IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i7p5922-d1110475.html

Dynamic Scenario Predictions of Peak Carbon Emissions in China’s Construction Industry

Author

Listed:
  • Xilian Wang

    (Energy Economics and Management Research Centre, College of Management, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Lihang Qu

    (Energy Economics and Management Research Centre, College of Management, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Yueying Wang

    (School of Foreign Languages, Northwest University, Xi’an 710127, China)

  • Helin Xie

    (School of Civil Engineering, Sun Yat-sen University, Zhuhai 519082, China)

Abstract

As the largest carbon emitter in the world, China aims to reach its peak carbon emissions goal by the year 2030, while the construction industry makes a significant contribution to carbon emissions, directly affecting the country’s commitment to meet its target. The present paper investigates the dynamic characteristics of carbon emissions released by China’s construction industry under single- and multiple-scenario settings with altering economic growth rates, optimizing energy structures, adjusting industrial structures, and modifying carbon emission policy factors. The research results show that the total carbon emissions generally present a steady increase from the year 2000 and will reach 12,880.40 million tons (MT) by 2030 under a scenario without any intervention. Indirect carbon emissions released from associated industries account for over 96% of the total carbon emissions, while direct carbon emissions make a minor contribution to the total. Single and comprehensive scenarios have positive effects on reducing emissions; it was also observed that only under energy structure scenario III and comprehensive scenario III could carbon emissions released from the construction sector reach a peak value by 2030. The effects of emissions reductions as a result of single policies can be presented in the following order: energy structure, economic growth, carbon emissions policy factor, and industrial structure. All of the emissions reduction effects of multiple scenarios are superior to the single scenarios. The research results provide a basis and guidance for policymakers to adopt the correct steps to fulfill China’s aim of achieving peak carbon emissions by the projected date.

Suggested Citation

  • Xilian Wang & Lihang Qu & Yueying Wang & Helin Xie, 2023. "Dynamic Scenario Predictions of Peak Carbon Emissions in China’s Construction Industry," Sustainability, MDPI, vol. 15(7), pages 1-19, March.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:7:p:5922-:d:1110475
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/7/5922/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/7/5922/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shao, Shuai & Liu, Jianghua & Geng, Yong & Miao, Zhuang & Yang, Yingchun, 2016. "Uncovering driving factors of carbon emissions from China’s mining sector," Applied Energy, Elsevier, vol. 166(C), pages 220-238.
    2. Shuai, Chenyang & Shen, Liyin & Jiao, Liudan & Wu, Ya & Tan, Yongtao, 2017. "Identifying key impact factors on carbon emission: Evidences from panel and time-series data of 125 countries from 1990 to 2011," Applied Energy, Elsevier, vol. 187(C), pages 310-325.
    3. Rongrong Li & Rui Jiang, 2017. "Moving Low-Carbon Construction Industry in Jiangsu Province: Evidence from Decomposition and Decoupling Models," Sustainability, MDPI, vol. 9(6), pages 1-14, June.
    4. Zhang, Jingxiao & Jin, Weixing & Yang, Guo-liang & Li, Hui & Ke, Yongjian & Philbin, Simon Patrick, 2021. "Optimizing regional allocation of CO2 emissions considering output under overall efficiency," Socio-Economic Planning Sciences, Elsevier, vol. 77(C).
    5. Wang, Ke & Yang, Kexin & Wei, Yi-Ming & Zhang, Chi, 2018. "Shadow prices of direct and overall carbon emissions in China’s construction industry: A parametric directional distance function-based sensitive estimation," Structural Change and Economic Dynamics, Elsevier, vol. 47(C), pages 180-193.
    6. Cheng, Yung-Hsiang & Chang, Yu-Hern & Lu, I.J., 2015. "Urban transportation energy and carbon dioxide emission reduction strategies," Applied Energy, Elsevier, vol. 157(C), pages 953-973.
    7. Li, Wei & Gao, Shubin, 2018. "Prospective on energy related carbon emissions peak integrating optimized intelligent algorithm with dry process technique application for China's cement industry," Energy, Elsevier, vol. 165(PB), pages 33-54.
    8. Hoekstra, Rutger & van den Bergh, Jeroen C. J. M., 2003. "Comparing structural decomposition analysis and index," Energy Economics, Elsevier, vol. 25(1), pages 39-64, January.
    9. Ke Wang & Kexin Yang & Yi-Ming Wei & Chi Zhang, 2018. "Shadow prices of direct and overall carbon emissions in China¡¯s construction industry: a parametric directional distance function-based sensitive estimation," CEEP-BIT Working Papers 120, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    10. Wang, H. & Zhou, P. & Xie, Bai-Chen & Zhang, N., 2019. "Assessing drivers of CO2 emissions in China's electricity sector: A metafrontier production-theoretical decomposition analysis," European Journal of Operational Research, Elsevier, vol. 275(3), pages 1096-1107.
    11. Wu, Lifeng & Liu, Sifeng & Liu, Dinglin & Fang, Zhigeng & Xu, Haiyan, 2015. "Modelling and forecasting CO2 emissions in the BRICS (Brazil, Russia, India, China, and South Africa) countries using a novel multi-variable grey model," Energy, Elsevier, vol. 79(C), pages 489-495.
    12. Cansino, José M. & Román, Rocío & Ordóñez, Manuel, 2016. "Main drivers of changes in CO2 emissions in the Spanish economy: A structural decomposition analysis," Energy Policy, Elsevier, vol. 89(C), pages 150-159.
    13. Qiang Du & Xinran Lu & Yi Li & Min Wu & Libiao Bai & Ming Yu, 2018. "Carbon Emissions in China’s Construction Industry: Calculations, Factors and Regions," IJERPH, MDPI, vol. 15(6), pages 1-17, June.
    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. Tiejun Dai & Jiaxin Wang, 2025. "Dynamic Simulation for Carbon Emissions of the Entire Building Industry Chain Based on System Dynamics," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 15(2), pages 1-10.
    2. Abdul Mateen Khan & Muhammad Abubakar Tariq & Sardar Kashif Ur Rehman & Talha Saeed & Fahad K. Alqahtani & Mohamed Sherif, 2024. "BIM Integration with XAI Using LIME and MOO for Automated Green Building Energy Performance Analysis," Energies, MDPI, vol. 17(13), pages 1-36, July.

    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. Li, Dezhi & Huang, Guanying & Zhu, Shiyao & Chen, Long & Wang, Jiangbo, 2021. "How to peak carbon emissions of provincial construction industry? Scenario analysis of Jiangsu Province," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    2. Liang, Wei & Gan, Ting & Zhang, Wei, 2019. "Dynamic evolution of characteristics and decomposition of factors influencing industrial carbon dioxide emissions in China: 1991–2015," Structural Change and Economic Dynamics, Elsevier, vol. 49(C), pages 93-106.
    3. Onat, Nuri Cihat & Kucukvar, Murat, 2020. "Carbon footprint of construction industry: A global review and supply chain analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    4. Yuhuan Zhao & Hao Li & Zhonghua Zhang & Yongfeng Zhang & Song Wang & Ya Liu, 2017. "Decomposition and scenario analysis of CO2 emissions in China’s power industry: based on LMDI method," 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. 86(2), pages 645-668, March.
    5. Chen, Zhenling & Zhang, Xiaoling & Ni, Guohua, 2020. "Decomposing capacity utilization under carbon dioxide emissions reduction constraints in data envelopment analysis: An application to Chinese regions," Energy Policy, Elsevier, vol. 139(C).
    6. Zbigniew Gołaś, 2022. "Changes in Energy-Related Carbon Dioxide Emissions of the Agricultural Sector in Poland from 2000 to 2019," Energies, MDPI, vol. 15(12), pages 1-18, June.
    7. Bo Yang & Minhaj Ali & Shujahat Haider Hashmi & Mohsin Shabir, 2020. "Income Inequality and CO 2 Emissions in Developing Countries: The Moderating Role of Financial Instability," Sustainability, MDPI, vol. 12(17), pages 1-24, August.
    8. Enkhjargal Enkhbat & Yong Geng & Xi Zhang & Huijuan Jiang & Jingyu Liu & Dong Wu, 2020. "Driving Forces of Air Pollution in Ulaanbaatar City Between 2005 and 2015: An Index Decomposition Analysis," Sustainability, MDPI, vol. 12(8), pages 1-17, April.
    9. Hua Liao & Celio Andrade & Julio Lumbreras & Jing Tian, 2018. "CO2 Emissions in Beijing: Sectoral Linkages and Demand Drivers," CEEP-BIT Working Papers 113, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    10. Yong Wang & Yu Zhou & Lin Zhu & Fei Zhang & Yingchun Zhang, 2018. "Influencing Factors and Decoupling Elasticity of China’s Transportation Carbon Emissions," Energies, MDPI, vol. 11(5), pages 1-29, May.
    11. Darío Serrano-Puente, 2021. "Are we moving toward an energy-efficient low-carbon economy? An input–output LMDI decomposition of CO $$_{2}$$ 2 emissions for Spain and the EU28," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 12(2), pages 151-229, June.
    12. Xuemei Jiang & Huijuan Wang & Yan Xia, 2020. "Economic structural change, renewable energy development, and carbon dioxide emissions in China," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 25(7), pages 1345-1362, October.
    13. Román-Collado, Rocío & Cansino, José M. & Botia, Camilo, 2018. "How far is Colombia from decoupling? Two-level decomposition analysis of energy consumption changes," Energy, Elsevier, vol. 148(C), pages 687-700.
    14. Román-Collado, Rocío & Colinet, Maria José, 2018. "Is energy efficiency a driver or an inhibitor of energy consumption changes in Spain? Two decomposition approaches," Energy Policy, Elsevier, vol. 115(C), pages 409-417.
    15. Cui, Lixin & Dong, Ruxue & Mu, Yunguo & Shen, Zhiyang & Xu, Jiatong, 2022. "How policy preferences affect the carbon shadow price in the OECD," Applied Energy, Elsevier, vol. 311(C).
    16. repec:ers:journl:v:xxiv:y:2021:i:2:p:1243-1257 is not listed on IDEAS
    17. Zbigniew Gołaś, 2023. "Decoupling Analysis of Energy-Related Carbon Dioxide Emissions from Economic Growth in Poland," Energies, MDPI, vol. 16(9), pages 1-27, April.
    18. Bowen Xiao & Dongxiao Niu & Xiaodan Guo, 2016. "The Driving Forces of Changes in CO 2 Emissions in China: A Structural Decomposition Analysis," Energies, MDPI, vol. 9(4), pages 1-17, March.
    19. Wu, Rui & Geng, Yong & Cui, Xiaowei & Gao, Ziyan & Liu, Zhiqing, 2019. "Reasons for recent stagnancy of carbon emissions in China's industrial sectors," Energy, Elsevier, vol. 172(C), pages 457-466.
    20. He, Qi & Jiang, Xujia & Gouldson, Andy & Sudmant, Andrew & Guan, Dabo & Colenbrander, Sarah & Xue, Tao & Zheng, Bo & Zhang, Qiang, 2016. "Climate change mitigation in Chinese megacities: A measures-based analysis of opportunities in the residential sector," Applied Energy, Elsevier, vol. 184(C), pages 769-778.
    21. Xu, Bin & Lin, Boqiang, 2016. "A quantile regression analysis of China's provincial CO2 emissions: Where does the difference lie?," Energy Policy, Elsevier, vol. 98(C), pages 328-342.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:gam:jsusta:v:15:y:2023:i:7:p:5922-:d:1110475. 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.