1. Aeration energy requirements for lipid production by Scenedesmus sp. in
airlift bioreactors
Sarah M.J. Jones, Susan T.L. Harrison ⁎
Centre for Bioprocess Engineering Research (CeBER), Department of Chemical Engineering, University of Cape Town, Private Bag X3, Rondebosch 7701, Cape Town, South Africa
a b s t r a c ta r t i c l e i n f o
Article history:
Received 8 November 2013
Received in revised form 3 February 2014
Accepted 23 March 2014
Available online 1 May 2014
Keywords:
Microalgae
Bioenergy
Lipid
Net energy ratio
Airlift photobioreactor
Mass transfer
Microalgae have potential to yield various bioenergy products, including algal biodiesel. For algal energy pro-
duction, the process energy input must be substantially lower than the product energy. Airlift photobioreactors
provide controlled environments with good mixing and mass transfer; however, previous work reports a net
energy ratio (NER; energy produced divided by energy consumed) less than 1. Here, the energy consumption
in these reactors was improved by combined optimisation of superficial gas velocity and its CO2 concentration.
Increasing CO2 concentration resulted in increased tolerance to lower superficial gas velocities, down to a critical
minimum value. A 75% reduction in aeration power input was obtained by reducing superficial gas velocity from
0.0210 to 0.0052 m s−1
at 5 400 ppm CO2, without substantial reduction in biomass concentration (2.27 to 1.93 g
L−1
, respectively) or productivity (0.189 to 0.173 g L−1
d−1
, respectively). The NER under these conditions was
5.47 for biomass plus lipid and 1.01 for lipid only. The CO2 supply rate, product of superficial gas velocity and CO2
concentration, correlated with the CO2 transfer rate which influenced algal productivity. The range of NERs
measured across the superficial gas velocities studied indicates the ability to optimise algal cultivation in
photobioreactors for the improved feasibility of algal bioenergy.
© 2014 Published by Elsevier B.V.
1. Introduction
Global interest in the commercial production of algae has increased
in recent years, driven by the potential of bioproducts as sustainable
alternatives to their chemical and petrochemical based counterparts,
and the growing demand for biofuels and bioenergy from renewable
sources [1,27,38].
Many species of microalgae show potential as useful bioresources
and have been used commercially in food or nutritional supplements,
pharmaceuticals, animal feed, aquaculture, wastewater treatment and
bioenergy; including biodiesel, algal oil, methane, hydrogen and ethanol
[4,6,13,15,33]. The ability of algae to produce a variety of products has
potential from a biorefinery point of view. Numerous microalgae have
high lipid content, making them good candidates for the production of
biodiesel, biosurfactants and high value oil products such as poly-
unsaturated and omega-3 fatty acids [20,26]. Research has shown that
the lipid content of microalgae can be further increased under nitrogen
limitation [18,35,49,54,55].
However, the use of algae or other microbial sources for the
production of commodity products is not without challenges, and
much research is being carried out into the improvement of these
systems [28,42,57,60]. Currently co-production is typically necessary
to maintain economic feasibility [3,9].
The cultivation stage of an algal bioprocess has the highest energy
burden, and a significant portion of this energy consumption is for
mixing and aeration [36,46]. For the production of bioenergy from
microalgae, it is essential to reduce energy requirements for the process
to be sufficiently energy positive and thus feasible [45,46,54,55].
Open ponds, typically raceway ponds, are the oldest and most
commonly used microalgae cultivation systems. However, there is on-
going debate over the benefits and economic feasibility of open systems
and closed photobioreactors (PBR) [9,29,43,47]. Closed PBRs have the
benefit of providing controlled environments for algal cultivation,
with limited contamination, temperature changes and evaporation
[26,53]. Although the PBR tends to have higher capital costs and energy
requirements than open ponds, some studies indicate that its high
productivity leads to lower projected running cost per unit of product
[9,45,47], while other studies show the contrary [29,45].
Carvalho [5], Chisti [9], Hadiyanto et al. [24], Harrison et al. [25], and
Singh and Sharma [53] identified gas transfer, nutrient distribution and
light requirements as key factors in algal cultivation and review current
cultivation systems designed for improved productivities. The most
popular PBR configurations are tubular and flat panel, due to their
enhanced light availability [5,9]. The airlift concept has been used
successfully for microalgal cultivation in both flat plate and tubular
reactors [9,22,34,51,52,59]. In airlift reactors, gas is sparged from the
Algal Research 5 (2014) 249–257
Abbreviations: NER, Net Energy Ratio; PBR, Photobioreactor; CTR, CO2 Transfer Rate;
CSR, CO2 Supply Rate.
⁎ Corresponding author at. Centre for Bioprocess Engineering Research (CeBER),
Department of Chemical Engineering, University of Cape Town, Private Bag X3,
Rondebosch 7701, Cape Town, South Africa. Tel.: +27 21 650 4021.
E-mail address: sue.harrison@uct.ac.za (S.T.L. Harrison).
http://dx.doi.org/10.1016/j.algal.2014.03.003
2211-9264/© 2014 Published by Elsevier B.V.
Contents lists available at ScienceDirect
Algal Research
journal homepage: www.elsevier.com/locate/algal

2. base, rising up in a discrete region of the reactor (the riser) and down in
a separate region (the downcomer) [5,53].
Gas transfer, nutrient distribution and light requirements are
dependent on mixing and aeration, and hence energy consumption
[36]. In reactors driven by the airlift concept, mixing and gas–liquid
mass transfer both occur by sparging gas (aeration). It is known that
airlift reactors have good gas–liquid mass transfer capabilities [5,10,
17]. Studies have reported factors influencing improved mixing and
mass transfer in airlifts, including geometric design, presence of stirrer,
sparger type and bubble size [11,32,39,61]. However, optimisation of
mass transfer and mixing has not been reported explicitly as a function
of energy input. Net energy ratios (NER), defined as the ratio of the
energy that can be obtained from a product to the energy consumed
to obtain that product [49], are useful for assessing the feasibility of
algal energy products. For bioenergy production, maximising NER is
critical.
The aim of this study was to determine the minimum aeration
energy input required to maintain algal biomass and lipid production
in an internal loop airlift reactor. Biomass and lipid concentrations
were measured at decreasing superficial gas velocities, and the resulting
NER calculated. Carbon dioxide mass transfer is dependent on both
superficial gas velocity and CO2 content. By including the CO2 partial
pressure in the sparge gas as a variable, both energy and mass transfer
influences were considered.
2. Materials and methods
2.1. Algae strain, bioreactor and cultivation conditions
Starter cultures of Scenedesmus sp. (isolated from Upington, South
Africa) were grown in glass bottles at a volume of 500 mL, with light
and CO2 enriched air provided. A 3 N BBM growth medium [2] was
used, adapted to contain 150 mg L−1
NO3 for increased lipid content
in airlift photobioreactor experiments.
For batch cultures of Scenedesmus sp. in airlift PBRs, the reactors
consisted of a glass cylinder (600 mm height; 100 mm external diame-
ter), with a working volume of 3.2 L, containing an inner glass column or
draft tube (475 mm height; 50 mm external diameter) to separate the
riser (inner tube) and downcomer regions (outer annulus) [34]. After
7 to 10 days of growth, the starter culture was inoculated into the airlift
reactors to an optical density (OD) of 0.1 at 750 nm. The cultures were
grown for 2 weeks under constant light (300 μmol m−2
s−1
) provided
using 18 W cool white fluorescent bulbs (Osram). For ‘standard condi-
tions’ cultures were sparged with CO2 enriched air at 10,400 ppm CO2
and a superficial gas velocity of 0.0210 m s−1
, equating to an air flow
rate of 2 L min−1
(0.0625 vvm). The temperature, measured regularly,
remained at 25 ± 2 °C.
2.2. Effect of superficial gas velocity and CO2 concentration
Following establishment of the performance of Scendesmus sp. under
standard conditions, its performance was studied under a range of
superficial gas velocities (0.0021, 0.0052, 0.0105 and 0.0210 m s−1
,
equivalent to air flow rates of 0.2 to 2 L min−1
). At each superficial
gas velocity Scenedesmus sp. was cultivated at four CO2 concentrations
(400, 1400, 5400 and 10,400 ppm) such that the effect of CO2 mass
transfer and energy supply could be considered separately. For each
set of experiments, a positive control was run under the ‘standard
condition’ to check consistency and provide data on reproducibility.
2.3. Biomass and lipid quantification
Biomass of the starter cultures was measured by optical density at
750 nm [19]. Biomass in the airlift reactors was quantified by both
optical density at 750 nm and measuring the dry weight. Samples
(10–30 mL) were filtered through pre-weighed 0.45 μm cellulose
nitrate filters (Sartorius Stedim) and dried at 80 °C for 48 h before
being weighed. The total lipid content (measured as the total fatty
acid content) and the fatty acid profiles were measured by the direct
transesterification method followed by gas chromatography [21].
Under the ‘standard condition’, duplicate samples were taken to calcu-
late the standard deviation for both the biomass and lipid quantification.
For all other experiments the standard deviation of lipid and biomass
were calculated from the multiple runs at the ‘standard condition’
repeated with each experiment.
2.4. Mass transfer coefficient
The gassing-in method was used to measure the O2 mass transfer
coefficient (kLa). Dissolved oxygen was displaced by bubbling nitrogen
into the reactor. Air was then sparged into the reactor at the desired
superficial gas velocity (0.0021–0.0210 m s−1
). A dissolved oxygen
metre and probe (Mettler Toledo, O2 4100; response time 10–20 s),
the latter placed at the top and centre of an airlift reactor, was used to
measure the increase in dissolved oxygen at 5 s time intervals. The kLa
for oxygen was calculated as the slope of the linearised two film theory
equation (Eq. (1)):
ln
C
Ã
−CL0
CÃ
−CL
¼ kLa à t ð1Þ
where C⁎ is the saturation concentration of dissolved oxygen, CLO is the
initial dissolved oxygen concentration at time t0 and CL is the oxygen
concentration at time t [10].
The kLa measured for oxygen was converted to the kLa for carbon
dioxide (kLa;CO2
) using the relative diffusivities of these gases and
(Eq. (2)):
kLa;CO2
¼ kLa;O2
DCO2
DO2
#0:5
ð2Þ
where the diffusivity for oxygen (DO2
) and carbon dioxide (DCO2
) (Talbot
et al., 1991) were taken to be 2.278 [58] and 1.94 cm2
s−1
[56],
respectively, at 25 °C in dilute solutions.
2.5. Mixing time
Mixing time was determined using a 6 M NaOH tracer and a single
conductivity probe (AZ Instruments) placed at the top and centre of
the reactor as described by Chisti et al. [7]. A phenolphthalein pH
indicator was also used to monitor mixing patterns in the airlift reactor
visually [16].
2.6. Net energy ratio
The Net Energy Ratio (NER) at each superficial gas velocity and CO2
concentration was calculated according to (Eq. (3)):
NER ¼
EOUT
EIN
ð3Þ
where EOUT is the energy that could be obtained from resulting biomass
or lipid (kJ), and EIN is the energy required to aerate the reactors (kJ).
Values for EOUT were calculated based on the calorific values of the
resulting biomass or lipid (Eq. (4)):
EOUT ¼ CX à Vr à Cal ð4Þ
where CX is the biomass or lipid concentration (g L−1
), Vr is the reactor
volume (L) and Cal is the calorific value of biomass or lipid (kJ g−1
). The
calorific values of high-lipid Scenedesmus cultures grown at high
(10,400 ppm) and low (3900 ppm) CO2 were measured using bomb
250 S.M.J. Jones, S.T.L. Harrison / Algal Research 5 (2014) 249–257

3. calorimetry (Department of Forest and Wood Science, University of
Stellenbosch, South Africa), and the calorific value of lipid was taken
from estimates by Lardon et al. [35].
Values for EIN were calculated according to the power used and the
cultivation time (Eqs. (5) and (6)):
EIN ¼ PG Ã t ð5Þ
PG
VL
¼
ρL à g à UG
1 þ
Ad
Ar
ð6Þ
where PG is the power for aeration (W), t is time (s), VL is the liquid
volume (m3
), ρL is the liquid density (kg m−3
), g is the gravitational
acceleration (m s−2
), UG is the superficial gas velocity (m s−1
), Ad is
the cross-sectional area of the downcomer (m2
), and Ar is the cross-
sectional area of the riser (m2
) [8].
2.7. CO2 transfer rate
The carbon dioxide transfer rate (CTR) can be described by (Eq. (7)):
CTR ¼
dCCO2
dt
¼ kLa;CO2
à CCO2;sat−CCO2;l
ð7Þ
whereCCO2;l is the residual dissolved CO2 in the bulk liquid andCCO2;sat is
the saturation solubility of CO2 at a given partial pressure, temperature
and ionic strength of the growth media. CCO2;sat was calculated for each
of the CO2 partial pressures used in these experiments, by thermo-
dynamic modelling using Visual MINTEQ software, version 3.0
developed by Gustafsson [23]. The CTR was then calculated using the kL
a;CO2
obtained at each superficial gas velocity used (Section 2.4). In this
work we calculated the maximum CTR obtainable when the CO2 is
completely depleted from solution and so the CCO2;l term was excluded.
2.8. Carbon uptake
The amount of carbon fixed into lipid was calculated using (Eq. (8)):
CUlipid ¼ Y Ã nlipid ð8Þ
where CUlipid is the number of moles of carbon used in lipid production
in a given experiment, Y is the number of moles of lipid produced, and
nlipid is the average number of moles of carbon in a mole of lipid.
These values were estimated based on the fatty acid profile of
Scenedesmus sp. cultivated under nitrogen limitation, yielding 46.2%
oleic acid (C18:1), 24.3% palmitic acid (C16:0) and 15.9% linoleic acid
(C18:2) [22].
2.9. CO2 supply rate
The CO2 supply rate (CSR) was calculated according to (Eq. (9)):
CSR ¼ UG Ã CCO2
ð9Þ
where CSR is the rate at which CO2 is supplied to the reactor given as the
superficial CO2 velocity in m s−1
, UG is the superficial gas velocity of the
sparge gas, and CCO2
is the percentage of this sparge gas that is CO2.
3. Results and discussion
3.1. Mixing and mass transfer
The mixing time and CO2 mass transfer coefficient (kLa;CO2
) were
measured at increasing superficial gas velocity (UG) in an airlift reactor
containing cell-free 3 N BBM media (Fig. 1). These parameters improved
(i.e. mixing time decreased and kLa;CO2
increased) with increasing
aeration, as expected. The power input was calculated at each super-
ficial gas velocity according to Eq. (6). Fig. 1 shows that the increased
mass transfer and improved mixing were at the expense of increased
power input.
Similar data are found in the literature, however kLa and mixing time
vary according to the type of sparger used, the liquid viscosity and the
airlift dimensions [32,37,41]. According to previous studies, mixing
times in airlift reactors range from 20 to 150 s at a UG of 0.0210 m s−1
[11,39,40,50]. The reactor dimensions and sparger described in this
work resulted in a mixing time of 32.9 s at 0.0210 m s−1
(Fig. 1), i.e.
at the lower end of the range found in the literature, indicating good
mixing.
Carbon dioxide transfer rates (CTR) were calculated with respect to
the saturation solubility of CO2 at various partial pressures (400 to 10
400 ppm) and the kLa;CO2
at superficial gas velocities of 0.0021,
0.0052, 0.0105 and 0.0210 m s−1
(Eq. (7)). These indicated the amount
of carbon available to algal cells. Fig. 2 shows CTRs at increasing power
input for aeration at the given velocities (Fig. 2a) and at increasing
CO2 supply rates (CSR; a function of superficial gas velocity and CO2
concentration, Fig. 2b). This figure demonstrates the importance of
high CO2 concentrations for good CTR. The CTR increased with increased
power for aeration at each CO2 concentration, and dropped substantial-
ly with reduced CO2 concentration. The CTR correlated well with CO2
supply rate (superficial CO2 velocity) across varying both superficial
gas velocity and CO2 concentration.
Moo-Young and Blanch [41] describe the increase in kLa with
increased power input in different reactor types. In accordance with
this work, they show the same relationship between power input and
mass transfer, highlighting the dependence of carbon availability on
the energy provided to the reactor for algal cultivation.
3.2. Biomass and lipid production
Fig. 3 shows the algal growth and lipid production with respect to
time under ‘standard cultivation conditions’ (10 400 ppm CO2; 0.0210
m s−1
superficial gas velocity). Concentrations of 2.27 g L−1
biomass
and 0.635 g L−1
lipid were measured after 12 days cultivation. A
maximum lipid content of 32.1% biomass, and maximum biomass and
lipid productivities of 0.306 and 0.081 g L−1
d−1
, respectively, were
also obtained under ‘standard conditions’. The subsequent experiments
assessed the effect of reduced input for aeration on maintaining these
concentrations.
The maximum biomass and lipid concentrations in Fig. 3 correlate
with previous results from the growth of Scenedesmus sp. under
Fig. 1. Power input required for aeration (W m−3
) at increasing superficial gas velocities
(m s−1
) with respect to mixing time (s) andkLa;CO2
(s−1
) at these superficial gas velocities.
Error bars represent the standard deviation of n = 3 replicates.
251S.M.J. Jones, S.T.L. Harrison / Algal Research 5 (2014) 249–257

4. nitrogen limited conditions [22]. In a comparison of several microalgal
species it was seen that Scenedesmus sp. had high lipid productivity,
motivating its use in the current work [22]. Griffiths and Harrison [20]
reviewed the maximum lipid content, biomass and lipid productivity
of a wide variety of algal species. Biomass productivities were reported
to range from 0.03 to 0.59 g L−1
d−1
with biomass productivity
obtained in this work well within this range (0.306 g L−1
d−1
). Griffiths
and Harrison [20] reported lipid content to range from 5 to 64% biomass
under nitrogen deficient conditions, and lipid productivity from 0.017 to
0.164 g L−1
d−1
. Scenedesmus sp. cultivated in this work reported
towards the upper end of these ranges, demonstrating its ability as a
lipid producer. Scenedesmus sp. also had higher biomass and lipid
productivities under standard conditions compared to a number of
freshwater algal species reviewed by Rodolfi et al. [49].
Growth experiments at superficial gas velocity and CO2 con-
centration lower than the ‘standard conditions’ were conducted, and
biomass growth and lipid production were monitored. The superficial
CO2 velocity or CO2 supply rate (CSR) was calculated as the product of
the percentage CO2 sparged into the reactor (400, 1400, 5400 and
10,400 ppm) at the four superficial gas velocities (0.0021, 0.0052,
0.0105 and 0.0210 m s−1
). Fig. 4a shows the increased biomass con-
centration with increased CSR to a maximum of 2.27 g L−1
. Above the
critical CSR of 2.7 × 10−5
m s−1
(equivalent to a superficial gas velocity
Fig. 2. CO2 transfer rates (a function of CO2 saturation solubilities andkLa;CO2
) with respect
to a) power input, and b) CO2 supply rate at various CO2 partial pressures and superficial
aeration velocities. Note: the deeper the shade of the point, the higher the UG; where the
black points represent data at a superficial gas velocity of 0.0210 m s−1
.
Fig. 3. Growth curve of Scendesmus sp. showing biomass and lipid production. Error bars
indicate the standard deviation of n = 2 dry weight and lipid measurements.
Fig. 4. a) Maximum biomass concentration; b) overall biomass productivity, calculated
according to the number of days required to reach maximum biomass concentration;
c) instantaneous biomass productivity obtained in 2 week cultivation in relation to the
superficial CO2 velocity or CO2 supply rate to the reactor. Note: the deeper the shade of
the point, the higher the UG; where the black points represent data at a superficial gas
velocity of 0.0210 m s−1
. The dotted line represents the CSR threshold. Error bars show
the standard deviation calculated from n = 5 repeats under ‘standard conditions’ (0.144
g L−1
biomass).
252 S.M.J. Jones, S.T.L. Harrison / Algal Research 5 (2014) 249–257

5. of 0.0052 m s−1
and CO2 concentration of 5400 ppm), further increase
in either CO2 concentration or superficial gas velocity did not increase
biomass production significantly. This is a significant consideration for
energy input. While differences in the maximum biomass concentra-
tions obtained may also be influenced by limitation of other nutrients,
these concentrations were not altered in this study. The rate of growth
during the linear phase, representing biomass productivity, is a better
indication of the influence of CO2 limitation independently of other
nutrients. This productivity, given as overall and instantaneous pro-
ductivity in Fig. 4b and c respectively, follows similar trends to the
maximum biomass concentration given in Fig. 4a, where a critical CO2
supply rate can be reached at low superficial gas velocity (0.0052 m s
−1
) and high CO2 concentration (10,400 ppm).
Fig. 5a illustrates the maximum biomass concentration attained as a
function of CO2 transfer rate. The same trend is seen as in Fig. 4, with a
critical CTR (0.00185 mol L−1
h−1
) above which no further increase in
biomass concentration is observed. Figs. 4 and 5 demonstrate that at
400 and 1 400 ppm CO2, the standard superficial gas velocity of
0.0210 m s−1
; (shown as black points on the graphs) is required to
maintain maximum biomass concentrations of ≥2 g L−1
; whereas at
5400 and 10,400 ppm CO2, the superficial gas velocities could be
reduced to 0.0052 m s−1
without sacrificing biomass concentration or
productivity. According to Fig. 1, this equates to a 75% reduction in the
power input required for aeration.
Fig. 5a shows that, at lower superficial gas velocities, the maximum
biomass concentration is not achieved despite the critical CTR being
met. This suggests that superficial gas velocity influences a second factor
(in addition to carbon limitation) required for growth. This highlights
the complexity of algal cultivation systems, with interdependent
parameters. In an airlift reactor, gas sparging is responsible for CO2
provision and for mixing. Mixing is important for distribution of
nutrients (carbon, nitrogen, phosphorous, and other nutrients) and
access of algal cells to sufficient light for photosynthesis. Therefore,
the reduction in growth at low superficial gas velocity under non-
limiting CTR suggests mixing or light limitation. The latter is shown by
Gani and Harrison (in prep). Fig. 5b shows the decrease in biomass
with decreased superficial gas velocity, which affects both CO2 provision
and mixing. The rate at which biomass increases with increased CO2
concentration is higher at the lower gas velocities, indicating the degree
of carbon limitation. Also, at higher CO2 there is a smaller difference in
biomass across superficial gas velocities.
Biomass productivity depends on both the rate of biomass formation
and its concentration (Q = μX); its relationship with time thus
influences the energy input requirement. Fig. 6 shows that at 10,400
and 5400 ppm CO2, the superficial gas velocity could be reduced from
0.021 to 0.0052 m s−1
without a significant decrease in biomass
productivity. Energy consumption is discussed further in Section 3.3.
Typical CO2 concentrations used in previous algal cultivation studies
range from 10,400 to 150,400 ppm [31,49,52]. In support of this study,
results from Sasi [52] showed that air enriched with CO2 above
50,000 ppm does not lead to further increase in growth rate of Chlorella
vulgaris; and similarly Langley et al. [34] show a minimum threshold of
1200 ppm CO2 to maintain algal biomass productivity of C. vulgaris.
Kaewpintong et al. [31] investigated the effect of superficial gas velocity
on the growth of Haematococcus pluvialis and demonstrated an increase
in growth with increased velocity up to 0.04 m s−1
, above which no
further increase occurred. These results support the claim that a critical
CO2 availability or sparging rate exists. However, the reports study
either CO2 concentration or superficial gas velocity independently, and
data represented by varying only one of these factors is system-
specific and of limited value to generalised application. This work is
the first to report the combined effect of both CO2 concentration and
superficial gas velocity, represented as a critical CO2 supply rate or CO2
transfer rate.
Lipid production data also showed a critical CSR, but at 1.4 × 10−5
m
s−1
(0.0105 m s−1
superficial gas velocity and 1400 ppm CO2) with lipid
content as a percentage of the biomass reaching 38.3% (Fig. 7a). Inter-
estingly, the lipid content peaked between 1.4 × 10−5
and 2.1 × 10−5
m s−1
and then dropped with further increase in CSR before rising
again to 36.3%. This perhaps indicates that at lower CSR (around 1.4 ×
10−5
m s−1
) the algae favour lipid storage over cellular replication,
and above this CSR the algae return to favouring cellular replication
and use up the lipid stores for growth, thus leading to a reduction in
the cellular lipid content. The lipid content increased again when
Fig. 5. a) Maximum biomass concentration with respect to CO2 transfer rate (a function of
CO2 concentration andkLa;CO2
). Note: the deeper the shade of the point, the higher the UG;
the horizontal line indicates the drop from the maximum biomass, where mixing or light
could be limiting. Error bars show the standard deviation calculated from n = 5 repeats
under ‘standard conditions’ (0.144 g L−1
biomass). b) Maximum biomass obtained with
respect to CO2 concentration in the sparge gas at each of the superficial gas velocities
independently.
Fig. 6. Superficial gas velocity and CO2 concentration with respect to biomass productivity
(Qx), calculated according to the number of days required to reach maximum biomass
concentration. Error bars indicate standard deviation calculated from n = 5 repeats
under ‘standard conditions’.
253S.M.J. Jones, S.T.L. Harrison / Algal Research 5 (2014) 249–257

6. there was excess carbon available for growth and lipid storage. A similar
trend was seen in Fig. 7b and c, for volumetric lipid production (g L−1
)
and lipid productivity (g L−1
d−1
), respectively. However, these graphs
indicate that the drop in lipid production and productivity coincides
with lower superficial gas velocity. This suggests a second factor, other
than carbon limitation, such as mixing rates (affecting light regimes,
and distribution of media components, as discussed earlier), influences
the lipid production and productivity despite the CSRs. This trend can
also be seen in Fig. 8, where the moles of carbon fixed into lipid
increased to a peak at a lower CSR (0.01 mol at 2.8 × 10−5
m s−1
),
then decreased, and finally reached a maximum at high CSR (0.13 mol
at 1.1 × 10−4
m s−1
), when superficial gas velocity is high.
Previous studies have highlighted the link between nutrient
availability and lipid production, but most of these studies have focused
on nitrogen, phosphorous and silicon [13–15,20]. The findings in this
work are important to begin understanding the relationship between
carbon availability and lipid production by algae. A study by Chiu et al.
[12] reported similar results to this work, where Nannochloropsis oculata
had biomass and lipid productivities that were poor at 400 ppm CO2
(air),reached maximum at 20,400 ppm (0.145 g L−1
d−1
lipid), and
decreased again between 50,400 and 150,400 ppm CO2.
3.3. Net energy ratios
Net energy ratios (NER) were calculated according to Eqs. (3) to (6).
For a NER greater than 1, more energy can be obtained from the biomass
or lipid than is used for aeration. Fig. 9 shows that at the ‘standard’
superficial gas velocity (0.0210 m s−1,
) the energy required for aeration
outweighed the energy that could be obtained from the cultivated
biomass (NER b 1). For 0.0021, 0.0052 and 0.0105 m s−1
, the NER was
above 1 provided that the CO2 concentration was above 400 ppm. At
400 ppm, low biomass concentrations resulted in NERs below 1 at all
superficial gas velocities. A maximum NER of 10.87 was obtained at
0.0021 m s−1
and 5 400 ppm CO2, however, under these conditions the
biomass concentration was only 1.49 g L−1
(compared to 2.27 g L−1
under ‘standard conditions’, Fig. 3). A lower biomass concentration
could lead to increased energy input required for harvesting and down-
stream processing, as well as a greater reactor volume required to yield
the same amount of product. At 0.0052 m s−1
and 5 400 ppm, on
the other hand, the NER was 5.47 and the biomass concentration was
2.08 g L−1
, indicating an improved energy ratio and minor reduction
in biomass compared to the standard conditions (0.0210 m s−1
and
10,400 ppm).
The instantaneous biomass productivity and NER increased simulta-
neously (Fig. 9b) due to the dependence of NER on the maximum bio-
mass concentration obtained and the time taken to reach this. Fig. 9b
shows that this increase reaches a maximum at 0.223 g L−1
d−1
and
an NER of 2.65 (at 0.01 m s−1
and 10,400 ppm), and that an NER of
4.99 can be reached with only a slight decrease in productivity (0.199
g L−1
d−1
; at 0.005 m s−1
and 10,400 ppm).
In a microalgae bio-production plant, the energy for aeration, mixing
and harvesting have major impacts on the NER [29,49]. In this study,
values of NER were calculated based on mixing and aeration by gas
sparging, and did not include light provision, pumping, harvesting or
Fig. 7. The CO2 supply rate is also shown in relation to a) the maximum lipid content (as %
of biomass) and b) the maximum lipid concentration obtained during 2 weeks cultivation,
and c) the lipid productivity (Qp) calculated according to the time taken to reach
maximum lipid concentration. Note: the deeper the shade of the point, the higher the
UG. Error bars indicate the standard deviation calculated from n = 5 repeats under
‘standard conditions’.
Fig. 8. Carbon uptake, or the total number of moles of carbon fixed into lipids (calculated
based on the moles of lipid produced, and the average number of moles of carbon in a mole
of lipid), with respect to the CO2 supplied to the reactor. Note: the deeper the shade of the
point, the higher the UG. Error bars indicate the standard deviation calculated from n = 5
repeats under ‘standard conditions’.
254 S.M.J. Jones, S.T.L. Harrison / Algal Research 5 (2014) 249–257

7. lipid extraction, owing to these having smaller impacts on NER com-
pared to the substantial impact of the reactor energy requirements [46].
Previous studies have shown NER based on mixing, aeration and
harvesting (or dewatering) to be between b1 (for a flat panel reactor
with bubble column concept for mixing; and external loop airlift) and
6 (for an algal biofilm reactor) [30,44,49]. This indicates the potential
for improvement of NER values based on reactor choice and design, as
well as aeration, mixing and harvesting approaches. The optimisation
of aeration and CO2 supply in this work resulted in a maximum NER
well above the range found in literature (10.87), and a NER of 5.47 at
biomass concentrations comparable to literature values, indicating
the importance of this work in progressing towards feasible algal
production processes in PBRs.
NER based on lipid production only are much lower than for biomass
plus lipid. Fig. 10 shows that NER values were below 1 for all reactor
conditions, except 0.0021 m s−1
and 0.005 m s−1
at 5400 and
10,400 ppm CO2. However, under these conditions the volumetric
lipid concentrations were 0.376, 0.375, 0.403 and 0.343 g L−1
,
respectively, which are substantially lower than lipid concentration
under ‘standard conditions’ (0.635 g L−1
). Hence, both biomass and
lipid must be used for feasible bioenergy production.
Several comprehensive techno-economic evaluations have been
published with respect to the feasibility of algal bioenergy. They all
highlight the considerable impact of power for mixing and gas provision
on the overall energy consumption and cost. Jonker and Faaij [29] and
Chisti [9] suggest that using airlift devices in place of mechanical stirring
could reduce the high energy consumption and cultivation costs
associated with bioenergy production from microalgae. Optimisation
of aeration and CO2 supply strategies, as shown in the current work
(Figs. 4 to 10), can further improve the energetic feasibility of algal
lipid production and thus reduce cost. Evaluation of CO2 uptake efficien-
cies is also important for further improvements [29,48].
Jonker and Faaij [29] and Zhang et al. [60] illustrate the energetic and
economic improvements incurred by using CO2 from flue gas as well as
wastewater for algal cultivation. There is a considerable energy cost as-
sociated with CO2 supply in the form of compressed gas, but in this work
we assume that due to the availability of numerous high CO2 content
waste streams, this requirement can be avoided. In addition to reduced
reactor energy, use of waste CO2 streams is important for CO2 cycling, to
enable on-going value generation from the same CO2, rather than liber-
ating new CO2.
4. Conclusions
For the effective production of algal bioenergy, NER is a major con-
sideration in selecting reactor operating conditions. This study sought
to improve the NER of algal biomass and lipid production in an airlift
PBR by optimising superficial gas velocity and CO2 concentration. At
high CO2 concentration in the gas phase (5400–10,400 ppm), the super-
ficial gas velocity could be reduced fourfold over that previously report-
ed (0.02 m s−1
) without substantial decrease in biomass concentration
or productivity. On further reduction of superficial gas velocity below
0.005 m s−1
, it was proposed that the decreased biomass formation
observed was attributed to compromised mixing. On sparging with
gases of lower CO2 concentration (400–1400 ppm), some loss of
productivity was observed with decreasing superficial gas velocity.
These factors were considered using the combined term, carbon supply
Fig. 9. a) Maximum net energy ratios obtained during growth at various superficial gas ve-
locities (UG) and CO2 concentrations (ppm). b) Instantaneous biomass productivity (g L−1
d−1
) with respect to NER; where the dotted line is at NER = 1, and the solid line illustrates
the small decrease in productivity (0.223 to 0.199 g L−1
d−1
), and large increase in NER
(2.65 to 4.99, respectively) between these points. Error bars indicate the standard devia-
tion calculated from n = 5 repeats under ‘standard conditions’.
Fig. 10. a) Maximum net energy ratios at various superficial gas velocities (UG) and CO2
concentrations (ppm). b) Instantaneous lipid productivity (g L−1
d−1
) with respect to
NER. The dotted line indicates NER = 1. Error bars indicate the standard deviation calcu-
lated from n = 5 repeats under ‘standard conditions’.
255S.M.J. Jones, S.T.L. Harrison / Algal Research 5 (2014) 249–257

8. rate (CSR, also termed CO2 superficial velocity), to develop a generalised
relationship to describe CTR (carbon transfer rate). A critical value for
the CSR was demonstrated which, if exceeded, had no further benefit
to productivity; this has not been reported previously. By considering
this approach, the NER could be increased to values of 5.5 at appropriate
biomass productivities and 10.9 at reduced biomass productivity. These
represent a substantial increase over those below 1, reported pre-
viously. The NER based on lipid only was also increased above 1, but
only at lower lipid productivity, indicating the importance of dual prod-
uct systems where lipid is the desired product. The results of this work
are testament to the importance of this approach toward the feasible
production of algal bioenergy.
Acknowledgments
The assistance of Dr Griffiths (University of Cape Town) and Dr
Menkin (Stellenbosch University) are gratefully acknowledged, as is
the assistance of Murray Fraser through the provisions of mixing time
data for the reactor system. The financial support of the South African
Research Chairs Initiative (SARChI) (UID 64778) of the Department of
Science and Technology and the National Research Foundation (NRF)
of South Africa (80049) is also acknowledged. The Grantholder ac-
knowledges that opinions, findings and conclusions or recommenda-
tions expressed in any publication generated by the NRF supported
research are that of the authors, and that the NRF accepts no liability
whatsoever in this regard.
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