IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i11p4422-d364517.html
   My bibliography  Save this article

Benchmarking of Water, Energy, and Carbon Flows in Academic Buildings: A Fuzzy Clustering Approach

Author

Listed:
  • Abdulaziz Alghamdi

    (School of Engineering, University of British Columbia (Okanagan), 3333 University Way, Kelowna, BC V1V 1V7, Canada)

  • Guangji Hu

    (School of Engineering, University of British Columbia (Okanagan), 3333 University Way, Kelowna, BC V1V 1V7, Canada)

  • Husnain Haider

    (Department of Civil Engineering, College of Engineering, Qassim University, Buraydah, Qassim 51452, Saudi Arabia)

  • Kasun Hewage

    (School of Engineering, University of British Columbia (Okanagan), 3333 University Way, Kelowna, BC V1V 1V7, Canada)

  • Rehan Sadiq

    (School of Engineering, University of British Columbia (Okanagan), 3333 University Way, Kelowna, BC V1V 1V7, Canada)

Abstract

In Canada, higher educational institutions (HEIs) are responsible for a significant portion of energy consumption and anthropogenic greenhouse gas (GHG) emissions. Improving the environmental performance of HEIs is an important step to achieve nationwide impact reduction. Academic buildings are among the largest infrastructure units in HEIs. Therefore, it is crucial to improve the environmental performance of academic buildings during their operations. Identifying critical academic buildings posing high impacts calls for methodologies that can holistically assess the environmental performance of buildings with respect to water and energy consumption, and GHG emission. This study proposes a fuzzy clustering approach to classify academic buildings in an HEI and benchmark their environmental performance in terms of water, energy, and carbon flows. To account for the fuzzy uncertainties in partitioning, the fuzzy c-means algorithm is employed to classify the buildings based on water, energy, and carbon flow indicators. The application of the developed methodology is demonstrated by a case study of 71 academic buildings in the University of British Columbia, Canada. The assessed buildings are grouped into three clusters representing different levels of performances with different degrees of membership. The environmental performance of each cluster is then benchmarked. Based on the results, the environmental performances of academic buildings are holistically determined, and the building clusters associated with low environmental performances are identified for potential improvements. The subsequent benchmark will allow HEIs to compare the impacts of academic building operations and set realistic targets for impact reduction.

Suggested Citation

  • Abdulaziz Alghamdi & Guangji Hu & Husnain Haider & Kasun Hewage & Rehan Sadiq, 2020. "Benchmarking of Water, Energy, and Carbon Flows in Academic Buildings: A Fuzzy Clustering Approach," Sustainability, MDPI, vol. 12(11), pages 1-25, May.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:11:p:4422-:d:364517
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/11/4422/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/11/4422/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Papadopoulos, Sokratis & Kontokosta, Constantine E., 2019. "Grading buildings on energy performance using city benchmarking data," Applied Energy, Elsevier, vol. 233, pages 244-253.
    2. Ward, Ian & Ogbonna, Anthony & Altan, Hasim, 2008. "Sector review of UK higher education energy consumption," Energy Policy, Elsevier, vol. 36(8), pages 2929-2939, August.
    3. Mehdi Chihib & Esther Salmerón-Manzano & Francisco Manzano-Agugliaro, 2020. "Benchmarking Energy Use at University of Almeria (Spain)," Sustainability, MDPI, vol. 12(4), pages 1-16, February.
    4. Monika Urbanski & Walter Filho, 2015. "Measuring sustainability at universities by means of the Sustainability Tracking, Assessment and Rating System (STARS): early findings from STARS data," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 17(2), pages 209-220, April.
    5. Abdulaziz Alghamdi & Husnain Haider & Kasun Hewage & Rehan Sadiq, 2019. "Inter-University Sustainability Benchmarking for Canadian Higher Education Institutions: Water, Energy, and Carbon Flows for Technical-Level Decision-Making," Sustainability, MDPI, vol. 11(9), pages 1-26, May.
    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. Denner Deda & Helena Gervásio & Margarida J. Quina, 2023. "Bibliometric Analysis and Benchmarking of Life Cycle Assessment of Higher Education Institutions," Sustainability, MDPI, vol. 15(5), pages 1-18, February.
    2. Wang, Xue-Chao & Klemeš, Jiří Jaromír & Ouyang, Xiao & Xu, Zihan & Fan, Weiguo & Wei, Hejie & Song, Weize, 2021. "Regional embodied Water-Energy-Carbon efficiency of China," Energy, Elsevier, vol. 224(C).
    3. Md. Salman Islam & Gengyuan Liu & Duo Xu & Yu Chen & Hui Li & Caocao Chen, 2023. "University-Campus-Based Zero-Carbon Action Plans for Accelerating the Zero-Carbon City Transition," Sustainability, MDPI, vol. 15(18), pages 1-24, September.

    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. Amila Omazic & Bernd Markus Zunk, 2021. "Semi-Systematic Literature Review on Sustainability and Sustainable Development in Higher Education Institutions," Sustainability, MDPI, vol. 13(14), pages 1-45, July.
    2. 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).
    3. Wang, Ran & Lu, Shilei & Feng, Wei, 2020. "A novel improved model for building energy consumption prediction based on model integration," Applied Energy, Elsevier, vol. 262(C).
    4. Anete Veidemane, 2022. "Education for Sustainable Development in Higher Education Rankings: Challenges and Opportunities for Developing Internationally Comparable Indicators," Sustainability, MDPI, vol. 14(9), pages 1-20, April.
    5. Riccardo Boiocchi & Marco Ragazzi & Vincenzo Torretta & Elena Cristina Rada, 2023. "Critical Analysis of the GreenMetric World University Ranking System: The Issue of Comparability," Sustainability, MDPI, vol. 15(2), pages 1-15, January.
    6. Yu, Xinran & Ergan, Semiha & Dedemen, Gokmen, 2019. "A data-driven approach to extract operational signatures of HVAC systems and analyze impact on electricity consumption," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    7. Salah Vaisi & Saleh Mohammadi & Benedetto Nastasi & Kavan Javanroodi, 2020. "A New Generation of Thermal Energy Benchmarks for University Buildings," Energies, MDPI, vol. 13(24), pages 1-18, December.
    8. Yusuf A. Adenle & Edwin H. W. Chan & Yi Sun & C.K. Chau, 2020. "Modifiable Campus-Wide Appraisal Model (MOCAM) for Sustainability in Higher Education Institutions," Sustainability, MDPI, vol. 12(17), pages 1-19, August.
    9. Jaqueline Litardo & Ruben Hidalgo-Leon & Guillermo Soriano, 2021. "Energy Performance and Benchmarking for University Classrooms in Hot and Humid Climates," Energies, MDPI, vol. 14(21), pages 1-17, October.
    10. Habib M. Alshuwaikhat & Ismaila R. Abubakar & Yusuf A. Aina & Yusuf A. Adenle & Muhammad Umair, 2017. "The Development of a GIS-Based Model for Campus Environmental Sustainability Assessment," Sustainability, MDPI, vol. 9(3), pages 1-23, March.
    11. Mehdi Chihib & Esther Salmerón-Manzano & Mimoun Chourak & Alberto-Jesus Perea-Moreno & Francisco Manzano-Agugliaro, 2021. "Impact of the COVID-19 Pandemic on the Energy Use at the University of Almeria (Spain)," Sustainability, MDPI, vol. 13(11), pages 1-21, May.
    12. Geraldi, Matheus Soares & Ghisi, Enedir, 2022. "Data-driven framework towards realistic bottom-up energy benchmarking using an Artificial Neural Network," Applied Energy, Elsevier, vol. 306(PA).
    13. Wadud, Zia & Royston, Sarah & Selby, Jan, 2019. "Modelling energy demand from higher education institutions: A case study of the UK," Applied Energy, Elsevier, vol. 233, pages 816-826.
    14. Andrews, Abigail & Jain, Rishee K., 2022. "Beyond Energy Efficiency: A clustering approach to embed demand flexibility into building energy benchmarking," Applied Energy, Elsevier, vol. 327(C).
    15. Che-Hao Chang & Jason Lin & Jia-Wei Chang & Yu-Shun Huang & Ming-Hsin Lai & Yen-Jen Chang, 2024. "Hybrid Deep Neural Networks with Multi-Tasking for Rice Yield Prediction Using Remote Sensing Data," Agriculture, MDPI, vol. 14(4), pages 1-21, March.
    16. Liu, Xue & Ding, Yong & Tang, Hao & Fan, Lingxiao & Lv, Jie, 2022. "Investigating the effects of key drivers on energy consumption of nonresidential buildings: A data-driven approach integrating regularization and quantile regression," Energy, Elsevier, vol. 244(PA).
    17. Lo, Kevin, 2013. "Energy conservation in China's higher educationinstitutions," Energy Policy, Elsevier, vol. 56(C), pages 703-710.
    18. Abdulaziz Alghamdi & Husnain Haider & Kasun Hewage & Rehan Sadiq, 2019. "Inter-University Sustainability Benchmarking for Canadian Higher Education Institutions: Water, Energy, and Carbon Flows for Technical-Level Decision-Making," Sustainability, MDPI, vol. 11(9), pages 1-26, May.
    19. Mohammed Hammam Mohammed Al-Madani & Yudi Fernando & Ming-Lang Tseng, 2022. "Assuring Energy Reporting Integrity: Government Policy’s Past, Present, and Future Roles," Sustainability, MDPI, vol. 14(22), pages 1-24, November.
    20. Yu, Yinyun & Li, Congdong & Fu, Yelin & Yang, Weiming, 2023. "A group decision-making method to measure national energy architecture performance: A case study of the International energy Agency," Applied Energy, Elsevier, vol. 330(PA).

    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:12:y:2020:i:11:p:4422-:d:364517. 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.