ForestPaths member Amelie Müller, from VITO WET (Water and Energy Transition), in collaboration with Timo Diepers from RWTH Aachen University, Arthur Jakobs from Paul Scherrer Institute, and other researchers, have developed an open-source Python tool for time-explicit Life Cycle Assessment (LCA). The tool, named bw_timex, provides a more accurate assessment method for environmental impacts by accounting for the timing of processes and emissions and the technological developments at that point in time. This is a step forward from existing LCA methods that consider product systems at a single point in time without accounting for temporal dynamics.
Unlike conventional LCA, bw_timex accounts for the timing of processes throughout the supply chain. For example, it tracks that a product’s end-of-life treatment occurs decades after its production. It also models variable or evolving supply chains and technologies by relinking processes in time to the latest supply chain data for that point in time, such as the increasing share of renewable electricity over time. The resulting LCI (Life Cycle Inventory) reflects the current technology status within the production system at the actual time of each process. Additionally, bw_timex offers dynamic characterisation functions, which account for the timing of emissions, ensuring more precise environmental impact assessment results.
Bw_timex builds on the Brightway (bw) LCA framework, enabling users to apply other Brightway LCA functionalities at the same time. The tool is easy to use: the user only needs to specify the timing of processes and emissions in the product system and to provide background databases for future production landscapes, while bw_timex calculates the temporal connections in the system and relinks the processes automatically. The time scales at data input and impact assessment can be chosen flexibly, allowing the researcher to tailor the tool to her own research question and data availability. Bw_timex is particularly beneficial for cases with variable or strongly evolving production systems, long-lived products, and biogenic carbon. It ensures that the environmental impacts of products and processes are assessed more accurately compared to conventional LCA, by taking into account the dynamic nature of product systems and supply chains.
You can explore the potential of bw_timex to enhance your environmental impact assessments and ensure your analyses reflect the true temporal dynamics of production and emissions here.
