Advanced Metabolic Engineering Approaches and Renewable Energy to Improve Environmental Benefits of Algal Biofuels: LCA of Large-scale Biobutanol Production with Cyanobacteria Synechocystis PCC6803

With modern genetic engineering tools, microorganisms can become resilient green cell factories to produce sustainable biofuels directly. Compared to non-engineered algae and cyanobacteria, the photon conversion efficiency can be significantly increased. Furthermore, simplified harvesting processes are feasible since the novel microorganisms are excreting the biofuels or their precursors continuously and directly into the cultivation media. Along with higher productivity and direct product harvesting, it is expected that environmental benefits can be achieved, especially for climate protection. A life cycle assessment (LCA) for biobutanol production with the genetically engineered cyanobacteria Synechocystis PCC6803 is performed to test this hypothesis. A prospective and upscaled approach was applied to assess the environmental impacts at large-scale production (20 ha plant) for better comparability with conventional butanol production. The LCA results show that the engineering of microorganisms can improve the environmental impact, mainly due to the higher productivity compared to non-engineered cyanobacteria. However, the nevertheless high electricity demand required for the cultivation and harvesting process overcompensates this benefit. According to the scenario calculations, a more favourable climate gas balance can be achieved if renewable electricity is used. Then, greenhouse gas emissions are reduced to 3.1 kg CO2 eq/kg biobutanol, corresponding to 20% more than the fossil reference: (2.45 kg CO2 eq./kg 1-butanol). The results indicate the importance of genetic engineering and the energy transition towards renewable electricity supply to take full advantage of the environmental potential of microorganisms as future green cell factories for sustainable biofuel production. Besides, the necessity of developing different scenarios for perspective and upscaled LCA for a fairer comparison with maturereference technologies is demonstrated