IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-37131-6.html
   My bibliography  Save this article

Carbon reduction technology pathways for existing buildings in eight cities

Author

Listed:
  • Yu Qian Ang

    (Massachusetts Institute of Technology)

  • Zachary Michael Berzolla

    (Massachusetts Institute of Technology)

  • Samuel Letellier-Duchesne

    (Massachusetts Institute of Technology)

  • Christoph F. Reinhart

    (Massachusetts Institute of Technology)

Abstract

We work with policymakers in eight cities worldwide to identify technology pathways toward their near- and long-term carbon emissions reduction targets for existing buildings. Based on policymakers’ interests, we define city-specific shallow and deep retrofitting packages along with onsite photovoltaic generation potential. Without further grid decarbonization measures, stock-wide implementation of these retrofits in the investigated neighborhoods reduces energy use and carbon emissions by up to 66% and 84%, respectively, helping Braga, Dublin, Florianopolis, Middlebury, and Singapore to meet their 2030 goals. With projected grid decarbonization, Florianopolis and Singapore will reach their 2050 goals. The remaining emissions stem from municipalities not planning to electrify heating and/or domestic hot water use. Different climates and construction practices lead to varying retrofit packages, suggesting that comparable technology pathway analyses should be conducted for municipalities worldwide. Twenty months after the project ended, seven cities have implemented policy measures or expanded the analysis across their building stock.

Suggested Citation

  • Yu Qian Ang & Zachary Michael Berzolla & Samuel Letellier-Duchesne & Christoph F. Reinhart, 2023. "Carbon reduction technology pathways for existing buildings in eight cities," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-37131-6
    DOI: 10.1038/s41467-023-37131-6
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-37131-6
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-023-37131-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. 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).
    2. Ang, Yu Qian & Polly, Allison & Kulkarni, Aparna & Chambi, Gloria Bahl & Hernandez, Matthew & Haji, Maha N., 2022. "Multi-objective optimization of hybrid renewable energy systems with urban building energy modeling for a prototypical coastal community," Renewable Energy, Elsevier, vol. 201(P1), pages 72-84.
    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. Yin, Linfei & Xiong, Yi, 2024. "Fast-apply deep autoregressive recurrent proximal policy optimization for controlling hot water systems," Applied Energy, Elsevier, vol. 367(C).
    2. Alina Galimshina & Maliki Moustapha & Alexander Hollberg & Sébastien Lasvaux & Bruno Sudret & Guillaume Habert, 2024. "Strategies for robust renovation of residential buildings in Switzerland," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    3. Ramon Elias Weber & Caitlin Mueller & Christoph Reinhart, 2024. "A hypergraph model shows the carbon reduction potential of effective space use in housing," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    4. Yan, Zichun & Tian, Fangzhu & Sun, Yuying & Wang, Shouyang, 2024. "A time-frequency-based interval decomposition ensemble method for forecasting gasoil prices under the trend of low-carbon development," Energy Economics, Elsevier, vol. 134(C).
    5. Sheng Yang & Hong-Yi Shi & Jia Liu & Yang-Yan Lai & Özgür Bayer & Li-Wu Fan, 2024. "Supercooled erythritol for high-performance seasonal thermal energy storage," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    6. Chen, Qi & Kuang, Zhonghong & Liu, Xiaohua & Zhang, Tao, 2024. "Application-oriented assessment of grid-connected PV-battery system with deep reinforcement learning in buildings considering electricity price dynamics," Applied Energy, Elsevier, vol. 364(C).

    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. Yael Nidam & Ali Irani & Jamie Bemis & Christoph Reinhart, 2023. "Census-based urban building energy modeling to evaluate the effectiveness of retrofit programs," Environment and Planning B, , vol. 50(9), pages 2394-2406, November.
    2. Xavier Faure & Tim Johansson & Oleksii Pasichnyi, 2022. "The Impact of Detail, Shadowing and Thermal Zoning Levels on Urban Building Energy Modelling (UBEM) on a District Scale," Energies, MDPI, vol. 15(4), pages 1-18, February.
    3. Johari, F. & Lindberg, O. & Ramadhani, U.H. & Shadram, F. & Munkhammar, J. & Widén, J., 2024. "Analysis of large-scale energy retrofit of residential buildings and their impact on the electricity grid using a validated UBEM," Applied Energy, Elsevier, vol. 361(C).
    4. Shamsi, Mohammad Haris & Ali, Usman & Mangina, Eleni & O’Donnell, James, 2021. "Feature assessment frameworks to evaluate reduced-order grey-box building energy models," Applied Energy, Elsevier, vol. 298(C).
    5. Stefano Converso & Paolo Civiero & Stefano Ciprigno & Ivana Veselinova & Saffa Riffat, 2023. "Toward a Fast but Reliable Energy Performance Evaluation Method for Existing Residential Building Stock," Energies, MDPI, vol. 16(9), pages 1-24, May.
    6. 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).
    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. Rafael Campamà Pizarro & Ricardo Bernardo & Maria Wall, 2023. "Streamlining Building Energy Modelling Using Open Access Databases—A Methodology towards Decarbonisation of Residential Buildings in Sweden," Sustainability, MDPI, vol. 15(5), pages 1-17, February.
    9. Javier García-López & Juan José Sendra & Samuel Domínguez-Amarillo, 2024. "Validating ‘GIS-UBEM’—A Residential Open Data-Driven Urban Building Energy Model," Sustainability, MDPI, vol. 16(6), pages 1-18, March.
    10. Osman, Mohamed & Saad, Mostafa M. & Ouf, Mohamed & Eicker, Ursula, 2024. "From buildings to cities: How household demographics shape demand response and energy consumption," Applied Energy, Elsevier, vol. 356(C).
    11. Liao, Wei & Xiao, Fu & Li, Yanxue & Zhang, Hanbei & Peng, Jinqing, 2024. "A comparative study of demand-side energy management strategies for building integrated photovoltaics-battery and electric vehicles (EVs) in diversified building communities," Applied Energy, Elsevier, vol. 361(C).
    12. Prataviera, Enrico & Vivian, Jacopo & Lombardo, Giulia & Zarrella, Angelo, 2022. "Evaluation of the impact of input uncertainty on urban building energy simulations using uncertainty and sensitivity analysis," Applied Energy, Elsevier, vol. 311(C).
    13. 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).
    14. 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).
    15. Corsini, Alessandro & Delibra, Giovanni & Pizzuti, Isabella & Tajalli-Ardekani, Erfan, 2023. "Challenges of renewable energy communities on small Mediterranean islands: A case study on Ponza island," Renewable Energy, Elsevier, vol. 215(C).
    16. Guglielmina Mutani & Pamela Vocale & Kavan Javanroodi, 2023. "Toward Improved Urban Building Energy Modeling Using a Place-Based Approach," Energies, MDPI, vol. 16(9), pages 1-17, May.
    17. 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).
    18. Iflah Javeed & Rahmat Khezri & Amin Mahmoudi & Amirmehdi Yazdani & G. M. Shafiullah, 2021. "Optimal Sizing of Rooftop PV and Battery Storage for Grid-Connected Houses Considering Flat and Time-of-Use Electricity Rates," Energies, MDPI, vol. 14(12), pages 1-19, June.
    19. 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).
    20. Gong, Jun & Chew, Lup Wai & Lee, Poh Seng, 2024. "Theoretical model for high-rise solar chimneys and optimum shape for uniform flowrate distribution," Energy, Elsevier, vol. 298(C).

    More about this item

    Statistics

    Access and download statistics

    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:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-37131-6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.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.