Life Cycle Assessment (LCA) of emerging technologies involves great uncertainty due to limited data, technological pathway indeterminacy, and scale-up challenges. This systematic literature review examines how practitioners quantify and address uncertainty in LCA of emerging technologies, the limitations of current approaches, and their usefulness for supporting technology development and decision-making. A systematic literature review following PRISMA guidelines was conducted using Scopus. Studies were eligible if they focused on emerging technologies and explicitly addressed uncertainty using parameter uncertainty, scenario analysis, and/or sensitivity analysis methods. Of 444 initial records identified, 230 peer-reviewed journal articles were included. Data extraction covered four categories: parameter uncertainty, scenario analysis, sensitivity analysis, and scale-up. Of 230 studies, scenario analysis was applied in 211, sensitivity analysis in 193, parameter uncertainty in 94, and scale-up was addressed in 163. Methods frequently overlapped, reflecting both methodological flexibility and the different questions uncertainty assessment needs to answer. Probabilistic sampling dominated parameter uncertainty, but can create false precision when probability distributions cannot be meaningfully defined. Scenario analysis was particularly useful for exploring alternative technological pathways and future conditions, while sensitivity analysis can identify where further data collection or technology development is most valuable. Discrete sensitivity analysis was the most frequently applied sensitivity approach, although one-at-a-time methods can miss interactions and non-linearities. Scale-up further introduces uncertainty in both parameter values and technological configurations. The dominance of readily implemented methods does not necessarily reflect their suitability for emerging technologies. Probabilistic approaches remain appropriate for well-characterized parameters, but highly uncertain foreground data may require possibility-based or qualitative treatment. Scenario and sensitivity analyses are particularly valuable for technology development by comparing plausible pathways, identifying development priorities, and establishing decision thresholds. Practical guidance and software support for combining these approaches according to the available knowledge are needed.
Buildings with long service life are associated with recurring greenhouse gas (GHG) emissions arising from repeated activities such as refurbishments over time, which can significantly contribute to the cumulative climate change impact. In particular, multi-tenant office buildings, where fit-outs typically occur every 2–10 years, contribute approximately a quarter of GHG emissions over the building service life. This study applies prospective LCA (pLCA) to quantify the climate change impact over the service life of a tenanted office building and assesses the effect of circular economy (CE) strategies using time-differentiated analysis. In contrast to static life cycle assessment (LCA), this approach enables climate change impact assessment of future scenarios with changed processes to account for potential future emissions. An office fit-out case study in Aotearoa New Zealand was modelled using attributional LCA. The climate change impact was initially quantified using static LCA and hotspots were identified for applying CE strategies. Alternative CE strategies were then modelled using static LCA, related to maximising reuse, design for optimisation, and using low-impact materials. Then pLCA was conducted using the premise software to quantify the future climate change impact by analysing office fit-outs across four subsequent fit-out cycles at 10-year intervals, with and without implementation of CE strategies. In addition to the global future scenarios in premise, a national electricity decarbonisation pathway was included in the scenario modelling. Sensitivity analyses were conducted to assess the robustness to key assumptions in the evaluated CE strategies and use of alternative climate policy pathways. The static LCA results showed that office fit-outs in module B5 are dominated by GHG emissions arising from manufacture of materials and components. Implementing all the evaluated CE strategies can reduce the net climate change impact of a single office fit-out - modelled using static LCA - by 17
Cultural ecosystem services (CES) are absent from current Life Cycle Impact Assessment (LCIA) methods. This study investigates the use of willingness-to-pay as a basis for deriving monetary effect factors (EFs) for marine CES affected by macroplastics. To our knowledge, this study provides the first set of spatialized EFs for marine CES impacts, demonstrating how willingness-to-pay (WTP) can quantify impact on CES within the LCIA framework. Monetary EFs were developed based on an European WTP survey on marine plastic removal in eight countries, additional 13 countries´ WTP were extrapolated using disposable income. Coupled with marine plastic burden in each country, the resulting 21 national EFs express the potential loss of holistic cultural utility per unit of stranded macroplastics in [€/kg] and [€/item]. The mass of an average stranded plastic item is derived from each countries’ beach cleanup results. The dual units ensure compatibility with life cycle inventories. A case application in the Froan Archipelago (Norway) illustrates the relevance of the EFs and their role in the LCIA cause–effect chain, linking plastics stress to CES loss. The WTP-based EFs enable the quantification of CES impacts in monetary terms consistent with existing LCA monetization. National EFs varied greatly, ranging from 233 €/kg to 1,730,000 €/kg by mass and 7.41€/item to 74,200 €/item by item count. The population-weighted averages for Europe were 65,200 €/kg and 5,310 €/item, respectively. This variability was driven mainly by differences in estimated stranded plastic burden, while WTP differences, reflecting economic and cultural contexts, contributed to a smaller extent. Incorporating WTP-based valuation offers a transferable means for integrating impacts on ecosystem services into LCIA. This study demonstrates that WTP provides a practical and conceptually coherent basis for quantifying CES impacts within LCIA. The proposed EFs represent an initial step toward monetized characterization factors for CES damages from macroplastics. The framework enhances the representation of ecosystem services in LCA and can be extended to other environmental stressors and geographic contexts.
The shift of the textile sector to the principles of the circular economy is still limited by disjointed sustainability evaluations and the lack of application-focused directions between the production, consumption, and policy interventions. The paper fills this gap by creating an integrated framework of life cycle sustainability assessment (LCSA)-based evaluation and operationalisation of environmental, economic, and social performance throughout the textile life cycle. Three scenarios, linear baseline (S0), circular low adoption (S1), and circular high adoption (S2) are evaluated using representative secondary data of the Indian textile sector on the life-cycle. The results demonstrate that for the same amount of fabric, S₂ has a lower GWP (9.8 to 5.2 kg CO₂-eq/kg fabric), lower cumulative energy demand (124 to 78 MJ/kg fabric), lower freshwater use (310 to 180 L/kg fabric), lower human toxicity (3.4 to 2.0 kg 1,4-DB eq), and lower release of micro-fibres (2.3 to 1.5 g fibres) than S₀. The total life cycle cost reduces from ₹337 to ₹305 per kg fabric and worker health and safety increases by 72
Demand-side interventions, including food waste prevention, are widely promoted as means to reduce the environmental impacts of food systems. Life Cycle Assessment is central to quantifying these benefits, yet assessments often rely on substitution assumptions, while other behavioural and economic responses remain weakly addressed. This study examines how Life Cycle Assessment practitioners understand, consider, and address rebound effects in food-system assessments, using food-waste prevention as a salient example. An online survey was conducted among Life Cycle Assessment practitioners working with food-system and food-waste-related assessments (n = 79). The survey combined quantitative questions on familiarity, perceived importance, and current practice with open-ended questions capturing motivations, barriers, and reasoning. Quantitative responses were analysed descriptively, and qualitative responses were analysed thematically to identify recurring patterns and explanatory themes. Rebound effects were rated as moderately important but were rarely included in quantitative modelling. Practitioners did not exclude rebound effects because they were considered irrelevant, but because conditions for credible inclusion were often lacking, including data limitations, high uncertainty, limited procedural guidance, and insufficient interdisciplinary capacity. In contrast, substitution assumptions implemented via system expansion are routinely applied despite comparable uncertainty. This suggests an asymmetric treatment of substitution assumptions and rebound effects in applied food-system Life Cycle Assessment practice, where uncertainty functions as a selective gatekeeper rather than a consistent criterion for inclusion or exclusion. The findings indicate a structural misalignment between the recognised relevance of rebound effects and their practical treatment in food-system Life Cycle Assessments. Addressing this misalignment requires clearer methodological guidance on how rebound mechanisms relate to commonly applied substitution assumptions and how uncertainty can be handled more consistently when Life Cycle Assessment is used to inform food-system policies, mitigation targets, and intervention prioritisation.
