On the boundary between economy and environment in life cycle assessment

Purpose

We investigate how the boundary between product systems and their environment has been delineated in life cycle assessment and question the usefulness and ontological relevance of a strict division between the two.

Methods

We consider flows, activities and impacts as general terms applicable to both product systems and their environment and propose that the ontologically relevant boundary is between the flows that are modelled as inputs to other activities (economic or environmental)—and the flows that—in a specific study—are regarded as final impacts, in the sense that no further feedback into the product system is considered before these impacts are applied in decision-making. Using this conceptual model, we contrast the traditional mathematical calculation of the life cycle impacts with a new, simpler computational structure where the life cycle impacts are calculated directly as part of the Leontief inverse, treating product flows and environmental flows in parallel, without the need to consider any boundary between economic and environmental activities.

Results and discussion

Our theoretical outline and the numerical example demonstrate that the distinctions and boundaries between product systems and their environment are unnecessary and in some cases obstructive from the perspective of impact assessment, and can therefore be ignored or chosen freely to reflect meaningful distinctions of specific life cycle assessment (LCA) studies. We show that our proposed computational structure is backwards compatible with the current practice of LCA modelling, while allowing inclusion of feedback loops both from the environment to the economy and internally between different impact categories in the impact assessment.

Conclusions

Our proposed computational structure for LCA facilitates consistent, explicit and transparent modelling of the feedback loops between environment and the economy and between different environmental mechanisms. The explicit and transparent modelling, combining economic and environmental information in a common computational structure, facilitates data exchange and re-use between different academic fields.