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Sustainability 2018, 10(10), 3655; https://doi.org/10.3390/su10103655 (registering DOI)

Building Retrofit Measures and Design: A Probabilistic Approach for LCA

1
Department of Engineering and Architecture, Parco Area delle Scienze 181/A, Università di Parma, 43124 Parma, Italy
2
Department of Building, Civil Engineering and Architecture, Università Politecnica delle Marche, via Brecce Bianche 12, 60131 Ancona, Italy
3
Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, via Brecce Bianche 12, 60131 Ancona, Italy
*
Author to whom correspondence should be addressed.
Received: 26 July 2018 / Revised: 12 September 2018 / Accepted: 8 October 2018 / Published: 12 October 2018
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Abstract

Green building design and architecture have become widespread tenets in the development of sustainable buildings. In this context, the use of sustainable materials and the awareness of resource/energy consumption are strategic aspects to consider for the improvement of building performances. This paper presents a new and structured approach to address uncertainty and sensitivity analysis in Life Cycle Assessment (LCA) to support the decision-making process in building renovation. This “probabilistic” approach to LCA allows for the obtaining of results expressed as ranges of environmental impacts and for alternative solutions, offering an idea of the meaning of input parameters’ uncertainties and their influence on the result. The approach includes (i) the assessment of inputs’ uncertainties (represented by Probability Density Functions—PDF); (ii) the data sampling; and (iii) the uncertainty propagation (Monte Carlo method). Variance decomposition techniques have been used to sample inputs’ PDFs and assess their impact on the LCA result distribution (sensitivity analysis). The methodology application is illustrated through a case study where three building retrofit measures were assessed. Results provide an insight about the uncertainties of LCA indicators in terms of climate change and nonrenewable energy. The input parameters related to the use phase are confirmed as the most influential in building LCA. View Full-Text
Keywords: probabilistic LCA; building retrofit; inputs’ uncertainties; Monte Carlo; sensitivity analysis probabilistic LCA; building retrofit; inputs’ uncertainties; Monte Carlo; sensitivity analysis
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Favi, C.; Di Giuseppe, E.; D’Orazio, M.; Rossi, M.; Germani, M. Building Retrofit Measures and Design: A Probabilistic Approach for LCA. Sustainability 2018, 10, 3655.

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