Abstract
Early-stage system-level assessment of emerging technologies is essential for achieving climate neutrality and a circular economy; however, such assessments are often constrained by the lack of representative life cycle inventory data. In thermal energy systems, performance strongly depends on scale, making direct application of laboratory- or bench-scale experimental data potentially misleading in life cycle assessment (LCA). This study investigates the influence of experimental scale on system-level evaluation using a zeolite-based thermal energy storage (TES) system as a case study.LCAs were conducted using performance data from laboratory-, bench-, and pilot-scale experiments and compared with predicted commercial-scale performance derived from numerical simulations. The TES system stores waste heat via water vapor desorption from zeolite and generates pressurized steam using a moving-bed with indirect heat exchanging system. Heat recovery ratios of 36%, 50%, and 61% were obtained at laboratory, bench, and pilot scales, respectively, while commercial-scale performance was predicted to reach approximately 80% due to reduced heat losses. Accordingly, LCAs based on small-scale data indicated higher greenhouse gas (GHG) emissions than conventional technologies, whereas assessments using commercial-scale data demonstrated clear GHG reduction potential.The results highlight the risk of erroneous conclusions when small-scale data are directly used for system evaluation. By integrating experimentally validated numerical modeling with computer-aided process engineering, scale-dependent data can be transformed into system-representative inputs, enabling fair and consistent assessment of emerging technologies.