Biological-chemical conversion process design and machine learning-related life cycle assessment: Bio-lubricant production in a real case study of South Korea
- Authors
- Lee, Yoonjae; Ko, Jaerak; Kwon, Oseok; Park, Hoyoung; Lee, Hyeonjeong; Jeong, Sumin; Ha, Byeongmin; Hwangbo, Soonho; Han, Jeehoon
- Issue Date
- Apr-2025
- Publisher
- Academic Press
- Keywords
- Biomass; Poly alpha olefin; Integrated process; Process design; Life cycle assessment; Machine learning
- Citation
- Journal of Environmental Management, v.379
- Indexed
- SCIE
SCOPUS
- Journal Title
- Journal of Environmental Management
- Volume
- 379
- URI
- https://scholarworks.gnu.ac.kr/handle/sw.gnu/77813
- DOI
- 10.1016/j.jenvman.2025.124877
- ISSN
- 0301-4797
1095-8630
- Abstract
- This study explores the production of poly alpha olefin (PAO) from biomass as an environmentally friendly alternative to fossil fuel-based methods, aiming to reduce greenhouse gas (GHG) emissions. The primary goal is to design a process for converting 2,000 metric tons of biomass into PAO daily, integrating biological and chemical pathways. Environmental impact is assessed through a life cycle assessment (LCA), comparing this biomass-based method with traditional fossil fuel-derived processes. Key findings include the successful production of 458 metric tons of PAO, with the LCA revealing a 34.8% reduction in GHG emissions (9.88 kg CO2eq./kg of PAO) compared to fossil fuel-based PAO. Sensitivity analyses on the oligomerization yield (60-70%, base case at 65%) and the recycle ratio of glucose in the bioprocess for octanoic acid production show significant environmental benefits when exceeding a 55% recycle ratio. Additionally, an energy scenario analysis predicts the impact of shifting to renewable energy by 2030. In a scenario where all electric utilities are renewable (RE100 scenario), GHG emissions are estimated at 13.07 kg CO2-eq./kg of PAO, further emphasizing the environmental advantage of biomass-based PAO. This study, through its integration of biological and chemical processes and comprehensive LCA, provides critical insights into the potential of biomass-based materials for reducing GHG emissions, making a substantial contribution to future research in high-value material production from renewable resources.
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