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Building Retrofit Measures and Design: A Probabilistic Approach for LCA

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  • Claudio Favi

    (Department of Engineering and Architecture, Parco Area delle Scienze 181/A, Università di Parma, 43124 Parma, Italy)

  • Elisa Di Giuseppe

    (Department of Building, Civil Engineering and Architecture, Università Politecnica delle Marche, via Brecce Bianche 12, 60131 Ancona, Italy)

  • Marco D’Orazio

    (Department of Building, Civil Engineering and Architecture, Università Politecnica delle Marche, via Brecce Bianche 12, 60131 Ancona, Italy)

  • Marta Rossi

    (Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, via Brecce Bianche 12, 60131 Ancona, Italy)

  • Michele Germani

    (Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, via Brecce Bianche 12, 60131 Ancona, Italy)

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.

Suggested Citation

  • Claudio Favi & Elisa Di Giuseppe & Marco D’Orazio & Marta Rossi & Michele Germani, 2018. "Building Retrofit Measures and Design: A Probabilistic Approach for LCA," Sustainability, MDPI, vol. 10(10), pages 1-15, October.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:10:p:3655-:d:175205
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    References listed on IDEAS

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    Cited by:

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    3. Xabat Oregi & Rufino Javier Hernández & Patxi Hernandez, 2020. "Environmental and Economic Prioritization of Building Energy Refurbishment Strategies with Life-Cycle Approach," Sustainability, MDPI, vol. 12(9), pages 1-22, May.
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    6. Andrea Urbinati & Davide Chiaroni & Paolo Maccarrone & Antonio Messeni Petruzzelli & Federico Frattini, 2022. "A multidimensional scorecard of KPIs for retrofit measures of buildings: A systematic literature review," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 29(6), pages 1968-1979, November.
    7. Elisa Di Giuseppe & Marco D’Orazio & Guangli Du & Claudio Favi & Sébastien Lasvaux & Gianluca Maracchini & Pierryves Padey, 2020. "A Stochastic Approach to LCA of Internal Insulation Solutions for Historic Buildings," Sustainability, MDPI, vol. 12(4), pages 1-35, February.
    8. Antonio Dominguez-Delgado & Helena Domínguez-Torres & Carlos-Antonio Domínguez-Torres, 2020. "Energy and Economic Life Cycle Assessment of Cool Roofs Applied to the Refurbishment of Social Housing in Southern Spain," Sustainability, MDPI, vol. 12(14), pages 1-35, July.
    9. Nima Pirhadi & Xiaowei Tang & Qing Yang & Fei Kang, 2018. "A New Equation to Evaluate Liquefaction Triggering Using the Response Surface Method and Parametric Sensitivity Analysis," Sustainability, MDPI, vol. 11(1), pages 1-24, December.
    10. Galimshina, Alina & Moustapha, Maliki & Hollberg, Alexander & Padey, Pierryves & Lasvaux, Sébastien & Sudret, Bruno & Habert, Guillaume, 2022. "Bio-based materials as a robust solution for building renovation: A case study," Applied Energy, Elsevier, vol. 316(C).

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