Digital Twins in Sustainability Initiatives: A Review From Life Cycle Assessment Perspective

The use of Digital Twins (DTs) to aid decision-making has grown significantly in recent years, especially with the rise of Industry 4.0. Among the various goals and applications, DTs are particularly noteworthy in sustainability initiatives and Life Cycle Assessment (LCA). In LCA, DTs can replicate physical systems using real-time data, supporting various stages of the analysis. Despite its potential, there is a noted lack of theoretical foundation in this area. Therefore, this article aims to provide a systematic literature review on the use of DTs for decision-making in LCA studies. The review includes 57 studies published in scientific journals and conference proceedings available in the main scientific databases. Unlike prior reviews that have examined DTs in sustainability more broadly, this work consolidated evidence and provided a comprehensive mapping based on key research questions. We highlight that the literature on this topic is recent and growing, with applications concentrated mainly in construction and manufacturing, but also extending to supply chains, energy, mining, and consumer products. Most studies apply DTs in the Life Cycle Inventory phase to support real-time data collection via Industry 4.0 technologies, while more advanced works extend their use to impact assessment, interpretation, and scenario optimization. Overall, DTs show strong potential to enable dynamic, data-driven, and decision-oriented LCA, although challenges related to data quality, interoperability, scalability, and standardization still limit their widespread adoption.