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Zhang Z, Lou S, Liu S, Zhou X, Zhou F, Yang Z, Chen S, Zou Y, Radnaeva LD, Nikitina E, Fedorova IV. Potential risk assessment and occurrence characteristic of heavy metals based on artificial neural network model along the Yangtze River Estuary, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:32091-32110. [PMID: 38648002 DOI: 10.1007/s11356-024-33400-z] [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: 12/17/2023] [Accepted: 04/16/2024] [Indexed: 04/25/2024]
Abstract
Pollution from heavy metals in estuaries poses potential risks to the aquatic environment and public health. The complexity of the estuarine water environment limits the accurate understanding of its pollution prediction. Field observations were conducted at seven sampling sites along the Yangtze River Estuary (YRE) during summer, autumn, and winter 2021 to analyze the concentrations of seven heavy metals (As, Cd, Cr, Pb, Cu, Ni, Zn) in water and surface sediments. The order of heavy metal concentrations in water samples from highest to lowest was Zn > As > Cu > Ni > Cr > Pb > Cd, while that in surface sediments samples was Zn > Cr > As > Ni > Pb > Cu > Cd. Human health risk assessment of the heavy metals in water samples indicated a chronic and carcinogenic risk associated with As. The risks of heavy metals in surface sediments were evaluated using the geo-accumulation index (Igeo) and potential ecological risk index (RI). Among the seven heavy metals, As and Cd were highly polluted, with Cd being the main contributor to potential ecological risks. Principal component analysis (PCA) was employed to identify the sources of the different heavy metals, revealing that As originated primarily from anthropogenic emissions, while Cd was primarily from atmospheric deposition. To further analyze the influence of water quality indicators on heavy metal pollution, an artificial neural network (ANN) model was utilized. A modified model was proposed, incorporating biochemical parameters to predict the level of heavy metal pollution, achieving an accuracy of 95.1%. This accuracy was 22.5% higher than that of the traditional model and particularly effective in predicting the maximum 20% of values. Results in this paper highlight the pollution of As and Cd along the YRE, and the proposed model provides valuable information for estimating heavy metal pollution in estuarine water environments, facilitating pollution prevention efforts.
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Affiliation(s)
- Zhirui Zhang
- Department of Hydraulic Engineering, Tongji University, Shanghai, 200092, China
| | - Sha Lou
- Department of Hydraulic Engineering, Tongji University, Shanghai, 200092, China.
- Key Laboratory of Yangtze River Water Environment, Ministry of Education, Tongji University, Shanghai, 200092, China.
| | - Shuguang Liu
- Department of Hydraulic Engineering, Tongji University, Shanghai, 200092, China
- Key Laboratory of Yangtze River Water Environment, Ministry of Education, Tongji University, Shanghai, 200092, China
| | - Xiaosheng Zhou
- Department of Hydraulic Engineering, Tongji University, Shanghai, 200092, China
| | - Feng Zhou
- Department of Hydraulic Engineering, Tongji University, Shanghai, 200092, China
| | - Zhongyuan Yang
- Department of Hydraulic Engineering, Tongji University, Shanghai, 200092, China
| | - Shizhe Chen
- Department of Hydraulic Engineering, Tongji University, Shanghai, 200092, China
| | - Yuwen Zou
- Department of Hydraulic Engineering, Tongji University, Shanghai, 200092, China
| | - Larisa Dorzhievna Radnaeva
- Laboratory of Chemistry of Natural Systems, Baikal Institute of Nature Management of Siberian Branch of the Russian Academy of Sciences, Ulan-Ude, Republic of Buryatia, Russia
| | - Elena Nikitina
- Laboratory of Chemistry of Natural Systems, Baikal Institute of Nature Management of Siberian Branch of the Russian Academy of Sciences, Ulan-Ude, Republic of Buryatia, Russia
| | - Irina Viktorovna Fedorova
- Institute of Earth Sciences, Saint Petersburg State University, 7-9 Universitetskaya Embankment, 199034, St Petersburg, Russia
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He F, Luo X, Heman A, Chen Z, Jia J. Anthropogenic perturbations on heavy metals transport in sediments in a river-dominated estuary (Modaomen, China) during 2003-2021. MARINE POLLUTION BULLETIN 2024; 199:115970. [PMID: 38171160 DOI: 10.1016/j.marpolbul.2023.115970] [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: 10/14/2023] [Revised: 12/09/2023] [Accepted: 12/21/2023] [Indexed: 01/05/2024]
Abstract
Heavy metal pollutants in sediment greatly impact the estuarine environment and ecosystems, increasingly influenced by anthropogenic perturbations. Here, we examined the surface sediments of the Modaomen estuary in 2003, 2015, and 2021 to understand how human-induced changes influence the fate of heavy metals in the estuary's sediments. The potential ecological risk index (RI) suggests Cd should be the priority pollutant for environmental pollution control due to its high toxicity coefficient. In each sampling period, two main sources were identified through normalized heavy metals and PCA-MLR: natural and mixed anthropogenic sources (agricultural, industrial, and traffic activities), reflecting an increase in heavy metals pollution, later mitigated by successful environmental protection measures. Moreover, anthropogenic activities have not only impacted the sources discharge of heavy metals but have also influenced their spatial and temporal distribution through factors such as land reclamation, leading to sediment coarsening and reduced heavy metal content in specific areas.
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Affiliation(s)
- Fangting He
- State Key Laboratory of Estuarine and Coastal Research, School of Marine Sciences, East China Normal University, Shanghai 200241, China
| | - Xiangxin Luo
- Institute of Estuarine and Coastal Research/State and Local Joint Engineering Laboratory of Estuarine Hydraulic Technology, School of Ocean Engineering and Technology, Sun Yat-sen University, Guangzhou 510275, China.
| | - Ali Heman
- Institute of Estuarine and Coastal Research/State and Local Joint Engineering Laboratory of Estuarine Hydraulic Technology, School of Ocean Engineering and Technology, Sun Yat-sen University, Guangzhou 510275, China
| | - Zhenkai Chen
- Institute of Estuarine and Coastal Research/State and Local Joint Engineering Laboratory of Estuarine Hydraulic Technology, School of Ocean Engineering and Technology, Sun Yat-sen University, Guangzhou 510275, China
| | - Jianjun Jia
- State Key Laboratory of Estuarine and Coastal Research, School of Marine Sciences, East China Normal University, Shanghai 200241, China.
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Liu R, Wang Y, Wang L, Wang Y, Peng X, Cao L, Liu Y. Spatio-temporal distribution and source identification of antibiotics in suspended matter in the Fen River Basin. CHEMOSPHERE 2023; 345:140497. [PMID: 37866500 DOI: 10.1016/j.chemosphere.2023.140497] [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: 03/26/2023] [Revised: 10/18/2023] [Accepted: 10/19/2023] [Indexed: 10/24/2023]
Abstract
In this study, 26 typical antibiotics in the suspended matter of the Fen River basin were analyzed during the wet and dry seasons, and the main sources of antibiotic contamination were further identified. The results showed that the concentrations of antibiotics in the suspended matter varied seasonally. Sixteen antibiotics were detected in the suspended matter during the wet season with an average concentration of 463.56 ng/L. However, a total of 21 antibiotics were detected in the dry season, with an average concentration of 106.00 ng/L. The concentration of chloramphenicol antibiotics was outstanding in the wet season and dry season. The spatial distribution of the antibiotics in suspended matter showed little spatial discrepancy during the wet season. During the dry season, nevertheless, the concentration was higher upstream than midstream and downstream. The main sources of antibiotics in the Fen River Basin were livestock and poultry breeding, wastewater from wastewater treatment plants (WWTPs), agricultural drainage, domestic sewage, and pharmaceutical wastewater. Wastewater from WWTPs and domestic sewage were identified as two primary sources in the suspended matter during the wet season, with wastewater from WWTPs contributing the most accounting for 37%. While the most significant source of antibiotics in the suspended matter in the dry season was pharmaceutical wastewater, accounting for 36%. In addition, the contribution proportion of sources for antibiotics exhibited discrepant spatial distribution characteristics. In the wet season, wastewater from WWTPs dominated in the upstream and midstream, and livestock and poultry breeding was prominent in the midstream and downstream. Pharmaceutical wastewater was the main source in the midstream and downstream regions during the dry season.
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Affiliation(s)
- Ruimin Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China.
| | - Yunan Wang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China.
| | - Linfang Wang
- Sorghum Research Institute, Shanxi Agricultural University/Shanxi Academy of Agricultural Sciences, No.238, Yuhuaxi Street, Jinzhong, 030600, China.
| | - Yifan Wang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China.
| | - Xinyuan Peng
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China.
| | - Leiping Cao
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China.
| | - Yue Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China.
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Fan J, Fan D, Wu Y. Spatiotemporal variations of heavy metal historical accumulation records and their influencing mechanisms in the Yangtze River Estuary. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 854:158733. [PMID: 36108832 DOI: 10.1016/j.scitotenv.2022.158733] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 09/07/2022] [Accepted: 09/09/2022] [Indexed: 06/15/2023]
Abstract
Complex transformations of heavy metals in the mega-river-estuary continuum limit our understanding of their pollution history. This study investigated sedimentary compositions of heavy metals, major elements, total organic carbon, grain size, and radionuclides to study spatiotemporal variations in heavy metal accumulation patterns and their controlling mechanisms in four sediment cores (E1-E4) from the Yangtze River Estuary (YRE). Results show that only E3 in the distal YRE front mirrors well the heavy metal pollution history due to its continuous deposition in a stable sedimentary environment, while E1 and E2 record the influence of riverine and estuarine projects and processes apparently. E1 in the proximal YRE front registers intense human disturbance through sediment dredging and dumping activities to produce a thick layer of abnormal low 210Pbex and minor heavy metal concentrations. E2 in the intermediate YRE front demonstrates the recently increasing influence of reduced sediment discharge by its upcore coarsening trend with decreased heavy metal concentrations. Flood and storm events left different imprints in core sediments of E2 and E3 by their coarse stratal units with fewer heavy metal concentrations. The source analysis indicates that heavy metals in estuarine sediments mainly come from natural processes but are significantly affected by human activities. A direct linkage of the heavy metal accumulation history with the socioeconomic development in recent decades is found by a comparison study of core data from the tidal river to the estuary, albeit with a remarkable spatiotemporal difference, which is jointly determined by grain size, offshore distance, hydrodynamic condition, depositional status, and sedimentation rate besides estuarine processes. This warns us to carefully interpret the heavy metal history from single or sparse core data in a mega estuary system with intense natural forces and human disturbances analogous to the YRE.
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Affiliation(s)
- Jiayu Fan
- State Key Laboratory of Marine Geology, Tongji University, Shanghai, China
| | - Daidu Fan
- State Key Laboratory of Marine Geology, Tongji University, Shanghai, China; Laboratory of Marine Geology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.
| | - Yijing Wu
- State Key Laboratory of Marine Geology, Tongji University, Shanghai, China
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Xu Y, Wang X, Cui G, Li K, Liu Y, Li B, Yao Z. Source apportionment and ecological and health risk mapping of soil heavy metals based on PMF, SOM, and GIS methods in Hulan River Watershed, Northeastern China. ENVIRONMENTAL MONITORING AND ASSESSMENT 2022; 194:181. [PMID: 35157146 DOI: 10.1007/s10661-022-09826-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 01/29/2022] [Indexed: 06/14/2023]
Abstract
Heavy metals in agricultural soils not only affect the food security and soil security, but also endanger the human health through the food chain. Based on the incorporation of index analysis, positive matrix factorization (PMF), self-organizing map (SOM), and geostatistical methods, this research performed the assessment of source apportionment and ecological and health risks of soil heavy metals in Hulan River Watershed, Northeastern China. According to the Pollution Load Index (PLI), 83.08% of the soil samples were slightly or mildly polluted, and 1.54% of the soil samples were severely polluted. The ecological risk index (EI) showed that about 80.77% and 60.77% of the soil samples were beyond the low risk level for Hg and Cd, respectively. In this research, the non-carcinogenic and carcinogenic risk indices for children were higher than adult males and adult females. Four potential sources were revealed based on the PMF and SOM analysis including atmospheric deposition and industrial emission; transportation source; agricultural source; and a combination of agricultural, industrial, and natural sources. Considerable and high ecological risk from Hg existed in the area close to the coal steam-electric plant, and considerable and high ecological risk from Cd existed in the Hulan River estuary area. The eastern part of the study area experienced higher non-carcinogenic and carcinogenic risks for adults and children than the western part of the study area. The source apportionment and ecological and health risk mapping provide important role in reducing pollution sources. Zonal pollution control and soil restoration measures should be performed in the areas with high ecological and health risks.
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Affiliation(s)
- Yiming Xu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
- Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China
| | - Xianxia Wang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Guannan Cui
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
- Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China
| | - Ke Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
- Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China
| | - Yanfeng Liu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Bin Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China.
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China.
- Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing, 100048, China.
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