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New power generation technology options under the greenhouse gases mitigation scenario in China

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  • Liu, Qiang
  • Shi, Minjun
  • Jiang, Kejun

Abstract

Climate change has become a global issue. Almost all countries, including China, are now considering adopting policies and measures to reduce greenhouse gas (GHG) emissions. The power generation sector, as a key source of GHG emissions, will also have significant potential for GHG mitigation. One of the key options is to use new energy technologies with higher energy efficiencies and lower carbon emissions. In this article, we use an energy technology model, MESSAGE-China, to analyze the trend of key new power generation technologies and their contributions to GHG mitigation in China. We expect that the traditional renewable technologies, high-efficiency coal power generation and nuclear power will contribute substantially to GHG mitigation in the short term, and that solar power, biomass energy and carbon capture and storage (CCS) will become more important in the middle and long term. In the meantime, in order to fully bring the role of technology progress into play, China needs to enhance the transfer and absorption of international advanced technologies and independently strengthen her ability in research, demonstration and application of new power generation technologies.

Suggested Citation

  • Liu, Qiang & Shi, Minjun & Jiang, Kejun, 2009. "New power generation technology options under the greenhouse gases mitigation scenario in China," Energy Policy, Elsevier, vol. 37(6), pages 2440-2449, June.
    • Handle: RePEc:eee:enepol:v:37:y:2009:i:6:p:2440-2449
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    1. McDonald, Alan & Schrattenholzer, Leo, 2001. "Learning rates for energy technologies," Energy Policy, Elsevier, vol. 29(4), pages 255-261, March.
    2. Masui, Toshihiko, 2005. "Policy evaluations under environmental constraints using a computable general equilibrium model," European Journal of Operational Research, Elsevier, vol. 166(3), pages 843-855, November.
    3. Miketa, Asami & Schrattenholzer, Leo, 2004. "Experiments with a methodology to model the role of R&D expenditures in energy technology learning processes; first results," Energy Policy, Elsevier, vol. 32(15), pages 1679-1692, October.
    4. Christou, Costas & Hadjipaschalis, Ioannis & Poullikkas, Andreas, 2008. "Assessment of integrated gasification combined cycle technology competitiveness," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(9), pages 2459-2471, December.
    5. Yeh, Sonia & Rubin, Edward S., 2007. "A centurial history of technological change and learning curves or pulverized coal-fired utility boilers," Institute of Transportation Studies, Working Paper Series qt96z5s545, Institute of Transportation Studies, UC Davis.
    6. Rubin, Edward S & Taylor, Margaret R & Yeh, Sonia & Hounshell, David A, 2004. "Learning curves for environmental technology and their importance for climate policy analysis," Energy, Elsevier, vol. 29(9), pages 1551-1559.
    7. Kypreos, Socrates, 2005. "Modeling experience curves in MERGE (model for evaluating regional and global effects)," Energy, Elsevier, vol. 30(14), pages 2721-2737.
    8. Yeh, Sonia & Rubin, Edward S., 2007. "A centurial history of technological change and learning curves for pulverized coal-fired utility boilers," Energy, Elsevier, vol. 32(10), pages 1996-2005.
    9. Yeh, Sonia & Rubin, Edward S., 2007. "A centurial history of technological change and learning curves or pulverized coal-fired utility boilers," Institute of Transportation Studies, Working Paper Series qt1f25b3xq, Institute of Transportation Studies, UC Davis.
    10. Yeh, Sonia & Rubin, Edward S, 2007. "A centurial history of technological change and learning curves or pulverized coal-fired utility boilers," Institute of Transportation Studies, Working Paper Series qt3zz2w2wr, Institute of Transportation Studies, UC Davis.
    11. Yeh, Sonia & Rubin, Edward, 2007. "A centurial history of technological change and learning curves or pulverized coal-fired utility boilers," Institute of Transportation Studies, Working Paper Series qt4xn4w7rn, Institute of Transportation Studies, UC Davis.
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