Method to analyse the contribution of material's sensitivity in buildings' environmental impact

Hoxha, Endrit; Habert, Guillaume; Chevalier, Jacques; Bazzana, Manuel; Roy, Robert Le

doi:10.1016/j.jclepro.2013.10.056

Cited by 83 publications

(44 citation statements)

References 32 publications

(28 reference statements)

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“…As a result, the following life cycle stages are considered: (i) the production stage (modules A1-A3), (ii) the use stage (modules B2 maintenance, B4 replacement, and B6 operational energy use), and (iii) the End of Life (EoL) stage (modules C1-C4). Based on the literature survey and reports of LCA practitioners, the construction processes are less relevant in the LCA of building components than the operational ones [37,[52][53][54]. The distinction between modules B2 (maintenance), B3 (repair), B4 (replacement) is considered according to EeBGuide guidance recommendations [55].…”

Section: Goal and Scope Definitionmentioning

confidence: 99%

“…Indeed, neglecting uncertainties and variabilities of various life cycle parameters and scenarios may affect the results' reliability and robustness for final decisions.In the state of the art, several studies in the building field deal with "probabilistic" approaches to LCA [31][32][33][34]. Some works especially focus on materials or structural components, mainly addressing parameter uncertainties, which can be traced from more than one source, such as material quantities, the unitary environmental impact of materials, heat transmission losses, service life (SL) estimation, etc.For instance, Hoxha et al investigated the impact of construction materials uncertainties on LCA reliability in few works [35][36][37]. In [37], the authors used the statistical method to identify parameters having the greatest contribution to the uncertainty of the final result.…”

mentioning

confidence: 99%

“…Some works especially focus on materials or structural components, mainly addressing parameter uncertainties, which can be traced from more than one source, such as material quantities, the unitary environmental impact of materials, heat transmission losses, service life (SL) estimation, etc.For instance, Hoxha et al investigated the impact of construction materials uncertainties on LCA reliability in few works [35][36][37]. In [37], the authors used the statistical method to identify parameters having the greatest contribution to the uncertainty of the final result. They focused on the service life of the building component, the environmental impact of building component's production, and the amount of material used within the building.…”

mentioning

confidence: 99%

“…For instance, Hoxha et al investigated the impact of construction materials uncertainties on LCA reliability in few works [35][36][37]. In [37], the authors used the statistical method to identify parameters having the greatest contribution to the uncertainty of the final result.…”

mentioning

confidence: 99%

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A Stochastic Approach to LCA of Internal Insulation Solutions for Historic Buildings

Giuseppe

D’Orazio

et al. 2020

Sustainability

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Internal insulation is a typical renovation solution in historic buildings with valuable façades. However, it entails moisture-related risks, which affect the durability and life-cycle environmental performance. In this context, the EU project RIBuild developed a risk assessment method for both hygrothermal and life-cycle performance of internal insulation, to support decision-making. This paper presents the stochastic Life Cycle Assessment method developed, which couples the LCA model to a Monte-Carlo simulation, providing results expressed by probability distributions. It is applied to five insulation solutions, considering different uncertain input parameters and building heating scenarios. In addition, the influence of data variability and quality on the result is analyzed, by using input data from two sources: distributions derived from a generic Life Cycle Inventory database and "deterministic" data from Environmental Product Declarations. The outcomes highlight remarkable differences between the two datasets that lead to substantial variations on the systems performance ranking at the production stage. Looking at the life-cycle impact, the general trend of the output distributions is quite similar among simulation groups and insulation systems. Hence, while a ranking of the solutions based on a "deterministic" approach provides misleading information, the stochastic approach provides more realistic results in the context of decision-making.Sustainability 2020, 12, 1535 2 of 35 and cultural values. For this reason, internal insulation is generally considered as a valid alternative to external insulation in order to improve the buildings' thermal performance. However, its design and application could be technically complex entailing several risks [4,5]. For instance, the risks of internal dampness, mold growth, interstitial condensation, and freeze-thaw damage may further lead to structural deterioration, aesthetical damages, and eventually a reduced service life for the whole renovation intervention. At present, there is a lack of knowledge on how to apply correctly internal insulations and handle the inherent risks. The EU project RIBuild (Robust Internal Thermal Insulation of Historic Buildings) aims to fill this gap, by investigating how and under which conditions internal insulation can be safely used [6].Regarding insulation materials and systems for historical buildings, there is a large number of products available in the market, including natural materials (e.g., cellulose, cork), conventional materials (e.g., mineral wool, glass wool, polyurethane, expanded polystyrene, insulating plaster) and other advanced materials (e.g., calcium silicate, aerated concrete) [7,8]. According to Vereecken, internal insulation systems can be categorized into three types: (i) condensate-preventing insulation systems, based on vapor-tight insulation materials or metal foil; (ii) condensate-limiting insulation systems with normal or smart vapor barrier; (iii) condensate-tolerating insulation systems with capillary act...

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Section: Goal and Scope Definitionmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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A Stochastic Approach to LCA of Internal Insulation Solutions for Historic Buildings

Giuseppe

D’Orazio

et al. 2020

Sustainability

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“…In most of the previous studies on uncertainty in LCA, the focus has been on the uncertainties in the emission factors. However, as discussed in Section 2, other sources of uncertainty, such as the variability of the expected service life of components and amount of materials play an important role and have a significant influence on the results (Aktas, 2011;Hoxha, Habert, Chevalier, Bazzana, & Le Roy, 2014). In order to illustrate the consequences of considering uncertainty in different categories of input factors, Monte Carlo simulations have been carried out and uncertainties have been included at various levels: (1) for emission factors only; (2) for emission factors and material amounts; (3) emission factors, material amounts and expected service life.…”

Section: Monte Carlo Simulationsmentioning

confidence: 99%

Consideration of uncertainties in LCA for infrastructure using probabilistic methods

Ivanov

Honfí

Santandrea

et al. 2019

Structure and Infrastructure Engineering

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The construction and usage of transport infrastructure are major causes of greenhouse gas emissions and energy consumption. The effects of resource consumption and pollutant emissions are often quantified through Life Cycle Assessment (LCA) models. All decisions made in infrastructure projects during the whole life cycle are afflicted by uncertainty, e.g. physical properties of materials or amount of pollutants emitted by certain processes. The pervasive role of uncertainty is reflected in LCA models, which therefore should consider uncertainty from various sources and provide a sound quantification of their effects. The aim of the work presented in this paper is to give an overview of different sources of uncertainty in LCA of infrastructure projects and to describe systematic methods to evaluate their influence on the results. The possibility of including uncertainty in a LCA-tool for infrastructure is presented, studying the sensitivity of the model output to the input parameters and two alternative approaches for propagation of uncertainty using two case studies. It is shown that, besides the influence of uncertainty in emission factors, other inputs such as material amounts and service life could contribute significantly to the variability of model output and has to be considered if reliable results are sought. ARTICLE HISTORY

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Analyse des Ressourceneinsatzes und der Umweltwirkung von detailliert modellierten Außenwandaufbauten

Schwede

Störl

2017

Bautechnik

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Fünf Außenwandkonstruktionen unterschiedlicher Bauweisen mit gleichem U‐Wert (konform zur EnEV 2014) werden hinsichtlich des Ressourcenbedarfs (Primärenergie) und der Umweltwirkung (Treibhausgaspotenzial) analysiert. Die Bauteilaufbauten wurden detailliert modelliert, sodass die Analyse neben den funktionsbestimmenden Bauteilschichten auch den Einfluss der Befestigungsmittel und der Sekundärkonstruktionselemente abbildet. Bauteilaufbauten werden getrennt nach Material‐ und Funktionsgruppen ökologisch bewertet. Zum einen wird gezeigt, dass einzelne Materialgruppen und besonders auch Elemente der Sekundärkonstruktion, Befestigungsmittel und Kleinteile in der Konstruktion zwar in der Massenbilanz marginale Bedeutung haben, aber doch überdurchschnittlich zum Ressourceneinsatz und zur Umweltwirkung beitragen. Auf der anderen Seite wird gezeigt, dass zusätzliche Dämmschichtdicken (über das heute übliche Maß hinaus) in der Gesamtbilanz des Gebäudes nur einen geringen Anteil am Ressourceneinsatz und der Umweltwirkung hätten. So wird argumentiert, dass die Analyse des Ressourceneinsatzes und der Umweltwirkungen und die entsprechende Optimierung von Bauelementen parallel zur bauphysikalischen und konstruktiven Durchbildung durchgeführt werden sollte. Die Gesamtbilanzierung des Gebäudes im Lebenszyklus hingegen liefert bei erheblichem Aufwand für die Planer nur einen geringen Nutzen für die Optimierung von nachhaltigen Gebäuden.

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Method to analyse the contribution of material's sensitivity in buildings' environmental impact

Cited by 83 publications

References 32 publications

A Stochastic Approach to LCA of Internal Insulation Solutions for Historic Buildings

A Stochastic Approach to LCA of Internal Insulation Solutions for Historic Buildings

Consideration of uncertainties in LCA for infrastructure using probabilistic methods

Analyse des Ressourceneinsatzes und der Umweltwirkung von detailliert modellierten Außenwandaufbauten

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