A decision support framework for upscaling sustainable bio-based technologies: integration of digital twins and life cycle assessment

Climate change mitigation is driving growing innovation in bio-materials production technologies, with a focus on improving their environmental sustainability. This study presents a decision-support framework based on a careful integration of technical requirements, implemented in a process digital twin and life cycle assessment (LCA). Our framework aims at guiding the development of emerging biotech companies towards achieving their sustainability objectives. We are focusing on the challenge of translation of lab-scale concepts to commercial scale innovations. Using an iteratively refined understanding of foreground and background production systems, this framework can support companies in making informed scale-up decisions from both technical and socio-economic perspetives. The framework is demonstrated for the case study of Seprify AG, a deeptech company specializing in developing sustainable cellulosic particles and cellulose-based hybrid materials. In the short term, Seprify AG achieved ca. 20% reduction in GHG emissions by optimizing post-treatment conditions, compared to the initial pilot-scale operating conditions. For long-term optimization, integrating Seprify’s cellulose production with existing industrial sites, such as a pulp mill, is expected to achieve greenhouse gas (GHG) emission reductions up to 89%, compared to the initial baseline. Following the energy transition trend in the EU, GHG emissions for Seprify’s cellulose particles production can be further reduced by additional 60~80% by 2050. Additional attention may be needed to address the trade-offs with other environmental impacts, such as land use, and to explore greener biomass feedstock supplies, such as forest residues.