|
Description
|
In chapters 5 and 11 it has already been explained that in each life cycle technique, thus also in Life Cycle Sustainability Assessment (LCSA), the goal and scope are defined, specifying (1) the function fulfilled by the considered product(s), expressed in terms of the functional unit, and (2) the product system that provides the service or function. In our chapter, we focus on the second step that encompasses the compilation of the life cycle inventory (LCI) results, that is, the quantification of the elementary flows, pressures or conditions, of the product system scaled with respect to the chosen functional unit (Figure 14.1). This is a basic notion of (envi- ronmental) life cycle assessment (LCA) (Heijungs and Suh, 2002), but also of LCSA (Valdivia et al., 2021, 2013). Elementary flows (material or energy) consist of all the emissions to the natural environment and all the natural resources extracted from it. Pressures and conditions need to be interpreted in a broad sense, especially in the context of LCSA, including for example also labour conditions. For LCSA, the additional challenge is to consistently consider all types of LCI results as relevant for the three pillars and potentially their integrated effect. What we present is pertinent for all types of LCSA, most notably both the three-pillar approach (Finkbeiner et al., 2010; Klöpffer, 2008) and the integrated approach for LCSA (Guinée, 2016; Guinée et al., 2011; Schaubroeck and Rugani, 2017). Moreover, to obtain the LCI results, one needs to also model, indirectly, all intermediate flows between processes. This step is ideally the same for all pillars in the context of LCSA. For the sake of feasibility, LCI modelling and data collection is often done with more scrutiny for part of the system, the foreground system, than for the rest of the system, the background system. Furthermore, in this chapter, we will also focus on the difference between LCI modelling for attributional life cycle methods and that for consequential life cycle methods, because (1) they answer different prominent ques- tions, (2) many databases are considerably aligned with one or the other, and (3) they have a major impact on the product system and the LCI (Schaubroeck et al., 2021c; Schaubroeck, 2022a; Sonnemann et al., 2011; UNEP-SETAC, 2011). Note that other chapters in this book deal with the data for LCSA (chapters 12 and 13), and thus in this chapter we will mainly focus on LCI modelling (2024-06-06)
***This entry has been automatically imported via Infodoc(ASO) CSV by LIST harvest scripts. Please refer to https://doi.org/10.4337/9781800378650.00024 for the original and latest version of the dataset and data downloads*** (2025-09-03)
|
