IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v36y2008i9p3286-3299.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301-4215(08)00218-8
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Taseska, Verica & Markovska, Natasa & Callaway, John M., 2012. "Evaluation of climate change impacts on energy demand," Energy, Elsevier, vol. 48(1), pages 88-95.
    2. 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.
    3. Li, Junchen & Dong, Xiucheng & Shangguan, Jianxin & Hook, Mikael, 2011. "Forecasting the growth of China’s natural gas consumption," Energy, Elsevier, vol. 36(3), pages 1380-1385.
    4. 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.
    5. Adom, Philip Kofi & Bekoe, William, 2012. "Conditional dynamic forecast of electrical energy consumption requirements in Ghana by 2020: A comparison of ARDL and PAM," Energy, Elsevier, vol. 44(1), pages 367-380.
    6. Wu, Qunli & Peng, Chenyang, 2017. "A hybrid BAG-SA optimal approach to estimate energy demand of China," Energy, Elsevier, vol. 120(C), pages 985-995.
    7. Sen, Doruk & Günay, M. Erdem & Tunç, K.M. Murat, 2019. "Forecasting annual natural gas consumption using socio-economic indicators for making future policies," Energy, Elsevier, vol. 173(C), pages 1106-1118.
    8. Tsai, Miao-Shan & Chang, Ssu-Li, 2015. "Taiwan’s 2050 low carbon development roadmap: An evaluation with the MARKAL model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 178-191.
    9. Li, Wei & Lu, Can, 2019. "The multiple effectiveness of state natural gas consumption constraint policies for achieving sustainable development targets in China," Applied Energy, Elsevier, vol. 235(C), pages 685-698.
    10. 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.
    11. Ziwei Yan & Chunying Cui, 2022. "How Natural Gas Infrastructure Affects Carbon Emission Indicators in Guangdong Province?," Sustainability, MDPI, vol. 14(13), pages 1-26, July.
    12. Soldo, Božidar, 2012. "Forecasting natural gas consumption," Applied Energy, Elsevier, vol. 92(C), pages 26-37.
    13. Gonzales Palomino, Raul & Nebra, Silvia A., 2012. "The potential of natural gas use including cogeneration in large-sized industry and commercial sector in Peru," Energy Policy, Elsevier, vol. 50(C), pages 192-206.
    14. Arora, Vipin & Cai, Yiyong & Jones, Ayaka, 2016. "The national and international impacts of coal-to-gas switching in the Chinese power sector," Energy Economics, Elsevier, vol. 60(C), pages 416-426.
    15. Darda, Md Abud & Guseo, Renato & Mortarino, Cinzia, 2015. "Nonlinear production path and an alternative reserves estimate for South Asian natural gas," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 654-664.
    16. 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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fujii, Hidemichi & Managi, Shunsuke, 2013. "Which industry is greener? An empirical study of nine industries in OECD countries," Energy Policy, Elsevier, vol. 57(C), pages 381-388.
    2. Zhao, Xiaoli & Li, Shujie & Zhang, Sufang & Yang, Rui & Liu, Suwei, 2016. "The effectiveness of China's wind power policy: An empirical analysis," Energy Policy, Elsevier, vol. 95(C), pages 269-279.
    3. Ling Xiong & Shaozhou Qi, 2018. "Financial Development And Carbon Emissions In Chinese Provinces: A Spatial Panel Data Analysis," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 63(02), pages 447-464, March.
    4. Du, Limin & Hanley, Aoife & Wei, Chu, 2015. "Estimating the Marginal Abatement Cost Curve of CO2 Emissions in China: Provincial Panel Data Analysis," Energy Economics, Elsevier, vol. 48(C), pages 217-229.
    5. Zheng, Jiali & Mi, Zhifu & Coffman, D'Maris & Milcheva, Stanimira & Shan, Yuli & Guan, Dabo & Wang, Shouyang, 2019. "Regional development and carbon emissions in China," Energy Economics, Elsevier, vol. 81(C), pages 25-36.
    6. Zhang, Lin, 2017. "Correcting the uneven burden sharing of emission reduction across provinces in China," Energy Economics, Elsevier, vol. 64(C), pages 335-345.
    7. Yu, Wei & Pagani, Roberto & Huang, Lei, 2012. "CO2 emission inventories for Chinese cities in highly urbanized areas compared with European cities," Energy Policy, Elsevier, vol. 47(C), pages 298-308.
    8. Richard T. Carson, 2010. "The Environmental Kuznets Curve: Seeking Empirical Regularity and Theoretical Structure," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 4(1), pages 3-23, Winter.
    9. Jayanthakumaran, Kankesu & Verma, Reetu & Liu, Ying, 2012. "CO2 emissions, energy consumption, trade and income: A comparative analysis of China and India," Energy Policy, Elsevier, vol. 42(C), pages 450-460.
    10. QIN, Bo & WU, Jianfeng, 2015. "Does urban concentration mitigate CO2 emissions? Evidence from China 1998–2008," China Economic Review, Elsevier, vol. 35(C), pages 220-231.
    11. Newbold, Stephen C. & Johnston, Robert J., 2020. "Valuing non-market valuation studies using meta-analysis: A demonstration using estimates of willingness-to-pay for water quality improvements," Journal of Environmental Economics and Management, Elsevier, vol. 104(C).
    12. Shao, Shuai & Yang, Lili & Yu, Mingbo & Yu, Mingliang, 2011. "Estimation, characteristics, and determinants of energy-related industrial CO2 emissions in Shanghai (China), 1994-2009," Energy Policy, Elsevier, vol. 39(10), pages 6476-6494, October.
    13. Doupe, Patrick, 2014. "The costs of error in setting reference rates for reduced deforestation," Working Papers 249497, Australian National University, Centre for Climate Economics & Policy.
    14. Xueqin Lin & Xiao Zhou & Pengfei Wang, 2023. "Spatial differentiation and influencing factors of industrial resource and environmental pressures in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(9), pages 9991-10015, September.
    15. Buck, Steven & Soldati, Hilary & Sunding, David L., 2015. "Forecasting Urban Water Demand in California: Rethinking Model Evaluation," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205737, Agricultural and Applied Economics Association.
    16. Zheng, Siqi & Kahn, Matthew E. & Liu, Hongyu, 2010. "Towards a system of open cities in China: Home prices, FDI flows and air quality in 35 major cities," Regional Science and Urban Economics, Elsevier, vol. 40(1), pages 1-10, January.
    17. He, Jie & Richard, Patrick, 2010. "Environmental Kuznets curve for CO2 in Canada," Ecological Economics, Elsevier, vol. 69(5), pages 1083-1093, March.
    18. Luo, Xiaohu & Caron, Justin & Karplus, Valerie J. & Zhang, Da & Zhang, Xiliang, 2016. "Interprovincial migration and the stringency of energy policy in China," Energy Economics, Elsevier, vol. 58(C), pages 164-173.
    19. Tian, Lixin & Jin, Rulei, 2012. "Theoretical exploration of carbon emissions dynamic evolutionary system and evolutionary scenario analysis," Energy, Elsevier, vol. 40(1), pages 376-386.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:enepol:v:36:y:2008:i:9:p:3286-3299. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/enpol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.