Accounting for learning in prospective LCA: Theory and practical guidance

Abstract

Learning is important for the development of industrially deployed technologies, and learning curves have been used to determine future production costs. Although the effect of learning on costs has been extensively studied, little evidence exists for its effect on environmental impacts, and a conceptual underpinning is lacking. Based on a review of theoretical foundations and empirical evidence, this study presents a procedure for assessing learning of industrial processes in ex ante and prospective life cycle assessment (LCA). We argue that learning involves operational or organizational changes, which are motivated by incentives. Therefore, environmental impacts may follow a learning curve trend if the origins of impacts coincide with dominant incentives. A key observation is that the results may vary by impact category, and certain impacts may not decline at all. Therefore, we developed guidelines that consider these differences when evaluating environmental learning effects and rates, as illustrated with examples in an LCA context. Further research is needed to expand the evidence base for environmental learning, by re-interpreting datasets of existing technologies to determine their learning rates.