T-reX: Quantifying waste and material footprints in current and future Life Cycle Assessment (LCA) databases

The quintessential principle of the circular economy is to minimise material consumption and waste generation. Thus, identifying and quantifying waste and material flows is critical. Life Cycle Assessment (LCA) is a powerful quantitative method for this, especially given its capacity to expose the details of an activity’s entire life cycle, often guiding the implementation of circular principles to where they could be most effective. Pursuant to these goals the authors have developed ‘T-reX’, an analytical tool for LCA, written in Python. T-reX extends on the existing computational ecosystem centred on Brightway and Premise and can facilitate the quantification of user-defined supply chain demands for activities in current and prospective scenarios. T-reX streamlines database manipulation for LCA practitioners, integrating methods to aggregate and analyse demand inventories that could expose hotspots of hidden risk. With a simple case study using lithium-ion batteries, we demonstrate some of T-reX’s potential by detailing and exploring aspects of their waste and material footprints. Since such footprints are often linked to negative externalities, T-reX could support sustainable decision-making and contribute to the development of the circular economy by promoting the understanding of our material consumption and waste generation.