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Emissions Intensity Targeting: From China's 12th Five Year Plan to its Copenhagen Commitment

Author

Listed:
  • Yingying Lu
  • Alison Stegman
  • Yiyong Cai
Abstract
China is currently the world’s largest single source of fossil fuel related CO2 emissions. In response to pressure from the international community, and in recognition of its role in global climate change mitigation, the Chinese government has announced a series of climate policy commitments, in both the Copenhagen Accord and its domestic 12th 5 Year Plan, to gradually reduce emissions intensity by 2020. Emissions intensity reduction commitments differ significantly from emission level reduction commitments that are commonly adopted by developed economies. In this paper, we investigate the economic implications of China’s recent commitments to reduce emissions intensity, and highlight the complexities involved in modelling intensity targets under uncertainty. Using G-Cubed, an intertemporal, computable general equilibrium model of the world economy, we show that China’s emissions intensity targets could be achieved with a range of low and high growth emissions level trajectories corresponding to low and high growth GDP scenarios, which lead to different welfare consequences.

Suggested Citation

  • Yingying Lu & Alison Stegman & Yiyong Cai, 2012. "Emissions Intensity Targeting: From China's 12th Five Year Plan to its Copenhagen Commitment," CAMA Working Papers 2012-45, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    • Handle: RePEc:een:camaaa:2012-45
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    References listed on IDEAS

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    Cited by:

    1. Xuankai Deng & Yanhua Yu & Yanfang Liu, 2015. "Temporal and Spatial Variations in Provincial CO 2 Emissions in China from 2005 to 2015 and Assessment of a Reduction Plan," Energies, MDPI, vol. 8(5), pages 1-23, May.
    2. Cai, Yiyong & Newth, David & Finnigan, John & Gunasekera, Don, 2015. "A hybrid energy-economy model for global integrated assessment of climate change, carbon mitigation and energy transformation," Applied Energy, Elsevier, vol. 148(C), pages 381-395.
    3. Yingying Lu & David I. Stern, 2016. "Substitutability and the Cost of Climate Mitigation Policy," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 64(1), pages 81-107, May.
    4. Larry Hughes & Moniek Jong & Zach Thorne, 2021. "(De)coupling and (De)carbonizing in the economies and energy systems of the G20," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(4), pages 5614-5639, April.
    5. Wang, Jiexin & Wang, Song, 2023. "The effect of electricity market reform on energy efficiency in China," Energy Policy, Elsevier, vol. 181(C).
    6. Jun Dong & Yu Ma & Hongxing Sun, 2016. "From Pilot to the National Emissions Trading Scheme in China: International Practice and Domestic Experiences," Sustainability, MDPI, vol. 8(6), pages 1-17, May.
    7. Yiyong Cai & Yingying Lu & David Newth & Alison Stegman, 2013. "Modelling Complex Emissions Intensity Targets with a Simple Simulation Algorithm," CAMA Working Papers 2013-33, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    8. Lebunu Hewage Udara Willhelm Abeydeera & Jayantha Wadu Mesthrige & Tharushi Imalka Samarasinghalage, 2019. "Global Research on Carbon Emissions: A Scientometric Review," Sustainability, MDPI, vol. 11(14), pages 1-25, July.
    9. Lu, Yingying & Stegman, Alison & Cai, Yiyong, 2013. "Emissions intensity targeting: From China's 12th Five Year Plan to its Copenhagen commitment," Energy Policy, Elsevier, vol. 61(C), pages 1164-1177.
    10. Yulan Lv & Yumeng Pang & Buhari Doğan, 2022. "The role of Chinese fiscal decentralization in the governance of carbon emissions: perspectives from spatial effects decomposition and its heterogeneity," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 68(3), pages 635-668, June.
    11. Cai, Yiyong & Arora, Vipin, 2015. "Disaggregating electricity generation technologies in CGE models: A revised technology bundle approach with an application to the U.S. Clean Power Plan," Applied Energy, Elsevier, vol. 154(C), pages 543-555.
    12. Zhu, Bangzhu & Wang, Kefan & Chevallier, Julien & Wang, Ping & Wei, Yi-Ming, 2015. "Can China achieve its carbon intensity target by 2020 while sustaining economic growth?," Ecological Economics, Elsevier, vol. 119(C), pages 209-216.
    13. Xiang Chen & Xuping Zhang & Xin Wu & Ching-Cheng Lu, 2022. "The environmental health and energy efficiency in China: A network slacks-based measure," Energy & Environment, , vol. 33(1), pages 170-188, February.
    14. Li, Guangyao & Yang, Jin & Chen, Dingjiang & Hu, Shanying, 2017. "Impacts of the coming emission trading scheme on China’s coal-to-materials industry in 2020," Applied Energy, Elsevier, vol. 195(C), pages 837-849.
    15. Xiangsheng Dou & Huanying Cui, 2017. "Low-carbon society creation and socio-economic structural transition in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 19(5), pages 1577-1599, October.
    16. Rodríguez, Miguel & Pena-Boquete, Yolanda, 2017. "Carbon intensity changes in the Asian Dragons. Lessons for climate policy design," Energy Economics, Elsevier, vol. 66(C), pages 17-26.
    17. Yiyong Cai & Yingying Lu & Alison Stegman & David Newth, 2017. "Simulating emissions intensity targets with energy economic models: algorithm and application," Annals of Operations Research, Springer, vol. 255(1), pages 141-155, August.

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    More about this item

    Keywords

    China; Emissions intensity targeting; Climate policy; G-Cubed model;
    All these keywords.

    JEL classification:

    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy

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