Temporal Hotspot Identification using Dynamic Life Cycle Inventory: Which are the Critical Time-spans within the Product Life Cycle?

Abstract

Dynamic Life Cycle Assessment (LCA) accounts for the temporal variation of the LCA model. Due to the relative lack of temporally-differentiated characterization factors for the Life Cycle Impact Assessment stage, the most common way to perform dynamic LCA is to limit the dynamic component to the Life Cycle Inventory (LCI) stage. In the manufacturing context, this would translate into a shop-floor connected through Internet of Things (IoT) technologies, to continuously track inventory variables such as technological and environmental flows as well as throughput rate. LCA impacts could then be assessed for each time-step, following their temporal distribution, which would have been overseen with a traditional static LCA. Hotspot analysis can be used to analyze the most relevant drivers of LCA impacts. It can be repeated for each impact category, is embedded in commercial LCA software and, can be done at life cycle stage, process, technological and elementary flow levels. We define temporal hotspots as critical time-spans, responsible for a significant share of LCA impacts. Here we show how to identify temporal hotspots in the context of a dynamic LCI. This would allow for the assessment and management of a new level of differentiation for the hotspot analysis, the temporal one. Moreover, traditional levels of hotspot identification (e.g. process or flow) can be used in an assessment focused on the critical time-spans. To guide readers through the implementation of the methodology, we test it on a hypothetical case study. The methodology could inform decision makers looking for detailed data-driven solutions to reduce LCA impacts of those life cycle stages for which dynamic LCI data is available. Since dynamic LCI data rarely covers the full life cycle, a hotspot analysis with static data is still needed, as a preliminary assessment.