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Chu K, Ye F, Sereyvatanak KY, Zhang X, Li Q, Lu Y, Liu Y, Zhang G. Fugacity model covering abiotic and biotic matrices to investigate the transfer and fate of perfluoroalkyl acids in a large shallow lake of eastern China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 952:175997. [PMID: 39233071 DOI: 10.1016/j.scitotenv.2024.175997] [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: 03/13/2024] [Revised: 08/30/2024] [Accepted: 09/01/2024] [Indexed: 09/06/2024]
Abstract
Solving the challenges faced during the measurement of the cross-interface transfer of perfluoroalkyl acids (PFAAs) in lakes is crucial for clarifying environmental behaviours of these chemicals and their efficient governance. This study developed a multimedia fugacity model based on the quantitative water-air-sediment interaction (QWASI) covering abiotic/biotic matrices to investigate the cross-interface transfer and fate of PFAAs in Luoma Lake, a typical PFAA-contaminated shallow lake in eastern China. The accuracy and reliability of the established model were confirmed using Percent bias and Monte Carlo simulation, respectively. Using the QWASI model, the multimedia transfer of the PFAAs and their accumulation and persistence in different sub-compartments were described and measured, and the differences among individual PFAAs were explored. The simulation results showed that the sedimentation and resuspension of PFAAs were the most intense cross-interfacial transfers, and the sediments served as a chemical sink in the long term. A significant negative correlation of NC-F (the number of CF bonds) with the relative outflow flux (TW·out-ct) but a positive correlation with the relative net transfer across the interface between water and aquatic plants (Tp-ct) was detected, indicating that the PFAA migration capacity decreased but the bioaccumulation potential increased with the CF bond number. The persistence in water (Pw) of individual PFAAs ranged from 19.65d (PFOA) to 32.22d (PFOS), with an average of 26.15d; their persistence in sediment (Ps) ranged from 432d (PFBA) to 3216d (PFOS), with an average of 1524d, increasing linearly with an increase in NC-F. The water advection flows into and out of the lake (QW·in and QW·out), the PFAA concentration of water inflow (CW·in), and bioconcentration factor of aquatic plants (BCFp) were the primary parameters sensitive to PFAAs in all sub-compartments, which are essential indexes for exploring promising remediation pathways for lacustrine PFAA contamination based on the fugacity model simulation.
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Affiliation(s)
- Kejian Chu
- Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Ministry of Education, College of Environment, Hohai University, Nanjing 210098, PR China; Yangtze Institute for Conservation and Development, Hohai University, Nanjing 210098, PR China
| | - Fuzhu Ye
- Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Ministry of Education, College of Environment, Hohai University, Nanjing 210098, PR China; Yangtze Institute for Conservation and Development, Hohai University, Nanjing 210098, PR China.
| | | | - Xu Zhang
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, PR China
| | - Qiming Li
- Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Ministry of Education, College of Environment, Hohai University, Nanjing 210098, PR China; Yangtze Institute for Conservation and Development, Hohai University, Nanjing 210098, PR China
| | - Ying Lu
- Institute for Smart City of Chongqing University in Liyang, Liyang 213300, PR China
| | - Yuanyuan Liu
- Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Ministry of Education, College of Environment, Hohai University, Nanjing 210098, PR China; Yangtze Institute for Conservation and Development, Hohai University, Nanjing 210098, PR China
| | - Gang Zhang
- Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Ministry of Education, College of Environment, Hohai University, Nanjing 210098, PR China; Yangtze Institute for Conservation and Development, Hohai University, Nanjing 210098, PR China
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Wang X, Wang J, Niu Z. Modelling based study on the occurrence characteristics and influencing factors of the typical antibiotics in Bohai Bay. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 906:167853. [PMID: 37844646 DOI: 10.1016/j.scitotenv.2023.167853] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 09/27/2023] [Accepted: 10/13/2023] [Indexed: 10/18/2023]
Abstract
Previous studies have demonstrated that antibiotics have the potential impacts to ecosystems and human health. However, due to their various classes and distinct characteristics, creating comprehensive, integrated and dynamic simulations has proven to be a challenging task. In this study, a 3D hydrodynamic-contaminant model was developed to gain a better understanding of the transportation and prevalence of antibiotics in the Bohai Bay. Specifically, we focused on four types of antibiotics as examples. To accurately capture the dynamic distribution of antibiotics, both transport and biochemical processes were taken into account. Based on this model, the antibiotics' spatial and temporal distribution was examined, the potential impact of the future antibiotics consumption and climate change was also analyzed. The study found that human activity has a greater impact on the presence of antibiotics in Bohai Bay than temperature rise. Based on the current consumption rate, the total amount of antibiotics in Bohai Bay may increase by 10 ng/L and affect nearly one third of the study area within the next 20-30 years. The significant impact of human activity on water contamination in coastal areas may also have implications for other coastal regions. This finding can provide a valuable framework for pollution prevention and control.
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Affiliation(s)
- Xuan Wang
- Key Laboratory of Ocean Observation Technology of Ministry of Natural Resources, School of Marine Science and Technology, Tianjin University, Tianjin 300072, China.
| | - Jinxin Wang
- Key Laboratory of Ocean Observation Technology of Ministry of Natural Resources, School of Marine Science and Technology, Tianjin University, Tianjin 300072, China
| | - Zhiguang Niu
- Key Laboratory of Ocean Observation Technology of Ministry of Natural Resources, School of Marine Science and Technology, Tianjin University, Tianjin 300072, China
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Tong X, Mohapatra S, Zhang J, Tran NH, You L, He Y, Gin KYH. Source, fate, transport and modelling of selected emerging contaminants in the aquatic environment: Current status and future perspectives. WATER RESEARCH 2022; 217:118418. [PMID: 35417822 DOI: 10.1016/j.watres.2022.118418] [Citation(s) in RCA: 87] [Impact Index Per Article: 43.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 02/07/2022] [Accepted: 04/04/2022] [Indexed: 06/14/2023]
Abstract
The occurrence of emerging contaminants (ECs), such as pharmaceuticals and personal care products (PPCPs), perfluoroalkyl and polyfluoroalkyl substances (PFASs) and endocrine-disrupting chemicals (EDCs) in aquatic environments represent a major threat to water resources due to their potential risks to the ecosystem and humans even at trace levels. Mathematical modelling can be a useful tool as a comprehensive approach to study their fate and transport in natural waters. However, modelling studies of the occurrence, fate and transport of ECs in aquatic environments have generally received far less attention than the more widespread field and laboratory studies. In this study, we reviewed the current status of modelling ECs based on selected representative ECs, including their sources, fate and various mechanisms as well as their interactions with the surrounding environments in aquatic ecosystems, and explore future development and perspectives in this area. Most importantly, the principles, mathematical derivations, ongoing development and applications of various ECs models in different geographical regions are critically reviewed and discussed. The recommendations for improving data quality, monitoring planning, model development and applications were also suggested. The outcomes of this review can lay down a future framework in developing a comprehensive ECs modelling approach to help researchers and policymakers effectively manage water resources impacted by rising levels of ECs.
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Affiliation(s)
- Xuneng Tong
- Department of Civil & Environmental Engineering, National University of Singapore, 1 Engineering Drive 2, Singapore 117576, Singapore
| | - Sanjeeb Mohapatra
- NUS Environmental Research Institute, National University of Singapore, 1 Create way, Create Tower, #15-02, Singapore 138602, Singapore
| | - Jingjie Zhang
- NUS Environmental Research Institute, National University of Singapore, 1 Create way, Create Tower, #15-02, Singapore 138602, Singapore; Shenzhen Municipal Engineering Lab of Environmental IoT Technologies, Southern University of Science and Technology, Shenzhen, 518055, China; Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China.
| | - Ngoc Han Tran
- NUS Environmental Research Institute, National University of Singapore, 1 Create way, Create Tower, #15-02, Singapore 138602, Singapore
| | - Luhua You
- NUS Environmental Research Institute, National University of Singapore, 1 Create way, Create Tower, #15-02, Singapore 138602, Singapore
| | - Yiliang He
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Karina Yew-Hoong Gin
- Department of Civil & Environmental Engineering, National University of Singapore, 1 Engineering Drive 2, Singapore 117576, Singapore; NUS Environmental Research Institute, National University of Singapore, 1 Create way, Create Tower, #15-02, Singapore 138602, Singapore.
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Xu H, Badea AF, Cheng X. Sensitivity analysis of thermal-hydraulic models based on FFTBM-MSM two-layer method for PKL IBLOCA experiment. ANN NUCL ENERGY 2020. [DOI: 10.1016/j.anucene.2020.107732] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Kim J, Mackay D, Powell DE. Roles of steady-state and dynamic models for regulation of hydrophobic chemicals in aquatic systems: A case study of decamethylcyclopentasiloxane (D5) and PCB-180 in three diverse ecosystems. CHEMOSPHERE 2017; 175:253-268. [PMID: 28226279 DOI: 10.1016/j.chemosphere.2017.02.050] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2016] [Revised: 02/06/2017] [Accepted: 02/08/2017] [Indexed: 06/06/2023]
Abstract
We seek to contribute to the improved regulatory use of mass balance models to complement environmental monitoring data by applying the steady-state Quantitative Water Air Sediment Interactive model (QWASI) and a novel unsteady-state QWASI model. A steady-state model can yield not only a useful simulation of chemical fate under near steady-state conditions, but it can provide insights into the likely influences of increasing or decreasing emission rates, temperature changes, and unexpectedly high sensitivities to model parameters that may require additional investigation. We compared the consistency of insights from both types of model, in the expectation that while the dynamic model provides a closer simulation of actual conditions, for many purposes a simple, less computationally demanding, more transparent and less expensive model may be adequate for many regulatory purposes. We investigated the response times of decamethylcyclopentasiloxane (D5) and PCB-180 concentrations in water and sediment under three emission scenarios in three different aquatic systems, namely Lake Ontario, Oslofjord, and Lake Pepin. D5 was predicted to be removed largely by hydrolysis and volatilization in Lake Ontario and Oslofjord whereas it is subject to removal by advective loss in Lake Pepin. The half-times of D5 water concentration to a stepwise reduction in emission were <60 days in all three water bodies. In contrast, the predicted half-times were 0.53, 1.4, and 2.9 years in Lake Pepin, Oslofjord, and Lake Ontario, respectively. We also explored how uncertainties in input parameters propagate into uncertainties of concentrations in water and sediments possibly necessitating more accurate values.
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Affiliation(s)
- Jaeshin Kim
- Toxicology and Environmental Research and Consulting, The Dow Chemical Company, Midland, MI, USA.
| | - Donald Mackay
- Canadian Centre for Environmental Modelling and Chemistry, Trent University, Peterborough, ON, Canada
| | - David E Powell
- Toxicology and Environmental Research and Consulting, The Dow Chemical Company, Midland, MI, USA
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Sun Y, Liang Z, Xiang X, Lan J, Zhang Q, Yuan D. Simulation of the transfer and fate of γ-HCH in epikarst system. CHEMOSPHERE 2016; 148:255-262. [PMID: 26807947 DOI: 10.1016/j.chemosphere.2015.10.091] [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: 07/07/2015] [Revised: 10/21/2015] [Accepted: 10/22/2015] [Indexed: 06/05/2023]
Abstract
The thin surface soil layer and karst features in karst terrains lead to poor filtration, poor pre-purification and rapid infiltration, so that karst groundwater systems are particularly vulnerable to contamination. Due to its extensive use in past, gamma-hexachlorocyclohexane (γ-HCH) is ubiquitous in various environmental compartments of China, even though it has been prohibited since 1984. However, very little is known about its movement and behavior in special karst system. In this study, a dynamic fugacity model was established for γ-HCH in epikarst system via dividing the karst soil into multiple layers coupled with the physical-chemical properties of γ-HCH. The simulated results in soil profile were in good agreement with the measured values of γ-HCH. The modeled results predict that only 18 g γ-HCH will be left in the studied area in 2020, which is only 0.4% of the largest reserves in 1983, and about 99.99% of γ-HCH will remains in soil. The concentrations of γ-HCH in air, plant and 0-20 cm layer soil in the studied area descended quickly after HCHs was prohibited in 1984, while its concentration in soil layer deeper than 20 cm (deeper soil) increased continuously till 1997. The dominant transfer process of γ-HCH between the adjacent compartments in the studied area was from 0-20 cm layer to the deeper soil. Sensitivity analysis results showed that emission rate, infiltration coefficient, total organic carbon of soil, degradation rate in soil, compartment area and volume were the top six influential parameters for predicting γ-HCH concentration.
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Affiliation(s)
- Yuchuan Sun
- Key Laboratory of Eco-environments in Three Gorges Reservoir Region, Ministry of Education, School of Geographical Sciences, Southwest University, Chongqing 400715, China; Karst Dynamics Laboratory, Ministry of Land and Resources, Institute of Karst Geology, Chinese Academy of Geological Sciences, Guilin 541004, China; Field Scientific Observation & Research Base of Karst Eco-environments at Nanchuan in Chongqing, Ministry of Land and Resources of China, Chongqing 40843, China.
| | - Zuobing Liang
- Key Laboratory of Eco-environments in Three Gorges Reservoir Region, Ministry of Education, School of Geographical Sciences, Southwest University, Chongqing 400715, China
| | - Xinyi Xiang
- Key Laboratory of Eco-environments in Three Gorges Reservoir Region, Ministry of Education, School of Geographical Sciences, Southwest University, Chongqing 400715, China
| | - Jiacheng Lan
- Institute of South China Karst, Guizhou Normal University, Guiyang 550001, China
| | - Qiang Zhang
- Karst Dynamics Laboratory, Ministry of Land and Resources, Institute of Karst Geology, Chinese Academy of Geological Sciences, Guilin 541004, China
| | - Daoxian Yuan
- Key Laboratory of Eco-environments in Three Gorges Reservoir Region, Ministry of Education, School of Geographical Sciences, Southwest University, Chongqing 400715, China; Karst Dynamics Laboratory, Ministry of Land and Resources, Institute of Karst Geology, Chinese Academy of Geological Sciences, Guilin 541004, China
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