IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i9p3677-d1132371.html
   My bibliography  Save this article

Framework for Quantifying Energy Impacts of Rehabilitation of Derelict Buildings: Assessment in Lisbon, Portugal

Author

Listed:
  • Pedro Lima

    (Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisboa, Portugal)

  • Patrícia Baptista

    (IN+, Centre for Innovation, Technology and Policy Research, LARSyS–Laboratory for Robotics and Engineering Systems, Instituto Superior Técnico, Universidade de Lisboa, 049-001 Lisbon, Portugal)

  • Ricardo Gomes

    (IN+, Centre for Innovation, Technology and Policy Research, LARSyS–Laboratory for Robotics and Engineering Systems, Instituto Superior Técnico, Universidade de Lisboa, 049-001 Lisbon, Portugal)

Abstract

Cities are currently responsible for an important part of energy consumption and greenhouse gas emissions, justifying the need to develop measures to help them become more sustainable. One of those measures can be to address under-utilized assets in cities, such as derelict buildings with high potential for rehabilitation, and the establishment of new residence hubs within cities. Consequently, this work establishes a novel framework for evaluating the impact of rehabilitating these buildings in an urban area in Lisbon, considering the energy consumption associated with the usage of the dwelling as well as the impact on mobility, since it was considered that these buildings will be occupied by people who currently work nearby but live in the outskirts of Lisbon, favouring an urban planning of proximity between home and work. To this extent, a methodology was developed for selecting the buildings to be analysed and the commuting movements to be replaced. Then, buildings were simulated in an urban building energy modelling (UBEM) tool, considering three rehabilitation scenarios, and the required primary energy, CO 2 emissions, and costs were calculated. Regarding mobility, three new scenarios were compared with the current scenario. The results obtained confirm the high potential savings from the rehabilitation of derelict buildings and in the best-case scenario—corresponding to the rehabilitation considering envelope insulation, the installation of efficient windows, and the adoption of a heat pump together with a mobility standard targeting 15 min cities—reductions of 76% in primary energy and 84% in CO 2 emissions were achieved.

Suggested Citation

  • Pedro Lima & Patrícia Baptista & Ricardo Gomes, 2023. "Framework for Quantifying Energy Impacts of Rehabilitation of Derelict Buildings: Assessment in Lisbon, Portugal," Energies, MDPI, vol. 16(9), pages 1-19, April.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:9:p:3677-:d:1132371
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/9/3677/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/9/3677/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Miguel Lorga & João Fragoso Januário & Carlos Oliveira Cruz, 2022. "Housing Affordability, Public Policy and Economic Dynamics: An Analysis of the City of Lisbon," JRFM, MDPI, vol. 15(12), pages 1-12, November.
    2. Ang, Yu Qian & Berzolla, Zachary Michael & Reinhart, Christoph F., 2020. "From concept to application: A review of use cases in urban building energy modeling," Applied Energy, Elsevier, vol. 279(C).
    3. Chen, Yixing & Hong, Tianzhen & Piette, Mary Ann, 2017. "Automatic generation and simulation of urban building energy models based on city datasets for city-scale building retrofit analysis," Applied Energy, Elsevier, vol. 205(C), pages 323-335.
    4. Fonseca, Jimeno A. & Schlueter, Arno, 2015. "Integrated model for characterization of spatiotemporal building energy consumption patterns in neighborhoods and city districts," Applied Energy, Elsevier, vol. 142(C), pages 247-265.
    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. Teresa Santos & Filipa Ramalhete, 2024. "Urban Transformation: Analyzing the Combined Forces of Vacant Building Occupancy and Socio-Economic Dynamics," Sustainability, MDPI, vol. 16(11), pages 1-19, May.

    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. Prataviera, Enrico & Zarrella, Angelo & Morejohn, Joshua & Narayanan, Vinod, 2024. "Exploiting district cooling network and urban building energy modeling for large-scale integrated energy conservation analyses," Applied Energy, Elsevier, vol. 356(C).
    2. Perwez, Usama & Yamaguchi, Yohei & Ma, Tao & Dai, Yanjun & Shimoda, Yoshiyuki, 2022. "Multi-scale GIS-synthetic hybrid approach for the development of commercial building stock energy model," Applied Energy, Elsevier, vol. 323(C).
    3. 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.
    4. Abbasabadi, Narjes & Ashayeri, Mehdi & Azari, Rahman & Stephens, Brent & Heidarinejad, Mohammad, 2019. "An integrated data-driven framework for urban energy use modeling (UEUM)," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    5. Katal, Ali & Mortezazadeh, Mohammad & Wang, Liangzhu (Leon), 2019. "Modeling building resilience against extreme weather by integrated CityFFD and CityBEM simulations," Applied Energy, Elsevier, vol. 250(C), pages 1402-1417.
    6. Zhang, Xingxing & Lovati, Marco & Vigna, Ilaria & Widén, Joakim & Han, Mengjie & Gal, Csilla & Feng, Tao, 2018. "A review of urban energy systems at building cluster level incorporating renewable-energy-source (RES) envelope solutions," Applied Energy, Elsevier, vol. 230(C), pages 1034-1056.
    7. Battini, Federico & Pernigotto, Giovanni & Gasparella, Andrea, 2023. "District-level validation of a shoeboxing simplification algorithm to speed-up Urban Building Energy Modeling simulations," Applied Energy, Elsevier, vol. 349(C).
    8. Ali, Usman & Shamsi, Mohammad Haris & Bohacek, Mark & Purcell, Karl & Hoare, Cathal & Mangina, Eleni & O’Donnell, James, 2020. "A data-driven approach for multi-scale GIS-based building energy modeling for analysis, planning and support decision making," Applied Energy, Elsevier, vol. 279(C).
    9. Bianchi, Carlo & Zhang, Liang & Goldwasser, David & Parker, Andrew & Horsey, Henry, 2020. "Modeling occupancy-driven building loads for large and diversified building stocks through the use of parametric schedules," Applied Energy, Elsevier, vol. 276(C).
    10. Rosenfelder, Markus & Wussow, Moritz & Gust, Gunther & Cremades, Roger & Neumann, Dirk, 2021. "Predicting residential electricity consumption using aerial and street view images," Applied Energy, Elsevier, vol. 301(C).
    11. Katal, Ali & Mortezazadeh, Mohammad & Wang, Liangzhu (Leon) & Yu, Haiyi, 2022. "Urban building energy and microclimate modeling – From 3D city generation to dynamic simulations," Energy, Elsevier, vol. 251(C).
    12. Kobashi, Takuro & Choi, Younghun & Hirano, Yujiro & Yamagata, Yoshiki & Say, Kelvin, 2022. "Rapid rise of decarbonization potentials of photovoltaics plus electric vehicles in residential houses over commercial districts," Applied Energy, Elsevier, vol. 306(PB).
    13. Wang, Xiaoyu & Tian, Shuai & Ren, Jiawen & Jin, Xing & Zhou, Xin & Shi, Xing, 2024. "A novel resistance-capacitance model for evaluating urban building energy loads considering construction boundary heterogeneity," Applied Energy, Elsevier, vol. 361(C).
    14. Oraiopoulos, A. & Howard, B., 2022. "On the accuracy of Urban Building Energy Modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    15. Nutkiewicz, Alex & Mastrucci, Alessio & Rao, Narasimha D. & Jain, Rishee K., 2022. "Cool roofs can mitigate cooling energy demand for informal settlement dwellers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    16. Mauree, Dasaraden & Naboni, Emanuele & Coccolo, Silvia & Perera, A.T.D. & Nik, Vahid M. & Scartezzini, Jean-Louis, 2019. "A review of assessment methods for the urban environment and its energy sustainability to guarantee climate adaptation of future cities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 733-746.
    17. Ehsan Kamel, 2022. "A Systematic Literature Review of Physics-Based Urban Building Energy Modeling (UBEM) Tools, Data Sources, and Challenges for Energy Conservation," Energies, MDPI, vol. 15(22), pages 1-24, November.
    18. Wang, Wei & Hong, Tianzhen & Xu, Xiaodong & Chen, Jiayu & Liu, Ziang & Xu, Ning, 2019. "Forecasting district-scale energy dynamics through integrating building network and long short-term memory learning algorithm," Applied Energy, Elsevier, vol. 248(C), pages 217-230.
    19. Shen, Pengyuan & Wang, Huilong, 2024. "Archetype building energy modeling approaches and applications: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
    20. Schlör, Holger & Venghaus, Sandra & Hake, Jürgen-Friedrich, 2018. "The FEW-Nexus city index – Measuring urban resilience," Applied Energy, Elsevier, vol. 210(C), pages 382-392.

    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:9:p:3677-:d:1132371. 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.