Lights and shadows in consequential LCA

By A. Zamagni, Jeroen B. Guinée, Reinout Heijungs, Paolo Masoni, A. Raggi. The International Journal of Life Cycle Assessment, 2012

332 citations recorded by the source corpus.

PurposeConsequential LCA (CLCA) is becoming widely used in the scientific community as a modelling technique which describes the consequences of a decision. However, despite the increasing number of case studies published, a proper systematization of the approach has not yet been achieved. This paper investigates the methodological implications of CLCA and the extent to which the applications are in line with the theoretical dictates. Moreover, the predictive and explorative nature of CLCA is discussed, highlighting the role of scenario modelling in further structuring the methodology.MethodsAn extensive literature review was performed, involving around 60 articles published over a period of approximately 18 years, and addressing both methodological issues and applications. The information was elaborated according to two main aspects: what for (questions and modes of LCA) and what (methodological implications of CLCA), with focus on the nature of modelling and on the identification of the affected processes.Results and discussionThe analysis points out that since the modelling principles of attributional LCA (ALCA) and CLCA are the same, what distinguishes the two modes of LCA is the choice of the processes to be included in the system (i.e. in CLCA, those that are affected by the market dynamics). However, the identification of those processes is often done inconsistently, using different arguments, which leads to different results. We suggest the use of scenario modelling as a way to support CLCA in providing a scientifically sound basis to model specific product-related futures with respect to technology development, market shift, and other variables.ConclusionsThe CLCA is a sophisticated modelling technique that provides a way to assess the environmental consequences of an action/decision by including market mechanisms into the analysis. There is still room for improvements of the method and for further research, especially in relation to the following aspects: clarifying when and which market information is important and necessary; understanding the role of scenario modelling within CLCA; and developing a procedure to support the framing of questions to better link questions to models. Moreover, we suggest that the logic of mechanisms could be the reading guide for overcoming the dispute between ALCA and CLCA. Going further, this logic could also be extended, considering CLCA as an approach—rather than as a modelling principle with defined rules—to deepen LCA, providing the conceptual basis for including more mechanisms than just the market ones.

Subfields: Economics and Econometrics, Environmental Engineering, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/139d5518a1947abf11a52c814870b29996825065

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Citations in the corpus

The ecoinvent database version 3 (part I): overview and methodology (2016, methodology): “The consequential system model follows a substitution-based approach and is intended to serve as a background database in consequential LCA studies (Earles and Halog 2011; Ekvall and Weidema 2004; Pehnt et al. 2008; Reinhard and Zah 2009; Suh and Yang 2014; Tonini et al. 2012; Weidema et al. 2009; Z”
The Future of Ex-Ante LCA? Lessons Learned and Practical Recommendations (2019, background): “Therefore, a brief overview of the properties of the most commonly applied system models is provided in this section (more info can be found in [21,83,84]).”
Using Attributional Life Cycle Assessment to Estimate Climate‐Change Mitigation Benefits Misleads Policy Makers (2014, methodology): “System-Boundary Truncation in Consequential Life Cycle Assessment CLCA also suffers from truncation errors resulting from practical difficulties in identifying and including all affected processes (Zamagni et al. 2012).”
The ecoinvent database version 3 (part II): analyzing LCA results and comparison to version 2 (2016, background): “Since the Consequential version aims at looking at consequences of changes (Earles and Halog 2011; Ekvall and Weidema 2004; Zamagni et al. 2012), its underlying modeling principles are fundamentally different (Wernet et al.”
Life cycle inventory development for corn and stover production systems under different allocation methods. (2013, background): “Most do not consider market-mediated effects or engage in economic modeling, which, as indicated previously, recent scholarly work in LCA considers an essential element of consequential LCA [13,17].”
Attributional and consequential LCA in the ILCD handbook (2016, background): “2009) and that significant time and effort are required to understand and reduce this uncertainty (e.g., Ekvall et al. 2005; Zamagni et al. 2012).”
Exploring the Current Challenges and Opportunities of Life Cycle Sustainability Assessment (2019, methodology): “This is, among other characteristics, reflected in the way CLCA address multifunctionality through system expansion, allowing the fate of the coproducts in other markets (i.e., displacements) to be included [18].”
Integrated environmental and economic assessment of current and future fuel cell vehicles (2015, result): “The evaluation of such effects and relationships call for consequential LCAs, as opposed to the attributional approach used in this study (Lund et al. 2010; Earles and Halog 2011; Zamagni et al. 2012).”