IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i23p7721-d1285787.html
   My bibliography  Save this article

Analyzing the Differences in the Quantitative and Spatial Characteristics of Inter-Provincial Embodied Carbon Transfers in China Induced via Various Demand Factors

Author

Listed:
  • Qinghua Li

    (School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China)

  • Cong Chen

    (School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China)

Abstract

The development of human society has led to the growing consumption of industrial products, which generates significant amounts of carbon emissions. However, relatively few in-depth studies have been conducted on the influence of different demand factors (e.g., household consumption, government consumption, export, and capital formation) on carbon emissions, which hinders the development of targeted industrial policies. To address this issue, an analytical framework based on input–output theory, the hypothesis extraction method, and complex network analysis was established to estimate the intrinsic influence of different demand factors on the embodied carbon transfer between provinces in China. The key findings can be summed up as follows: (1) The macro direction of China’s embodied carbon transfer runs from resource-rich northern provinces to industrially developed southern provinces. (2) From the perspective of different demand factors, capital formation is the most significant contributor to China’s embodied carbon transfer, with the construction industry being the most important driver. In contrast, government consumption causes the least embodied carbon transfer, but it has the highest average carbon emission intensity. (3) According to complex network theory, the carbon transfer networks via provinces and industries caused by exports are the most concentrated, with the manufacture of electrical machinery and electronic equipment serving as the main source of demand. In contrast, the carbon transfer network resulting from household consumption exhibits a high level of decentralization, with dominant sectors including electric power, gas and water production, and supply and other services. Based on these findings, this study is expected to contribute targeted suggestions with which provinces and industries can formulate demand-side carbon reduction policies for different demand factors, which will contribute to the achievement of “carbon peaking and carbon neutrality”.

Suggested Citation

  • Qinghua Li & Cong Chen, 2023. "Analyzing the Differences in the Quantitative and Spatial Characteristics of Inter-Provincial Embodied Carbon Transfers in China Induced via Various Demand Factors," Energies, MDPI, vol. 16(23), pages 1-29, November.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:23:p:7721-:d:1285787
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/23/7721/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/23/7721/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yu, Feng & Dong, Huijuan & Geng, Yong & Fang, Alex S. & Li, Haifeng, 2022. "Uncovering the differences of household carbon footprints and driving forces between China and Japan," Energy Policy, Elsevier, vol. 165(C).
    2. Duncan J. Watts & Steven H. Strogatz, 1998. "Collective dynamics of ‘small-world’ networks," Nature, Nature, vol. 393(6684), pages 440-442, June.
    3. Li, Jia Shuo & Zhou, H.W. & Meng, Jing & Yang, Q. & Chen, B. & Zhang, Y.Y., 2018. "Carbon emissions and their drivers for a typical urban economy from multiple perspectives: A case analysis for Beijing city," Applied Energy, Elsevier, vol. 226(C), pages 1076-1086.
    4. Zhifu Mi & Jiali Zheng & Jing Meng & Jiamin Ou & Klaus Hubacek & Zhu Liu & D’Maris Coffman & Nicholas Stern & Sai Liang & Yi-Ming Wei, 2020. "Economic development and converging household carbon footprints in China," Nature Sustainability, Nature, vol. 3(7), pages 529-537, July.
    5. Duarte, Rosa & Sanchez-Choliz, Julio & Bielsa, Jorge, 2002. "Water use in the Spanish economy: an input-output approach," Ecological Economics, Elsevier, vol. 43(1), pages 71-85, November.
    6. Cella, Guido, 1984. "The Input-Output Measurement of Interindustry Linkages," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 46(1), pages 73-84, February.
    7. Mi, Zhifu & Zheng, Jiali & Meng, Jing & Zheng, Heran & Li, Xian & Coffman, D'Maris & Woltjer, Johan & Wang, Shouyang & Guan, Dabo, 2019. "Carbon emissions of cities from a consumption-based perspective," Applied Energy, Elsevier, vol. 235(C), pages 509-518.
    8. Zhang, Pan & Wang, Huan, 2022. "Do provincial energy policies and energy intensity targets help reduce CO2 emissions? Evidence from China," Energy, Elsevier, vol. 245(C).
    9. Wiedmann, Thomas, 2009. "A review of recent multi-region input-output models used for consumption-based emission and resource accounting," Ecological Economics, Elsevier, vol. 69(2), pages 211-222, December.
    10. Junning Cai & Pingsun Leung, 2004. "Linkage Measures: a Revisit and a Suggested Alternative," Economic Systems Research, Taylor & Francis Journals, vol. 16(1), pages 63-83.
    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. Wang, Yuan & Wang, Wenqin & Mao, Guozhu & Cai, Hua & Zuo, Jian & Wang, Lili & Zhao, Peng, 2013. "Industrial CO2 emissions in China based on the hypothetical extraction method: Linkage analysis," Energy Policy, Elsevier, vol. 62(C), pages 1238-1244.
    2. Yu Song & Chunlu Liu & Craig Langston, 2006. "Linkage measures of the construction sector using the hypothetical extraction method," Construction Management and Economics, Taylor & Francis Journals, vol. 24(6), pages 579-589.
    3. Umed Temurshoev, 2010. "Identifying Optimal Sector Groupings With The Hypothetical Extraction Method," Journal of Regional Science, Wiley Blackwell, vol. 50(4), pages 872-890, October.
    4. Bu, Yan & Wang, Erda & Möst, Dominik & Lieberwirth, Martin, 2022. "How population migration affects carbon emissions in China: Factual and counterfactual scenario analysis," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    5. Fitsum Semere Weldegiorgis & Evelyn Dietsche & Shabbir Ahmad, 2023. "Inter-Sectoral Economic Linkages in the Mining Industries of Botswana and Tanzania: Analysis Using Partial Hypothetical Extraction Method," Resources, MDPI, vol. 12(7), pages 1-26, June.
    6. Tian, Jing & Andraded, Celio & Lumbreras, Julio & Guan, Dabo & Wang, Fangzhi & Liao, Hua, 2018. "Integrating Sustainability Into City-level CO2 Accounting: Social Consumption Pattern and Income Distribution," Ecological Economics, Elsevier, vol. 153(C), pages 1-16.
    7. Maeno, Keitaro & Tokito, Shohei & Kagawa, Shigemi, 2022. "CO2 mitigation through global supply chain restructuring," Energy Economics, Elsevier, vol. 105(C).
    8. Junning Cai & Pingsun Leung, 2004. "Linkage Measures: a Revisit and a Suggested Alternative," Economic Systems Research, Taylor & Francis Journals, vol. 16(1), pages 63-83.
    9. An, Na & Huang, Chenyu & Shen, Yanting & Wang, Jinyu & Yu, Zhongqi & Fu, Jiayan & Liu, Xiao & Yao, Jiawei, 2024. "Efficient data-driven prediction of household carbon footprint in China with limited features," Energy Policy, Elsevier, vol. 185(C).
    10. Jordan Hristov & Aleksandra Martinovska-Stojcheska & Yves Surry, 2016. "The Economic Role of Water in FYR Macedonia: An Input–Output Analysis and Implications for the Western Balkan Countries," Water Economics and Policy (WEP), World Scientific Publishing Co. Pte. Ltd., vol. 2(04), pages 1-37, December.
    11. Kash Barker & Joost R. Santos, 2010. "A Risk‐Based Approach for Identifying Key Economic and Infrastructure Systems," Risk Analysis, John Wiley & Sons, vol. 30(6), pages 962-974, June.
    12. Allan, Grant J. & Ross, Andrew G., 2019. "The characteristics of energy employment in a system-wide context," Energy Economics, Elsevier, vol. 81(C), pages 238-258.
    13. Argyrios D. Kolokontes & Achilleas Kontogeorgos & Efstratios Loizou & Fotios Chatzitheodoridis, 2020. "Decomposition Analysis for the Comparison and the Comprehension of Conventional Input-Output Impacts’ Indicators: An Empirical Paradigm," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 67(2), pages 193-217, June.
    14. Sajid, M. Jawad & Cao, Qingren & Kang, Wei, 2019. "Transport sector carbon linkages of EU's top seven emitters," Transport Policy, Elsevier, vol. 80(C), pages 24-38.
    15. Shang, Wen-Long & Ling, Yantao & Ochieng, Washington & Yang, Linchuan & Gao, Xing & Ren, Qingzhong & Chen, Yilin & Cao, Mengqiu, 2024. "Driving forces of CO2 emissions from the transport, storage and postal sectors: A pathway to achieving carbon neutrality," Applied Energy, Elsevier, vol. 365(C).
    16. Bösch, Matthias & Jochem, Dominik & Weimar, Holger & Dieter, Matthias, 2015. "Physical input-output accounting of the wood and paper flow in Germany," Resources, Conservation & Recycling, Elsevier, vol. 94(C), pages 99-109.
    17. Meng, Jing & Zhang, Zengkai & Mi, Zhifu & Anadon, Laura Diaz & Zheng, Heran & Zhang, Bo & Shan, Yuli & Guan, Dabo, 2018. "The role of intermediate trade in the change of carbon flows within China," Energy Economics, Elsevier, vol. 76(C), pages 303-312.
    18. Rehkamp, Sarah & Canning, Patrick, 2018. "Measuring Embodied Blue Water in American Diets: An EIO Supply Chain Approach," Ecological Economics, Elsevier, vol. 147(C), pages 179-188.
    19. Holz, Carsten A., 2011. "The unbalanced growth hypothesis and the role of the state: The case of China's state-owned enterprises," Journal of Development Economics, Elsevier, vol. 96(2), pages 220-238, November.
    20. Muhammad Jawad Sajid & Ernesto D. R. Santibanez Gonzalez, 2021. "The Impact of Direct and Indirect COVID-19 Related Demand Shocks on Sectoral CO 2 Emissions: Evidence from Major Asia Pacific Countries," Sustainability, MDPI, vol. 13(16), pages 1-19, August.

    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:jeners:v:16:y:2023:i:23:p:7721-:d:1285787. 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.