Kefa Cen

Simultaneous Multi-Pollutants Removal in Flue Gas by Ozone mainly introduces the multi-pollution control technology in flue gas by ozone oxidation. Based on the authors' recent research works, the book will provide readers with the updated fundamental research findings, comprised of the detail kinetic mechanisms between ozone and gas components in flue gas integrated with experimental and kinetic modeling work. The demonstration case of the multi-pollutant removal technology by ozone is also presented. The book is suitable for the researchers working in the areas of energy and environmental protection, and pollutant control technology. Zhihua Wang is a Professor at the State Key Laboratory of Clean Energy Utilization of Zhejiang University; Kefa Cen is the Academician of Chinese Academy of Engineering, and the director of Institute for Thermal Power Engineering of Zhejiang University; Junhu Zhou is a Qiushi Scholar Professor at the State Key Laboratory of Clean Energy Utilization of Zhejiang University; Jianren Fan is the Cheung Kong Scholar Professor at the State Key Laboratory of Clean Energy Utilization of Zhejiang University.

This book presents the latest multi-pollutant (mainly NOx, SOx, particulate matter, heavy metals) control technologies for flue gases and the applications in coal-fired power plants. Pollutant control by catalytic, electric, and absorption methods, the multi-pollutant removal system and its performance evaluation are systematically introduced. This book is a valuable reference for researchers and practitioners in environmental science & engineering, energy power engineering, and chemical science & engineering, etc.

This book presents the latest findings on the subject of combustion optimization based on computational intelligence. It covers a broad range of topics, including the modeling of coal combustion characteristics based on artificial neural networks and support vector machines. It also describes the optimization of combustion parameters using genetic algorithms or ant colony algorithms, an online coal optimization system, etc. Accordingly, the book offers a unique guide for researchers in the areas of combustion optimization, NOx emission control, energy and power engineering, and chemical engineering.

This book presents the latest findings on the subject of combustion optimization based on computational intelligence. It covers a broad range of topics, including the modeling of coal combustion characteristics based on artificial neural networks and support vector machines. It also describes the optimization of combustion parameters using genetic algorithms or ant colony algorithms, an online coal optimization system, etc. Accordingly, the book offers a unique guide for researchers in the areas of combustion optimization, NOx emission control, energy and power engineering, and chemical engineering.