Modeling of the Whole Lifecycle Dioxins for Municipal Solid Waste Inci

Description

This book by leading experts consolidates knowledge on the numerical simulation and AI-driven modeling of multiple points dioxins concentration in the municipal solid waste incineration (MSWI) process to provide readers with the skills to develop safer and more efficient waste management practices. The authors explore the complex interplay between MSW management and environmental health,... Read more

This book by leading experts consolidates knowledge on the numerical simulation and AI-driven modeling of multiple points dioxins concentration in the municipal solid waste incineration (MSWI) process to provide readers with the skills to develop safer and more efficient waste management practices.

The authors explore the complex interplay between MSW management and environmental health, specifically focusing on the generation and production of dioxins during incineration. This comprehensive work amalgamates theoretical insights and practical applications, leveraging numerical simulations and artificial intelligence techniques to offer innovative modeling solutions. It addresses the critical problem of dioxin generation and emissions from MSWI through a structured approach that integrates exhaustive research data, case studies, and advanced computational methodologies that provides an integrated model that accounts for various operational parameters and their effects on emissions. It both discusses the existing theoretical frameworks and empirical studies and applies advanced modeling techniques to yield practical insights. Readers will find clear representations of simulation processes alongside discussions on optimization and control mechanisms. This facilitates an understanding of the underlying mechanisms of dioxin formation, enabling targeted solutions that are informed by both experimental results and advanced simulation techniques. This ultimately furnishes practitioners with robust tools to better understand and mitigate the risks associated with dioxin emissions so they can contribute to safer and more efficient waste management practices.

This is an essential resource for engineers, policy-makers, and researchers involved in sustainable waste management and environmental protection. In particular, environmental engineers, MSWI plant operators, and researchers will benefit from the integrated theoretical and practical approach and discussion of real-world scenarios and applications.

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1. Introduction Part I: Dioxins characteristics analysis of in MSWI process 2. MSWI Process Description for Dioxins 3. Investigation on Dioxins Emission Characteristic during Complete Maintenance Operating Period 4. Assessment of Dioxins Formation and Emission Characteristics for One Year Part II: Dioxins with numerical simulation modelling 5. Non-Manipulated Variable Modeling of Solid-Phase Combustion in the Furnace 6. Unveiling Dioxin Dynamics: A Whole-Process Simulation Model Part III: Dioxins with AI driven detection modeling and risk warning 7. Multi-Scale Modeling Using Gan And Deep Forest Regression for Dioxin Emission Concentration 8. Hybrid Simulator-Based Mechanism and Data-Driven Modeling for Multi-Demand Dioxin Emissions Concentration 9. Multimodal Data-Driven Interpretable Deep Modeling Approach of Dioxins Generation Concentration 10. AI-Based Tree Modeling for Multi-Point Dioxin Concentrations 11. Virtual Sample Generation Method Based on Generative Adversarial Fuzzy Neural Network for Dioxin Emission Risk Warning 12. Summary and outlook

Author(s)

Biography

Jian Tang is a Professor at Beijing University of Technology and Deputy Director of Beijing Laboratory of Smart Environmental Protection. He received his Ph.D. from Northeastern University, Shenyang, China, in 2012. He has authorized over 50 US/Chinese invention patents and obtained over 30 software copyrights. He is a senior member of IEEE.

Loai Aljerf is a Professor at Damascus University. He has created partnerships and memberships in prestigious organizations, including the Advances in Cleaner Production Network, the German Chemical Society e.V. (GDCh), the Asian Chemical Society, and the American University of Beirut.

Junfei Qiao is a Professor with the Beijing University of Technology and Director of Beijing Laboratory of Smart Environmental Protection, Beijing, China. He received his Ph.D. from Northeastern University, Shenyang, China, in 1998. He is a member of several government bodies and director of several national committees in China. He is a senior member of IEEE.

Modeling of the Whole Lifecycle Dioxins for Municipal Solid Waste Incineration Numerical Simulation and AI-Driven Method

Description

Table of Contents

Author(s)

Biography

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