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Audino F, Pérez-Moya M, Graells M, Espuña A, Csukas B, Varga M. A novel modeling approach for a generalizable photo-Fenton-based degradation of organic compounds. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2020; 27:22913-22934. [PMID: 32329002 PMCID: PMC7293673 DOI: 10.1007/s11356-020-08616-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Accepted: 03/26/2020] [Indexed: 06/11/2023]
Abstract
This work aims at proposing and validating a model that can be exploited for the future development of industrial applications (e.g., process design and control) of Fenton and photo-Fenton processes. Hence, a compromise modeling solution has been developed between the non-generalizable accuracy of the first principles models (FPMs) and the oversimplification of the empirical models (EMs). The work presents a novel model of moderate complexity that is simplified enough to be generalizable and computationally affordable, while retaining physical meaning. The methodology is based on a general degradation mechanism that can be algorithmically generated from the carbon number of the target compound, as well as from the knowledge of two kinetic parameters, one for the faster initial rate and the other one for the subsequent degradation steps. The contaminant degradation mechanism has been combined with an appropriately simplified implementation of the well-known Fenton and photo-Fenton kinetics. This model describes the degradation not only of the target compound and of the oxidant, but also of total organic carbon (TOC), which is used to define the overall quality of the water. Experimental design techniques were used along with a non-conventional modeling methodology of programmable process structures (PPS). This novel modeling approach was applied and validated on the degradation of three model compounds. A successful prediction of the evolution of the contaminants H2O2 and TOC was confirmed and assessed by the root mean square error (RMSE).
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Affiliation(s)
- Francesca Audino
- Chemical Engineering Department, Escola d'Enginyeria de Barcelona Est (EEBE), Universitat Politècnica de Catalunya, Av. Eduard Maristany, 16, 08019, Barcelona, Spain
| | - Montserrat Pérez-Moya
- Chemical Engineering Department, Escola d'Enginyeria de Barcelona Est (EEBE), Universitat Politècnica de Catalunya, Av. Eduard Maristany, 16, 08019, Barcelona, Spain
| | - Moisès Graells
- Chemical Engineering Department, Escola d'Enginyeria de Barcelona Est (EEBE), Universitat Politècnica de Catalunya, Av. Eduard Maristany, 16, 08019, Barcelona, Spain
| | - Antonio Espuña
- Chemical Engineering Department, Escola d'Enginyeria de Barcelona Est (EEBE), Universitat Politècnica de Catalunya, Av. Eduard Maristany, 16, 08019, Barcelona, Spain
| | - Bela Csukas
- Research Group on Process Network Engineering, Institute of Methodology, Kaposvar University, 40 Guba S, Kaposvar, 7400, Hungary
| | - Monika Varga
- Research Group on Process Network Engineering, Institute of Methodology, Kaposvar University, 40 Guba S, Kaposvar, 7400, Hungary.
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Varga M, Csukas B. Generation of extensible ecosystem models from a network structure and from locally executable programs. Ecol Modell 2017. [DOI: 10.1016/j.ecolmodel.2017.09.014] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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