Dynamic emissions modeling for sustainable algal carbon nanofiber production

Abstract

The demand for sustainable materials continues to grow, along with the need for accurate environmental impact assessments. Dynamic life cycle assessments (DLCA) provide a more comprehensive sustainability evaluation by incorporating temporal and spatial variability into traditional impact assessments. This thesis uses a dynamic life cycle assessment (DLCA) to evaluate the environmental impact of algal carbon nanofibers (ACNF), including CO₂ emissions, material use, and water consumption. A process-based model estimated industrial-scale energy use, which was converted into emissions using a dynamic normalization factor (DNF). The approach assessed four future energy mix scenarios within the RMPA sub-grid. Results suggest strong system resilience for algal-based products, particularly with advanced cultivation methods like photobioreactors. ACNF production is highly resource-intensive, with significant CO₂ emissions and upstream water use driven by the large quantities of solvent required. Mitigation strategies were explored and offer a foundation for future research. Incorporating dynamic LCA elements provided clear improvements by more accurately capturing evolving energy system impacts. This study reinforces the importance of adaptive environmental assessments when evaluating novel materials with sustainability potential. Future research should further validate this framework with industrial-scale data, expand regional applicability, and explore additional life cycle impact categories to improve the accuracy and relevance of sustainability assessments.