Downstream processing of microalgal feedstock for lipid and carbohydrate in a biorefinery concept: a holistic approach for biofuel applications

Abstract

An integrated microalgal feedstock-based biorefinery approach towards improving overall performance of downstream processing of algal biomass to produce multiple products is necessary to make a good value proposition. The present study thus focuses on the development of an integrated downstream processing strategy for the concomitant extraction of lipid and carbohydrate as feedstocks for potential biofuel applications. A harvesting efficiency of up to 90.6 ± 2.8% and 98.7 ± 2.1% was accomplished for Chlorococcum cells by employing minimal FeCl₃ in first the 30 min and 150 min, respectively, as opposed to 55.52 ± 2.2% in 30 min using only its self-flocculation ability. Various physical and chemical pretreatment methods were attempted to maximize the recovery of sugars and lipids, separately and simultaneously. Microalgal lipid was efficiently recovered using cell disruption with bead-beating and chloroform–methanol (2 : 1, v/v) as the extraction solvent. The microalgal carbohydrate recovery and conversion into free fermentable sugars was found to be greater in the case of acid hydrolysis as compared to alkaline hydrolysis. The microalgal biomass, when pretreated separately, gave a total sugar yield of 89.6 ± 3.1% and a total lipid yield of 96.2 ± 2.9%. Therefore, to improve the performance of the process, simultaneous extraction of carbohydrate and lipid was carried out using bead-beating followed by acid treatment. The recoveries of fermentable sugars from the supernatant and that of lipid from pellets were most efficient, with respective yields of nearly 86.5 ± 2.6% and 74.1 ± 1.8%, without any downtime. The extracted lipid was then converted into fatty acid methyl esters (FAME) as a biodiesel product using the standardized acid catalyzed transesterification reaction, resulting in FAME conversion of 94.7 ± 2.5%. The fermentability of the total sugars to bioethanol using S. cerevisiae was studied and a maximum ethanol concentration of 4.1 ± 0.2 g L⁻¹ was obtained. Thus, the study holistically addresses some technological challenges in the downstream processing of microalgal biomass for the efficient recovery of lipid and carbohydrate for the production of biofuels in a biorefinery model for sustainable future development.

---

1. Introduction

The continued use of fossil-derived liquid fuels is regarded as unsustainable due to their depleting reserves and associated environmental concerns.¹ Almost 85% of all petroleum-derived fuels are burned in the transportation sector.² Global energy utilization is expected to increase greatly due to extensive anthropogenic activities, coupled with the rising population. Therefore, there is a need for sustainable initiatives that not only lessen the dependence on fossil fuels but also solve the climate crisis. Microalgal feedstock, a credible biofuels source, has drawn much attention as a renewable and sustainable alternative to rapidly depleting fossil fuels. This is because many microalgal species have superior photosynthetic efficiencies and biomass production potentials than terrestrial crops. Microalgae also have environmental advantages, as they can grow in a wide range of pH, nutrient availabilities, temperatures, wastewater, etc., and most importantly microalgae has a short generation cycle, due to which it can be harvested year-round.^3,4 Microalgae derived lipids and carbohydrates could be efficiently used for biofuels production such as biodiesel and bioethanol, and are considered potential liquid biofuels because of their compatibilities with the existing transportation systems and fuel markets.^5–7 In addition to lipids, microalgae stores a significant amount of carbohydrates, primarily composed of polysaccharide, starch and cellulose (with the absence of lignin), which could be considered as a potential source for bioethanol production. Bioethanol from microalgae displays greater sustainability and commercial advantages over conventional lignocellulosic biomass.^8–10 Various species of microalgae have been explored for biofuel production, such as Chlorella sp., Botryococcus sp., Scenedesmus sp., Nannochloropsis sp., Chlorococcum sp., etc.^1,7,10,11 Chlorococcum sp. is one of the economically important microalgae species that is rich in bioactive substances including carotenoids, eicosapentaenoic acid, fucoxanthin, etc. and has been widely used in aquaculture.^10,12,13 Chlorococcum sp. has also shown potential to be a useful biofuel feedstock, as a lipid and carbohydrate source, for biodiesel and bioethanol production.^9,14 Microalgae derived biofuels may prove to be an alternative fuel source that can be developed for the long-term replacement of rapidly depleting fossil fuel. In addition to their potential biofuel applications, microalgae have been applied in CO₂ sequestration, wastewater-bioremediation and the production of many commercially important biochemicals and bioproducts.^7,15

Despite various benefits and the significant progress made in the development of the algal biofuels generation, some technological drawbacks remain when using algal feedstock in the downstream processing for conversion of algal biomass into biofuels, which subsequently diminishes the economics of fuel production.¹⁶ Major practical limitations for the algal biofuel industry have remained in the extraction of biofuels from wet algal biomass. Moreover, most of the reported literature has focused on upstream processes, i.e., algal cultivation technologies.⁴ Typically, biodiesel production from microalgae involves four steps, which are cultivation, harvesting, lipid extraction and transesterification. With the exception of cultivation, the downstream processes constituting the last three steps contribute to approximately 60% of the total biodiesel production cost.^16,17 In general, suspended algae cultivation involves substantial challenges of biomass harvesting or dewatering that can account for nearly 20–30% of the total cost. Moreover, this could vary based on the type of harvesting technology used, the nature or types of microalgae and the density of the microalgal culture.¹⁸ Concentrating methods play an important role to increase the solid concentration of microalgae in suspension and volume reduction, which could contribute to considerable savings in the downstream processes. Typically, concentrating processes involve the use of flocculants (chemical and biological based), centrifugation, gravity sedimentation, or flotation or processes such as auto-flocculation, electro-flocculation or microbial flocculation.^19,20 Flocculation has lower energy requirements than centrifugation, and increases the settling rate by aggregating suspended particles to increase the biomass concentration.²⁰ Subsequently, the pretreatment of the harvested microalgal biomass is essential for the effective extraction of lipids to augment biofuel yields.¹⁵ This pretreatment, besides being quite an energy-intensive step, involves a large amount of chemicals, such as acids, bases, organic solvents and/or physical treatments including cell disruption, autoclaving, sonication, etc., incorporated in either stepwise or simultaneous mode.¹⁵ Lipid recovery is often limited by the low extraction yields from the algae cells.²¹ Even bioethanol production from algal biomass requires a pretreatment step to make the sugars accessible for fermentation.⁵ Finally, in the product conversion step, the extracted microalgal lipid is converted into the final product as fatty acid methyl esters (FAME) or biodiesel. The transesterification of microbial lipids to produce biodiesel is conventionally catalyzed by catalysts, such as acid, alkali, solid catalysts or enzymes. This final stage also accounts for the major cost to the overall biodiesel production process.²²

The feasibility of algae-based biofuel and biochemical production is largely dependent on technologies that have the potential to be integrated into the existing upstream and downstream steps so as to develop a holistic process for biofuel production.^16,17 Otherwise, downstream processing steps (such as harvesting, lipid extraction, and transesterification) when performed independently demand different chemicals and/or equipment, which account for the high processing cost.¹⁵ Additionally, most of the current algal biofuel technologies adopt one strain and one product specific strategy, where mainly the lipid fraction serves as a feedstock for biodiesel production. Nevertheless, the key practical barrier for the algal biofuel industry is achieving a net positive cost and energy balance for the extraction of biofuels from wet algal biomass.⁴ Hence, it is necessary to improve the economics and sustainability of the biofuel production process, through various strategies such as improving the efficiency of downstream processing by integration of various unit operations, combining additional value added co-products with biofuel products, etc. The integration of various biomass components as well as the involvement of technologies in the form of the biorefinery model presents an immense opportunity to advance in the field of microalgal based biofuel production. Moreover, it has been reported that the production of more than one product improves the economic efficiency by 33%, compared to one strain and one product specific processes.²³

Currently, there are a large number of reports on the independent production of bioethanol and biodiesel from microalgae, however there are not many studies that report an integrated process for bioethanol and biodiesel production, except a few studies carried out by Wang et al.,⁸ and Laurens et al.²³ There are barely any reports that have demonstrated a systematic downstream processing of microalgal culture, starting from harvesting to the pretreatment of algal biomass for the effective extraction of lipid and carbohydrate in an integrated approach, and finally their conversion into biofuels, biodiesel and bioethanol. The objective of this work was to present a holistic approach to downstream processing for the conversion of algal biomass into biofuel products such as biodiesel and bioethanol in an integrated mode to develop a microalgal based biorefinery model.

2. Materials and methods

2.1. Microalgal cultivation

The microalgae species used in this study was Chlorococcum infusionum.¹⁴ The microalga was cultivated in an airlift photobioreactor (APBR) with a working volume of 1.5 L (length: 1180 mm, diameter: 75 mm) and supplied with air at a flow rate of 1500 mL min⁻¹ at 30 ± 2 °C under an illumination of 100 μmol photons per m² per s (14 : 10 h light : dark cycle) to produce microalgal biomass. The microalgal slurry was collected from the early stationary phase grown culture for usage in downstream processing for harvesting studies. The composition of the algae biomass has been summarized in Table 1.

Table 1 Composition of Chlorococcum sp.

	Values
Elemental composition
C, %	51.47
H, %	7.91
N, %	6.25
O, %	34.01
Biochemical composition
Total lipid, mg g^−1	250
Total carbohydrate, mg g^−1	247

---

2.2. Harvesting methods and efficiency

Harvesting studies using FeCl₃ and Al₂SO₄ as flocculants on the microalgae culture were carried out in cylindrical glass tubes with 25 mL of culture volume. After addition of the flocculants, the algae suspension was rapidly mixed and left to settle. The doses of flocculants were varied from 10 to 100 mg L⁻¹. In the subsequent experiments, the effect of change in the microalgal culture densities (0.25–1.5 g L⁻¹) was also determined. The harvesting efficiency was calculated following eqn (1)where OD_i and OD_f correspond to the optical density of the sample taken at the initial time zero and at the final time f at a regular interval of time. Optical density was measured at 750 nm using a UV-VIS spectrophotometer (Chemito Instruments-UV 2100).

2.3. Biomass pretreatment for lipid and carbohydrate extraction

2.3.1. Cell disruption. Cell disruption of the algal biomass by various physical and chemical means such as bead-beating, homogenization, sonication, lyophilization, acid treatment and autoclaving for the extraction of lipid was conducted. The lipid was then directly extracted using chloroform and methanol (1 : 2) as extraction solvents in a single batch.

2.3.2. Solvent system for lipids. Various single and binary solvent systems were selected for the extraction of lipid for this study. Lipids were extracted in four different single solvent systems, viz. chloroform, hexane, methanol and ethanol (Merck, India), at room temperature. Binary solvent systems such as chloroform–methanol (in 1 : 2 and 2 : 1 ratio), hexane–methanol (1 : 1), and hexane–ethanol (1 : 1) were also used for lipid extraction. The extracted lipid was filtered and the lipid content was quantified gravimetrically following evaporation of the solvents, and was expressed as % dry cell weight (w/w, dcw).

2.3.3. Chemical pretreatment for sugars. Studies on the chemical pretreatment of microalgae for the extraction of sugars were carried out by investigating different physicochemical parameters such as different chemicals (acid/base), their concentration, temperature and pre-treatment time. The lyophilized and ground microalgae were pretreated with various acid (H₂SO₄ and H₃PO₄) and alkali (NaOH and ammonium) chemicals. Further, the effects of different concentrations of chemicals (NaOH and H₂SO₄) ranging from 0.1 to 0.3 M were evaluated. Next, the effect of varying the temperature from 70 to 120 °C and 120 °C in an autoclave (15 psi) was also tested. Finally, the effect of reaction time, ranging from 15 to 45 min, was evaluated. After hydrolysis, the samples were cooled to room temperature, centrifuged and the supernatant containing reducing sugars was collected and analyzed using the phenol-sulfuric acid and dinitrosalicylic acid (DNS) assay. The sugar yield (%) is defined as follows in eqn (2)

2.3.4. Concomitant pretreatment and extraction of lipid and carbohydrates. The wet biomass generated after harvesting was used for the extraction of lipids and sugars. For combined extraction, the most suitable pretreatment conditions obtained from the previous observations were selected, and it was thus carried out using the bead-beating and acid pretreatments in an autoclave. In the process sequence, first the algal biomass was treated with bead-beating for 15 min followed by acid treatments at 120 °C and 15 psi for 30 min. From the reaction mixture, sugars were obtained from the supernatant, whereas lipid was extracted from the residual biomass using a chloroform–methanol (2 : 1) mixture. Lipid was extracted at the end point of the pretreatment reaction and not after the bead-beating; this was to cut down the downtime required for solvent evaporation.

2.4. Biofuel production

2.4.1. Transesterification for biodiesel. Microalgal lipid extracted from the algal biomass was used for the transesterification study. The conversion of microalgal lipid to fatty acid methyl esters (FAME) was carried out using an acid based transesterification process. The better performing sulfuric acid was used for the standardization of the transesterification process. The critical process parameters such as the molar methanol to oil ratio (25–200), catalyst concentration (0.5–4.5 M), reaction temperature (30–80 °C) and time (3–9 h) were performed sequentially to obtain the optimal transesterification conditions for the maximum conversion of algal lipids into FAME. The transesterification was carried out in airtight capped glass vials (10 cm³, Borosil) and the reaction mixture was kept in a temperature controlled incubator. The percentage FAME conversion was calculated using eqn (3).

2.4.2. Ethanol fermentation. The suspension remaining after pretreatment was centrifuged, neutralized with NaOH (to nearly pH 6) and the liquor containing the sugar fraction was concentrated suitably to test its fermentability using Saccharomyces cerevisiae. Yeast was grown up to the mid-log phase in YPD (0.3% yeast extract, 0.3% peptone, and 2% glucose) medium at 30 °C, 150 rpm for 48 h. The growth of yeast was monitored by measuring optical density at 600 nm using a spectrophotometer. For the fermentation experiment, algal hydrolysate was used instead of glucose in the YPD medium, inoculated with 5% (v/v) seed culture of yeast and grown anaerobically at 30 °C, 150 rpm for 72 h. Periodic measurements of the concentrations of cell density, ethanol and sugars were carried out. All the experiments were carried out in triplicate, and the average value with standard deviation (SD) was reported.

2.5. Analytical methods for biodiesel and bioethanol

The total lipids were determined by extracting the algae with chloroform–methanol and was quantified gravimetrically as percent lipid on a dry weight basis.¹⁴ The phenol–sulfuric acid method was applied to quantify the amount of sugars; the reaction mixture was mixed with 1 mL of 5% (w/v) phenol solution, 1 mL microalgae solution and 2 mL of concentrated sulfuric acid for 10–20 min. The absorbance of the characteristic yellow-orange color was measured under a wavelength of 490 nm.²⁴

2.5.1. FAME conversion. High performance thin layer chromatography (HPTLC) was used to analyze the transesterified samples at room temperature to calculate the percentage FAME conversion and was also corroborated with gas chromatography (GC). Two microlitres of sample mixed with hexane was loaded onto a TLC silica gel plate (20 × 20 cm, silica gel 60 F254, MERCK, Germany). The mobile phase used was a mixture of hexane, ethyl acetate and acetic acid (90 : 10 : 1). The TLC plate was air dried and then scanned through HPTLC scanner 3 (CAMAG, Switzerland) at a 208 nm wavelength. A methyl palmitate standard was run in a lane to compare the position of FAME on the plate. The percentage conversion was calculated using eqn (3).²⁵where A_MG, A_DG, A_TG and A_FAME correspond to the areas under the peaks of monoacylglycerols (MAG), diacylglycerols (DAG), triacyglycerols (TAG) and FAME respectively, as obtained from the HPTLC chromatogram (Fig. S2†). Experiments were carried out in triplicate and results are shown with standard error bars.

2.5.2. Bioethanol. The ethanol concentration was analyzed using a gas chromatograph (GC) (Clarus 500, PerkinElmer) equipped with a PLOT-Q capillary column (30 m length and inner diameter of 0.32 mm) and a flame ion detector (FID). The injector, detector and oven temperatures were maintained at 150 °C, 200 °C and 50–120 °C, respectively. Nitrogen gas was used as the carrier gas. The bioethanol concentration was quantified using a calibration curve prepared by injecting different concentrations of an ethanol standard (100–500 ppm).

3. Results and discussion

3.1. Downstream process overview

The present investigation highlights the downstream processing steps involved after microalgal biomass cultivation to obtain lipids and carbohydrates for biofuel production. The downstream processing steps are divided into three stages: (i) harvesting of algal culture or slurry through a flocculation method to obtain concentrated biomass, (ii) algal biomass pretreatment for the extraction of microalgal lipid and carbohydrate using various methods including cell disruption, solvent extraction and chemical hydrolysis, and finally (iii) conversion of the extracted lipids and sugars into biodiesel and bioethanol via transesterification and fermentation, respectively. Fig. 1 shows a flow scheme depicting the different steps carried out in this study. This study also demonstrated an integrated approach of simultaneous extraction of lipids and carbohydrates from wet biomass for the production of biodiesel and bioethanol in a biorefinery model.

Fig. 1 Process scheme of combined biodiesel and bioethanol production using microalgal culture.

3.2. Studies on harvesting by flocculation

This stage corresponds to the first four boxes to the left in Fig. 1. This study was conducted to maximize harvesting efficiency by using a minimal dosage of flocculant. The self-flocculating ability of Chlorococcum sp. was used as control in order to assess and compare the harvesting efficiency with different flocculants such as ferric chloride (FeCl₃·6H₂O) and alum (Al₂(SO₄)₃·12H₂O) (Fig. 2a). For a preliminary screening experiment, the initial and final OD reading of the culture samples at times of zero min and 30 min were noted. It was observed that the harvesting efficiency of Chlorococcum sp. culture was significantly influenced by the change in FeCl₃ concentration (Fig. 2a). A maximum microalgal flocculation efficiency of 85.9 ± 3.5% was obtained with an FeCl₃ dosage of 100 mg L⁻¹. These results were in good agreement with the reported literature where the use of FeCl₃ at 200 mg L⁻¹ at low pH as a coagulant was found to be effective for Chlorella sp.¹⁵

Fig. 2 Harvesting efficiencies of Chlorococcum sp. using (a) alum and FeCl₃ at varied concentrations (0–100 mg L⁻¹) and (b) time profile with the change in biomass density (0.25–1.5 g L⁻¹) at pH 7.8 with FeCl₃ (100 mg L⁻¹) and without FeCl₃ (control).

The various properties of microalgae that affect their separation from an aqueous medium include size, shape, surface charge, specific gravity, motility, growth phase, presence of appendages and extracellular organic matter (EOM) composition and concentration.²⁶ Additionally, algal harvesting is greatly influenced by the properties of the culture medium, including cell concentration, pH and ionic strength. Though various mechanisms of flocculation have been extensively explored, flocculation by the use of multivalent metal cations has been reported to be simple and less energy intensive. It was found that such metal ions in the growth medium were hydrolyzed to form positive precipitates, which coagulate negatively charged microalgal cells by sweeping flocculation and charge neutralization.²⁷ Flocculation can also occur due to a change in the physical–chemical properties of the microalgal cells i.e. their surface charge. However, literature reports also suggest that polysaccharides released by many microalgae species during growth aid in the flocculation by a bridging mechanism.²⁷ In the current study, the staining of cells with Alcian blue dye revealed the binding of EPS to the cells (Fig. S1†) which promoted the self-flocculation of cells. Flocculation is achieved when there is a coalescence of finely divided particles in suspension which occurs due to charge neutralization and/or polysaccharide bridging, forming larger aggregates followed by the agglomeration of these into larger flocs that settle to the bottom of the vessel, leaving a clear supernatant.

Next, we explored the influence of different algal cell densities in the culture medium and found that with the increase in biomass density (0.25–1.5 g L⁻¹) the harvesting efficiency was also enhanced. Fig. 2b shows the time profile with the change in biomass density (0.25–1.5 g L⁻¹) using FeCl₃ (100 mg L⁻¹) at pH 7.8, whereas the control set was carried out in the absence of FeCl₃ at pH 7.8. The maximum harvesting efficiency of 90.6 ± 2.8% was achieved with 30 min of flocculation reaction using 100 mg L⁻¹ FeCl₃ with a biomass culture density of 1.5 g L⁻¹. The literature reports also suggest that ferric chloride was the most suitable flocculant for harvesting, as it showed no deleterious effects on algal growth and the least influence on the cell physiological activity and cell components. Most importantly, it is reported that the culture medium can be reprocessed after performing ferric chloride based harvesting; on the contrary, low concentrations (<5 ppm) of residual alum have shown an inhibitory effect on microalgal growth.²⁸

3.3. Biomass pretreatment for the extraction of lipids and carbohydrates

Pretreatment is the following step after the dewatering and harvesting of microalgal biomass from the culture slurry. Efficient pretreatment of biomass feedstock is often recommended to achieve high biofuel yields. To date the pretreatment of biomass is considered one of the most important and expensive steps.²⁹ Pretreatment of microalgal biomass involves processes such as cell disruption, solvent extraction and chemical treatment of microalgal biomass to enable maximum recovery of the metabolites (lipid and carbohydrate) of interest. The effects of various physical and chemical pretreatment methods on the algal biomass were evaluated with respect to the extraction yields of lipid and carbohydrate, carried out in separate and simultaneous mode. In Fig. 1, this section corresponds to the middle three boxes. The center box represents cell disruption, which is also the preliminary step in the pretreatment processes for the recovery of lipids and carbohydrates.

3.3.1. Cell disruption. Various cell disruption methods were employed to improve the mass transfer and thus increase the extraction efficiency of lipid and carbohydrate. Typically, the lipid content of Chlorococcum sp. was found to average 25% (dcw, w/w) when grown under normal conditions, whereas a lipid content as high as 45% (dcw, w/w) was obtained under nitrogen limiting conditions (data not shown). Cell disruption assisted by physical and chemical means was carried out through bead-beating, homogenization, sonication, lyophilization, acid treatment and autoclaving, and the lipid was extracted using chloroform/methanol (1 : 2, v/v) as the extraction solvents (Fig. 3a). The maximum lipid recovery of 79.5 ± 3.2% was obtained when the biomass was pretreated with bead-beating. The next greatest lipid recovery values of 73.6 ± 2.5% and 70.4 ± 3.1% were obtained using autoclaving and homogenization, respectively, although the difference was rather small to bead-beating, whereas cell disruption without any pretreatment as a negative control resulted in a lipid recovery of merely 12.1 ± 1.8% (Fig. 3a). Typically, cell disruption not only improves access to stored lipids but also releases protein and carbohydrates.²¹ Subsequently, the time duration of bead-beating of algal biomass for lipid recovery was varied from 5 to 25 min, and the time length of 15 min was noted as optimal (85.5 ± 2.4%) (data not shown). While considering the one time extraction, a similar observation has been reported where bead-beating treatment resulted in efficient extraction of microalgal lipid.³⁰ The best known mechanical cell disruption techniques are reported to be bead milling and high speed homogenization, where the mechanism of solid–liquid interfacial shear forces results in high cell disruption efficiency.³¹

Fig. 3 Lipid extraction from Chlorococcum sp. biomass. (a) Effects of various cell disruption methods; (b) effect of various single and binary solvent systems on lipid recovery from biomass.

3.3.2. Lipid extraction using various solvent systems. Fig. 3b shows the extracted lipid recovery from microalgae using various single and binary solvent systems at room temperature. Among the single solvent systems, the lipid recovery was recorded to be 52.5 ± 2.5% (w/w) in chloroform, whereas among the binary solvents, chloroform/methanol in a 2 : 1 ratio resulted in the maximum lipid recovery of 96.2 ± 2.9% (w/w). A similar observation has been reported using various microalgal species where chloroform/methanol is best suited for the extraction of lipid.³² The lipid extraction with the hexane and hexane/methanol solvents was lower as hexane, being a non-polar solvent, mainly extracts neutral lipids.³³ Fig. 3b shows the comparative analysis of the extraction efficiency of different solvent systems.

When a microalgal cell is exposed to a non-polar organic solvent, such as hexane and chloroform, the solvent penetrates the cell membrane and interacts with neutral lipids (i.e., triglycerides) present in the cytoplasm. The solvent interacts with lipids because of van der Waals forces to form an organic solvent–neutral lipid complex. This complex, driven by a concentration gradient, diffuses across the cell membrane and the static organic solvent film surrounding the cell, enabling organic solvent to enter the cells.³⁴ As a result, the neutral lipids are extracted from the cells and remain dissolved in the non-polar organic solvent. Some neutral lipids are found in the cytoplasm as complexes with polar lipids (i.e., phospholipids, glycolipids, etc.). These complexes are strongly linked via hydrogen bonds to proteins in the cell membrane. The van der Waals interactions formed between non-polar organic solvents and neutral lipids are inadequate to disrupt these membrane based lipid–protein associations, making it necessary to use methanol or ethanol as a polar organic solvent. Mixtures of chloroform/methanol are used to ensure the complete extraction of the total lipids including the neutral lipids present in the form of free globules and in the form of complex associated proteins. Thus, these mixtures extract both neutral and polar lipids by chloroform and methanol, respectively, and are considered efficient in the extraction of total lipids.³⁴

3.3.3. Sugar extraction via chemical pretreatment. We explored a mild chemical pretreatment method for the extraction and conversion of the algal carbohydrates into fermentable sugars (Fig. 4). In this study, various acid (H₂SO₄ and H₃PO₄) and alkali (NaOH and ammonium) chemicals were used for the pretreatment of microalgal biomass (Fig. 4a). The sugar recovery was most efficient with NaOH and H₂SO₄. Thus, in the subsequent experiment, different concentrations of NaOH and H₂SO₄ were studied with the microalgal biomass (Fig. 4b). The higher sugar recovery in NaOH relative to H₂SO₄ could be because NaOH is a known as an effective agent for lysing entire microalgae cells, especially used for protein extraction under mild conditions.¹¹ Not only does it extract carbohydrates embedded both within the cell itself and in the cell wall, but it also extracts glycoproteins, contrastingly, sulfuric acid treatment tends to primarily extract carbohydrates. We next explored the effect of the operating temperatures and reaction time on microalgal hydrolysis with both acid and alkali pretreatment. The release of sugars was most effective when Chlorococcum sp. was pretreated with sulfuric acid at higher temperature (Fig. 4c). This indicates that an increase in temperature favors the activity of the acid. Typically, there is a trade-off between acid concentration and temperature; the more dilute acid requires higher temperatures, and vice versa, and the treatment with higher temperatures also shortened the residence time of the process.³⁵ While sulfuric acid is potent and quick enough to act upon these complex sugars at elevated temperatures, it is possible that sodium hydroxide acts more slowly in comparison, leading to the direct solubilization of complex microalgal carbohydrates. Such an effect has been seen in the literature regarding sulfuric acid at temperatures above 160 °C.¹⁰ The literature also indicates that alkaline pretreatments tend to be less effective than acid ones, which could explain the disparity between the two treatments.³⁶ The maximum recovery of 89.6 ± 3.1% sugar yield was obtained when the biomass was acid pretreated at the optimal conditions of 121 °C (15 psi) in an autoclave under mildly acidic conditions (0.3 N H₂SO₄ concentration) for 30 min (Fig. 4d). Pretreatment of the algae by acid hydrolysis is a potentially effective and low cost method.⁵ The polysaccharides like celluloses and starches are solubilized under acidic conditions, and the combination of high temperature under pressure increases the rate of their hydrolysis into monosaccharides.³⁵ A small portion of algal carbohydrate remained at the end point of the reaction, suggesting that algal starch might be recalcitrant toward mild acid pretreatment.³⁷

Fig. 4 The yield of sugar release under different conditions of pre-treatment. (a) Effect of various chemical pretreatments, (b) effect of chemical concentration, (c) effect of temperature and (d) effect of reaction time.

The carbohydrate content in Chlorococcum sp. represented nearly 24.7 ± 0.6% (w/w), which comprised mostly glucose; other components such as mannose, xylose and galactose were also found. Sugar composition examined by HPLC showed peak overlap, and it could not be ruled out that these overlapping peaks constituted a heterogeneous mixture of sugars. A region of overlapping peaks due to severe co-elution may represent some combination of mannose, galactose and xylose.^23,37 Xylose and glucose were confirmed separately using GOD-POD assay and Bial’s test (orcinol method). The remaining sugars could be substantiated as mannose and galactose, as reported by Harun et al. in Chlorococcum sp.¹⁰

3.4. Concomitant extractions of lipid and carbohydrate

In this section, both stepwise and concomitant extraction of carbohydrate and lipid were carried out using the wet biomass (Table 2). The microalgal biomass of Chlorococcum sp. was initially pretreated with bead-beating followed by autoclaving under acidic conditions, then from the reaction mixture the sugars were obtained from the supernatant whereas lipid was extracted from the residual biomass. During the simultaneous extraction process, maximum sugar and lipid recoveries of 86.5 ± 2.6% and 74.1 ± 1.8%, respectively, were achieved (Table 2). The favorable process conditions for the extractions were achieved with initial pretreatment with bead-beating for 15 min followed by autoclaving (121 °C, 15 psi) in mild acidic condition (0.3 N H₂SO₄) for 30 min. Cell disruption increases mass transfer to support the extraction of both sugars and lipids.³⁸ It is well documented that cell disruption not only releases the stored lipids but also protein and carbohydrates.²¹ In the concomitant extraction process, the recovery of sugar was found to be excellent after acid pretreatment, however some extraction loss of lipid was observed, which might be due to the hydrolysis of lipid or the single solvent extraction step (one time) at the end point of the process.³³ Lipid extracted after hydrolysis is reported to have decreased phospholipid (PL) content, however higher free fatty acid (FFA) content, which could be totally converted to FAME and most of TAG, DAG and MAG were also transformed into FAME. In addition, the conversion rate of TAGs in lipids was found to be higher than that before hydrolysis.⁸

Table 2 Lipid and carbohydrate extraction strategy in two different modes

Strategy	Pretreatment methods		Results
	Stage I	Stage II
Stepwise extraction	(1) Bead-beater assisted cell disruption	Acid treatment at 121 °C in autoclave	Sugar yield = 89.6 ± 3.1% (w/w)
	(2) Chloroform/methanol solvent system		Lipid yield = 96.2 ± 2.9%(w/w)
Simultaneous extraction	(1) Bead-beater assisted cell disruption	Recovery of sugars from supernatant and lipids from cell pellet using chloroform/methanol	Sugar yield = 86.5 ± 2.6% (w/w)
	(2) Acid treatment at 121 °C in autoclave		Lipid yield = 74.1 ± 1.8% (w/w)

---

Mild treatment with mechanical and non-mechanical methods for short durations could result in optimal results in addition to lower energy consumption. Recent studies suggest that for the industrial scale mechanical methods are ideal, whereas non-mechanical methods have lower energy needs and may provide uniform cell disruption with higher selectivity.³¹ A similar observation was reported where the efficiency of acid-catalyzed hot-water extraction of lipids from C. vulgaris was found to be around 85–90% at a 1% sulfuric acid concentration incubated at 120 °C for 60 min.³³ Temperature is known to be an important parameter in pretreatment of biomass; its effect was tested by varying temperature from 25–120 °C.³⁹ At high temperatures, the cell lyses and the simultaneous extraction of metabolites (lipid and carbohydrate) was indeed far more effective, and the additional pressure caused by the higher temperature in autoclaving than the normal boiling point might have a positive effect on disrupting cells as well.³⁹ Moreover the very addition of acid in this process assists especially in the hydrolysis of starch while extracting lipid simultaneously. The remaining biomass could be effectively used as animal feed or for anaerobic digestion to generate biogas.

3.5. Biofuels production

This stage corresponds to the last two boxes to the right in Fig. 1. The final step in downstream processing was the conversion of the extracted lipid and carbohydrate after pretreatment into the products, biodiesel and bioethanol. Typically, lipids are converted into fatty acid methyl esters (FAME) by transesterification, in which chemicals or enzymes can be applied as a catalyst to convert triglycerides into esters. The carbohydrates that are hydrolyzed or broken down into monomeric forms undergo anaerobic fermentation to produce bioethanol.

3.5.1. Transesterification for biodiesel production. Fig. 5 shows the effect of various process parameters of transesterification reaction for the conversion of algal oil into fatty acid methyl esters (FAME). Generally, microbially derived lipid has a high concentration of free fatty acids.^32,40 Therefore acid-catalyst based transesterification reactions are applied to algal lipid to produce FAME that can be used as a biodiesel.⁴⁰ Operating conditions such as solvent to oil ratio, acid concentration, temperature and time, were standardized using Chlorococcum sp. derived lipid. The sulfuric acid identified as a suitable catalyst was used for the transesterification process. The catalyst amount was varied from 0.5–4.5 M, and showed profound effects on conversion yields; the conversion increased exponentially as the catalyst amount increased, up to 3.5 M. Higher catalyst concentration increased the contact opportunity of the catalyst and the reactant, which directly influenced the reaction speed and the conversion.⁴¹ Similarly, a molar ratio higher than the stoichiometric molar ratio of methanol was required to shift the equilibrium forward toward the formation of FAME. Temperature clearly influenced the FAME conversion, but the conversion remained constant beyond 70 °C. A maximum FAME conversion yield of 95.2 ± 2.8% was achieved, with the operating reaction conditions of a molar ratio of 100 of methanol to oil and 3.5 M acid concentration, conducted at 70 °C for a reaction time of 7 h (Fig. 5) (Fig. S2d†). More than 90% of the conversion occurred within 5 h of incubation time, and after 7 h the conversion remained nearly constant at almost 95% because of a near equilibrium conversion.⁴¹ These results also indicate that saponifiable lipids other than triglycerides, such as PL and glycolipids are transformed into FAME by this method. Moreover lipid extracted after hydrolysis is reported to have decreased PL content, and most of TAG, DAG, MAG and FFA are also transformed into FAME with high conversion rates of nearly 98% via transesterification.⁸ The results were in agreement with the literature, where 4.5 M HCl was favorable for FAME conversion.³²

Fig. 5 Effect of various critical parameters on conversion of algal lipid into FAME using transesterification process; (a) molar ratio of methanol to oil (b) acid concentration (c) temperature and (d) reaction time.

3.5.2. Fermentative production of bioethanol. After acid pretreatment, the fermentability of microalgal sugars to bioethanol using S. cerevisiae was investigated; an initial sugar concentration of 20 g L⁻¹ was used. Fig. 6 shows the time course profile of ethanol concentration and residual sugar during the bioethanol fermentation process. In the fermentation process, almost 90% of sugar was consumed within 72 h. Nonetheless, increase in OD slowed after 60 h, perhaps as a result of physiological changes in the cells and/or assimilation of a secondary substrate.³⁷ Ethanol concentrations peaked at 48 h and stayed almost constant to 72 h. A maximum ethanol yield of 4.1 ± 0.25 g L⁻¹ was observed. The ethanol yield percentage was 40% of the theoretical yield; this yield could be increased by using a more competent strain of S. cerevisiae. The result obtained compared favorably with published data where the ethanol yield ranged from 2 to 5.6 g L⁻¹ by S. cerevisiae in the fermentation of microalgal sugar.⁴²

Fig. 6 Time course profiles of bioethanol production and total sugar depletion via fermentation of algal sugar by S. cerevisiae.

3.5.3. Analysis of literature data on the economics of algal biofuels. Techno-economic analyses (TEA) of various algal biofuel processes have been reported. However literature reports have shown large variations in the calculated fuel cost with ±30% accuracy.⁴³ Depending on the process design and raw material inputs, the biofuel cost was reported to vary from a low value of $1.65 gal⁻¹ to a higher value of $33.16 gal⁻¹.^44,45 Significant reduction in variability within a harmonized range from $11.68–$14.31 gal⁻¹ was achieved through meta-analysis.⁴⁶ When TEA was carried out based on comprehensive mass balances, the cost of biodiesel production was determined to be $9.84 gal⁻¹ for open algal ponds and $20.53 gal⁻¹ for closed photobioreactors.⁴⁷ Another report on detailed techno-economic analysis of optimized production processes indicated improved cost estimations with the final costs of biodiesel from $1.59–3.67 gal⁻¹.⁴³

Though the technical feasibility of microalgal biodiesel has been established, economic viability will ultimately depend on new technological breakthroughs and of course, on the cost of crude oil.⁴⁸ An integrated process in a biorefinery model that generates more than one value-added product from microalgal biomass feedstock can considerably reduce the cost of the overall process and make the process profitable and feasible.⁴⁹ However, there are hardly any reports on techno-economic analysis of biofuel production in a biorefinery. Harun et al. reported substantial reduction in the cost of biodiesel production by nearly 33% in a biorefinery producing both biodiesel and methane.⁴⁸ A similar study, wherein the carbohydrate and lipid based combined biofuel yields showed cost cutting by up to 33% when compared to a lipids-only process, proved the necessity and cost-effectiveness of a biorefinery.²³

4. Conclusions

This study convincingly demonstrated an integrated approach in downstream processing for concomitant extraction of lipids and carbohydrates for the development of a microalgal based biofuel biorefinery to obtain both biodiesel and bioethanol as potential liquid fuels. A series of harvesting and pretreatment experiments confirmed the feasibility of the key process steps in the proposed holistic approach. This experimental work confirmed the ability to use wet algal biomass for pretreatment to achieve encouraging biofuel yields. The process resolves the current major limitations to the economic and energetic feasibility of algal biofuels by integrating some of the unit operations involved in pretreatment of algal biomass for simultaneous extraction of lipids and sugars. Thus, this holistic approach is expected to provide operational flexibility and feasibility by integrating some of the steps in downstream processes for valorizing microalgal biomass components. Moreover, algae can also be grown in wastewater and next to power-plant smokestacks, where they can digest the pollutants and deliver the feedstock for biofuels. The present investigation presented the potential for operational simplicity in downstream processing especially from the harvesting of algal cells to the extraction of potential microalgal metabolites for their conversion into biofuels to promote commercial scale production. This synergetic approach to biofuel production could offer a sustainable alternative to current methods in catering for the energy demand and replacing petroleum-based fuels for the sustainable development of a bio-based economy in the near future.

Acknowledgements

The authors gratefully acknowledge Department of Biotechnology (DBT), Govt. of India for fellowship, IIT Kharagpur, and Department of Science & Technology (DST), Govt. of India, for the financial support for the project (No. DST/IS-STAC/CO2-SR-160/13(G); Date: 08.07.2013). AK thankfully acknowledges Prabuddha Dey, Atrayee Chattopadhyay and Shanti Kiran for their technical assistance.

References

1. A. Karemore and R. Sen, RSC Adv., 2015, 5, 70929–70938.
2. E. Kwon, H. Yi and Y. J. Jeon, Environ. Sci. Technol., 2013, 47, 2817–2822.
3. Y. Peralta-Ruiz, A. D. González-Delgado and V. Kafarov, Appl. Energy, 2013, 101, 226–236.
4. Y. Zhou, L. Schideman, G. Yu and Y. Zhang, Energy Environ. Sci., 2013, 6, 3765.
5. Y. A. Castro, J. T. Ellis, C. D. Miller and R. C. Sims, Appl. Energy, 2015, 140, 14–19.
6. L. Lin, Z. Cunshan, S. Vittayapadung, S. Xiangqian and D. Mingdong, Appl. Energy, 2011, 88, 1020–1031.
7. Y. Chisti, Biotechnol. Adv., 2007, 25, 294–306.
8. H. Wang, C. Ji, S. Bi, P. Zhou, L. Chen and T. Liu, Bioresour. Technol., 2014, 172, 169–173.
9. R. Harun, M. K. Danquah and G. M. Forde, J. Chem. Technol. Biotechnol., 2010, 85, 199–203.
10. R. Harun and M. K. Danquah, Appl. Energy, 2011, 46, 304–309.
11. R. Harun, W. S. Y. Jason, T. Cherrington and M. K. Danquah, Appl. Energy, 2011, 88, 3464–3467.
12. D. H. Zhang and Y. K. Lee, J. Appl. Phycol., 1997, 9, 459–463.
13. D. M. Mahapatra and T. V. Ramachandra, Curr. Sci., 2013, 105, 47–55.
14. A. Karemore, R. Pal and R. Sen, Algal Res., 2013, 2, 113–121.
15. Y. H. Seo, M. Sung, B. Kim, Y.-K. Oh, D. Y. Kim and J.-I. Han, Bioresour. Technol., 2015, 181, 143–147.
16. G. W. Roberts, M. O. P. Fortier, B. S. M. Sturm and S. M. Stagg-Williams, Energy Fuels, 2013, 27, 857–867.
17. J. Kim, G. Yoo, H. Lee, J. Lim, K. Kim, C. W. Kim, M. S. Park and J. W. Yang, Biotechnol. Adv., 2013, 31, 862–876.
18. L. B. Christenson and R. C. Sims, Biotechnol. Bioeng., 2012, 109, 1674–1684.
19. S. Salim, R. Bosma, M. H. Vermuë and R. H. Wijffels, J. Appl. Phycol., 2011, 23, 849–855.
20. A. K. Lee, D. M. Lewis and P. J. Ashman, Appl. Energy, 2013, 108, 45–53.
21. X. Bai, P. M. Schenk, Z. Yuan, P. A. Lant and S. Pratt, Appl. Energy, 2015, 154, 183–189.
22. D. T. Tran, K. L. Yeh, C. L. Chen and J. S. Chang, Bioresour. Technol., 2012, 108, 119–127.
23. L. M. L. Laurens, N. Nagle, R. Davis, N. Sweeney, S. van Wychen, A. Lowell and P. T. Pienkos, Green Chem., 2015, 17, 1145–1158.
24. M. DuBois, K. A. Gilles, J. K. Hamilton, P. A. Rebers and F. Smith, Anal. Chem., 1956, 28, 350–356.
25. S. Chattopadhyay, A. Karemore, S. Das, A. Deysarkar and R. Sen, Appl. Energy, 2011, 88, 1251–1256.
26. I. Udom, B. H. Zaribaf, T. Halfhide, B. Gillie, O. Dalrymple, Q. Zhang and S. J. Ergas, Bioresour. Technol., 2013, 139, 101–106.
27. J. Liu, Y. Zhu, Y. Tao, Y. Zhang, A. Li, T. Li, M. Sang and C. Zhang, Biotechnol. Biofuels, 2013, 6, 98.
28. P. Zhao, Z. Zang, X. Xie, A. Huang and G. Wang, Process Biochem., 2014, 49, 681–687.
29. R. Harun and M. K. Danquah, Chem. Eng. J., 2011, 168, 1079–1084.
30. E. Ryckebosch, K. Muylaert and I. Foubert, J. Am. Oil Chem. Soc., 2012, 89, 189–198.
31. E. Günerken, E. D’Hondt, M. H. M. Eppink, L. Garcia-Gonzalez, K. Elst and R. H. Wijffels, Biotechnol. Adv., 2015, 33, 243–260.
32. S. Mandal, R. Patnaik, A. K. Singh and N. Mallick, Environ. Technol., 2013, 34, 2009–2018.
33. J. Y. Park, Y. K. Oh, J. S. Lee, K. Lee, M. J. Jeong and S. A. Choi, Bioresour. Technol., 2014, 153, 408–412.
34. R. R. Dos Santos, D. M. Moreira, C. N. Kunigami, D. A. G. Aranda and C. M. L. L. Teixeira, Ultrason. Sonochem., 2014, 22, 95–99.
35. M. Thu, M. Thu, S. P. Choi, S. P. Choi, J. Lee, J. Lee, J. H. Lee, J. H. Lee, S. J. Sim and S. J. Sim, J. Microbiol., 2009, 19, 161–166.
36. P. Kumar, P. Kumar, D. M. Barrett, D. M. Barrett, M. J. Delwiche, M. J. Delwiche, P. Stroeve and P. Stroeve, Ind. Eng. Chem. Res., 2009, 48, 3713–3729.
37. M. J. Scholz, M. R. Riley and J. L. Cuello, Biomass Bioenergy, 2013, 48, 59–65.
38. C. C. Fu, T. C. Hung, J. Y. Chen, C. H. Su and W. T. Wu, Bioresour. Technol., 2010, 101, 8750–8754.
39. D.-Y. Kim, Y.-K. Oh, J.-Y. Park, B. Kim, S.-A. Choi and J.-I. Han, Bioresour. Technol., 2015, 191, 469–474.
40. G. Vicente, L. F. Bautista, F. J. Gutiérrez, R. Rodríguez, V. Martínez, R. A. Rodríguez-Frómeta, R. M. Ruiz-Vázquez, S. Torres-Martínez and V. Garre, Energy Fuels, 2010, 24, 3173–3178.
41. Y.-M. Dai, K.-T. Chen and C.-C. Chen, Chem. Eng. J., 2014, 250, 267–273.
42. H. Guo, M. Daroch, L. Liu, G. Qiu, S. Geng and G. Wang, Bioresour. Technol., 2013, 127, 422–428.
43. S. Nagarajan, S. K. Chou, S. Cao, C. Wu and Z. Zhou, Bioresour. Technol., 2013, 145, 150–156.
44. J. R. Benemann and W. J. Oswald, Systems and economic analysis of microalgae ponds for conversion of CO{sub 2} to biomass, Final report, Pittsburgh, PA and Morgantown, WV, 1996.
45. J. W. Richardson, M. D. Johnson and J. L. Outlaw, Algal Res., 2012, 1, 93–100.
46. J. C. Quinn and R. Davis, Bioresour. Technol., 2015, 184, 444–452.
47. R. Davis, A. Aden and P. T. Pienkos, Appl. Energy, 2011, 88, 3524–3531.
48. R. Harun, M. Davidson, M. Doyle, R. Gopiraj, M. Danquah and G. Forde, Biomass Bioenergy, 2011, 35, 741–747.
49. T. L. Da Silva, L. Gouveia and A. Reis, Appl. Microbiol. Biotechnol., 2014, 98, 1043–1053.

---

Footnote

† Electronic supplementary information (ESI) available. See DOI: 10.1039/c6ra01477a

---