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.