Life cycle assessment as a driver for process optimisation of cellobiose lipids fermentation and purification

Abstract

Abstract Purpose Cellobiose lipids (CL) are biosurfactants produced by various Ustilaginaceae species in aerobic fermentations. They show high potential for application as alternatives to conventional oleochemical- or petrochemical surfactants. To ensure their environmentally friendly performance, we aimed to assess CL production from a life cycle perspective at an early developmental stage to identify process steps that have the highest impact on the environment. With this information, optimisation approaches can be derived. Materials and methods Following a cradle-to-gate approach, we modelled the CL fermentation and purification process based on experimental data from the lab scale and process simulation data at a 10 m3 scale. For LCA, the impact categories (IC) abiotic depletion potential (ADP), eutrophication potential, photochemical ozone creation potential, global warming potential, acidification potential, and the primary energy demand were calculated for all process steps. Based on the obtained results, process bottlenecks were identified, and alternative process scenarios varying the related process parameters were simulated. These were used to assess the environmental impact reduction potential (EIRP) of an optimised process and draw recommendations for experimental process optimisation. Results and discussion The obtained results showed that the fermentation caused ~ 73% of ADP and more than 85% of all other ICs. The major contributor was the electricity consumption for continuous fermenter aeration. Thus, reducing the fermentation duration from the initial 14 to 5 days would result in a decrease in all investigated ICs of up to ~ 27–52%. An increase in CL concentration results in a decrease in all ICs of a similar magnitude due to the higher yield per batch at comparable energy and material consumption. Although the share of purification process steps to all ICs is overall relatively small, implementing foam fractionation for in situ product recovery showed an additional EIRP of 18–27% in all purification IC shares. Conclusions The conducted LCA showed that overall, more EIRP can be achieved by optimising fermentation process parameters compared to purification process steps. This is mainly due to the long fermentation duration and large energy consumption for fermenter aeration. This highlights the importance of using LCA as a driver for process optimisation to identify process steps with high EIRP. While some of the results are specific to CL, other obtained results can be transferred to other fermentations.