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Statistical method to identify robust building renovation choices for environmental and economic performance

Authors: Alina Galimshina; Maliki Moustapha; Alexander Hollberg; Pierryves Padey; Sébastien Lasvaux; Bruno Sudret; Guillaume Habert;

Statistical method to identify robust building renovation choices for environmental and economic performance

Abstract

Building renovation is urgently required to decrease the energy consumption of the existing building stock and reduce greenhouse gas emissions coming from the building sector. Selecting an appropriate renovation strategy is challenging due to the long building service life and consequent uncertainties. In this paper, we propose a new framework for the robust assessment of renovation strategies in terms of environmental and economic performance of the building's life cycle. First, we identify the possible renovation strategies and define the probability distributions for 74 uncertain parameters. Second, we create an integrated workflow for Life Cycle Assessment (LCA) and Life Cycle Cost analysis (LCC) and make use of Sobol’ indices to identify a prioritization strategy for the renovation. Finally, the selected renovation scenario is assessed by metamodeling techniques to calculate its robustness. The results of three case studies of residential buildings from different construction periods show that the priority in renovation should be given to the heating system replacement, which is followed by the exterior wall insulation and windows. This result is not in agreement with common renovation practices and this discrepancy is discussed at the end of the paper.

Building and Environment, 183

ISSN:0360-1323

ISSN:0360-1323

Countries
Switzerland, Switzerland
Keywords

[STAT.AP]Statistics [stat]/Applications [stat.AP], Life cycle cost, Life cycle assessment, Life cycle assessment; Life cycle cost; Uncertainty quantification; Building renovation, [SPI.GCIV.RHEA]Engineering Sciences [physics]/Civil Engineering/Rehabilitation, Building renovation, Uncertainty quantification

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    41
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
41
Top 1%
Top 10%
Top 10%
Green
hybrid