Review pubs.acs.org/journal/estlcu
Energetic Performance of Photobioreactors for Algal Cultivation Brief Review A. K. Pegallapati, Y. Arudchelvam, and N. Nirmalakhandan* Civil Engineering Department, New Mexico State University, Las Cruces, New Mexico 88003, United States S Supporting Information *
ABSTRACT: Microalgae are currently being investigated as a potential fuel crop. For algae to be an energy-efficient fuel crop, cultivation systems and operating conditions that have been optimized for biomass productivity have to be refocused toward energy production. In this work, data from the literature on a variety of algal photobioreactors (PBRs) were compiled to reassess them in terms of biomass productivity per unit energy input to the cultivation process. This assessment showed that PBRs that have been optimized for biomass productivity without considering the energy input did not necessarily perform well in terms of energy efficiency. This review recommends that selection of algal PBRs for energy production should consider optimal geometry for efficient utilization of incident light, and their operation should be based on the optimal sparging rate for efficient mixing to maximize energy efficiency.
■
INTRODUCTION Microalgae are emerging as a promising feedstock for biofuel production.1,2 Although microalgae have a long history as a feedstock in the production of high-value products, its potential as a fuel crop has been established only recently. Its advantages over traditional fuel crops include a faster growth rate, a higher energy content, the potential for conversion of the entire biomass into useful products, and its nonreliance on cropland. However, on the basis of current cultivation and biomass-toenergy conversion technologies, algal biofuels are not yet economically viable. According to several reports, the viability of algal biodiesel is currently limited because of the high cost of feedstock accounting for 60−75% of the final product cost,1 and algal production costs must be reduced by a factor of 10 for algal fuels to be competitive with fossil fuels.3 Traditionally, microalgae have been cultivated either in outdoor raceways or in engineered photobioreactors (PBRs) under natural or artificial illumination. The two systems have their own advantages and shortcomings.4−6 Although PBRs are generally viewed as being more capital-intensive than raceways, they are more stable and capable of higher photosynthetic efficiencies, biomass densities, CO2 utilization efficiencies, and volumetric productivities.7 The aim of this review is to reassess PBRs considering their energetic performance rather than biomass production, as has been done previously. Traditionally, PBRs have been evaluated and optimized in terms of volumetric biomass productivity, PB (grams per liter per day). The energy input to the cultivation process, EC (kilojoules per liter per day), had been overlooked because of the high value of the end products. However, for affordable large-scale algal biofuel production, energy spent during cultivation has to be minimized to maximize the net energy © 2013 American Chemical Society
yield. To assess the energy efficiency of the cultivation process, we propose the metric specific biomass productivity, PB/EC (milligrams per kilojoule), defined as the biomass productivity per unit energy input; clearly, PB/EC should be maximized by maximizing PB and minimizing EC.
■
ENERGY EVALUATION OF PBRS Recent reports have evaluated the energy of PBRs in different ways: considering PB with light and mixing energy as inputs, PB/EC;8,9 considering biomass density per unit incident light energy;10 or considering sparging energy as the input and the lower heating value of the biomass and lipid productivity as the output.11,12 These limited studies suggest that PBR geometries and operating conditions may have to be reengineered to maximize PB/EC. Energy Input for Cultivation, EC. Energy input for cultivation includes that required for sparging, ES (kilojoules per liter per day), and that for illumination, EL (kilojoules per liter per day), in the case of indoor PBRs. In the latter case, EL is an order of magnitude higher than ES, whereas in outdoor PBRs, ES is the only concern. Additionally, relatively smaller amounts of energy are spent in pumping and maintaining the temperature of algal cultures. These were not included here because most literature reports compiled in this study did not present all the data necessary to estimate such energy inputs. A procedure for optimizing ES in sparged bubble columns (summarized in the Supporting Information) has been Received: Revised: Accepted: Published: 2
September 14, 2013 October 14, 2013 October 16, 2013 October 16, 2013 dx.doi.org/10.1021/ez400079f | Environ. Sci. Technol. Lett. 2014, 1, 2−7
Environmental Science & Technology Letters
Review
proposed and validated.12−14 At the optimal gas:culture volume ratio, (Q/V)opt, ES can be estimated from12
⎛Q ⎞ ES = 1.440γH ⎜ ⎟ ⎝ V ⎠opt
biomass productivities and lipid contents.17 For instance, a lipid productivity of 50 mg L−1 day−1 can be attained either with a lipid content of 20% and a PB of 0.25 g L−1 day−1 or with values of 35% and 0.15 g L−1 day−1 by extending the process time under stress. Maximizing PB could be more efficient than maximizing lipid content because extending the process time necessitates a larger total reactor volume and additional energy input for sparging and illumination. One study with Chlorella vulgaris, for example, had claimed a lipid content of 53% in the second stage versus 43% in the first stage.23 However, lipid productivity was essentially the same (77.1 and 77.8 mg L−1 day−1 in the first and second stages, respectively), and PB/EC was 18% higher in the first stage (1.55 and 1.23 kJ L−1 day−1 in the first and second stages, respectively), negating the need for two-stage cultivation. This argument to maximize PB rather than lipid productivity is contrary to a recent report advocating the opposite.24 Whereas that report was based on the lipid extraction process, more recent studies have established that algal biofuel production via lipid extraction may be uneconomical because of the need to predry the harvested biomass, which is an energy-intensive step.24 For example, predrying would require 107.3 MJ of energy/kg of algal biodiesel yield; this is ∼5 times the energy content of the algal biomass.25 Hydrothermal liquefaction (HTL) has now emerged as a more efficient pathway to algal biofuel. The HTL process involves heating wet algal slurry to temperatures of 250−350 °C under pressures of 1500−3000 psi. Under such conditions, cell liquefaction and water-catalyzed reactions convert the biomass slurry to oil, gas, and solid fractions. The crude oil fraction can be readily separated for further refinement. Advantages of HTL processes include the ability to handle wet biomass and the ability to convert whole biomass into biocrude and other useful products.26−34 Because biomass with a low lipid content can also be processed by HTL to convert the protein and carbohydrate content to oil,35 this review focuses on biomass productivity rather than lipid productivity. Previous reports have reviewed the features of common PBR designs and their performance based primarily on PB.4,6,36 While most reviews had covered externally illuminated PBRs, this review includes recently proposed internally illuminated configurations for improved light utilization efficiency. A theoretical comparison of an internally illuminated PBR with an externally illuminated bubble column PBR of the same SV demonstrated a smaller footprint, a shorter L, a higher biomass density, and a higher PB/EC.37 For this review, we compiled literature reports on indoor and outdoor PBRs that had focused on PB and reevaluated them in terms of PB/EC, where EC = ES + EL. As mentioned earlier, EL can be ignored in outdoor PBRs; accordingly, PB/EC can be expressed for indoor PBRs as
(1)
where γ is the specific weight (newtons per cubic meter) and H (meters) is the depth of the culture medium. Energy spent on illumination, EL (kilojoules per liter per day), can be estimated from the measured incident illumination, I0 (microeinsteins per square meter per second), and the incident area per unit culture volume of the PBR, SV (inverse meters), as in8 EL =
0.2177 × 86400(I0S V ) ≅ 0.02I0S V 1000 × 1000
(2)
Thus, the total energy input for cultivation, ES, can be estimated from ⎛Q ⎞ EC = ES + E L = 1.440γH ⎜ ⎟ + 0.021I0S V ⎝ V ⎠opt
(3)
To maximize the energy yield from the algal biomass, early research had strived to maximize the lipid content of the biomass and extract its lipid fraction via transesterification.15,16 The common approach to maximizing lipid content had been to extend cultivation in a second stage under stress (e.g., nutrient starvation). Results for several algal species in the literature summarized in Figure 1 show that a desired lipid productivity can be achieved through different combinations of
PB PB = = EC ES + E L 1.440γH
PB Q V opt
( )
+ 0.021I0S V
(4a)
and, for outdoor PBRs, as PB P PB = B = EC ES 1.440γH
Figure 1. Range of lipid content and biomass productivity for selected species reported in the literature, with calculated contours of lipid productivity superimposed. Data from refs 18−22.
(QV )opt
3
(4b)
dx.doi.org/10.1021/ez400079f | Environ. Sci. Technol. Lett. 2014, 1, 2−7
Environmental Science & Technology Letters
■
Review
DISCUSSION
translate to lower capital cost and higher biomass productivities, while a low Q/V would translate to lower operating costs. Specific Biomass Productivity. Specific biomass productivity is a function of algal strain that could be maximized by controlling growth conditions through optimal sparging and nutrient supply, as well as by efficient utilization of the incident light through optimal PBR geometry. In outdoor PBRs, PB/EC is further dependent on location and alignment with respect to the sun. The suboptimality of any of the above parameters and conditions could lead to poor energetic performance. PB/EC would also aid in optimizing second-stage operation in twostage cultivation for producing target metabolites.48 As mentioned earlier, specific productivity estimations in this study ignored the energy spent on cooling or heating the cultures. Cheng-Wu et al.,46 for example, reported that the energy input for cooling accounted for only ∼11% of the total energy input. Another study by Jorquera et al.49 reported that the energy input for pumping water for cooling amounted to 3.26 × 10−5 MJ/kg of the biomass produced, which is a minor fraction of the typical energy content of the biomass (21 MJ/ kg), justifying our case for ignoring inputs other than EL and ES in estimating EC. PB and PB/EC for the indoor PBRs (Table S2) are compared in Figure 3, where the PBRs are rearranged along the abscissa in
Table S1 of the Supporting Information lists the 13 types of PBRs included in this review and their geometric and performance characteristics compiled from the literature. Table S2 of the Supporting Information lists the energetic metrics (EL, ES, and PB/EC) calculated in this study for these PBRs. Dependence of PB/EC on Geometric and Operating Parameters. Geometric (SV and L) and operating (I0, X, and Q/V) parameters of PBRs are critical for their energetic performance because, for a given I0, different designs with different SV and L values at different X and Q/V values can result in a different distribution of light within the cultures. Because PB is highly dependent on the extent of light penetration and the frequency of exposure of the cells to light, optimal PBR geometry and operating conditions are a prerequisite for maximizing PB/EC. Bubble plots (Figure 2) created from the data compiled in this study illustrate the dependence of PB/EC on SV, L, and Q/ V. Even though these studies covered different algal species and PBR configurations, PB/EC is seen to provide a rational basis for comparing them. In effect, a larger SV and a shorter L would
Figure 3. Biomass productivities, P B , and specific biomass productivities, PB/EC, for a variety of indoor PBRs listed in Table S1 of the Supporting Information, rearranged in order of increasing PB. Bold labels indicate internally illuminated PBRs.
increasing order of PB. This comparison highlights the observation that optimizing PBRs for PB does not necessarily correspond to energy-efficient cultivation. For example, the internally illuminated photobioreactor ranked at the bottom of the list of the 18 indoor PBRs in terms of PB; however, in terms of PB/EC, it is ranked 10th.37 Conversely, the modular flat panel photobioreactor, ranking second in terms of PB, ranked 28th in terms of PB/EC.40 Similar analysis could not be done for outdoor PBRs because those studies covered a wide range of geographical locations and diverse conditions. Flat Plate PBRs. Of the flat plate PBRs evaluated,38−41 the modular flat plate PBR design with a high SV and the smallest L resulted in a PB of 0.85 g L−1 day−1, which is 2−8 times higher than that of other flat plate PBRs.40 However, in spite of the high PB, modular flat plate PBRs were found to be inefficient in terms of PB/EC, which could have been due to nonoptimal sparging, a large illumination area, and a low biomass density resulting in excessive energy expenditure. The maximal PB/EC of 9.98 mg kJ−1 was achieved with a flat plate airlift PBR design,39 followed by a transparent rectangular
Figure 2. Dependence of specific biomass productivity (represented by bubble radius) on light energy input per unit volume and (a) incident area per unit volume, (b) light path length, and (c) gas:culture volume ratio. 4
dx.doi.org/10.1021/ez400079f | Environ. Sci. Technol. Lett. 2014, 1, 2−7
Environmental Science & Technology Letters
Review
(0.23 min−1) resulted in a higher PB/EC (123.9 mg/kJ compared to 79.37 mg/kJ for the annular PBR).43,47 Outdoor versus Indoor PBRs. In a rare study in which the growth of three algal strains (H. akashiwo, A. minutum, and K. venef icum) was evaluated in the same PBR sparged at the same rate, under indoor and outdoor conditions,43 H. akashiwo produced a maximal PB of 0.2 g L−1 day−1 indoors while A. minutum produced a maximal PB of 0.35 g L−1 day−1 outdoors; the PB/EC values were 11.9 and 123.9 mg/kJ, respectively. This comparison showed 7−12-fold higher PB/EC values for outdoor cultivation, implying outdoor PBRs are an energy-efficient option for any strain. This energetic analysis showed that a higher PB could compensate for a lower lipid content and result in a higher energy efficiency than the traditional approach of maximizing lipid productivity and optimizing the cultivation system for maximizing PB/EC could be a more energy-efficient approach than maximizing PB. It is suggested that PBRs should be selected and optimized to maximize light utilization and minimize sparging energy.
chamber design (9.62 mg kJ).38 However, both these studies involved PBRs with small SV values and short L values, and a wide range of light intensities (80 and 660 microeinsteins m−2 s−1), implying that PBRs need strain-specific optimization with regard to operating conditions. Among the outdoor flat plate PBRs considered, the highest PB of 0.36 g L−1 day−1 was recorded in a green-wall panel PBR with a high SV of 22.3 m−1 and an L of 0.045 m.18 This same design scored the highest in terms of PB/EC (of 86.7 mg/kJ), as well, suggesting that the green-wall panel PBR could be an optimal design for energy-efficient algal cultivation. Tubular PBRs of Bubble Columns and Airlift Designs. Of the 11 studies on tubular PBRs, the most common design was the vertical column operated as the airlift or bubble column; other designs included the horizontal tubular and helical tubular configurations.4 Among these tubular PBRs, bubble column PBRs43 with Heterosigma akashiwo and the helical airlift PBR42 with Porphyridium cruentum resulted in high PB/EC values of 11.94 and 11.65 mg/kJ, respectively, followed by bubble column PBRs with Alexandrium minutum and Karlodinium venef icum (9.55 and 8.95 mg/kJ, respectively).43 Among the outdoor bubble column PBRs, optimal light levels and sparging resulted in a better PB/EC.43 In the case of the helical airlift PBR, a large SV and a small L (0.01 m) favored a high PB/EC.42 From the available data for bubble column PBRs, it can be deduced that most had been optimized for maximal PB ignoring the energy expenditure, leading to poor energetic performance. However, the recent studies that had adapted energetic optimization ranked better in terms of PB/ EC.11,37 Among the outdoor bubble column PBRs, the study with A. minutum achieved the highest PB/EC of 123.9 mg/kJ compared to those of two other algal strains cultivated in the same PBR design, implying again that species-specific growth characteristics have to be considered along with the optimal PBR design to maximize PB/EC.43 Internally Illuminated PBRs. Of the limited studies on internally illuminated PBRs,37,44,45,50−55 three had reported all the parameters necessary to complete the energetic evaluation.37,44,45 Among the indoor annular PBRs evaluated, the internally illuminated PBR design resulted in the highest PB/EC of 16.45 mg/kJ with Scenedesmus sp. and 4.27 mg/kJ with Nannochloropsis salina.37 Despite the smallest L of 0.02 m and the SV of 50 m−1, the internally illuminated external swirl flow PBR did not rank well in terms of PB/EC, probably because of the supply of excess light and the inappropriate choice of algal strain.44 Though the annular PBR design of Zittelli et al.45 recorded a higher or comparable PB, energetically it ranked lower among the other annular PBRs, probably because of suboptimal sparging. However, annular PBR design studied outdoors with a high ES with Tetraselmis suecica resulted in a PB/EC of 79.37 mg/kJ, implying again that algal strain and light supply can significantly influence the energetic performance of PBRs.47 Among the outdoor PBRs, a high PB of 0.49 g L−1 day−1 was recorded in annular PBRs (SV of 44.2 m−1 and L of 0.045 m),47 followed by 0.36 and 0.35 g L−1 day−1 in green-wall panel PBR18 and bubble column PBRs,43 respectively. However, bubble column PBRs scored the highest PB/EC values of 123.9 and 88.5 mg/kJ.43 Though the PB of the annular PBR (0.49 g L−1 day−1) was 1.9 times higher than that of the bubble column PBRs (0.35 g L−1 day−1), the lower sparging rate in the bubble column PBR (0.1 min−1) compared to that of the annular PBR
■
ASSOCIATED CONTENT
S Supporting Information *
Calculation of energy input for sparging, ES, and Tables S1 and S2. This material is available free of charge via the Internet at http://pubs.acs.org.
■
AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected]. Notes
The authors declare no competing financial interest.
■
ACKNOWLEDGMENTS This study was supported by the National Science Foundation Engineering Research Center, ReNUWIt, and the Ed & Harold Foreman Endowed Chair at New Mexico State University.
■
REFERENCES
(1) Mata, T. M.; António, A. M.; Caetano, N. S. Microalgae for biodiesel production and other applications: A review. Renewable Sustainable Energy Rev. 2010, 14 (1), 217−232. (2) Darzins, A. L.; Pienkos, P.; Edye, L. Final report: Current status and potential for algal biofuels production; IEA Bioenergy Task, 39, Golden, CO, August 2010. (3) Wijffels, R. H.; Barbosa, M. J. An outlook on microalgal biofuels. Science 2010, 329 (5993), 796−799. (4) Carvalho, A. P.; Luís, A. M.; Malcata, X. F. Microalgal reactors: A review of enclosed system designs and performances. Biotechnol. Prog. 2006, 22 (6), 1490−1506. (5) Ugwu, C. U.; Aoyagi, H.; Uchiyama, H. Photobioreactors for mass cultivation of algae. Bioresour. Technol. 2008, 99 (10), 4021− 4028. (6) Xu, L.; Weathers, P. M.; Xiong, X. R.; Liu, C. Z. Microalgal bioreactors: Challenges and opportunities. Eng. Life Sci. 2009, 9 (3), 178−189. (7) Ugoala, E.; Ndukwe, G.; Mustapha, K. B.; Ayo, R. I. Constraints to large scale algae biomass production and utilization. Journal of Algal Biomass Utilization 2012, 3 (2), 14−32. (8) Pegallapati, A. K.; Nirmalakhandan, N. Energetic evaluation of an internally illuminated photobioreactor for algal cultivation. Biotechnol. Lett. 2011, 33 (11), 2161−2167. (9) Ketheesan, B.; Nirmalakhandan, N. Feasibility of microalgal cultivation in a pilot-scale airlift-driven raceway reactor. Bioresour. Technol. 2012, 108, 196−202. 5
dx.doi.org/10.1021/ez400079f | Environ. Sci. Technol. Lett. 2014, 1, 2−7
Environmental Science & Technology Letters
Review
(10) Li, Y.; Zhou, W.; Hu, B.; Min, M.; Chen, P.; Ruan, R. R. Effect of light intensity on algal biomass accumulation and biodiesel production for mixotrophic strains Chlorella kessleri and Chlorella protothecoide cultivated in highly concentrated municipal wastewater. Biotechnol. Bioeng. 2012, 109 (9), 2222−2229. (11) Hulatt, C. J.; Thomas, D. N. Productivity, carbon dioxide uptake and net energy return of microalgal bubble column photobioreactors. Bioresour. Technol. 2011, 102 (10), 5775−5787. (12) Arudchelvam, Y.; Nirmalakhandan, N. Optimizing net energy gain in algal cultivation for biodiesel production. Bioresour. Technol. 2012, 114, 294−302. (13) Arudchelvam, Y.; Nirmalakhandan, N. Energetic optimization of algal lipid production in bubble columns: Part 1: Evaluation of gas sparging. Biomass Bioenergy 2012, 46, 757−764. (14) Arudchelvam, Y.; Nirmalakhandan, N. Energetic optimization of algal lipid production in bubble columns: Part II: Evaluation of CO2 enrichment. Biomass Bioenergy 2012, 46, 765−772. (15) Li, Y.; Horsman, M.; Wang, B.; Wu, N.; Lan, C. Q. Effects of nitrogen sources on cell growth and lipid accumulation of green alga Neochloris oleoabundans. Appl. Microbiol. Biotechnol. 2008, 81, 629− 636. (16) Ge, Y.; Liu, J.; Tian, T. Growth characteristics of Botryococcus braunii 765 under high CO2 concentration in photobioreactor. Bioresour. Technol. 2011, 102, 130−134. (17) Chen, C. Y.; Yeh, K. L.; Aisyah, R.; Lee, D. J.; Chang, J. S. Cultivation, photobioreactor design and harvesting of microalgae for biodiesel production: A critical review. Bioresour. Technol. 2011, 102, 71−81. (18) Rodolfi, L.; Zittelli, C. G.; Bassi, N.; Padovani, G.; Biondi, N.; Bonini, G.; Tredici, M. R. Microalgae for oil: Strain selection, induction of lipid synthesis and outdoor mass cultivation in a low-cost photobioreactor. Biotechnol. Bioeng. 2009, 102 (1), 100−112. (19) Gouveia, L.; Oliveira, A. C. Microalgae as a raw material for biofuels production. J. Ind. Microbiol. Biotechnol. 2009, 36, 269−274. (20) Mandal, S.; Mallick, N. Microalga Scenedesmus obliquus as a potential source for biodiesel production. Appl. Microbiol. Biotechnol. 2009, 84, 281−291. (21) Yoo, C.; Jun, S. Y.; Lee, J. Y.; Ahn, C. Y.; Oh, H. M. Selection of microalgae for lipid production under high levels carbon dioxide. Bioresour. Technol. 2010, 101, 571−574. (22) Xu, H.; Miao, X. L.; Wu, Q. Y. High quality biodiesel production from a microalga Chlorella protothecoides by heterotrophic growth in fermenters. J. Biotechnol. 2006, 126, 499−507. (23) Mujtaba, G.; Choi, W.; Lee, C. G.; Lee, K. Lipid production by Chlorella vulgaris after a shift from nutrient-rich to nitrogen starvation conditions. Bioresour. Technol. 2012, 123, 279−283. (24) Davis, R.; Aden, A.; Pienkos, P. T. Techno-economic analysis of autotrophic microalgae for fuel production. Appl. Energy 2011, 88 (10), 3524−3531. (25) Lardon, L.; Hélias, A.; Sialve, B.; Steyer, J. P.; Bernard, O. Lifecycle assessment of biodiesel production from microalgae. Environ. Sci. Technol. 2009, 43 (17), 6475−6481. (26) Minowa, T.; Yokoyama, S.; Kishimoto, M.; Okakura, T. Oil production from algal cells of Dunaliella tertiolecta by direct thermochemical liquefaction. Fuel 1995, 74 (12), 1735−1738. (27) Brown, T. M.; Duan, P. G.; Savage, P. E. Hydrothermal liquefaction and gasification of Nannochloropsis sp. Energy Fuels 2010, 24, 3639−3646. (28) Biller, P.; Ross, A. B. Potential yields and properties of oil from the hydrothermal liquefaction of microalgae with different biochemical content. Bioresour. Technol. 2011, 102 (1), 215−225. (29) Duan, P.; Savage, P. E. Hydrothermal liquefaction of a microalga with heterogeneous catalysts. Ind. Eng. Chem. Res. 2011, 50 (1), 52− 61. (30) Jena, U.; Das, K. C.; Kastner, J. R. Effect of operating conditions of thermochemical liquefaction on biocrude production from Spirulina platensis. Bioresour. Technol. 2011, 102 (10), 6221−6229.
(31) Jena, U.; Das, K. C. Comparative evaluation of thermochemical liquefaction and pyrolysis for bio-oil production from microalgae. Energy Fuels 2011, 25 (11), 5472−5482. (32) Vardon, D. R.; Sharma, B. K.; Scott, J.; Yu, G.; Wang, Z.; Schideman, L.; Strathmann, T. J. Chemical properties of biocrude oil from the hydrothermal liquefaction of Spirulina algae, swine manure, and digested anaerobic sludge. Bioresour. Technol. 2011, 102 (17), 8295−8303. (33) Yu, G.; Zhang, Y. H.; Schideman, L.; Funk, T.; Wang, Z. C. Distributions of carbon and nitrogen in the products from hydrothermal liquefaction of low-lipid microalgae. Energy Environ. Sci. 2011, 4 (11), 4587−4595. (34) Alba, L. G.; Torri, C.; Samorì, C.; Spek, J. V.; Fabbri, D.; Kersten, S. R. A.; Brilman, D. W. F. Hydrothermal treatment (HTT) of microalgae: Evaluation of the process as conversion method in an algae biorefinery concept. Energy Fuels 2012, 26 (1), 642−657. (35) Frank, E. D.; Elgowainy, A.; Han, J.; Wang, Z. Life cycle comparison of hydrothermal liquefaction and lipid extraction pathways to renewable diesel from algae. Mitigation and Adaptation Strategies for Global Change 2013, 18, 137−158. (36) Briassoulis, D.; Chionidis, P. M.; Tzenos, D.; Lalos, A.; Tsinos, C.; Berberidis, K.; Jacobsen, A. An experimental helical-tubular photobioreactor for continuous production of Nannochloropsis sp. Bioresour. Technol. 2010, 101 (17), 6768−6777. (37) Pegallapati, A. K.; Arudchelvam, Y.; Nirmalakhandan, N. Energy-efficient photobioreactor configuration for algal biomass production. Bioresour. Technol. 2012, 126, 266−273. (38) Hsieh, C. H.; Wu, W. T. A novel photobioreactor with transparent rectangular chambers for cultivation of microalgae. Biochem. Eng. J. 2009, 46, 300−305. (39) Reyna-Velarde, R.; Christiani-Urbina, E.; Hernandez-Melchor, D. J.; Thalassoa, F.; Canizares-Villanuevaa, R. O. Hydrodynamic and mass transfer characterization of a flat-panel airlift photobioreactor with high light path. Chem. Eng. Process. 2010, 49, 97−103. (40) Zittelli, G. C.; Pastorelli, R.; Tredici, M. R. A modular flat panel photobioreactor (MFPP) for indoor mass cultivation of Nannochloropsis sp. under artificial illumination. J. Appl. Phycol. 2000, 12, 521− 526. (41) Goksan, T.; Duraz, Y.; Gokpınar, S. Effects of light path lengths and initial culture density on the cultivation of Chaetoceros muelleri. Aquaculture 2003, 217, 431−436. (42) Lee, E. T. Y.; Bazin, M. J. A laboratory scale air-lift helical photobioreactor to increase biomass output rate of photosynthetic algal cultures. New Phytol. 1990, 116, 331−335. (43) Fuentes-Grünewald, C.; Garcés, E.; Alacid, E.; Rossi, S.; Camp, J. Biomass and lipid production of dinoflagellates and raphidophytes in indoor and outdoor photobioreactors. Mar. Biotechnol. 2013, 15 (1), 37−47. (44) Loubiere, K.; Pruvost, J.; Aloui, F.; Legrand, J. Investigations in an external-loop airlift photobioreactor with annular light chambers and swirling flow. Chem. Eng. Res. Des. 2010, 89 (2), 164−171. (45) Zittelli, C. G.; Rodolfi, L.; Tredici, M. R. Mass cultivation of Nannochloropsis sp. in annular reactors. J. Appl. Phycol. 2003, 15, 107− 114. (46) Cheng-Wu, Z.; Zmora, O.; Kopel, R.; Richmond, A. An industrial-size flat plate glass reactor for mass production of Nannochloropsis sp. (Eustigmatophyceae). Aquaculture 2001, 195 (1), 35−49. (47) Zittelli, C. G.; Rodolfi, L.; Biondi, N.; Tredici, M. R. Productivity and photosynthetic efficiency of outdoor cultures of Tetraselmis suecica in annular columns. Aquaculture 2006, 261 (3), 932−943. (48) Pegallapati, A. K.; Nirmalakhandan, N.; Dungan, B.; Holguin, F. O.; Schaub, T. Evaluation of internally illuminated photobioreactor for improving energy ratio. J. Biosci. Bioeng. 2013, DOI: 10.1016/ j.jbiosc.2013.06.020. (49) Jorquera, O.; Kiperstok, A.; Sales, E. A.; Embiruçu, M.; Ghirardi, M. L. Comparative energy life-cycle analyses of microalgal biomass 6
dx.doi.org/10.1021/ez400079f | Environ. Sci. Technol. Lett. 2014, 1, 2−7
Environmental Science & Technology Letters
Review
production in open ponds and photobioreactors. Bioresour. Technol. 2010, 101 (4), 1406−1413. (50) Tsygankov, A. A.; Laurinavichene, T. V.; Gogotov, I. N. Laboratory scale photobioreactor. Biotechnol. Tech. 1994, 8, 575−578. (51) Javalmardian, M.; Palsson, B. O. High-density photoautotrophic algal cultures: Design, construction, and operation of a novel photobioreactor system. Biotechnol. Bioeng. 1991, 38, 1182−1189. (52) Ogbonna, J. C.; Yada, H.; Masui, H.; Tanaka, H. A novel internally illuminated stirred tank photobioreactor for large-scale cultivation of photosynthetic cells. J. Ferment. Bioeng. 1995, 82 (1), 61−67. (53) Ogbonna, J. C.; Soejima, T.; Tanaka, H. An integrated solar and artificial light system for internal illumination of photobioreactors. J. Biotechnol. 1999, 70, 289−297. (54) Csogor, Z.; Herrenbauer, M.; Schmidt, K.; Posten, C. Light distribution in a novel photobioreactor: Modelling for optimization. J. Appl. Phycol. 2001, 13, 325−333. (55) Patino, R.; Janssen, M.; Stockar, U. V. A study of the growth for the microalga Chlorella vulgaris by photo-bio-calorimetry and other online and off-line techniques. Biotechnol. Bioeng. 2007, 96, 757−767.
7
dx.doi.org/10.1021/ez400079f | Environ. Sci. Technol. Lett. 2014, 1, 2−7
