Systematic review of scale-up methods for prospective Life Cycle Assessment of emerging technologies

Prospective Life Cycle Assessments (LCAs) are crucial for analyzing and optimizing emerging technologies' conceivable environmental performance. However, emerging technologies are often subject to high uncertainties and are still at laboratory or pilot scale, necessitating the scale-up of LCA relevant data, such as energy and material flows, to an industrial level. Hence, robust and adequate scaling methods are required as an integrated part of any sustainability-oriented prospective assessment. This work presents a systematic review of scaling techniques used in various LCA related studies (n=78) and analyzes their frequency and the respective technology type's and group's potential influence. Literature providing detailed scaling methodologies are identified, exposed, and quantitatively evaluated to discover their advantages and disadvantages. An Excel-based tool is derived to assist in selecting appropriate scaling methodologies as provided by literature by customizing the respective evaluation criteria (complexity, data intensity, duration, and uncertainty). With its primary focus on prospective LCA to provide practical guidance, the work offers insights that are relevant to other sustainability assessment methods as well. Essential guidance in the selection of appropriate scaling methods is provided, facilitating more robust sustainability assessments and supporting decision-making processes in research, industry, and policymaking.