Conceptual Design of an Autotrophic Multi-Strain Microalgae-Based Biorefinery: Preliminary Techno-Economic and Life Cycle Assessments

Abstract

Microalgae represent a promising solution in addressing the impacts associated with the current agricultural and manufacturing practices which are causing irreparable environmental damage. Microalgae have considerable biosynthetic potential, being a rich source of lipids, proteins, and high-value compounds. Under the scope of the H2020-BBI MULTI-STR3AM project, an innovative large-scale production system of valuable commodities for the food, feed, and fragrance sectors is being developed on the basis of microalgae, reducing costs, increasing the scale of production, and boosting value chain sustainability. In this work, we aimed to create a process model that can mimic an industrial plant to estimate mass and energy balances, optimize scheduling, and calculate production costs for a large-scale plant. Three autotrophic microalgae strains (Nannochloropsis sp., Dunaliella sp. and Spirulina sp.) were considered for this assessment, as well as the use of locally sourced CO2 (flue gas). The developed process model is a useful tool for obtaining the data required for techno-economic analysis (TEA) and life cycle assessment (LCA) of industrial biorefinery-based processes. Nannochloropsis sp. was the most economic option, whereas Dunaliella sp. was the most expensive strain to produce due to its lower productivity. Preliminary environmental assessments of the climate change impact category revealed that water recirculation and the use of flue gas could lead to values of 5.6, 10.6, and 9.2 kgCO2eq·kgAFDW−1 for Nannochloropsis sp., Dunaliella sp., and Spirulina sp., respectively, with electricity and NaCl as the main contributors. The obtained data allow for the quantification of the production costs and environmental impacts of the microalgal biomass fractions produced, which will be fundamental for future comparison studies and in determining if they are higher or lower than those of the replaced products. The process model developed in this work provides a useful tool for the evaluation and optimization of large-scale microalgae production systems.