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Comparison of different photobioreactor configurations and empirical computational fluid dynamics simulation for fucoxanthin production
Algal Research 37 (2019) 195–204
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Algal Research journal homepage: www.elsevier.com/locate/algal
Comparison of different photobioreactor configurations and empirical computational fluid dynamics simulation for fucoxanthin production Bahar Aslanbay Gulera, Irem Denizb, Zeliha Demirela, Suphi S. Oncela, Esra Imamoglua, a b
T
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Department of Bioengineering, Faculty of Engineering, University of Ege, Bornova, Izmir, Turkey Department of Bioengineering, Celal Bayar University, Muradiye, Manisa, Turkey
A R T I C LE I N FO
A B S T R A C T
Keywords: Fucoxanthin Phaeodactylum tricornutum Photobioreactor Computational fluid dynamics Simulation
Microalgae production in culture systems has been a topic of intense study for a long time. Optimization of cultivation conditions and design parameters of photobioreactors are essential for the development of economically and technically feasible algae technologies. The present study aimed to evaluate the effect of different photobioreactor (PBR) configurations on biomass and fucoxanthin production from Phaeodactylum tricornutum and to examine culture conditions by using Computational Fluid Dynamics (CFD) simulation for the photobioreactor having the maximum yield. The cells were first cultivated in three different PBRs (flat plate, airlift and stirred tank) and the maximum cell concentration of 5.94 ± 0.12 × 107 cells/ml was obtained in flat plate PBR. Also, highest fucoxanthin amount was found in the same PBR with the value of 2.43 ± 0.23 mg g−1. Flat plate PBR was simulated using CFD and the obtained results were used to evaluate mixing efficiency, flow dynamics and velocity fields. The extent of mixing was found sufficient to achieve homogenous culture medium and mean turbulent kinetic energy field suggested a homogeneous dissipation, also higher intensities of turbulence were observed around the nozzles and at the liquid-gas interphase. However, dead zones and vortex formations were observed in a small proportion of PBR. For further researches, assembling mixers or baffles into the PBR may be a feasible and effective method to improve the mixing efficiency and to prevent hydrodynamic problems. It was shown that the result of cultivation experiment had good agreement with that of CFD prediction.
1. Introduction Marine organisms are currently considered as an important potential source of bioactive compounds and among them Phaeodactylum tricornutum is one of the most studied. It is a brown diatom that contains high amount of polyunsaturated fatty acids and carotenoids, especially fucoxanthin [1]. Fucoxanthin is a well-known xanthopyll which has attracted much interest in the field of food, cosmetic, aquaculture and medical science owing to its broad spectrum of biological activities [2]. Currently, fucoxanthin is available in the market for dietary supplements as a substance supporting weight loss with varying purity and quality. Most of its extractions are conducted with macroalgae such as Laminaria japonica, Eisenia bicyclis and Undaria pinnatifida which have fucoxanthin content of 0.1–1 mg g−1. These macroalgal species are produced in coastal waters, open ponds or open-sea culture systems and they are harvested periodically for commercial fucoxanthin extraction. On the other hand, no studies have been reported on the commercial production of fucoxanthin derived from microalgae. Based on the literature, microalgae have several fold higher fucoxanthin than in
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macroalgae [3,4]. Hence P. tricornutum was investigated as a potential fucoxanthin source in the present study. Generally, microalgae cultivation process is carried out in closed photobioreactors (PBRs) for carotenoid production and different types of PBRs can be used as flat plate, tubular (vertical and horizontal), stirred tank, algal bio-film and their modified configurations. Regarding commercial production, previous studies have mainly focused on the following types: flat panel, vertical tubular and stirred tank PBRs. Flat plate PBRs have noticeable advantages for mass cultivation of microalgae because they have high surface area to volume ratio, have low oxygen accumulation, are easy to clean, and have flexible structure. However, there are also some limitations of these systems such as hydrodynamic stress which is generated by aeration, biofouling near the internal surface and scale up problems [5,6]. Alternatively, tubular PBRs are commonly preferred which can be divided into bubble column and airlift based on the mode of liquid flow. Airlift PBRs are effective systems due to high rate of mass transfer, efficiently mixing with low shear rate, low energy consumption, and maximum benefit from light with continuous mixing. The major drawback of using these systems is
Corresponding author. E-mail address: [email protected] (E. Imamoglu).
https://doi.org/10.1016/j.algal.2018.11.019 Received 18 May 2018; Received in revised form 26 November 2018; Accepted 27 November 2018 2211-9264/ © 2018 Elsevier B.V. All rights reserved.
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sterilization was applied by using 1.5% (v/v) hypochlorite for this reactors. Finally, for the stirred-tank PBR productions, P. tricornutum cultivation was carried out in 2 L (Sartorius Biostat® A-plus, Germany) stirred tank bioreactor. It was equipped with 6-blade Rushton turbine impellers and the probes of pH and DO and the baffle insert consisted of a holder with four vertical baffles. The pH was maintained at 7.0 by the automatic addition of 1 N HCl for PBRs. All PBRs have the working volume of 1.6 L and they were operated at constant temperature value of 18 ± 2 °C. Illumination was provided continuously by fluorescent daylight lamp (Philips LTD90 18 W) along the PBRs from one side and light intensity was measured by a quantum meter (Lambda L1-185) on the surface of them. Both the constant light energy per unit volume and the constant volumetric power input were applied for the evaluation of different PBRs under the same operational conditions. The energy of light per unit volume considering the illuminated surface of the PBRs was calculated based on the energy of a photon (1 μE = 0.2176 J) [14]. The light intensities were calculated as 30, 55, 50 μE·m−2·s−1 which corresponded to the constant light energy of 0.315 kJ m−3 s−1 for AL, FP and ST PBRs, respectively. The fluid was mixed by sparging with air through spargers in AL and FP PBRs while ST PBR involved both aeration and mechanical agitation with the use of impellers for efficient mixing. The aeration rates and agitation value were calculated based on the constant volumetric power input (P/V) as 1.85 L min−1, 5.3 L min−1 and 1 L min−1 with the mixing rate of 170 rpm which corresponded to the constant P/V value of 93.38 Wm−3 for AL, FP and ST PBRs, respectively. Operational conditions of PBRs are presented in Table 1.
difficulty of scale up process that limits the use of this photobioreactor in commercial applications [5,7]. As mentioned above, stirred tanks are another type of PBR where agitation is provided mechanically with the use of impellers. Mixing efficiency is significantly higher than other PBRs so these systems have the optimal heat and mass transfer. On the other hand, mechanical agitation leads to high shear stress on microalgae cells which is a common mechanism of cell damage and they are expensive to operate and maintain due to heat generating by agitation [8,9]. Microalgae cultivation in a PBR is a complex system and should be examined before the use of this technology at industrial scale. To better understand the rheology and hydrodynamic parameters of production in PBRs, different simulation and modeling process can be applied. Computational Fluid Dynamics (CFD) technique is a powerful tool to simulate hydrodynamics, fluid flows induced by mixing, heat and mass transfer within PBR by numerically solving Navier-Stokes equations [10,11]. Generally, CFD expresses the solution of fundamental transport equations in a three-dimensional system. The application of CFD for modeling of PBR design has primarily focused on optimal mixing in two phased systems, gas–liquid mass transfer, flow regime, dissociation of O2/CO2 in the liquid phase [12]. Fucoxanthin is considered as a trend carotenoid due to the expectation of increase in its market share between the years 2020–2024 and has high potential usage in food and feed, agriculture, cosmetic, pharmaceutical, medical and aquaculture areas. In this context, increasing the production efficiency of high value added product with low cost and developing a protocol for reliable and sustainable microalgal cultivation should be investigated. There is a need for novel, economic, environment friendly, safe, fast and low energy consumption production techniques. Therefore, two main objectives of the present study were: (i) to evaluate the difference between three photobioreactors; flat plate, airlift and stirred tank photobioreactors according to fucoxanthin yield from P. tricornutum, (ii) to examine culture conditions by using CFD simulation for the photobioreactor which had maximum yield.
2.3. CFD methodology Numerical Computational Fluid Dynamics (CFD) simulations were carried out to study the flow dynamics in the most efficient PBR which was flat plate PBR found in this study. The dimension details of flat plate photobioreactor are shown in Table 2. 3-dimensional geometry of the PBR was created in the Design Modeler of ANSYS Fluent 17.1, and it was imported to Fluent platform for meshed structure (Fig. 2). Different mesh densities were tested until the mesh independency test criterion was provided. A refined mesh with approximately 5.3 ∗ 106 elements and 2.9 ∗ 106 node points was generated. These results show that the mesh with elements 5.3 ∗ 106 was satisfactory for the current simulation. The simulation runs were performed using the ANSYS CFX-17.1 CFD software. Specifically, the air-culture medium interactions were considered as multiphase problems, where air momentum was transferred to water, and turbulence was also involved. Two-phase simulations were carried out by Eulerian-Eulerian multiphase model in which medium was considered as a continuous phase and air as a discrete particle phase which is assumed to consist of spherical bubbles of the same size with a mean diameter of 3 mm, all under the reference pressure of 1 atm. A SST turbulence k-Ω model was selected to provide predicted turbulence solutions. The flow phenomenon is governed by the following equations. Continuity equation;
2. Material and methods 2.1. Microalgal species and inoculum preparation Phaeodactylum tricornutum EGE MACC-70 was obtained from the Culture Collection of Microalgae at the University of Ege, Izmir, Turkey. Stock culture was cultivated in F/2 [13] medium at 22 ± 2 °C under continuous illumination (65 μE m−2 s−1) in a 2 L sterile bottle for 15 days. For the preparation of the inoculum, the cells from the stock culture were collected and concentrated by centrifugation (1160 ×g, 2 min) and the supernatant was removed. The collected cells were transferred, incubated aseptically in 250 mL flasks containing 100 mL of F/2 medium under the light intensity of 65 μE·m−2·s−1 with the agitation rate of 120 rpm at 22 ± 2 °C for five days. Five-day-old culture of cells was used as inoculum at 10% volume for all experiments. 2.2. Photobioreactors (PBRs) The microalgal strain P. tricornutum was cultivated in three different 2 L PBRs as airlift (AL), flat plate (FP) and stirred tank (ST). Schematic diagrams of used 2 L PBRs are shown in Fig. 1. A plexiglass internal loop airlift PBR was equipped with an online controller (Biosis, Pikolab, Turkey), consisting of a combined temperature-dissolved oxygen probe and pH probe. The riser was sparged with air through a ring sparger (2.4 cm in diameter) located at its base. The sparger had 5 nozzles, 0.4 cm in diameter. The vertical flat plate PBR which was made of plexiglas (0.5 cm wall thickness) was equipped with an on-line controller (Sartorious Biostat A, Germany) consisting of temperature, dissolved oxygen and pH probe. The gas spargers were placed to the bottom of the PBR so as to provide homogenous culture medium. The sparger included 24 nozzles with the diameter of 0.3 cm. Chemical
∂ (ρα rα ) ∂t
+ ∇∙ (ρα Uα rα ) = 0
(1)
where t stands for time, ρα, Uα, rα are the density, velocity and volume fraction of α phase (α = medium, gas), respectively. Momentum equation;
∂ (ρ Uα rα ) + ∇∙ (rα (ρα Uα Uα )) = −rα ∇Pα + rα ρα g ∂t α + ∇∙ (rα μα, eff (∇Uα + (Uα )T )) + Mα
(2)
where g represents the acceleration of gravity, μα,eff represents the 196
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Fig. 1. Schematic diagram of photobioreactors used; a) airlift, b) flat plate, c) stirred tank.
In these equations, k represents the turbulence kinetic energy which is the mean kinetic energy per unit mass associated with eddies in flow, w represents specific rate of dissipation that is the rate at which turbulence kinetic energy is converted into thermal internal energy per unit volume and time. Gk is the generation of turbulence kinetic energy due to mean velocity gradients, Gω is the generation of ω, Γk and Γω are the effective diffusivity of k and ω, respectively. Yk and Yω represent the dissipation of k and ω due to turbulence, Sk and Sω are user-defined source terms. The whole fluid domain was assumed to be under isothermal condition due to the constant temperature in the photobioreactor. Thus, the heat exchange was not considered. The outlet was set with a degassing boundary, which meant that only the gas in the dispersed phase could escape from the surface freely but the continuous phase could not penetrate the top surface. The walls of the PBR were set to no-slip boundary condition with water. The cultivation medium was modeled based on the physical properties with the density of 1004.88 kg m−3 and the dynamic viscosity of 0.006 kg m−1 s−1 at 20 °C under the atmospheric pressure. A time step of 0.005 s was considered for all simulations and each simulation run was completed up to 2 s. Computations were performed until they converged at a residual of 10−4 and the volume averaged gas holdup within the PBRs reached the constant.
Table 1 Operational conditions for photobioreactors. Photobioreactor types
Temperature (°C) Light energy (kJ m−3 s−1) Light intensity (μE·m−2 s−1) Volumetric power input (Wm−3) Aeration rate (Lmin−1) Stirrer rate (rpm)
Airlift PBR
Flat plate PBR
Stirred tank PBR
18 0.315 30 93.38 1.85 –
18 0.315 55 93.38 5.3 –
18 0.315 50 93.38 1 170
Table 2 Dimensions of flat plate photobioreactor. Dimensions
Value
VL (L) Hp (cm) Lp (cm) wp (cm) Hs (cm) Ls (cm) Number of nozzles at air sparger Diameter of nozzles at air sparger HL (cm)
1.6 25 26 3.7 22.7 21 24 0.3 20.5
2.4. Experimental analysis VL, working volume, Hp, height of plate; Lp, width of plate; wp, thickness of plate; Hs, height of air sparger; Ls, length of air sparger, HL, height of liquid.
Samples were taken at indicated times, and the following growth parameters were measured immediately; the cell concentration was determined by counting samples in a Neubauer hemocytometer. The cellular turbidity (optical density) was measured at 600 nm in UV/VIS spectrophotometer (GE Healthcare Ultrospec 1100 pro, UK). Dry weight was determined by filtering a 5 mL culture sample through preweighed GF/C filter (Whatman, UK) and drying the cell mass at 60 °C for overnight. For the chlorophyll-a measurement, cells were harvested at 6000 rpm for 5 min. Chlorophyll in the cells was extracted with 4:1 (v/ v) dimethylsulfoxide (DMSO): water and the amount of chlorophyll-a was determined spectrophotometrically by measuring the light absorption at wavelength of 665 nm. The chlorophyll content was
effective viscosity of α phase, Mα represents the interphase momentum transfer coefficient and P represents the pressure. Turbulent kinetic energy equation and the specific dissipation rate equation;
∂ ∂ ∂ ⎛ ∂k ⎞ (ρk ) + (ρkui ) = ⎜Γk ⎟ + Gk − Yk + Sk ∂t ∂x i ∂x j ⎝ ∂x j ⎠
(3)
∂ ∂ ∂ ⎛ ∂w ⎞ (ρω) + (ρωui ) = ⎜Γw ⎟ + Gw − Yw + Sk ∂t ∂x i ∂x j ⎝ ∂x j ⎠
(4) 197
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Fig. 2. Configuration of flat plate PBR in ANSYS a. Geometry of photobioreactor with components, b. Meshed structure.
injection volume was 20.0 μL, and detection was made by diode array detector with quantitation at the wavelength of maximum absorption for each analyte in order. On the other hand, the chromotogram was obtained at 450 nm for fucoxanthin. For the flow of mobile phase, a gradient system was developed due to its resolving power and improved sensitivity. The mobile phase consisted of a gradient of methanol (A), methyltert-butyl ether (B) and water (C) [16]. Considering the cell death was negligible, specific growth rate (μ) was calculated for the exponential phase of growth (Eq. (6)) as following;
calculated using the following Eq. (5):
Chlorophyll − a (g L−1) =
A665 72.8
(5)
where A665 corresponds to the absorbance of extracted supernatant at 665 nm wavelength with 1 cm pathway cuvette [15]. Fucoxanthin was extracted by a simple ultrasound-assisted extraction method using ultrasonic bath. Then, the solvents were removed with the use of rotary evaporator. Samples collected from the photobioreactor were centrifuged at 6000 rpm for 10 min via centrifuge. The supernatant was removed and CaCO3 was added to each cell pellet. Then, fucoxanthin was extracted with 10.0 mL of THF/DCM (1:1) containing 0.010% (w/v) pyrogallol. The mixture was placed in the ultrasonic bath for 15.0 min. After the ultrasonic extraction, the solution was centrifuged at 6000 rpm for 10 min, and the supernatant was collected. The residue was repeatedly extracted with 10.0 mL extraction solvent until it was colorless. The supernatants were combined and evaporated by the rotary evaporator at 40.0 °C under vacuum [16]. HPLC-DAD system was used for the determination of carotenoids. The C18 column (YMC) temperature was set at 25.0 °C. The separation was achieved by gradient elution at a flow rate of 1.0 mL/min. The
μ=
ln X2 − ln X1 ∆t
(6)
where X2 is the final cell concentration (cells ml−1), X1 is the initial cell concentration (cells ml−1) and Δt is the time required for the increase in concentration from X1 to X2 (day) [17]. Culture medium viscosity was measured twice at the beginning and at the end of the cultivation period by a rotational viscometer (Brookfield model DV-E, USA) with LV type spring torque using LV3 (63) spindle. All the experimental analysis were done in duplicates and presented 198
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Fig. 3. Cell growth profile, fucoxanthin and chlorophyll-a concentrations of P. tricornutum cells, a) cell concentration, b) turbidity, c) fucoxanthin, d) chlorophyll-a; ( ) Flat plate PBR, ( ) Airlift PBR, ( ) Stirred tank PBR. Data shown as mean ± SD (n = 2).
in figures and tables with the average values. The experimental data were analyzed using a one-way analysis of variance (ANOVA). A probability value of p ≪ 0.05 was considered to denote a statistically significant difference.
lag phase was observed during the cultivation in which maximum cell number of 1.74 ± 0.02 × 107 cells ml−1 was obtained at the 7th day. Moreover, the specific growth rate and dry weight concentration of microalgae were found to be lower in AL PBR than the other cultivations (Table 3). For the cultivation conducted in ST PBR, the maximum cell number of 3.42 ± 0.04 × 107 cells ml−1 was achieved where the cells entered stationary phase at the 5th day of cultivation. It's important to note that the main limitation of the use of ST PBRs are shear stress due to the mechanical agitation where microorganisms, bioflocs and other suspended solids are susceptible to damage. Also, low surface area to volume ratio, which in turn decreases the light harvesting efficiency is another disadvantage of these systems [9]. Therefore, the growth rate of cells might be limited in comparison with the aerated cultivation systems. As reported by Sobzcuk et al. [18], increasing the rate of mechanical agitation in stirred tanks led to rise of biomass concentration until an upper limit on agitation speed was reached and this limit depended on the microalgal species. Further increase in agitation speed could be detrimental to the algal cells. FP PBRs are one of the most preferred closed cultivation systems because of the large illumination surface area, ease of sterilization and low shear stress formation [19]. In this study, P. tricornutum cultivation resulted in the highest biomass yield in terms of cell number and dry weight (Fig. 3a and Table 3). In a similar study, cultivation of diatom Entomonies sp. was performed in mechanically stirred tank and flatpanel photobioreactors and the maximum cell number density was determined in FP PBR which was about 73% higher than the result from the stirred tank photobioreactor [20]. Considering the cell movement in PBR, a nonuniform distribution was observed behind the sparger pipe. In this area, the cell density was lower than the other parts of PBR because of the stable flow pattern of fluid and insufficient aeration. This might be an effect of the aeration rate and the locations of nozzles. Cultivation in AL PBR had the lowest cell growth and this growth profile might be an effect of low liquid velocity or improper configuration in terms of the column length which led to uneven densities of
3. Results and discussion 3.1. Photobioreactor cultivations 3.1.1. Cell growth characteristics P. tricornutum cells were grown for 7 days in three different PBRs in batch operations and Fig. 3 demonstrates the microalgal growth performances in terms of cell number and microalgal turbidity. Biomass productivities were significantly different between the three cultivations. FP PBR presented the highest cell concentration of 5.94 ± 0.12 × 107 cells ml−1 which was 3.4 and 1.7-fold higher than obtained in airlift and stirred tank PBRs, respectively (Fig. 3a). Besides, growth parameters achieved in FP PBR also gave the highest values among three cultivations (Table 3). As shown in Fig. 3b, the cultivations had similar OD growth pattern with cell number where the highest cell turbidity of 1.249 ± 0.008 was obtained in FP PBR. In AL PBR, a long Table 3 Growth parameters for photobioreactor cultivations of P. tricornutum. Data shown as mean ± SD (n = 2).
−1
μ (d ) Doubling time (day) Dry weight (g L−1) Fucoxanthin yield (mg g−1 cell) Fucoxanthin accumulation rate (mg L−1 d−1)
Airlift PBR
Stirred tank PBR
Flat plate PBR
0.27 2.56 1.93 ± 0.09 1.4 ± 0.09
0.3 2.23 2.09 ± 0.19 0.82 ± 0.16
0.37 1.83 3.03 ± 0.3 2.42 ± 0.23
0.387 ± 0.12
0.245 ± 0.08
1.05 ± 0.23
199
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fluid flow. Variation on flow pattern cause heterogeneous nutrient dispersion and unsufficient light utilization of cells. These datas supported that P. tricornutum cells formed aggregates and collapsed at the bottom of AL PBR during cultivation. As a result, changing photobioreactor configuration was the main effect considering the mixing type, shear stress and light penetration for the cell growth and the product yield. It was recorded that the shear stress was 5.4 times lower in FP PBR, in comparison to the value of 1.82 Pa calculated in AL PBR. Therefore, FP PBR was found the most appropriate cultivation system due to the effective illumination and low shear stress. It's well-known that P. tricornutum cells have a low tolerance for the damaging forces like mechanical agitation, impeller blades, bubble break-ups [18]. In this study, aeration did not cause hydrodynamic stress on cells in FP PBR. Illumination is another critical parameter for microalgae cultivation and closed PBRs are performed under the artificial lights. Light intensity was calculated based on the same energy on a photon theory and FP PBR was illuminated with the highest intensity of 55 μE·m−2·s−1 than other PBRs because of its high illumination surface area. So, it was recorded that increasing light intensity led to increase of cell concentration until the light saturation point.
an important role in diffusion rate and air supply for microalgal cells [25]. In this simulation, air bubbles strongly concentrated in the area between the dissolved oxygen and pH probes. The gas volume fraction for the flow conditions was varied between 2% and 12.5% and the local gas volume fraction in the most parts of the reactor was 8% except at the maxima along the sparger nozzles (Fig. 4b). This result was in agreement with previous studies that reported the highest gas volume fraction was obtained in the air sparger and it decreased at the upper part of reactors [10,26]. However, it had the lowest value around the sparger and at the bottom of the PBR. It is also important to underline that the gas distribution was minimum behind the sparger elbow so it could affect the diffusion rate negatively in this area. This result was supported by the air velocity contour plot. When comparing air volume fraction and air velocity contours, a parallel behavior was evident as observed in Fig. 4c. Maximum velocity values were produced around the value of 1.0 m s−1 at the nozzles on sparger where air was fed into PBR. Moreover, it showed higher values around probes as well as gas volume fraction. It can be explained that bubbles hit the probes and broke up into small bubbles so they moved up faster. Another high velocity zone was air-medium interface where air bubbles broke up and they moved forward to outlet quickly. Considering the whole PBR tank, the average air velocity was found as 0.42 m s−1. When air vectors were added to the velocity contours, it was shown that strong local circulations formed in some points demonstrated by red circle in Fig. 4c. It effected diffusion rate and mixing efficiency negatively, and some development studies can be applied for the further researches such as adding mixer or baffles to the system. Huang et al. [27] reported that developing a novel mixer in FP PBRs could significantly increase the fluid velocity along the light attenuation and light/dark cycles, thus further increased the maximum biomass concentration. Thus, the PBRs with novel mixers are greatly applicable for high-efficiency cultivation of microalgae. Another research reported that a flat plate PBR with optimized horizontal baffles improved the algal productivity effectively and economically, and also uniform the growth conditions of algal cells at different locations inside the PBR [28]. Culture medium velocity profile of cross-sections along the y-direction are presented in Fig. 5. The maximum liquid velocity of 0.32 m s−1 was produced under the air sparger while it gradually decreased toward to upper part of the PBR. It is important to note here that placement of sparger nozzles is a critical issue to provide the homogenous air and liquid dispersion. In order to produce more uniform culture medium, their layout might be rearranged. Yang et al. [29] studied the characteristics of the turbulent mixing of multiphase flows in a flat-panel PBR with the different nozzle configurations. Six different cases were tested with the corresponding airflow rate and aeration configurations. After CFD simulation, it was found that the number and the placement of nozzles changed the mean velocity fluid between the range of 0.038–0.106 m s−1. Thus, it is possible to make more efficient cultivation systems with small changes on nozzle configuration. In the present study, medium velocity contours showed similar pattern to that of air phase in some points where the probes were located. In these areas medium velocity was relatively higher than observed in most of the PBR. Another significant result was formation of the dead zones that are defined as the proportion of the reactor volume where the fluid velocity was lower than a limited value. This fluid velocity varies in literature from 0.001 to 0.5 m s−1 [30] and it was determined as 0.02 m s−1 for this study. Dead zones were observed in the upper side of PBR, especially in the top left corner. This may be explained by the movement of air bubbles. The bubbles moved in the upward direction without breaking up and more slowly. Therefore, the lowest medium velocity was observed in these area because of the drag force generated by the deceleration and backward gravity. A common problem of this zone is the cell sedimentation or suspension, therefore the mass transfer rate is reduced, which cause a decrease in the cell growth [31]. In contrast to the gas phase, culture medium velocity showed a higher value behind the air sparger. As shown in Fig. 5c the medium velocity
3.1.2. Fucoxanthin and chlorophyll-a production Fucoxanthin found as main carotenoid in P. tricornutum microalgae where it acts as a primary carotenoid with chlorophyll-a to harvest light and transfer energy [3]. A comparison of fucoxanthin production for cells grown under different cultivation systems is presented in Fig. 3c. Among three systems, FP PBR gave the most abundant fucoxanthin content with the value of 7.35 ± 0.23 mg L−1, followed by AL PBR with the fucoxanthin amount of 2.71 ± 0.12 mg L−1. Contrary to cell concentration, P. ticornutum cells accumulated the lowest fucoxanthin pigment during ST PBR cultivation. The fucoxanthin yield for all cultivations were 0.82 ± 0.16 mg g−1 in ST PBR, 1.4 ± 0.09 mg g−1 in AL PBR and 2.43 ± 0.23 mg g−1 in FP PBR. Maximum fucoxanthin concentration in FP PBR, was probably a result of the low light penetration due to increasing cell concentration and self-shading effect of cells in PBR. It was observed that decreasing the light penetration led to an increase in the fucoxanthin concentration. Such results are in agreement with the previous studies of Xia et al. [2] for O. aurita cultures, Benavides et al. [1] and Gao et al. [21] for P. tricornutum culture and Guo et al. [22] for C. cryptica. McClure et al. [23] reported that, such increment may be related with that fucoxanthin acts as a ‘light harvesting’ pigment and that the algae increases its concentration to compensate for a reduced light intensity. These results suggest that fucoxanthin production is closely related to the light intensity more than growth of microalgae. Chlorophyll-a content showed similar changes with the fucoxanthin concentration, as shown in Fig. 3d. It was an expected result because diatoms possess fucoxanthin chlorophyll a/c binding proteins (FCPs complex) which is responsible for light harvesting during photosynthesis. Most of the studies reported that chlorophyll and fucoxanthin concentration had parallel variations under different light intensities [24]. In this study, the maximum chlorophyll-a concentration of 0.37 ± 0.005 mg L−1 was found in FP PBR. In the other PBRs, its content was lower than obtained in FP PBR, as expected. 3.2. CFD simulation After the experimental analysis, the highest fucoxanthin yield was found in FP PBR under the constant operational conditions. The another aim of this study was to evaluate mixing characteristics, flow dynamics and shear stress for the photobioreactor having the maximum fucoxanthin yield. Thus, the simulation was performed for FP PBR with the chosen parameters. Fig. 4a and b show contour plots of the gas bubble distribution inside the PBR after 2 s of simulation. Gas volume fraction is a key factor in the process of interphase air mass transfer and it plays 200
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Fig. 4. Gas distribution contours, a. Air volume fraction, b. Gas holdup profile c. Air velocity.
in this area reached a value of 0.26 m s−1. This might be due to circulation of the fluid flow around the sparger and the effect of gravity that induced flow toward the bottom of PBR. Similar to the air velocity vectors, vortex formation was observed in the area that air bubbles presented circulation loop. Fluid velocity is a quantitative parameter to describe the mixing performance of the PBR and it can be used to determine turbulent mixing zones inside the PBR. It was defined as the fluid velocity (U) < 0.005 m s−1 as the very low-velocity zone, 0.05 ≤ U ≤ 0.1 m s−1 as the low-velocity zone, 0.1 ≤ U ≤ 0.2 m s−1 as the medium velocity zone, U > 0.2 m s−1 as the high-velocity zone. Generally, the PBR with a better mixing performance contains larger area percentage of the high-velocity zone [29,32]. Considering this point, Fig. 5a shows the velocity profile of PBR and it can be said that percentage of high velocity zone was high throughout the most parts of PBR. There was low-velocity zones where liquid made circulations, as expected. These results showed that efficient mixing was provided and so a much faster algae growth was achieved for flat plate PBR. The detailed fluid characteristic of PBR was presented in Fig. 6, including turbulent kinetic energy (TKE) and eddy viscosity. TKE represents the mean kinetic energy per unit mass associated with eddies in turbulent flow of each grid in the PBR. A higher TKE value means better fluid mixing, heat and mass transfer and improves the growth of
microalgae [27]. In this PBR, the high TKE region was mainly located at the aerated spargers and liquid-gas interface in top of PBR, which could be contributed the frequency of bubble burst in this area. Overall, the profile of TKE (Fig. 6a) showed similar pattern to that of medium velocity (Fig. 5a), however different TKE contours were observed in some domains such as bottom of the PBR and behind the air sparger. In these regions, turbulent energy behavior mostly had several characteristics with air velocity contours (Fig. 4c). This might be due to the phase interactions between the medium and the air could influence the turbulence kinetic energy as reported by Calvo et al. [10]. Also, eddy (or turbulent) viscosity, representing the extent of mixing and the strength of the turbulence in PBRs, plays a significant role in fluid flows. The plots showed varying magnitudes of eddy viscosity throughout the solution domain where it had greatest value at the top portions of the PBR, as shown in turbulence kinetic energy. In the near wall region, the value of turbulent viscosity was found almost zero so it can be noted that the fluid near the PBR walls did not present turbulence behavior (Fig. 6b). The above results showed that the flow and mixing performance was at desired level for the most parts of PBR. This finding was supported by the experimental investigations and velocity and turbulence kinetic energy profile from CFD simulation. However, homogeneity of 201
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Fig. 5. Velocity profile of culture medium a. Medium superficial velocity contours, b. Four section through the reactor column, c. Medium superficial velocity chart at four section.
simulation and the fluid velocity was enhanced from 5.8 × 10−5 m s−1 to 0.45 m s−1 with the appliance of paddlewheels. Also, the mixing time decreased by 31.3% and the mass transfer coefficient increased by 41.2%. In another study, the effect of flat and waved baffles on the mass transfer in flat plate PBR was investigated using CFD software and the waved baffles with low cross section area were found as effective to improve the mass transfer [34]. Su et al. [35] conducted a study to achieve better mixing with low fluid velocity, especially in the vertical direction in a flat plate PBR. With this aim, they designed one flat plate structure in which the destabilizing bar was built in and flow field was simulated using CFD software FLUENT. Simulated results showed that
the culture medium was not provided throughout the PBR because of the different variables such as nozzle diameter, configuration and placement, aeration rate and design parameters of the PBR. Therefore, some modifications should be applied to this system to enhance cultivation efficiency. Many studies can be found in the literature to design the novel flat plate PBRs and these improvements can be used for further researches with this PBR. One of these studies, Cheng et al. [33] proposed double paddlewheels to generate the cycle flow for increasing horizontal fluid velocity between dark and light zones in a flat plate photobioreactor and paddlewheels were positioned at 20 cm high and 60 cm high inside the bioreactor. Studies were conducted with CFD
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Fig. 6. Turbulence kinetic energy and eddy viscosity profile of culture medium: a. medium turbulence kinetic energy, b. medium eddy viscosity.
Research and have no conflict of interest.
this destabilizing bar can effectively intensify mixing, which is vital for the algal culturing. Better mixing conditions can be provided with the optimum bar size, flat plate depth and aeration rate [35]. These improvements could be applied to flat plate PBR used in the present study.
Funding information This work was supported by the Scientific and Technological Research Council of Turkey (TUBITAK), Grant number 115M014.
4. Conclusion
References
The comparison of cultivation systems for P. tricornutum for fucoxanthin production, including airlift, flat plate, and stirred tank PBR, suggested that flat plate PBR was superior with the fucoxanthin yield of 2.42 ± 0.23 mg g−1 cell at the temperature of 18 °C under the constant light energy of 0.315 kJ m−3 s−1 using the constant power input of 93.38 W m−3. It was found that the fucoxanthin yield was 3-fold higher in FP PBR than obtained in ST PBR. It is noteworthy to mention that PBR selection depends on the type of strains, type of product desired and operating conditions (efficiently mixing with low shear rate, low energy consumption, optimal heat and mass transfer). When considering the results of CFD simulation, better mixing was observed using the maximum air velocity of 1.0 m s−1 around the sparger nozzles and in the area between pH and dissolved oxygen probes in FP PBR. Also, more homogeneous TKE distribution between the range of 0.0010 and 0.0045 J kg−1 in the middle section of PBR suggested higher mixing efficiency. However, mixing was not provided uniformly throughout the PBR as indicated by varying magnitudes of TKE and eddy viscosity in the PBR domain. Therefore, some development studies could enhance the optimum design of flat plate PBRs.
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Acknowledgments This study was a part of Cost action ES1408 and the authors would like to thank the Scientific and Technological Research Council of Turkey (TUBITAK) with the project number of 115M014 for the financial support. Declaration of interest None. Statement of informed consent, human/animal rights No conflicts, informed consent, human or animal rights applicable. Declaration of authors agreement to authorship and submission All authors mutually agree for submitting this paper to Algal 203
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Comparison of different photobioreactor configurations and empirical computational fluid dynamics simulation for fucoxanthin production Bahar Aslanbay Gulera, Irem Denizb, Zeliha Demirela, Suphi S. Oncela, Esra Imamoglua, a b
T
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Department of Bioengineering, Faculty of Engineering, University of Ege, Bornova, Izmir, Turkey Department of Bioengineering, Celal Bayar University, Muradiye, Manisa, Turkey
A R T I C LE I N FO
A B S T R A C T
Keywords: Fucoxanthin Phaeodactylum tricornutum Photobioreactor Computational fluid dynamics Simulation
Microalgae production in culture systems has been a topic of intense study for a long time. Optimization of cultivation conditions and design parameters of photobioreactors are essential for the development of economically and technically feasible algae technologies. The present study aimed to evaluate the effect of different photobioreactor (PBR) configurations on biomass and fucoxanthin production from Phaeodactylum tricornutum and to examine culture conditions by using Computational Fluid Dynamics (CFD) simulation for the photobioreactor having the maximum yield. The cells were first cultivated in three different PBRs (flat plate, airlift and stirred tank) and the maximum cell concentration of 5.94 ± 0.12 × 107 cells/ml was obtained in flat plate PBR. Also, highest fucoxanthin amount was found in the same PBR with the value of 2.43 ± 0.23 mg g−1. Flat plate PBR was simulated using CFD and the obtained results were used to evaluate mixing efficiency, flow dynamics and velocity fields. The extent of mixing was found sufficient to achieve homogenous culture medium and mean turbulent kinetic energy field suggested a homogeneous dissipation, also higher intensities of turbulence were observed around the nozzles and at the liquid-gas interphase. However, dead zones and vortex formations were observed in a small proportion of PBR. For further researches, assembling mixers or baffles into the PBR may be a feasible and effective method to improve the mixing efficiency and to prevent hydrodynamic problems. It was shown that the result of cultivation experiment had good agreement with that of CFD prediction.
1. Introduction Marine organisms are currently considered as an important potential source of bioactive compounds and among them Phaeodactylum tricornutum is one of the most studied. It is a brown diatom that contains high amount of polyunsaturated fatty acids and carotenoids, especially fucoxanthin [1]. Fucoxanthin is a well-known xanthopyll which has attracted much interest in the field of food, cosmetic, aquaculture and medical science owing to its broad spectrum of biological activities [2]. Currently, fucoxanthin is available in the market for dietary supplements as a substance supporting weight loss with varying purity and quality. Most of its extractions are conducted with macroalgae such as Laminaria japonica, Eisenia bicyclis and Undaria pinnatifida which have fucoxanthin content of 0.1–1 mg g−1. These macroalgal species are produced in coastal waters, open ponds or open-sea culture systems and they are harvested periodically for commercial fucoxanthin extraction. On the other hand, no studies have been reported on the commercial production of fucoxanthin derived from microalgae. Based on the literature, microalgae have several fold higher fucoxanthin than in
⁎
macroalgae [3,4]. Hence P. tricornutum was investigated as a potential fucoxanthin source in the present study. Generally, microalgae cultivation process is carried out in closed photobioreactors (PBRs) for carotenoid production and different types of PBRs can be used as flat plate, tubular (vertical and horizontal), stirred tank, algal bio-film and their modified configurations. Regarding commercial production, previous studies have mainly focused on the following types: flat panel, vertical tubular and stirred tank PBRs. Flat plate PBRs have noticeable advantages for mass cultivation of microalgae because they have high surface area to volume ratio, have low oxygen accumulation, are easy to clean, and have flexible structure. However, there are also some limitations of these systems such as hydrodynamic stress which is generated by aeration, biofouling near the internal surface and scale up problems [5,6]. Alternatively, tubular PBRs are commonly preferred which can be divided into bubble column and airlift based on the mode of liquid flow. Airlift PBRs are effective systems due to high rate of mass transfer, efficiently mixing with low shear rate, low energy consumption, and maximum benefit from light with continuous mixing. The major drawback of using these systems is
Corresponding author. E-mail address: [email protected] (E. Imamoglu).
https://doi.org/10.1016/j.algal.2018.11.019 Received 18 May 2018; Received in revised form 26 November 2018; Accepted 27 November 2018 2211-9264/ © 2018 Elsevier B.V. All rights reserved.
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sterilization was applied by using 1.5% (v/v) hypochlorite for this reactors. Finally, for the stirred-tank PBR productions, P. tricornutum cultivation was carried out in 2 L (Sartorius Biostat® A-plus, Germany) stirred tank bioreactor. It was equipped with 6-blade Rushton turbine impellers and the probes of pH and DO and the baffle insert consisted of a holder with four vertical baffles. The pH was maintained at 7.0 by the automatic addition of 1 N HCl for PBRs. All PBRs have the working volume of 1.6 L and they were operated at constant temperature value of 18 ± 2 °C. Illumination was provided continuously by fluorescent daylight lamp (Philips LTD90 18 W) along the PBRs from one side and light intensity was measured by a quantum meter (Lambda L1-185) on the surface of them. Both the constant light energy per unit volume and the constant volumetric power input were applied for the evaluation of different PBRs under the same operational conditions. The energy of light per unit volume considering the illuminated surface of the PBRs was calculated based on the energy of a photon (1 μE = 0.2176 J) [14]. The light intensities were calculated as 30, 55, 50 μE·m−2·s−1 which corresponded to the constant light energy of 0.315 kJ m−3 s−1 for AL, FP and ST PBRs, respectively. The fluid was mixed by sparging with air through spargers in AL and FP PBRs while ST PBR involved both aeration and mechanical agitation with the use of impellers for efficient mixing. The aeration rates and agitation value were calculated based on the constant volumetric power input (P/V) as 1.85 L min−1, 5.3 L min−1 and 1 L min−1 with the mixing rate of 170 rpm which corresponded to the constant P/V value of 93.38 Wm−3 for AL, FP and ST PBRs, respectively. Operational conditions of PBRs are presented in Table 1.
difficulty of scale up process that limits the use of this photobioreactor in commercial applications [5,7]. As mentioned above, stirred tanks are another type of PBR where agitation is provided mechanically with the use of impellers. Mixing efficiency is significantly higher than other PBRs so these systems have the optimal heat and mass transfer. On the other hand, mechanical agitation leads to high shear stress on microalgae cells which is a common mechanism of cell damage and they are expensive to operate and maintain due to heat generating by agitation [8,9]. Microalgae cultivation in a PBR is a complex system and should be examined before the use of this technology at industrial scale. To better understand the rheology and hydrodynamic parameters of production in PBRs, different simulation and modeling process can be applied. Computational Fluid Dynamics (CFD) technique is a powerful tool to simulate hydrodynamics, fluid flows induced by mixing, heat and mass transfer within PBR by numerically solving Navier-Stokes equations [10,11]. Generally, CFD expresses the solution of fundamental transport equations in a three-dimensional system. The application of CFD for modeling of PBR design has primarily focused on optimal mixing in two phased systems, gas–liquid mass transfer, flow regime, dissociation of O2/CO2 in the liquid phase [12]. Fucoxanthin is considered as a trend carotenoid due to the expectation of increase in its market share between the years 2020–2024 and has high potential usage in food and feed, agriculture, cosmetic, pharmaceutical, medical and aquaculture areas. In this context, increasing the production efficiency of high value added product with low cost and developing a protocol for reliable and sustainable microalgal cultivation should be investigated. There is a need for novel, economic, environment friendly, safe, fast and low energy consumption production techniques. Therefore, two main objectives of the present study were: (i) to evaluate the difference between three photobioreactors; flat plate, airlift and stirred tank photobioreactors according to fucoxanthin yield from P. tricornutum, (ii) to examine culture conditions by using CFD simulation for the photobioreactor which had maximum yield.
2.3. CFD methodology Numerical Computational Fluid Dynamics (CFD) simulations were carried out to study the flow dynamics in the most efficient PBR which was flat plate PBR found in this study. The dimension details of flat plate photobioreactor are shown in Table 2. 3-dimensional geometry of the PBR was created in the Design Modeler of ANSYS Fluent 17.1, and it was imported to Fluent platform for meshed structure (Fig. 2). Different mesh densities were tested until the mesh independency test criterion was provided. A refined mesh with approximately 5.3 ∗ 106 elements and 2.9 ∗ 106 node points was generated. These results show that the mesh with elements 5.3 ∗ 106 was satisfactory for the current simulation. The simulation runs were performed using the ANSYS CFX-17.1 CFD software. Specifically, the air-culture medium interactions were considered as multiphase problems, where air momentum was transferred to water, and turbulence was also involved. Two-phase simulations were carried out by Eulerian-Eulerian multiphase model in which medium was considered as a continuous phase and air as a discrete particle phase which is assumed to consist of spherical bubbles of the same size with a mean diameter of 3 mm, all under the reference pressure of 1 atm. A SST turbulence k-Ω model was selected to provide predicted turbulence solutions. The flow phenomenon is governed by the following equations. Continuity equation;
2. Material and methods 2.1. Microalgal species and inoculum preparation Phaeodactylum tricornutum EGE MACC-70 was obtained from the Culture Collection of Microalgae at the University of Ege, Izmir, Turkey. Stock culture was cultivated in F/2 [13] medium at 22 ± 2 °C under continuous illumination (65 μE m−2 s−1) in a 2 L sterile bottle for 15 days. For the preparation of the inoculum, the cells from the stock culture were collected and concentrated by centrifugation (1160 ×g, 2 min) and the supernatant was removed. The collected cells were transferred, incubated aseptically in 250 mL flasks containing 100 mL of F/2 medium under the light intensity of 65 μE·m−2·s−1 with the agitation rate of 120 rpm at 22 ± 2 °C for five days. Five-day-old culture of cells was used as inoculum at 10% volume for all experiments. 2.2. Photobioreactors (PBRs) The microalgal strain P. tricornutum was cultivated in three different 2 L PBRs as airlift (AL), flat plate (FP) and stirred tank (ST). Schematic diagrams of used 2 L PBRs are shown in Fig. 1. A plexiglass internal loop airlift PBR was equipped with an online controller (Biosis, Pikolab, Turkey), consisting of a combined temperature-dissolved oxygen probe and pH probe. The riser was sparged with air through a ring sparger (2.4 cm in diameter) located at its base. The sparger had 5 nozzles, 0.4 cm in diameter. The vertical flat plate PBR which was made of plexiglas (0.5 cm wall thickness) was equipped with an on-line controller (Sartorious Biostat A, Germany) consisting of temperature, dissolved oxygen and pH probe. The gas spargers were placed to the bottom of the PBR so as to provide homogenous culture medium. The sparger included 24 nozzles with the diameter of 0.3 cm. Chemical
∂ (ρα rα ) ∂t
+ ∇∙ (ρα Uα rα ) = 0
(1)
where t stands for time, ρα, Uα, rα are the density, velocity and volume fraction of α phase (α = medium, gas), respectively. Momentum equation;
∂ (ρ Uα rα ) + ∇∙ (rα (ρα Uα Uα )) = −rα ∇Pα + rα ρα g ∂t α + ∇∙ (rα μα, eff (∇Uα + (Uα )T )) + Mα
(2)
where g represents the acceleration of gravity, μα,eff represents the 196
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Fig. 1. Schematic diagram of photobioreactors used; a) airlift, b) flat plate, c) stirred tank.
In these equations, k represents the turbulence kinetic energy which is the mean kinetic energy per unit mass associated with eddies in flow, w represents specific rate of dissipation that is the rate at which turbulence kinetic energy is converted into thermal internal energy per unit volume and time. Gk is the generation of turbulence kinetic energy due to mean velocity gradients, Gω is the generation of ω, Γk and Γω are the effective diffusivity of k and ω, respectively. Yk and Yω represent the dissipation of k and ω due to turbulence, Sk and Sω are user-defined source terms. The whole fluid domain was assumed to be under isothermal condition due to the constant temperature in the photobioreactor. Thus, the heat exchange was not considered. The outlet was set with a degassing boundary, which meant that only the gas in the dispersed phase could escape from the surface freely but the continuous phase could not penetrate the top surface. The walls of the PBR were set to no-slip boundary condition with water. The cultivation medium was modeled based on the physical properties with the density of 1004.88 kg m−3 and the dynamic viscosity of 0.006 kg m−1 s−1 at 20 °C under the atmospheric pressure. A time step of 0.005 s was considered for all simulations and each simulation run was completed up to 2 s. Computations were performed until they converged at a residual of 10−4 and the volume averaged gas holdup within the PBRs reached the constant.
Table 1 Operational conditions for photobioreactors. Photobioreactor types
Temperature (°C) Light energy (kJ m−3 s−1) Light intensity (μE·m−2 s−1) Volumetric power input (Wm−3) Aeration rate (Lmin−1) Stirrer rate (rpm)
Airlift PBR
Flat plate PBR
Stirred tank PBR
18 0.315 30 93.38 1.85 –
18 0.315 55 93.38 5.3 –
18 0.315 50 93.38 1 170
Table 2 Dimensions of flat plate photobioreactor. Dimensions
Value
VL (L) Hp (cm) Lp (cm) wp (cm) Hs (cm) Ls (cm) Number of nozzles at air sparger Diameter of nozzles at air sparger HL (cm)
1.6 25 26 3.7 22.7 21 24 0.3 20.5
2.4. Experimental analysis VL, working volume, Hp, height of plate; Lp, width of plate; wp, thickness of plate; Hs, height of air sparger; Ls, length of air sparger, HL, height of liquid.
Samples were taken at indicated times, and the following growth parameters were measured immediately; the cell concentration was determined by counting samples in a Neubauer hemocytometer. The cellular turbidity (optical density) was measured at 600 nm in UV/VIS spectrophotometer (GE Healthcare Ultrospec 1100 pro, UK). Dry weight was determined by filtering a 5 mL culture sample through preweighed GF/C filter (Whatman, UK) and drying the cell mass at 60 °C for overnight. For the chlorophyll-a measurement, cells were harvested at 6000 rpm for 5 min. Chlorophyll in the cells was extracted with 4:1 (v/ v) dimethylsulfoxide (DMSO): water and the amount of chlorophyll-a was determined spectrophotometrically by measuring the light absorption at wavelength of 665 nm. The chlorophyll content was
effective viscosity of α phase, Mα represents the interphase momentum transfer coefficient and P represents the pressure. Turbulent kinetic energy equation and the specific dissipation rate equation;
∂ ∂ ∂ ⎛ ∂k ⎞ (ρk ) + (ρkui ) = ⎜Γk ⎟ + Gk − Yk + Sk ∂t ∂x i ∂x j ⎝ ∂x j ⎠
(3)
∂ ∂ ∂ ⎛ ∂w ⎞ (ρω) + (ρωui ) = ⎜Γw ⎟ + Gw − Yw + Sk ∂t ∂x i ∂x j ⎝ ∂x j ⎠
(4) 197
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Fig. 2. Configuration of flat plate PBR in ANSYS a. Geometry of photobioreactor with components, b. Meshed structure.
injection volume was 20.0 μL, and detection was made by diode array detector with quantitation at the wavelength of maximum absorption for each analyte in order. On the other hand, the chromotogram was obtained at 450 nm for fucoxanthin. For the flow of mobile phase, a gradient system was developed due to its resolving power and improved sensitivity. The mobile phase consisted of a gradient of methanol (A), methyltert-butyl ether (B) and water (C) [16]. Considering the cell death was negligible, specific growth rate (μ) was calculated for the exponential phase of growth (Eq. (6)) as following;
calculated using the following Eq. (5):
Chlorophyll − a (g L−1) =
A665 72.8
(5)
where A665 corresponds to the absorbance of extracted supernatant at 665 nm wavelength with 1 cm pathway cuvette [15]. Fucoxanthin was extracted by a simple ultrasound-assisted extraction method using ultrasonic bath. Then, the solvents were removed with the use of rotary evaporator. Samples collected from the photobioreactor were centrifuged at 6000 rpm for 10 min via centrifuge. The supernatant was removed and CaCO3 was added to each cell pellet. Then, fucoxanthin was extracted with 10.0 mL of THF/DCM (1:1) containing 0.010% (w/v) pyrogallol. The mixture was placed in the ultrasonic bath for 15.0 min. After the ultrasonic extraction, the solution was centrifuged at 6000 rpm for 10 min, and the supernatant was collected. The residue was repeatedly extracted with 10.0 mL extraction solvent until it was colorless. The supernatants were combined and evaporated by the rotary evaporator at 40.0 °C under vacuum [16]. HPLC-DAD system was used for the determination of carotenoids. The C18 column (YMC) temperature was set at 25.0 °C. The separation was achieved by gradient elution at a flow rate of 1.0 mL/min. The
μ=
ln X2 − ln X1 ∆t
(6)
where X2 is the final cell concentration (cells ml−1), X1 is the initial cell concentration (cells ml−1) and Δt is the time required for the increase in concentration from X1 to X2 (day) [17]. Culture medium viscosity was measured twice at the beginning and at the end of the cultivation period by a rotational viscometer (Brookfield model DV-E, USA) with LV type spring torque using LV3 (63) spindle. All the experimental analysis were done in duplicates and presented 198
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Fig. 3. Cell growth profile, fucoxanthin and chlorophyll-a concentrations of P. tricornutum cells, a) cell concentration, b) turbidity, c) fucoxanthin, d) chlorophyll-a; ( ) Flat plate PBR, ( ) Airlift PBR, ( ) Stirred tank PBR. Data shown as mean ± SD (n = 2).
in figures and tables with the average values. The experimental data were analyzed using a one-way analysis of variance (ANOVA). A probability value of p ≪ 0.05 was considered to denote a statistically significant difference.
lag phase was observed during the cultivation in which maximum cell number of 1.74 ± 0.02 × 107 cells ml−1 was obtained at the 7th day. Moreover, the specific growth rate and dry weight concentration of microalgae were found to be lower in AL PBR than the other cultivations (Table 3). For the cultivation conducted in ST PBR, the maximum cell number of 3.42 ± 0.04 × 107 cells ml−1 was achieved where the cells entered stationary phase at the 5th day of cultivation. It's important to note that the main limitation of the use of ST PBRs are shear stress due to the mechanical agitation where microorganisms, bioflocs and other suspended solids are susceptible to damage. Also, low surface area to volume ratio, which in turn decreases the light harvesting efficiency is another disadvantage of these systems [9]. Therefore, the growth rate of cells might be limited in comparison with the aerated cultivation systems. As reported by Sobzcuk et al. [18], increasing the rate of mechanical agitation in stirred tanks led to rise of biomass concentration until an upper limit on agitation speed was reached and this limit depended on the microalgal species. Further increase in agitation speed could be detrimental to the algal cells. FP PBRs are one of the most preferred closed cultivation systems because of the large illumination surface area, ease of sterilization and low shear stress formation [19]. In this study, P. tricornutum cultivation resulted in the highest biomass yield in terms of cell number and dry weight (Fig. 3a and Table 3). In a similar study, cultivation of diatom Entomonies sp. was performed in mechanically stirred tank and flatpanel photobioreactors and the maximum cell number density was determined in FP PBR which was about 73% higher than the result from the stirred tank photobioreactor [20]. Considering the cell movement in PBR, a nonuniform distribution was observed behind the sparger pipe. In this area, the cell density was lower than the other parts of PBR because of the stable flow pattern of fluid and insufficient aeration. This might be an effect of the aeration rate and the locations of nozzles. Cultivation in AL PBR had the lowest cell growth and this growth profile might be an effect of low liquid velocity or improper configuration in terms of the column length which led to uneven densities of
3. Results and discussion 3.1. Photobioreactor cultivations 3.1.1. Cell growth characteristics P. tricornutum cells were grown for 7 days in three different PBRs in batch operations and Fig. 3 demonstrates the microalgal growth performances in terms of cell number and microalgal turbidity. Biomass productivities were significantly different between the three cultivations. FP PBR presented the highest cell concentration of 5.94 ± 0.12 × 107 cells ml−1 which was 3.4 and 1.7-fold higher than obtained in airlift and stirred tank PBRs, respectively (Fig. 3a). Besides, growth parameters achieved in FP PBR also gave the highest values among three cultivations (Table 3). As shown in Fig. 3b, the cultivations had similar OD growth pattern with cell number where the highest cell turbidity of 1.249 ± 0.008 was obtained in FP PBR. In AL PBR, a long Table 3 Growth parameters for photobioreactor cultivations of P. tricornutum. Data shown as mean ± SD (n = 2).
−1
μ (d ) Doubling time (day) Dry weight (g L−1) Fucoxanthin yield (mg g−1 cell) Fucoxanthin accumulation rate (mg L−1 d−1)
Airlift PBR
Stirred tank PBR
Flat plate PBR
0.27 2.56 1.93 ± 0.09 1.4 ± 0.09
0.3 2.23 2.09 ± 0.19 0.82 ± 0.16
0.37 1.83 3.03 ± 0.3 2.42 ± 0.23
0.387 ± 0.12
0.245 ± 0.08
1.05 ± 0.23
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fluid flow. Variation on flow pattern cause heterogeneous nutrient dispersion and unsufficient light utilization of cells. These datas supported that P. tricornutum cells formed aggregates and collapsed at the bottom of AL PBR during cultivation. As a result, changing photobioreactor configuration was the main effect considering the mixing type, shear stress and light penetration for the cell growth and the product yield. It was recorded that the shear stress was 5.4 times lower in FP PBR, in comparison to the value of 1.82 Pa calculated in AL PBR. Therefore, FP PBR was found the most appropriate cultivation system due to the effective illumination and low shear stress. It's well-known that P. tricornutum cells have a low tolerance for the damaging forces like mechanical agitation, impeller blades, bubble break-ups [18]. In this study, aeration did not cause hydrodynamic stress on cells in FP PBR. Illumination is another critical parameter for microalgae cultivation and closed PBRs are performed under the artificial lights. Light intensity was calculated based on the same energy on a photon theory and FP PBR was illuminated with the highest intensity of 55 μE·m−2·s−1 than other PBRs because of its high illumination surface area. So, it was recorded that increasing light intensity led to increase of cell concentration until the light saturation point.
an important role in diffusion rate and air supply for microalgal cells [25]. In this simulation, air bubbles strongly concentrated in the area between the dissolved oxygen and pH probes. The gas volume fraction for the flow conditions was varied between 2% and 12.5% and the local gas volume fraction in the most parts of the reactor was 8% except at the maxima along the sparger nozzles (Fig. 4b). This result was in agreement with previous studies that reported the highest gas volume fraction was obtained in the air sparger and it decreased at the upper part of reactors [10,26]. However, it had the lowest value around the sparger and at the bottom of the PBR. It is also important to underline that the gas distribution was minimum behind the sparger elbow so it could affect the diffusion rate negatively in this area. This result was supported by the air velocity contour plot. When comparing air volume fraction and air velocity contours, a parallel behavior was evident as observed in Fig. 4c. Maximum velocity values were produced around the value of 1.0 m s−1 at the nozzles on sparger where air was fed into PBR. Moreover, it showed higher values around probes as well as gas volume fraction. It can be explained that bubbles hit the probes and broke up into small bubbles so they moved up faster. Another high velocity zone was air-medium interface where air bubbles broke up and they moved forward to outlet quickly. Considering the whole PBR tank, the average air velocity was found as 0.42 m s−1. When air vectors were added to the velocity contours, it was shown that strong local circulations formed in some points demonstrated by red circle in Fig. 4c. It effected diffusion rate and mixing efficiency negatively, and some development studies can be applied for the further researches such as adding mixer or baffles to the system. Huang et al. [27] reported that developing a novel mixer in FP PBRs could significantly increase the fluid velocity along the light attenuation and light/dark cycles, thus further increased the maximum biomass concentration. Thus, the PBRs with novel mixers are greatly applicable for high-efficiency cultivation of microalgae. Another research reported that a flat plate PBR with optimized horizontal baffles improved the algal productivity effectively and economically, and also uniform the growth conditions of algal cells at different locations inside the PBR [28]. Culture medium velocity profile of cross-sections along the y-direction are presented in Fig. 5. The maximum liquid velocity of 0.32 m s−1 was produced under the air sparger while it gradually decreased toward to upper part of the PBR. It is important to note here that placement of sparger nozzles is a critical issue to provide the homogenous air and liquid dispersion. In order to produce more uniform culture medium, their layout might be rearranged. Yang et al. [29] studied the characteristics of the turbulent mixing of multiphase flows in a flat-panel PBR with the different nozzle configurations. Six different cases were tested with the corresponding airflow rate and aeration configurations. After CFD simulation, it was found that the number and the placement of nozzles changed the mean velocity fluid between the range of 0.038–0.106 m s−1. Thus, it is possible to make more efficient cultivation systems with small changes on nozzle configuration. In the present study, medium velocity contours showed similar pattern to that of air phase in some points where the probes were located. In these areas medium velocity was relatively higher than observed in most of the PBR. Another significant result was formation of the dead zones that are defined as the proportion of the reactor volume where the fluid velocity was lower than a limited value. This fluid velocity varies in literature from 0.001 to 0.5 m s−1 [30] and it was determined as 0.02 m s−1 for this study. Dead zones were observed in the upper side of PBR, especially in the top left corner. This may be explained by the movement of air bubbles. The bubbles moved in the upward direction without breaking up and more slowly. Therefore, the lowest medium velocity was observed in these area because of the drag force generated by the deceleration and backward gravity. A common problem of this zone is the cell sedimentation or suspension, therefore the mass transfer rate is reduced, which cause a decrease in the cell growth [31]. In contrast to the gas phase, culture medium velocity showed a higher value behind the air sparger. As shown in Fig. 5c the medium velocity
3.1.2. Fucoxanthin and chlorophyll-a production Fucoxanthin found as main carotenoid in P. tricornutum microalgae where it acts as a primary carotenoid with chlorophyll-a to harvest light and transfer energy [3]. A comparison of fucoxanthin production for cells grown under different cultivation systems is presented in Fig. 3c. Among three systems, FP PBR gave the most abundant fucoxanthin content with the value of 7.35 ± 0.23 mg L−1, followed by AL PBR with the fucoxanthin amount of 2.71 ± 0.12 mg L−1. Contrary to cell concentration, P. ticornutum cells accumulated the lowest fucoxanthin pigment during ST PBR cultivation. The fucoxanthin yield for all cultivations were 0.82 ± 0.16 mg g−1 in ST PBR, 1.4 ± 0.09 mg g−1 in AL PBR and 2.43 ± 0.23 mg g−1 in FP PBR. Maximum fucoxanthin concentration in FP PBR, was probably a result of the low light penetration due to increasing cell concentration and self-shading effect of cells in PBR. It was observed that decreasing the light penetration led to an increase in the fucoxanthin concentration. Such results are in agreement with the previous studies of Xia et al. [2] for O. aurita cultures, Benavides et al. [1] and Gao et al. [21] for P. tricornutum culture and Guo et al. [22] for C. cryptica. McClure et al. [23] reported that, such increment may be related with that fucoxanthin acts as a ‘light harvesting’ pigment and that the algae increases its concentration to compensate for a reduced light intensity. These results suggest that fucoxanthin production is closely related to the light intensity more than growth of microalgae. Chlorophyll-a content showed similar changes with the fucoxanthin concentration, as shown in Fig. 3d. It was an expected result because diatoms possess fucoxanthin chlorophyll a/c binding proteins (FCPs complex) which is responsible for light harvesting during photosynthesis. Most of the studies reported that chlorophyll and fucoxanthin concentration had parallel variations under different light intensities [24]. In this study, the maximum chlorophyll-a concentration of 0.37 ± 0.005 mg L−1 was found in FP PBR. In the other PBRs, its content was lower than obtained in FP PBR, as expected. 3.2. CFD simulation After the experimental analysis, the highest fucoxanthin yield was found in FP PBR under the constant operational conditions. The another aim of this study was to evaluate mixing characteristics, flow dynamics and shear stress for the photobioreactor having the maximum fucoxanthin yield. Thus, the simulation was performed for FP PBR with the chosen parameters. Fig. 4a and b show contour plots of the gas bubble distribution inside the PBR after 2 s of simulation. Gas volume fraction is a key factor in the process of interphase air mass transfer and it plays 200
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Fig. 4. Gas distribution contours, a. Air volume fraction, b. Gas holdup profile c. Air velocity.
in this area reached a value of 0.26 m s−1. This might be due to circulation of the fluid flow around the sparger and the effect of gravity that induced flow toward the bottom of PBR. Similar to the air velocity vectors, vortex formation was observed in the area that air bubbles presented circulation loop. Fluid velocity is a quantitative parameter to describe the mixing performance of the PBR and it can be used to determine turbulent mixing zones inside the PBR. It was defined as the fluid velocity (U) < 0.005 m s−1 as the very low-velocity zone, 0.05 ≤ U ≤ 0.1 m s−1 as the low-velocity zone, 0.1 ≤ U ≤ 0.2 m s−1 as the medium velocity zone, U > 0.2 m s−1 as the high-velocity zone. Generally, the PBR with a better mixing performance contains larger area percentage of the high-velocity zone [29,32]. Considering this point, Fig. 5a shows the velocity profile of PBR and it can be said that percentage of high velocity zone was high throughout the most parts of PBR. There was low-velocity zones where liquid made circulations, as expected. These results showed that efficient mixing was provided and so a much faster algae growth was achieved for flat plate PBR. The detailed fluid characteristic of PBR was presented in Fig. 6, including turbulent kinetic energy (TKE) and eddy viscosity. TKE represents the mean kinetic energy per unit mass associated with eddies in turbulent flow of each grid in the PBR. A higher TKE value means better fluid mixing, heat and mass transfer and improves the growth of
microalgae [27]. In this PBR, the high TKE region was mainly located at the aerated spargers and liquid-gas interface in top of PBR, which could be contributed the frequency of bubble burst in this area. Overall, the profile of TKE (Fig. 6a) showed similar pattern to that of medium velocity (Fig. 5a), however different TKE contours were observed in some domains such as bottom of the PBR and behind the air sparger. In these regions, turbulent energy behavior mostly had several characteristics with air velocity contours (Fig. 4c). This might be due to the phase interactions between the medium and the air could influence the turbulence kinetic energy as reported by Calvo et al. [10]. Also, eddy (or turbulent) viscosity, representing the extent of mixing and the strength of the turbulence in PBRs, plays a significant role in fluid flows. The plots showed varying magnitudes of eddy viscosity throughout the solution domain where it had greatest value at the top portions of the PBR, as shown in turbulence kinetic energy. In the near wall region, the value of turbulent viscosity was found almost zero so it can be noted that the fluid near the PBR walls did not present turbulence behavior (Fig. 6b). The above results showed that the flow and mixing performance was at desired level for the most parts of PBR. This finding was supported by the experimental investigations and velocity and turbulence kinetic energy profile from CFD simulation. However, homogeneity of 201
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Fig. 5. Velocity profile of culture medium a. Medium superficial velocity contours, b. Four section through the reactor column, c. Medium superficial velocity chart at four section.
simulation and the fluid velocity was enhanced from 5.8 × 10−5 m s−1 to 0.45 m s−1 with the appliance of paddlewheels. Also, the mixing time decreased by 31.3% and the mass transfer coefficient increased by 41.2%. In another study, the effect of flat and waved baffles on the mass transfer in flat plate PBR was investigated using CFD software and the waved baffles with low cross section area were found as effective to improve the mass transfer [34]. Su et al. [35] conducted a study to achieve better mixing with low fluid velocity, especially in the vertical direction in a flat plate PBR. With this aim, they designed one flat plate structure in which the destabilizing bar was built in and flow field was simulated using CFD software FLUENT. Simulated results showed that
the culture medium was not provided throughout the PBR because of the different variables such as nozzle diameter, configuration and placement, aeration rate and design parameters of the PBR. Therefore, some modifications should be applied to this system to enhance cultivation efficiency. Many studies can be found in the literature to design the novel flat plate PBRs and these improvements can be used for further researches with this PBR. One of these studies, Cheng et al. [33] proposed double paddlewheels to generate the cycle flow for increasing horizontal fluid velocity between dark and light zones in a flat plate photobioreactor and paddlewheels were positioned at 20 cm high and 60 cm high inside the bioreactor. Studies were conducted with CFD
202
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Fig. 6. Turbulence kinetic energy and eddy viscosity profile of culture medium: a. medium turbulence kinetic energy, b. medium eddy viscosity.
Research and have no conflict of interest.
this destabilizing bar can effectively intensify mixing, which is vital for the algal culturing. Better mixing conditions can be provided with the optimum bar size, flat plate depth and aeration rate [35]. These improvements could be applied to flat plate PBR used in the present study.
Funding information This work was supported by the Scientific and Technological Research Council of Turkey (TUBITAK), Grant number 115M014.
4. Conclusion
References
The comparison of cultivation systems for P. tricornutum for fucoxanthin production, including airlift, flat plate, and stirred tank PBR, suggested that flat plate PBR was superior with the fucoxanthin yield of 2.42 ± 0.23 mg g−1 cell at the temperature of 18 °C under the constant light energy of 0.315 kJ m−3 s−1 using the constant power input of 93.38 W m−3. It was found that the fucoxanthin yield was 3-fold higher in FP PBR than obtained in ST PBR. It is noteworthy to mention that PBR selection depends on the type of strains, type of product desired and operating conditions (efficiently mixing with low shear rate, low energy consumption, optimal heat and mass transfer). When considering the results of CFD simulation, better mixing was observed using the maximum air velocity of 1.0 m s−1 around the sparger nozzles and in the area between pH and dissolved oxygen probes in FP PBR. Also, more homogeneous TKE distribution between the range of 0.0010 and 0.0045 J kg−1 in the middle section of PBR suggested higher mixing efficiency. However, mixing was not provided uniformly throughout the PBR as indicated by varying magnitudes of TKE and eddy viscosity in the PBR domain. Therefore, some development studies could enhance the optimum design of flat plate PBRs.
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Acknowledgments This study was a part of Cost action ES1408 and the authors would like to thank the Scientific and Technological Research Council of Turkey (TUBITAK) with the project number of 115M014 for the financial support. Declaration of interest None. Statement of informed consent, human/animal rights No conflicts, informed consent, human or animal rights applicable. Declaration of authors agreement to authorship and submission All authors mutually agree for submitting this paper to Algal 203
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