eNvironmental Success under Uncertainty and Risk (eNSURe)

In a context of ecological emergency, ex-ante Life Cycle Assessment (LCA) can be used to prioritize investments into technological concepts that are expected to make human activities less damaging to ecosystems and humans. Yet forecasts about the future environmental success of technological concepts come with high incertitude and require careful appraisal of the distinct levels of knowledge associated with the technology’s indeterminacies. This study introduces the algorithmic procedure ENSURe (ENvironmental Success under Uncertainty and Risk) to apply ex-ante LCA when incertitude can be decomposed into risk, manageable with probability distributions, and uncertainty, a lack of knowledge so problematic that it prevents from defining probability distributions. The procedure applies a scenario discovery algorithm to identify combinations of requirements on the most uncertain factors to ensure a minimum conditional probability of success which stems exclusively from risk. The analysis of these requirements allows evaluating whether the total probability of success for the technological concept is above a decision-threshold. The procedure is demonstrated on the case of ex-ante LCA applied to the production of new microalgal compounds for health-management in fish farming. ENSURe can be extended to any type of model used to inform decisions under the co-existence of risk and uncertainty.