Challenges in predicting the impact of climate change on thermal building performance through simulation : A systematic review
Duan, Zhuocheng ; de Wilde, Pieter LU
; Attia, Shady
and Zuo, Jian
(2025)
In Applied Energy
382.
- Abstract
The intricate relationship between climate change and the building sector is characterized by a self-reinforcing loop. Rising temperatures driven by global warming will inevitably impact heating and cooling energy, while buildings simultaneously contribute significantly to carbon emissions throughout their lifecycle, further exacerbating climate change. However, current knowledge regarding the interaction between climate change and the building sector remains fragmented, often limited to specific regions, climate zones, and mitigation strategies, lacking a holistic view. This systematic review analyzes 212 peer-reviewed articles to examine current approaches, challenges, and future directions in predicting building thermal performance... (More)
The intricate relationship between climate change and the building sector is characterized by a self-reinforcing loop. Rising temperatures driven by global warming will inevitably impact heating and cooling energy, while buildings simultaneously contribute significantly to carbon emissions throughout their lifecycle, further exacerbating climate change. However, current knowledge regarding the interaction between climate change and the building sector remains fragmented, often limited to specific regions, climate zones, and mitigation strategies, lacking a holistic view. This systematic review analyzes 212 peer-reviewed articles to examine current approaches, challenges, and future directions in predicting building thermal performance under climate change. The analysis covers key aspects, including climate data, methods/tools for future weather file generation, computational methods and performance metrics. The reliance on outdated climate scenarios and models undermines the accuracy and applicability of predictions. Despite a general rise in cooling and decline in heating, considerable variances occur among geographies, climate data, and carbon emissions. This review highlights several important gaps, including 1) inconsistencies in geographical disparities and data quality; 2) challenges in scaling from individual buildings to district-level predictions; 3) the need for more advanced control and modeling capabilities in simulation; and 4) insufficient consideration of robust, resilient design strategies to address uncertainties posed by climate change, localized microclimate, and extremes. In addition, significant methodological inconsistencies across studies hinder reliable comparisons and potentially undermine prediction accuracy. The review proposes the development of a standardized protocol to guide researchers while preserving context-specific investigations. This aims to incorporate updated climate scenarios, high-resolution data, and robust modeling techniques to enhance prediction accuracy under a changing climate. Breaking this vicious cycle requires an integrated approach combining building science, climate science, and urban planning.
(Less)
- author
- Duan, Zhuocheng
; de Wilde, Pieter
LU
; Attia, Shady
and Zuo, Jian
- organization
- publishing date
- 2025-03
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Downscaling methods, Energy consumption, Energy saving, Future weather files, Global warming, Greenhouse gas (GHG)/carbon emissions, Heating and cooling energy demand
- in
- Applied Energy
- volume
- 382
- article number
- 125331
- publisher
- Elsevier
- external identifiers
-
- scopus:85214583184
- ISSN
- 0306-2619
- DOI
- 10.1016/j.apenergy.2025.125331
- language
- English
- LU publication?
- yes
- id
- 2cc8610c-f176-4344-861c-81b234645eed
- date added to LUP
- 2025-03-11 14:23:20
- date last changed
- 2025-03-11 14:24:20
@article{2cc8610c-f176-4344-861c-81b234645eed,
abstract = {{<p>The intricate relationship between climate change and the building sector is characterized by a self-reinforcing loop. Rising temperatures driven by global warming will inevitably impact heating and cooling energy, while buildings simultaneously contribute significantly to carbon emissions throughout their lifecycle, further exacerbating climate change. However, current knowledge regarding the interaction between climate change and the building sector remains fragmented, often limited to specific regions, climate zones, and mitigation strategies, lacking a holistic view. This systematic review analyzes 212 peer-reviewed articles to examine current approaches, challenges, and future directions in predicting building thermal performance under climate change. The analysis covers key aspects, including climate data, methods/tools for future weather file generation, computational methods and performance metrics. The reliance on outdated climate scenarios and models undermines the accuracy and applicability of predictions. Despite a general rise in cooling and decline in heating, considerable variances occur among geographies, climate data, and carbon emissions. This review highlights several important gaps, including 1) inconsistencies in geographical disparities and data quality; 2) challenges in scaling from individual buildings to district-level predictions; 3) the need for more advanced control and modeling capabilities in simulation; and 4) insufficient consideration of robust, resilient design strategies to address uncertainties posed by climate change, localized microclimate, and extremes. In addition, significant methodological inconsistencies across studies hinder reliable comparisons and potentially undermine prediction accuracy. The review proposes the development of a standardized protocol to guide researchers while preserving context-specific investigations. This aims to incorporate updated climate scenarios, high-resolution data, and robust modeling techniques to enhance prediction accuracy under a changing climate. Breaking this vicious cycle requires an integrated approach combining building science, climate science, and urban planning.</p>}},
author = {{Duan, Zhuocheng and de Wilde, Pieter and Attia, Shady and Zuo, Jian}},
issn = {{0306-2619}},
keywords = {{Downscaling methods; Energy consumption; Energy saving; Future weather files; Global warming; Greenhouse gas (GHG)/carbon emissions; Heating and cooling energy demand}},
language = {{eng}},
publisher = {{Elsevier}},
series = {{Applied Energy}},
title = {{Challenges in predicting the impact of climate change on thermal building performance through simulation : A systematic review}},
url = {{http://dx.doi.org/10.1016/j.apenergy.2025.125331}},
doi = {{10.1016/j.apenergy.2025.125331}},
volume = {{382}},
year = {{2025}},
}