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The future of natural gas consumption in Beijing, Guangdong and Shanghai: An assessment utilizing MARKAL

Author

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  • Jiang, BinBin
  • Wenying, Chen
  • Yuefeng, Yu
  • Lemin, Zeng
  • Victor, David

Abstract

Natural gas could possibly become a si0gnificant portion of the future fuel mix in China. However, there is still great uncertainty surrounding the size of this potential market and therefore its impact on the global gas trade. In order to identify some of the important factors that might drive natural gas consumption in key demand areas in China, we focus on three regions: Beijing, Guangdong, and Shanghai. Using the economic optimization model MARKAL, we initially assume that the drivers are government mandates of emissions standards, reform of the Chinese financial structure, the price and available supply of natural gas, and the rate of penetration of advanced power generating and end-use. The results from the model show that the level of natural gas consumption is most sensitive to policy scenarios, which strictly limit SO2 emissions from power plants. The model also revealed that the low cost of capital for power plants in China boosts the economic viability of capital-intensive coal-fired plants. This suggests that reform within the financial sector could be a lever for encouraging increased natural gas use.

Suggested Citation

  • Jiang, BinBin & Wenying, Chen & Yuefeng, Yu & Lemin, Zeng & Victor, David, 2008. "The future of natural gas consumption in Beijing, Guangdong and Shanghai: An assessment utilizing MARKAL," Energy Policy, Elsevier, vol. 36(9), pages 3286-3299, September.
    • Handle: RePEc:eee:enepol:v:36:y:2008:i:9:p:3286-3299
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    References listed on IDEAS

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    1. P. Bauer, 2006. "Discussions," Biometrics, The International Biometric Society, vol. 62(3), pages 676-678, September.
    2. Auffhammer, Maximilian & Carson, Richard T., 2008. "Forecasting the path of China's CO2 emissions using province-level information," Journal of Environmental Economics and Management, Elsevier, vol. 55(3), pages 229-247, May.
    3. Victor,David G. & Jaffe,Amy M. & Hayes,Mark H. (ed.), 2006. "Natural Gas and Geopolitics," Cambridge Books, Cambridge University Press, number 9780521865036, Enero-Abr.
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    3. Jean Gaston Tamba & Salom Ndjakomo Essiane & Emmanuel Flavian Sapnken & Francis Djanna Koffi & Jean Luc Nsouand l & Bozidar Soldo & Donatien Njomo, 2018. "Forecasting Natural Gas: A Literature Survey," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 216-249.
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    6. Suganthi, L. & Samuel, Anand A., 2012. "Energy models for demand forecasting—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1223-1240.
    7. Soldo, Božidar, 2012. "Forecasting natural gas consumption," Applied Energy, Elsevier, vol. 92(C), pages 26-37.
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    11. Xie, Minghua & Yi, Xiangyu & Liu, Kui & Sun, Chuanwang & Kong, Qingbao, 2023. "How much natural gas does China need: An empirical study from the perspective of energy transition," Energy, Elsevier, vol. 266(C).
    12. Qiaochu Li & Peng Zhang, 2025. "Study of the Safety–Economy–Environmental Protection Coordination of Beijing’s Natural Gas Industry Based on a Coupling Coordination Degree Model," Sustainability, MDPI, vol. 17(6), pages 1-25, March.
    13. Yong Zeng & Yanpeng Cai & Guohe Huang & Jing Dai, 2011. "A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty," Energies, MDPI, vol. 4(10), pages 1-33, October.
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