IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i11p8638-d1156409.html
   My bibliography  Save this article

A Simulation Study on Peak Carbon Emission of Public Buildings—In the Case of Henan Province, China

Author

Listed:
  • Hui Li

    (College of Architecture and Civil Engineering, Xinyang Normal University, Xinyang 464000, China)

  • Yanan Zheng

    (College of Architecture and Civil Engineering, Xinyang Normal University, Xinyang 464000, China)

  • Guan Gong

    (College of Architecture and Civil Engineering, Xinyang Normal University, Xinyang 464000, China)

  • Hongtao Guo

    (Financial Department, Xinyang Normal University, Xinyang 464000, China)

Abstract

With the continuous development of the social economy, carbon emissions from various buildings are increasing. As the most important category of building carbon emissions, the rapid peaking of public buildings is an important part of achieving carbon peak and carbon neutrality. This paper is based on the industrial background of the energy consumption structure of Henan Province, a central province in the developing country of China. Firstly, the energy consumption intensity of buildings and public buildings in Henan Province from 2010 to 2020 was calculated according to the energy balance sheet. The Kaya–LMDI decomposition method was also used to analyse the carbon emissions of public buildings, determining the impact of each influencing parameter on public buildings. Secondly, the scenario prediction model Monte Carlo was run 100,000 times to set the stochastic parameters of the variables in the model to predict the time of carbon peak and carbon emissions. The analysis results indicated that: ① Carbon emissions in Henan Province have exhibited a steady growth trend, increasing from 1533 t in 2010 to 6561 t in 2020; ② The primary factors influencing carbon emissions of public buildings in Henan Province were urbanization rate, public floor area per capita, and energy intensity per unit of public floor area; and ③ Carbon emissions of public buildings in Henan Province followed an inverted U-shaped distribution and are expected to peak at approximately 7423 t by the year 2035. The research method in this paper can guide the simulation study of peak carbon emission prediction in Henan Province based on the influencing parameters of carbon emission from different types of buildings. Moreover, the results of this paper can provide a reference for a more precise study of building carbon reduction in similar regions of developing countries.

Suggested Citation

  • Hui Li & Yanan Zheng & Guan Gong & Hongtao Guo, 2023. "A Simulation Study on Peak Carbon Emission of Public Buildings—In the Case of Henan Province, China," Sustainability, MDPI, vol. 15(11), pages 1-20, May.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:11:p:8638-:d:1156409
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/11/8638/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/11/8638/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dong, Jia & Li, Cunbin, 2022. "Scenario prediction and decoupling analysis of carbon emission in Jiangsu Province, China," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    2. Lei Zhao & Wenbin Pan & Hao Lin, 2022. "Can Fujian Achieve Carbon Peak and Pollutant Reduction Targets before 2030? Case Study of 3E System in Southeastern China Based on System Dynamics," Sustainability, MDPI, vol. 14(18), pages 1-22, September.
    3. Lu, Mengxue & Lai, Joseph, 2020. "Review on carbon emissions of commercial buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 119(C).
    4. Hong, Lixuan & Zhou, Nan & Feng, Wei & Khanna, Nina & Fridley, David & Zhao, Yongqiang & Sandholt, Kaare, 2016. "Building stock dynamics and its impacts on materials and energy demand in China," Energy Policy, Elsevier, vol. 94(C), pages 47-55.
    5. Di Peng & Haibin Liu, 2022. "Measurement and Driving Factors of Carbon Emissions from Coal Consumption in China Based on the Kaya-LMDI Model," Energies, MDPI, vol. 16(1), pages 1-19, December.
    6. Jiang, Xuemei & Guan, Dabo, 2016. "Determinants of global CO2 emissions growth," Applied Energy, Elsevier, vol. 184(C), pages 1132-1141.
    7. Wang, Huan & Chen, Wenying & Shi, Jingcheng, 2018. "Low carbon transition of global building sector under 2- and 1.5-degree targets," Applied Energy, Elsevier, vol. 222(C), pages 148-157.
    8. Yongkun Wang & Yang Liang & Liangshan Shao & Polinpapilinho Katina, 2022. "Driving Factors and Peak Forecasting of Carbon Emissions from Public Buildings Based on LMDI-SD," Discrete Dynamics in Nature and Society, Hindawi, vol. 2022, pages 1-10, April.
    9. Wu, Rong & Wang, Jieyu & Wang, Shaojian & Feng, Kuishuang, 2021. "The drivers of declining CO2 emissions trends in developed nations using an extended STIRPAT model: A historical and prospective analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    10. Li, Bing-Bing & Liang, Qiao-Mei & Wang, Jin-Cheng, 2015. "A comparative study on prediction methods for China's medium- and long-term coal demand," Energy, Elsevier, vol. 93(P2), pages 1671-1683.
    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. 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.

    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. Huo, Tengfei & Xu, Linbo & Liu, Bingsheng & Cai, Weiguang & Feng, Wei, 2022. "China’s commercial building carbon emissions toward 2060: An integrated dynamic emission assessment model," Applied Energy, Elsevier, vol. 325(C).
    2. Mehmet Balcilar & Daberechi Chikezie Ekwueme & Hakki Ciftci, 2023. "Assessing the Effects of Natural Resource Extraction on Carbon Emissions and Energy Consumption in Sub-Saharan Africa: A STIRPAT Model Approach," Sustainability, MDPI, vol. 15(12), pages 1-23, June.
    3. Khozema Ahmed Ali & Mardiana Idayu Ahmad & Yusri Yusup, 2020. "Issues, Impacts, and Mitigations of Carbon Dioxide Emissions in the Building Sector," Sustainability, MDPI, vol. 12(18), pages 1-11, September.
    4. Langevin, J. & Reyna, J.L. & Ebrahimigharehbaghi, S. & Sandberg, N. & Fennell, P. & Nägeli, C. & Laverge, J. & Delghust, M. & Mata, É. & Van Hove, M. & Webster, J. & Federico, F. & Jakob, M. & Camaras, 2020. "Developing a common approach for classifying building stock energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    5. Lili Sun & Huijuan Cui & Quansheng Ge, 2021. "Driving Factors and Future Prediction of Carbon Emissions in the ‘Belt and Road Initiative’ Countries," Energies, MDPI, vol. 14(17), pages 1-21, September.
    6. Zhenfen Wu & Zhe Wang & Qiliang Yang & Changyun Li, 2024. "Prediction Model of Electric Power Carbon Emissions Based on Extended System Dynamics," Energies, MDPI, vol. 17(2), pages 1-22, January.
    7. Xuejing Zheng & Boxiao Xu & Shijun You & Huan Zhang & Yaran Wang & Leizhai Sun, 2020. "Energy Consumption and CO 2 Emissions of Coach Stations in China," Energies, MDPI, vol. 13(14), pages 1-22, July.
    8. Yang, Yi & Yuan, Zhuqing & Yang, Shengnan, 2022. "Difference in the drivers of industrial carbon emission costs determines the diverse policies in middle-income regions: A case of northwestern China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
    9. 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.
    10. Zhong, Zhangqi & Jiang, Lei & Zhou, Peng, 2018. "Transnational transfer of carbon emissions embodied in trade: Characteristics and determinants from a spatial perspective," Energy, Elsevier, vol. 147(C), pages 858-875.
    11. Bai, Lujian & Wang, Shusheng, 2019. "Definition of new thermal climate zones for building energy efficiency response to the climate change during the past decades in China," Energy, Elsevier, vol. 170(C), pages 709-719.
    12. Qiao, Hui & Chen, Siyu & Dong, Xiucheng & Dong, Kangyin, 2019. "Has China's coal consumption actually reached its peak? National and regional analysis considering cross-sectional dependence and heterogeneity," Energy Economics, Elsevier, vol. 84(C).
    13. Yue Dou & Muhammad Shahbaz & Kangyin Dong & Xiucheng Dong, 2022. "How natural disasters affect carbon emissions: the global case," 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. 113(3), pages 1875-1901, September.
    14. Zhang, Kaiqiang & Jia, Na & Liu, Lirong, 2019. "CO2 storage in fractured nanopores underground: Phase behaviour study," Applied Energy, Elsevier, vol. 238(C), pages 911-928.
    15. Li, Danyang & Chen, Wenying, 2019. "TIMES modeling of the large-scale popularization of electric vehicles under the worldwide prohibition of liquid vehicle sales," Applied Energy, Elsevier, vol. 254(C).
    16. Yun-Hsun Huang & Jung-Hua Wu & Hao-Syuan Huang, 2021. "Analyzing the Driving Forces behind CO 2 Emissions in Energy-Resource-Poor and Fossil-Fuel-Centered Economies: Case Studies from Taiwan, Japan, and South Korea," Energies, MDPI, vol. 14(17), pages 1-14, August.
    17. Yamaguchi, Yohei & Shoda, Yuto & Yoshizawa, Shinya & Imai, Tatsuya & Perwez, Usama & Shimoda, Yoshiyuki & Hayashi, Yasuhiro, 2023. "Feasibility assessment of net zero-energy transformation of building stock using integrated synthetic population, building stock, and power distribution network framework," Applied Energy, Elsevier, vol. 333(C).
    18. Vladimir Z. Gjorgievski & Nikolas G. Chatzigeorgiou & Venizelos Venizelou & Georgios C. Christoforidis & George E. Georghiou & Grigoris K. Papagiannis, 2020. "Evaluation of Load Matching Indicators in Residential PV Systems-the Case of Cyprus," Energies, MDPI, vol. 13(8), pages 1-18, April.
    19. Liu, Junling & Yin, Mingjian & Xia-Hou, Qinrui & Wang, Ke & Zou, Ji, 2021. "Comparison of sectoral low-carbon transition pathways in China under the nationally determined contribution and 2 °C targets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    20. Gonçalves, Juliana E. & Montazeri, Hamid & van Hooff, Twan & Saelens, Dirk, 2021. "Performance of building integrated photovoltaic facades: Impact of exterior convective heat transfer," Applied Energy, Elsevier, vol. 287(C).

    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:11:p:8638-:d:1156409. 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.