Unveiling dioxin dynamics: A whole-process simulation study of municipal solid waste incineration.

Sci Total Environ

Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China; Beijing Laboratory of Smart Environmental Protection, Beijing 100124, China.

Published: December 2024

AI Article Synopsis

  • The article discusses how theoretical research explains the formation of dioxin (DXN) during the incineration of municipal solid waste (MSW), highlighting discrepancies between predicted and actual DXN concentrations.
  • It identifies key factors affecting these discrepancies, including the type of waste treatment, waste characteristics, and operational controls, while noting that the process of DXN generation, adsorption, and emission is not fully understood.
  • To address this, the authors propose a detailed numerical simulation model that incorporates multiple stages of DXN concentration evolution, aiming to improve strategies for reducing DXN emissions and advancing intelligent control technologies in MSWI plants.

Article 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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Source
http://dx.doi.org/10.1016/j.scitotenv.2024.176241DOI Listing

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