IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i18p13520-d1236577.html
   My bibliography  Save this article

Research on the Spatial Pattern of Carbon Emissions and Differentiated Peak Paths at the County Level in Shandong Province, China

Author

Listed:
  • Xinyu Han

    (School of Architecture and Urban Planning, Shandong Jianzhu University, Jinan 250101, China
    Yellow River Institution, Shandong Jianzhu University, Jinan 250101, China)

  • Peng Qu

    (Shandong Urban and Rural Planning Design Institute Co., Ltd., Jinan 250013, China)

  • Jiaqi Wu

    (School of Architecture, Tsinghua University, Beijing 100084, China)

  • Beile Su

    (School of Art, Shandong Jianzhu University, Jinan 250101, China)

  • Ning Qiu

    (School of Architecture and Urban Planning, Shandong Jianzhu University, Jinan 250101, China
    Yellow River Institution, Shandong Jianzhu University, Jinan 250101, China)

  • Lili Zhang

    (School of Art, Shandong Jianzhu University, Jinan 250101, China)

Abstract

In the pursuit of China’s carbon peak and carbon neutrality objectives, county-level areas assume a pivotal role in orchestrating diverse initiatives for low-carbon development. However, empirical evidence is limited. This paper aims to fill this gap by exploring the driving factors of carbon peak and carbon peak path at the county level, using Shandong Province as a case study. Employing data related to economic development, industrial structure, land utilization, energy consumption, and emission characteristics, a principal component analysis (PCA) was utilized to extract the following five driving factors of carbon peak: green transformation, urbanization, industrial construction, energy consumption, and environmental constraints. Subsequently, K-means clustering identified five cluster areas: (1) agricultural transformation pending area, (2) low-carbon lagging area, (3) industrial transformation area, (4) low-carbon potential areas, and (5) low-carbon demonstration area. Based on these areas, this study further elucidates spatial combination models of carbon peak within the urban system, spanning central cities, coastal cities, resource-based cities, and agricultural cities. The paper enhances comprehension of the integral role county-level areas play in achieving China’s carbon reduction objectives. By providing nuanced insights into diverse developmental trajectories and spatial interactions, the study contributes to effective low-carbon strategy formulation. The findings underscore the importance of considering specific county attributes in urban areas to devise precise optimization strategies and trajectories, ultimately facilitating the realization of carbon peak goals.

Suggested Citation

  • Xinyu Han & Peng Qu & Jiaqi Wu & Beile Su & Ning Qiu & Lili Zhang, 2023. "Research on the Spatial Pattern of Carbon Emissions and Differentiated Peak Paths at the County Level in Shandong Province, China," Sustainability, MDPI, vol. 15(18), pages 1-18, September.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:18:p:13520-:d:1236577
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/18/13520/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/18/13520/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xin Yang & Yifei Sima & Yabo Lv & Mingwei Li, 2023. "Research on Influencing Factors of Residential Building Carbon Emissions and Carbon Peak: A Case of Henan Province in China," Sustainability, MDPI, vol. 15(13), pages 1-18, June.
    2. Park, Se-Hark, 1992. "Decomposition of industrial energy consumption : An alternative method," Energy Economics, Elsevier, vol. 14(4), pages 265-270, October.
    3. Chen, Huanyu & Yi, Jizheng & Chen, Aibin & Peng, Duanxiang & Yang, Jieqiong, 2023. "Green technology innovation and CO2 emission in China: Evidence from a spatial-temporal analysis and a nonlinear spatial durbin model," Energy Policy, Elsevier, vol. 172(C).
    4. Kennedy, Christopher & Steinberger, Julia & Gasson, Barrie & Hansen, Yvonne & Hillman, Timothy & Havránek, Miroslav & Pataki, Diane & Phdungsilp, Aumnad & Ramaswami, Anu & Mendez, Gara Villalba, 2010. "Methodology for inventorying greenhouse gas emissions from global cities," Energy Policy, Elsevier, vol. 38(9), pages 4828-4837, September.
    5. Xu, Chong, 2023. "Towards balanced low-carbon development: Driver and complex network of urban-rural energy-carbon performance gap in China," Applied Energy, Elsevier, vol. 333(C).
    6. Kais, Saidi & Sami, Hammami, 2016. "An econometric study of the impact of economic growth and energy use on carbon emissions: Panel data evidence from fifty eight countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1101-1110.
    7. Cemal Atici, 2009. "Carbon emissions in Central and Eastern Europe: environmental Kuznets curve and implications for sustainable development," Sustainable Development, John Wiley & Sons, Ltd., vol. 17(3), pages 155-160.
    8. Philippe Aghion & Patrick Bolton, 1997. "A Theory of Trickle-Down Growth and Development," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(2), pages 151-172.
    9. Wu, Rongxin & Tan, Zhizhou & Lin, Boqiang, 2023. "Does carbon emission trading scheme really improve the CO2 emission efficiency? Evidence from China's iron and steel industry," Energy, Elsevier, vol. 277(C).
    10. Zhu Liu & Dabo Guan & Wei Wei & Steven J. Davis & Philippe Ciais & Jin Bai & Shushi Peng & Qiang Zhang & Klaus Hubacek & Gregg Marland & Robert J. Andres & Douglas Crawford-Brown & Jintai Lin & Hongya, 2015. "Reduced carbon emission estimates from fossil fuel combustion and cement production in China," Nature, Nature, vol. 524(7565), pages 335-338, August.
    11. Du, Limin & Wei, Chu & Cai, Shenghua, 2012. "Economic development and carbon dioxide emissions in China: Provincial panel data analysis," China Economic Review, Elsevier, vol. 23(2), pages 371-384.
    12. Boyd, Gale A. & Hanson, Donald A. & Sterner, Thomas, 1988. "Decomposition of changes in energy intensity : A comparison of the Divisia index and other methods," Energy Economics, Elsevier, vol. 10(4), pages 309-312, October.
    13. Susie Moloney & Ralph Horne, 2015. "Low Carbon Urban Transitioning: From Local Experimentation to Urban Transformation?," Sustainability, MDPI, vol. 7(3), pages 1-17, February.
    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. Juan Tan & Jinyu Wei, 2024. "Balancing Growth and Sustainability: a Regional Analysis of Industrial Carbon Efficiency in China," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 13946-13978, September.
    2. Ding, Dan & Liu, Xiaoping & Xu, Xiaocong, 2024. "Projecting the future fine-resolution carbon dioxide emissions under the shared socioeconomic pathways for carbon peak evaluation," Applied Energy, Elsevier, vol. 365(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. Chontanawat, Jaruwan & Wiboonchutikula, Paitoon & Buddhivanich, Atinat, 2014. "Decomposition analysis of the change of energy intensity of manufacturing industries in Thailand," Energy, Elsevier, vol. 77(C), pages 171-182.
    2. Andreoni, V. & Galmarini, S., 2012. "Decoupling economic growth from carbon dioxide emissions: A decomposition analysis of Italian energy consumption," Energy, Elsevier, vol. 44(1), pages 682-691.
    3. Xing Zhou & Meihua Zhou & Ming Zhang, 2016. "Contrastive analyses of the influence factors of interprovincial carbon emission induced by industry energy in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(3), pages 1405-1433, April.
    4. Ang, B. W., 2004. "Decomposition analysis for policymaking in energy:: which is the preferred method?," Energy Policy, Elsevier, vol. 32(9), pages 1131-1139, June.
    5. Sun, J. W., 1998. "Changes in energy consumption and energy intensity: A complete decomposition model," Energy Economics, Elsevier, vol. 20(1), pages 85-100, February.
    6. Fernández González, P. & Landajo, M. & Presno, M.J., 2014. "Tracking European Union CO2 emissions through LMDI (logarithmic-mean Divisia index) decomposition. The activity revaluation approach," Energy, Elsevier, vol. 73(C), pages 741-750.
    7. Sudhakara Reddy, B. & Kumar Ray, Binay, 2011. "Understanding industrial energy use: Physical energy intensity changes in Indian manufacturing sector," Energy Policy, Elsevier, vol. 39(11), pages 7234-7243.
    8. Jeong, Kyonghwa & Kim, Suyi, 2013. "LMDI decomposition analysis of greenhouse gas emissions in the Korean manufacturing sector," Energy Policy, Elsevier, vol. 62(C), pages 1245-1253.
    9. Muhammad Shahbaz & Avik Sinha, 2019. "Environmental Kuznets curve for CO2emissions: a literature survey," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 46(1), pages 106-168, January.
    10. Tiba, Sofien & Omri, Anis, 2017. "Literature survey on the relationships between energy, environment and economic growth," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 1129-1146.
    11. Wenxiang Peng & Yutao Lei & Xuan Zhang, 2023. "Analysis of China’s High-Carbon Manufacturing Industry’s Carbon Emissions in the Digital Process," Sustainability, MDPI, vol. 15(20), pages 1-35, October.
    12. Lingyun He & Fang Yin & Zhangqi Zhong & Zhihua Ding, 2017. "The impact of local government investment on the carbon emissions reduction effect: An empirical analysis of panel data from 30 provinces and municipalities in China," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-20, July.
    13. Binay Kumar Ray & B. Sudhakara Reddy, 2007. "Decomposition of energy consumption and energy intensity in Indian manufacturing industries," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2007-020, Indira Gandhi Institute of Development Research, Mumbai, India.
    14. Zhang, Zhong Xiang, 2001. "Why has the energy intensity fallen in China's industrial sector in the 1990s? : the relative importance of structural change and intensity change," CCSO Working Papers 200105, University of Groningen, CCSO Centre for Economic Research.
    15. Sofien, Tiba & Omri, Anis, 2016. "Literature survey on the relationships between energy variables, environment and economic growth," MPRA Paper 82555, University Library of Munich, Germany, revised 14 Sep 2016.
    16. Burke, Paul J. & Liao, Hua, 2015. "Is the price elasticity of demand for coal in China increasing?," China Economic Review, Elsevier, vol. 36(C), pages 309-322.
    17. Lingming Chen & Congjia Huo, 2021. "Impact of Green Innovation Efficiency on Carbon Emission Reduction in the Guangdong-Hong Kong-Macao GBA," Sustainability, MDPI, vol. 13(23), pages 1-22, December.
    18. Jiang, Jingjing & Ye, Bin & Liu, Junguo, 2019. "Research on the peak of CO2 emissions in the developing world: Current progress and future prospect," Applied Energy, Elsevier, vol. 235(C), pages 186-203.
    19. Duan, Cuncun & Chen, Bin & Feng, Kuishuang & Liu, Zhu & Hayat, Tasawar & Alsaedi, Ahmed & Ahmad, Bashir, 2018. "Interregional carbon flows of China," Applied Energy, Elsevier, vol. 227(C), pages 342-352.
    20. Zhang, F. Q. & Ang, B. W., 2001. "Methodological issues in cross-country/region decomposition of energy and environment indicators," Energy Economics, Elsevier, vol. 23(2), pages 179-190, March.

    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:18:p:13520-:d:1236577. 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.