Defatted algal biomass as feedstock for short chain carboxylic acids and biohydrogen production in the biorefinery format

Accepted Manuscript Defatted Algal Biomass as Feedstock for Short Chain Carboxylic Acids and Biohydrogen Production in the Biorefinery Format Naresh Kumar, Booki Min, S. Venkata Mohan PII: DOI: Reference:

S0960-8524(18)31163-5 https://doi.org/10.1016/j.biortech.2018.08.059 BITE 20342

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Bioresource Technology

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7 June 2018 15 August 2018 16 August 2018

Please cite this article as: Kumar, N., Min, B., Venkata Mohan, S., Defatted Algal Biomass as Feedstock for Short Chain Carboxylic Acids and Biohydrogen Production in the Biorefinery Format, Bioresource Technology (2018), doi: https://doi.org/10.1016/j.biortech.2018.08.059

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Defatted Algal Biomass as Feedstock for Short Chain Carboxylic Acids and Biohydrogen Production in the Biorefinery Format A. Naresh Kumar a,b, Booki Min c S. Venkata Mohan a,b,c * a Bioengineering and Environmental Sciences Lab, CEEFF CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Hyderabad- 500 007, India. b Academy of Scientific and Innovative Research (AcSIR), c Department of Environmental Science and Engineering, Kyung Hee University, Seocheon- dong, Yongin-si, Gyeonggi-do 446-701, Republic of Korea * E-mail: [email protected], [email protected], Tel: +9140-27191765 Abstract The objective of the study was to evaluate the potential application of defatted algal biomass (DAB) as a resource for biobased product synthesis in the biorefinery framework. Acidcatalyzed pretreatment of DAB resulted in higher reducing sugars (RS) solubilization (0.26 g RS/g DAB) than corresponding base method (0.19 g RS/g DAB). Subsequently, resulting RS were acidogenically fermented for the production of Bio-H2 and short chain carboxylic acids (SCA) at varying redox conditions (pH: 6, 7 and 10). Biosystem with pH-6 resulted in higher SCA (0.54 g SCA/g RS) and Bio-H2 production (0.83 l) followed by pH-10 (0.43 g SCA/g RS, 0.71 l) and pH-7 (0.27 g SCA/g RS, 0.48 l). Higher SCA production in pH-6 system resulted in maximum acidification (23%). Algal biomass majorly derived from CO2 and its residues after lipids extraction accounted as major feedstock for acidogenic product synthesis, thus offers sustainability to algal refineries on its entirity use.

Keywords: Algal Biomass, Short chain carboxylic Acids, Reducing Sugars, Acidification, Fermentation, Acetic Acid

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1. Introduction Fossil based resources are finite and also emits the greenhouse gases when utilized, which directly associates with global warming (Matsakas et al., 2017; Show et al., 2018). Shift towards sustainable sources of energy and material is in much focus. Especially cultivation of algae hails a great promise for renewable material, chemical and fuels (Singh et al., 2011). Algae during autotrophic growth sequester carbon dioxide and store carbon in the form of carbohydrate (4050%), lipids (20-30%) and proteins (15-20%) (Khan et al., 2018). Production of 100 g of algal biomass consumes around 180 g of carbon dioxide (Laurens et al., 2015). Despite of its sustainable potential, large-scale cultivation of algae for bulk production is hampered by energy requirements, operational and capital costs (Laurens et al., 2015, Venkata Mohan et al., 2015). Studies were majorly focused on lipid-only pathway by leaving the oil extracted microalgae biomass as waste (Gonzalez et al., 2018). The leftover defatted (lipid-extracted) algal biomass (DAB) residue contains good amount of usable carbon. Its utilization as a resource in biological process accounts an additional benefits to the algal refineries (Chen et al., 2013, Wijffels et al., 2010). Rigid cell wall of microalgae protects its biodegradation and thus lowers the process net energetic yields. Pretreatment of DAB is prerequisite to convert the polysaccharides (starch and cellulose) into monomers prior to using it as feed stock (Harun and Danquah, 2011, Yang et al., 2011). These simplified monomers eliminate the process of hydrolysis in the fermentation and thus accelerates product yields. In this realm, the study was designed and evaluated for the production of various bio-based products using DAB a main feedstock through acidogenic process in the format of biorefinery (Subhash and Venkata Mohan, 2014). The major bio-based products anticipated in this communication are biohydrogen (bio-H2) and short chain carboxylic acids (SCA). Hydrogen is considered as ecofriendly energy carrier and it’s also being used as a drop-in fuel in oil refineries to upgrade low-grade crude and to remove the problematic sulfur (Cao et al., 2018). Biological hydrogen production offers a possibility of being renewable avenue and carbon neutral sustainable technology (Venkata Mohan et al., 2008, 2016, Moscoviz et al., 2018; Mota et al., 2018). SCA are the reduced organic metabolites accumulated during the fermentative substrate biotransformation under oxygen-depleted conditions (Dahiya et al., 2015, Liu et al., 2016). Additionally, SCA are considered as platform chemicals and act as building blocks for various high value products synthesis like alcohols, medium chain fatty acids, biopolymers and biodiesel 2

(Venkata Mohan et al., 2016; Lee et al., 2014). Reversibly, SCA’s could be used as a substrate for microalgae cultivation as it compositions is simple in nature (Srikanth et al., 2009; Venkata Mohan and Devi, 2012, Chiranjeevi and Venkata Mohan, 2017). These integrated approaches facilitate the sustainable solution for the algal biofuel production industries with the scalable coproducts concepts and also improves the bioeconomy (Laurens et al., 2015; Venkata Mohan et al., 2016; Mohanakrishna and Venkata Mohan, 2013). Primarily, DAB was subjected to preteatment with acid and base catalyzed conditions for the transformation polysaccharides into monomeric RS. Subsequently, resulting RS were acidogenically fermented for the production of Bio-H2 and short chain carboxylic acids (SCA) production. The acidogenic process performance was evaluated at varying redox conditions (pH: 6, 7 and 10) and the SCA production and distribution were also studied with the course of time.

2. Experimental Methodology 2.1. Defatted Algal Biomass -Pretreatment The defatted algal biomass (DAB) residue after harnessing the biodiesel (Hemalatha and Venkata Mohan, 2016) was used as primary feedstock for the production of RS followed by short chain carboxylic acids (SCA) and biohydrogen (Bio-H2). Primarily, DAB was subjected to pretreatment to convert the polysaccharides into soluble monomeric sugars. The pretreatment was evaluated using physical, chemical and physicochemical methods with the solid loading of 20% (w/v). Two physical methods are individually evaluated in this study, in the first method DAB was subjected to autoclave at 121oC for 15 min (AU) and in the second method DAB was ultrasonicated (US) at 40 kHz; 3 times with 20 sec interval (Q Sonica, Q55). The chemical method was evaluated by incubating with acid (HCl, H2SO4) and base (NaOH, CaOH2) (1% v/v) for 24h with 120 rpm at 28±0.2oC. The physicochemical method is a combined physical and chemical (hybrid) method, where acids and (HCl, H2SO4) and bases (NaOH, CaOH2) were added primarily followed by autoclaving at 121oC for 15 min. Secondly, the resulting hydrolysate (rich in RS) was filtered using nylon cloth (10 µ) and the liquid portion was collected. Further, it was used as a substrate for Bio-H2 and SCA in the acidogenic fermentation process with the sugar loading rate of 5214 mg/l. The obtained sugar concentration per gram of DAB and their distribution is represented in Table 1.

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2.2 Acidogenic Fermentation Anaerobic bioreactors were fabricated using borosilicate glass bottles with the total/working volume of 0.5/0.4 L. The reactors were operated in suspended growth mode configuration in batch mode for 10 cycles with 48h of hydraulic retention time (HRT). Each cycle was comprised of 20 min of fill phase, 47 h of react phase, 20 min of settle phase and 20 min of decant phase in sequencing mode of operation (Dahiya et al., 2015). The anaerobic consortium acquired from a full scale anaerobic effluent treatment plant was used as parent inoculum for all the reactors (10%). Prior to inoculation, parent biomass was washed twice with phosphate buffer (50 mM: 5000 rpm, 28±2°C) followed by heat-shock pretreatment (80oC for one hour) to selectively eliminate the non-spore forming methanogenic microbiomes (Venkata Mohan et al., 2008). Hydrolysate resulting from acid catalyzed physicochemical method (1% H2SO4) showed higher RS solubilization (5214 mg/l), hence its hydrolysate was used as a substrate for acidogenic fermentation process. All the reactors pH was adjusted to 6, 7 and 10 using 1 N HCL or 1 N NaOH. The reactors were kept in suspension mode by continuous mixing at 120 rpm (28 ± 2oC). Proper care was taken during samples collection, feeding and to maintain the anaerobic microenvironment. 2.3. Analysis Total sugars were estimated by dinitrosalicilic acid method (Miller, 1959). The composition analysis of sugars and short chain carboxylic acids (SCA’s) were assayed by HPLC (Rezex Monosaccharide’s and organic acids RH+ column: Flow rate 0.5 ml/min, oven temperature 75°C) using 1N H2SO4 as mobile phase with 20 µl sample injection (Sarkar et al., 2017). The performances of all the bioreactors were evaluated by analyzing the chemical oxygen demand (COD), short chain carboxylic acids (SCA) and pH (APHA, 1998). The gas composition was assayed by using gas chromatography with the following specifications: argon as carrier gas, the injector and detector were maintained at 60oC and the oven was with 40oC isothermally (GC; NUCON 5765: thermal conductivity detector (TCD) with Heysep Q column) (Dahiya et al., 2015). Buffering capacity analysis was evaluated for acidogenic fermentation samples based on the acid-base titrations using auto-titrator. The collected samples were divided into two parts of 3 ml each prior to the test. The first part was titrated with 0.1 N HCl till it reaches to pH = 1.9 followed by the second titration against the 0.1 N NaOH (end point: pH=12). 4

The below equation (Eq. 1) used for the buffering calculations, where in C represents the concentration of acid or base (mol), Vs is the volume of sample (ml) and m is the slope of tangent on curve (Sarkar et al., 2016). β=

C Vs x m

…………………. (1)

Acidification degree was also calculated to understand the transformational changes of the substrate into corresponding organic acids (SCA) during the course of acidogenic fermentation (Naresh Kumar et al., 2018). The below equation (Eq. 2) was used to calculate the acidification degree, where in Si represents the initial substrate concentration measured in terms of COD as mg/l and Sf is the net short chain carboxylic acids concentration as theoretical equivalents of COD concentration. The COD equivalents of individual SCA vary with respect to its carbon number (acetic acid; 1.066 (mg/l), propionic acid; 1.512 (mg/l), butyric acid; 1.816 (mg/l) and isovaleric acid; 2.036 (mg/l)). Degree of Acidification (DOA) = (Sf/Si) x 100 …………… (2)

2.4 Dehydrogenase Enzyme Activity Dehydrogenase enzyme (DH) activity of the biocatalyst was determined during the course of acidogenesis. The estimation methods was based on the reduction of 2, 3, 5-triphenyl tetrazolium chloride (TTC) (Venkata Mohan et al., 2013). Five milliliter (ml) of TTC (5 g/l stock) and 2 ml of glucose solution (0.1 mol/l) were added to 5 ml of culture and the resulting solution was stirred continuously (20 min; 200 rpm) followed by incubation (37°C; 12 h). Further, one milliliter (ml) of concentrated sulfuric acid (H2SO4) was added to the reaction mixture to stop the reaction followed by 5 ml of Toluene to extract the triphenylformazan (TF) formed in the reaction mixture. The sample was agitated at 200 rpm (30 min). After keeping idle for 3 min, the reaction mixture was then centrifuged at 4000 rpm (5 min) and the absorbance of the supernatant was measured at 492 nm (TF forms a colored complex with toluene). All the biochemical analysis was performed in triplicates and the mean values were represented and discussed.

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3. Results and discussion 3.1 Pretreatment of DAB Considering the positive net energetic yield from the defatted algal biomass (DAB) residues, it was subjected to various pretreatment methods viz., individual (physical and chemical) and hybrid (physicochemical) to harness the reducing sugars (RS) after lipid extraction. Acidcatalyzed physicochemical pretreatment (1% H2SO4) resulted in higher RS solubilization (0.26±0.03 g RS/gDAB) (Table 1). Individual physical methods (AU and US) without acid catalysis resulted in lower RS solubilization (0.15±0.02 g RS/gDAB (AU), 0.11±0.03 g RS/gDAB (US). On the other side, chemical method with acid-catalyzed condition resulted in good RS solubilization (0.09±0.01 g RS/gDAB (1% HCl)), 0.11±0.02 g RS/gDAB (1% H2SO4)) than corresponding base condition (0.063±0.01 g RS/gDAB (1% NaOH)), 0.04±0.01 g RS/gDAB (1% Ca(OH)2). Considering the advantages of individual methods, a combined hybrid strategy (physicochemical) was evaluated thereafter. Physicochemical method with acid catalyzed conditions resulted in higher RS solubilization (0.23±0.02 g RS/gDAB (1% HCl), 0.26±0.03 g RS/gDAB (H2SO4)) than the corresponding base condition (0.19±0.02 g RS/gDAB (1% NaOH), 0.17±0.02 g RS/gDAB (1%Ca (OH)2). As higher RS solubilization was resulted with physicochemical acid catalyzed pretreatment, its hydrolysate was further used as a substrate for acidogenic fermentation process with the organic loading rate of 5124 mg/l. The RS distribution analysis of DAB pretreated hydrolysate resulted in glucose as a major fraction followed by mannose, galactose and xylose (Table 1). In the case of physicochemical pretreatment with acid-catalyzed conditions (1% H2SO4) higher glucose was depicted (0.13±0.01 g/g DAB) followed by mannose (0.06 ±0.01 g/gDAB), galactose (0.04±0.02 g/gDAB) and xylose (0.03 ±0.02 g/gDAB). On the other side, physicochemical pretreatment with base catalyzed condition (1% NaOH) resulted in similar composition of RS with acid method, but the concentration of sugars was lower. Where in, glucose content was the higher (0.12±0.01, g/g DAB) followed by mannose (0.04±0.01 g/gDAB), galactose (0.02±0.01 g/gDAB) and xylose (0.01±0.002 g/gDAB). DAB residues are majorly composed of cellulose in the cell wall and starch in the plastids apart from the low hemicelluloses and other simple carbohydrate contents. The polysaccharide materials can be converted into fermentable sugars with course of pretreatment (Laurens, et al., 2015). At the molecular level, use of acid catalyzed conditions hydrolysis specific to cellulose begin with the protonation of oxygen in a β-1,4-glycosidic bond 6

or the protonation of cyclic oxygen in a glucopyranose ring (Krassig et al. 2007, Fan et al. 1987). Further, splitting of glycosidic bond will occur with the water followed by ring opening phase finally converted to monomeric glucose (Yu and Wu, 2010). Use of dilute acids (0.5 to 1% (v/v)) and moderate temperature (80-125oC) eliminates the formation of sugar degrading compounds (furfurals and 5-hydroxymethyl furfural (HMF) (Hafid et al., 2015). Table 1 3.2 Acidogenic Fermentation 3.2.1 Short chain carboxylic acids (SCA) The extracted sugars from acid catalyzed physiochemical (1% H2SO4) method were used as primary substrate for production of SCA and Bio-H2 through acidogenic fermentation. Redox conditions showed significant influence on the substrate synthesis. Biosystem with pH-6 condition resulted in relatively higher SCA production (0.54±0.3 g SCA/g RS) followed by pH10 (0.43±0.2 g SCA/g RS) and pH-7 (0.27±0.2 g SCA/g RS) (Fig 1a). Rapid increment in SCA production until 24 h (Cycle-5: 2466 mg/l) was relatively rapid with pH-6 followed by a marginal from 36 h to 48 h (2824±0.4 mg/l). In the case of pH-10, SCA accumulation was minimal until 12 h (1326±0.2 mg/l) followed by rapid increment from 24 h to 48 h (2246± 0.3 mg/l). A possible explanation for the higher SCA production at pH-6 condition, as low pH conditions are rich in H+ concentration and thus rapidly increases the rate of metabolic reaction followed by a drop (Venkata Mohan, 2008). In the case of alkaline conditions (pH-10) initially substrate leaching will occur followed by its biotransformation and thus leads to higher substrate transformation in later phases. Additionally, alkaline conditions (pH: 8-11) also inhibit the methanogenic microbiomes (SCA consumers) with simultaneous maintenance of the system buffer (Zhang et al., 2005).

Operation with pH-7 resulted in gradual increment in SCA

concentration until 36 h (1408±0.2 mg/l) followed by a marginal drop by the end of cycle operation (48 h: 1372±0.2 mg/l). Specifically, consumption of SCA was observed in pH7 operation n during the later phase of operation (36 to 48 h) in cycle 4 and 5. In addition, employing the mixed microbiomes as a catalyst for SCA production offers the reduction in the economic inputs by non-sterile conditions.

Fig 1a

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Application of kinetic models helps in comparing the stable process performance under practical conditions (Rao and Singh, 2004). The first order dynamics was used to calculate the rate of SCA production and distribution with the studied experimental variations (Eq. 3) (Cekmecelioglu ad Uncu, 2013). C=Cm (1 - e-kt) ………………… (3)

Where, C represents the change in SCA concentration (g/l) with respect to initial concentration (C(t)-C0), Cm represents maximum SCA accumulation by the end of cycle period (48 h) and k is the rate constant of SCA production (h-1). The time constant (τ), represents the time required for the production to reach 63.2% of the final steady level during the fermentation process (Cekmecelioglu and Uncu, 2013). The data obtained during the cycle-5 operation was used for first order kinetics analysis (Fig 1b). The production rate (k (h-1)) showed marked variations with redox variations studied. pH-6 operation showed relatively higher production rate (0.17 h-1) followed by pH-10 (0.13 h-1) and pH-7 (0.11 h-1). Pretreated substrate and predominant acidic conditions in the pH-6 might have accelerated the higher substrate transformation specifically in pH-6 condition followed by others. Fig 1b 3.2.2. Fatty acids profile Acidogenic fermentation is an electron neutral process (no external electron acceptors), where in organic molecules get reduced to simplified products. The acidogenic product spectrum majorly composed of acetic (C2), propionic (C3), butyric (C4) and valeric acids (C5) in the media apart from the gaseous products (H2/CH4/CO2). System redox condition showed significant influence on the SCA distribution during the course of acidogenesis (Fig 2). Relatively pH-6 condition showed higher acetic acid production (1824±0.2 mg/l) followed by butyric (474±0.1 mg/l), propionic (358± 0.2 mg/l) and valeric acid (168±0.2 mg/l). Acetic acid is the primary and simple organic acid which accumulated in the fermentation processes. In case of pH 10, the SCA distribution was more or less similar with pH-6, but the concentrations. Acetic acid was the major fraction (1389±0.3 mg/l) followed by butyric acid (526±0.2 mg/l), valeric acid (206±0.2 mg/l) and propionic acid (126± 0.2 mg/l). Interestingly, valeric acid concentration was found higher at pH-10 condition than the propionic acid. This attributed to initial alkaline condition 8

facilitates good buffering and thus resulting in higher chain fatty acids synthesis than hydrogen consuming propionic acid synthesis (Dahiya et al., 2015). On the other side, pH-7 condition resulted in high acetic acid (932±0.2 mg/l) followed by propionic acid (296±0.1 mg/l) and butyric (191±0.2 mg/l). There was no valeric acid production observed due to favorable methanogenic conditions which eventually restricts accumulation of higher chain fatty acids. Marked influence of redox condition was observed on the SCA accumulation and allocation as well as on acidogenic process performance. Better understanding of the products distribution, interaction between substrate type, retention time and appropriate pH might help to develop industrially feasible SCA production process using waste streams (Jankowska et al., 2017).

Fig 2 3.2.3 Biohydrogen The sugars derived from DAB also resulted in good Bio-H2 production apart from SCA. Although similar biocatalyst was used in all the experimental variations, differences were observed in the biogas profiles and thus illustrate the role of redox microenvironment on the ongoing acidogenic fermentation process. Biosystem with pH-6 resulted in relatively higher cumulative Bio-H2 production (CHP) (0.83±0.2 l) followed by pH-10 (0.71±0.4 l) and pH-7 (0.48±0.3 l) (Fig 3). Acidophilic pH range (5.5-6.0) represses the methanogenic microbiomes which indirectly promotes the Bio-H2 producers within the system (Venkata Mohan et al., 2008). In the case of pH-6 condition, from 4 h onwards a rapid increment in CHP was observed until 32h. Similarly, biosystem with pH-7 resulted in gradual increment in Bio-H2 production until end of cycle period. Biosystem with pH-10 resulted in rapid Bio-H2 production from 12 h to 36 h. The composition of total biogas also showed higher Bio-H2 with pH-6 (23%) followed by pH10 (18%) and pH-7 (8%). Where in the case of neutral pH conditions (pH-7), higher biomethane was resulted (18%) than Bio-H2. Fig 3 3.2.4 Sugar Consumption During the course of acidogenic fermentation a gradual decrement in the sugar concentration was illustrated with time (Fig 4a). Relatively, biosystem with pH-6 resulted in maximum sugar consumption (68±0.3%) followed by pH-10 (65±0.2%) and pH-7 (61± 0.1%). Although the substrate removal profiles were depicted marginal variations, marked difference was noticed 9

with SCA production with the function of system pH condition. This attributed to availability of simplified substrate (monomeric sugars) eliminated the process of hydrolysis and resulted in good substrate transformation in all the studied experimental variations. The individual sugar consumption profiles were also varied with respect to redox conditions (Fig 4b). Higher glucose removal was noticed with pH-6 operation (2331±1.2 mg/l) followed by mannose (737± 0.1 mg/l), galactose (531± 0.3 mg/l) and xylose (96±0.4 mg/l) by the end of cycle period (48 h). In the case of pH-10 system, glucose was majorly utilized (2131±0.3 mg/l) followed by mannose (800±0.3 mg/l), galactose (478±0.3 mg/l) and xylose (68 ± 0.2 mg/l). On the contrary, pH-7 operation which resulted in relatively low RS consumption depicted major glucose consumption (1668±0.3 mg/l) compared to mannose (918± 0.3 mg/l), galactose (511± 0.2 mg/l) and xylose (106± 0.2 mg/l). System operated with pH-7 resulted in relatively higher xylose consumption than corresponding pH-6 and pH-10. Specifically, in the pH-6 condition rapid substrate consumption was noticed than corresponding other pH variations. This attributed to pre-existing acidic conditions in the media facilitated the relatively higher protons (H+) towards metabolic actions of acidogenic microbiomes and thus accelerated the substrate transformations (Venkata Mohan, 2008, Jankowska et al., 2017). Fig 4 a, b 3.2.5 Degree of Acidification Acidification degree (DOA) represents the capabilities of substrate biotransformation into corresponding acids (SCA) with the course of acidogenic fermentation (Naresh Kumar and Venkata Mohan, 2018). Represented DOA profiles were calculated with total and individual SCA contributions (Fig 4c). Maximum DOA was observed with pH 6.0 (23%) followed by pH10 (20%) and pH-7 (10%). Apart from the total DOA, individual SCA contributions towards the acidification were also calculated. Acetic acid fraction with pH-6 operation was major for DOA contributor (14.3%) followed by butyric acid (4.1%), valeric acid (2.5%) and propionic acid (2.3%). In the case of pH-10 was more or less similar [acetic (11.4%); butyric (3.5%), valeric (3.1%); propionic acid (2.1%)]. Specifically in pH-10, valeric acid also contributed relatively good DOA than propionic acid. On the other hand, pH-7 system showed higher with acetic (5.2%) followed by propionic (3.1%) and then butyric (2.1%). The depicted results illustrate the acidification potential of DAB in the fermentation process. In addition, understanding the

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substrate acidification is important to estimate the potential of a particular substrate for SCA production specific to acidogenesis. Fig 4c 3.3 Dehydrogenase Activity Biological oxidation of organic compounds is interceded by various dehydrogenase enzymes (Nielsen, 1975). Substrate reduction to its intermediate products catalyzes the proton transfer and thus can be assessed by dehydrogenase enzyme (DH) activity. DH plays a critical role in the proton shuttling. Distinct variations in the DH activity were observed with the function of pH and operation time (Fig 5). Relatively, pH-6 condition resulted in higher DH activity (1.71±0.05 µg/ml) followed by pH-10 (1.52±0.06 µg/ml) and pH-7 (1.05± 0.04 µg/ml). DH activity correlates well with both SCA and Bio-H2 production patterns. Interestingly, pH-6 and pH-7 operation showed rapid increment in the DH activity until 24 h followed by a marginal from 36 h to 48 h. On the other side, biosystem with pH-10 showed marginal increment until 12 h (0.65 µg/ml) followed by a rapid increment from 24 h (1.52 µg/ml) to till cycle end.

Fig 5 3.4. Redox Microenvironment The composition of organic growth media and the changes in external pH condition can bring about subsequent alterations in several primary physiological parameters like internal pH, concentration of H+, membrane potential, proton-motive force etc., (Jankowska et al., 2017, Wang et al., 2017). During the process of acidogenesis accumulation of acids in the media leads to drop in the pH and thus indirectly signifies the accumulation of acids (SCA). All the studied experimental variations resulted in pH drop towards acidic conditions due to SCA accumulation (Fig 6). Higher SCA accumulation in pH-6 system resulted in rapid pH drop (6.0± 0.2 to 4.63± 0.2; 24 h) followed by a marginal by the end of cycle period (4.32±0.3). On the other hand, pH10 resulted in pH drop throughout the cycle operation. On the contrary, pH-7 resulted in marginal pH variations and thus can be attributed to SCA consumption resulting in lower pH drop. The observed variations in the pH changes attributed to eventual changes in the SCA accumulation leads to change in the H+ availability and thus direct metabolic actions of biocatalyst and substrate transformation efficiency.

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Due to its direct influence on the microorganism specific growth rate and substrate transformations efficiencies, understanding the suitable process redox conditions considered as one of the important parameter in acidogenic fermentation (Wang et al., 2017). SCA production and consumption leads to change in system buffering conditions. Relatively, maximum buffering was documented with pH-10 system (36 h: 0.041 βmol) followed by pH-6 (24 h: 0.036 βmol) and pH-7 (48 h: 0.025 βmol) (Fig 6). Solubility of generated CO2 as bicarbonate also helps in the buffer maintenance of fermentation process (Dahiya et al., 2015). Higher CO 2 liberated from the substrate metabolism might assisted in the maintenance of good buffering conditions during the initial hours of operation (until 24 h) specifically in pH-6 condition. On the contrary, pH-10 system buffering showed gradual increment until 48 h ascribed to initial substrate leaching followed by higher CO2 production at later stage thus assisted in good buffering maintenance.

Fig 6 4. Conclusions Acid-catalyzed physicochemical pretreatment of DAB showed relatively higher reducing sugars (RS) solubilization. Subsequent acidogenic fermentation of DAB residue derived RS resulted in good Bio-H2 and SCA production. In the process of acidogenesis, system redox conditions were significantly influenced the process performance and product distribution. Higher SCA production in pH-6 system resulted in maximum acidification degree (23%) followed by other studied variations. The reutilization of sugars from DAB residues for renewable chemicals and fuels production renders the sustainability on its entirity utilization. The concept of multiproduct approach invokes a novel avenue to the existing algal refineries in the biorefinery framework. Acknowledgement The research was funded by Department of Science and Technology (DST), Government of India (INT/Korea/P-34) and Ministry of Education, Science and Technology, Republic of Korea. Part of the research was also supported by Department of Biotechnology (DBT), Government of India (DBT;13642/BBE/117/80/2015). ANK duly acknowledges CSIR for providing fellowship. The authors wish to thank the CSIR-IICT and Kyung Hee University for supporting the research.

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15

Figures pH-6

pH-7

pH-10

SCA Concentration (mg/l)

3000

2400

1800

1200

600

0 0

48

96

144

192

240

Time (h) pH-6

pH-7

pH-10

SCA/ RS (g/g)

0.48

0.36

0.24

0.12

0.00 6

12

24

36

48

Time (h) Fig 1a: Variations in the SCA concentration with respect to studied pH conditions

pH-6

pH-7

pH-10

Model fit

SCA Concentration (mg/l)

3000

2500

2000

1500

1000

500

0 0

6

12

18

24

30

36

42

48

Time (h) Fig 1b: Kinetic model fit of SCA concentrations with the studied pH conditions (cycle 5)

Acetic Acid

Propionic Acid

SCA Concentration (mg/l)

2000

Butyric Acid

Valeric Acid

pH-6

1600

1200

800

400

0 0

12

24 Time (h)

36

48

2000

pH-7

SCA Concentration (mg/l)

1600

1200

800

400

0

0

12

24

36

48

Time (h) 2000 pH-10

SCA Concentration (mg/l)

1600

1200

800

400

0

0

12

24

36

48

Time (h)

Fig 2: Variation in SCA distribution with respect to pH and time

pH-6

0.90

pH-7

pH-10

0.75

CHP (L)

0.60

0.45

0.30

0.15

0.00

0

12

24

36

48

Time (h) pH-6

Biohydrogen (%)

30

pH-7

pH-10

24 18 12 6

Biomethane (%)

0 24 18 12 6 0 12

24

36

48

12

24

36

48

Time (h) Fig 3: Cumulative biohydrogen production and the total biogas profiles with respect to studied pH condition and time (% v/v)

Sugars Consumption (mg/l)

pH-6

pH-7

pH-10

4800

4000

3200

2400

1600

0

48

96

144

192

240

Time (h)

pH-6

pH-7

pH-10

Sugars Removal (%)

60

45

30

15

0 6

12

24

36

48

Time (h) Fig 4 (a): Total reducing sugars consumption profiles with the course of operation time

Glucose

Mannose

Galactose

Xylose

pH-6

Sugar Concentration (mg/l)

3200

2400

1600

800

0 0

6

24

12

36

48

Time (h) pH-7

Sugar Concentration (mg/l)

3200

2400

1600

800

0 0

6

12

24

36

48

24

36

48

Time (h) pH-10

Sugar Concentration (mg/l)

3200

2400

1600

800

0 0

6

12

Time (h)

Fig 4 (b): Individual sugar consumption variation as a function of pH and time

Acetic Acid

Propionic Acid

Butyric Acid

Valeric Acid

Total DOA

Degree of Acidification (%)

28 24 20 16 12 8 4 0 pH-6

pH-7

pH-10

Fig 4 (c): Degree of acidification (DOA) with respect to pH and SCA allocation

Dehydrogenase Activity (g/ml of Toluene)

pH-6

pH-7

pH-10

1.8

1.5

1.2

0.9

0.6

0.3 0

48

96

144

192

240

Time (h) Fig 5: Dehydrogenase enzyme (DH) activity with respect to pH condition

pH-6

pH-7

pH-10

10.5

pH

9.0

7.5

6.0

4.5 0

48

96

144

192

240

Time (h)

Buffering Capacity ( mol)

pH-6

pH-7

pH-10

0.036

0.024

0.012

0.000 6

12

24

36

Time (h) Fig 6: Variations in the pH and buffering profiles as a function of time

48

Table 1: Composition of DAB after various pre-treatments Physical Methods

Physicochemical Methods (AU* combined with acid/base)

Chemical Methods

Parameter AU*

US#

1% HCl

1% H2SO4

1% NaOH

1% Ca(OH)2

1% HCl

1% H2SO4

1% NaOH

1% Ca(OH)2

pH

7.08 ± 0.3

7.11 ± 0.2

1.56 ± 0.2

1.42 ± 0.3

10.8 ± 0.2

10.6 ± 0.3

1.54 ± 0.2

1.48 ± 0.2

10.9 ± 0.1

10.8 ± 0.3

Total Sugars (g /g DAB)

0.15 ± 0.02

0.11 ± 0.03

0.09 ± 0.01

0.11 ± 0.02

0.063 ± 0.003

0.04 ± 0.002

0.23 ± 0.02

0.26 ± 0.03

0.19 ± 0.02

0.17 ± 0.01

Glucose (g/g DAB)

0.08 ± 0.001

0.07 ± 0.002

0.04 ± 0.003

0.06 ± 0.001

0.028 ± 0.003

0.025 ± 0.001

0.12 ± 0.003

0.13 ± 0.002

0.12 ± 0.001

0.11 ± 0.003

Mannose (g /g DAB)

0.03 ± 0.002

0.02 ± 0.001

0.02 ± 0.003

0.03 ± 0.002

0.004 ± 0.001

0.05 ± 0.001

0.05 ± 0.003

0.06 ± 0.001

0.04 ± 0.002

0.02 ± 0.001

Galactose (g /g DAB)

0.02 ± 0.003

0.01 ± 0.001

0.02 ± 0.002

0.01 ± 0.003

0.011 ± 0.004

0.03 ± 0.002

0.03 ± 0.003

0.04 ± 0.002

0.02 ± 0.001

0.02 ± 0.002

Xylose (g /g DAB)

0.02 ± 0.002

0.01 ± 0.001

0.01 ± 0.002

0.01 ± 0.003

0.02 ± 0.002

0.03 ± 0.001

0.03 ± 0.001

0.03 ± 0.003

0.01 ± 0.001

0.02 ± 0.001

AU*=Autoclave at 121oC for 15 min, US# = Ultrasonication 40 kHz; 3 times with 20 sec interval

28

Defatted Algal Biomass as Feedstock for Short Chain Carboxylic Acids and Biohydrogen Production in the Biorefinery Format B. Naresh Kumar a,b, Booki Min c S. Venkata Mohan a,b * a Bioengineering and Environmental Sciences Lab, EEFF Department CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Hyderabad- 500 007, India. b Academy of Scientific and Innovative Research (AcSIR), c Department of Environmental Science and Engineering, Kyung Hee University, Seocheon- dong, Yongin-si, Gyeonggi-do 446-701, Republic of Korea * E-mail: [email protected], [email protected], Tel: +9140-27191765

Graphical Abstract

CO2

Biodiesel H2

Algal Cultivation System

H2

Head Space Short Chain Carboxylic Acids (SCA)

Biomass Transesterification

Biomass Collection

Peristaltic Pump Microbial Culture

29

Reducing Sugars

PreTreatment Defatted Algal Biomass



Acid catalyzed pretreatment of DAB residues resulted in higher sugar solubilization



Higher biohydrogen production was resulted with pH-6 operation



Biosystem redox condition showed influence on SCA production and distribution



Use of DAB as a resource renders the sustainability to current algal biorefineries

30