Service Life Assessment of Building Components: Lessons from a Cross-Country Empirical Comparison for Windows, Heating Systems, and Roofs

Accurate service life (SL) data for building components are a critical yet poorly constrained input for life cycle assessment (LCA). Reference service life (RSL) values published in national frameworks are typically derived from technical standards rather than empirical observation. This paper compares two independent, methodologically aligned empirical datasets for windows, heating systems, and roofs for Belgium and The Netherlands. SL distributions are estimated using Weibull survival analysis, selected with AICc model comparison, and differences between survival functions are assessed using a Bonferroni-corrected Log-Rank test. Estimates are benchmarked against Belgian and Dutch RSLs. Two sets of insights emerge. First, on SL estimates: robust cross-national divergence is found only for flat roofs, is sensitivity-dependent for windows and pitched roofs and could not be assessed for heating systems due to incompatible definitions across surveys. Second, on survey methodology: both datasets query a single renovation cycle, biasing SL estimates towards longer values, particularly for shorter-lived components, underscoring that definitional alignment and multi-cycle survey design are essential for valid cross-national comparison. Together with the empirical SL estimates, these methodological lessons, of broader relevance beyond the present datasets, provide practical input for LCA and renovation planning in Belgium and The Netherlands, and guide future survey-based SL research.

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Journal
Buildings
Published
2026-09-25
DOI
https://doi.org/10.3390/buildings16193821
Primary Topic
Environmental Impact and Sustainability
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article
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Service Life Assessment of Building Components: Lessons from a Cross-Country Empirical Comparison for Windows, Heating Systems, and Roofs

Griet Verbeeck, B Gepts, Veerle Vandersmissen
Buildings
Environmental Impact and Sustainability
article

Service Life Assessment of Building Components: Lessons from a Cross-Country Empirical Comparison for Windows, Heating Systems, and Roofs

Griet Verbeeck, B Gepts, Veerle Vandersmissen
article en

Abstract

Accurate service life (SL) data for building components are a critical yet poorly constrained input for life cycle assessment (LCA). Reference service life (RSL) values published in national frameworks are typically derived from technical standards rather than empirical observation. This paper compares two independent, methodologically aligned empirical datasets for windows, heating systems, and roofs for Belgium and The Netherlands. SL distributions are estimated using Weibull survival analysis, selected with AICc model comparison, and differences between survival functions are assessed using a Bonferroni-corrected Log-Rank test. Estimates are benchmarked against Belgian and Dutch RSLs. Two sets of insights emerge. First, on SL estimates: robust cross-national divergence is found only for flat roofs, is sensitivity-dependent for windows and pitched roofs and could not be assessed for heating systems due to incompatible definitions across surveys. Second, on survey methodology: both datasets query a single renovation cycle, biasing SL estimates towards longer values, particularly for shorter-lived components, underscoring that definitional alignment and multi-cycle survey design are essential for valid cross-national comparison. Together with the empirical SL estimates, these methodological lessons, of broader relevance beyond the present datasets, provide practical input for LCA and renovation planning in Belgium and The Netherlands, and guide future survey-based SL research.

BuildingsVol. 16(19)
Hasselt University (BE)
Responsible consumption and production
Openalex Percentile: Top 19%
Environmental Impact and Sustainability
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Service Life Assessment of Building Components: Lessons from a Cross-Country Empirical Comparison for Windows, Heating Systems, and Roofs — Griet Verbeeck, B Gepts, et al. · Buildings (2026) | TGRS Research Map | TGRS