ECOPT²: An adaptable life cycle assessment model for the environmentally constrained optimization of prospective technology transitions

Abstract

Life cycle assessment (LCA) is a method to evaluate the environmental impacts of technologies from cradle to grave. However, LCAs are commonly defined in terms of the consumption of a single unit of a product and thus ignore scaling issues in large-scale deployment of technologies. Such product-level LCAs often do not consider capital manufacturing capacity and supply chain bottlenecks that may hinder the rapid, widespread uptake of emerging technologies entering the market; emerging technologies often require the expansion of existing supply chains or the development of entirely new supply chains, such as the manufacturing of novel materials. As a result, such LCA studies are limited in their ability to realistically assess impacts at the macro-scale and thus to guide large-scale decisions. In this work, we present ECOPT 2 , a generalized adaptable model that combines these constraints to the LCA approach using a mathematical programming approach and dynamic stock modeling.ECOPT 2 combines LCA factors with transition scenarios from energy systems models to determine the environmentally optimal deployment of new technologies while accounting for material circularity constraints and barriers to uptake. We also introduce the structure of the software tool and demonstrate its features using a stylized vehicle electrification scenario.

Assessing the European Electric-Mobility Transition: Emissions from Electric Vehicle Manufacturing and Use in Relation to the EU Greenhouse Gas Emission Targets

“…Taking the passenger vehicles in lower-medium size as the reference models, the assessment of GHG emissions for the manufacturing process was based on aggregated energy consumption results from previous LCA studies, and for the in-use phase was based on driving patterns influenced by the current usage of passenger vehicles, which were all assumed to remain constant for different scenarios. More detailed modeling for the future studies could include potential improvements in EV battery chemistries and manufacturing process, 60 changes in driving behavior due to EV adoption (e.g., rebound effects), and reference model changes affected by customer choices to have a more comprehensive investigation of the changes and challenges during the EU e-mobility transition.…”

Optimization of the end‐of‐life tire repartition within the European treatment system to minimize its environmental impacts

“…The matrix representation of the model is based on the traditional LCA equation described by Heijungs and Suh (2002):…”

“…It is likely that such scenarios do not match with optimal solutions, especially in complex systems (Ekvall et al., 2007). Since 1998 (Azapagic & Clift, 1998, 1999), LCA and input–output (IO) practitioners have used an optimization approach for a broad range of applications, such as waste management (Kondo & Nakamura, 2005), energy (Saner et al., 2014), transport (Hung et al., 2022), biofuels (Wietschel et al., 2021), biorefinery technologies (Budzinski et al., 2019), and many others. The method has demonstrated its ability to quickly, explicitly, efficiently, and autonomously provide the optimal technological combination by exploring the whole solution space.…”