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Impacts of China's emissions trading schemes on deployment of power generation with carbon capture and storage

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  • Morris, Jennifer
  • Paltsev, Sergey
  • Ku, Anthony Y.

Abstract

The establishment of an emissions trading scheme (ETS) in China creates the potential for a “least cost” solution for achieving the greenhouse gas (GHG) emissions reductions required for China to meet its Paris Agreement pledges. China has pledged to reduce CO2 intensity by 60–65% in 2030 relative to 2005 and to stop the increase in absolute CO2 emissions around 2030. In this series of studies, we enhance the MIT Economic Projection and Policy Analysis (EPPA) model to include the latest assessments of the costs of power generation technologies in China to evaluate the impacts of different potential ETS pathways on deployment of carbon capture and storage (CCS) technology. This paper reports the results from baseline scenarios where power generation prices are assumed to be homogeneous across the country for a given mode of generation. We find that there are different pathways where CCS might play an important role in reducing the emission intensity in China's electricity sector, especially for low carbon intensity targets consistent with the ultimate goals of the Paris Agreement. Uncertainty about the exact technology mix suggests that decision makers should be wary of picking winning technologies, and should instead seek to provide incentives for emission reductions. While it will be challenging to meet the CO2 intensity target of 550 g/kWh for the electric power sector by 2020, multiple pathways exist for achieving lower targets over a longer timeframe. Our initial analysis shows that carbon prices of 35–40$/tCO2 make CCS technologies on coal-based generation cost-competitive against other modes of generation and that carbon prices higher than 100$/tCO2 favor a major expansion of CCS. The next step is to confirm these initial results with more detailed modeling that takes into account granularity across China's energy sector at the provincial level.

Suggested Citation

  • Morris, Jennifer & Paltsev, Sergey & Ku, Anthony Y., 2019. "Impacts of China's emissions trading schemes on deployment of power generation with carbon capture and storage," Energy Economics, Elsevier, vol. 81(C), pages 848-858.
  • Handle: RePEc:eee:eneeco:v:81:y:2019:i:c:p:848-858
    DOI: 10.1016/j.eneco.2019.05.014
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    Citations

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    Cited by:

    1. Mo, Jianlei & Cui, Lianbiao & Duan, Hongbo, 2021. "Quantifying the implied risk for newly-built coal plant to become stranded asset by carbon pricing," Energy Economics, Elsevier, vol. 99(C).
    2. Yang, Dongfeng & Xu, Yang & Liu, Xiaojun & Jiang, Chao & Nie, Fanjie & Ran, Zixu, 2022. "Economic-emission dispatch problem in integrated electricity and heat system considering multi-energy demand response and carbon capture Technologies," Energy, Elsevier, vol. 253(C).
    3. Rahman, Arief & Richards, Russell & Dargusch, Paul & Wadley, David, 2023. "Pathways to reduce Indonesia’s dependence on oil and achieve longer-term decarbonization," Renewable Energy, Elsevier, vol. 202(C), pages 1305-1323.
    4. Yao, Xing & Fan, Ying & Zhu, Lei & Zhang, Xian, 2020. "Optimization of dynamic incentive for the deployment of carbon dioxide removal technology: A nonlinear dynamic approach combined with real options," Energy Economics, Elsevier, vol. 86(C).
    5. Liu, Feng & Lv, Tao & Meng, Yuan & Li, Cong & Hou, Xiaoran & Xu, Jie & Deng, Xu, 2023. "Potential analysis of BESS and CCUS in the context of China's carbon trading scheme toward the low-carbon electricity system," Renewable Energy, Elsevier, vol. 210(C), pages 462-471.
    6. Paes, Carlos Eduardo & Gandelman, Dan Abensur & Firmo, Heloisa Teixeira & Bahiense, Laura, 2022. "The power generation expansion planning in Brazil: Considering the impact of greenhouse gas emissions in an Investment Decision Model," Renewable Energy, Elsevier, vol. 184(C), pages 225-238.
    7. Dinh Hoa Nguyen & Andrew Chapman & Takeshi Tsuji, 2023. "Assessing the Optimal Contributions of Renewables and Carbon Capture and Storage toward Carbon Neutrality by 2050," Sustainability, MDPI, vol. 15(18), pages 1-22, September.
    8. Feng Liu & Tao Lv & Yuan Meng & Xiaoran Hou & Jie Xu & Xu Deng, 2022. "Low-Carbon Transition Paths of Coal Power in China’s Provinces under the Context of the Carbon Trading Scheme," Sustainability, MDPI, vol. 14(15), pages 1-14, August.
    9. Shihong Zeng & Gen Li & Shaomin Wu & Zhanfeng Dong, 2022. "The Impact of Green Technology Innovation on Carbon Emissions in the Context of Carbon Neutrality in China: Evidence from Spatial Spillover and Nonlinear Effect Analysis," IJERPH, MDPI, vol. 19(2), pages 1-25, January.
    10. Yang, Bo & Wei, Yi-Ming & Liu, Lan-Cui & Hou, Yun-Bing & Zhang, Kun & Yang, Lai & Feng, Ye, 2021. "Life cycle cost assessment of biomass co-firing power plants with CO2 capture and storage considering multiple incentives," Energy Economics, Elsevier, vol. 96(C).
    11. Zhao, Tian & Liu, Zhixin, 2019. "A novel analysis of carbon capture and storage (CCS) technology adoption: An evolutionary game model between stakeholders," Energy, Elsevier, vol. 189(C).
    12. Wang, Zhaohua & Zhang, Hongzhi & Li, Hao & Wang, Bo & Cui, Qi & Zhang, Bin, 2022. "Economic impact and energy transformation of different effort-sharing schemes to pursue 2 ℃ warming limit in China," Applied Energy, Elsevier, vol. 320(C).
    13. Fan, Jing-Li & Li, Zezheng & Li, Kai & Zhang, Xian, 2022. "Modelling plant-level abatement costs and effects of incentive policies for coal-fired power generation retrofitted with CCUS," Energy Policy, Elsevier, vol. 165(C).
    14. Jin, Yi & Scherer, Laura & Sutanudjaja, Edwin H. & Tukker, Arnold & Behrens, Paul, 2022. "Climate change and CCS increase the water vulnerability of China's thermoelectric power fleet," Energy, Elsevier, vol. 245(C).
    15. Ouyang, Yiling & Guo, Jian, 2022. "Carbon capture and storage investment strategy towards the dual carbon goals," Journal of Asian Economics, Elsevier, vol. 82(C).

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