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Can China realize its carbon emission reduction goal in 2020: From the perspective of thermal power development

Author

Listed:
  • Liu, Liwei
  • Zong, Haijing
  • Zhao, Erdong
  • Chen, Chuxiang
  • Wang, Jianzhou

Abstract

This paper answers the question of whether China can realize its target to reduce the intensity of carbon dioxide (CO2) emissions per unit of GDP that was announced at the Copenhagen Conference by forecasting CO2 emission intensity in 2020 from the perspective of China’s coal-fired thermal power development. We construct a combined forecasting model with a grey model (GM(1,1)), an autoregressive integrated moving average model (ARIMA) and a second order polynomial regression model (SOPR) and improve forecast accuracy by optimizing three coefficients of the individual aforementioned models with Particle Swarm Optimization (PSO). The results show that by 2020 thermal power generation will reach 7258.83billion kWh, CO2 emissions will reach 17379.90million tons, and CO2 emission intensity will be 0.21kilogram per Yuan, which is almost twice as 40–45% of the 2005 level. It is warned that situation of meeting targets over the timescale by Chinese government is extremely serious if China’s coal-fired thermal power continues expanding at its current rate. The thermal power generation of 2020 that satisfies the emission reduction target should be controlled in an interval between 3801.45 and 4492.62billion kWh. The regional forecasting results of coal-fired thermal power generation based on administrative region and economic belt demonstrate power output from coal-fired thermal power of East China and Eastern Economic Belt respectively account for 30.3% and 45.65% that of China by the end of 2020. Shanghai, Jiangsu, Zhejiang, Shandong and Fujian are thermal power generation concentrated areas with arduous task of carbon emission reduction by 2020.

Suggested Citation

  • Liu, Liwei & Zong, Haijing & Zhao, Erdong & Chen, Chuxiang & Wang, Jianzhou, 2014. "Can China realize its carbon emission reduction goal in 2020: From the perspective of thermal power development," Applied Energy, Elsevier, vol. 124(C), pages 199-212.
  • Handle: RePEc:eee:appene:v:124:y:2014:i:c:p:199-212
    DOI: 10.1016/j.apenergy.2014.03.001
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    References listed on IDEAS

    as
    1. Zhang, Shaojun & Wu, Ye & Liu, Huan & Huang, Ruikun & Yang, Liuhanzi & Li, Zhenhua & Fu, Lixin & Hao, Jiming, 2014. "Real-world fuel consumption and CO2 emissions of urban public buses in Beijing," Applied Energy, Elsevier, vol. 113(C), pages 1645-1655.
    2. Tsai, Chi-Yang & Yeh, Szu-Wei, 2008. "A multiple objective particle swarm optimization approach for inventory classification," International Journal of Production Economics, Elsevier, vol. 114(2), pages 656-666, August.
    3. Yuan, Jiahai & Hou, Yong & Xu, Ming, 2012. "China's 2020 carbon intensity target: Consistency, implementations, and policy implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 4970-4981.
    4. ZhongXiang Zhang, 2010. "Assessing China’s Energy Conservation and Carbon Intensity: How Will the Future Differ from the Past?," Working Papers 2010.92, Fondazione Eni Enrico Mattei.
    5. Du, Kerui & Lu, Huang & Yu, Kun, 2014. "Sources of the potential CO2 emission reduction in China: A nonparametric metafrontier approach," Applied Energy, Elsevier, vol. 115(C), pages 491-501.
    6. Michieka, Nyakundi M. & Fletcher, Jerald & Burnett, Wesley, 2013. "An empirical analysis of the role of China’s exports on CO2 emissions," Applied Energy, Elsevier, vol. 104(C), pages 258-267.
    7. Chandran Govindaraju, V.G.R. & Tang, Chor Foon, 2013. "The dynamic links between CO2 emissions, economic growth and coal consumption in China and India," Applied Energy, Elsevier, vol. 104(C), pages 310-318.
    8. Yu, Shiwei & Wei, Yi-Ming & Fan, Jingli & Zhang, Xian & Wang, Ke, 2012. "Exploring the regional characteristics of inter-provincial CO2 emissions in China: An improved fuzzy clustering analysis based on particle swarm optimization," Applied Energy, Elsevier, vol. 92(C), pages 552-562.
    9. ZhiDong, Li, 2003. "An econometric study on China's economy, energy and environment to the year 2030," Energy Policy, Elsevier, vol. 31(11), pages 1137-1150, September.
    10. Saxena, Samveg & Phadke, Amol & Gopal, Anand, 2014. "Understanding the fuel savings potential from deploying hybrid cars in China," Applied Energy, Elsevier, vol. 113(C), pages 1127-1133.
    11. Guo, Zhenhai & Zhao, Jing & Zhang, Wenyu & Wang, Jianzhou, 2011. "A corrected hybrid approach for wind speed prediction in Hexi Corridor of China," Energy, Elsevier, vol. 36(3), pages 1668-1679.
    12. Zhang, Zhongxiang, 2000. "Decoupling China's Carbon Emissions Increase from Economic Growth: An Economic Analysis and Policy Implications," World Development, Elsevier, vol. 28(4), pages 739-752, April.
    13. Choi, Yongrok & Zhang, Ning & Zhou, P., 2012. "Efficiency and abatement costs of energy-related CO2 emissions in China: A slacks-based efficiency measure," Applied Energy, Elsevier, vol. 98(C), pages 198-208.
    14. Weber, Christopher L. & Peters, Glen P. & Guan, Dabo & Hubacek, Klaus, 2008. "The contribution of Chinese exports to climate change," Energy Policy, Elsevier, vol. 36(9), pages 3572-3577, September.
    15. Xu, Gang & Yang, Yong-ping & Lu, Shi-yuan & Li, Le & Song, Xiaona, 2011. "Comprehensive evaluation of coal-fired power plants based on grey relational analysis and analytic hierarchy process," Energy Policy, Elsevier, vol. 39(5), pages 2343-2351, May.
    16. Yue, Ting & Long, Ruyin & Chen, Hong & Zhao, Xin, 2013. "The optimal CO2 emissions reduction path in Jiangsu province: An expanded IPAT approach," Applied Energy, Elsevier, vol. 112(C), pages 1510-1517.
    17. Wang, Ping & Wu, Wanshui & Zhu, Bangzhu & Wei, Yiming, 2013. "Examining the impact factors of energy-related CO2 emissions using the STIRPAT model in Guangdong Province, China," Applied Energy, Elsevier, vol. 106(C), pages 65-71.
    18. Su, Bin & Ang, B.W., 2014. "Input–output analysis of CO2 emissions embodied in trade: A multi-region model for China," Applied Energy, Elsevier, vol. 114(C), pages 377-384.
    19. Cai, Wenjia & Wang, Can & Wang, Ke & Zhang, Ying & Chen, Jining, 2007. "Scenario analysis on CO2 emissions reduction potential in China's electricity sector," Energy Policy, Elsevier, vol. 35(12), pages 6445-6456, December.
    20. Chung, Whan-Sam & Tohno, Susumu & Choi, Ki-Hong, 2011. "Socio-technological impact analysis using an energy IO approach to GHG emissions issues in South Korea," Applied Energy, Elsevier, vol. 88(11), pages 3747-3758.
    21. Tan, Zhongfu & Li, Li & Wang, Jianjun & Wang, Jianhui, 2011. "Examining the driving forces for improving China’s CO2 emission intensity using the decomposing method," Applied Energy, Elsevier, vol. 88(12), pages 4496-4504.
    22. Jon D. Samuels & Rodrigo Sekkel, 2013. "Forecasting with Many Models: Model Confidence Sets and Forecast Combination," Staff Working Papers 13-11, Bank of Canada.
    23. Zhang, Shuwei & Bauer, Nico & Luderer, Gunnar & Kriegler, Elmar, 2014. "Role of technologies in energy-related CO2 mitigation in China within a climate-protection world: A scenarios analysis using REMIND," Applied Energy, Elsevier, vol. 115(C), pages 445-455.
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    Keywords

    CO2 emission reduction; Thermal power; Combination forecast; China;

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