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Dynamic optimization of carbon capture technology deployment targeting carbon neutrality, cost efficiency and water stress: Evidence from China's electric power sector

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  • Yang, Lin
  • Lv, Haodong
  • Wei, Ning
  • Li, Yiming
  • Zhang, Xian

Abstract

The potential of carbon capture, utilization and storage (CCUS) has been widely discussed worldwide, while the dynamic changing process, lock-in risk and water resource constraints towards carbon neutrality target are not fully considered in the previous studies. This study developed a comprehensive approach to optimize carbon mitigation potential, total capital expenditure and water resource stress for China's coal-fired power plants (CFPPs) with CCUS retrofitting in a dynamic environment. We found that the annual capture scale will start to increase significantly until 2030 and reach 2.4 billion tons CO2 in 2050. The newly-added capture scale of first-generation technology will decline gradually after 2030 due to the breakthrough in second-generation technology. Inner Mongolia, Jiangsu and Guangdong have the greatest potential for implementing CCUS projects, and the least in Hainan, Sichuan and Qinghai. The annual capture cost roughly presents an "inverted U" shape with the peaking (14.70 billion CNY) occurring in 2035, while the annual R&D investment can be observed a moderate "N" shape with the peaking (11.24 billion CNY) occurring in 2030. The annual non-corporate expenditures (subsidy) will picture a significant "inverted U" type trend, peaking at 63.71 billion CNY in 2044 as a result of the risk factors such as CCUS facility investment and additional storage cost caused by uncertain geological conditions. In addition, the annual water withdrawal and consumption of capture process will increase from 0.09 and 0.06 billion m3 respectively in 2021 to 9.12 and 6.22 billion m3 respectively in 2050, while CO2-EWR (Enhanced water recovery) process will make CCUS technology supply extra water resource since 2035, reaching 27.05 billion m3 in 2050. Meanwhile, in terms of first- and second-generation capture technology, the unit water withdrawal will drop 35.04% and 36.71%, respectively, while the unit water consumption will drop 66.89% and 74.12%, respectively during 2021–2050. Overall, although CCUS will not intensify water resource stress in the future, the appropriate relaxation ratio of water quota is essential at the initial stage.

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  • Yang, Lin & Lv, Haodong & Wei, Ning & Li, Yiming & Zhang, Xian, 2023. "Dynamic optimization of carbon capture technology deployment targeting carbon neutrality, cost efficiency and water stress: Evidence from China's electric power sector," Energy Economics, Elsevier, vol. 125(C).
  • Handle: RePEc:eee:eneeco:v:125:y:2023:i:c:s0140988323003699
    DOI: 10.1016/j.eneco.2023.106871
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    as
    1. Holz, Franziska & Scherwath, Tim & Crespo del Granado, Pedro & Skar, Christian & Olmos, Luis & Ploussard, Quentin & Ramos, Andrés & Herbst, Andrea, 2021. "A 2050 perspective on the role for carbon capture and storage in the European power system and industry sector," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 104, pages 1-18.
    2. Yang, Lin & Xu, Mao & Fan, Jingli & Liang, Xi & Zhang, Xian & Lv, Haodong & Wang, Dong, 2021. "Financing coal-fired power plant to demonstrate CCS (carbon capture and storage) through an innovative policy incentive in China," Energy Policy, Elsevier, vol. 158(C).
    3. Zhang, Xian & Wang, Xingwei & Chen, Jiajun & Xie, Xi & Wang, Ke & Wei, Yiming, 2014. "A novel modeling based real option approach for CCS investment evaluation under multiple uncertainties," Applied Energy, Elsevier, vol. 113(C), pages 1059-1067.
    4. Rubin, Edward S. & Yeh, Sonia & Antes, Matt & Berkenpas, Michael & Davison, John, 2007. "Use of experience curves to estimate the future cost of power plants with CO2 capture," Institute of Transportation Studies, Working Paper Series qt46x6h0n0, Institute of Transportation Studies, UC Davis.
    5. Reyer Gerlagh & Bob van der Zwaan, 2006. "Options and Instruments for a Deep Cut in CO2 Emissions: Carbon Dioxide Capture or Renewables, Taxes or Subsidies?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 25-48.
    6. Margaret Insley, 2003. "On the option to invest in pollution control under a regime of tradable emissions allowances," Canadian Journal of Economics, Canadian Economics Association, vol. 36(4), pages 860-883, November.
    7. Smriti Mallapaty, 2020. "How China could be carbon neutral by mid-century," Nature, Nature, vol. 586(7830), pages 482-483, October.
    8. Laurikka, Harri & Koljonen, Tiina, 2006. "Emissions trading and investment decisions in the power sector--a case study in Finland," Energy Policy, Elsevier, vol. 34(9), pages 1063-1074, June.
    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 qt96z5s545, Institute of Transportation Studies, UC Davis.
    10. Li, Sheng & Zhang, Xiaosong & Gao, Lin & Jin, Hongguang, 2012. "Learning rates and future cost curves for fossil fuel energy systems with CO2 capture: Methodology and case studies," Applied Energy, Elsevier, vol. 93(C), pages 348-356.
    11. Lorenzo Rosa & Jeffrey A. Reimer & Marjorie S. Went & Paolo D’Odorico, 2020. "Hydrological limits to carbon capture and storage," Nature Sustainability, Nature, vol. 3(8), pages 658-666, August.
    12. Grimaud, André & Lafforgue, Gilles & Magné, Bertrand, 2011. "Climate change mitigation options and directed technical change: A decentralized equilibrium analysis," Resource and Energy Economics, Elsevier, vol. 33(4), pages 938-962.
    13. Fan, Jing-Li & Xu, Mao & Li, Fengyu & Yang, Lin & Zhang, Xian, 2018. "Carbon capture and storage (CCS) retrofit potential of coal-fired power plants in China: The technology lock-in and cost optimization perspective," Applied Energy, Elsevier, vol. 229(C), pages 326-334.
    14. Avinash K. Dixit & Robert S. Pindyck, 1994. "Investment under Uncertainty," Economics Books, Princeton University Press, edition 1, number 5474.
    15. Amigues, Jean-Pierre & Lafforgue, Gilles & Moreaux, Michel, 2016. "Optimal timing of carbon capture policies under learning-by-doing," Journal of Environmental Economics and Management, Elsevier, vol. 78(C), pages 20-37.
    16. Rosa, Lorenzo & Sanchez, Daniel L. & Realmonte, Giulia & Baldocchi, Dennis & D'Odorico, Paolo, 2021. "The water footprint of carbon capture and storage technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    17. Duan, Hong-Bo & Fan, Ying & Zhu, Lei, 2013. "What’s the most cost-effective policy of CO2 targeted reduction: An application of aggregated economic technological model with CCS?," Applied Energy, Elsevier, vol. 112(C), pages 866-875.
    18. Renner, Marie, 2014. "Carbon prices and CCS investment: A comparative study between the European Union and China," Energy Policy, Elsevier, vol. 75(C), pages 327-340.
    19. 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.
    20. McDonald, Alan & Schrattenholzer, Leo, 2001. "Learning rates for energy technologies," Energy Policy, Elsevier, vol. 29(4), pages 255-261, March.
    21. Jong-Hyun Kim & Yong-Gil Lee, 2018. "Learning Curve, Change in Industrial Environment, and Dynamics of Production Activities in Unconventional Energy Resources," Sustainability, MDPI, vol. 10(9), pages 1-11, September.
    22. Marie Renner, 2014. "Carbon prices and CCS investment: comparative study between the European Union and China," Working Papers 1402, Chaire Economie du climat.
    23. Yang, Lin & Xu, Mao & Yang, Yuantao & Fan, Jingli & Zhang, Xian, 2019. "Comparison of subsidy schemes for carbon capture utilization and storage (CCUS) investment based on real option approach: Evidence from China," Applied Energy, Elsevier, vol. 255(C).
    24. Riahi, Keywan & Rubin, Edward S. & Taylor, Margaret R. & Schrattenholzer, Leo & Hounshell, David, 2004. "Technological learning for carbon capture and sequestration technologies," Energy Economics, Elsevier, vol. 26(4), pages 539-564, July.
    25. Lohwasser, Richard & Madlener, Reinhard, 2013. "Relating R&D and investment policies to CCS market diffusion through two-factor learning," Energy Policy, Elsevier, vol. 52(C), pages 439-452.
    26. Fukui, Rokuhei & Greenfield, Carl & Pogue, Katie & van der Zwaan, Bob, 2017. "Experience curve for natural gas production by hydraulic fracturing," Energy Policy, Elsevier, vol. 105(C), pages 263-268.
    27. 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).
    28. Turner, Karen & Race, Julia & Alabi, Oluwafisayo & Katris, Antonios & Swales, J. Kim, 2021. "Policy options for funding carbon capture in regional industrial clusters: What are the impacts and trade-offs involved in compensating industry competitiveness loss?," Ecological Economics, Elsevier, vol. 184(C).
    29. 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.
    30. Rubin, Edward S. & Azevedo, Inês M.L. & Jaramillo, Paulina & Yeh, Sonia, 2015. "A review of learning rates for electricity supply technologies," Energy Policy, Elsevier, vol. 86(C), pages 198-218.
    31. Boomsma, Trine Krogh & Meade, Nigel & Fleten, Stein-Erik, 2012. "Renewable energy investments under different support schemes: A real options approach," European Journal of Operational Research, Elsevier, vol. 220(1), pages 225-237.
    32. 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.
    33. Abadie, Luis M. & Chamorro, José M., 2008. "European CO2 prices and carbon capture investments," Energy Economics, Elsevier, vol. 30(6), pages 2992-3015, November.
    34. Nakata, Toshihiko & Sato, Takemi & Wang, Hao & Kusunoki, Tomoya & Furubayashi, Takaaki, 2011. "Modeling technological learning and its application for clean coal technologies in Japan," Applied Energy, Elsevier, vol. 88(1), pages 330-336, January.
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