IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i7p3094-d1110073.html
   My bibliography  Save this article

Exploring the Driving Factors and Their Spatial Effects on Carbon Emissions in the Building Sector

Author

Listed:
  • Jia Wei

    (School of Economics and Finance, Xi’an Jiaotong University, Xi’an 710061, China)

  • Wei Shi

    (Future City Innovation Technology Co., Ltd., Shaanxi Construction Engineering Holding Group, Xi’an 712000, China
    SCEGC-XJTU Joint Research Center for Future City Construction and Management Innovation, Xi’an Jiaotong University, Xi’an 712000, China)

  • Jingrou Ran

    (School of Economics and Finance, Xi’an Jiaotong University, Xi’an 710061, China)

  • Jing Pu

    (Future City Innovation Technology Co., Ltd., Shaanxi Construction Engineering Holding Group, Xi’an 712000, China
    SCEGC-XJTU Joint Research Center for Future City Construction and Management Innovation, Xi’an Jiaotong University, Xi’an 712000, China)

  • Jiyang Li

    (School of Economics and Finance, Xi’an Jiaotong University, Xi’an 710061, China
    Shaanxi Construction Engineering Group Co., Ltd., Xi’an 710003, China)

  • Kai Wang

    (Future City Innovation Technology Co., Ltd., Shaanxi Construction Engineering Holding Group, Xi’an 712000, China
    SCEGC-XJTU Joint Research Center for Future City Construction and Management Innovation, Xi’an Jiaotong University, Xi’an 712000, China)

Abstract

This study measured the lifecycle carbon emissions of buildings in 30 Chinese provinces from 2005 to 2020 and decomposed the drivers of carbon emissions in the materialization stage and operation stage of building, respectively, using the Stochastic Impacts with the Regression on Population, Affluence, and Technology (STIRPAT) model in order to investigate the drivers of carbon emissions and their spatial influence effects in the building sector. The spatial Durbin model (SDM) was used to thoroughly investigate the spatial effects of carbon emissions and their drivers in the building sector under geographic and economic distances. According to the findings, China’s building sector has a high concentration of carbon emissions in the east and a low concentration in the west. There is also a sizable spatial autocorrelation, and the spatial spillover effects in the materialization and operation stages shift in opposite directions. To help the building sector to achieve the carbon peaking and neutrality goals, specific policy recommendations are made based on the study’s findings.

Suggested Citation

  • Jia Wei & Wei Shi & Jingrou Ran & Jing Pu & Jiyang Li & Kai Wang, 2023. "Exploring the Driving Factors and Their Spatial Effects on Carbon Emissions in the Building Sector," Energies, MDPI, vol. 16(7), pages 1-21, March.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:7:p:3094-:d:1110073
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/7/3094/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/7/3094/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. de Bruyn, S. M. & van den Bergh, J. C. J. M. & Opschoor, J. B., 1998. "Economic growth and emissions: reconsidering the empirical basis of environmental Kuznets curves," Ecological Economics, Elsevier, vol. 25(2), pages 161-175, May.
    2. Meng Yang & Yisheng Liu & Jinzhao Tian & Feiyu Cheng & Pengbo Song, 2022. "Dynamic Evolution and Regional Disparity in Carbon Emission Intensity in China," Sustainability, MDPI, vol. 14(7), pages 1-15, March.
    3. Fakher, Hossein Ali & Ahmed, Zahoor & Acheampong, Alex O. & Nathaniel, Solomon Prince, 2023. "Renewable energy, nonrenewable energy, and environmental quality nexus: An investigation of the N-shaped Environmental Kuznets Curve based on six environmental indicators," Energy, Elsevier, vol. 263(PA).
    4. Zhang, Yang & Yan, Da & Hu, Shan & Guo, Siyue, 2019. "Modelling of energy consumption and carbon emission from the building construction sector in China, a process-based LCA approach," Energy Policy, Elsevier, vol. 134(C).
    5. James P. LeSage & R. Kelley Pace, 2008. "Spatial Econometric Modeling Of Origin‐Destination Flows," Journal of Regional Science, Wiley Blackwell, vol. 48(5), pages 941-967, December.
    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. Dinan Li & Yuge Huang & Chengzhou Guo & Haitao Wang & Jianwei Jia & Lu Huang, 2023. "Low-Carbon Optimization Design for Low-Temperature Granary Roof Insulation in Different Ecological Grain Storage Zones in China," Sustainability, MDPI, vol. 15(18), pages 1-19, September.
    2. Xu, Feng & Li, Xiaodong & Yang, Zhihan & Zhu, Chen, 2024. "Spatiotemporal characteristics and driving factor analysis of embodied CO2 emissions in China's building sector," Energy Policy, Elsevier, vol. 188(C).
    3. Chao Dai & Yuan Tan & Shuangping Cao & Hong Liao & Jie Pu & Haiyan Huang & Weiguang Cai, 2024. "Analysis and Short-Term Peak Forecasting of the Driving Factors of Carbon Emissions in the Construction Industry at the Provincial Level in China," Energies, MDPI, vol. 17(16), pages 1-15, August.

    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. Amina Andreichyk & Pavel Tsvetkov, 2023. "Study of the Relationship between Economic Growth and Greenhouse Gas Emissions of the Shanghai Cooperation Organization Countries on the Basis of the Environmental Kuznets Curve," Resources, MDPI, vol. 12(7), pages 1-20, July.
    2. Abban, Olivier Joseph & Xing, Yao Hong & Nuţă, Alina Cristina & Nuţă, Florian Marcel & Borah, Prasad Siba & Ofori, Charles & Jing, Yao Jing, 2023. "Policies for carbon-zero targets: Examining the spillover effects of renewable energy and patent applications on environmental quality in Europe," Energy Economics, Elsevier, vol. 126(C).
    3. Claudia García-García & Catalina B. García-García & Román Salmerón, 2021. "Confronting collinearity in environmental regression models: evidence from world data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(3), pages 895-926, September.
    4. Muhammad Shahbaz & Vassilios G. Papavassiliou & Amine Lahiani & David Roubaud, 2023. "Are we moving towards decarbonisation of the global economy? Lessons from the distant past to the present," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2620-2634, July.
    5. Song, Tao & Zheng, Tingguo & Tong, Lianjun, 2008. "An empirical test of the environmental Kuznets curve in China: A panel cointegration approach," China Economic Review, Elsevier, vol. 19(3), pages 381-392, September.
    6. Kaika, Dimitra & Zervas, Efthimios, 2013. "The environmental Kuznets curve (EKC) theory. Part B: Critical issues," Energy Policy, Elsevier, vol. 62(C), pages 1403-1411.
    7. Peter Rafaj & Markus Amann, 2018. "Decomposing Air Pollutant Emissions in Asia: Determinants and Projections," Energies, MDPI, vol. 11(5), pages 1-14, May.
    8. Karina Acosta & Hengyu Gu, 2022. "Locked up? The development and internal migration nexus in Colombia," Documentos de Trabajo Sobre Economía Regional y Urbana 19931, Banco de la República, Economía Regional.
    9. Lei Gao & Taowu Pei & Jingran Zhang & Yu Tian, 2022. "The “Pollution Halo” Effect of FDI: Evidence from the Chinese Sichuan–Chongqing Urban Agglomeration," IJERPH, MDPI, vol. 19(19), pages 1-17, September.
    10. Daniel A. Griffith & Manfred M. Fischer & James LeSage, 2017. "The spatial autocorrelation problem in spatial interaction modelling: a comparison of two common solutions," Letters in Spatial and Resource Sciences, Springer, vol. 10(1), pages 75-86, March.
    11. Jha, Raghbendra & Murthy, K. V. Bhanu, 2003. "An inverse global environmental Kuznets curve," Journal of Comparative Economics, Elsevier, vol. 31(2), pages 352-368, June.
    12. Bilgili, Faik & Mugaloglu, Erhan & Koçak, Emrah, 2018. "The impact of oil prices on CO2 emissions in China: A Wavelet coherence approach," MPRA Paper 90170, University Library of Munich, Germany.
    13. Sebri, Maamar, 2009. "La Zone Méditerranéenne Face à la Pollution de L’air : Une Investigation Econométrique [The Mediterranean Zone in front of Air pollution: an Econometric Investigation]," MPRA Paper 32382, University Library of Munich, Germany.
    14. G. Mythili & Shibashis Mukherjee, 2011. "Examining Environmental Kuznets Curve for river effluents in India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 13(3), pages 627-640, June.
    15. Raffin, Natacha & Seegmuller, Thomas, 2014. "Longevity, pollution and growth," Mathematical Social Sciences, Elsevier, vol. 69(C), pages 22-33.
    16. Zhenxiang Cao & Liqing Peng, 2023. "The Impact of Digital Economics on Environmental Quality: A System Dynamics Approach," SAGE Open, , vol. 13(4), pages 21582440231, December.
    17. C. Seri & A. de Juan Fernandez, 2021. "The relationship between economic growth and environment. Testing the EKC hypothesis for Latin American countries," Papers 2105.11405, arXiv.org.
    18. Kristian Behrens & Cem Ertur & Wilfried Koch, 2012. "‘Dual’ Gravity: Using Spatial Econometrics To Control For Multilateral Resistance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(5), pages 773-794, August.
    19. Evangelos V. Dioikitopoulos & Sugata Ghosh & Eugenia Vella, 2016. "Technological Progress, Time Perception and Environmental Sustainability," Working Papers 2016002, The University of Sheffield, Department of Economics.
    20. Irene Brunetti & Davide fiaschi & Lisa Gianmoena, 2013. "An Index of Growth Rate Volatility: Methodology and an Application to European Regions," Discussion Papers 2013/169, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.

    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:7:p:3094-:d:1110073. 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.