6 VALORIZATION OF D. SALINA REMNANT BIOMASS
under these conditions. At temperatures around 250◦C amides are formed as a product of the cyclization reaction of the hydroxyl group in long-chained fatty acids and the ammonia derived from deamination of amino acids (Gai et al., 2015b). Glycerol is a product which is present in the aqueous phase at low temperatures (Guo et al., 2015).
The molecule is decomposed in alcohols, light alkanes and aldehydes at temperatures above 310◦C (Buehler et al., 2002; Qadariyah et al., 2011).
The depolymerization of polysaccharides is initiated at relatively mild conditions and results in monosaccharides like glucose, maltose, fructose and acetic acid (Chen et al., 2014). Acetic acid is next to glycerol one of the most abundant products in the aqueous phase of HTL (Zhou et al., 2010). The monosaccharides are further decom-posed in C1-C3 intermediates (acids, ketones, alcohols, etc.) or dehydrated in furfural derivatives which undergo polymerization in cyclic oxygenates at temperatures above 200◦C (Chen et al., 2015, 2014; López Barreiro et al., 2013). Furfural derivatives as 5-hydroxylmethylfurfural (5-HMF) are rated as innovative building block chemicals for bio-based products in industry (Peterson et al., 2008). The pathways of monosaccha-rides and amino acids from protein hydrolysis can interact by the Maillard reaction to form polycyclic nitrogenous compounds (Toor et al., 2011). These chemical species are known to potentially inhibit the bio-oil yield (Yang et al., 2015). At high temperatures, polysaccharides are hydrolyzed to produce phenol (Gai et al., 2015b).
The initial hydrolysis of proteins results in amino acids which are either broken down into alcohols, amines, carbonic acids and CO2 by decarboxylation or in ammonia and organic acids by deamination at intermediate temperatures between 100 and 200◦C (López Barreiro et al., 2013). The CO2 generated during degradation is one main product of the gas phase. A repolymerization of the molecules in cyclic hydrocarbons as well as cyclic amides starts at temperatures above 200◦C.
6.3 Materials and methods
analyzed by elemental analysis (Currenta, Germany). The heating value HHVBoie of the extracted biomass was calculated according to the Boie equation (Boie, 1953) in MJ kg−1:
HHVBoie= 0.3516C+ 1.16225H−0.1109O+ 0.0628N (6.1) The moisture and ash contents of the extracted D. salina powder were determined by weight dierence of samples prior and after overnight drying at 100◦C and 450◦C, respectively. The carbohydrate concentration was quantied by an enzymatic assay kit based on the determination of glucose (R-Biopharm AG, Germany). For the determi-nation of the protein content the method of Lowry was used (Lowry et al., 1951). The residual lipid content in the remnant biomass was calculated as dierence of all other biochemical components from 100%.
6.3.2 Hydrothermal treatment of remnant biomass
A 200 mL stainless steel batch reactor (Picoclave 3, Büchi Labortechnik GmbH, Ger-many; recording software: Büchi log'n see bls2, Büchi Labortechnik GmbH) was used to hydrothermally liquefy the D. salina biomass (see Figure 6.3a). Therefore, the reactor
Stirring unit
Vessel
Outlet
Thermometer Manometer Gas ports
Heating system
a) b)
b)
c)
0 min 30 min 60min
Figure 6.3: a) Hydrothermal liquefaction reactor, b) used biomass remnant and c) aque-ous phase of three experiments using 180◦C and 0-60 min.
was lled with a slurry containing 6 g of the extracted biomass mixed with 100 mL bidistilled water. After sealing the reactor, the headspace was purged by nitrogen for 5 min to remove air. The reactor was operated under constant mixing with a frequency of 1800 rpm at temperatures and reaction times between 100-200◦C and 0-60 min,
6 VALORIZATION OF D. SALINA REMNANT BIOMASS
respectively. The reaction time started running from the moment the set point of tem-perature was reached. After cooling down, the reactor content was transferred through a preweighted lter into a separation funnel. To collect any remaining lipophilic products, the reactor and stirrer were rinsed with 60 mL n-hexane. Afterwards, the n-hexane mix-ture was passed through another preweighted lter into the separation funnel containing the aqueous phase. Filters were dried and oil residuals in the lter and on the solid surface were recovered by applying 30 min Soxhlet extraction using 60 mL n-hexane.
Thereafter, lters were dried again and weighted to determine the yield of the solid phase. The immiscible water-hexane fraction in the separation funnel was intensively mixed to extract all bio-oil products into the hydrophobic phase. After that, the bipha-sic mixture was allowed to separate into an aqueous and a hydrophobic n-hexane phase.
To recover the bio-crude, the n-hexane phase was mixed with that obtained by Soxhlet extraction and evaporated at 40◦C and reduced pressure. For the quantication of the bio-crude fraction the remaining lipophilic substances were dried overnight. The yields of all product fractions were calculated based on the dry weight of the used biomass.
The yield of the aqueous phase was determined by weighting two overnight-dried 6 mL samples of the aqueous phase. The yield of the gas phase was calculated as subtraction of all other products yields from 100%.
6.3.3 Analysis of the aqueous phase
Concentrations of glucose, fructose, sucrose, galactose and glycerol were determined in duplicates or triplicates using substrate specic enzymatic test kits (R-Biopharm AG, Germany) based on absorbance measurements at 340 nm. Nutrient concentrations were determined by ion chromatography (930 compact IC ex, Metrom, Switzerland).
Concentrations of anions were measured using a Metrosep A Supp 5 column at 35◦C, an eluent containing 3.2 mM Na2CO3and 1 mM NaHCO3 and a ow rate of 0.7 mL min−1. Cations concentrations were measured using a Metrosep C6 column at 45◦C, an eluent containing 1.7 mM HNO3 and 1.7 mM C7H5NO4 and a ow rate of 0.9 mL min−1. 6.3.4 Cultivation experiments using glucose from the aqueous phase
as carbon source
Chlorella vulgaris SAG 211.12, Escherichia coli MG1655 and Saccharomyces cerevisiae Y187 were used as model organisms to test the glucose recovered from the HTL ex-periments as carbon source for microbial growth. In all cultivation trials media were applied with a glucose concentrations commonly used for the individual microorganism.
The respective glucose concentration in the individual control medium was adjusted by the addition of purchased glucose (Sigma-Aldrich, USA). The glucose concentra-tion in the individual test medium was adjusted by adding appropriate volumes of the glucose-rich aqueous phase (∼48 g L−1 glucose) obtained by mild HTL at 100◦C to reach concentration equal to the corresponding control medium. The aqueous phase (approx. 10 mL/100 mL LB, 10 mL/100 mL BG11, 42 mL/100 mL YPD) was added to the medium before the water and pH adjustment was done. All other media ingredients
6.3 Materials and methods
were identical in source and concentration to the described control media recipes. The pH in the control and test media was adjusted to the same value.
C. vulgaris was grown mixotrophically at a pH of 7.1 in 300 mL shaking asks con-taining 100 mL BG11 medium (Stanier et al., 1971) with 0.5% glucose. The cultivations were carried out in a rotary shaking incubator as previously described in (Pirwitz et al., 2015b). E. coli was cultivated aerobically in 500 mL shaking asks lled with 75 mL LB medium (tryptone 1%, yeast extract 0.5%, sodium chloride 0.5%, glucose 0.5%) adjusted to a pH of 7. The cultivation occurred at 37◦C and a mixing frequency of 200 rpm. Growth experiments with S. cerevisiae were carried out under aerobic condi-tion using 500 mL shaking asks lled with 100 mL YPD medium (tryptone 2%, yeast extract 1%, glucose 2%). The cultures were incubated at 30◦C and 200 rpm.
The growth of all microorganisms was followed by absorbance measurements of the cul-tures at 735 nm for C. vulgaris or 600 nm for E. coli and S. cerevisiae, respectively. The glucose consumption of the individual cultures was determined from ltrated samples of the supernatants by the previously mentioned enzymatic assay kit (see Section 6.3.3).
6.3.5 Energy and operating cost analysis of mild HTL
To calculate the additional energy demand and the operating costs for the glucose generation from the remnant biomass, the process model described by Pirwitz et al.
(2015a) was extended by a process unit of liquefaction as illustrated in Figure 6.4. The energy consumption of liquefaction comprises the energy required for water and slurry pumping, for mixing as well as for heating. Pumping and mixing work were calculated according to the assumptions made in the process model already described in 3.2. The energy required for the heating of the algal slurry containing 6% dry weight biomass was estimated by the heat capacity equation (see Equation 5.5).
Solvent recycle Water recycle
Extraction (Hexane) Pigment extract
Electricity Electricity
x1 x4
p1
Cultivation (Pond)
O2 Evaporation
CO2 Electricity
x2
Heat Dewatering
Drying (Spray)
Heat
Liquefaction (mild) Water
Nutrients
Centrifuge (one step)
x3
By-product
p2
Figure 6.4: Process scheme of industrial β-carotene production by D. salina divided in four main subunits: cultivation of the algae for biomass generation, harvesting and dewatering of the biomass,β-carotene extraction and utilization of the residual biomass.
Liquefaction was assumed to be operated in a continuous-working isolated reactor with a working volume of 400 L. The reactor was simulated to be heated from 20◦C
6 VALORIZATION OF D. SALINA REMNANT BIOMASS
to 100◦C by a conventional boiler in combination with a heat exchanger with an ef-ciency of 80% (Delrue et al., 2013). The heat capacity of algal biomass was set to the value 1.25 kJ kg−1 K−1 (Orosz & Forney, 2008). After liquefaction the reaction mixture was separated in a separation unit. The biomass concentration as well as the biomass conversion and the yield of glucose were adopted from the results of the mild HTL experiment at 100◦C presented in this study. The total revenue of glucose was estimated considering the recent commodity price of 747.55 USD t−1 published by the United States Department of Agriculture (USDA, 2016).
For the consideration of uncertainties in the parameter values used in the process model, Monte Carlo simulations were applied in Matlab (MathWorks) using 5 x 105 independent normally distributed samples. The variances were dened in dependence of the used parameters as explained in Section 3.2.5.