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Classification of Heritage Residential Building Stock and Defining Sustainable Retrofitting Scenarios in Khedivial Cairo

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  • Hanan S.S. Ibrahim

    (Sustainable Architecture and Urbanism Lab, Department of Building, Architecture & Town Planning (BATir), Free University of Brussels, 1050 Brussels, Belgium
    Department of Architectural Engineering, Faculty of Engineering and Technology, Future University in Egypt (FUE), 11835 Cairo, Egypt)

  • Ahmed Z. Khan

    (Sustainable Architecture and Urbanism Lab, Department of Building, Architecture & Town Planning (BATir), Free University of Brussels, 1050 Brussels, Belgium)

  • Shady Attia

    (Sustainable Building Design (SBD) Lab, Department of UEE, Faculty of Applied Sciences, University of Liège, 4000 Liège, Belgium)

  • Yehya Serag

    (Department of Architectural Engineering, Faculty of Engineering and Technology, Future University in Egypt (FUE), 11835 Cairo, Egypt)

Abstract

This study aims to develop an integrated classification methodology for retrofitting that preserves both energy use and cultural value aspects in hot climates, especially, in North Africa, as a hot zone, which lacks retrofitting initiatives of built heritage. Despite the number of existing methods of classification for energy purposes, little attention has been paid to integrate the perceptions of cultural values in those methods. The proposed methodology classifies heritage building stocks based on building physical characteristics, as well as heritage significance levels, and then later integrates the outcomes into a matrix to propose sustainable retrofitting scenarios based on three dimensions, i.e., heritage value locations, types, and heritage significance level. For validation, the methodology was applied to the heritage residential building stock along with a microscale analysis on a building in Khedivial Cairo, Egypt. The findings include extracting twelve building classes, providing a reference building for each class, and a detailed catalogue of the extracted reference buildings that includes retrofitting scenarios for creating energy models. The originality of this work lies in integrating cultural values in a building classification methodology and providing a list of sustainable retrofitting scenarios for reference buildings. The findings contribute to fill the gap in existing building classifications, more specifically in hot climates.

Suggested Citation

  • Hanan S.S. Ibrahim & Ahmed Z. Khan & Shady Attia & Yehya Serag, 2021. "Classification of Heritage Residential Building Stock and Defining Sustainable Retrofitting Scenarios in Khedivial Cairo," Sustainability, MDPI, vol. 13(2), pages 1-26, January.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:2:p:880-:d:481766
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    References listed on IDEAS

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    1. Marta Bottero & Chiara D’Alpaos & Alessandra Oppio, 2019. "Ranking of Adaptive Reuse Strategies for Abandoned Industrial Heritage in Vulnerable Contexts: A Multiple Criteria Decision Aiding Approach," Sustainability, MDPI, vol. 11(3), pages 1-18, February.
    2. Sartori, Igor & Wachenfeldt, Bjrn Jensen & Hestnes, Anne Grete, 2009. "Energy demand in the Norwegian building stock: Scenarios on potential reduction," Energy Policy, Elsevier, vol. 37(5), pages 1614-1627, May.
    3. Martínez-Molina, Antonio & Tort-Ausina, Isabel & Cho, Soolyeon & Vivancos, José-Luis, 2016. "Energy efficiency and thermal comfort in historic buildings: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 70-85.
    4. Brandão de Vasconcelos, Ana & Pinheiro, Manuel Duarte & Manso, Armando & Cabaço, António, 2015. "A Portuguese approach to define reference buildings for cost-optimal methodologies," Applied Energy, Elsevier, vol. 140(C), pages 316-328.
    5. Ballarini, Ilaria & Corgnati, Stefano Paolo & Corrado, Vincenzo, 2014. "Use of reference buildings to assess the energy saving potentials of the residential building stock: The experience of TABULA project," Energy Policy, Elsevier, vol. 68(C), pages 273-284.
    6. Filogamo, Luana & Peri, Giorgia & Rizzo, Gianfranco & Giaccone, Antonino, 2014. "On the classification of large residential buildings stocks by sample typologies for energy planning purposes," Applied Energy, Elsevier, vol. 135(C), pages 825-835.
    7. Caputo, Paola & Costa, Gaia & Ferrari, Simone, 2013. "A supporting method for defining energy strategies in the building sector at urban scale," Energy Policy, Elsevier, vol. 55(C), pages 261-270.
    8. Ilaria Ballarini & Vincenzo Corrado, 2017. "A New Methodology for Assessing the Energy Consumption of Building Stocks," Energies, MDPI, vol. 10(8), pages 1-22, July.
    9. Mata, Érika & Sasic Kalagasidis, Angela & Johnsson, Filip, 2013. "Energy usage and technical potential for energy saving measures in the Swedish residential building stock," Energy Policy, Elsevier, vol. 55(C), pages 404-414.
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    Cited by:

    1. Hanan S.S. Ibrahim & Ahmed Z. Khan & Waqas Ahmed Mahar & Shady Attia & Yehya Serag, 2021. "Assessment of Passive Retrofitting Scenarios in Heritage Residential Buildings in Hot, Dry Climates," Energies, MDPI, vol. 14(11), pages 1-27, June.

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