The transition to bioeconomy and low-fossil carbon economy (LFCE) requires long-term investments, whose environmental and economic performance will be affected by various future conditions, such as the raw material availability and the type of energy or fertilizers used (and replaced). Considering multiple background futures instead of one single projection in building time-dependent inventories for assessing LFCE solutions would greatly enhance the robustness of the decision support provided by environmental assessments such as Life Cycle Assessments (LCA). Here, we reviewed, through automatized and manual text-mining, six internationally well-recognized global environmental scenario studies and one intelligence report. The aim was to uncover the key variables and cause-effect relationships at play in these scenario studies. Through constructing causal loop diagrams for each reviewed study, we identified the variables with the greatest number of causal connections, the “cause” and “effect” variables, and revealed the most reported cause-effect relationships across all studies. Our main findings are: (1) the top 5 causal variables are mitigation policies, technological progress, consumers’ awareness, economic growth and education level, while (2) the top 5 affected variables are climate change, materials use, food security, natural ecosystems, and social justice. Amongst the top 10 causal and affected variables (3), 68 connected pairs were identified with no disagreement in their causal relationship directions. The three most reported pairs were (4) mitigation policy → climate change, healthy and sustainable diet → land use, and population → materials use (each reported in four studies). Finally, (5) we highlighted that all the reviewed studies are based on the decision-making logic of maximizing utility. We concluded that identifying these key cause-effect variables and relationships was essential for building time-dependent inventories in LCA, and that these may be a more useful input than the direct use of any of the scenario reviewed herein.
Spatial time-dependent reliability analysis of corrosion damage to RC structures with climate change
