An Expert View on Data and Modelling for Planning Domestic Retrofit
Auteur(s): |
Marianna J. Coulentianos
Danielle Abbey Christy Tsz So Wil O. C. Ward |
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Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | Buildings, 27 mars 2024, n. 4, v. 14 |
Page(s): | 887 |
DOI: | 10.3390/buildings14040887 |
Abstrait: |
The transition to Net Zero rests partly on the widespread adoption of energy-efficient retrofit measures for domestic dwellings. The scale of retrofit efforts is extensive, as up to 80% of the UK’s domestic housing stock for 2050 has already been built. To address the scope, data and models will play a crucial role in informing design decisions and optimising retrofit strategies. While new methods and tools for data and modelling in retrofit continue to be developed, the perspectives of professionals using these tools on their quality remain mainly absent from discussion across academia and practice. This study investigated the experiences and perceptions of data and modelling from professionals working in the planning stages of domestic retrofit, serving as a needs-finding exercise driving retrofit planning. Through semi-structured interviews and qualitative coding, the results highlight a critical trade-off between precision, confidence, and the burden of data collection. These findings underscore the need to balance precision, ease of use, and adaptability in data and modelling retrofit tools. Issues around data availability and wider access to data and modelling results across stakeholders emerged as a missed opportunity. |
Copyright: | © 2024 by the authors; licensee MDPI, Basel, Switzerland. |
License: | Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original. |
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10773379 - Publié(e) le:
29.04.2024 - Modifié(e) le:
05.06.2024