How Long Do Buildings Live: A Systematic Review and Meta-Analysis of Global Building Lifetimes.
- 1Institute of Environmental Engineering, ETH Zurich , Zurich8093, Switzerland.
- 2Department of Energy and Process Engineering, Norwegian University of Science and Technology, Trondheim7034, Norway.
Abstract
Building lifetime is a foundational parameter for modeling stock dynamics, informing environmental impact assessment and urban development, yet current lifetime assumptions frequently lack empirical grounding. Although well-established in medicine and demography, survival analysis concepts have not penetrated building stock research to the same extent. This study bridges this gap through a systematic review and meta-analysis of 258 median building lifetime estimates across 46 global studies. Central to our analysis is right-censoring, when a building's demolition remains unobserved at the end of the observation period, which, if unaccounted for in estimation, leads to underestimated lifetimes. We systematize five estimation approaches based on data type and the capacity to account for right-censoring, describe the currently available empirical evidence, and apply a meta-regression to identify significant predictors of median lifetimes: world region, use class, structural material, and right-censoring bias, the latter underestimating building lifetimes by 50% (95% CI: 49-51%). Of the five estimation approaches identified, three inherently consider right-censoring, one inherently cannot correct for it, and one requires an active correction step that is frequently omitted. Our work identifies critical data gaps and offers targeted recommendations for users and producers of lifetime estimates to improve transparency, reproducibility, and methodological rigor.
Related
- Development and energy savings analysis of active thermal switches with thermal storage for dynamic building envelopes in residential buildings
- Environmental antimicrobial resistance and human infectious disease outcomes: a global one health systematic review and meta-analysis of observational studies.
- Where is the evidence? A global systematic review of sanitation system resilience to climate hazards
- Digital Twins for Building Sustainability: A Life Cycle-Oriented Critical Review
- Consistent estimates of carbonyl sulfide and methane stratospheric lifetimes retrieved from AirCore profiles at different latitudes
BibTeX
@article{krych2026long,
title = {{How Long Do Buildings Live: A Systematic Review and Meta-Analysis of Global Building Lifetimes.}},
author = {Kamila Krych and Nils Dittrich and Daniel B Müller and Stefanie Hellweg},
journal = {Environmental science \& technology},
year = {2026},
month = sep,
doi = {10.1021/acs.est.6c06705},
url = {https://europepmc.org/article/MED/42916245},
note = {CC BY},
}
RIS
TY - JOUR
TI - How Long Do Buildings Live: A Systematic Review and Meta-Analysis of Global Building Lifetimes.
AU - Kamila Krych
AU - Nils Dittrich
AU - Daniel B Müller
AU - Stefanie Hellweg
PY - 2026
DA - 2026/09/01
JO - Environmental science & technology
DO - 10.1021/acs.est.6c06705
UR - https://europepmc.org/article/MED/42916245
AB - Building lifetime is a foundational parameter for modeling stock dynamics, informing environmental impact assessment and urban development, yet current lifetime assumptions frequently lack empirical grounding. Although well-established in medicine and demography, survival analysis concepts have not penetrated building stock research to the same extent. This study bridges this gap through a systematic review and meta-analysis of 258 median building lifetime estimates across 46 global studies. Central to our analysis is right-censoring, when a building's demolition remains unobserved at the end of the observation period, which, if unaccounted for in estimation, leads to underestimated lifetimes. We systematize five estimation approaches based on data type and the capacity to account for right-censoring, describe the currently available empirical evidence, and apply a meta-regression to identify significant predictors of median lifetimes: world region, use class, structural material, and right-censoring bias, the latter underestimating building lifetimes by 50% (95% CI: 49-51%). Of the five estimation approaches identified, three inherently consider right-censoring, one inherently cannot correct for it, and one requires an active correction step that is frequently omitted. Our work identifies critical data gaps and offers targeted recommendations for users and producers of lifetime estimates to improve transparency, reproducibility, and methodological rigor.
SN - 0013-936X
SN - 1520-5851
ER -