Data implementation matters: Effect of software choice and LCI database evolution on a comparative LCA study of permanent magnets

Abstract

Life cycle assessment (LCA) databases and software evolve. We analyzed to which extent software and evolving life cycle inventory databases affect the comparison of technology alternatives, using a comparative LCA on permanent magnets as a case study, with two selected software tools: CMLCA and Brightway LCA. We migrated the system models from the CMLCA to Brightway LCA software and alternated between the ecoinvent database versions 2.2 and 3.1 to 3.6 in the system background.When using ecoinvent v3.6 instead of v2.2, the change of the indicator results ranged from −34% to 283%. The evolution of the ecoinvent database impacted the absolute amounts of the characterized results and the relative performance between alternatives. The impact category with the highest variability was ionizing radiation, which even showed a ranking inversion with ecoinvent v3.4. In contrast, the impact of using CMLCA or Brightway was negligible because the same data and modeling assumptions caused percentage differences below 0.4%. During the semi-automated data migration to Brightway, we identified 23 environmental flows in the CMLCA model that were not paired with their corresponding characterization factors in the published study of reference. This error had led to an underestimation of 63% in the photochemical oxidation indicator of one of the alternatives. This underestimation relates to an interoperability issue regarding the nomenclature of environmental flows in software alternatives and is a matter of data implementation rather than an issue intrinsic to the selected software. Finally, we identified improvement opportunities for the transparency and reusability of LCA models. This article met the requirements for a Gold-Gold JIE data openness badge described at http://jie.click/badges.

Integrating Life Cycle Assessment in Conceptual Aircraft Design: A Comparative Tool Analysis

“…These discrepancies contributed to the differences observed in the impact results. Miranda Xicotencatl et al [30] analyzed the effect of LCI database versions and software choice (Brightway and CMLCA). They tested the hypothesis of whether the same data and modeling yield the same result on the example a of permanent magnet.…”

Uncertainties in greenhouse gas emission factors: A comprehensive analysis of switchgrass‐based biofuel production

“…This comprehensive data requirement, coupled with varying methodologies and assumptions, inherently introduces uncertainty into LCA results. Several studies have explored this uncertainty, examining how variations in input parameters and the selection of life cycle inventory (LCI) databases influence the outcomes of LCA studies (Baral et al, 2020;Heijungs & Lenzen, 2014;Hsu et al, 2010;Huijbregts et al, 2003;Igos et al, 2019;Kalverkamp et al, 2020;Miranda Xicotencatl et al, 2023;Mullins et al, 2011;Pauer et al, 2020;Shi & Guest, 2020;Spatari & MacLean, 2010;Wang et al, 2020;Zhao et al, 2019).…”