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Understanding the complexity of existing fossil fuel power plant decarbonization.
Zhang, Chuan; Zhai, Haibo; Cao, Liwei; Li, Xiang; Cheng, Fangwei; Peng, Liqun; Tong, Kangkang; Meng, Jing; Yang, Lei; Wang, Xiaonan.
Afiliación
  • Zhang C; Institute of Energy, Peking University, Beijing 100871, China.
  • Zhai H; Andlinger Center for Energy and the Environment, Princeton University, Princeton, NJ 08544, USA.
  • Cao L; Department of Civil & Architectural Engineering, University of Wyoming, Laramie, WY 82071, USA.
  • Li X; Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
  • Cheng F; Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge CB3 0AS, UK.
  • Peng L; Institute of Energy, Peking University, Beijing 100871, China.
  • Tong K; Andlinger Center for Energy and the Environment, Princeton University, Princeton, NJ 08544, USA.
  • Meng J; Princeton School of Public and International Affairs, Princeton University, Princeton, NJ 08544, USA.
  • Yang L; China-UK Low Carbon College, Shanghai Jiao Tong University, Shanghai, 201308 China.
  • Wang X; The Bartlett School of Sustainable Construction, University College London, London, WC1E 7HB, UK.
iScience ; 25(8): 104758, 2022 Aug 19.
Article en En | MEDLINE | ID: mdl-35942095
ABSTRACT
Growing national decarbonization commitments require rapid and deep reductions of carbon dioxide emissions from existing fossil-fuel power plants. Although retrofitting existing plants with carbon capture and storage or biomass has been discussed extensively, yet such options have failed to provide evident emission reductions at a global scale so far. Assessments of decarbonization technologies tend to focus on one specific option but omit its interactions with competing technologies and related sectors (e.g., water, food, and land use). Energy system models could mimic such inter-technological and inter-sectoral competition but often aggregate plant-level parameters without validation, as well as fleet-level inputs with large variability and uncertainty. To enhance the accuracy and reliability of top-down optimization models, bottom-up plant-level experience accumulation is of vital importance. Identifying sweet spots for plant-level pilot projects, overcoming the technical, financial, and social obstacles of early large-scale demonstration projects, incorporating equity into the transition, propagating the plant-level potential to generate fleet-level impacts represent some key complexity of existing fossil-fuel power plant decarbonization challenges that imposes the need for a serious re-evaluation of existing fossil fuel power plant abatement in energy transition.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: IScience Año: 2022 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: IScience Año: 2022 Tipo del documento: Article País de afiliación: China