Workshop 07: Advanced Analysis Techniques in LCA

Main Presenter: Lise Laurin

Co-Authors:Miguel Hernandez

Workshop Format: Short input by selected speakers

In this workshop, you will learn how to use some new techniques which improve our ability to use LCA.
Often, there is sufficient uncertainty in our models that the results seem unsubstantiated. We’ll discuss how to leverage uncertainty to help develop robust conclusions.
When applying the pedigree matrix, we often find we’re applying it for both the amount of an input or output and for the fit of the dataset selected. We’ll work through a second pedigree matrix to assess fit for purpose.
Underspecification supports product development and data gap filling by enabling users to consider “sets” of materials or services, such as “all thermoplastics” or “all plastics.”
Traditional single scores are often used to assess tradeoffs, but rely on a few experts’ opinions as to what will really change life as we know it in the future. Stochastic Multi-Attribute Analysis (SMAA) provides a scientific way to handle tradeoffs.
Adapting Design of Experiments (DOE) from empirical research enables an assessment of a broad scope of products, enabling broader claims and a better foundation for review of automated LCAs.
For each of these, we will use an example and explore hands-on how to address it using the technique.

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