LCA of emerging technologies: addressing high uncertainty on inputs' variability when performing global sensitivity analysis

Abstract

In the life cycle assessment (LCA) context, global sensitivity analysis (GSA) has been identified by several authors as a relevant practice to enhance the understanding of the model's structure and ensure reliability and credibility of the LCA results. GSA allows establishing a ranking among the input parameters, according to their influence on the variability of the output. Such feature is of high interest in particular when aiming at defining parameterized LCA models. When performing a GSA, the description of the variability of each input parameter may affect the results. This aspect is critical when studying new products or emerging technologies, where data regarding the model inputs are very uncertain and may cause misleading GSA outcomes, such as inappropriate input rankings. A systematic assessment of this sensitivity issue is now proposed. We develop a methodology to analyze the sensitivity of the GSA results (i.e. the stability of the ranking of the inputs) with respect to the description of such inputs of the model (i.e. the definition of their inherent variability). With this research, we aim at enriching the debate on the application of GSA to LCAs affected by high uncertainties. We illustrate its application with a case study, aiming at the elaboration of a simple model expressing the life cycle greenhouse gas emissions of enhanced geothermal systems (EGS) as a function of few key parameters. Our methodology allows identifying the key inputs of the LCA model, taking into account the uncertainty related to their description.

Global sensitivity analysis as a support for the generation of simplified building stock energy models

“…Limitations of this methodology lie in the need for detailed input data on the building stock necessary to generate probability distributions of input parameters. Lacking sufficiently detailed information and making imprecise assumptions might result in inaccurate results [71]. However, the increasing availability of GIS data on buildings will enhance and facilitate the generation of probability distributions, especially for parameters related to geometry and construction characteristics.…”

Life Cycle Assessment for the Design of Chemical Processes, Products, and Supply Chains

“…Having quantified the uncertainty in LCA results, the LCA practitioner can reduce the uncertainty by increasing data accuracy of key parameters using the methods discussed in Section 3. A powerful method to identify these key parameters is global sensitivity analysis (181,182), which analyzes how strongly each parameter affects the overall LCA results.…”

Life cycle assessment of emerging technologies: Evaluation techniques at different stages of market and technical maturity

“…Accounting for uncertainty is critical in LCAs of both commercial technologies (discussed in Gregory et al., ; Igos, Benetto, Meyer, Baustert, & Othoniel, ; Mendoza Beltran et al., ; Lloyd and Ries, ) as well as emerging technologies. Some studies (Lacirignola, Blanc, Girard, Pérez‐López, & Blanc, ; Ravikumar et al., ) have proposed new methods for accounting for uncertainty in LCA of emerging technologies using sensitivity analyses to aid in identifying key parameters affecting a technology's environmental impacts. Integrated Assessment Models have been used to develop future demand scenarios to account for market conditions surrounding demand for current technologies (Mendoza Beltran et al., ) or deployment of emerging technologies (Cucurachi, Borgonovo, & Heijungs, ; Steubing, Reinhard, Zah, & Ludwig, ).…”