Performance evaluation of NOx absorption by different denitration absorbents in wet flue gas denitration

Liu, Bingcheng; Peng, Dewen; Chiang, Pen‐Chi; Chu, Chih‐Peng

doi:10.1016/j.jtice.2023.104840

Cited by 5 publications

(1 citation statement)

References 58 publications

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“…Mainly, three ways can be used in the removal of NO x : source control, process control, and end-of-pipe control. Among them, selective catalytic reduction (SCR), which is end-of-pipe control, was widely used in the industry for removing NO x due to its high denitration efficiency, safe operation, and no secondary pollution [82][83][84][85]. One important application in industry is the marine SCR system for ocean-going vessels.…”

Section: Removing No Xmentioning

confidence: 99%

Preparation of Mesoporous Zeolites and Their Applications in Catalytic Elimination of Atmospheric Pollutants

Miao,

Wang,

Zhou

et al. 2024

Catalysts

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With increasing environmental awareness, the issue of atmospheric pollution has gained significant attention. Specifically, three types of atmospheric pollutants, namely, nitrogen oxides, volatile organic compounds, and carbon monoxide, have become the focus of widespread concern. In addressing these pollutants, mesoporous zeolites have emerged as promising materials due to their large specific surface area, which enables effective dispersion of active sites, and their large pore volume, which facilitates efficient diffusion. This article provides a comprehensive overview of the preparation methods of mesoporous zeolites and their applications in removing nitrogen oxides, volatile organic compounds, and carbon monoxide. It also highlights the challenges and limitations faced by the application of mesoporous zeolites in pollutant removal and emphasizes their potential as efficient catalysts.

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Section: Removing No Xmentioning

confidence: 99%

Preparation of Mesoporous Zeolites and Their Applications in Catalytic Elimination of Atmospheric Pollutants

Miao,

Wang,

Zhou

et al. 2024

Catalysts

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Denitrification Technology and The Catalysts: A Review and Recent Advances

Liu,

Zhang,

Chen

2024

ChemCatChem

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With the acceleration of industrialization and the increasing prominence of environmental pollution problems, the emission of nitrogen oxides (NOx) in the atmosphere has become a global concern. These emissions are not only hazardous to human health, but also one of the main factors leading to acid rain, photochemical smog and global climate change. Therefore, the development and implementation of efficient denitrification technologies are an important issue for environmental protection. The present review focuses on the research progress of the denitrification technology in the recent years, including the traditional denitrification methods and common technologies. At the same time, the advantages, limitations and application prospects of each method are analyzed. The mechanisms, influencing factors, advantages and disadvantages of the denitrification catalysts are also discussed. In addition, the future research trends and potential challenges of denitrification technology are discussed. It is expected that this review will provide useful references for promoting the development and application of denitrification technology, which may help researchers to choose high‐performance and cost‐effective methods.

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NOx formation model for utility boilers using robust two-step steady-state detection and multimodal residual convolutional auto-encoder

Chen,

Yu,

Zhu

et al. 2024

Journal of the Taiwan Institute of Chemical Engineers

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Performance evaluation of NOx absorption by different denitration absorbents in wet flue gas denitration

Cited by 5 publications

References 58 publications

Preparation of Mesoporous Zeolites and Their Applications in Catalytic Elimination of Atmospheric Pollutants

Preparation of Mesoporous Zeolites and Their Applications in Catalytic Elimination of Atmospheric Pollutants

Denitrification Technology and The Catalysts: A Review and Recent Advances

NOx formation model for utility boilers using robust two-step steady-state detection and multimodal residual convolutional auto-encoder

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