Multilateral approach on enhancing economic viability of lipid production from microalgae: A review

Accepted Manuscript Review Multilateral approach on enhancing economic viability of lipid production from microalgae: A review Ye Sol Shin, Hong Il Choi, Jin Won Choi, Jeong Seop Lee, Young Joon Sung, Sang Jun Sim PII: DOI: Reference:

S0960-8524(18)30340-7 https://doi.org/10.1016/j.biortech.2018.03.002 BITE 19641

To appear in:

Bioresource Technology

Received Date: Revised Date: Accepted Date:

13 January 2018 27 February 2018 1 March 2018

Please cite this article as: Shin, Y.S., Il Choi, H., Won Choi, J., Lee, J.S., Joon Sung, Y., Sim, S.J., Multilateral approach on enhancing economic viability of lipid production from microalgae: A review, Bioresource Technology (2018), doi: https://doi.org/10.1016/j.biortech.2018.03.002

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Title Multilateral approach on enhancing economic viability of lipid production from microalgae: A review

Authors Ye Sol Shina, Hong Il Choia, Jin Won Choia, Jeong Seop Leea, Young Joon Sunga, Sang Jun Sima*

Affiliations a

Department of Chemical and Biological Engineering, Korea University, 145, Anam-ro,

Seongbuk-gu, Seoul 02841, Republic of Korea *Correspondence to: [email protected]

Abstract Microalgae have been rising as a feedstock for biofuel in response to the energy crisis. Due to a high lipid content, composed of fatty acids favorable for the biodiesel production, microalgae are still being investigated as an alternative to biodiesel. Environmental factors and process conditions can alternate the quality and the quantity of lipid produced by microalgae, which can be critical for the overall production of biodiesel. To maximize both the lipid content and the biomass productivity, it is necessary to start with robust algal strains and optimal physio–chemical properties of the culture environment in combination with a novel culture system. These accumulative approaches for cost reduction can take algal process one step closer in achieving the economic feasibility.

Keywords Microalgae Photobioreactor Mass cultivation Lipid productivity Economic feasiblity

Graphical abstract

1. Introduction Microalgae are unicellular, photoautotrophic organisms which have numerous advantages over terrestrial crops in producing biodiesel: (1) oil production per area of microalgae highly surpass other oilseed crops (Schenk et al., 2008), (2) water source is much less necessary in cultivation rather than terrestrial crops (Dismukes et al., 2008), (3) microalgae have robust environmental adaptation ability and no need to compete with arable land (Brennan & Owende, 2010), (4) rapid and direct carbon fixation of waste CO2 is possible (Chisti, 2007). However, microalgae also have several significant limitations: (1) hard to select appropriate microalgal strain which has high lipid productivity (Ono & Cuello, 2006); (2) difficulties of maintaining outdoor mass cultivation (Rodolfi et al., 2009); (3) although their relatively fast growth rate and high lipid productivity, still low economic feasibility (Mata et al., 2010). In this review, we will focus on the methodology of how to enhance lipid productivity of microalgal cells as seen in Figure 1. Lipid contents and biomass productivity are two most essential parameters when it comes to maximizing the overall lipid productivity of microalgae. There are several factors to improve the induction of lipid accumulation with stress such as light, temperature, pH, and nutrient. When an excess of light illuminates to microalgae, they can induce lipid accumulation rapidly which is one of the self-defense systems for photo-oxidative damage (Markou & Nerantzis, 2013). Temperature can also act as a stress factor which can elevate the reactive oxygen species (ROS) level and induce neutral lipids in the form of TAG (Xin et al., 2011). In nutrient deficiency condition, microalgal cells transform the carbon source to energy-rich form like lipid or starch (Guschina & Harwood, 2006). Enhancement of biomass production is also crucial in lipid productivity and, we will discuss the ways to increase biomass production by improving photobioreactor design. Photobioreactor can be classified into two systems: an open system and a closed system. An open system refers to an open-pond system which is more cost-efficient than a closed system. However, the closed system including flat panel, bubble-column, tubular, plastic bag, stirred tank and other forms has much more advantages over open pond system such as minimizing contamination, easy to maintain culture condition, and less loss of water and supplied CO2 (Liao et al., 2014). Although closed photobioreactors have superiority over the

open-pond system, they still have low biomass productivity due to their inefficient light conversion (Posten, 2009). Many efforts have been made to enhance the biomass productivity by optimizing the surface area to volume ratio, applying baffles for more efficient mixing and effective illuminating techniques (Carvalho et al., 2006).

2. Species-specific characteristics for lipid production from microalgae The success of microalgal mass cultivation is much dependent on the choice of species, especially when aiming for the production of a relatively low-valued product such as biodiesel (Griffiths & Harrison, 2009). Although documented in various literature of ways to produce lipid from microalgae by altering the culture condition, the fundamental limitation cannot be overcome if the selected microalgae strain for biofuel production is not apt for the purpose. In order to obtain economic viability in producing microalgal biofuel, there are major species specific parameters to consider: growth rate, lipid content, fatty acid profile and the ease of harvesting (Nwokoagbara et al., 2015; Viswanath et al.). In general, microalgae have harvesting cycle 1-10 days and has the ability to double their biomass yields as short as 3.5 h depending on species (Nwokoagbara et al., 2015). The fast growth rate, resulting in rapid accumulation of biomass density will enable in the decrease of production cost by increasing the yield per harvest volume (Krzemińska et al., 2014). In addition, the fast growth rate will reduce the risk of contamination, when cultivated in outdoor condition by outcompeting other organism such as bacteria (Kamjunke et al., 2008). For biodiesel production, the total lipid content of a corresponding microalgal strain is directly proportional to the quantity of biodiesel. Therefore, strains with high lipid content is advantageous and desirable (Griffiths & Harrison, 2009). The lipid content of microalgae has a wide range as seen in Table 1. Furthermore, starting with species that naturally produce favorable classes of fatty acid (FA). Microalgal oil contain four different fatty acids: free fatty acids (FFA), monounsaturated fatty acid (MUFA), polyunsaturated fatty acids (PUFA), and saturated fatty acid (SUFA). Biodiesel of different ratios of these fatty acids determines the quality of the biodiesel by altering the energy yield, oxidative stability, cetane number and cold flow properties of the produced biodiesel (Nascimento et al., 2013). Finally, choosing of microalgal strain that can be easier in harvesting is essential in perspective of saving the production cost (Grima et al., 2003). In this section, we will discuss key strain specific parameters that can be beneficial for reducing the biofuel production cost.

2.1 Lipid productivity Most of microalgae accumulate considerable amount lipids under stress condition, resulting in high oil yield. However, the culture condition where biosynthesis of lipids and TAGs occurs, concurrently induces biodegradation of protein, compromising the cell growth and biomass accumulation. This subsequently affects the overall lipid productivity of different species in different magnitude (Chen et al., 2017). The relationship between lipid productivity and nitrogen concentration is species-dependent. The two representative examples of traits for increasing lipid productivity can be observed from 1) Botryococcus braunii with moderate growth rate lipid content is as high as 50% with 28 mg/l/day of biomass productivity (Dayananda et al., 2007) and 2) strain Chlorella vulgaris with relatively fast doubling time of 19 h and accumulate 20% of lipid content (Griffiths & Harrison, 2009). Lipid productivity is the product of lipid content (%DCW) and biomass productivity (grams dry weight per litre per day). It is an essential indicator of produced oil on the basis of both volume and time. A report of lipid content without an indicator of growth rate or biomass productivity can be misleading, since a species with fast growth rate may score higher lipid productivity than those with high lipid content (Griffiths & Harrison, 2009). The mathematical analyses of Yu et al. (2015) demonstrated how strain properties, lipid contents and biomass productivity, weigh heavy in determining the biofuel production cost. In their first analysis of Nannochloropsis sp. F&M-M26 and Nannochloropsis sp. F&M-M27 with similar cell size and biomass productivity, showed 10 % to 20 % cost reduction for the first mentioned strain, due to its 25 % higher lipid content. Additionally, in an analysis of Chlorella vul. F&M-M49 and Chlorella vul. CCAP 211/11B of similar cell size and lipid content, Chlorella vul. F&M-M49 decreased the production cost due to its higher biomass productivity (Yu et al., 2015). Notably, the time factor of the lipid productivity is a critical component of algae due to the adverse culture condition for lipid induction that is detrimental to the cell growth. As seen in Table 1., different strains are indicative of a range of different lipid productivities, despite similar nitrogen starvation condition. Neochloris oleoabundans showed higher lipid productivity of 0.202 gL−1day−1 when Porphyridium cruentum had lipid productivity of 0.038 gL−1day−1, both at nitrogen starvation, making Neochloris oleoabundans more favorable strain to be used in a biofuel industry at the perspective of

comparative lipid productivity (Breuer et al., 2012).

2.2 Fatty acid profiles Beside from the lipid productivity, obtaining a high quality of the lipid is crucial to the success of algal-based biodiesel industry (Chandra et al., 2015; Huerlimann et al., 2010). Biodiesel is composed of five to six methyl esters produced via the transesterification of fatty acids, where it reacts with short chains of alcohol (usually methanol or ethanol) (Gerpen, 2005). The major methyl esters used in biodiesel includes methyl palmitate (C16:0), methyl stearate (C18:0), methyl oleate (C18:1), methyl linoleate (C18:2), and methyl linolenate (C18:3). This matches with the profiles of fatty acids that are naturally produced by microalgae (Graboski & McCormick, 1998; Mishra et al., 2016). Microalgae predominately produce C16:0 and C18:1 and accumulate a considerable amount of C18:0, C18:2 and C18:3 as seen in Table 2 (Sun et al., 2014). The quality of biodiesel can be controlled by selectively choosing the appropriate classes of fatty acid for the transesterification (Karpagam et al., 2015a). According to Schenk et al. (2008), an optimal ratio of fatty acid for biodiesel production from microalgae is 5:4:1 ratio of C16:1, C18:1, and C14:0, respectively. This ratio gives out the high quality of biodiesel properties which can be estimated from high cetane number (CN), low iodine value (IV), and low value of cold filter plugging point (CFPP) which are parameters used for attesting a biodiesel property (Kwak et al., 2016; Nascimento et al., 2013). These standards vary in relation to the molecular structures of fatty acid methyl ester (FAME) such as the size of the carbon chain, the position of the double bond and the ratio of saturated to unsaturated FA, thereby affecting the quantity and quality of synthesized biodiesel (Hu et al., 2008).

2.3 Harvesting: Species specificity The recovery of microalgal biomass is energy intensive and costly that take up about 2030% of the total production cost (Nwokoagbara et al., 2015), mainly due to the low biomass to liquid media ratio. In general, the ratio of biomass concentration of microalgae to the volume of liquid media in the culture is as low as 0.3 5 g/l, which is problematic when attempting for an industrial scale production (Coward et al., 2013). In order to meet the industrial conversion operations concentrations of 300 400 g/l dry

weight, several thickening and dewatering processes are required which negatively effects the economy of the process (Barros et al., 2015; Coward et al., 2013). The problem of low biomass to liquid ratio is further compounded if the selected species have cell diameter <30 μm with specific gravities similar to the culture media (Becker, 1994). The sensitivity analysis on inherent microalgae properties conducted by Yu et al. (2015) indicated the impact of cell diameter can give on the production cost. It can outweigh the benefit of high volumetric productivity and high lipid content by increasing the production cost by 110% when effective diameter was reduced by 50%. In this point of view, harvesting method of microalgal biomass should be carefully selected considering the properties of the working species, including shape, size, surface property, specific gravity of cell, cultivation mode such as open pond or closed system and the final application of microalgae biomass (Griffiths & Harrison, 2009; Muylaert et al., 2017; Nwokoagbara et al., 2015). As for the low-value biofuel production, the selected harvesting method must be able to perform efficient output and inexpensive to achieve the economic feasibility of the process. The principal harvesting methods are filtration, centrifugation, chemical and biological flocculation, gravity sedimentation, flotation and electrical based methods (Barros et al., 2015). Harvesting process should not interfere with the quality of the biomass by causing cell rupture or loss of cellular content, have high efficiency in biomass settling, enable reuse of culture media and have no detrimental impact on environment (Barros et al., 2015; Coward et al., 2013; Muylaert et al., 2017). Centrifugation is most general and reliable method for harvesting biomass due to its high-throughput process ability and applicability across all microalgal species. However, it consumes excessive energy as high as 3000 kWh/t due to the required rotational speeds for acceleration and deceleration for separation (Coward et al., 2013; Schenk et al., 2008), thereby not being suitable to economic processes. Owing to the versatility and simple process, chemical coagulation/flocculation is conceived as another common way for harvesting microalgae. But chemical coagulants which neutralize the negatively charged cell surface, thereby destabilizing the cell suspension, increases operational cost and causes deleterious effects on the biomass product such as metal contamination and/or cell lysis (Papazi et al., 2010). Meanwhile, sedimentation, flotation, filtration, biological flocculation and electrical based strategies are much more dependent on the properties of working species than the

abovementioned methods. Naturally, the sedimentation and filtration are preferred by microalgal species possessing large cell sizes (<10 μm) and high specific gravities for securing straightforward separation and recovery efficiency (Mariam Al et al., 2015). On the contrary, the flotation technique can be applied to relatively small and light microalgal species because it literally exploits the low density of the suspended particles (Edzwald, 1993). On a side note, this technique is deemed appropriate for harvesting lipid-rich microalgal biomass because microalgae with high lipid content tend to float spontaneously (Brennan & Owende, 2010). Harvesting by bio-flocculation takes advantages of clustering of microalgae with biological reagents (i.e., microorganisms), resulting in increase of specific gravity and sedimentation of the cell cluster (Salim et al., 2011). This strategy is an especially species-dependent method since it takes place only when the affinity between working microalgae and bio-coagulant is ensured (Mariam Al et al., 2015). The compatibilities of several filamentous algae, bacteria and fungi as bioflocculants with widely used Chlorella sp. have been successfully investigated and verified (Tiron et al., 2017). Lastly, electrophoretic harvesting utilizes electric field to destabilize the cell surface’s negative charge, inducing flocculation of the cells. Although this method is applicable to a wide variety of microalgal species practically, the flocculation efficiency varies with working species’ living environment (i.e., fresh or sea water) because the high salinity of the medium enables the suspended particles to experience higher electric field, enhancing electrophoretic harvesting efficiency (González-Fernández & Ballesteros, 2013). On balance, even the species characteristics are carefully contemplated, economic viability, throughput of the process and harvesting efficiency are hard to achieve simultaneously with a single technique. Thus, combination of several harvesting strategies, including flocculation followed by filtration should be adapted in practice for economic microalgal fuel production process (Schenk et al., 2008). Decision process for species-specific harvesting strategy is shown in Figure 2.

3. Optimization of microalgal lipid productivity during lipid induction stage Lipid productivity of microalgae is strongly strain-dependent, but there are physio– chemical properties such as light, temperature and cultivation conditions that can be adjusted to enhance the total lipid yield (Davis et al., 2011; George et al., 2014; Wahidin et al., 2013). However, aiming to increase the overall lipid productivity through the optimization of

cultivation condition have limitation due to the contradictory culture conditions for increasing biomass productivity and lipid content. Hence, most commonly a non–interactive, two-stage cultivation method is usually implemented to obtain high biomass accumulation for the first stage of cultivation, then switches the culture conditions, usually deprived of nitrogen, that are apt for high triacylglycerides (TAGs) production (Lucas-Salas et al., 2013; Minhas et al., 2016; Su et al., 2011; Toledo-Cervantes et al., 2013). A single-stage method of nitrogen starvation is often used where the culture starts at a desired nutrient level and slowly reaches to the point of nutrient starvation. The efficiency of two method for nitrogen starvation for lipid productivity is strain-dependent (Yen et al., 2013). In case of C.vulgaris ESP-31, singlestage cultivation with low initial nitrogen concentration was effective method for attaining lipid productivity of 78 mg/L/d and a lipid content of 55.9% (Yeh & Chang, 2011). The microalgal biomass with higher lipid content showed a higher calorific value. In case of C. vulgaris, biomass obtained from nitrogen deprived medium had increased in calorific value by 5 kJ/g, resulting of 23 kJ/g. The calorific value is dependent on the lipid content rather than the protein or the carbohydrate contents (Illman et al., 2000). In addition, the quality of fuel is greatly affected by the characteristics of each fatty acid methyl esters converted from the transesterification of TAGs (Huerlimann et al., 2010). Therefore, studying of methods that can enrich the microalgal oil with beneficial classes of fatty acids is crucial. This section of the review will be focusing on approaches to improve both the quality and quantity of lipid content (DCW%) by altering physio-chemical properties of the cultivation system.

3.1 Effect of light: light intensity and spectral light quality on microalgae to induce high lipid accumulation In a photoautotrophic culture, microalgae use light as their primary source of energy via photosynthesis, thereby making light intensity and wavelength indispensably important parameter that affects their lipid content and their fatty acid composition. In general microalgae have light saturation limit around 600 ft. candles and exposure to light intensity higher than the limit will lead to oxidative stress (Sforza et al., 2012; Wahidin et al., 2013). The excessive photo-assimilation result in lipid storage from the self-defense mechanism to avoid photo-oxidative damage; thereby, converting excess light energy to chemical energy (Guo et al., 2015a; Solovchenko et al., 2008). Based on

this principle, Chlorella sp. showed the highest lipid accumulation when cultivated under the light intensity of 320 μE m−2 s−1 and the result was consistent with different cultivation mediums (Guo et al., 2015a). A similar result was obtained for Botryococcus braunii KMITL 2, which was isolated from freshwater in Thailand. The culture exposed to high light intensities of 200 and 538 μE m−2 s−1 accumulated more lipid than those grown under the lower light intensity of 87.5 μE m−2 s−1 (Ruangsomboon, 2012). In addition, Liao et al. (2017) cultivated Chlorella vulgaris in a planar waveguide flat-plate photobioreactor and have confirmed that the organism showed 92.89% improvement in lipid yield when cultivated at the high light intensity of 560 μE m−2 s−1 than the lower intensity of 160 μE m−2 s−1. Light spectral quality is another aspect of light that significantly influences the total lipid production and the fatty acid profile of microalgae (Hultberg et al., 2014). Light spectral quality depends on the absorption spectrum of the chlorophyll and accessory pigments such as phycobilins and carotenoids present in microalgae. The chlorophyll of microalgae has an absorption band in red (630–675 nm) and blue (450–475 nm) spectral regions (Teo et al., 2014). Therefore, irradiation of matching the band of light for the constitutive pigments can maximize the photosynthetic rate and the lipid productivity with minimum energy consumption (Ra et al., 2016). The marine microalgae, Tetraselmis sp., Nannochloropsis sp. and Isochrysis galbana produced higher lipid contents under blue light than other wavelength such as red, red-blue, white light (Teo et al., 2014; Yoshioka et al., 2012). This phenomenon can be explained by the study of Roscher and Zetsche (1986) where it indicated that the blue light of wavelength 430–510 nm promoted the synthesis of enzymes ribulose bisphosphate carboxylase/oxygenase (RuBPCase) and carbonic anhydrase, thereby increasing the productivity of TAGs. In addition, exposure to different light wavelength induces production of varying fatty acid composition. Hultberg et al. (2014) reported that Chlorella vulgaris exposed to monochromatic light at green wavelength showed an increase in polyunsaturated fatty acids of C16:3 and C18:3 than at yellow, red, white wavelength.

3.2 Effect of temperature Temperature is an abiotic stressor that stimulates TAG metabolism and changes the composition of fatty acid produced by microalgae (Converti et al., 2009; Renaud et al.,

2002). During the growth phase, synthesized fatty acids are mostly esterified to produce membrane lipid that is glycerol-based. Conversely, microalgal lipid metabolic activities are switched to accumulate neutral lipids in forms of TAG at stress condition that usually accompanied by high reactive oxygen species (ROS) level (Roleda et al., 2013; Xin et al., 2011). Xin et al. (2011) measured the ROS level of Scenedesmus sp. LX1 for different cultivation temperatures and observed an increase in ROS level lower temperature of 10 to 20 °C than at a temperature of 25 to 30 °C. Accordingly, more lipid was accumulated at lower temperatures of 10 to 20 °C than the standard cultivation temperature of 25 °C. However, Converti et al. (2009) showed that the optimal temperature for increasing lipid contents differed species to species. In case of Chlorella vulgaris, a trend of decrease in lipid contents was observed with increase in temperature from 25 to 30°C. For Nannochloropsis oculata, lipid contents doubled with the increase in temperature from 20 to 25 °C. Temperature also affects the fatty acid composition. At high temperature, the formation of saturated fatty acids is favorable in many species of microalgae which are influenced by the fluidization of the cell membrane. And as the number of double bond increased, the fluidity of phospholipid bilayers increased. (Los & Murata, 2004; Renaud et al., 2002; Thompson et al., 1992). At the high temperature of 30 °C, Scenedesmus sp. LX1 nearly all of the fatty acids were saturated and long-chain species (C16 ~ C18) (Xin et al., 2011). Similar results were achieved by different species such Rhodomonas sp., Cryptomonas sp., and prymnesiophyte NT19 (Renaud et al., 2002).

3.3 Effect of cultivation condition: CO2 and pH The aeration of CO2 gas into a photoautotrophic culture provide the carbon source needed for the photosynthesis. An adequate amount of carbon source is needed to maximize the lipid production in microalgae (Zhu et al., 2016). Hui et al. (2016) studied the effect of different concentrations of CO2 (0.03–20%) in microalgae, Tribonema minus, and observed a general trend of decreased lipid productivity with increased CO 2 concentration. The highest total lipid content was achieved at 2% CO2 aeration, and lowest total lipid content was at 20% CO2. However, the culture aerated at 0.03% CO2 resulted in second lowest lipid content, indicating the lack of carbon source in the culture which limited the photosynthesis. Chiu et al. (2009) cultivated Nannochloropsis oculata

at various concentration of CO2 (2 %, 5%, 10%, 15%) and explained the correlation of CO2 concentration with lipid productivity using the change in the pH of the culture. The presence of high level of carbonic acids (H2CO3) that were converted from the unused CO2, lowered the pH of the culture media, making the culture condition unfavorable for the growth of microalgae. In addition, the decreased pH negatively affect the carbon assimilation of lipid synthesis due to the lowered concentration of bicarbonate at low pH (Chiu et al., 2009; Choi et al., 2017; Hui et al., 2016; Zhu et al., 2016). The changes in pH lead to various biochemical responses to microalgae. In case of Chlorella, high pH inhibited the cell division cycle, induced the release of autospores and lead to the utilization of TAG (B. Guckert & Cooksey, 1990; Peng et al., 2015). The composition of fatty acid changes in response to the different concentration of CO2. For microalgae strains Nannochloropsis sp., Nannochloropsis oculata (Droop) Hibberd, Nannochloris atomus Butcher and Isochrysis sp., cultivated at contionous 15 vol.% CO2 (CO2 stresss condition) produced more of long chain fatty acids, starting from 17 carbon atoms (C17:1, C18:0, C18:1, C18:3n-6 and C20:0) (Roncarati et al., 2004). Cheng et al. (2016) explained that the microalgal fatty synthesis begins from C16 and C18 fatty acids, which succeed by desaturation and elongation reactions, leading to the decreased in saturated and monosaturated fatty acids and increased in polyunsaturated fatty acids (PUFAs) (Ratledge, 2004). However, if the cells were at nitrogen or phosphorous limited conditions, the relevant enzymes that carry out desaturation and elongation reactions will be produced at a smaller amount, leading to decreased in PUFAs production (Cheng et al., 2016).

3.4 Nutrient starvation The microalgal fatty acid composition is closely related to the chemical composition of the cultivation medium (Paliwal et al., 2017). Microalgae at the nutrient-limited condition, reduce their cell division and remobilizes the available carbon source to accumulate energy-rich storage products such as lipid or starch (Doan et al., 2011; Praveenkumar et al., 2012). Thereby, the percentage of polar and nonpolar lipid can be regulated by altering the ratio of nitrogen, phosphorous and inorganic carbon in the culture medium (Rodolfi et al., 2009). In addition, depending on nutrient deprivation conditions and the species of choice, the resulting composition of fatty acids differed. For

D.salina, most abundant fatty acid was linolenic acid (C18:3) when cultivated at iron deprivation medium. In contrast, palmitoleic acid (C16:1) was observed at the highest level during a nitrogen deprivation (Gao et al., 2013). Of many different nutrient limitation methods, nitrogen starvation is one of the most effective and reliable way to induce lipid accumulation (Yeh & Chang, 2011). Gao et al. (2013) cultivated Chaetoceros muelleri and Dunaliella salina in different nutrient limiting medium (nitrogen, phosphate and iron deprivations) and among three conditions mentioned, total lipid content was the highest during nitrogen starvation. This is in agreement with Chlamydomonas reinhardtii, which resulted in the relatively high amount of lipid at nitrogen starvation condition (James et al., 2011). In addition, a new nitrogen deficiency strategy of enhancing the biomass productivity and lipid content simultaneously is arising. It is so called “continuous nitrogen limitation” which reduces downtime and operation flexibility under varying outdoor conditions (Chi et al., 2016; Liu et al., 2016; Schulze et al., 2016). The studies show higher lipid productivity can be achieved using novel method of nitrogen starvation of where the initial nitrate concentration is provided at low concentration. By doing so, the cells in the environment are continuously kept in nutrient stress and thereby accumulate lipid in their body while they proliferate. As a result, high lipid content is reached at a small cost in growth.

4. Improvement of culture system: Photobioreactor design The success of practical lipid production from microalgae depends on the efficiency of the cultivation system. The two prevailing large-scale microalgal cultivation systems are open ponds and closed photobioreactors (PBRs), where microalgae are suspended in liquid media (Sun et al., 2016). The open ponds have the benefit of its low capital and operation cost. However, such systems are unable to control the operational conditions such as temperature and light. In addition, open pond systems are at constant risk of contamination (Borowitzka, 2013). On the other hand, closed cultivation systems such as tubular and flat panel photobioreactor (PBR) have high biomass and lipid productivity due to its high photosynthetic efficiency and its ease to maintain a monoculture (de Vree et al., 2015; Dogaris et al., 2015; Hwang et al., 2012) but, it suffers from high capital and operational expenditure from mixing, cooling and embodies energy (Zittelli et al., 2013). Table 3 shows different biomass productivity depending on photobioreactor designs. For this reason, new methods for improving process design and operation are rising to compensate the high cost

by increasing the overall efficiency of the reactor. In this section of the review, we will be discussing key design parameters important for the scale-up of a photobioreactor and presenting novel photobioreactor designs to increase general productivity.

4.1 Scaling-up of a photobioreactor: maintaining of the photosynthetic efficiency In a photobioreactor scale-up, maintaining an optimal level of microalgal productivity while increasing the cultivation volume is crucial. The scale-up process is a stage-by-stage method of selecting design conditions with optimized operational procedures for specific microalgae strain (Cuello et al., 2016; Vernerey et al., 2001). In case of a photobioreactor, a higher degree of complexity is present than the conventional reactors because additional factor of light needs to be taken into account (Vernerey et al., 2001). Aforementioned, light is a fundamental force and a stressor for microalgae to synthesize chemical energy through photosynthesis, thereby affecting the growth and lipid accumulation. Therefore, microalgal lipid production greatly depends on the light availability in a culture. However, light penetration through a microalgal suspension is rather uneven due to the shading effects of cells (Kumar et al., 2010), making light availability a limiting factor during a scale-up of a PBR (Wang et al., 2014). The overall light condition in a PBR can be determined by the light distribution and the light penetration. The light distribution within a PBR can be improved by implementing an efficient mixing system which will homogenously circulate the cells between light deficient and light efficient areas. This includes bubbling with active stirring mechanism in a stirredtank PBR, bubbling of gas in an airlift system, and built-in static mixer that promote mixing along light gradient (Huang et al., 2014; Sobczuk et al., 2005; Sun et al., 2016; Zhang et al., 2015). Huang et al. (2014) developed flat-plate PBRs with mixers trapezoidal chamber units of mixing degree along the light gradient and showed a 42.9% increase in biomass concentration. The light penetration depth can be increased via implementing novel technologies. Sun et al. (2016) developed a planar waveguides doped with light scattering nanoparticles into a flat-plate PBR to enable even distribution of light within microalgae. This system showed 10.3 times increased illumination surface area per unit volume than a flat-plate PBR without a planar waveguide. (Sun et al., 2016) integrated a hollow polymethyl methacrylate (PMMA) tubes into a flat-plate PBR which improved the incident light by 2–6.5 times and improving photosynthetic efficiency by

12.52% than the control PBR.

4.2 Scaling-up of a photobioreactor: hydrodynamics and mass transfer properties The consideration of key design parameters, liquid-gas hydrodynamics and mass transfer, is essential for a successful scale-up of a photobioreactor or a predictable design of novel photobioreactor. As for an aerobic bioprocess, aeration and agitation power per reactor volume are important factors that provide an efficient oxygen mass transfer rate (Moutafchieva et al., 2013; Vernerey et al., 2001). Mass transfer can vary depending on designs and operation modes for mixing-sparging equipment installed in bioreactors and can be analyzed by the volumetric mass transfer coefficient, kLa (Akita & Yoshida, 1973; Moutafchieva et al., 2013). During an autotrophic microalgal culture with continuous supply of CO2 or direct utilization of flue gas in attempt for biological carbon capture and utilization technology, the dynamic behavior of CO2 bubbles determines the distribution and growth of microalgae (Choi et al., 2017; Ding et al., 2016). The parametric study of Ding et al. (2016) in a bubble column reactor indicated that the problem of “bubble carrying” in a reactor which led to a non-uniform distribution of microalgal cells can be solved with the optimal operation conditions of 5% (V/V) in the inlet CO2 concentration at flow rate of 20ml/min, accompanied by 20 μm blast orifice. As mentioned above, different concentration of CO2 can attribute to the accumulation of lipid in microalgae in autothrophic culture. It is essential to provide a suitable amount of CO2 to maximize the lipid production. Therefore, aeration rate is an essential parameter to enhance the microalgal cell growth and lipid accumulation in a PBR by enhancing the transfer of CO2 included in the supply gas to the cells. Seyed Hosseini et al. (2015) developed a top–lit open bioreactor coupled with a gas–lift system in which microalgae were exposed to 6% CO2 and resulted in 27% increase in lipid content than microalgae grown in PBR without CO2. However, excessive aeration may cause damages to cells from mechanical shear forces (Acién et al., 2017; Pham et al., 2017). The aeration of CO2 is also important as a means of pH control, and a method for internal mixing of cells which can alleviate the formation of nutrient concentration gradients (Anjos et al., 2013; Guo et al., 2015b). Choi et al. (2017) developed a cost-effective bicarbonate/phosphate (BP) buffer system, in which the performance of the buffer improves under the continuous CO2 supplementation from the flue gas and resulted in 105% increase in biomass of Haematococcus pluvialis.

New PBR designs based on the knowledge of the fluid dynamics and the mass transfer can maximize the attainable productivity. Guo et al. (2015b) suggested a rectangular airlift loop photobioreactor that has the advantages of good mixing, relatively high gas–liquid mass transfer rate and well-defined fluid flow pattern. Pham et al. (2017) developed an x-shaped airlift PBR and tested for its efficiency via parameters such as gas hold up, mixing time, gas liquid mass transfer coefficient, shear stress. It resulted that new designed PBR produced 30.05% more biomass than control PBR and induced high contents of monounsaturated lipids that are favorable for biodiesel production. 4.3 Controlling for optimal nutrient in a photobioreactor For the proper growth of microalgae, an adequate amount of nutrients required. The growth rate and lipid production can be controlled via regulating the availability of major nutrients, nitrogen and phosphorous, and essential nutrients, carbon, hydrogen, sulfur, calcium, magnesium, sodium, potassium and chlorine. Additionally, trace metals such as iron, boron, manganese, copper, molybdenum, vanadium, cobalt, nickel, silicon, and selenium are supplemented in the culture (Kunjapur & Eldridge, 2010). However, the sophisticated nutrient control in practical scale PBR is not always easy. In this regard, Kim et al. (2015) develop the semi-permeable membrane PBRs (SPM-PBRs) for managing nutrient concentration in the cell culture. The nutritional condition can be automatically controlled by diffusion through the semi-permeable membrane attached to the PBR, thereby avoiding the necessity of complicated nutrient monitoring and controlling systems. As a result, the fatty acid content increased from 12 to 30% at day 0 along with the increase in the biomass productivity. Additionally, McGinn et al. (2017) have proposed a flow rate automated 300 L continuous photobioreactor using an online flow control algorithm, enabling the real-time optimization. The establishment of continuous culture system allow cultures at steady state of nutrient supply and light intensity to support the highest rates of biomass productivity (MacIntyre & Cullen, 2005). As a result, Scenedesmus AMDD culture produced an average volumetric biomass productivity of 0.11 g/L/d during 25 days of cultivation and outperformed the control turbidostat photobioreactor by 70% increase in productivity.

5. Future prospects Microalgal biofuel has started a new generation of biofuel system without increasing the pressure on the “food versus fuel” debate nor disrupting the forest ecosystem. However, to

date, microalgal biofuel has not gained its economic feasibility. Economic analysis suggested that a development of a coupled systems of microalgal biofuel and co-products (e.g., biochar, pigments, nutraceuticals) productions will enable a practical operation by targeting larger market (Gendy & El-Temtamy, 2013; Stephens et al., 2010). For the success of industry, targeted products should have a high yield and stable end-products. However, microalgae accumulate lipid during stress condition where biomass productivity is negatively affected. The most effective way to approach this problem is through the use of genetic engineering (Chen et al., 2017). Trentacoste et al. (2013) performed targeted knockdown of multifunctional lipase/phospholipase/acyltransferase in diatom Thalassiosira pseudonana using RNAi, resulting in 3.24.1-fold increase in the lipid content without compensating the growth rate. A similar result can be achieved for Chlamydomonas reinhardtii, a model strain for microalgae. With the application of genetic engineering tool such as CRISPR-cas9 and RNAi, targeted mutation is possible. Targeted mutation can enhance the synthesis of targeted molecule, can increase tolerance of a strain to different environmental conditions, and can create special traits such as autolysis or direct secretion of targeted products. In addition, microalgae cultivated at pond have far lower photosynthetic efficiency of 14% than the maximum theoretical photosynthetic efficiency of 812%, providing a margin for improvement (Stephens et al., 2010). To improve the apparent inefficiency, biological strategies of reducing the size of the chlorophyll-binding photosynthetic light-harvesting antenna system have been tested, in which each photosystems used light more efficiently (Polle et al., 2003). Microalgal biofuel technologies have strength due to its potential of providing environmentally friendly and sustainability fuel. In addition, microalgae have a wide spectrum of applicability where food and pharmaceutical industries can benefit. With the help of innovative technologies, microalgal industry will be able to grow as a stand-alone industry over the next decade.

6. Conclusion The lipid, an energy reserve in the microalgal cell, is a promising feedstock for biodiesel. This review suggests strategies for increasing overall economic feasibility of lipid production. In a microalgal bioprocess, microalgal strain with desirable characteristics is essential for

decreasing the overall cost of biodiesel production. In addition, several physio-chemical factors such as light, temperature, pH, CO2 concentration, and nutrient starvation, affect the lipid productivity and the fatty acid composition. In practice, implementing an optimized PBR system can increase lipid productivity and satisfy economic feasibility. This review lays a foundation for strategic ways for lipid induction of microalgae of their significance in practice.

Acknowledgements The authors would like to acknowledge the support of the Korea CCS R&D Center (Korea CCS 2020 Project) funded by the Korea government (Ministry of Science and ICT) in 2017 (grant number: KCRC2014M1A8A1049278) and National Research Foundation of Korea (NRF) funded by Korea government (grant number: NRF2016R1A2A1A05005465) and Korea Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by the Korea government (Ministry of Trade, Industry and Energy) (grant number: 20172010202050). And a special thanks to Korea University.

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Figure Captions:

Figure 1. Overview of parameters affecting economics of lipid production from microalgae

Figure 2. Decision process for species-dependent harvesting method

Tables

Table 1. Lipid productivities of each microalgal species during nitrogen starvation condition

Species

Culture mode

Biomass productivity (gL-1day-1)

Lipid content (DCW%)

Lipid Productivity (gL-1day-1)

Chaetoceros muelleri

Batch

0.0115

46

0.0050

Gao et al. (2013)

Chlorella pyrenoidosa

Continuous

0.4178

34.69

0.1449

Wen et al. (2014)

Chlorella vulgaris

Batch

0.2341

31.6

0.074

Deng et al. (2018)

Chlorella zofingiensis

Batch

0.1714

30

0.036

Mao et al. (2018)

Chlorococcum pamirum

Batch

0.047

64.9

0.041

Feng et al. (2014)

Chlorococcum sp.

Semicontinuous

0.1066

22.82

0.0238

Zhou et al. (2013)

Coelastrella sp.

Batch

0.0316

24

0.0075

Karpagam et al. (2015b)

Desmodesmus sp.

Batch

0.262

38.1

0.098

Ho et al. (2014)

Dunaliella salina

Batch

0.013

48

0.0065

Gao et al. (2013)

Micractinium. sp

Batch

0.06071

13.85

0.00841

Sun et al. (2014)

Nannochloropsis gaditana

Continuous

0.49

38

0.051

San Pedro et al. (2013)

Nannochloropsis oceanica

Batch

0.1257

46.14

0.05691

Meng et al. (2015)

Nanochloropsis oculalta

Batch

0.1357

12.5

0.0171

Polishchuk et al. (2015)

Reference

Neochloris oleoabundans

Batch

0.426

47.4

0.202

Breuer et al. (2012)

Scenedesmus abundans

Batch

0.1672

43.93

0.1247

Mandotra et al. (2014)

Scenedesmus dimorphus

Batch

1.083

36.6

0.17

Wang et al. (2013)

Scenedesmus obtusiusculus

Batch

0.500

55.7

0.200

Toledo-Cervantes et al. (2013)

Tetraselmis marina

Batch

0.100

34

0.013

Dahmen-Ben Moussa et al. (2017)

Trentepohila arborum

Batch

0.1657

26.3

0.04363

Chen et al. (2016)

Table 2. Fatty compositions of different microalgal species Fatty Acids

Chlorella vulgaris

Neochloris oleoabundans

Nannochloropsis oculata

C12:0

-

-

-

C14:0

-

1

3.3

C16:0

17.11

23

17.8

15

17.55

C16:1

1.5

3

26.6

1

C16:2

7.01

3

-

C16:3

4.13

2

-

C16:4

3.03

-

-

3

0.9

C18:0

Chlorella zofingiensis

Chlorococcum sp.

Chlorella pyrenoidosa

Micractinium sp.

Scenedesmus dimorphus

Chlorococcum pamirum

-

-

-

-

-

0.53

0.4

1.55

28.91

25.21

13.1

25.77

5.75

3.00

3.32

4.3

10.29

4

-

4.33

-

2.4

-

2

-

5.67

-

1.8

-

-

-

-

12.9

-

3

7.82

2.45

4.19

0.5

28.84

C18:1

39

41

7.7

47

1.17

13.42

11.03

7.3

13.86

C18:2

15.11

21

2.9

17

32.45

21.37

10.1

10.6

10.28

C18:3

10.08

3

0.7

8

15.8

26.3

7.11

21.5

7.4

C18:4

-

-

-

-

-

-

2.9

-

C20:0

-

-

-

-

-

2.13

-

0.01

C20:1

-

-

-

-

-

-

-

0.05

C20:4

-

-

7.1

-

-

-

-

-

C20:5

-

-

28.4

-

-

-

-

-

Others

3.03

-

0.2

19.46

-

36.38

6.7

Ref.

Liu et al.

Breuer et al.

Khozin-

Breuer et

Sun et al.

Shekh et al.

Sun et al.

Islam et al.

(2016)

(2012)

Goldberg and

al. (2012)

(2014)

(2013)

(2014)

(2013)

Boussiba (2011)

1.95 Feng et al. (2014)

Table 3. Comparative biomass productivity from different photobioreactor designs

Photobioreactor

Strain

Culture mode

Light intensity (μmol m2 s−1)b

Biomass Productivity (g L-1 d-1)

Volume (L)

References

Bubble column

Tetraselmis sp.

Photoautotrophic

100  5

8.6  0.9

0.4

Kim et al.

KCTC12236BP Flat panel airlift

Chlorella

(2017) Photoautotrophic

45

0.086  0.003a

2

vulgaris

BenaventeValdés et al. (2017)

Stirred tank

Chlorella

Photoautotrophic

45

0.181  0.001a

2

vulgaris

BenaventeValdés et al. (2017)

Vertical tubular

Chlorella kessleri

Photoautotrophic

40 W

0.087

2

de Morais and Costa (2007)

Bubble Column

Chlorella

Photoautotrophic

13000 lux

0.0044 a

vulgaris

a

The biomass productivity was calculated and estimated from the original paper

b

Unit other than μmol m2 s−1 indicated in the table

0.5

Scarsella et al. (2010)

Figures

Figure for Graphical abstract

Figure 1.

Figure 2.

Title Multilateral approach on enhancing economic viability of lipid production from microalgae: A review

Authors Ye Sol Shina, Hong Il Choia, Jin Won Choia, Jeong Seop Leea, Young Joon Sunga, Sang Jun Sima*

Affiliations Department of Chemical and Biological Engineering, Korea University, 145,

a

Anam-ro, Seoungbuk-gu, Seoul 02841, Republic of Korea *Correspondence to: [email protected]

These authors contributed equally to this work.

1

*Corresponding author:

Sang Jun Sim

Tel.: +82 2 3290 4853; fax: +82 2 926 6102. E-mail: [email protected]

Highlights -

Mass cultivation of microalgae for biodiesel production

-

Selecting of strains for mass cultivation

-

Physio–chemical properties to increase lipid contents of microalgae

-

Novel designs of photobioreactors to enhance overall lipid productivity