Costs analysis of microalgae production

2019 
Abstract In this chapter, a techno-economic analysis of the production of microalgae for different applications is presented. First, a costs estimation methodology previously validated is shown. Next, a market analysis of different microalgae applications is performed, and from this it is concluded that agriculture- and aquaculture-related applications today are highly interesting. The cost analysis methodology is then used to determine the production cost of microalgae for these markets in different scenarios. A case study considering a 5-ha facility using open reactors, raceway, and thin-layer cascade is analyzed in depth. Results confirm that microalgae biomass can be produced for these applications at 4.5 and 2.3 €/kg, using raceway and thin-layer cascade, respectively. To reduce the production cost, it is necessary to use wastewaters as a nutrient source; this enables the biomass production cost to reduce to 3.6 and 1.4 €/kg for raceway and thin-layer cascade, respectively. Further reduction requires a substantial decrease in manpower for the operation of the process. By reducing up to 0.1 person/ha, the biomass production cost can be reduced to 2.6 and 0.8 €/kg for raceway and thin-layer cascade, respectively. On the other hand, when analyzing the process as a wastewater treatment process, the treatment cost can be reduced to minimum values of 1.1 and 1.2 €/m 3 for raceway and thin-layer cascade, respectively. These costs are higher than those of conventional systems, of 0.2 €/m 3 . However, if including the service of wastewater treatment cost as an input for the production of biomass, the final biomass production cost can be reduced to minimum values of 2.1 and 0.6 €/kg using raceway and thin-layer cascade, respectively. Thus, techno-economic analysis is confirmed as a powerful tool to perform the optimization of any process, also allowing us to identify the target markets in which the biomass can be used, thus contributing to the expansion of microalgae-based processes.
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