3.5. Strengths and limitations of ePBRs for biomass productivity estimation
This study further supports the convenience of using commercially available devices such as ePBRs for low cost and low risk assessment of potential microalgal productivity on any geographical region and to contribute information on the effect of cultivation variables with high resolution of site and season specificity. This is especially important for advancing R&D of microalgal biotechnology in developing countries. This is mostly because the costs of installation and operation of raceway ponds, even being the least expensive cultivation systems, might still represent a barrier to accelerate R&D in developing countries. Thus, both mathematical modeling [18,36] and devices for productivity estimation under climate simulated conditions are generally valuable [23,26] and especially useful to optimized limited resourced allocated to R&D in developing counties [2,19,22].
As commented before [23,37] ePBRs proved to be highly reliable in terms of producing very consistent results with low variation among independent runs after randomizing the scripts and the ePBR units.
On the other side, a validation study by Huesemann and colleagues (2017) suggested that PhenometricsTM ePBRs might underestimate microalgal biomass productivity up to 44% for C. sorokiniana (DOE 1412) in Arizona (US) simulated-climate. Similarly, the optical-density-based biomass productivity and the rate of increase in cell counts of Picochlorum soloecismus in the ePBRs was also lower than in custom-built PNNL indoor climate-simulation ponds[23]. It is currently unknown whether ePBRs generally underestimate microalgal biomass productivity and/or if the inaccuracy could be strain specific. Although this raises some uncertainties on the absolute productivity potential of the geographical sites analyzed in this study, and others, it tends to provide an optimistic base-line for a comparative estimation. Additionally, it is important to take into account that these simulations oversimplify the complexity of outdoors cultivation of microalgae for weather homogenization around historical annual averages of temperature and irradiation. Overriding year specific climatic fluctuations might give reasonably accurate predictions of microalgal biomass productivity in the long-term. However, weather fluctuations at different time scales (from hours to years) should be tolerated by selected robust strains to make both short- and long-term predictions more realistic. Robustness of selected strains should also prevent and/or tolerate contamination, predation and/or grazing for more realistic predictive models.
As concluding remarks, this study represents a pioneering work for the estimation of microalgal biomass productivity in South America. Results support a high potential of Tropical and Subtropical regions for high biomass productivities. Fortaleza (Brazil) was identified as one of the candidate production sites with a predicted annual average biomass productivity of 23 g · m-2 · d-1, which is very close to the target estimated by the DOE for economic feasibility of microalgal biofuels.
This study contributes guidance for comprehensive resource assessment and techno-economic analyses of the potential of microalgal biotechnology according to the South American resources and specific needs.