Chemical Engineering Journal 252 (2014) 104–111

Contents lists available at ScienceDirect

Chemical Engineering Journal

journal homepage: www.elsevier .com/locate /ce j

Dynamic photosynthetic response of the microalgaScenedesmus obtusiusculus to light intensity perturbations

http://dx.doi.org/10.1016/j.cej.2014.04.0731385-8947/� 2014 Elsevier B.V. All rights reserved.

⇑ Corresponding author. Tel.: +52 55 5814 6536.E-mail address: srevah@correo.cua.uam.mx (S. Revah).

Juan Cabello a, Marcia Morales b, Sergio Revah b,⇑a Doctorado en Biotecnología, Universidad Autónoma Metropolitana-Iztapalapa, San Rafael Atlixco 186, C.P. 09340 México, DF, Mexicob Departamento de Procesos y Tecnología, Universidad Autónoma Metropolitana-Cuajimalpa, Av. Vasco de Quiroga 4871, colonia Santa Fe Cuajimalpa, C.P. 05300 México, DF, Mexico

h i g h l i g h t s

� The microalga Scenedesmus obtusiusculus acclimates fast to irradiance changes.� Dynamic experiments allow rapid analysis of short-term photosynthetic response.� Temperature variations may induce an apparent hysteresis in photosynthetic response.� N-starved cells show slow re-directing of metabolic fluxes to lipid accumulation.

a r t i c l e i n f o

Article history:Received 3 January 2014Received in revised form 1 April 2014Accepted 17 April 2014Available online 30 April 2014

Keywords:Photo-acclimationPhotosynthetic responseScenedesmusPhotobioreactorsAlgal oilDynamic model

a b s t r a c t

Unsteady state experiments in microalgal cultivation are important to evaluate the influence of the irra-diance on the dynamic photosynthetic response and to develop dynamic models for the design of photo-bioreactors. In this paper, the short-term effect of incident light fluctuations on the oxygen production bythe microalga Scenedesmus obtusiusculus cultivated in a 20 L air-lift photobioreactor was performed at dif-ferent operation times under nitrogen-replete or nitrogen-starved conditions. It was possible to reachsteady states in the oxygen production indicating short-term photosynthetic acclimation and the highestvalues during the incremental light step-changes were between 103 and 207 mgO2 gb

�1 h�1 for light inten-sities between 141 and 505 lmol m�2 s�1 at 0.13 gb L�1. The photosynthetic response was not symmetricin the increase/decrease light step-changes due to temperature variations caused by the illumination sys-tem. Moreover, in nitrogen-starved conditions the dynamic photosynthetic response was slower than innitrogen-replete levels declining to 70% at 0.5 gb L�1 at the maximum light intensity. Furthermore, amathematical model was developed to estimate the dynamic oxygen response and the biomass produc-tivity. The simulations predicted the highest O2 concentrations at 35 �C and irradiances above600 lmol m�2 s�1 and the highest biomass productivity was 0.78 gb L�1 d�1.

� 2014 Elsevier B.V. All rights reserved.

1. Introduction

Microalgal cultivation is a promising technology for the biologi-cal fixation of carbon dioxide and the generation of high value-added products including renewable fuels [1]. As an example, oilsfrom algae can yield biodiesel through transterification and gasolineor jet fuel through distillation and cracking. Different photobioreac-tor configurations can be used for cultivation, including tubular,panel and raceway ponds. Light availability influences decisivelythe photosynthesis process, the specific growth rate andconsequently biomass productivity. Light is absorbed and scatteredby the cells [2] and therefore is spatially distributed; and most of the

cultivation systems are limited by light availability. The influence oflight on the photosynthesis rate can be obtained from the photosyn-thesis–irradiance, P–I curve [3], which is particular for each strainand must be measured under diluted culture to assure that cellsare exposed to the same irradiance. For spatial light distributionmost of the works consider an average irradiance defined as theaverage of local irradiance values inside the culture [4] but someothers represent the radial decrease of light intensities [2,5] andthe mixing effects [6,7]. Furthermore, the knowledge of photosyn-thesis dynamics under fluctuating light conditions and the determi-nation of physical and biological parameters is important andneeded for: (a) the design, modeling and simulation of the process,(b) the scale up of laboratory experiments to industrial level and (c)the development of control systems that can be implemented formeasuring or estimating key variables in the process unit to

Nomenclature

Cb biomass concentration, g L�1

CG,O2 oxygen bulk-gas concentration, mg L�1

CG,O20 initial oxygen concentration, mg L�1

CL,O2 oxygen bulk-liquid concentration, mg L�1

CL,O2sat saturation oxygen concentration, mg L�1

CL,O2,i oxygen concentration by each pseudo-steady state,mg L�1

CCO2,s CO2 concentration in gas phase at the inlet of the reac-tor, mg L�1

CCO2,e CO2 concentration in gas phase at the outlet of the reac-tor, mg L�1

CL,CO2sat saturation carbon dioxide concentration, mg L�1

DO2 diffusion coefficient for oxygen, m2 s�1

DCO2 diffusion coefficient for carbon dioxide, m2 s�1

Daz axial dispersion coefficient, m2 s�1

dt tube diameter, mEa activation energy, kcal mol�1

Ed deactivation energy, kcal mol�1

FG gas flow, L min�1

H partition coefficient from Henry law, defined by H = H�/RT, dimensionless

H� Henry coefficient, atm-m3 mol�1

hg gas hold-up, m3 m�3

hL liquid hold-up, m3 m�3

I0 incident light intensity on reactor surface, lmol m�2 s�1

Iav average light intensity within the reactor, lmol m�2 s�1

k0, k1 frequency factors of Arrhenius, mgO2 gb�1 s�1

Ka biomass light absorption coefficient, m2 gb�1

Kd metabolic coefficient, h�1

KI inhibition constant for light intensity, lmol m�2 s�1

KLaO2 volumetric mass transfer coefficient for oxygen, h�1

KLaCO2 volumetric mass transfer coefficient for carbon dioxide,h�1

Ks irradiation constant, lmol m�2 s�1

L reactor length, mPb biomass productivity, gb L�1 h�1

PO2,max maximum photosynthesis rate, mgO2 gb�1 s�1

PPFR photosynthetic photon fluence rate, lmol m�2 s�1

rO2,exp experimental oxygen production rate per biomass unit,mgO2 gb

�1 h�1

rO2,intr intrinsic oxygen production rate per biomass unit,mgO2 gb

�1 h�1

rCO2,exp experimental carbon dioxide uptake rate per biomassunit, mgCO2 gb�1 h�1

T temperature, Kt time, minuGe effective gas velocity, m s�1

uLe effective liquid velocity, m s�1

Yb/O2 biomass yield on oxygen, gb gO2�1

VR reactor volume, m3

z axial direction, m

J. Cabello et al. / Chemical Engineering Journal 252 (2014) 104–111 105

increase growth and biomass yield [8–11]. Temperature is anotherimportant environmental variable, which affects both the structureof cell components and the reaction rates. Recently, Béchet et al.[11] presented a complete review of the models used to describemicroalgal growth kinetics.

Photobioreactor design requires precise information on micro-algal growth. Biomass evolution results from the combined andcumulative effects of physical and biological phenomena includingphotosynthesis, fluid dynamics, mass transfer and irradiancewhich are spatially and diachronically distributed in the photobi-oreactors [12,13]. The models describing growth generally lumpthese effects and consequently it is not generally possible to ana-lyze them independently. Additionally, experiments are generallylengthy and several assays with different initial and operating con-ditions are required. An alternative is the determination of the oxy-gen production rate [3,9], which contrary to the growth rate, has adynamic response in the time scale of minutes. It is proportional tothe growth rate according to the stoichiometry of the overall pho-tosynthetic reaction [3] and it provides information about thephoto-acclimation phenomena generated in the photosystem IIas a response to fluctuations in the light intensity [14,15]. Further-more, the time needed for determination of the photosynthesis-irradiance curves and the associated kinetic parameters is reducedand some models [8,9,11,16–18] have been developed for predict-ing O2 production. However, photosynthesis rate curves under N-replete conditions obtained in short unsteady state experimentsof incident light fluctuating have not been quantitatively deter-mined yet.

Nitrogen starvation conditions have so far been the most com-monly employed approach for directing metabolic fluxes to lipidaccumulation of microalgae. However, the effect of incident lightperturbations on the oxygen dynamic responses under nitrogenN-starved conditions has not been studied. This could provideinformation about the changes in the metabolic regulation, whichwould be achieved by the adjustment of PSI:PSII stoichiometry anddepends on the novo protein synthesis [19].

The aim of this work was to study the dynamic response of thephotosynthetic activity of the microalga Scenedesmus obstusiuscu-lus to different light intensities in an air-lift photobioreactor underN-replete and N-starved conditions. The first case could be closelyrelated to the short-term photo-acclimation and the second case tothe long-term metabolic adaptation. Furthermore, a mathematicalmodel which predicts the oxygen concentration and biomass pro-ductivity using parameters obtained from experiments was vali-dated considering the hydrodynamics and mass transfer withinthe system and a kinetic expression for intrinsic oxygen productionrate representing the photosynthesis activity as function of tem-perature, light intensity and biomass concentration under N-replete conditions.

2. Materials and methods

2.1. Model development

A transient one-dimensional model was used to represent oxy-gen concentration as overall product of the photosynthesis processwithin an air-lift photobioreactor. The following assumptions wereconsidered:

(1) The gas and liquid-microalga phases are homogeneouslydistributed inside the reactor and their respective volumefraction is conserved, i.e. hL + hG = 1.

(2) There is a homogeneous distribution of rising bubblesthroughout the air-lift riser.

(3) The gas phase is represented by plug flow.(4) The liquid phase is represented by an isothermal and axial

dispersion model.(5) The physical and transport properties of the culture media

such as viscosity, density and axial dispersion coefficientare considered similar to those of water.

(6) Light distribution is considered within a homogenous isotro-pic medium.

Fig. 1. Schematic diagram of the experimental air-lift photobioreactor used for growth of the microalga S. obtusiusculus.

106 J. Cabello et al. / Chemical Engineering Journal 252 (2014) 104–111

(7) Biomass response is based on the average light in the photo-bioreactor and is independent on the short light cycles foundin the air-lift configuration.

(8) The biomass concentration does not change during thedynamic experiments.

(9) The concentrations of carbon dioxide and nutrients donot limit oxygen production during the dynamicexperiments.

Based on these assumptions, Eq. (1) shows the macroscopicoxygen mass balance in the liquid phase to estimate the oxygenbulk-liquid concentration CL,O2.

hL@CL;O2

@t¼ hLDaz

@2CL;O2

@z2 �hLuLe@CL;O2

@z�KLaO2 CL;O2 �

CG;O2

H

� �þ rO2 Cb ð1Þ

with the following initial and boundary conditions (Fig. 1):

t ¼ 0; CL;O2 ¼ CsatL;O2

z ¼ 0; CL;O2 ¼ CsatL;O2þ Daz

uLe

@CL;O2

@zz

¼ L;@CL;O2

@z¼ 0 ð2Þ

In Eq. (1), rO2,intr is the intrinsic O2 production rate per biomassunit defined as:

rO2 ;intr ¼ pO2 ;maxIav

Ks þ Iav þ I2avKI

0@

1A ð3Þ

where Iav is the average light intensity inside the air-lift photobior-eactor and is represented, [20], by:

Iav ¼I0

dtKaCb1� expð�dtKaCbÞ½ � ð4Þ

Moreover, pO2,max is the maximum O2 production rate for themicroalga under the culture conditions. It can be related to tem-perature through the Arrhenius expression given in Eq. (5) [21];

pO2 ;max ¼ k0 exp�Ea

TR

� �� k1 exp

�Ed

TR

� �ð5Þ

The mass balance for the oxygen bulk-gas concentration in gasphase CG,O2 is:

hg@CG;O2

@t¼ �uGehg

@CG;O2

@zþ KLaO2 CL;O2 �

CG;O2

H

� �ð6Þ

With the following initial and boundary conditions:

t ¼ 0; CG;O2 ¼ C0G;O2

z ¼ L;@CG;O2

@z¼ 0 ð7Þ

Biomass productivity Pb is associated to the rO2,intr and to themetabolic coefficient (Kd) [11,17] as:

dCb

dt¼ Pb ¼ rO2 ;intrCbYb=O2

� KdCb ð8Þ

The numerical solution of the Eqs. (1)–(7) was carried out inFlexPDE software 6.06 student version. It uses the finite elementmethod for solving partial differential equations. The hydrodynam-ics of the photobioreactor was solved using the Bubbly Flow appli-cation in the Chemical Engineering module of the commercialsoftware COMSOL Multiphysics, (Burlington MA, USA).

Fig. 2. Experimental data of N-replete biomass growth, dissolved O2, dissolved CO2,pH and temperature evolution during the normal operation conditions of the air-liftphotobioreactor, and the periods in which the perturbations in the light intensitywere carried out (DI0).

J. Cabello et al. / Chemical Engineering Journal 252 (2014) 104–111 107

2.2. Experimental

2.2.1. InoculumThe microalga Scenedesmus obtusiusculus [22], a promissory

strain for dioxide carbon fixation and lipid storage was used. Itwas initially cultivated for 2 weeks in a 3 L bubble column reactorwith mineral medium BG-11 at 30 �C and a pH of 7.5 under contin-uous fluorescent light illumination of 96 lmol m�2 s�1. The reactorwas fed with air containing 3.8% CO2 at a superficial velocity of0.014 m s�1. The air-lift photobioreactor was inoculated with thisculture in the exponential growth phase. N-replete medium exper-iments refer to the BG-11 medium with normal nitrogen concen-tration and N-starved is when medium does not contain nitrogensource.

2.2.2. Description of the instrumented air-lift photobioreactorFig. 1 shows a schematic representation of the internal loop air-

lift photobioreactor. The acrylic column has a coaxial section withinternal diameter of 12.7 cm and a height of 110 cm and a degas-sing zone of 40 cm with a diameter of 20 cm. The concentric tubehas an inner diameter of 8.3 cm and an effective height of105 cm, it was located 5 cm above the bottom of the column. Thegas phase was distributed from the bottom through a sparger with60 holes of 0.56 mm internal diameter.

The external artificial illumination system consisted of highintensity white light LEDs (10 m of LED 5050 strip lights, illumi-nate LEDs, China) and also four 54 Watts fluorescent lamps(400–700 nm, MAGG, Mexico). The intensity of light incident onthe surface of photobioreactor was measured with a quantum sensor2p (407026sp, Extech, USA) and the photosynthetic photon fluencerate, PPFR, in the center of reactor with a spherical micro quantumsensor 4p (US-SQS/L, Heinz Walz GmbH, Germany). The pH wasmeasured with an electrochemical sensor (27003-20, Cole-Parmer,USA). A polarographic sensor (SN-29020-10, Cole-Parmer, USA)was used to determine the dissolved oxygen concentration in therange of 0–200%; dissolved CO2 was measured with an electro-chemical sensor (SN-29000-01, Cole Parmer, USA). CO2 in the gasphase was monitored with an infrared detector (9500, OmegaAlpha, USA). The signals of the sensors located were continuouslyrecorded on-line by a data acquisition module (CompactDAQmx,NI, USA) connected to a computer equipped with a NI LabVIEWsoftware for data logging.

The photobioreactor was operated in batch mode with 16.8 L ofN-replete medium and 1.8 L of S. obtusiusculus inoculum andexposed to a continuous light intensity of 117 lmol m�2 s�1. Aircontaining 3.8% CO2 was continuously supplied at a gas superficialvelocity of 0.0104 m s�1 (based on the cross sectional area of theriser, 3.4 L min�1). The air-lift photobioreactor was also operatedin N-starved conditions with a biomass concentration of around0.5 g L�1. Biomass was determined every 24 h by dry weight afterfiltration with 0.4 lm and lipid content was evaluated at the endof the experiment with Nile Red [22].

2.2.3. Dynamic experimentsThe dynamic experiments to determine the O2 evolution at dif-

ferent light intensities and at different growth stages of the micro-alga S. obtusiusculus were made from the first day of operation andsequentially as indicated in Fig. 2. The dynamic experimentsstarted with a light intensity of 117 lmol m�2 s�1 followed by stepincreases to 141, 180, 336 and 505 lmol m�2 s�1 for periods of30 min each. Once the highest light intensity was reached, it wassequentially decreased to the same light intensities also for30 min down to the normal conditions (117 lmol m�2 s�1). Theseexperiments were done at different operation times when biomasscontents were 0.13, 0.3, 0.4, 0.5, 1.7 and 1.9 g L�1. At these condi-tions, the variables reached different pseudo-steady states and at

this point the observable rate of O2 production per biomass unitwas determined for each dynamic experiment by the equation:

rO2 ;exp ¼ KLaO2 ðCL;O2 i � CsatL;O2Þ ð9Þ

considering the O2 saturation concentration, CsatL,O2 and the O2 volu-

metric mass transfer, KLaO2, obtained in abiotic conditions.For each dynamic experiment, the CO2 uptake rate was deter-

mined based on the gas velocity and the difference of the CO2 con-centration in the gas phase at the inlet and outlet of the reactor foreach pseudo-steady state, using Eq. (10).

rCO2 ;exp ¼ðCCO2 ;s � CCO2 ;eÞ � FG

VRð10Þ

These dynamic experiments were done for both N-replete andN-starved conditions.

2.2.4. Determination of the model parametersAn independent experiment at 28 ± 3 �C, under N-replete

growth conditions, was made in the airlift photobioreactor withoutlight intensity perturbations to determine the stoichiometric yieldcoefficient, Yb/O2 and the metabolic coefficient, Kd. The parameterswere calculated from O2 production and biomass evolution during9 days of operation.

The axial dispersion coefficient, Daz, was experimentally evalu-ated in abiotic conditions from the residence time distributioncurve obtained by injection of a tracer (1 M NaOH, 15 ml) intothe liquid phase. The gas hold-up, hG, effective gas velocity, uGe,and effective liquid velocity, uLe, in the air-lift photobioreactorwere estimated with the COMSOL software similarly to the workreported by Heckmat et al. [10], using the momentum transportequations (two-fluid Euler–Euler model) for bubble column flowfor the axial symmetry (2D) geometry (mesh of 12704 triangularelements. The simulation was done with a gas superficial velocityof 0.0104 m s�1.

The volumetric mass transfer coefficient for O2, KLaO2, wasexperimentally estimated from the overall gas–liquid mass trans-fer coefficient of carbon dioxide. It was determined at pH of 4 bythe mass balance of the CO2 absorption in liquid phase, for a gassuperficial velocity of 0.0104 m s�1. The CO2 mass balance and

Fig. 3. Photosynthetic photon fluence rate (PPFR) in the airlift photobioreactorcenter as a function of biomass content and time (insert) during the normaloperation conditions.

108 J. Cabello et al. / Chemical Engineering Journal 252 (2014) 104–111

the correction for the diffusion coefficients were established as fol-lows [23]:

dCL;CO2

dt¼ KLaCO2 ðC

satL;CO2� CL;CO2 Þ; KLaO2 ¼ KLaCO2

DO2

DCO2

� �1=2

ð11Þ

The photosynthesis-irradiance curves of S. obtusiusculus at dif-ferent temperatures were obtained with a method similar to thatdescribed by Brindley et al. [3]. Thus, the intrinsic oxygen produc-tion rate was determined in a 3.5 ml jacketed reactor withmechanical agitation under controlled temperature and incidentlight intensity conditions. The initial biomass was adjusted to0.1 g L�1. Temperatures studied were between 5–40 �C and lightintensities between 9 and 2400 lmol m�2 s�1 in an arrangementof LEDs and fluorescence lamps set around the reactor. Dissolvedoxygen was continuously recorded on-line by a data acquisitionmodule for a 20 min period. The effect of the dynamic photosyn-thetic response to the temperature variations caused by the lightstep-changes was evaluated in an agitated isothermal 100 ml reac-tor containing 80 ml of a 0.5 g L�1 cell suspension.

Intrinsic kinetic parameters in Eq. (3), Ks, KI and pO2,max wereobtained from the photosynthetic-irradiance curves. The valuesof the intrinsic oxygen production rate were expressed as a func-tion of average irradiance, Iav, to which the cells were exposed,and fitted using a hyperbolic model with an inhibitory term[11,24]. The values of Ea, Ed, k0 and k1 were obtained by fittingEq. (5) to the maximum oxygen production, PO2,max, and the tem-perature. Intrinsic O2 production rate refers only to biological effectassuming low resistance of transport phenomena, low light atten-uation and uniform irradiance in the jacketed reactor.

The biomass light absorption coefficient in Eq. (4), Ka, wasdetermined by measuring the absorbance of cultures with differentbiomass concentrations. Light intensity in the center of the 3.5 mljacketed reactor illuminated from all directions was measuredwith the spherical micro quantum sensor 4p. The absorption coef-ficient was calculated with the Beer–Lambert law equation.

Fig. 4. Dynamic oxygen response to the light step-changes experiments, (a) and theeffect of temperature for a biomass content of 0.5 g L�1. (b) For biomass content of0.3, 0.4, 0.5 and 1.7 g L�1.

3. Results and discussion

Fig. 2 shows the evolution of biomass and operational condi-tions of S. obtusiusculus in the photobioreactor under N-repleteconditions. The discontinuities reflect the periods where thedynamic experiments comprising step changes of light intensitieswere performed. The dissolved O2 concentration increased fromsaturation, 6.4 mg L�1, to 10.5 mg L�1 when the biomass was1.7 g L�1. The dissolved CO2 concentration remained at around95.6% of saturation with respect to the inlet gas CO2 and the pHincreased from 6.4 to 7.2 due to nitrate and CO2 uptake. The overallresults showed cyclic temperature variations due to environmentalconditions, which in turn affected the produced O2 due to changesin the photosynthetic activity, the CO2 consumed through an initialaccumulation of intracellular inorganic carbon and further carbox-ylation reactions [25] and the pH by changes in the CO2 and bicar-bonate ion in the liquid phase. The small reduction in activity,observed at around day 11, was also related to the lower temper-ature. An algal concentration close to 2 g L�1 at day 15 was consis-tent with the initial mineral medium added and a residual solublenitrogen concentration of 64 mg L�1. The values of Yb/O2 of 0.65 gb

gO2�1 and of the metabolic coefficient (Kd) of 0.005 h�1 were obtained

in the experiment without light perturbation. The Yb/O2, was simi-lar to that reported by Acién et al. [20] of 0.77 gb gO2

�1 and the Kd tothat reported by Molina et al. [4] of 0.00385 h�1.

Fig. 3 shows the relationship between the internal PPFR and thebiomass. The non-linear behavior responds to the light attenuationcaused by absorption and scattering associated to the biomassincrease [12]. For instance, for biomass contents of 0.25 and

0.5 g L�1, the photon flux density in the center decreased fourfoldfrom 120 to 30 lmol m�2 s�1. In our case, for biomass concentra-tions above 1 g L�1, the reactor operated with less than17.2 lmol m�2 s�1 of PPFR in the annular section (laminar flow)and a dark phase in the concentric section (bubble flow). Underthese growth conditions, the final biomass content (close to2.0 g L�1) was lower than that previously found for this strain,[22], in a bubble column with an inner diameter of 0.105 m, and

Fig. 5. Comparison between the dynamic photosynthetic responses in N-repleteand N-starved conditions, for a biomass content of 0.5 g L�1 and 505 lmol m�2 s�1.Insert: relationship of the photosynthetic photon fluence rate (PPFR) under N-starved conditions; with high chlorophyll pigmentation (day 3) and low pigmen-tation (day 18).

Fig. 6. Experimental data representing the short-term photosynthetic acclimationof S. obtusiusculus under different incident light fluctuations for biomass contents of0.13(.), 0.3 (j), 0.4 (D), 0.5 (d), 1.7 ( ) and 1.9 g L�1 (s) of (a) the specific O2

production rates; and (b) the specific CO2 uptake rates.

J. Cabello et al. / Chemical Engineering Journal 252 (2014) 104–111 109

with an irradiance of 134 lmol m�2 s�1. Compared to air lift biore-actors, bubble columns induce a higher frequency of cells shiftingbetween the photic and dark zones due to mixing in all thecross-sectional area of the column which may possibly explainthe final yield difference.

3.1. Dynamic fluctuation of light intensity

As seen in Fig. 4a for a biomass content of 0.5 g L�1 under N-replete conditions, O2 concentration varies initially sharply as aphotosynthetic response to the light change and then slower dueto small temperature changes caused by the heat generated bythe external lamps. The pseudo-steady state O2 concentration, foreach irradiance, was obtained from the average in the slowresponse period with its corresponding temperature. The O2 con-centration response was not symmetric in the increase/decreaselight step-changes. The pseudo-steady state O2 concentrations,obtained during the decrementing steps in the light intensities,were higher than those previously obtained in the incremental partdue to a higher photosynthetic activity at higher temperatures. Therelevance of temperature is shown in Fig. 4a for an irradiance of336 lmol m�2 s�1, where the increment of about 3 �C increasedthe pseudo-steady state oxygen in the liquid phase approximately21% with respect to saturation despite the fact that at this highertemperature the O2 solubility is reduced by approximately 5%.For this microalga, the maximum value of the photosynthesisactivity is reached by an optimum temperature of 35 �C. A separatedynamic irradiance experiment in the 100 ml reactor under iso-thermal conditions (30 �C) yielded similar pseudo steady state dis-solved O2 values on both increasing/decreasing irradianceconfirming that the asymmetric behavior in Fig. 4b was inducedby temperature. Experiments presented by Levy et al. [26] showedthat, for some algae, the photosynthetic activities may vary in day-time during the morning and the afternoon, at the same sunlightintensities levels. This apparent hysteresis effect has been attrib-uted to a delay between the irradiation and the temperature gradi-ent that is generated [26].

Fig. 4b shows the results of the not symmetric photosyntheticresponse at different operation times when biomass were between0.3 and 1.7 g L�1 to the step changes of light intensities. For bio-mass contents of 0.3, 0.4, 0.5 and 1.7 g L�1, the highest values ofpseudo-steady state O2 concentrations were 10.4, 11.1, 11.3 and12.6 g L�1 for the increment in the light step-changes up to505 lmol m�2 s�1. Each pseudo-steady state represents theshort-term photo-acclimation period of S. obtusiusculus. In thiscase, the state transitions (excitation energy redistributionbetween photosystems) and non-photochemical mechanism oper-ate to adjust the amount of light energy delivered to photosystemII on a time scale of minutes [14,15,27].

Furthermore, significant changes in the optical properties of S.obstusiusculus were observed in the N-starved dynamic experi-ments. Fig. 5 compares the dynamic responses of O2 concentrationunder N-replete and N-starved conditions during the changes inthe light intensities. Nitrogen deprivation affected the mechanismsthat regulated short-term photosynthetic acclimation, resulting ina reduction in the photosynthesis activity and, therefore, the O2

concentration yield declined to 29% (day 3 of N-starvation) andto 70% (day 18 of N-starvation) of the N-replete levels due tochanges observed in cell pigmentation. N-limitation affects photo-synthesis activity reducing the efficiency of energy collection dueto the chlorophyll loss and to the adjustment of the relative quan-tities of non-photochemically active molecules such as lipids orcarotenoids [19,28].

The delay in the dynamic O2 responses under N-starved condi-tion in Fig. 5 compared to the N-replete medium, may be attributedto the slow adjustment of the PSI/PSII stoichiometry ratio [15] due

to the decrease of the novo protein synthesis that directly affectsthe PSII core proteins [19,27] due to nitrogen limitation. The N-starved dynamic O2 response reached 95% of the response inpseudo-steady state in about 6 h, (data not shown) indicating along-term photosynthetic adaptation of the cells [27].

Fig. 5 shows the light attenuation under N-starvation conditionsand the increase in the light availability due to changes in the opti-cal properties of the cells. For instance, at the maximum incident

Fig. 7. Relation between simulated and experimental values obtained for the O2

concentrations at pseudo-steady state for biomass of 0.3 (j), 0.5 (d) and 1.7 g L�1

( ).

110 J. Cabello et al. / Chemical Engineering Journal 252 (2014) 104–111

light intensity, the PPFR values increased up to 3-fold in the centerof the reactor at day 18 of N-starvation in comparison to the day 3of N-starvation. Under these conditions, the light penetration wasbetter and the cells were exposed to a larger quantity of lightenergy, resulting in a higher metabolic flux generated from photo-synthesis to be channeled to lipid accumulation from a content of19% at day 3 to 42% at day 18.

Fig. 6a shows the O2 production rates for the incremental lightstep-changes experiments that were determined by Eq. (9) for eachshort-term photosynthetic photo-acclimation state (Fig. 4b) underN-replete conditions. As can be seen, for biomass contents of0.13–1.9 g L�1 the photosynthetic activity increased linearly as theincident light intensity increased from 141 to 505 lmol m�2 s�1,indicating the absence of light saturation at these relatively lowlight intensities. For the reactor used in this study, a biomass con-tent of 1.9 g L�1 produces an 87% reduction in O2 specific produc-tion rates due to the light attenuation. Fig. 6b shows the overallrates of carbon dioxide consumption determined by Eq. (10), thevalues increased with respect to the light intensity and diminishedas biomass content increased. Fig. 1SI in the supplementary infor-mation relates CO2 consumption and O2 production predicting anendogenous respiration rate of 27.7 mg CO2 gb

�1 h�1.The light response curves (Fig. 6a and b) show that the overall

photosynthetic process is governed by light availability which inturn defines the microalgal performance. The response to the lightdepends strongly on the strain and the internal phenomena takingplace within photobioreactor. As far as we know, no analysis of thistype of photosynthesis response curves by changes in the lightintensity for Scenedesmus has been published yet. The behaviorof the light response curves can be compared qualitatively to thoseobtained by Mazzuca et al. [29] and Rebolloso et al. [18] for a con-tinuous pilot-scale tubular photobioreactor operated under cyclicvariation of solar radiation.

Fig. 8. Model simulations of the effect of the temperature and light intensity on thepredicted O2 concentration in the liquid phase.

3.2. Model validation

The mathematical model was validated by comparing experi-mental data (the increments of light step-changes in Fig. 4b) andthe predicted O2 concentration. The parameters used in the modelsimulation are listed in Table 1. The values of the parameters areconsistent with those reported in the work by Fernández et al.[9] and a recent report by Béchet et al. [11]. Fig. 7 shows a goodagreement (±5%) between experimental and predicted data andtherefore the model can be considered an adequate approximationto describe the pseudo-steady state of the O2 concentration for bio-mass contents up to 1.7 g L�1.

Table 1Parameters used in the model.

Parameters Value Units

Daz 0.027 m2 s�1

DCO2 1.9 � 10�5 m2 s�1

DO2 2.7 � 10�5 m2 s�1

Ea 16.1 kcal mol�1

Ed 30 kcal mol�1

hg 0.02 m3 m�3

Ka 0.096 m2 gb�1

Kd 0.005 h�1

KI 4970 lmol m�2 s�1

KLaO2 12.3 h�1

KLaCO2 10.3 h�1

Ks 75.7 lmol m�2 s�1

k0 8.60 � 1013 gO2 Kgb�1 h�1

k1 3.63 � 1023 gO2 Kgb�1 h�1

uGe 0.74 m s�1

uLe 0.07 m s�1

Yb/O2 0.65 gb gO2�1

The simulations obtained through of the mathematical modelare shown in Fig. 8, under N-replete condition and for a biomassof 0.5 g L�1. The effect of the incident light and the temperatureon the O2 production was considered to obtain the best operationconditions that could be used for the growth of the S. obtusiusculusin the air-lift photobioreactor. The predicted O2 production wasnormalized to better observe the influence of the variables. Themodel allowed describing the response curves of the irradianceeffect on photosynthesis, predicting between 72% and 85% of thehighest O2 concentration for light intensities between 600 and980 lmol m�2 s�1. The effect of temperature on photosynthesisestimated the maximum O2 concentration at 35 �C and decreasesat temperatures between 38 and 45 �C due to greater sensibilityof Ed in Eq. (5). Ed represents the enzymatic deactivation energyof the photosynthesis apparatus of S. obtusiusculus. Validation ofthe model with Yb/O2 and Kd values, (Eq. (8)), at 35 �C with theexperimental data for biomass production at 117 lmol�1 s�1 isshown in Fig. 2SI. The results do not show an influence of thedynamic experiments on the overall response of the microalga, thismay be due on one hand to the fact that the duration of the testswas small, less that 10%, as compared to the experiment duration(16 days) and on the other hand to the slow response of the

J. Cabello et al. / Chemical Engineering Journal 252 (2014) 104–111 111

biomass growth as compared to O2 or CO2. The model is furtherused to estimate concentration (Fig. 3SI) and productivity(Fig. 4SI) at different light intensities obtaining values up to0.78 gb L�1 d�1 at 610 lmol m�2 s�1.

4. Conclusions

The results showed that short unsteady state experiments onmicroalgal cultivation allow gathering solid information that canbe used for a rapid analysis of the short-term oxygen response ofphotosynthetic cells to changes in light fluctuation avoiding longexperiments. A key finding in this study is that the dynamicresponse indicated that the adaptation of the photosynthetic appa-ratus to light fluctuations in N-starved cells is very slow for direct-ing metabolic fluxes to lipid accumulation and could represent thecurrent bottleneck for the production of microalgal oil.

The proposed model seems an efficient tool to predict the effectof temperature and light on the dynamic O2 concentration andconsequently CO2 uptake and biomass productivity and could beused in real-time control of photobioreactors and to select the bestoperating conditions and optimize growth and productivity in mic-roalgal production process.

Finally, dynamic changes in O2 production and CO2 uptake ratescould also be used to evaluate other critical operational variablessuch as CO2 concentration in the gas phase or the effect of superfi-cial gas velocity, which modifies both the frequency of cell expo-sure to light–dark cycles, especially in air-lift reactors, and thenutrient and gaseous transfer rates between the growth mediumand the microalga.

Acknowledgements

The authors thank to Alma Toledo, Teresa Lopez for their tech-nical support and the scholarship provided by the National Councilof Science and Technology (CONACYT).

Appendix A. Supplementary material

Supplementary data associated with this article can be found, inthe online version, at http://dx.doi.org/10.1016/j.cej.2014.04.073.

References

[1] Y. Chisti, Biodiesel from microalgae, Biotechnol. Adv. 25 (2007) 294–306.[2] Y.S. Yun, J.M. Park, Attenuation of monochromatic and polychromatic lights in

Chlorella vulgaris suspensions, Appl. Microbiol. Biotechnol. 55 (2001) 765–770.[3] C. Brindley, F.G. Acién, J.M. Fernández, The oxygen evolution methodology

affects photosynthetic rate measurements of microalgae in well-defined lightregimes, Biotechnol. Bioeng. 106 (2010) 228–237.

[4] E. Molina, F. García, J.A. Sánchez, J.M. Fernández, F.G. Acién, A. Contreras, Amathematical model of microalgal growth in light limited chemostat culture, J.Chem. Technol. Biotechnol. 61 (1994) 167–173.

[5] F.G. Acién, J.A. Sánchez, J.M. Fernández, F. García, E. Molina, Modeling ofeicosapentaenoic acid (EPA) production from Phaeodactylum tricornutumcultures in tubular photobioreactors. Effects of dilution rate, tube diameter,and solar irradiance, Biotechnol. Bioeng. 68 (2000) 173–183.

[6] M.J. Barbosa, M. Janssen, N. Ham, J. Tramper, Microalgae cultivation in air-liftreactors: modeling biomass yield and growth rate as a function of mixingfrequency, Biotechnol. Bioeng. 82 (2003) 170–179.

[7] F. Camacho, F. García, J.M. Fernández, Y. Chisti, E. Molina, A mechanistic modelof photosynthesis in microalgae, Biotechnol. Bioeng. 81 (2003) 459–473.

[8] A. Concas, M. Pisu, Novel simulation model of the solar collector of Biocoilphotobioreactors for CO2 sequestration with microalgae, Chem. Eng. J. 157(2010) 297–303.

[9] I. Fernández, F.G. Acién, J.M. Fernández, J.L. Guzmán, J.J. Magán, M. Berenguel,Dynamic model of microalgal production in tubular photobioreactors,Bioresour. Technol. 126 (2012) 172–181.

[10] A. Hekmat, A.E. Amooghin, M.K. Moraveji, CFD simulation of gas-liquidbehavior in an air-lift reactor: determination of the optimum distance of thedraft tube, Simul. Model. Pract. Theory 18 (2010) 927–945.

[11] Q. Béchet, A. Shilton, B. Guieysse, Modeling the effects of light and temperatureon algae growth: State of the art and critical assessment for productivityprediction during outdoor cultivation, Biotechnol. Adv. 31 (2013) 1648–1663.

[12] H.P. Luo, M.H. Al-Dahhan, Airlift column photobioreactors for Porphyridium sp.culturing: Part I. Effect of hydrodynamics and reactor geometry, Biotechnol.Bioeng. 109 (2012) 932–941.

[13] H.P. Luo, M.H. Al-Dahhan, Analyzing and modeling of photobioreactors bycombining first principles of physiology and hydrodynamics, Biotechnol.Bioeng. 85 (2004) 382–393.

[14] D. Avendaño, H. Shubert, Oxygen evolution and respiration of thecyanobacterium Synechocystis sp., Physiol. Plant. 125 (2005) 381–391.

[15] A. Satoh, N. Kurano, H. Senger, M. Shigetoh, Regulation of energy balance inresponse to changes in CO2 concentrations and light intensities during growthin extremely-high-CO2-tolerant green microalgae, Plant Cell Physiol. 43 (2002)440–451.

[16] F. Camacho, F.G. Acién, J.A. Sánchez, F. García, E. Molina, Prediction of dissolvedoxygen and carbon dioxide concentration profiles in tubular photobioreactorsfor microalgal cultures, Biotechnol. Bioeng. 62 (1999) 71–86.

[17] D. Hu, M. Li, R. Zhou, Y. Sun, Design and optimization of photo bioreactor for O2

regulation and control by system dynamics and computer simulation,Bioresour. Technol. 104 (2012) 608–615.

[18] M.M. Rebolloso, J.L. García, J.M. Fernández, F.G. Acién, J.A. Sánchez, E. Molina,Outdoor continuous culture of Porphyridium cruentum in a tubularphotobioreactor: quantitative analysis of the daily cyclic variation of cultureparameters, J. Biotechnol. 70 (1999) 271–288.

[19] J.A. Berges, D.O. Charlebois, D.C. Mauzerall, P.G. Falkowski, Differential effectsof nitrogen limitation on photosynthetic efficiency of photosystems I and II inmicroalgae, Plant Physiol. 110 (1996) 689–696.

[20] F.G. Acién, J.M. Fernández, E. Molina, Photobioreactors for the production ofmicroalgae, Rev. Environ. Sci. Biotechnol. 12 (2013) 131–151.

[21] T.A. Costache, F.G. Acién, M.M. Morales, J.M. Fernández, I. Stamatin, E. Molina,Comprehensive model of microalgae photosynthesis rate as function of cultureconditions in photobioreactors, Appl. Microbiol. Biotechnol. 97 (2013) 7627–7637.

[22] A. Toledo, M. Morales, E. Novelo, S. Revah, Carbon dioxide fixation and lipidstorage by Scenedesmus obtusiusculus, Bioresour. Technol. 130 (2013) 652–658.

[23] A.K. Pegallapati, N. Nirmalakhandan, Modeling algal growth in bubble columnsunder sparging with CO2-enriched air, Bioresour. Technol. 124 (2012) 137–145.

[24] O. Bernard, Hurdles and challenges for modeling and control of microalgae forCO2 mitigation and biofuel production, J. Process Control 21 (2011) 1378–1389.

[25] J.V. Moroney, A. Somanchi, How do algae concentrate CO2 to increase theefficiency of photosynthetic carbon fixation, Plant Physiol. 119 (1999) 9–16.

[26] O. Levy, Z. Dubinsky, K. Shneider, Diurnal hysteresis in coral photosynthesis,Mar. Ecol. Prog. Ser. 268 (2004) 105–117.

[27] V. Bonardi, P. Pesaresi, T. Becker, E. Schleiff, R. Wagner, T. Pfannschmidt, P.Jahns, D. Leister, Photosystem II core phosphorylation and photosyntheticacclimation require two different protein kinases, Nature 437 (2005) 1179–1182.

[28] M.N. Merzlyak, O.B. Chivkunova, O.A. Gorelova, I.V. Reshetnikova, A.E.Solovchenko, I. Khozin, Z. Cohen, Effect of nitrogen starvation on opticalproperties, pigments, and arachidonic acid content of the unicellular greenalga Parietochloris incise (Trebouxiophyceae, Chlorophyta), J. Phycol. 43 (2007)833–843.

[29] T. Mazzuca, F. García, F. Camacho, F.G. Acién, E. Molina, Carbon dioxide uptakeefficiency by outdoor microalgal cultures in tubular airlift photobioreactors,Biotechnol. Bioeng. 67 (1999) 465–474.