A Method to Facilitate Uncertainty Analysis in LCAs of Buildings

Abstract

Life cycle assessment (LCA) is increasingly becoming a common technique to assess the embodied energy and carbon of buildings and their components over their life cycle. However, the vast majority of existing LCAs result in very definite, deterministic values which carry a false sense of certainty and can mislead decisions and judgments. This article tackles the lack of uncertainty analysis in LCAs of buildings by addressing the main causes for not undertaking this important activity. The research uses primary data for embodied energy collected from European manufacturers as a starting point. Such robust datasets are used as inputs for the stochastic modelling of uncertainty through Monte Carlo algorithms. Several groups of random samplings between 10 1 and 10 7 are tested under two scenarios: data are normally distributed (empirically verified) and data are uniformly distributed. Results show that the hypothesis on the data no longer influences the results after a high enough number of random samplings (10 4). This finding holds true both in terms of mean values and standard deviations and is also independent of the size of the life cycle inventory (LCI): it occurs in both large and small datasets. Findings from this research facilitate uncertainty analysis in LCA. By reducing significantly the amount of data necessary to infer information about uncertainty, a more widespread inclusion of uncertainty analysis in LCA can be encouraged in assessments from practitioners and academics alike.

Assessing the Climate Change Impacts of Biogenic Carbon in Buildings: A Critical Review of Two Main Dynamic Approaches

“…This would confirm the extent and level of certainty to which GWP bio can be used as a proxy for a full DLCA. A better assessment of the uncertainty of dynamic approaches would also be consistent with recent recommendations for a wider use of sensitivity and uncertainty analysis in building LCA [171,177].…”

On the Imaginary Accuracy of the LCA on the Basis of the Houseboat in Hamburg (Holistic Approach)

“…In this case, temporal characteristics of 50 years of a houseboat lifetime and spatial characteristics (Hamburg) is generalized in one single value. As the title of the paper implies and many authors such as Pompon et al [6] or Zhang et al [7] confirm, deterministic values in both input values and results carry an illusion of great certainty achieved in the LCA process. Metaphorically speaking, the outcome of LCA software models deny the existence of the elephant in the room.…”

“…Various methods have been developed for assessing uncertainty in the LCA such as possibility theory applied to the uncertainty analysis of life cycle inventory [8], fuzzy theory, data quality indicators, expert judgement or stochastic modelling; conducting the uncertainty propagation by using the Monte Carlo simulation ** . Pompon et al [6] tested the lastmentioned method on the two entries from the Life Cycle Inventory from the manufacture of one functional unit of double skin façade, a flat glass cladding system to prove that the collection of extensive data is not necessary for undertaking an uncertainty parameter analysis (precisely expressed, for the characterization of the data distribution). Similarly, Zhang et al [7] used a statistical method to calculate the probability distribution of the gathered data and Monte Carlo simulation to test randomly sampled inventory data on the LCA of a bridge.…”

From Zero Emission Buildings (ZEB) to Zero Emission Neighbourhoods (ZEN): A Mapping Review of Algorithm-Based LCA

“…The review shows that advances have been made toward applying global sensitivity analysis [59,60]; however, accounting simultaneously for varying parameters (i.e., design, scenario) and involved uncertainties in LCA calculations is identified as another under-researched method. The importance of accounting for uncertainties in LCA has been already been discussed in previous literature [40,45,[59][60][61][62][63][64][65][66][67][68] and also recognized in the ISO 14044 standard [69]. Sensitivity analyses can be used to identify the dominant parameters of the expected overall LCA of the considered system.…”