1. Introduction
Access to affordable and clean energy is one of the Sustainable Development Goals of the United Nations towards 2030[1]. Biomass is a primary source of energy for more than 2 billion people in developing countries. Besides the direct impact of increased access to clean energy, biomass-based industry represents an increasing source of jobs and income in poor rural areas, contributing significantly to well-being and development[2,3].
Microalgae are claimed as a promising alternative feedstock for biofuels, feed, food and chemical precursors due to a higher conversion efficiency of solar-to-chemical energy than terrestrial crops[4]. An estimation indicated that cultivation of 406 million ha of microalgae producing biomass at 10 g · m-2 · d-1 with an oil content in the biomass of 30% (w/w) would be enough to fulfill the global fuel demand[4]. This productivity would be about 27-fold higher than that of soybean, one of the main current feedstocks for biodiesel [4,5]. Additionally, microalgae can be cultivated on non-arable land, in brackish or seawater, and can take industrial and/or domestic waste as a source of nutrients/fertilizers[6], including CO2 from point sources of flue gas for additional benefits of C capture and recycling[7].
However, given the available technology for microalgal biomass production, only high-value products, such as carotenoids and algal biomass for aquaculture feed, have commercial potential in the short term [8–10]. Conversely, most techno-economic analyses indicated that for the production of biofuels from microalgal biomass, costs must be substantially reduced for commercial feasibility[8–10]. Regardless of the generally higher biomass productivity of microalgae in comparison with terrestrial crops, the currently high fixed expenses (construction and operation of cultivation facilities) make the algal biomass cost very sensitive to year-round productivity. For example, pioneering techno-economic analyses suggested that a 50% increase in productivity, from 20 to 30 g · m- 2 · d-1, would result in a 19% reduction in the cost of the algal biomass [8,11]. Most literature survey analyses indicated that the empirically achieved values for microalgal productivity in raceway ponds were 10 - 15 g · m- 2 ·d-1 based on sustained values averaged over the course of a year [8,9,12–15]. However, the National Renewable Energy Laboratory - U.S. Department of Energy (NREL-DOE; US) estimated an algal biomass productivity threshold of at least 25 g · m- 2 · d-1 for an algal biomass production cost of $ 0.54 · kg-1, that would enable cost-effective biofuel production from algal biomass towards 2022 [15,16]. The demonstration of a year-round mean productivity of microalgal biomass containing 40% (w/w) lipids of 23 g · m- 2 · d-1 in a production plant operated in Hawaii [13] supports the achievability of the DOE’s target, at least in selected locations of the world.
Modeling algal productivity potential is a fundamental aspect of resource assessment analyses for identifying those likely high-productivity sites as a critical part of techno-economic analyses, which are intended to minimize the risk of investments for siting algae production facilities for biofuels. However, extrapolation from laboratory-scale data and oversimplification of strain specific biological responses led to a large uncertainty in the results, and frequently in the overestimation of algal productivity[13,17,18]. The model proposed by Moody and colleagues suggested an average world productivity ofNannochloropsis of 9.4 g · m- 2 · d-1 and up to 15 g · m- 2 · d-1 in developing regions of the world such as South America, Africa and India [18]. Despite these mathematical models suggested that climate conditions would favor implementation of highly productive algal biomass facilities in these regions, R&D efforts in developing countries lag behind those in more developed regions of the world [2,19–22].
A high annual average productivity is frequently limited by the degree of variation between seasons of high and low productivity[14]. A reference techno-economic analysis predicted that shortening the annual growth period from 300 to 250 days would increase the cost of algal biomass by 33%[8]. Light and temperature are the main abiotic determinants of microalgal biomass productivity. Thus, seasonal variability at different geographical sites represents a major limitation for high mean annual productivity and biomass production cost at those locations [8,9,12–15]. A harmonized model presented by the NREL-DOE for Chlorella sorokiniana (DOE 1412) cultivated along the U.S. Gulf Coast during 2012–2013 assumed a productivity ratio of 5:1 between summer and winter. The same report set a target of 3:1 to be accomplished by 2022, either by rotation of different strains and/or genetic engineering [14].
More recently, the implementation of devices for climate-simulated conditions for microalgal cultivation in open ponds such as those at the Pacific Northwest National Laboratory [23], or the Phenometrics™ Environmental Photobioreactors (ePBRs)[24], brought a low-risk and cost-effective way of semi-empirical estimation of algal productivity at any specific geographic location. Thus, the cultivation of C. sorokiniana (DOE 1412) under climate-simulated conditions in open ponds during three seasons in Southern Florida indicated an average year-round biomass productivity of 15 g · m- 2 · d-1and a lower seasonal variability, with a productivity ratio of 1.7:1 between summer and winter [25].
Another recent study aimed at estimating the maximum achievable productivity of Scenedesmus obliquus in Brazilian simulated-climate in photobiorreactors showed higher biomass and lipid productivity in the most tropical areas of the country[26].
The goal of the present study was to provide an estimation of biomass and oil productivity of S. obliquus in open raceway ponds under South America simulated-climate. The study also simulated different pond’s depth, CO2 supplementation and seasonal variation in algal productivity at different geographical sites. Results support a high potential of most subtropical and tropical regions of the continent.