for the effective risk management of REEs in KD.
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Affiliation(s)
- Jian Hu
- The State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, PR China; University of Chinese Academy of Sciences, Beijing, 100049, PR China.
| | - Peng Wang
- The State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, PR China; State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences (Beijing), Beijing, 100083, PR China; Institute of Earth Sciences, China University of Geosciences (Beijing), Beijing, 100083, PR China
| | - Jun Li
- The State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, PR China; University of Chinese Academy of Sciences, Beijing, 100049, PR China
| | - Qian Zhang
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, PR China
| | - Liyan Tian
- Institute of Process Engineering, Chinese Academy of Sciences, Beijing, 100190, PR China
| | - Tingyi Liu
- Tianjin Key Laboratory of Water Resources and Environment, Tianjin Normal University, Tianjin, 300387, PR China
| | - Wenmin Ma
- The State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, PR China; State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences (Beijing), Beijing, 100083, PR China; Institute of Earth Sciences, China University of Geosciences (Beijing), Beijing, 100083, PR China
| | - Houyi Zheng
- China National Administration of Coal Geology, Beijing, 100038, PR China
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Zhang Y, Jiang B, Gao Z, Wang M, Feng J, Xia L, Liu J. Health risk assessment of soil heavy metals in a typical mining town in north China based on Monte Carlo simulation coupled with Positive matrix factorization model. ENVIRONMENTAL RESEARCH 2024; 251:118696. [PMID: 38493860 DOI: 10.1016/j.envres.2024.118696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 03/02/2024] [Accepted: 03/11/2024] [Indexed: 03/19/2024]
Abstract
The accumulation of heavy metals (HMs) in soil caused by mineral resource exploitation and its ancillary industrial processes poses a threat to ecology and public health. Effective risk control measures require a quantification of the impacts and contributions to health risks from individual sources of soil HMs. Based on high-density sampling, soil contamination risk indexes, positive matrix factorization (PMF) model, Monte Carlo simulation and human health risk analysis model were applied to investigate the risk of HMs in a typical mining town in North China. The results showed that As was the most dominant soil pollutant factor, Cd and Hg were the most dominant soil ecological risk factors, and Cr and Ni were the most dominant health risk factors in the study area. Overall, both pollution and ecological risks were at low levels, while there were still some higher hazard areas located in the central and south-central part of the region. According to the probabilistic health risk assessment (HRA), children suffered greater health risks than adults, with 21.63% of non-carcinogenic risks and 53.24% of carcinogenic risks exceeding the prescribed thresholds (HI > 1 and TCR>1E-4). The PMF model identified five potential sources: fuel combustion (FC), processing of building materials with limestone as raw materials (PBML), industry source (IS), iron ore mining combined with garbage (IOG), and agriculture source (AS). PBML is the primary source of soil HM contamination, as well as the major anthropogenic source of carcinogenic risk for all populations. Agricultural inputs associated with As are the major source of non-carcinogenic risk. This study offers a good example of probabilistic HRA using specific sources, which can provide a valuable reference for strategy establishment of pollution remediation and risk prevention and control.
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Affiliation(s)
- Yuqi Zhang
- College of Earth Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China.
| | - Bing Jiang
- The Fourth Geological Brigade of Shandong Provincial Bureau of Geology and Mineral Resources, Weifang 261021, China; Key Laboratory of Coastal Zone Geological Environment Protection of Shandong Geology and Mineral Exploration and Development Bureau, Weifang 261021, China.
| | - Zongjun Gao
- College of Earth Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China.
| | - Min Wang
- College of Earth Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China.
| | - Jianguo Feng
- College of Earth Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China.
| | - Lu Xia
- College of Earth Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China.
| | - Jiutan Liu
- College of Earth Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China.
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Lv S, Zhu Y, Cheng L, Zhang J, Shen W, Li X. Evaluation of the prediction effectiveness for geochemical mapping using machine learning methods: A case study from northern Guangdong Province in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 927:172223. [PMID: 38588737 DOI: 10.1016/j.scitotenv.2024.172223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 03/06/2024] [Accepted: 04/03/2024] [Indexed: 04/10/2024]
Abstract
This study compares seven machine learning models to investigate whether they improve the accuracy of geochemical mapping compared to ordinary kriging (OK). Arsenic is widely present in soil due to human activities and soil parent material, posing significant toxicity. Predicting the spatial distribution of elements in soil has become a current research hotspot. Lianzhou City in northern Guangdong Province, China, was chosen as the study area, collecting a total of 2908 surface soil samples from 0 to 20 cm depth. Seven machine learning models were chosen: Random Forest (RF), Support Vector Machine (SVM), Ridge Regression (Ridge), Gradient Boosting Decision Tree (GBDT), Artificial Neural Network (ANN), K-Nearest Neighbors (KNN), and Gaussian Process Regression (GPR). Exploring the advantages and disadvantages of machine learning and traditional geological statistical models in predicting the spatial distribution of heavy metal elements, this study also analyzes factors affecting the accuracy of element prediction. The two best-performing models in the original model, RF (R2 = 0.445) and GBDT (R2 = 0.414), did not outperform OK (R2 = 0.459) in terms of prediction accuracy. Ridge and GPR, the worst-performing methods, have R2 values of only 0.201 and 0.248, respectively. To improve the models' prediction accuracy, a spatial regionalized (SR) covariate index was added. Improvements varied among different methods, with RF and GBDT increasing their R2 values from 0.4 to 0.78 after enhancement. In contrast, the GPR model showed the least significant improvement, with its R2 value only reaching 0.25 in the improved method. This study concluded that choosing the right machine learning model and considering factors that influence prediction accuracy, such as regional variations, the number of sampling points, and their distribution, are crucial for ensuring the accuracy of predictions. This provides valuable insights for future research in this area.
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Affiliation(s)
- Songjian Lv
- Center for Health Geology & Carbon Peak and Carbon Neutrality of Lanzhou University, Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
| | - Ying Zhu
- Center for Health Geology & Carbon Peak and Carbon Neutrality of Lanzhou University, Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
| | - Li Cheng
- Center for Health Geology & Carbon Peak and Carbon Neutrality of Lanzhou University, Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
| | - Jingru Zhang
- Center for Health Geology & Carbon Peak and Carbon Neutrality of Lanzhou University, Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China; Guangdong Province Academic of Environmental Science, Guangzhou 510045, China
| | - Wenjie Shen
- School of Earth Sciences and Engineering, Sun Yat-sen University, Zhuhai 519000, China
| | - Xingyuan Li
- Center for Health Geology & Carbon Peak and Carbon Neutrality of Lanzhou University, Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China.
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14
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Gong C, Xia X, Lan M, Shi Y, Lu H, Wang S, Chen Y. Source identification and driving factor apportionment for soil potentially toxic elements via combining APCS-MLR, UNMIX, PMF and GDM. Sci Rep 2024; 14:10918. [PMID: 38740813 DOI: 10.1038/s41598-024-58673-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2024] [Accepted: 04/02/2024] [Indexed: 05/16/2024] Open
Abstract
The contamination and quantification of soil potentially toxic elements (PTEs) contamination sources and the determination of driving factors are the premise of soil contamination control. In our study, 788 soil samples from the National Agricultural Park in Chengdu, Sichuan Province were used to evaluate the contamination degree of soil PTEs by pollution factors and pollution load index. The source identification of soil PTEs was performed using positive matrix decomposition (PMF), edge analysis (UNMIX) and absolute principal component score-multiple line regression (APCS-MLR). The geo-detector method (GDM) was used to analysis drivers of soil PTEs pollution sources to help interpret pollution sources derived from receptor models. Result shows that soil Cu, Pb, Zn, Cr, Ni, Cd, As and Hg average content were 35.2, 32.3, 108.9, 91.9, 37.1, 0.22, 9.76 and 0.15 mg/kg in this study area. Except for As, all are higher than the corresponding soil background values in Sichuan Province. The best performance of APCS-MLR was determined by comparison, and APCS-MLR was considered as the preferred receptor model for soil PTEs source distribution in the study area. ACPS-MLR results showed that 82.70% of Cu, 61.6% of Pb, 75.3% of Zn, 91.9% of Cr and 89.4% of Ni came from traffic-industrial emission sources, 60.9% of Hg came from domestic-transportation emission sources, 57.7% of Cd came from agricultural sources, and 89.5% of As came from natural sources. The GDM results showed that distance from first grade highway, population, land utilization and total potassium (TK) content were the main driving factors affecting these four sources, with q values of 0.064, 0.048, 0.069 and 0.058, respectively. The results can provide reference for reducing PTEs contamination in farmland soil.
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Affiliation(s)
- Cang Gong
- Research Center of Applied Geology of China Geological Survey, Chengdu, China
- Key Laboratory of Natural Resource Coupling Process and Effects, Beijing, China
| | - Xiang Xia
- Research Center of Applied Geology of China Geological Survey, Chengdu, China.
| | - Mingguo Lan
- Technology Innovation Center for Analysis and Detection of the Elemental Speciation and Emerging Contaminants, China Geological Survey, Kunming, China
| | - Youchang Shi
- Technology Innovation Center for Analysis and Detection of the Elemental Speciation and Emerging Contaminants, China Geological Survey, Kunming, China
| | - Haichuan Lu
- Research Center of Applied Geology of China Geological Survey, Chengdu, China
| | - Shunxiang Wang
- Research Center of Applied Geology of China Geological Survey, Chengdu, China
| | - Ying Chen
- Research Center of Applied Geology of China Geological Survey, Chengdu, China.
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15
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Zhao Z, Li S, Li Y. Controlling factors and sources-specific ecological risks associated with toxic metals in core sediments from cascade reservoirs in Southwest China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 924:171570. [PMID: 38460694 DOI: 10.1016/j.scitotenv.2024.171570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 02/27/2024] [Accepted: 03/06/2024] [Indexed: 03/11/2024]
Abstract
Toxic metals (TMs) in reservoir sediments pose significant risks to ecosystem security and human safety, yet their presence in the cascade reservoirs of the Lancang River remains understudied. This research examined TMs in core sediments from the Manwan (MW) and Dachaoshan (DCS) cascade reservoirs, aiming to elucidate contamination characteristics, controlling factors, and source-specific ecological risks. The study revealed that the concentrations of As, Cd, Cr, Cu, Hg, Ni, and Zn in the MW Reservoir (37.3, 0.54, 95.1, 44.0, 0.09, 44.8, and 135.7 mg/kg) were notably higher compared to the DCS Reservoir (14.6, 0.30, 82.6, 31.0, 0.08, 36.6, and 108.7 mg/kg). While both reservoirs demonstrated elevated contamination levels of Cd and Hg, the MW Reservoir also exhibited high levels of As, whereas the DCS Reservoir showed relatively high levels of Pb. Mining activities in upstream metal deposits significantly correlated Cd, Hg, and Zn in the MW Reservoir with sulfur. In both reservoir sediments, Cr and Ni displayed a greater affinity for iron oxides, while As, Cd, Cu, Hg, and Zn showed more affinity with manganese oxides. Ecological risk index (RI) values in half of the sediments from the MW Reservoir ranged from 300 to 600, denoting a significant ecological risk. Conversely, in the DCS Reservoir, 93.3 % of the sediments exhibited RI values between 150 and 300, signifying a moderate ecological risk. Source-oriented ecological risks highlighted the need for particular attention to Cd from anthropogenic sources in the MW Reservoir. These findings underscore the importance of implementing measures for TM contamination prevention and control, contributing to strategic planning for sustainable water resource management in the Lancang-Mekong River.
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Affiliation(s)
- Zhenjie Zhao
- Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, School of Public Health, Guizhou Medical University, Guiyang 550025, China; State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China; Collaborative Innovation Center for Prevention and Control of Endemic and Ethnic Regional Diseases Co-constructed by the Province and Ministry, Guizhou Medical University, Guiyang 550025, China
| | - Shehong Li
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China.
| | - Yunlong Li
- Shandong Institute of Geophysical and Geochemical Exploration, Jinan 250013, China
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16
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Shao F, Li K, Ouyang D, Zhou J, Luo Y, Zhang H. Sources apportionments of heavy metal(loid)s in the farmland soils close to industrial parks: Integrated application of positive matrix factorization (PMF) and cadmium isotopic fractionation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 924:171598. [PMID: 38461995 DOI: 10.1016/j.scitotenv.2024.171598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 03/05/2024] [Accepted: 03/07/2024] [Indexed: 03/12/2024]
Abstract
Understanding the source identification and distribution of heavy metal(loid)s in soil is essential for risk management. The sources of heavy metal(loid)s in farmland soil, especially in areas with rapid economic development, were complicated and need to be explored urgently. This study combined geographic information system (GIS) mapping, positive matrix factorization (PMF) model and cadmium (Cd) isotope fingerprinting methods to identify heavy metal(loid) sources in a typical town in the economically developed Yangtze River Delta region of China. Cd, As, Cu, Zn, Pb, Ni and Co in different samples were detected. The results showed that Cd was the most severely contaminated element, with an exceedance rate of 78.0 %. GIS mapping results indicated that the hotspot area was located in the northeastern area with prolonged operational histories of electroplating and non-ferrous metal smelting industries. The PMF model analysis also identified emissions from smelting and electroplating enterprises as the main sources of Cd in the soil, counted for 49.28 %, followed by traffic (25.66 %) and agricultural (25.06 %) sources. Through further isotopic analysis, it was found that in soil samples near the industrial park, the contribution of electroplating and non-ferrous metal smelting enterprises to cadmium pollution was significantly higher than other regions. The integrated use of various methodologies allows for precise analysis of sources and input pathways, offering valuable insights for future pollution control and soil remediation endeavors.
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Affiliation(s)
- Fanglei Shao
- Zhejiang Provincial Key Laboratory of Soil Contamination Bioremediation, College of Environmental and Resource Sciences, Zhejiang Agriculture and Forestry University, Hangzhou 311300, China; Sino-Spain Joint Laboratory for Agricultural Environment Emerging Contaminants of Zhejiang Province, College of Environmental and Resource Sciences, Zhejiang Agriculture and Forestry University, Hangzhou 311300, China
| | - Kainan Li
- Zhejiang Provincial Key Laboratory of Soil Contamination Bioremediation, College of Environmental and Resource Sciences, Zhejiang Agriculture and Forestry University, Hangzhou 311300, China; Sino-Spain Joint Laboratory for Agricultural Environment Emerging Contaminants of Zhejiang Province, College of Environmental and Resource Sciences, Zhejiang Agriculture and Forestry University, Hangzhou 311300, China
| | - Da Ouyang
- Zhejiang Provincial Key Laboratory of Soil Contamination Bioremediation, College of Environmental and Resource Sciences, Zhejiang Agriculture and Forestry University, Hangzhou 311300, China; Sino-Spain Joint Laboratory for Agricultural Environment Emerging Contaminants of Zhejiang Province, College of Environmental and Resource Sciences, Zhejiang Agriculture and Forestry University, Hangzhou 311300, China
| | - Jiawen Zhou
- Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
| | - Yating Luo
- Zhejiang Provincial Key Laboratory of Soil Contamination Bioremediation, College of Environmental and Resource Sciences, Zhejiang Agriculture and Forestry University, Hangzhou 311300, China; Sino-Spain Joint Laboratory for Agricultural Environment Emerging Contaminants of Zhejiang Province, College of Environmental and Resource Sciences, Zhejiang Agriculture and Forestry University, Hangzhou 311300, China.
| | - Haibo Zhang
- Zhejiang Provincial Key Laboratory of Soil Contamination Bioremediation, College of Environmental and Resource Sciences, Zhejiang Agriculture and Forestry University, Hangzhou 311300, China; Sino-Spain Joint Laboratory for Agricultural Environment Emerging Contaminants of Zhejiang Province, College of Environmental and Resource Sciences, Zhejiang Agriculture and Forestry University, Hangzhou 311300, China.
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17
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Monaco F, Vignapiano A, Piacente M, Farina F, Pagano C, Marenna A, Leo S, Vecchi C, Mancuso C, Prisco V, Iodice D, Auricchio A, Cavaliere R, D'Agosto A, Fornaro M, Solmi M, Corrivetti G, Fasano A. Innova4Health: an integrated approach for prevention of recurrence and personalized treatment of Major Depressive Disorder. Front Artif Intell 2024; 7:1366055. [PMID: 38774832 PMCID: PMC11106633 DOI: 10.3389/frai.2024.1366055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Accepted: 04/22/2024] [Indexed: 05/24/2024] Open
Abstract
Background Major Depressive Disorder (MDD) is a prevalent mental health condition characterized by persistent low mood, cognitive and physical symptoms, anhedonia (loss of interest in activities), and suicidal ideation. The World Health Organization (WHO) predicts depression will become the leading cause of disability by 2030. While biological markers remain essential for understanding MDD's pathophysiology, recent advancements in social signal processing and environmental monitoring hold promise. Wearable technologies, including smartwatches and air purifiers with environmental sensors, can generate valuable digital biomarkers for depression assessment in real-world settings. Integrating these with existing physical, psychopathological, and other indices (autoimmune, inflammatory, neuroradiological) has the potential to improve MDD recurrence prevention strategies. Methods This prospective, randomized, interventional, and non-pharmacological integrated study aims to evaluate digital and environmental biomarkers in adolescents and young adults diagnosed with MDD who are currently taking medication. The study implements a sensor-integrated platform built around an open-source "Pothos" air purifier system. This platform is designed for scalability and integration with third-party devices. It accomplishes this through software interfaces, a dedicated app, sensor signal pre-processing, and an embedded deep learning AI system. The study will enroll two experimental groups (10 adolescents and 30 young adults each). Within each group, participants will be randomly allocated to Group A or Group B. Only Group B will receive the technological equipment (Pothos system and smartwatch) for collecting digital biomarkers. Blood and saliva samples will be collected at baseline (T0) and endpoint (T1) to assess inflammatory markers and cortisol levels. Results Following initial age-based stratification, the sample will undergo detailed classification at the 6-month follow-up based on remission status. Digital and environmental biomarker data will be analyzed to explore intricate relationships between these markers, depression symptoms, disease progression, and early signs of illness. Conclusion This study seeks to validate an AI tool for enhancing early MDD clinical management, implement an AI solution for continuous data processing, and establish an AI infrastructure for managing healthcare Big Data. Integrating innovative psychophysical assessment tools into clinical practice holds significant promise for improving diagnostic accuracy and developing more specific digital devices for comprehensive mental health evaluation.
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Affiliation(s)
- Francesco Monaco
- Department of Mental Health, ASL Salerno, Salerno, Italy
- European Biomedical Research Institute of Salerno (EBRIS), Salerno, Italy
| | - Annarita Vignapiano
- Department of Mental Health, ASL Salerno, Salerno, Italy
- European Biomedical Research Institute of Salerno (EBRIS), Salerno, Italy
| | - Martina Piacente
- European Biomedical Research Institute of Salerno (EBRIS), Salerno, Italy
| | - Federica Farina
- European Biomedical Research Institute of Salerno (EBRIS), Salerno, Italy
| | - Claudio Pagano
- Innovation Technology e Sviluppo (I.T.Svil), Salerno, Italy
| | - Alessandra Marenna
- European Biomedical Research Institute of Salerno (EBRIS), Salerno, Italy
| | - Stefano Leo
- European Biomedical Research Institute of Salerno (EBRIS), Salerno, Italy
| | - Corrado Vecchi
- European Biomedical Research Institute of Salerno (EBRIS), Salerno, Italy
| | - Carlo Mancuso
- Innovation Technology e Sviluppo (I.T.Svil), Salerno, Italy
| | | | - Davide Iodice
- Department of Mental Health, ASL Salerno, Salerno, Italy
| | | | - Roberto Cavaliere
- Ufficio Trasferimento Tecnologico, Università degli Studi di Cassino e del Lazio Meridionale, Cassino, Italy
| | - Amelia D'Agosto
- Istituto Polidiagnostico D'Agosto & Marino, Nocera Inferiore, Italy
| | - Michele Fornaro
- Department of Neuroscience, Reproductive Sciences, and Odontostomatology, Clinical Section of Psychiatry and Psychology, University School of Medicine Federico II, Naples, Italy
| | - Marco Solmi
- Department of Psychiatry, University of Ottawa, Ottawa, ON, Canada
- Department of Mental Health, The Ottawa Hospital, On Track: The Champlain First Episode Psychosis Program, Ottawa, ON, Canada
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON, Canada
- School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada
- Department of Child and Adolescent Psychiatry, Charité—Universitätsmedizin, Berlin, Germany
| | - Giulio Corrivetti
- Department of Mental Health, ASL Salerno, Salerno, Italy
- European Biomedical Research Institute of Salerno (EBRIS), Salerno, Italy
| | - Alessio Fasano
- European Biomedical Research Institute of Salerno (EBRIS), Salerno, Italy
- Department of Pediatrics, Massachusetts General Hospital for Children, Harvard Medical School, Division of Pediatric Gastroenterology and Nutrition, Boston, MA, United States
- Mucosal Immunology and Biology Research Center, Massachusetts General Hospital for Children, Boston, MA, United States
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Mao L, Ren W, Tang Y, Liu X, He M, Sun K, Zhang BT, Lin C, Ouyang W. Comprehensive insight into mercury contamination in atmospheric, terrestrial and aquatic ecosystems surrounding a typical antimony-coal mining district. JOURNAL OF HAZARDOUS MATERIALS 2024; 469:133880. [PMID: 38430592 DOI: 10.1016/j.jhazmat.2024.133880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 01/27/2024] [Accepted: 02/22/2024] [Indexed: 03/05/2024]
Abstract
This study comprehensively investigated mercury (Hg) contents of various environmental compartments in a typical antimony-coal mining area with intensive industrial activities over the past 120 years to analyze Hg environmental behaviors and evaluate Hg risks. The total mercury (THg) contents in river water, sediments, soils, PM10, dust falls, vegetables and corns were 1.16 ± 0.63 µg/L, 2.01 ± 1.64 mg/kg, 1.87 ± 3.88 mg/kg, 7.87 ± 18.68 ng/m3, 13.01 ± 14.53 mg/kg, 0.30 ± 0.34 mg/kg and 3.11 ± 0.51 µg/kg, respectively. The δ202Hg values in soils and dust falls were - 1.58 ∼ 0.12‰ and 0.25 ∼ 0.30‰, respectively. Environmental samples affected by industrial activities in the Xikuangshan (XKS) presented higher THg and δ202Hg values. Binary mixing model proved that atmospheric deposition with considerable Hg deposition flux (0.44 ∼ 6.40, 3.12 ± 2.20 mg/m2/y) in the XKS significantly contributed to Hg accumulations on surface soils. Compared with soils, sediments with more frequent paths and higher burst probabilities presented higher dynamic Hg risks. Children were faced higher health risk of multiple Hg exposure than adults. Furthermore, the health risk of THg by consuming leaf vegetables deserved more attention. These findings provided scientific basis for managing Hg contamination.
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Affiliation(s)
- Lulu Mao
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Wenbo Ren
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Yang Tang
- State Key Laboratory of Ore Deposit Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, 550081 Guiyang, China
| | - Xitao Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China.
| | - Mengchang He
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Ke Sun
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Bo-Tao Zhang
- College of Water Sciences, Beijing Normal University, Beijing 100875, China
| | - Chunye Lin
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Wei Ouyang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China; Advanced Interdisciplinary Institute of Environment and Ecology, Beijing Normal University, Zhuhai 519087, China
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Yang W, Zhang L, Gao B, Liu X, Duan X, Wang C, Zhang Y, Li Q, Wang L. Integrated assessment of potentially toxic elements in soil of the Kangdian metallogenic province: A two-point machine learning approach. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 276:116248. [PMID: 38579531 DOI: 10.1016/j.ecoenv.2024.116248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 02/17/2024] [Accepted: 03/20/2024] [Indexed: 04/07/2024]
Abstract
The accumulation of potentially toxic elements in soil poses significant risks to ecosystems and human well-being due to their inherent toxicity, widespread presence, and persistence. The Kangdian metallogenic province, famous for its iron-copper deposits, faces soil pollution challenges due to various potentially toxic elements. This study explored a comprehensive approach that combinescombines the spatial prediction by the two-point machine learning method and ecological-health risk assessment to quantitatively assess the comprehensive potential ecological risk index (PERI), the total hazard index (THI) and the total carcinogenic risk (TCR). The proportions of copper (Cu), cadmium (Cd), manganese (Mn), lead (Pb), zinc (Zn), and arsenic (As) concentrations exceeding the risk screening values (RSVs) were 15.03%, 5.1%, 3.72%, 1.24%, 1.1%, and 0.13%, respectively, across the 725 collected samples. Spatial prediction revealed elevated levels of As, Cd, Cu, Pb, Zn, mercury (Hg), and Mn near the mining sites. Potentially toxic elements exert a slight impact on soil, some regions exhibit moderate to significant ecological risk, particularly in the southwest. Children face higher non-carcinogenic and carcinogenic health risks compared to adults. Mercury poses the highest ecological risk, while chromium (Cr) poses the greatest health hazard for all populations. Oral ingestion represents the highest non-oncogenic and oncogenic risks in all age groups. Adults faced acceptable non-carcinogenic risks. Children in the southwest region confront higher health risks, both non-carcinogenic and carcinogenic, from mining activities. Urgent measures are vital to mitigate Hg and Cr contamination while promoting handwashing practices is essential to minimize health risks.
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Affiliation(s)
- Wantao Yang
- Yunnan Key Laboratory of Soil Erosion Prevention and Green Development, Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650500, China; Key Laboratory of Natural Resource Coupling Process and Effects, Ministry of Natural Resources, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; Kunming General Survey of Natural Resources Center, China Geological Survey, Kunming 650111, China; Technology Innovation Center for Natural Ecosystem Carbon Sink, Ministry of Natural Resources, Kunming 650111, China
| | - Liankai Zhang
- Kunming General Survey of Natural Resources Center, China Geological Survey, Kunming 650111, China; Technology Innovation Center for Natural Ecosystem Carbon Sink, Ministry of Natural Resources, Kunming 650111, China
| | - Bingbo Gao
- College of Land Science and Technology, China Agricultural University, 17 Tsinghua East Road, Beijing 100083, China
| | - Xiaojie Liu
- Key Laboratory of Natural Resource Coupling Process and Effects, Ministry of Natural Resources, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; Technology Innovation Center for Natural Ecosystem Carbon Sink, Ministry of Natural Resources, Kunming 650111, China.
| | - Xingwu Duan
- Yunnan Key Laboratory of Soil Erosion Prevention and Green Development, Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650500, China
| | - Chenyi Wang
- College of Land Science and Technology, China Agricultural University, 17 Tsinghua East Road, Beijing 100083, China
| | - Ya Zhang
- Kunming General Survey of Natural Resources Center, China Geological Survey, Kunming 650111, China; Technology Innovation Center for Natural Ecosystem Carbon Sink, Ministry of Natural Resources, Kunming 650111, China
| | - Qiang Li
- Kunming General Survey of Natural Resources Center, China Geological Survey, Kunming 650111, China; Technology Innovation Center for Natural Ecosystem Carbon Sink, Ministry of Natural Resources, Kunming 650111, China
| | - Lingqing Wang
- Key Laboratory of Natural Resource Coupling Process and Effects, Ministry of Natural Resources, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
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Wu Q, Li R, Chen J, Yang Z, Li S, Yang Z, Liang Z, Gao L. Historical construction, quantitative source identification and risk assessment of heavy metals contamination in sediments from the Pearl River Estuary, South China. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 359:120943. [PMID: 38701583 DOI: 10.1016/j.jenvman.2024.120943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2024] [Revised: 03/25/2024] [Accepted: 04/16/2024] [Indexed: 05/05/2024]
Abstract
Historical reconstruction of heavy metals (HMs) contamination in sediments is a key for understanding the effects of anthropogenic stresses on water bodies and predicting the variation trends of environmental state. In this work, eighteen sediment cores from the Pearl River Estuary (PRE) were collected to determine concentrations and geochemical fractions of HMs. Then, their potential sources and the relative contributions during different time periods were quantitatively identified by integrating lead-210 (210Pb) radioisotope dating technique into positive matrix factorisation (PMF) method. Pollution levels and potential ecological risks (PERs) caused by HMs were accurately assessed by enrichment factors (EF) based on establishment of their geochemical baselines (GCBs) and multiparameter evaluation index (MPE). HMs concentrations generally showed a particle size- and organic matter-dependent distribution pattern. During the period of 1958-1978, HMs concentrations remained at low levels with agricultural activities and natural processes being identified as the predominant sources and averagely contributing >60%. Since the reform and opening-up in 1978, industrial and traffic factors become the primary anthropogenic sources of HMs (such as Cu, Zn, Cd, Pb, Cr, and Ni), averagely increasing from 22.1% to 28.1% and from 11.6% to 23.4%, respectively. Conversely, the contributions of agricultural and natural factors decreased from 37.0% to 28.5% and from 29.3% to 20.0%, respectively. Subsequently, implementation of environmental preservation policies was mainly responsible for the declining trend of HMs after 2010. Little enrichment of sediment Cu, Zn, Pb, Cr and Ni with EFs (0.15-1.43) was found in the PRE, whereas EFs of Cd (1.16-2.70) demonstrated a slight to moderate enrichment. MPE indices of Cu (50.7-252), Pb (52.0-147), Zn (35.5-130), Ni (19.6-71.5), Cr (14.2-68.8) and Cd (0-9.90) highlighted their potential ecological hazards due to their non-residual fractions and anthropogenic sources.
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Affiliation(s)
- Qirui Wu
- Carbon-Water Research Station in Karst Regions of Northern Guangdong, School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
| | - Rui Li
- Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, China
| | - Jianyao Chen
- Carbon-Water Research Station in Karst Regions of Northern Guangdong, School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
| | - Zhigang Yang
- Carbon-Water Research Station in Karst Regions of Northern Guangdong, School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
| | - Shaoheng Li
- Carbon-Water Research Station in Karst Regions of Northern Guangdong, School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
| | - Zaizhi Yang
- Carbon-Water Research Station in Karst Regions of Northern Guangdong, School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
| | - Zuobing Liang
- Carbon-Water Research Station in Karst Regions of Northern Guangdong, School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China.
| | - Lei Gao
- Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, China.
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Guyonnet D, Coftier A, Bataillard P, Destercke S. Risk-based imprecise post-remediation soil quality objectives. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 923:171445. [PMID: 38442757 DOI: 10.1016/j.scitotenv.2024.171445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 02/22/2024] [Accepted: 03/01/2024] [Indexed: 03/07/2024]
Abstract
While risk-based contaminated land management is an essential component of sustainable remediation, uncertainty is an unavoidable aspect of risk assessment, since most of the parameters that influence risk are typically affected by uncertainty. Uncertainty may be of different origins; i.e., stochastic or epistemic. Stochastic (or aleatoric) uncertainty arises from random variability related to natural processes, while epistemic uncertainty arises from the incomplete/imprecise nature of available information. But the latter is rarely considered in risk assessments, with the result that risk-based soil quality objectives are almost invariably presented as precise (unique) threshold values. In this paper it is shown: (i) how the joint treatment of stochastic and epistemic uncertainty in risk assessment can lead to soil quality objectives presented as intervals rather than precise values and (ii) how this provides an upper risk-based safeguard for post-remediation monitoring values. The proposed method is illustrated by a real case of soils contaminated by arsenic located in the North-East of France. At this site steel manufacturers have gradually filled up a small valley with slag and dust, over more than a century. These materials are enriched in various metal(loid)s, including arsenic and lead. As the environmental authority has asked for a conversion of the site to other uses that may involve access by the general public, an investigation of human health risk was performed based on a sampling campaign and chemical characterizations including various types of extractions and an analysis of bioaccessibility. While further investigations are required to improve the bioaccessibility model, the human health risk presented herein shows how partial or imprecise information can be incorporated in the analysis while taking into account underlying uncertainties.
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Zhao M, Wang H, Sun J, Cai B, Tang R, Song X, Huang X, Liu Y, Fan Z. Human health risks of heavy metal(loid)s mediated through crop ingestion in a coal mining area in Eastern China. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 276:116305. [PMID: 38599158 DOI: 10.1016/j.ecoenv.2024.116305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 03/26/2024] [Accepted: 04/05/2024] [Indexed: 04/12/2024]
Abstract
The heavy metal(loid)s (HMs) in soils can be accumulated by crops grown, which is accompanied by crop ingestion into the human body and then causes harm to human health. Hence, the health risks posed by HMs in three crops for different populations were assessed using Health risk assessment (HRA) model coupled with Monte Carlo simulation. Results revealed that Zn had the highest concentration among three crops; while Ni was the main polluting element in maize and soybean, and As in rice. Non-carcinogenic risk for all populations through rice ingestion was at an "unacceptable" level, and teenagers suffered higher risk than adults and children. All populations through ingestion of three crops might suffer Carcinogenic risk, with the similar order of Total carcinogenic risk (TCR): TCRAdults > TCRTeenagers > TCRChildren. As and Ni were identified as priority control HMs in this study area due to their high contribution rates to health risks. According to the HRA results, the human health risk was associated with crop varieties, HM species, and age groups. Our findings suggest that only limiting the Maximum allowable intake rate is not sufficient to prevent health risks caused by crop HMs, thus more risk precautions are needed.
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Affiliation(s)
- Menglu Zhao
- School of Resoureces and Environment, Anqing Normal University, Anqing 246133, China; Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Huijuan Wang
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Jiaxun Sun
- Department of Geographical Sciences, University of Maryland, College Park 20742, United States
| | - Boya Cai
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Rui Tang
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Xiaoyong Song
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Xinmiao Huang
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Yafeng Liu
- School of Resoureces and Environment, Anqing Normal University, Anqing 246133, China.
| | - Zhengqiu Fan
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China.
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Shi H, Du Y, Li Y, Deng Y, Tao Y, Ma T. Determination of high-risk factors and related spatially influencing variables of heavy metals in groundwater. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 358:120853. [PMID: 38608578 DOI: 10.1016/j.jenvman.2024.120853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Revised: 04/01/2024] [Accepted: 04/03/2024] [Indexed: 04/14/2024]
Abstract
Identifying high-risk factors (heavy metals (HMs) and pollution sources) by coupling receptor models and health risk assessment model (HRA) is a novel approach within the field of risk assessment. However, this coupled model ignores the contribution of spatial differentiation to high-risk factors, resulting in the assessment being subjective. Taking Dongting Plain (DTP) as an example, a coupling framework by jointly using the positive matrix factorization model (PMF), HRA, Monte Carlo simulation, and geo-detector was developed, aiming to identify high-risk factors in groundwater, and further explore key environmental variables influencing the spatial heterogeneity of high-risk factors. The results showed that at least 82.86 % of non-carcinogenic risks and 97.41 % of carcinogenic risks were unacceptable for people of all ages, especially infants and children. According to the relationships among HMs, pollution sources, and health risks, As and natural sources were defined as high-risk HMs and sources, respectively. The interactions among Holocene thickness, oxidation-reduction potential, and dissolved organic carbon emerged as the primary drivers of spatial variability in high-risk factors, with their combined explanatory power reaching up to 74%. This proposed framework provides a scientific reference for future studies and a practical reference for environmental authorities in developing effective pollution management measures.
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Affiliation(s)
- Huanhuan Shi
- MOE Key Laboratory of Groundwater Quality and Health, China University of Geosciences, Wuhan, 430078, China; Hubei Key Laboratory of Yangtze Catchment Environmental Aquatic Science, China University of Geosciences, Wuhan, 430078, China; School of Environmental Studies & State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430078, China
| | - Yao Du
- MOE Key Laboratory of Groundwater Quality and Health, China University of Geosciences, Wuhan, 430078, China; Hubei Key Laboratory of Yangtze Catchment Environmental Aquatic Science, China University of Geosciences, Wuhan, 430078, China; School of Environmental Studies & State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430078, China.
| | - Yueping Li
- MOE Key Laboratory of Groundwater Quality and Health, China University of Geosciences, Wuhan, 430078, China; Hubei Key Laboratory of Yangtze Catchment Environmental Aquatic Science, China University of Geosciences, Wuhan, 430078, China; School of Environmental Studies & State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430078, China
| | - Yamin Deng
- MOE Key Laboratory of Groundwater Quality and Health, China University of Geosciences, Wuhan, 430078, China; Hubei Key Laboratory of Yangtze Catchment Environmental Aquatic Science, China University of Geosciences, Wuhan, 430078, China; School of Environmental Studies & State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430078, China
| | - Yanqiu Tao
- MOE Key Laboratory of Groundwater Quality and Health, China University of Geosciences, Wuhan, 430078, China; Hubei Key Laboratory of Yangtze Catchment Environmental Aquatic Science, China University of Geosciences, Wuhan, 430078, China; School of Environmental Studies & State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430078, China
| | - Teng Ma
- College of Resources and Environmental Engineering, Wuhan University of Science and Technology, Wuhan, 430081, China
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Duru SC, Echiegu EA, Anyadike CC, Alaneme GU, Okechukwu ME. Spatial variability of heavy metals concentrations in soil of auto-mechanic workshop clusters in Nsukka, Nigeria. Sci Rep 2024; 14:9681. [PMID: 38678097 PMCID: PMC11055925 DOI: 10.1038/s41598-024-60044-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2024] [Accepted: 04/18/2024] [Indexed: 04/29/2024] Open
Abstract
The indiscriminate disposal of spent engine oils and other hazardous waste at auto mechanic workshops clusters in Nsukka, Enugu State, Nigeria is an environmental concern. This study examines the concentration of heavy metals in the soil inside the workshop cluster and in the unpolluted soil outside the workshop cluster at approximately 100 m. Ten sampling points were randomly selected from within the cluster and another ten from outside the cluster. Using a hand-held Global Positioning System, the coordinates of the selected points were established and used to create a digital map. Soil samples at depths of 0-30 cm and 30-60 cm, were analyzed for Cu, Fe, Zn, Pb, As and Cd using Spectrophotometer. Moisture content determination and particle size analysis were also done on the samples. Spatial variability of heavy metals concentrations of the studied site was also mapped with ArcGIS 10.2.2 using interpolation methods. Results showed that the soil ranged from sandy loam to sandy clay loam. Cadmium and Zinc had the lowest and highest concentration, respectively, in the studied area. Comparing the concentrations of heavy metals in soils within and outside the auto mechanic cluster revealed notable differences across various depths (0-30 cm and 30-60 cm). The analysis results for soil samples within the cluster exhibited concentration levels (mg/kg) ranging from 0.716-0.751 (Cu), 2.981-3.327 (Fe), 23.464-30.113 (Zn), 1.115-1.21 (Pb), 2.6-2.912 (As), and 0.133-0.365 (Cd) demonstrating a variation pattern in the order of Zn > Fe > As > Pb > Cu > Cd. Conversely, for soil samples outside the cluster, concentration levels (mg/kg) ranged from 0.611-0.618 (Cu), 2.233-2.516 (Fe), 12.841-15.736 (Zn), 0.887-0.903 (Pb), 1.669-1.911 (As), and 0.091-0.091 (Cd). To assess the disparity in heavy metal concentration levels between samples collected within and outside the clusters, ANOVA test was performed. The test showed significant difference in heavy metal concentrations between samples within and outside the auto mechanic cluster (p < 0.05), implying auto mechanic activities significantly impact heavy metal levels within the cluster compared to outside areas. The assessment of soil pollution utilized indices including the Geo-accumulation Index (Igeo), Contamination factor (Cf), and anthropogenic metal concentration (QoC). Zinc, Cadmium, and Arsenic showed the highest contamination factors, indicating significant soil contamination likely due to anthropogenic activities. The concentrations of the metals analyzed were within WHO permissible limits while the metals concentrations were also observed to decrease as depth was increased. Using ArcGIS 10.2.2, spatial maps showing heavy metal distribution were developed, with the Kriging method proving superior. This study suggests that heavy metal levels in the soil at the area be monitored on a regular basis.
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Affiliation(s)
| | - Emmanuel Amagu Echiegu
- Agricultural and Bioresources Engineering Department, University of Nigeria, Nsukka, Nigeria
| | - Chinenye C Anyadike
- Agricultural and Bioresources Engineering Department, University of Nigeria, Nsukka, Nigeria
| | | | - Michael Emeka Okechukwu
- Agricultural and Bioresources Engineering Department, University of Nigeria, Nsukka, Nigeria
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Wang C, Luo A, Qu S, Liang X, Xiao B, Mu W, Wang Y, Yu R. Anthropogenic processes drive spatiotemporal variability of sulfate in groundwater from a multi-aquifer system: Dilution caused by mine drainage. JOURNAL OF CONTAMINANT HYDROLOGY 2024; 264:104358. [PMID: 38692144 DOI: 10.1016/j.jconhyd.2024.104358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 04/19/2024] [Accepted: 04/24/2024] [Indexed: 05/03/2024]
Abstract
The water quality evolution of surface and groundwater caused by mining activities and mine drainage is a grave public concern worldwide. To explore the effect of mine drainage on sulfate evolution, a multi-aquifer system in a typical coal mine in Northwest China was investigated using multi-isotopes (δ34SSO4, δ18OSO4, δD, and δ18Owater) and Positive Matrix Factorization (PMF) model. Before mining, the Jurassic aquifer was dominated by gypsum dissolution, accompanied by cation exchange and bacterial sulfate reduction, and the phreatic aquifers and surface water were dominated by carbonate dissolution. Significant increase in sulfate in phreatic aquifers due to mine drainage during the early stages of coal mining. However, in contrast to common mining activities that result in sulfate contamination from pyrite oxidation, mine drainage in this mining area resulted in accelerated groundwater flow and enhanced hydraulic connections between the phreatic and confined aquifers. Dilution caused by the altered groundwater flow system controlled the evolution of sulphate, leading to different degrees of sulfate decrease in all aquifers and surface water. As the hydrogeochemical characteristic of Jurassic aquifer evolved toward phreatic aquifer, this factor should be considered to avoid misjudgment in determining the source of mine water intrusion. The study reveals the hydrogeochemical evolution induced by mine drainage, which could benefit to the management of groundwater resources in mining areas.
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Affiliation(s)
- Chenyu Wang
- China University of Geosciences, Beijing 100083, China
| | - Ankun Luo
- Xi'an Research Institute of China Coal Technology & Engineering Group Corp, Xi'an 710054, China
| | - Shen Qu
- Inner Mongolia Key Laboratory of River and Lake Ecology, School of Ecology and Environment, Inner Mongolia University, Hohhot 010021, China.
| | - Xiangyang Liang
- Xi'an Research Institute of China Coal Technology & Engineering Group Corp, Xi'an 710054, China
| | - Binhu Xiao
- Xi'an Research Institute of China Coal Technology & Engineering Group Corp, Xi'an 710054, China
| | - Wenping Mu
- China University of Geosciences, Beijing 100083, China
| | - Yuqin Wang
- China University of Geosciences, Beijing 100083, China
| | - Ruihong Yu
- Inner Mongolia Key Laboratory of River and Lake Ecology, School of Ecology and Environment, Inner Mongolia University, Hohhot 010021, China
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Wang H, Zhao M, Huang X, Song X, Cai B, Tang R, Sun J, Han Z, Yang J, Liu Y, Fan Z. Improving prediction of soil heavy metal(loid) concentration by developing a combined Co-kriging and geographically and temporally weighted regression (GTWR) model. JOURNAL OF HAZARDOUS MATERIALS 2024; 468:133745. [PMID: 38401211 DOI: 10.1016/j.jhazmat.2024.133745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 01/23/2024] [Accepted: 02/05/2024] [Indexed: 02/26/2024]
Abstract
The study of heavy metal(loid) (HM) contamination in soil using extensive data obtained from published literature is an economical and convenient method. However, the uneven distribution of these data in time and space limits their direct applicability. Therefore, based on the concentration data obtained from the published literature (2000-2020), we investigated the relationship between soil HM accumulation and various anthropogenic activities, developed a hybrid model to predict soil HM concentrations, and then evaluated their ecological risks. The results demonstrated that various anthropogenic activities were the main cause of soil HM accumulation using Geographically and temporally weighted regression (GTWR) model. The hybrid Co-kriging + GTWR model, which incorporates two of the most influential auxiliary variables, can improve the accuracy and reliability of predicting HM concentrations. The predicted concentrations of eight HMs all exceeded the background values for soil environment in China. The results of the ecological risk assessment revealed that five HMs accounted for more than 90% of the area at the "High risk" level (RQ ≥ 1), with the descending order of Ni (100%) = Cu (100%) > As (98.73%) > Zn (95.50%) > Pb (94.90%). This study provides a novel approach to environmental pollution research using the published data.
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Affiliation(s)
- Huijuan Wang
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China; School of Resoureces and Environment, Anqing Normal University, Anqing 246133, China
| | - Menglu Zhao
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Xinmiao Huang
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Xiaoyong Song
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Boya Cai
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Rui Tang
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Jiaxun Sun
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China; Department of Geographical Sciences, University of Maryland, College Park 20742, the United States
| | - Zilin Han
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Jing Yang
- South China Institute of Environmental Sciences, Ministry of Ecology and Environment of the People's Republic of China, Guangzhou 510530, China
| | - Yafeng Liu
- School of Resoureces and Environment, Anqing Normal University, Anqing 246133, China.
| | - Zhengqiu Fan
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China.
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Zhou Y, Ding D, Zhao Y, Li Q, Jiang D, Lv Z, Wei J, Zhang S, Deng S. Determining priority control toxic metal for different protection targets based on source-oriented ecological and human health risk assessment around gold smelting area. JOURNAL OF HAZARDOUS MATERIALS 2024; 468:133782. [PMID: 38387175 DOI: 10.1016/j.jhazmat.2024.133782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 02/06/2024] [Accepted: 02/12/2024] [Indexed: 02/24/2024]
Abstract
Determining the priority control source and pollutant is the key for the eco-health protection and risk management around gold smelting area. To this end, a case study was conducted to explore the pollution characteristics, source apportionment, ecological risk and human health risk of toxic metals (TMs) in agricultural soils surrounding a gold smelting enterprise. Three effective receptor models, including positive matrix factorization model (PMF), ecological risk assessment (ERA), and probabilistic risk assessment (PRA) have been combined to apportion eco-human risks for different targets. More than 95.0% of samples had a Nemerow pollution index (NPI) > 2 (NPImean=4.27), indicating moderately or highly soil TMs contamination. Four pollution sources including gold smelting activity, mining source, agricultural activity and atmosphere deposition were identified as the major sources, with the contribution rate of 17.52%, 44.16%, 13.91%, and 24.41%, respectively. For ecological risk, atmosphere deposition accounting for 30.8% was the greatest contributor, which was mainly loaded on Hg of 51.35%. The probabilistic health risk assessment revealed that Carcinogenic risks and Non-carcinogenic risks of all population were unacceptable, and children suffered from a greater health risk than adults. Gold smelting activity (69.2%) and mining source (42.0%) were the largest contributors to Carcinogenic risks and Non-carcinogenic risks, respectively, corresponding to As and Cr as the target pollutants. The priority pollution sources and target pollutants were different for the eco-health protection. This work put forward a new perspective for soil risk control and management, which is very beneficial for appropriate soil remediation under limited resources and costs.
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Affiliation(s)
- Yan Zhou
- Nanjing Institute of Environmental Science, Ministry of Ecology and Environment, Nanjing 210042, China
| | - Da Ding
- Nanjing Institute of Environmental Science, Ministry of Ecology and Environment, Nanjing 210042, China
| | - Yuanchao Zhao
- Nanjing Institute of Environmental Science, Ministry of Ecology and Environment, Nanjing 210042, China
| | - Qun Li
- Nanjing Institute of Environmental Science, Ministry of Ecology and Environment, Nanjing 210042, China
| | - Dengdeng Jiang
- Nanjing Institute of Environmental Science, Ministry of Ecology and Environment, Nanjing 210042, China
| | - Zhengyong Lv
- NJSOIL Ecology & Environmental Co, Ltd., Nanjing 211100, China
| | - Jing Wei
- Nanjing Institute of Environmental Science, Ministry of Ecology and Environment, Nanjing 210042, China
| | - Shengtian Zhang
- Nanjing Institute of Environmental Science, Ministry of Ecology and Environment, Nanjing 210042, China
| | - Shaopo Deng
- Nanjing Institute of Environmental Science, Ministry of Ecology and Environment, Nanjing 210042, China.
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Li M, Zhou J, Cheng Z, Ren Y, Liu Y, Wang L, Cao L, Shen Z. Pollution levels and probability risk assessment of potential toxic elements in soil of Pb-Zn smelting areas. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2024; 46:165. [PMID: 38592368 DOI: 10.1007/s10653-024-01933-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Accepted: 02/21/2024] [Indexed: 04/10/2024]
Abstract
Soil pollution around Pb-Zn smelters has attracted widespread attention around the world. In this study, we compiled a database of eight potentially toxic elements (PTEs) Pb, Zn, Cd, As, Cr, Ni, Cu, and Mn in the soil of Pb-Zn smelting areas by screening the published research papers from 2000 to 2023. The pollution assessment and risk screening of eight PTEs were carried out by geo-accumulation index (Igeo), potential ecological risk index (PERI) and health risk assessment model, and Monte Carlo simulation employed to further evaluate the probabilistic health risks. The results suggested that the mean values of the eight PTEs all exceeded the corresponding values in the upper crust, and more than 60% of the study sites had serious Pb and Cd pollution (Igeo > 4), with Brazil, Belgium, China, France and Slovenia having higher levels of pollution than other regions. Besides, PTEs in smelting area caused serious ecological risk (PERI = 10912.12), in which Cd was the main contributor to PREI (86.02%). The average hazard index (HI) of the eight PTEs for adults and children was 7.19 and 9.73, respectively, and the average value of total carcinogenic risk (TCR) was 4.20 × 10-3 and 8.05 × 10-4, respectively. Pb and As are the main contributors to non-carcinogenic risk, while Cu and As are the main contributors to carcinogenic risk. The probability of non-carcinogenic risk in adults and children was 84.05% and 97.57%, while carcinogenic risk was 92.56% and 79.73%, respectively. In summary, there are high ecological and health risks of PTEs in the soil of Pb-Zn smelting areas, and Pb, Cd, As and Cu are the key elements that cause contamination and risk, which need to be paid attention to and controlled. This study is expected to provide guidance for soil remediation in Pb-Zn smelting areas.
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Affiliation(s)
- Mingyue Li
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
| | - Jinyang Zhou
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
| | - Zhiwen Cheng
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
| | - Yuanyang Ren
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
| | - Yawei Liu
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
| | - Linling Wang
- School of Environmental Science and Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Liu Cao
- Jiyuan Industrial and Urban Integration Demonstration Zone Ecological Environment Bureau, Jiyuan, 459000, China
| | - Zhemin Shen
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China.
- State Environmental Protection Key Laboratory of Environmental Health Impact Assessment of Emerging Contaminants, Shanghai, 200233, People's Republic of China.
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Bai Z, Li T, Zhang S, Wang G, Xu X, Zhou W, Pan X, Pu Y, Jia Y, Yang Z, Long L. Effects of climate and geochemical properties on the chemical forms of soil Cd, Pb and Cr along a more than 4000 km transect. JOURNAL OF HAZARDOUS MATERIALS 2024; 467:133746. [PMID: 38341885 DOI: 10.1016/j.jhazmat.2024.133746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Revised: 01/15/2024] [Accepted: 02/05/2024] [Indexed: 02/13/2024]
Abstract
Soil heavy metal speciation has received much attention for their different ecological and environmental effects. However, the effects of climate and soil geochemical properties on them in uncontaminated soils at macroscale were still unclear. Therefore, a transect more than 4000 km was chosen to study the effects of these factors on soil Cd, Pb and Cr forms. The results revealed that mean annual temperature and precipitation showed significant positive relations with the exchangeable and Fe-Mn oxide bound states of Cd, Pb and Cr, and residual Cr. And humidity and drought indexes were significantly positively correlated with their organic and carbonate bound forms, respectively. As for soil geochemical properties, pH displayed significant negative relationships with exchangeable, Fe-Mn oxide and organic bound Pb and Cr, and exchangeable Cd. Fe2O3 was significantly positively with the exchangeable and Fe-Mn oxide bound Cd, Pb and Cr, and residual Cr. And soil organic matter showed positive relations with organic bound Pb and Cr, and residual Cd and Cr, displayed negative relationships with carbonated bound Pb and Cr. Overall, climate and soil geochemical properties together affect the transformation and transport of heavy metals between different forms in uncontaminated soils.
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Affiliation(s)
- Zhiqiang Bai
- College of Environmental Sciences, Sichuan Agricultural University, Wenjiang 611130, PR China; Sichuan Provincial Key Laboratory of Soil Environmental Protection, Wenjiang 611130, PR China
| | - Ting Li
- College of Resources, Sichuan Agricultural University, Wenjiang 611130, PR China
| | - Shirong Zhang
- College of Environmental Sciences, Sichuan Agricultural University, Wenjiang 611130, PR China; Sichuan Provincial Key Laboratory of Soil Environmental Protection, Wenjiang 611130, PR China.
| | - Guiyin Wang
- College of Environmental Sciences, Sichuan Agricultural University, Wenjiang 611130, PR China; Sichuan Provincial Key Laboratory of Soil Environmental Protection, Wenjiang 611130, PR China
| | - Xiaoxun Xu
- College of Environmental Sciences, Sichuan Agricultural University, Wenjiang 611130, PR China
| | - Wei Zhou
- College of Resources, Sichuan Agricultural University, Wenjiang 611130, PR China
| | - Xiaomei Pan
- Chengdu Agricultural College, Wenjiang 611130, PR China
| | - Yulin Pu
- College of Resources, Sichuan Agricultural University, Wenjiang 611130, PR China
| | - Yongxia Jia
- College of Resources, Sichuan Agricultural University, Wenjiang 611130, PR China
| | - Zhanbiao Yang
- College of Environmental Sciences, Sichuan Agricultural University, Wenjiang 611130, PR China
| | - Lulu Long
- College of Environmental Sciences, Sichuan Agricultural University, Wenjiang 611130, PR China
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Yu J, Liu X, Yang B, Li X, Wang P, Yuan B, Wang M, Liang T, Shi P, Li R, Cheng H, Li F. Major influencing factors identification and probabilistic health risk assessment of soil potentially toxic elements pollution in coal and metal mines across China: A systematic review. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 274:116231. [PMID: 38503102 DOI: 10.1016/j.ecoenv.2024.116231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 02/08/2024] [Accepted: 03/14/2024] [Indexed: 03/21/2024]
Abstract
Deposition of potentially toxic elements (PTEs) in soils due to different types of mining activities has been an increasingly important concern worldwide. Quantitative differences of soil PTEs contamination and related health risk among typical mines remain unclear. Herein, data from 110 coal mines and 168 metal mines across China were analyzed based on 265 published literatures to evaluate pollution characteristics, spatial distribution, and probabilistic health risks of soil PTEs. The results showed that PTE levels in soil from both mine types significantly exceeded background values. The geoaccumulation index (Igeo) revealed metal-mine soil pollution levels exceeded those of coal mines, with average Igeo values for Cd, Hg, As, Pb, Cu, and Zn being 3.02-15.60 times higher. Spearman correlation and redundancy analysis identified natural and anthropogenic factors affecting soil PTE contamination in both mine types. Mining activities posed a significant carcinogenic risk, with metal-mine soils showing a total carcinogenic risk an order of magnitude higher than in coal-mine soils. This study provides policymakers a quantitative foundation for developing differentiated strategies for sustainable remediation and risk-based management of PTEs in typical mining soils.
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Affiliation(s)
- Jingjing Yu
- College of Water Sciences, Beijing Normal University, Beijing 100875, China; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Xiaoyang Liu
- Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing 100012, China.
| | - Bin Yang
- Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing 100012, China
| | - Xiaodong Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Panpan Wang
- College of Water Sciences, Beijing Normal University, Beijing 100875, China; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Bei Yuan
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing 100012, China
| | - Minghao Wang
- China Metallurgical Industry Planning and Research Institute, Beijing 100013, China
| | - Tian Liang
- College of Water Sciences, Beijing Normal University, Beijing 100875, China; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Pengfei Shi
- College of Water Sciences, Beijing Normal University, Beijing 100875, China; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Renyou Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; School of Ecology and Environment, Inner Mongolia University, Inner Mongolia, 010020, China
| | - Hongguang Cheng
- College of Water Sciences, Beijing Normal University, Beijing 100875, China
| | - Fasheng Li
- College of Water Sciences, Beijing Normal University, Beijing 100875, China; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
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Upadhyay V, Kumari A, Kumar S. From soil to health hazards: Heavy metals contamination in northern India and health risk assessment. CHEMOSPHERE 2024; 354:141697. [PMID: 38484997 DOI: 10.1016/j.chemosphere.2024.141697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 02/21/2024] [Accepted: 03/11/2024] [Indexed: 04/06/2024]
Abstract
Heavy metals contamination in soil is a global concern affecting the environment with far-reaching consequences for ecosystems and the health of human beings. Heavy metals contamination of soil entails a significant threat to the environment and human health. This research paper focuses on the quantification of heavy metals contamination in soil in Kanpur district, a highly industrialized and densely populated region in India. The study was aimed to identify the sources of heavy metals, map their spatial distribution, and evaluate the potential implications on the environment and human well-being. The prime intent of the current study was quantification of heavy metals in the soil as well as the comparison of risk on the health of human being using two different methods i.e., US EPA methodology for risk assessment and epidemiological study-based risk assessment. Heavy metals like Fe, Ni, Co, Cu, Mn, Cr, and Cd were analyzed in agricultural samples of soil with the help of inductively coupled plasma optical emission spectroscopy. On the basis of epidemiological data, the attributable and relative risk came out to be 0.001 and 1.060, respectively. On the basis of the calculation of Cr alone, the values of carcinogenic risk for adults came out to be 3.87 × 10-7 and for children it was 3.01 × 10- 6. In conclusion, this research paper highlights the alarming levels of heavy metals contamination in the soil of Kanpur district, emphasizing the urgent need for remediation and mitigation efforts, thereby guiding policy makers and stakeholders in developing targeted strategies for soil protection and safeguarding human health.
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Affiliation(s)
- Vidisha Upadhyay
- CSIR-National Environmental Engineering Research Institute (CSIR-NEERI), Nehru Marg, Nagpur, 440 020, Maharashtra, India
| | - Archana Kumari
- CSIR-National Environmental Engineering Research Institute (CSIR-NEERI), Nehru Marg, Nagpur, 440 020, Maharashtra, India
| | - Sunil Kumar
- CSIR-National Environmental Engineering Research Institute (CSIR-NEERI), Nehru Marg, Nagpur, 440 020, Maharashtra, India.
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Zhao B, O'Connor D, Huang Y, Hou R, Cai L, Jin Y, Wang P, Zhang H. An integrated framework for source apportionment and spatial distribution of mercury in agricultural soil near a primary ore mining site. CHEMOSPHERE 2024; 353:141556. [PMID: 38412890 DOI: 10.1016/j.chemosphere.2024.141556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 02/23/2024] [Accepted: 02/24/2024] [Indexed: 02/29/2024]
Abstract
Mercury (Hg) is a global environmental concern that affects both humans and ecosystem. The comprehensive understanding of sources and dynamics is crucial for facilitating targeted and effective control strategies. Herein, a robust approach integrating Multivariate Statistics, Geostatistics, and Positive Matrix Factorization (PMF) was employed to quantitatively elucidate the distribution and sources of Hg in agricultural lands. Results indicated elevated Hg concentrations in the land with 74.46% of soils, including 84.85% of topsoil, 69.70% of subsoil, and 67.31% of deepsoil, exceeding risk screening value. Geoaccumulation Index of Hg in soil surpassed level Ⅱ with more than 50% of Hg in the residual fraction regardless of the layer or location. The levels of Hg in surface water for irrigation exhibited a negative correlation with the distance from the mine and a positive correlation with that in sediment (R2>0.78, p < 0.01), suggesting the downstream migration and remobilization from sediment. Source apportion revealed that human activities as primary contributors despite high variability across locations and soil layers. Contributions to downstream soil Hg from Natural Background (NB), Primary Ore Mining (OM), Agricultural Practices (AP), and Wastewater Irrigation (WI) were 15.5%, 83.1%, 1.3%, and 0.1%, respectively. A reliable approach for source apportionment of Hg in soil was suggested, demonstrating potential applicability in the risk management of Hg-contaminated sites.
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Affiliation(s)
- Bin Zhao
- Guangdong Key Laboratory of Integrated Agro-environmental Pollution Control and Management, Institute of Eco-environmental and Soil Sciences, Guangdong Academy of Sciences, 510650, Guangzhou, China; School of Environment, Tsinghua University, 100084, Beijing, China; Norwegian University of Life Sciences, Department of Environmental Sciences, 5003, N-1432 Ås, Norway.
| | - David O'Connor
- School of Real Estate and Land Management, Royal Agricultural University, Stroud Rd, Cirencester, GL7 6JS, United Kingdom
| | - Yao Huang
- Guangdong Key Laboratory of Integrated Agro-environmental Pollution Control and Management, Institute of Eco-environmental and Soil Sciences, Guangdong Academy of Sciences, 510650, Guangzhou, China
| | - Renjie Hou
- School of Water Conservancy and Civil Engineering, Northeast Agricultural University, 150030, Harbin, Heilongjiang, China
| | - Linying Cai
- Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, 100012, Beijing, China
| | - Yuanliang Jin
- School of Environment, Tsinghua University, 100084, Beijing, China
| | - Pei Wang
- College of Tropical Crops, Hainan University, Haikou, 570228, China
| | - Hao Zhang
- School of Environment, Tsinghua University, 100084, Beijing, China; Technical Centre for Soil, Agriculture and Rural Ecology and Environment, Ministry of Ecology and Environment, 100012, Beijing, China.
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Li X, Ding D, Xie W, Zhang Y, Kong L, Li M, Li M, Deng S. Risk assessment and source analysis of heavy metals in soil around an asbestos mine in an arid plateau region, China. Sci Rep 2024; 14:7552. [PMID: 38555404 PMCID: PMC10981712 DOI: 10.1038/s41598-024-58117-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 03/25/2024] [Indexed: 04/02/2024] Open
Abstract
Asbestos is widely used in construction, manufacturing, and other common industrial fields. Human activities such as mining, processing, and transportation can release heavy metals from asbestos into the surrounding soil environment, posing a health hazard to the mining area's environment and its surrounding residents. The purpose of the present study was to determine the extent of ecological and human health damage caused by asbestos pollution, as well as the primary contributors to the contamination, by examining a large asbestos mine and the surrounding soil in China. The level of heavy metal pollution in soil and sources were analyzed using methods such as the geo-accumulation index (Igeo), potential ecological risk index (RI), and positive matrix factorization (PMF) model. A Monte Carlo simulation-based health risk model was employed to assess the health risks of heavy metals in the study area's soil to human beings. The results showed that the concentrations of As, Pb, Cr, Cu, and Ni in the soil were 1.74, 0.13, 13.31, 0.33, and 33.37 times higher than the local soil background values, respectively. The Igeo assessment indicated significant accumulation effects for Ni, Cr, and As. The RI evaluation revealed extremely high comprehensive ecological risks (RI ≥ 444) in the vicinity of the waste residue heap and beneficiation area, with Ni exhibiting strong individual potential ecological risk (Eir ≥ 320). The soil health risk assessment demonstrated that As and Cr posed carcinogenic risks to adults, with mean carcinogenic indices (CR) of 1.56E - 05 and 4.14E - 06, respectively. As, Cr, and Cd posed carcinogenic risks to children, with mean CRs of 1.08E - 04, 1.61E - 05, and 2.68E - 06, respectively. Cr also posed certain non-carcinogenic risks to both adults and children. The PMF model identified asbestos contamination as the primary source of heavy metals in the soil surrounding the asbestos mining area, contributing to 79.0%. According to this study, it is recommended that management exercise oversight and regulation over the concentrations of Ni, Cr, Cd, and As in the soil adjacent to asbestos mines, establish a designated control zone to restrict population activities, and locate residential zones at a safe distance from the asbestos mine production zone.
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Affiliation(s)
- Xuwei Li
- Ministry of Ecology and Environment of China, Nanjing Institute of Environmental Sciences, Nanjing, 210042, China
- State Environmental Protection Key Laboratory of Soil Environmental Management and Pollution Control, Nanjing, 210042, China
| | - Da Ding
- Ministry of Ecology and Environment of China, Nanjing Institute of Environmental Sciences, Nanjing, 210042, China
- State Environmental Protection Key Laboratory of Soil Environmental Management and Pollution Control, Nanjing, 210042, China
| | - Wenyi Xie
- Ministry of Ecology and Environment of China, Nanjing Institute of Environmental Sciences, Nanjing, 210042, China
- State Environmental Protection Key Laboratory of Soil Environmental Management and Pollution Control, Nanjing, 210042, China
| | - Ya Zhang
- Ministry of Ecology and Environment of China, Nanjing Institute of Environmental Sciences, Nanjing, 210042, China
- State Environmental Protection Key Laboratory of Soil Environmental Management and Pollution Control, Nanjing, 210042, China
| | - Lingya Kong
- Ministry of Ecology and Environment of China, Nanjing Institute of Environmental Sciences, Nanjing, 210042, China
- State Environmental Protection Key Laboratory of Soil Environmental Management and Pollution Control, Nanjing, 210042, China
| | - Ming Li
- Ministry of Ecology and Environment of China, Nanjing Institute of Environmental Sciences, Nanjing, 210042, China
- State Environmental Protection Key Laboratory of Soil Environmental Management and Pollution Control, Nanjing, 210042, China
| | - Mei Li
- Ministry of Ecology and Environment of China, Nanjing Institute of Environmental Sciences, Nanjing, 210042, China
- State Environmental Protection Key Laboratory of Soil Environmental Management and Pollution Control, Nanjing, 210042, China
| | - Shaopo Deng
- Ministry of Ecology and Environment of China, Nanjing Institute of Environmental Sciences, Nanjing, 210042, China.
- State Environmental Protection Key Laboratory of Soil Environmental Management and Pollution Control, Nanjing, 210042, China.
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Sun L, Liu T, Duan L, Tong X, Zhang W, Cui H, Wang Z, Zheng G. Spatial and temporal distribution characteristics and risk assessment of heavy metals in groundwater of Pingshuo mining area. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2024; 46:141. [PMID: 38491301 DOI: 10.1007/s10653-024-01906-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 02/08/2024] [Indexed: 03/18/2024]
Abstract
Groundwater pollution in the Pingshuo mining area is strongly associated with mining activities, with heavy metals (HMs) representing predominant pollutants. To obtain accurate information about the pollution status and health risks of groundwater, 189 groups of samples were collected from four types of groundwater, during three periods of the year, and analyzed for HMs. The results showed that the concentration of HMs in groundwater was higher near the open pit, waste slag pile, riverfront area, and human settlements. Except for Ordovician groundwater, excessive HMs were found in all investigated groundwater of the mining area, as compared with the standard thresholds. Fe exceeded the threshold in 13-75% of the groundwater samples. Three sources of HMs were identified and quantified by Pearson's correlation analysis and the PMF model, including coal mining activities (68.22%), industrial, agricultural, and residential chemicals residue and leakage (16.91%), and natural sources (14.87%). The Nemerow pollution index revealed that 7.58% and 100% of Quaternary groundwater and mine water samples were polluted. The health risk index for HMs in groundwater showed that the non-carcinogenic health risk ranged from 0.18 to 0.42 for adults, indicating an acceptable level. Additionally, high carcinogenic risks were identified in Quaternary groundwater (95.45%), coal series groundwater (91.67%), and Ordovician groundwater (26.67%). Both carcinogenic and non-carcinogenic risks were greater for children than adults, highlighting their increased vulnerability to HMs in groundwater. This study provides a scientific foundation for managing groundwater quality and ensuring drinking water safety in mining areas.
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Affiliation(s)
- Long Sun
- College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot, 010018, China
| | - Tingxi Liu
- College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot, 010018, China.
- Inner Mongolia Key Laboratory of Water Resource Protection and Utilization, Hohhot, 010018, China.
| | - Limin Duan
- College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot, 010018, China
- Inner Mongolia Key Laboratory of Water Resource Protection and Utilization, Hohhot, 010018, China
| | - Xin Tong
- College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot, 010018, China
- Inner Mongolia Key Laboratory of Water Resource Protection and Utilization, Hohhot, 010018, China
| | - Wenrui Zhang
- College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot, 010018, China
| | - He Cui
- College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot, 010018, China
| | - Zhiting Wang
- College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot, 010018, China
| | - Guofeng Zheng
- College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot, 010018, China
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Peng H, Yi L, Liu C. Spatial distribution, chemical fractionation and risk assessment of Cr in soil from a typical industry smelting site in Hunan Province, China. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2024; 46:113. [PMID: 38478134 DOI: 10.1007/s10653-024-01883-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Accepted: 01/23/2024] [Indexed: 04/12/2024]
Abstract
The closure or relocation of many industrial enterprises has resulted in a significant number of abandoned polluted sites enriched in heavy metals to various degrees, causing a slew of environmental problems. Therefore, it is essential to conduct research on heavy metal contamination in the soil of industrial abandoned sites. In this study, soils at different depths were collected in a smelting site located in Hunan Province, China, to understand the Cr distribution, speciation and possible risks. The results revealed that the high-content Cr and Cr(VI) contamination centers were mainly concentrated near S1 (Sample site 1) and S5. The longitudinal migration law of chromium was relatively complex, not showing a simply uniform trend of decreasing gradually with depth but presenting a certain volatility. The vertical distribution characteristics of chromium and Cr(VI) pollution suggest the need for attention to the pollution from chromium slag in groundwater and deep soil layers. The results of different speciation of Cr extracted by the modified European Community Bureau of Reference (BCR) method showed that Cr existed primarily in the residual state (F4), with a relatively low content in the weak acid extraction state (F1). The correlation analysis indicated that Cr was affected by total Cr, pH, organic matter and total carbon during the longitudinal migration process. The RSP results revealed that the smelting site as a whole had a moderate level of pollution. Soil at depths of 2-5 m was more polluted than other soil layers. Consequently, it is necessary to treat the site soil as a whole, especially the subsoil layer (2-5 m). Health risk assessment demonstrated that the soil chromium pollution was hazardous to both adults and children, and the probability of carcinogenic and non-carcinogenic risk was relatively high in the latter group. As a result, children should be a group of special concern regarding the assessment and remediation of soil contaminated with Cr. This study can provide some insight into the contamination characteristics, ecological and health risks of chromium in contaminated soils and offer a scientific basis for the prevention and control of chromium pollution at abandoned smelting sites.
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Affiliation(s)
- Hanfang Peng
- School of Geographical Sciences, Hunan Normal University, No. 36 Lushan Road, Changsha, 410081, People's Republic of China
| | - Liwen Yi
- School of Geographical Sciences, Hunan Normal University, No. 36 Lushan Road, Changsha, 410081, People's Republic of China.
- Hunan Key Laboratory of Geospatial Big Data Mining and Application, Hunan Normal University, Changsha, 410081, People's Republic of China.
| | - Chengai Liu
- School of Geographical Sciences, Hunan Normal University, No. 36 Lushan Road, Changsha, 410081, People's Republic of China
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Huang W, Wei L, Yang Y, Sun J, Ding L, Wu X, Zheng L, Huang Q. Estuarine environmental flow assessment based on the flow-ecological health index relation model: a case study in Yangtze River Estuary, China. ENVIRONMENTAL MONITORING AND ASSESSMENT 2024; 196:348. [PMID: 38446276 DOI: 10.1007/s10661-024-12487-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 02/19/2024] [Indexed: 03/07/2024]
Abstract
Environmental flow (e-flow) is the water demand of one given ecosystem, which can become the flow regulation target for protection and restoration of river or estuarine ecosystems. In this study, an e-flow assessment based on the flow-ecological health index (EHI) relation model was conducted to improve ecosystem health of the Yangtze River Estuary (YRE). Monitoring data of hydrology, biology, and water environment in the last decades were used for the model establishment. For the description of the YRE ecosystem, an EHI system was developed by cumulative frequency distribution curves and adaption of national standards. After preprocessing original flow values into proportional flow values, the generalized additive model and Monte Carlo random sampling were used for the establishment of the flow-EHI relation model. From the model calculation, the e-flow assessment results were that, in proportional flow values, the suitable flow range was 1.05-1.35, and the optimum flow range was 1.15-1.25 (flows in Yangtze River Datong Station). For flow regulation in two crucial periods, flows of 42,630-65,545 m3/s or over 14,675 m3/s are needed for the suitable flow of YRE in summer (June-August) or January, respectively. An adaptive management framework of ecological health-based estuarine e-flow assessment for YRE was contrived due to the limitation of current established model when facing the extreme drought in summer, 2022. The methodology and framework in this study are expected to provide valuable management and data support for the sustainable development of estuarine ecosystems and to bring inspiration for further studies at even continental or global levels.
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Affiliation(s)
- Weizheng Huang
- Key Laboratory of Yangtze River Water Environment of the Ministry of Education, College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, China
| | - Lai Wei
- Key Laboratory of Yangtze River Water Environment of the Ministry of Education, College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, China
| | - Ya Yang
- Key Laboratory of Yangtze River Water Environment of the Ministry of Education, College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, China
| | - Jinnuo Sun
- Key Laboratory of Yangtze River Water Environment of the Ministry of Education, College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, China
| | - Ling Ding
- Shanghai Investigation, Design and Research Institute Co., Ltd. (SIDRI), Shanghai, 200335, China
| | - Xinghua Wu
- Research Center for Eco-Environmental Engineering, China Three Gorges Corporation (CTG), Beijing, 100038, China
| | - Leifu Zheng
- Shanghai Investigation, Design and Research Institute Co., Ltd. (SIDRI), Shanghai, 200335, China
| | - Qinghui Huang
- Key Laboratory of Yangtze River Water Environment of the Ministry of Education, College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, China.
- Shanghai Institute of Pollution Control and Ecological Security, Shanghai, 200092, China.
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Hao X, Ouyang W, Gu X, He M, Lin C. Accelerated export and transportation of heavy metals in watersheds under high geological backgrounds. JOURNAL OF HAZARDOUS MATERIALS 2024; 465:133514. [PMID: 38228005 DOI: 10.1016/j.jhazmat.2024.133514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 01/05/2024] [Accepted: 01/10/2024] [Indexed: 01/18/2024]
Abstract
The geological background level of metals plays a major role in mineral distribution and watershed diffuse heavy metal (HM) pollution. In this study, field research and a distributed hydrological model were used to analyze the distribution, sources, and pollution risk of watershed HMs in sediments with high geological HM backgrounds. Study showed that the mineral distribution and landcover promoted the transport differences of watershed HMs from upstream to the estuary. And the main sources of Co, Ni, and V in the estuarine sediments were natural sources. Sources of Pb and Zn were dominated by anthropogenic sources, accounting for 76% and 64% of their respective totals. The overall ecological risk of anthropogenically sourced HMs was dominated by Pb (46.6%), while the contributions of Co and Ni were also relatively high, accounting for 35.70% and 33.40%. Moreover, redundancy analysis showed that HM variations in the sediments were most sensitive to soil erosion and mineralizing rock distribution. The spatial patterns of watershed HMs from natural sources were significantly influenced by P loading, precipitation, and forest distribution. This combination of experiments and model improves the understanding of watershed HM variation and provides a new perspective for formulating effective watershed HM management strategies.
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Affiliation(s)
- Xin Hao
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Wei Ouyang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China; Advanced interdisciplinary Institute of Environment and Ecology, Beijing Normal University, Zhuhai 519087, China.
| | - Xiang Gu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Mengchang He
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Chunye Lin
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
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Guo Y, Yang Y, Li R, Liao X, Li Y. Cadmium accumulation in tropical island paddy soils: From environment and health risk assessment to model prediction. JOURNAL OF HAZARDOUS MATERIALS 2024; 465:133212. [PMID: 38101012 DOI: 10.1016/j.jhazmat.2023.133212] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 11/22/2023] [Accepted: 12/07/2023] [Indexed: 12/17/2023]
Abstract
Cultivated soil quality is crucial because it directly affects food safety and human health, and rice is of primary concern because of its centrality to global food networks. However, a detailed understanding of cadmium (Cd) geochemical cycling in paddy soils is complicated by the multiple influencing factors present in many rice-growing areas that overlap with industrial centers. This study analyzed the pollution characteristics and health risks of Cd in paddy soils across Hainan Island and identified key influencing factors based on multi-source environmental data and prediction models. Approximately 27.07% of the soil samples exceeded the risk control standard screening value for Cd in China, posing an uncontaminated to moderate contamination risk. Cd concentration and exposure duration contributed the most to non-carcinogenic and carcinogenic risks to children, teens, and adults through ingestion. Among the nine prediction models tested, Extreme Gradient Boosting (XGBoost) exhibited the best performance for Cd prediction with soil properties having the highest importance, followed by climatic variables and topographic attributes. In summary, XGBoost reliably predicted the soil Cd concentrations on tropical islands. Further research should incorporate additional soil properties and environmental variables for more accurate predictions and to comprehensively identify their driving factors and corresponding contribution rates.
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Affiliation(s)
- Yan Guo
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yi Yang
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ruxia Li
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaoyong Liao
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Yonghua Li
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
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39
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Wang P, Han G, Hu J, Zhang Q, Tian L, Wang L, Liu T, Ma W, Li J, Zheng H. Remarkable contamination characteristics, potential hazards and source apportionment of heavy metals in surface dust of kindergartens in a northern megacity of China. JOURNAL OF HAZARDOUS MATERIALS 2024; 465:133295. [PMID: 38134690 DOI: 10.1016/j.jhazmat.2023.133295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 12/07/2023] [Accepted: 12/14/2023] [Indexed: 12/24/2023]
Abstract
It is essential to understand the impact of heavy metals (HMs) present in the surface dust (SD) of kindergartens on children, who are highly sensitive to contaminated dust in cities in their growth stage. A study was conducted on 11 types of HMs present in the SD of 73 kindergartens in Beijing. This study aims to assess the pollution levels and sources of eleven HMs in Beijing's kindergartens surface dust (KSD), and estimate the potential health risks in different populations and sources. The results indicate that Cd has the highest contamination in the KSD, followed by Pb, Zn, Ni, Ba, Cr, and Cu. The sources of these pollutants are identified as industrial sources (23.7%), natural sources (22.1%), traffic sources (30.4%), and construction sources (23.9%). Cancer risk is higher in children (4.02E-06) than in adults (8.93E-06). Notably, Cr is the priority pollutant in the KSD, and industrial and construction activities are the main sources of pollution that need to be controlled. The pollution in the central and surrounding areas is primarily caused by historical legacy industrial sites, transportation, urban development, and climate conditions. This work provides guidance to manage the pollution caused by HMs in the KSD of Beijing. ENVIRONMENTAL IMPLICATION: Children within urban populations are particularly sensitive to pollutants present in SD. Prolonged exposure to contaminated SD significantly heightens the likelihood of childhood illnesses. The pollution status and potential health risks of HMs within SD from urban kindergartens are comprehensively investigated. Additionally, the contributions from four primary sources are identified and quantified. Furthermore, a pollution-source-oriented assessment is adopted to clearly distinguish the diverse impacts of different sources on health risks, and the priority pollutants and sources are determined. This work holds pivotal importance for risk management, decision-making, and environmental control concerning HMs in KSD.
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Affiliation(s)
- Peng Wang
- Institute of Earth Sciences, China University of Geosciences (Beijing), Beijing 100083, PR China; Nu Surficial Environment & Hydrological Geochemistry Laboratory, China University of Geosciences (Beijing), Beijing 100083, PR China; The State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China
| | - Guilin Han
- Institute of Earth Sciences, China University of Geosciences (Beijing), Beijing 100083, PR China; Nu Surficial Environment & Hydrological Geochemistry Laboratory, China University of Geosciences (Beijing), Beijing 100083, PR China
| | - Jian Hu
- The State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China.
| | - Qian Zhang
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, PR China
| | - Liyan Tian
- Institute of Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, PR China
| | - Lingqing Wang
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, PR China
| | - Tingyi Liu
- Tianjin Key Laboratory of Water Resources and Environment, Tianjin Normal University, Tianjin 300387, P.R. China
| | - Wenmin Ma
- Institute of Earth Sciences, China University of Geosciences (Beijing), Beijing 100083, PR China; Nu Surficial Environment & Hydrological Geochemistry Laboratory, China University of Geosciences (Beijing), Beijing 100083, PR China
| | - Jun Li
- The State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China
| | - Houyi Zheng
- General Institute of Geological Survey, China Chemical Geology and Mine Bureau, Beijing 100013, PR China
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Nduka JK, Umeh TC, Kelle HI, Okeke FC, Iloka GC, Okafor PC. Ecological pollution features and health risk exposure to heavy metals via street dust and topsoil from Nkpor and Onitsha in Anambra, Nigeria. Environ Anal Health Toxicol 2024; 39:e2024005-0. [PMID: 38631397 PMCID: PMC11079403 DOI: 10.5620/eaht.2024005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Accepted: 01/16/2024] [Indexed: 04/19/2024] Open
Abstract
The manuscript presents the investigation results on the pollution and risk of metal mines, and it is considered an important report on environmental pollution near mines in Nigeria, with archival value. The research involved soil sampling and heavy metal analysis for about 12 months in three metal mines. Based on these results, the paper provides information on pollution levels and hazards using well-known methods like pollution and ecological risk indexes. The increasing population in urban communities attracted by various industrial, economic and social activities causes contamination of atmospheric environment that can affect human health. We investigated heavy metal distributions, correlation coefficient among elements, ecological indices and probable health risk assessment in street dust and topsoil from Nkpor and Onitsha urban suburb, Nigeria. The mean concentration of heavy metals in car dust from Onitsha and Nkpor suburb follows thus: Fe > Mn > Cu > As > Pb > Ni > Cr. The decreasing trend of heavy metal in rooftop dust from both area: Fe > Mn > Cu > Pb > As > Ni > Cr whereas metal contents in topsoil were: Fe > Mn > Cu > Pb > Ni > Cr > As for both areas. The degree of pollution indices was characterized by contamination factor (CF), geo-accumulation factor (I-geo), pollution load index (PLI), Nemerow (PN), ecological and potential ecological risk index (ER and PERI) which indicated low pollution in the urban street environment. The results of Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) showed that the estimated heavy metals displayed sources from atmospheric deposition, natural origin and anthropogenic sources. Risk assessment revealed that ingestion of dust and soil was the significant route for heavy metals exposure to the populace followed by inhalation, then dermal contact. Considering all factors, non-cancer risk was more prominent in children than adults and no significant health hazard could be attributed to both aged groups as of the period of study except for As and Ni that needs constant monitoring to avoid exceeding organ damaging threshold limit of 1 × 10-4.
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Affiliation(s)
- John Kanayochukwu Nduka
- Environmental Chemistry and Toxicology Research Unit, Pure and Industrial Chemistry Department, Nnamdi Azikiwe University, Nigeria
| | - Theresa Chisom Umeh
- Environmental Chemistry and Toxicology Research Unit, Pure and Industrial Chemistry Department, Nnamdi Azikiwe University, Nigeria
| | | | - Francisca Chioma Okeke
- Environmental Chemistry and Toxicology Research Unit, Pure and Industrial Chemistry Department, Nnamdi Azikiwe University, Nigeria
| | - Genevieve Chinyere Iloka
- Environmental Chemistry and Toxicology Research Unit, Pure and Industrial Chemistry Department, Nnamdi Azikiwe University, Nigeria
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41
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Hu C, Liu Y, Fang X, Zhou Z, Yu Y, Sun Y, Shui B. Assessing heavy metal pollution in sediments from the northern margin of Chinese mangrove areas: Sources, ecological risks, and health impacts. MARINE POLLUTION BULLETIN 2024; 200:116069. [PMID: 38335629 DOI: 10.1016/j.marpolbul.2024.116069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 01/19/2024] [Accepted: 01/19/2024] [Indexed: 02/12/2024]
Abstract
With the rapid economic development of coastal cities, the discharge of substantial amounts of heavy metal pollutants poses a serious hazard to mangroves; however, the potential sources of heavy metals and the resulting health risks are not fully understood. In this study, we analyzed the contents, sources, and ecological and health risks of heavy metal contamination in mangrove sediments from the northern margin of China. The accumulation of heavy metals in mangroves was primarily driven by five potential sources, namely agricultural (33.5 %), natural sources (21.3 %), industrial (19.1 %), aquaculture (14.3 %), and traffic (11.8 %). The assessment of health risks using a probabilistic approach demonstrated that noncarcinogenic risks were within acceptable limits for all populations. It was worth noting that both noncarcinogenic and carcinogenic risks were greater in children than in adults. Analysis of source-oriented health risks revealed that agricultural sources and As and Cd were priority sources and elements of pollution requiring attention.
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Affiliation(s)
- Chengye Hu
- Fisheries College, Zhejiang Ocean University, Zhoushan 316022, China
| | - Yongtian Liu
- Fisheries College, Zhejiang Ocean University, Zhoushan 316022, China
| | - Xuehe Fang
- Fisheries College, Zhejiang Ocean University, Zhoushan 316022, China
| | - Zeyu Zhou
- Fisheries College, Zhejiang Ocean University, Zhoushan 316022, China
| | - Yang Yu
- Fisheries College, Zhejiang Ocean University, Zhoushan 316022, China
| | - Yiyi Sun
- Fisheries College, Zhejiang Ocean University, Zhoushan 316022, China
| | - Bonian Shui
- Fisheries College, Zhejiang Ocean University, Zhoushan 316022, China.
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42
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Xie H, Shi Y, Wang L, Yan H, Ci M, Wang Z, Chen Y. Source and risk assessment of heavy metals in mining-affected areas in Jiangxi Province, China, based on Monte Carlo simulation. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:21765-21780. [PMID: 38393575 DOI: 10.1007/s11356-024-32554-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2023] [Accepted: 02/15/2024] [Indexed: 02/25/2024]
Abstract
In recent years, heavy metal contamination of soils has become a major concern in China due to the potential risks involved. To assess environmental pollution and human health risks in a typical heavy metal polluted site in Jiangxi Province, a thorough evaluation of the distribution, pollution levels, and sources of heavy metals in soils of the Yangmeijiang River watershed was conducted in this study. Positive matrix factorization and Monte Carlo simulation were used to evaluate the ecological and human health risks of heavy metals. The research findings indicate that heavy metal pollution was the most severe at the depth of 20-40 cm in soils, with local heavy metal pollution resulting from mining and sewage irrigation. The high-risk area accounted for 91.11% of the total area. However, the pollution level decreased with time due to sampling effects, rainfall, and control measures. Leaf-vegetables and rice were primarily polluted by Cd and Pb. The main four sources of heavy metals in soils were traffic emission, metal smelting, agricultural activities and natural sources, mining extraction, and electroplating industries. Heavy metals with the highest ecological risk and health risk are Cd and As, respectively. The non-carcinogenic and carcinogenic risks of children were 7.0 and 1.7 times higher than those of adults, respectively. Therefore, children are more likely to be influenced by heavy metals compared to adults. The results obtained by the risk assessments may contribute to the identification of specific sources of heavy metals (e.g., traffic emissions, metal smelting, mining excavation, and electroplating industries). Additionally, the environmental impacts and biotoxicity associated with various heavy metals (e.g., Cd and As) can also be reflected. These outcomes may serve as a scientific basis for the pollution monitoring and remediation in the mining-affected areas.
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Affiliation(s)
- Haijian Xie
- College of Civil Engineering and Architecture, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310027, China
- Center for Balance Architecture, Zhejiang University, 148 Tianmushan Road, Hanghzou, 310007, China
| | - Yanghui Shi
- College of Civil Engineering and Architecture, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310027, China
- The Architectural Design and Research Institute of Zhejiang University Co., Ltd., 148 Tianmushan Road, Hangzhou, 310028, China
| | - Liang Wang
- The Architectural Design and Research Institute of Zhejiang University Co., Ltd., 148 Tianmushan Road, Hangzhou, 310028, China
| | - Huaxiang Yan
- Zijin School of Geology and Mining, Fuzhou University, Fuzhou, Fujian, 350108, China.
| | - Manting Ci
- College of Civil Engineering and Architecture, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310027, China
- The Architectural Design and Research Institute of Zhejiang University Co., Ltd., 148 Tianmushan Road, Hangzhou, 310028, China
| | - Ziheng Wang
- Zijin School of Geology and Mining, Fuzhou University, Fuzhou, Fujian, 350108, China
| | - Yun Chen
- Center for Balance Architecture, Zhejiang University, 148 Tianmushan Road, Hanghzou, 310007, China
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Peng Q, Peng L, Liu J, Liu Y, Liu X, Yin J, Duan S, Liu X, Li Y, Gong Z, Wang Q. Exposure, bioaccumulation, and risk assessment of organophosphate flame retardants in crayfish in the middle and lower reaches of the Yangtze River. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:168859. [PMID: 38040355 DOI: 10.1016/j.scitotenv.2023.168859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Revised: 11/07/2023] [Accepted: 11/23/2023] [Indexed: 12/03/2023]
Abstract
Organophosphate flame retardants (OPFRs), a novel class of persistent pollutants, are widely distributed in the environment, and their potential health risks have garnered significant global attention in recent years. Crayfish is a popular freshwater crustacean product in China primarily sourced from the middle and lower reaches of the Yangtze River. The purpose of this study was to investigate the exposure levels of OPFRs in crayfish, assess the health and safety risks associated with crayfish consumption, and explore the bioaccumulation of OPFRs in environmental water and sediment on crayfish. Ultra-high performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) was employed to analyze 7 common OPFRs in 106 crayfish samples and 76 environmental samples. The results revealed that OPFRs were detected at a high frequency of 100 % in crayfish, with tripropyl phosphate (TPP) being the predominant pollutant found in edible portions while also exhibiting secondary contamination within the crayfish food chain. Monte Carlo modeling combined with @risk risk assessment software demonstrated that TPP present in crayfish muscles had the most substantial impact on health effects, however, overall OPFR exposure did not pose significant risks to human health. Furthermore, analysis of OPFRs bioenrichment ability indicated that crayfish predominantly accumulated these compounds within their edible parts from surrounding environmental water sources, particularly highlighting TPP's potential for bioaccumulation.
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Affiliation(s)
- Qiuhong Peng
- College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China
| | - Lingfeng Peng
- College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China
| | - Jin Liu
- College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China
| | - Yan Liu
- College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China; Key Laboratory for Deep Processing of Major Grain and Oil Ministry of Education, Hubei Key Laboratory for Processing and Transformation of Agricultural Products, Wuhan Polytechnic University, Wuhan 430023, China
| | - Xin Liu
- College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China; Key Laboratory for Deep Processing of Major Grain and Oil Ministry of Education, Hubei Key Laboratory for Processing and Transformation of Agricultural Products, Wuhan Polytechnic University, Wuhan 430023, China
| | - Jiaojiao Yin
- College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China; Key Laboratory for Deep Processing of Major Grain and Oil Ministry of Education, Hubei Key Laboratory for Processing and Transformation of Agricultural Products, Wuhan Polytechnic University, Wuhan 430023, China
| | - Shuo Duan
- College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China; Key Laboratory for Deep Processing of Major Grain and Oil Ministry of Education, Hubei Key Laboratory for Processing and Transformation of Agricultural Products, Wuhan Polytechnic University, Wuhan 430023, China
| | - Xiaofang Liu
- Hubei Provincial Key Laboratory for Applied Toxicology, Hubei Provincial Center for Disease Control and Prevention, Wuhan 430079, China
| | - Yuzhi Li
- College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China; Key Laboratory of Detection Technology of Focus Chemical Hazards in Animal-derived Food for State Market Regulation, Wuhan 430075, China
| | - Zhiyong Gong
- College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China; Key Laboratory for Deep Processing of Major Grain and Oil Ministry of Education, Hubei Key Laboratory for Processing and Transformation of Agricultural Products, Wuhan Polytechnic University, Wuhan 430023, China
| | - Qiao Wang
- College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China; Key Laboratory for Deep Processing of Major Grain and Oil Ministry of Education, Hubei Key Laboratory for Processing and Transformation of Agricultural Products, Wuhan Polytechnic University, Wuhan 430023, China.
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44
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Kao CS, Wang YL, Jiang CB, Tai PJ, Chen YH, Chao HJ, Lo YC, Hseu ZY, Hsi HC, Chien LC. Assessment of sources and health risks of heavy metals in metropolitan household dust among preschool children: The LEAPP-HIT study. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 352:120015. [PMID: 38194873 DOI: 10.1016/j.jenvman.2024.120015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 12/27/2023] [Accepted: 01/01/2024] [Indexed: 01/11/2024]
Abstract
The most common construction material used in Taiwan is concrete, potentially contaminated by geologic heavy metals (HMs). Younger children spend much time indoors, increasing HM exposure risks from household dust owing to their behaviors. We evaluated arsenic (As), cadmium (Cd), and lead (Pb) concentrations in fingernails among 280 preschoolers between 2017 and 2023. We also analyzed HM concentrations, including As, Cd, Pb, chromium (Cr), nickel (Ni), copper (Cu), zinc (Zn), iron (Fe), and manganese (Mn), in 90 household dust and 50 road dust samples from a residential area where children lived between 2019 and 2021 to deepen the understanding of sources and health risks of exposure to HMs from household dust. The average As, Cd, and Pb concentrations in fingernails were 0.12 ± 0.06, 0.05 ± 0.05, and 0.95 ± 0.77 μg/g, respectively. Soil parent materials, indoor construction activities, vehicle emissions, and mixed indoor combustion were the pollution sources of HMs in household dust. Higher Cr and Pb levels in household dust may pose non-carcinogenic risks to preschoolers. Addressing indoor construction and soil parent materials sources is vital for children's health. The finding of the present survey can be used for indoor environmental management to reduce the risks of HM exposure and avoid potential adverse health effects for younger children.
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Affiliation(s)
- Chi-Sian Kao
- School of Public Health, College of Public Health, Taipei Medical University, Taipei, Taiwan
| | - Ying-Lin Wang
- School of Public Health, College of Public Health, Taipei Medical University, Taipei, Taiwan; Graduate Institute of Environmental Engineering, National Taiwan University, Taipei, Taiwan
| | - Chuen-Bin Jiang
- Department of Pediatric Gastroenterology, Hepatology and Nutrition, MacKay Children's Hospital, Taipei, Taiwan; Department of Medicine, MacKay Medical College, SanZhi District, New Taipei City, Taiwan
| | - Pei-Ju Tai
- School of Public Health, College of Public Health, Taipei Medical University, Taipei, Taiwan
| | - Yi-Hua Chen
- School of Public Health, College of Public Health, Taipei Medical University, Taipei, Taiwan; Neuroscience Research Center, Taipei Medical University, Taipei, Taiwan
| | - Hsing-Jasmine Chao
- School of Public Health, College of Public Health, Taipei Medical University, Taipei, Taiwan; Neuroscience Research Center, Taipei Medical University, Taipei, Taiwan
| | - Yu-Chun Lo
- Neuroscience Research Center, Taipei Medical University, Taipei, Taiwan; Ph.D. Program in Medical Neuroscience, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
| | - Zeng-Yei Hseu
- Department of Agricultural Chemistry, National Taiwan University, Taipei, Taiwan
| | - Hsing-Cheng Hsi
- Graduate Institute of Environmental Engineering, National Taiwan University, Taipei, Taiwan.
| | - Ling-Chu Chien
- School of Public Health, College of Public Health, Taipei Medical University, Taipei, Taiwan; Neuroscience Research Center, Taipei Medical University, Taipei, Taiwan; Nutrition Research Center, Taipei Medical University Hospital, Taipei, Taiwan.
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45
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Behera RR, Satapathy DR, Majhi A. Human health risk assessment model associated with PM2.5 bound metals in paradip port township, India. CHEMOSPHERE 2024; 350:141111. [PMID: 38176588 DOI: 10.1016/j.chemosphere.2024.141111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Revised: 12/20/2023] [Accepted: 01/02/2024] [Indexed: 01/06/2024]
Abstract
This study aimed to assess the environmental risk and human health risks associated with PM2.5-bound metals in Paradip city between January 2019 and December 2021. The seasonal average concentrations of PM2.5 were measured 91.43 ± 70.18 μg m-3, 103.40 ± 60.80 μg m-3, 124.74 ± 62.37 μg m-3, and 159.37 ± 77.88 μg m-3 in pre-monsoon, monsoon, post-monsoon, and winter season respectively. The highest and lowest concentrations are estimated in the winter and pre-monsoon season. Paradip city experienced tropical weather conditions with a hot and humid climate. The wind pattern shows that the predominant wind direction was observed from the south-south-west (SSW) direction. The metals in PM2.5 were analysed using an atomic absorption spectrophotometer (AAS) by air-acetylene flame using a hollow cathode lamp. The average metal concentration decreased in the order of Fe > Al > Zn > Pb > Cr > Mn > Ni > Cu > Co > Cd > As. The value of the geo-accumulation index (Igeo) was evaluated >1 for Cd, Fe, and Zn elements. The health risk assessment (HRA) results showed that non-carcinogenic risk (NCR) was higher through the inhalation route followed by ingestion and dermal contact. The cumulative NCR, which is expressed in terms of the hazard index (HI), is greater than 1 for infant (2.78E+00), child (2.53E+00), and adult (1.04E+00) via inhalation pathway. The total carcinogenic risk (TCR) for infants, children, and adults was estimated at 1.45E-04, 7.24E-05 and 1.25E-05, respectively, which exceeded the acceptable limit of 1.00E-06. Our comprehensive research plays an important role in both policymakers and relevant stakeholders for the preparation of city action plans concerning ambient air pollution, which can improve the air quality in and around Paradip city, India.
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Affiliation(s)
- Rashmi Ranjan Behera
- CSIR-Institute of Minerals and Materials Technology (IMMT), Environment and Sustainability Department, Bhubaneswar, Odisha, 751013 , India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Deepty Ranjan Satapathy
- CSIR-Institute of Minerals and Materials Technology (IMMT), Environment and Sustainability Department, Bhubaneswar, Odisha, 751013 , India.
| | - Arakshita Majhi
- CSIR-Institute of Minerals and Materials Technology (IMMT), Environment and Sustainability Department, Bhubaneswar, Odisha, 751013 , India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
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Pan Y, Han W, Shi H, Liu X, Xu S, Li J, Peng H, Zhao X, Gu T, Huang C, Peng K, Wang S, Zeng M. Incorporating environmental capacity considerations to prioritize control factors for the management of heavy metals in soil. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 351:119820. [PMID: 38113783 DOI: 10.1016/j.jenvman.2023.119820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Revised: 11/22/2023] [Accepted: 12/09/2023] [Indexed: 12/21/2023]
Abstract
Heavy metals (HMs) pollution threatens food security and human health. While previous studies have evaluated source-oriented health risk assessments, a comprehensive integration of environmental capacity risk assessments with pollution source analysis to prioritize control factors for soil contamination is still lacking. Herein, we collected 837 surface soil samples from agricultural land in the Nansha District of China in 2019. We developed an improved integrated assessment model to analyze the pollution sources, health risks, and environmental capacities of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn. The model graded pollution source impact on environmental capacity risk to prioritize control measures for soil HMs. All HMs except Pb exceeded background values and were sourced primarily from natural, transportation, and industrial activities (31.26%). Approximately 98.92% (children), 97.87% (adult females), and 97.41% (adult males) of carcinogenic values exceeded the acceptable threshold of 1E-6. HM pollution was classified as medium capacity (3.41 kg/hm2) with mild risk (PI = 0.52). Mixed sources of natural backgrounds, transportation, and industrial sources were identified as priority sources, and As a priority element. These findings will help prioritize control factors for soil HMs and direct resources to the most critical pollutants and sources of contamination, particularly when resources are limited.
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Affiliation(s)
- Yujie Pan
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Wenjing Han
- Geological Survey Research Institute, China University of Geosciences, Wuhan, 430074, China
| | - Huanhuan Shi
- School of Environmental Studies, China University of Geosciences, Wuhan, 430074, China
| | - Xiaorui Liu
- China Electric Power Research Institute, Beijing, 100192, China
| | - Shasha Xu
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Jiarui Li
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Hongxia Peng
- School of Geography and Information Engineering, China University of Geosciences, Wuhan, 430074, China.
| | - Xinwen Zhao
- Wuhan Center of Geological Survey of China Geological Survey, Wuhan, 430205, China
| | - Tao Gu
- Wuhan Center of Geological Survey of China Geological Survey, Wuhan, 430205, China
| | - Chansgheng Huang
- Wuhan Center of Geological Survey of China Geological Survey, Wuhan, 430205, China
| | - Ke Peng
- Survey Affairs Center for Natural Resources and Planning of Yongzhou City, Yongzhou, 425000, China
| | - Simiao Wang
- College of Information Science and Engineering, Northeastern University, Shenyang, 314001, China
| | - Min Zeng
- Wuhan Center of Geological Survey of China Geological Survey, Wuhan, 430205, China.
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Zhang J, Yang T, Wang N, Luo X, Li H, Liao Y. Health risk assessment of heavy metals in wild fish and seasonal variation and source identification of heavy metals in sediments: a case study of typical urban river in Xi'an, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:8898-8916. [PMID: 38180666 DOI: 10.1007/s11356-023-31693-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Accepted: 12/19/2023] [Indexed: 01/06/2024]
Abstract
In order to determine the status of heavy metal pollution in river sediments and wild fish in Xi'an, concentrations of heavy metals (Cr, Ni, Cu, Zn, As, and Pb) were collected and analyzed in sediments and wild fish during dry season (October-November 2020) and wet season (June-July 2021). This study aimed to investigate the spatial and temporal variations of heavy metals in urban rivers of Xi'an, China. Their distribution characteristics and sources as well their pollution levels and health risks were assessed. The findings revealed that influenced by human activities, the heavy metal content in sediments (mg·kg-1 dry weight) in wet season was ranked as follows: Cr (73.09) > Zn (63.73) > Pb (40.31) > Ni (31.52) > Cu (24.86) > As (6.83); in the dry season: Zn (94.07) > Cr (69.59) > Cu (34.24) > Ni (33.60) > Pb (32.87) > As (7.60). Moreover, 32 fish samples from six species indicated an average metal content trend (mg·kg-1 wet weight) of Zn (8.70) > Cr (0.57) > Pb (0.28) > Ni (0.27) > Cu (0.24) > As (0.05). The potential ecological risk indices for sediment heavy metal concentrations in both seasons were well below the thresholds, which indicates that the aquatic environment is in safe level. The analysis of the potential ecological risk of sediment heavy metal concentrations indicates that the aquatic environment is safe for the time being. Based on the estimated daily intake (EDI), target risk quotient (THQ), total target risk quotient (TTHQ), cancer risk (CR), total cancer risk (TCR), and the permissible safety limits set by the agencies, the consumption of the fish examined is safe for human health. However, the presence of Cr and As in wild fish should still be a concern for human health, especially for children. The cumulative effect of heavy metals and the bioconcentration factor (BCF) suggest that sediment and heavy metals in fish are closely related, with higher concentrations in fish living in the bottom layer of the water column than in other water layers, and increasing with increasing predator levels. Correlation analysis and PMF modeling identified and determined four comparable categories of potential sources, namely, (1) atmospheric deposition and traffic sources, (2) agricultural sources, (3) industrial sources, and (4) natural sources.
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Affiliation(s)
- Jiale Zhang
- School of Geography and Tourism, Shaanxi Normal University, Xi'an, 710119, Shaanxi, People's Republic of China
| | - Tao Yang
- School of Geography and Tourism, Shaanxi Normal University, Xi'an, 710119, Shaanxi, People's Republic of China.
- International Joint Research Centre of Shaanxi Province for Pollutant Exposure and Eco-environmental Health, Xi'an, 710062, Shaanxi, People's Republic of China.
| | - Ning Wang
- School of Geography and Tourism, Shaanxi Normal University, Xi'an, 710119, Shaanxi, People's Republic of China
| | - Xingyu Luo
- School of Geography and Tourism, Shaanxi Normal University, Xi'an, 710119, Shaanxi, People's Republic of China
| | - Haiyan Li
- School of Geography and Tourism, Shaanxi Normal University, Xi'an, 710119, Shaanxi, People's Republic of China
| | - Yilin Liao
- School of Geography and Tourism, Shaanxi Normal University, Xi'an, 710119, Shaanxi, People's Republic of China
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Zhang Y, Wu X, Dong Y, Liu J. Quantitative risk analysis of sediment heavy metals using the positive matrix factorization-based ecological risk index method: a case of the Kuye River, China. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2024; 46:50. [PMID: 38227205 DOI: 10.1007/s10653-023-01836-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 12/13/2023] [Indexed: 01/17/2024]
Abstract
Identifying the sources of heavy metals (HMs) in river sediments is crucial to effectively mitigate sediment HM pollution and control its associated ecological risks in coal-mining areas. In this study, ecological risks resulting from different pollution sources were evaluated using an integrated method combining the positive matrix factorization (PMF) and the potential ecological risk index (RI) model. A total of 59 sediment samples were collected from the Kuye River and analyzed for eight HMs (Zn, Cr, Ni, Cu, Pb, As, Cd, and Hg). The obtained results showed that the sediment HM contents were higher than the corresponding soil background values in Shaanxi Province. The average sediment Hg content was 3.42 times higher than the corresponding background value. The PMF results indicated that HMs in the sediments were mainly derived from industrial, traffic, agricultural, and coal-mining sources. The RI values ranged from 26.15 to 483.70. Hg was the major contributor (75%) to the ecological risk in the vicinity of the Yanjiata Industrial Park. According to the PMF-based RI model, coal-mining activities exhibited the strongest impact on the river ecosystem (48.79%), followed, respectively, by traffic (34.41%), industrial (12.70%), and agricultural (4.10%) activities. These results indicated that the major anthropogenic sources contributing to the HM contents in the sediments are not necessarily those posing the greatest ecological risks. The proposed integrated approach in this study was useful in evaluating the ecological risks associated with different anthropogenic sources in the Kuye River, providing valuable suggestions for reducing sediment HM pollution and effectively protecting river ecosystems.
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Affiliation(s)
- Yaning Zhang
- School of Civil Engineering, Yulin University, Yulin, 719000, China
| | - Xijun Wu
- School of Civil Engineering, Yulin University, Yulin, 719000, China.
- State Key Laboratory of Eco-Hydraulics in Northwest Arid Region of China, Xi'an University of Technology, Xi'an, 710048, China.
| | - Ying Dong
- School of Civil Engineering, Yulin University, Yulin, 719000, China
| | - Jing Liu
- School of Civil Engineering, Yulin University, Yulin, 719000, China
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Zhu Y, An Y, Li X, Cheng L, Lv S. Geochemical characteristics and health risks of heavy metals in agricultural soils and crops from a coal mining area in Anhui province, China. ENVIRONMENTAL RESEARCH 2024; 241:117670. [PMID: 37979931 DOI: 10.1016/j.envres.2023.117670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 10/11/2023] [Accepted: 11/13/2023] [Indexed: 11/20/2023]
Abstract
Soil contamination by heavy metals (HMs) in mining areas is a major issue because of its significant impact on the environmental quality and physical health of residents. Mining of minerals used in energy production, particularly coal, has led to HMs entering the surrounding soil through geochemical pathways. In this study, a total of 166 surface soil and 100 wheat grain samples around the Guobei coal mine in southeast China were collected, and trace metal levels were determined via inductively coupled plasma mass spectrometry (ICP-MS). The average HMs (Ni, As, Cr, Cu, Pb, Cd, and Zn) concentrations were lower than the screening values in China (GB 15618-2018) but higher than the soil background values in the Huaibei Bozhou area of Anhui Province (except Zn), indicating HMs enrichment. Based on the geoaccumulation index (Igeo) and ecological risk index (IER), Cd pollution levels were low, while for the other metals the samples were pollution-free, and therefore no ecological risk warning was issued for the mining area. Both Cr and Pb had a higher noncarcinogenic health risks for adults and children. The lifetime carcinogenic risks (LCR) of Cr, Pb, and Cd were within acceptable levels. A positive matrix factorization (PMF) model identified two factors that could explain the HMs sources: factor 1 for Zn, Cd, and Pb, factor 2 for Ni, As, Cr, and Cu. Furthermore, HMs enrichment was observed in surface soil and the Carboniferous-Permian coal seams in the Guobei coal mine, which may suggest that coal mining is an important source for HMs enrichment in surface soil. Overall, this study provides a theoretical basis for undertaking the management and assessment of soil HMs pollution around a coal mine.
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Affiliation(s)
- Ying Zhu
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China
| | - Yanfei An
- School of Resources and Environmental Engineering, Anhui University, Hefei, 230601, China
| | - Xingyuan Li
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China.
| | - Li Cheng
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China
| | - Songjian Lv
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China
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50
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Su Z, Yang S, Han H, Bai Y, Luo W, Wang Q. Is biomagnetic leaf monitoring still an effective method for monitoring the heavy metal pollution of atmospheric particulate matter in clean cities? THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 906:167564. [PMID: 37802355 DOI: 10.1016/j.scitotenv.2023.167564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Revised: 09/27/2023] [Accepted: 10/01/2023] [Indexed: 10/10/2023]
Abstract
The development of a reasonable method for predicting heavy metals (HMs) pollution in atmospheric particulate matter (PM) remains challenging. This paper presents an elution-filtration method to collect PM from the surface of Osmanthus fragrans in a very clean area (Guiyang, China). The aim is to evaluate the effectiveness of biomagnetic leaf monitoring as a simple and rapid method for assessing HMs pollution in clean cities. For this purpose, we determined the magnetic parameters and concentrations of selected HMs in PM samples to investigate their relationships. The results showed that the magnetic minerals in PM samples were mainly low coercivity ferrimagnetic minerals, with a small amount of high coercivity minerals. The types of magnetic minerals were generally single, and the magnetic domain state was pseudo-single domain (PSD). There was a significant correlation between magnetic parameters and the heavy metal (HM) concentrations in PM. Low-field magnetic susceptibility (χ) could be used as an ideal proxy for determining anthropogenic HM pollution. Traffic emissions were the main atmospheric pollution source in urban Guiyang. Due to the incomplete traffic network and large traffic flow, traffic congestion (TC) often occurred at road intersections in the northwest and southwest corners of the city, resulting in the highest concentration of magnetic minerals and the most severe PM pollution. To mitigate atmospheric PM pollution and protect public health, it is strongly recommended that municipal authorities prioritize urban planning and traffic management to address TC. Measures should be implemented urgently to alleviate stop-and-go traffic.
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Affiliation(s)
- Zhihua Su
- School of Management Science and Engineering, Guizhou University of Finance and Economics, Guiyang 550025, China.
| | - Shixiong Yang
- Laboratory for Marine Geology, Laoshan Laboratory, Qingdao 266237, China; Key Laboratory of Coastal Wetland Biogeosciences, Qingdao Institute of Marine Geology, China Geological Survey, Qingdao 266071, China.
| | - Huiqing Han
- School of Architecture and Urban Planning, Guizhou Institute of Technology, Guiyang 550003, China
| | - Yumei Bai
- School of Management Science and Engineering, Guizhou University of Finance and Economics, Guiyang 550025, China
| | - Wei Luo
- School of Management Science and Engineering, Guizhou University of Finance and Economics, Guiyang 550025, China
| | - Qian Wang
- School of Management Science and Engineering, Guizhou University of Finance and Economics, Guiyang 550025, China
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