Are there infinitely many trucks in the technosphere, or exactly one? How independent sampling of instances of unit processes affects uncertainty analysis in LCA

Purpose Product systems use the same unit process models to represent distinct but similar activities. This notably applies to activities in cyclic dependency relationships (or “feedback loops”) that are required an infinite number of times in a product system. The study aims to test the sensitivity of uncertainty results on the assumption made concerning these different instances of the same activities. The default assumption assumes homogeneous production, and the same parameter values are sampled for all instances (e.g., there is one truck). The alternative assumption is that every instance is distinct, and parameter values are independently sampled for different instances of unit processes (e.g., there are infinitely many trucks). Intuitively, sampling the same values for each instance of a unit process should result in more uncertain results.