A probabilistic and environmental impact assessment of a cyanobacteria-based biorefinery - Beattie, Audrey, author; Quinn, Jason C., advisor; Arabi, Mazdak, committee member; Marchese, Anthony, committee member (Colorado State University. Libraries, 2021)
Microbial based biofuels represent a potential promising solution as an environmentally favorable transportation fuel. Cyanobacteria have many of the same advantages as microalgae: ability for rapid growth in otherwise non-arable regions, suitability for genetic engineering, and simple nutritional needs. Additionally, cyanobacteria can be engineered to secrete valuable co-products that can be harvested independent from the produced biomass. However, little work has been done to identify the processes and the economic and environmental impacts associated with a large-scale cyanobacteria-to-fuels facility. The present study is a concurrent techno-economic and life cycle assessment of a facility that generates fuels and methyl laurate, an oleochemical, from the cyanobacterial species Synechocystis sp. PCC 6803. The biorefinery model includes all aspects of cultivation, separation of the secreted methyl laurate, biomass harvesting and fuel processing via hydrothermal liquefaction (HTL) of the dewatered biomass. The assessments leverage Monte Carlo analysis (MCA) to address uncertainty and variability inherent in the most significant input parameters, replacing them with probabilistic functions. For the facility configuration producing both fuels and the oleochemical co-product, the MCA average minimum fuel selling price (MFSP) is $2.47 per liter or $9.34 per gallon of gasoline equivalent (gge) with the corresponding average global warming potential determined to be 118 g CO2-eq/MJ-1. The case producing only fuels results in an MCA average MFSP of $2.01/L-1 ($7.60/gge) and an average environmental impact of 100 g CO2-eq/MJ-1. These results are compared to static optimistic and conservative scenario analysis estimates, illustrating the over- and under-estimation of outcomes associated with non-stochastic methods. Suggested facility improvements include increases in pond productivity of both the biomass and methyl laurate oil production, as well as improvements to carbon utilization and bio-crude yield from HTL processing.
Keywords: cyanobacteria; methyl laurate; techno-economic analysis; life cycle assessment; biofuels; Monte Carlo analysis