Abstract Purpose: Transitions to sustainable societies require assessments of future environmental impacts at the macro-level. We examined how prospective process-based Life Cycle Assessment (LCA) is used to model environmental impacts at national to global scales. Our research objectives were to (i) provide an overview of modelling approaches in prospective macro-level LCA; (ii) identify common pitfalls and best practices; and (iii) highlight key challenges and suggest priorities for future research. Method: We conducted a systematic literature review. An initial search in Web of Science, complemented by studies reviewed by Bisinella et al. (2021), yielded 925 studies. After screening based on predefined inclusion criteria and adding 34 additional articles through citation tracking, a final set of 87 peer-reviewed articles was analysed. We reviewed these studies with a primary focus on how system scaling, temporal evolution, and temporal distribution were addressed in the inventory analysis phase. In addition, we assessed elements from the other three LCA phases, including research objectives, temporal scope, system boundaries, and the treatment of sensitivity and uncertainty. We also examined terminology use and transparency. Results and Discussion: We classified the reviewed approaches by how system scaling is treated in the foreground system: coupling with Dynamic Stock Models, which captures stock dynamics but overlooks socioeconomic aspects; coupling with Energy System Models, which provides detailed energy insights but is sector-limited; coupling with Integrated Assessment Models, which offers broader socioeconomic coverage but operates at coarse resolution and typically requires collaboration with model developers; and uncoupled approaches, which allow flexibility but risk oversimplification. We identify twelve key pitfalls, including simplified treatments of system scaling, temporal dynamics, and distribution; a narrow climate focus; limited scenario diversity; and weak internal consistency. We also highlight several best practices. Conclusions and Recommendations: Our review reveals a diverse field with inconsistent terminology, assumptions, and modelling practices. To strengthen the field, we recommend improving transparency and adopting consistent terminology; improving the representation of the complexity of sustainability transitions; strengthening policy relevance; and developing methodological guidance. Addressing these priorities will improve the robustness of prospective macro-level LCA and advance understanding of sustainability transitions.
Paris et al. (Thu,) studied this question.