IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i9p7508-d1138903.html
   My bibliography  Save this article

Predicting the Potential of China’s Geothermal Energy in Industrial Development and Carbon Emission Reduction

Author

Listed:
  • Honglei Shi

    (Institute of Hydrogeology and Environmental Geology, Chinese Academy of Geological Sciences, Shijiazhuang 050061, China
    Technology Innovation Center of Geothermal & Hot Dry Rock Exploration and Development, Ministry of Natural Resources, Shijiazhuang 050061, China)

  • Guiling Wang

    (Institute of Hydrogeology and Environmental Geology, Chinese Academy of Geological Sciences, Shijiazhuang 050061, China
    Technology Innovation Center of Geothermal & Hot Dry Rock Exploration and Development, Ministry of Natural Resources, Shijiazhuang 050061, China)

  • Wei Zhang

    (Institute of Hydrogeology and Environmental Geology, Chinese Academy of Geological Sciences, Shijiazhuang 050061, China
    Technology Innovation Center of Geothermal & Hot Dry Rock Exploration and Development, Ministry of Natural Resources, Shijiazhuang 050061, China)

  • Feng Ma

    (Institute of Hydrogeology and Environmental Geology, Chinese Academy of Geological Sciences, Shijiazhuang 050061, China
    Technology Innovation Center of Geothermal & Hot Dry Rock Exploration and Development, Ministry of Natural Resources, Shijiazhuang 050061, China)

  • Wenjing Lin

    (Institute of Hydrogeology and Environmental Geology, Chinese Academy of Geological Sciences, Shijiazhuang 050061, China
    Technology Innovation Center of Geothermal & Hot Dry Rock Exploration and Development, Ministry of Natural Resources, Shijiazhuang 050061, China)

  • Menglei Ji

    (Institute of Hydrogeology and Environmental Geology, Chinese Academy of Geological Sciences, Shijiazhuang 050061, China
    Technology Innovation Center of Geothermal & Hot Dry Rock Exploration and Development, Ministry of Natural Resources, Shijiazhuang 050061, China)

Abstract

The goal of carbon peaking and carbon neutrality requires major systemic changes in the energy supply sector. As one of the major non-carbon-based energy sources, geothermal energy is characterized by large reserves, stability, and reliability. This paper summarizes the current situation of geothermal resource endowment and industrial development in China. Based on this, a system dynamics model of geothermal industrialization is established, and the potential of geothermal industrialization and carbon emission reduction in China is predicted. The prediction results show that the growth rate of geothermal heating and cooling areas in the next 40 years will follow a trend of acceleration followed by deceleration. China’s geothermal energy heating and cooling area will reach 11.32–14.68 billion m 2 by 2060, an increase of about 9–12 times compared to 2020. The proportion of geothermal heating and cooling area to the total building area in China will reach 13.77–17.85%. The installed capacity of geothermal power generation will reach 14,452.80–20,963.20 MW by 2060 under the scenario with electricity subsidies. The proportion of geothermal energy in China’s primary energy consumption structure will reach 3.67–5.64%. The annual carbon emission reduction potential of the geothermal industry will reach 436–632 million tons, equivalent to 4.41–6.39% of China’s carbon emissions in 2020. The results of this study can provide a reference for the healthy and high-quality development of China’s geothermal industry and help to achieve carbon peaking and carbon neutrality goals.

Suggested Citation

  • Honglei Shi & Guiling Wang & Wei Zhang & Feng Ma & Wenjing Lin & Menglei Ji, 2023. "Predicting the Potential of China’s Geothermal Energy in Industrial Development and Carbon Emission Reduction," Sustainability, MDPI, vol. 15(9), pages 1-16, May.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:9:p:7508-:d:1138903
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/9/7508/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/9/7508/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dalla Longa, Francesco & Nogueira, Larissa P. & Limberger, Jon & Wees, Jan-Diederik van & van der Zwaan, Bob, 2020. "Scenarios for geothermal energy deployment in Europe," Energy, Elsevier, vol. 206(C).
    2. Yu, Shiwei & Wei, Yi-Ming & Guo, Haixiang & Ding, Liping, 2014. "Carbon emission coefficient measurement of the coal-to-power energy chain in China," Applied Energy, Elsevier, vol. 114(C), pages 290-300.
    3. Song Han & Changqing Lin & Baosheng Zhang & Arash Farnoosh, 2019. "Projections and Recommendations for Energy Structure and Industrial Structure Development in China through 2030: A System Dynamics Model," Sustainability, MDPI, vol. 11(18), pages 1-20, September.
    4. Wang, Yuqing & Liu, Yingxin & Dou, Jinyue & Li, Mingzhu & Zeng, Ming, 2020. "Geothermal energy in China: Status, challenges, and policy recommendations," Utilities Policy, Elsevier, vol. 64(C).
    5. Zhu, Zhi-Shuang & Liao, Hua & Cao, Huai-Shu & Wang, Lu & Wei, Yi-Ming & Yan, Jinyue, 2014. "The differences of carbon intensity reduction rate across 89 countries in recent three decades," Applied Energy, Elsevier, vol. 113(C), pages 808-815.
    6. Yuanyuan He & Luxin Wan & Manli Zhang & Huijuan Zhao, 2022. "Regional Renewable Energy Installation Optimization Strategies with Renewable Portfolio Standards in China," Sustainability, MDPI, vol. 14(17), pages 1-18, August.
    7. Hongxia Sun & Yao Wan & Huirong Lv, 2020. "System Dynamics Model for the Evolutionary Behaviour of Government Enterprises and Consumers in China’s New Energy Vehicle Market," Sustainability, MDPI, vol. 12(4), pages 1-21, February.
    8. Hongliang Zhang & Jianhong E. Mu & Bruce A. McCarl & Jialing Yu, 2022. "The impact of climate change on global energy use," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 27(1), pages 1-19, January.
    9. Zhu, Jialing & Hu, Kaiyong & Lu, Xinli & Huang, Xiaoxue & Liu, Ketao & Wu, Xiujie, 2015. "A review of geothermal energy resources, development, and applications in China: Current status and prospects," Energy, Elsevier, vol. 93(P1), pages 466-483.
    10. Laimon, Mohamd & Mai, Thanh & Goh, Steven & Yusaf, Talal, 2022. "System dynamics modelling to assess the impact of renewable energy systems and energy efficiency on the performance of the energy sector," Renewable Energy, Elsevier, vol. 193(C), pages 1041-1048.
    11. Haiyang Jiang & Liangliang Guo & Fengxin Kang & Fugang Wang & Yanling Cao & Zhe Sun & Meng Shi, 2023. "Geothermal Characteristics and Productivity Potential of a Super-Thick Shallow Granite-Type Enhanced Geothermal System: A Case Study in Wendeng Geothermal Field, China," Sustainability, MDPI, vol. 15(4), pages 1-25, February.
    12. Song Han & Changqing Lin & Baosheng Zhang & Arash Farnoosh, 2019. "Projections and Recommendations for Energy Structure and Industrial Structure Development in China through 2030: A System Dynamics Model," Post-Print hal-02408957, HAL.
    13. Alsaleh, Mohd & Yang, Zhengyong & Chen, Tinggui & Wang, Xiaohui & Abdul-Rahim, Abdul Samad & Mahmood, Haider, 2023. "Moving toward environmental sustainability: Assessing the influence of geothermal power on carbon dioxide emissions," Renewable Energy, Elsevier, vol. 202(C), pages 880-893.
    14. Wu, Chenyu & Gu, Wei & Luo, Enbo & Chen, Xi & Lu, Hai & Yi, Zhongkai, 2023. "An economic cybernetic model for electricity market operation coupled with physical system dynamics," Applied Energy, Elsevier, vol. 335(C).
    Full references (including those not matched with items on IDEAS)

    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. Zhi-Fu Mi & Yi-Ming Wei & Chen-Qi He & Hua-Nan Li & Xiao-Chen Yuan & Hua Liao, 2017. "Regional efforts to mitigate climate change in China: a multi-criteria assessment approach," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 22(1), pages 45-66, January.
    2. Eising, Jan Willem & van Onna, Tom & Alkemade, Floortje, 2014. "Towards smart grids: Identifying the risks that arise from the integration of energy and transport supply chains," Applied Energy, Elsevier, vol. 123(C), pages 448-455.
    3. Yang, Ranran & Long, Ruyin & Yue, Ting & Shi, Haihong, 2014. "Calculation of embodied energy in Sino-USA trade: 1997–2011," Energy Policy, Elsevier, vol. 72(C), pages 110-119.
    4. Shu-Hong Wang & Ma-Lin Song & Tao Yu, 2019. "Hidden Carbon Emissions, Industrial Clusters, and Structure Optimization in China," Computational Economics, Springer;Society for Computational Economics, vol. 54(4), pages 1319-1342, December.
    5. Xiao, Hao & Sun, Ke-Juan & Bi, Hui-Min & Xue, Jin-Jun, 2019. "Changes in carbon intensity globally and in countries: Attribution and decomposition analysis," Applied Energy, Elsevier, vol. 235(C), pages 1492-1504.
    6. Zhao, Xueting & Wesley Burnett, J. & Lacombe, Donald J., 2015. "Province-level convergence of China’s carbon dioxide emissions," Applied Energy, Elsevier, vol. 150(C), pages 286-295.
    7. Li, Jin & Wang, Rui & Li, Haoran & Nie, Yaoyu & Song, Xinke & Li, Mingyu & Shi, Mai & Zheng, Xinzhu & Cai, Wenjia & Wang, Can, 2021. "Unit-level cost-benefit analysis for coal power plants retrofitted with biomass co-firing at a national level by combined GIS and life cycle assessment," Applied Energy, Elsevier, vol. 285(C).
    8. Qianyu Zhao & Boyu Xie & Mengyao Han, 2023. "Unpacking the Sub-Regional Spatial Network of Land-Use Carbon Emissions: The Case of Sichuan Province in China," Land, MDPI, vol. 12(10), pages 1-22, October.
    9. Guangfang Luo & Jianjun Zhang & Yongheng Rao & Xiaolei Zhu & Yiqiang Guo, 2017. "Coal Supply Chains: A Whole-Process-Based Measurement of Carbon Emissions in a Mining City of China," Energies, MDPI, vol. 10(11), pages 1-18, November.
    10. Wang, Ke & Zhang, Jianjun & Cai, Bofeng & Yu, Shengmin, 2019. "Emission factors of fugitive methane from underground coal mines in China: Estimation and uncertainty," Applied Energy, Elsevier, vol. 250(C), pages 273-282.
    11. Shaikh, Mohammad A. & Kucukvar, Murat & Onat, Nuri Cihat & Kirkil, Gokhan, 2017. "A framework for water and carbon footprint analysis of national electricity production scenarios," Energy, Elsevier, vol. 139(C), pages 406-421.
    12. Yuan, Baolong & Ren, Shenggang & Chen, Xiaohong, 2015. "The effects of urbanization, consumption ratio and consumption structure on residential indirect CO2 emissions in China: A regional comparative analysis," Applied Energy, Elsevier, vol. 140(C), pages 94-106.
    13. Chen, Jiandong & Cheng, Shulei & Song, Malin & Wu, Yinyin, 2016. "A carbon emissions reduction index: Integrating the volume and allocation of regional emissions," Applied Energy, Elsevier, vol. 184(C), pages 1154-1164.
    14. Yang, Qing & Zhang, Lei & Zou, Shaohui & Zhang, Jinsuo, 2020. "Intertemporal optimization of the coal production capacity in China in terms of uncertain demand, economy, environment, and energy security," Energy Policy, Elsevier, vol. 139(C).
    15. Yu Sang Chang & Dosoung Choi & Hann Earl Kim, 2017. "Dynamic Trends of Carbon Intensities among 127 Countries," Sustainability, MDPI, vol. 9(12), pages 1-21, December.
    16. Gong, Chengzhu & Yu, Shiwei & Zhu, Kejun & Hailu, Atakelty, 2016. "Evaluating the influence of increasing block tariffs in residential gas sector using agent-based computational economics," Energy Policy, Elsevier, vol. 92(C), pages 334-347.
    17. Chen, Jiandong & Gao, Ming & Mangla, Sachin Kumar & Song, Malin & Wen, Jie, 2020. "Effects of technological changes on China's carbon emissions," Technological Forecasting and Social Change, Elsevier, vol. 153(C).
    18. Yibo Wang & Lijuan Wang & Yang Bai & Zhuting Wang & Jie Hu & Di Hu & Yaqi Wang & Shengbiao Hu, 2021. "Assessment of Geothermal Resources in the North Jiangsu Basin, East China, Using Monte Carlo Simulation," Energies, MDPI, vol. 14(2), pages 1-17, January.
    19. Hanak, Dawid P. & Kolios, Athanasios J. & Manovic, Vasilije, 2016. "Comparison of probabilistic performance of calcium looping and chemical solvent scrubbing retrofits for CO2 capture from coal-fired power plant," Applied Energy, Elsevier, vol. 172(C), pages 323-336.
    20. Yu Hao & Shang Gao & Yunxia Guo & Zhiqiang Gai & Haitao Wu, 2021. "Measuring the nexus between economic development and environmental quality based on environmental Kuznets curve: a comparative study between China and Germany for the period of 2000–2017," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(11), pages 16848-16873, November.

    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:gam:jsusta:v:15:y:2023:i:9:p:7508-:d:1138903. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.