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Liu H, Chi L, Shen J, Arandiyan H, Wang Y, Wang X. Principles, applications, and limitations of diffusive gradients in thin films induced fluxed in soils and sediments. CHEMOSPHERE 2024; 350:141061. [PMID: 38159729 DOI: 10.1016/j.chemosphere.2023.141061] [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: 08/24/2023] [Revised: 12/26/2023] [Accepted: 12/27/2023] [Indexed: 01/03/2024]
Abstract
The diffusive gradients in thin films (DGT) technique serves as a passive sampling method, inducing analyte transport and concentration. Its application is widespread in assessing labile components of metals, organic matter, and nutrients across various environmental media such as water, sediments, and saturated soils. The DGT devices effectively reduce the porewater concentration through irreversible binding of solutes, consequently promoting the release of labile species from the soil/sediment solid phase. However, the precise quantification of simultaneous adsorption and desorption of labile species using DGT devices alone remains a challenge. To address this challenge, the DGT-Induced Fluxes in Soils and Sediments (DIFS) model was developed. This model simulates analyte kinetics in solid phases, solutions, and binding resins by incorporating factors such as soil properties, resupply parameters, and kinetic principles. While the DIFS model has been iteratively improved to increase its accuracy in portraying kinetic behavior in soil/sediment, researchers' incomplete comprehension of it still results in unrealistic fitting outcomes and an oversight of the profound implications posed by kinetic parameters during implementation. This review provides a comprehensive overview of the optimization and utilization of DIFS models, encompassing fundamental concepts behind DGT devices and DIFS models, the kinetic interpretation of DIFS parameters, and instances where the model has been applied to study soils and sediments. It also highlights preexisting limitations of the DIFS model and offers suggestions for more precise modeling in real-world environments.
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Affiliation(s)
- Huaji Liu
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China; National Observation and Research Station of Erhai Lake Ecosystem in Yunnan, Dali, 671000, China
| | - Lina Chi
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China; National Observation and Research Station of Erhai Lake Ecosystem in Yunnan, Dali, 671000, China
| | - Jian Shen
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China; National Observation and Research Station of Erhai Lake Ecosystem in Yunnan, Dali, 671000, China
| | - Hamidreza Arandiyan
- Laboratory of Advanced Catalysis for Sustainability, School of Chemistry, University of Sydney, Sydney, NSW, 2006, Australia; Centre for Advanced Materials and Industrial Chemistry (CAMIC), School of Science, RMIT University, Melbourne, VIC, 3000, Australia
| | - Yuan Wang
- Department of Chemical Engineering, The University of Melbourne, Parkville, VIC 3010 Australia
| | - Xinze Wang
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China; National Observation and Research Station of Erhai Lake Ecosystem in Yunnan, Dali, 671000, China; Yunnan Dali Research Institute of Shanghai Jiao Tong University, Dali, 67100, China.
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