Absolute environmental sustainability assessments of long-lived systems: A review of challenges with the representation of time and future research directions

In Absolute Environmental Sustainability Assessment (AESA) various changes over time in e.g., technologies, environmental conditions, and socio-economic conditions are typically not explicitly considered. This may lead to a risk of invalid results and conclusions in assessments of product systems with a long lifetime (e.g., buildings), on the extent to which its future environmental impacts will be low enough. The aim of this study is to identify possible changes to AESA for improved representation of different types of changes throughout the lifetime of long-lived systems. First, we carried out a meta review of existing reviews of AESAs and dynamic life cycle assessments (LCAs) to compile pre-identified challenges related to the time dimension. Second, we identified and reviewed relevant AESA studies that specifically focus on long-lived systems to identify the current practices.

We identified 52 time-related challenges from the meta review and grouped them according to methodological- and stakeholder relevance. Most challenges are relevant for LCA development, including for researchers and practitioners. We found that most of the 14 identified AESA studies of long-lived systems focus on the representation of changes over time in the life cycle inventory phase, while changes over time in characterization factors, carrying capacities and the data for sharing the carrying capacities are rarely considered. Lastly, we offer suggestions for improvements to the current practice of AESA that can potentially address the identified challenges, such as consistent use of future scenarios (e.g., the shared socioeconomic pathways) throughout the phases of an AESA, e.g., for estimating prospective characterization factors and carrying capacities, and for sharing the carrying capacities. Our study contributes to the field of AESA by highlighting critical areas in need of future research to enable appropriate representation of time in studies of long-lived systems.