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Unveiling dioxin dynamics: A whole-process simulation study of municipal solid waste incineration.
Xia, Heng; Tang, Jian; Aljerf, Loai; Chen, Jiakun.
Afiliación
  • Xia H; Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China; Beijing Laboratory of Smart Environmental Protection, Beijing 100124, China.
  • Tang J; Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China; Beijing Laboratory of Smart Environmental Protection, Beijing 100124, China. Electronic address: freeflytang@bjut.edu.cn.
  • Aljerf L; Faculty of Pharmacy, Al-Sham Private University, Damascus 5910011, Syrian Arab Republic; Department of Physical Sciences, Collage of Sciences, University of Findlay, 1000 N. Main St., Findlay, OH 45840, USA. Electronic address: loai_aljerf.foph@aspu.edu.sy.
  • Chen J; Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China; Beijing Laboratory of Smart Environmental Protection, Beijing 100124, China.
Sci Total Environ ; 954: 176241, 2024 Sep 18.
Article en En | MEDLINE | ID: mdl-39299308
ABSTRACT
Theoretical research has explained the process of dioxin (DXN) formation in the municipal solid waste incineration (MSWI). This process includes the generation, adsorption, and emission of DXN. Actual DXN concentrations often significantly deviate from theoretical models. This discrepancy is influenced by several key factors the type of integrated municipal solid waste (MSW) treatment process, the characteristics of the waste, and the operational controls. The progression of DXN generation, adsorption, and emission concentrations within the MSWI process remains unclear. This lack of clarity is especially pronounced when examining the accounting for the specific components of the MSW. To unravel the evolution of DXN, this article proposes a comprehensive numerical simulation model for the entire process of DXN concentration in an MSWI plant. The model is designed based on existing knowledge of MSW combustion and DXN mechanisms, leveraging FLIC and ASPEN simulation software. It incorporates six key stages to facilitate the DXN simulation precipitation and formation, high-temperature pyrolysis, high-temperature gas-phase synthesis, low-temperature catalytic synthesis, adsorption on activated carbon, and emission to the atmosphere. Under both benchmark and multiple operating conditions, the simulated experiments confirm the effective representation of the evolution of DXN concentrations throughout the process. Consequently, this study presents a model designed to enhance the development of strategies aimed at reducing DXN emissions and to foster innovation in intelligent control technologies.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Sci Total Environ Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Países Bajos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Sci Total Environ Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Países Bajos