IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i23p16459-d1291688.html
   My bibliography  Save this article

Passive Energy Conservation Strategies for Mitigating Energy Consumption and Reducing CO 2 Emissions in Traditional Dwellings of Peking Area, China

Author

Listed:
  • Liang Xie

    (School of Architecture and Art, Central South University, Changsha 410075, China)

  • Lai Fan

    (School of Architecture and Urban Planning, Beijing University of Civil Engineering and Architecture, Beijing 100044, China)

  • Dayu Zhang

    (School of Architecture and Urban Planning, Beijing University of Civil Engineering and Architecture, Beijing 100044, China)

  • Jixin Liu

    (School of Architecture and Art, Central South University, Changsha 410075, China)

Abstract

Within China, brick dwellings stand as archetypal relics of traditional habitation, embodying a “living fossil” status. The sustainability of these dwellings is contingent upon the integration of energy-conservation strategies. This study scrutinized and empirically assessed a representative dwelling in the Peking area. Using numerical simulations, the impact on energy consumption of factors such as insulation and glazing type, external wall thickness, insulation thickness, and solar energy utilization was evaluated. The outcomes reveal that introducing external thermal insulation—specifically, expanded polystyrene panels with a thickness of 60 mm and 40 mm for the roof and exterior walls, respectively—along with a sunspace of depth 1.5 m yielded superior energy efficiency. Additionally, substituting conventional roofing with solar tiles exhibited a potential annual electricity generation coupled with an annual solar radiation conversion efficiency of 17%. Collectively, these strategies induced a substantial reduction in annual energy consumption. This study presents tailored energy-conservation measures and provides design decision support for architects’ practical recommendations on thermal environment control of passive traditional dwellings in the Peking area.

Suggested Citation

  • Liang Xie & Lai Fan & Dayu Zhang & Jixin Liu, 2023. "Passive Energy Conservation Strategies for Mitigating Energy Consumption and Reducing CO 2 Emissions in Traditional Dwellings of Peking Area, China," Sustainability, MDPI, vol. 15(23), pages 1-24, November.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:23:p:16459-:d:1291688
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/23/16459/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/23/16459/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Helton, J.C. & Johnson, J.D. & Sallaberry, C.J. & Storlie, C.B., 2006. "Survey of sampling-based methods for uncertainty and sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 91(10), pages 1175-1209.
    2. Prativa Lamsal & Sushil Bahadur Bajracharya & Hom Bahadur Rijal, 2023. "A Review on Adaptive Thermal Comfort of Office Building for Energy-Saving Building Design," Energies, MDPI, vol. 16(3), pages 1-23, February.
    3. Saad Odeh, 2018. "Thermal Performance of Dwellings with Rooftop PV Panels and PV/Thermal Collectors," Energies, MDPI, vol. 11(7), pages 1-14, July.
    4. Karunakaran, R. & Iniyan, S. & Goic, Ranko, 2010. "Energy efficient fuzzy based combined variable refrigerant volume and variable air volume air conditioning system for buildings," Applied Energy, Elsevier, vol. 87(4), pages 1158-1175, April.
    5. Hai-fan Wang & Shang-chia Chiou, 2020. "Spatial Form Analysis and Sustainable Development Research of Traditional Residential Buildings," Sustainability, MDPI, vol. 12(2), pages 1-19, January.
    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. Panagiotis Michailidis & Iakovos Michailidis & Dimitrios Vamvakas & Elias Kosmatopoulos, 2023. "Model-Free HVAC Control in Buildings: A Review," Energies, MDPI, vol. 16(20), pages 1-45, October.
    2. Zhou, Yuekuan & Zheng, Siqian, 2020. "Uncertainty study on thermal and energy performances of a deterministic parameters based optimal aerogel glazing system using machine-learning method," Energy, Elsevier, vol. 193(C).
    3. Helton, Jon C. & Johnson, Jay D. & Sallaberry, Cédric J., 2011. "Quantification of margins and uncertainties: Example analyses from reactor safety and radioactive waste disposal involving the separation of aleatory and epistemic uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 96(9), pages 1014-1033.
    4. Plischke, Elmar & Borgonovo, Emanuele, 2019. "Copula theory and probabilistic sensitivity analysis: Is there a connection?," European Journal of Operational Research, Elsevier, vol. 277(3), pages 1046-1059.
    5. Saurbayeva, Assemgul & Memon, Shazim Ali & Kim, Jong, 2023. "Integrated multi-stage sensitivity analysis and multi-objective optimization approach for PCM integrated residential buildings in different climate zones," Energy, Elsevier, vol. 278(PB).
    6. Donghyeon Yoo & Jinhwan Park & Jaemin Moon & Changwan Kim, 2021. "Reliability-Based Design Optimization for Reducing the Performance Failure and Maximizing the Specific Energy of Lithium-Ion Batteries Considering Manufacturing Uncertainty of Porous Electrodes," Energies, MDPI, vol. 14(19), pages 1-15, September.
    7. Tian, Wei & Song, Jitian & Li, Zhanyong & de Wilde, Pieter, 2014. "Bootstrap techniques for sensitivity analysis and model selection in building thermal performance analysis," Applied Energy, Elsevier, vol. 135(C), pages 320-328.
    8. Javier Urquizo & Carlos Calderón & Philip James, 2017. "Using a Local Framework Combining Principal Component Regression and Monte Carlo Simulation for Uncertainty and Sensitivity Analysis of a Domestic Energy Model in Sub-City Areas," Energies, MDPI, vol. 10(12), pages 1-22, December.
    9. Nutkiewicz, Alex & Yang, Zheng & Jain, Rishee K., 2018. "Data-driven Urban Energy Simulation (DUE-S): A framework for integrating engineering simulation and machine learning methods in a multi-scale urban energy modeling workflow," Applied Energy, Elsevier, vol. 225(C), pages 1176-1189.
    10. Cao, Jiaokun & Du, Farong & Ding, Shuiting, 2013. "Global sensitivity analysis for dynamic systems with stochastic input processes," Reliability Engineering and System Safety, Elsevier, vol. 118(C), pages 106-117.
    11. Xiaokang Wang & Li Zhu & Jiang Li & Ni Zhang & Yue Tang & Yilin Sun & Honglin Wu & Chuang Cheng, 2023. "Architectural Continuity Assessment of Rural Settlement Houses: A Systematic Literature Review," Land, MDPI, vol. 12(7), pages 1-17, July.
    12. Guo, Zehua & Dailey, Ryan & Feng, Tangtao & Zhou, Yukun & Sun, Zhongning & Corradini, Michael L & Wang, Jun, 2021. "Uncertainty analysis of ATF Cr-coated-Zircaloy on BWR in-vessel accident progression during a station blackout," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    13. Wang, Ran & Lu, Shilei & Feng, Wei, 2020. "A three-stage optimization methodology for envelope design of passive house considering energy demand, thermal comfort and cost," Energy, Elsevier, vol. 192(C).
    14. Jiayi Shi & Tao Zhang & Hiroatsu Fukuda & Qun Zhang & Lujian Bai, 2022. "Socio-Environmental Responsive Strategy and Sustainable Development of Traditional Tianshui Dwellings," Sustainability, MDPI, vol. 14(14), pages 1-27, July.
    15. Jingwen Song & Zhenzhou Lu & Pengfei Wei & Yanping Wang, 2015. "Global sensitivity analysis for model with random inputs characterized by probability-box," Journal of Risk and Reliability, , vol. 229(3), pages 237-253, June.
    16. Rehman, Hassam ur & Hirvonen, Janne & Sirén, Kai, 2017. "A long-term performance analysis of three different configurations for community-sized solar heating systems in high latitudes," Renewable Energy, Elsevier, vol. 113(C), pages 479-493.
    17. Auder, Benjamin & De Crecy, Agnès & Iooss, Bertrand & Marquès, Michel, 2012. "Screening and metamodeling of computer experiments with functional outputs. Application to thermal–hydraulic computations," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 122-131.
    18. Galetakis, Michael & Roumpos, Christos & Alevizos, George & Vamvuka, Despina, 2011. "Production scheduling of a lignite mine under quality and reserves uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 96(12), pages 1611-1618.
    19. Bolado-Lavin, R. & Castaings, W. & Tarantola, S., 2009. "Contribution to the sample mean plot for graphical and numerical sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 94(6), pages 1041-1049.
    20. Zio, E. & Pedroni, N., 2010. "An optimized Line Sampling method for the estimation of the failure probability of nuclear passive systems," Reliability Engineering and System Safety, Elsevier, vol. 95(12), pages 1300-1313.

    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:23:p:16459-:d:1291688. 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.