A publication of
CHEMICAL ENGINEERING TRANSACTIONS
VOL. 35, 2013
The Italian Association
of Chemical Engineering
www.aidic.it/cet
Guest Editors: Petar Varbanov, Jiří Klemeš, Panos Seferlis, Athanasios I. Papadopoulos, Spyros Voutetakis
Copyright © 2013, AIDIC Servizi S.r.l.,
ISBN 978-88-95608-26-6; ISSN 1974-9791
Exergetic Assessment of Bioethanol Production Process
from Residual Microalgal Biomass of Chlorella vulgaris
Angel J. Sierra, Jeberth A. Bautista, Yeimmy Y. Peralta, Viatcheslav Kafarov*
Industrial University of Santander, Chemical Engineering Department.
Carrera 27 con Calle 9, Bucaramanga, Colombia
kafarov@uis.edu.co
Three technologies for bioethanol production from carbohydrates of Chorella vulgaris microalgae residual
biomass were evaluated using the Exergy Analysis Method in order to identify potential improvements
from the energy point of view. Cases were simulated using industrial process simulation software, taking
as feedstock 78,953 tons per year of microalgal carbohydrates (cellulose 53.5 %, starch 31.1 % and
hemicellulose 15.4 %), initiating with a dilute acid hydrolysis step and ending with a distillation step where
molecular sieve technology was employed. Case 1 used Separate Hydrolysis and Fermentation
Technology (SHF) and Saccharomyces cerevisiae as fermenting microorganism, Case 2 and 3 utilized
Separate Hydrolysis and co-Fermentation (SHCF) and Simultaneous Saccharification and coFermentation (SSCF) technologies both with the recombinant bacterium Zymomonas mobilis. As result
were obtained a bioethanol production (99.5 % pure) of 24,887 t/y, 27,893 t/y and 28,214 t/y on Case 1, 2
and 3 respectively. Case 3 showed the highest exergetic efficiency (31.8 %) and the lowest irreversibilities
per kilogram of ethanol (57.8 MJ / kg ethanol), followed by Case 2 (30.4 %, 61.7 MJ / kg ethanol) and
Case 1 (27.7 %, 70.4 MJ / kg ethanol). Cellulose Hydrolysis (Cases 1 and 2) and SSCF Fermentation
(Case 3) presented the lowest exergetic efficiencies (52.5 % and 55.8 % respectively) due to the
localization of a significant waste stream in those steps. The exergetic assessment developed also was
useful for identify both reduction of process waste and utilities requirements as two key factors to ensure
the efficient use of energy.
1. Introduction
Deterioration of environment due to CO2 emissions from burning fossil fuels has led to direct a part of
scientific research worldwide to finding new sources of energy. One of the renewable energy sources is
microalgal biomass potentially useful for biofuel production like bioethanol.
As Lam and Lee (2012) explain, microalgae have received great interest because of its rapid growth and
ability to accumulate into its cells large amounts of lipids and carbohydrates suitable for biodiesel and
bioethanol production respectively. However, until now this interest has been focused mainly on the study
of lipid extraction. It has been suggested by Rojan et al. (2011) that after lipid extraction the residual
biomass of microalgae there is sufficient carbohydrates useful for ethanol production by anaerobic
fermentation.
The microalgae is a unicellular organism composed mainly of lipids, proteins and carbohydrates in
different proportions depending on genus, species and culture conditions used in the cell growth. In the
case of bioethanol production from microalgae is essential to determine the content and type of
monosaccharides present in the cell structure since this substantially affects characteristics of the process.
Modeled composition of Chlorella sp. biomass is shown in Table 1.
Table 1: Modeled composition of Chlorella sp. microalgae.
Components
Triglycerides
Free fatty acids
Amino acids
Water
Carbohydrates
Cellulose
Starch
Hemicellulose
Total microalgae
Composition (%)
28.47
1.53
40.05
5.03
24.92
13.33
7.75
3.84
100.00
In this paper were evaluated three cases for the production of bioethanol from microalgal residual biomass
Chlorella vulgaris by applying exergy analysis methodology (cases were simulated in Aspen Plus TM
software). According to Dincer and Rocen (2007), this methodology allows calculating exergetic
efficiencies helpful to identify the causes and locations of thermodynamic losses and thus it is possible to
estimate improvements in the process.
2. Bioethanol production process from microalgae
Biomass conversion to bioethanol usually contains the following steps: pretreatment of feedstock,
hydrolysis, fermentation and distillation of bioethanol, as it is explained by Harun et al. (2003).
2.1 Pretreatment
Carbohydrates in green algae such as Chlorella vulgaris are mainly starch and cellulose, two glucose-rich
polysaccharides. This has been demonstrated by Lee et al. (2011) who have obtained high yields of
glucose (and a lesser extent galactose, xylose and fructose) applying an acid hydrolysis pretreatment at
110 °C and 5 % of sulfuric acid.
2.2 Hydrolysis and fermentation
It is necessary the hydrolysis step because the mixture coming from the pretreatment step not only
contains sugars such as pentoses and hexoses, but also polysaccharides (mainly cellulose) which were
not fully converted.
There are different combinations of the hydrolysis and fermentation steps depending on both the amounts
and types of monosaccharides, and the microorganism used to ferment sugars (Harun et al., 2010):
Separate Hydrolysis and Fermentation (SHF), Separate Hydrolysis and co-Fermentation (SHCF),
Simultaneous Saccharification and Fermentation (SSF), Simultaneous Saccharification and coFermentation (SSCF).
Most of the ethanol produced in the world is obtained using yeast Saccharomyces cerevisiae which
ferments hexoses like glucose (and a lesser extent galactose) but not pentoses (Mousdale, 2008).
According to the work of Hamelinck et al. (2003) there is also the ethanologénic bacterium called
Zymomonas mobilis unable to ferment pentoses; nevertheless, advances in the field of metabolic
engineering have allowed obtaining the recombinant Zymomonas mobilis bacterium suitable for being
used in co-fermentation processes.
2.3 Distillation
The resulting culture broths from fermentation processes range an ethanol concentration from 2.5 to 10 %,
therefore it is necessary to concentrate the ethanol to values greater than 99 %. Commonly this separation
is carried out by a conventional distillation process which elevates the ethanol concentration in the broth
until 45-50 % and this stream is then sent to a rectification column in which a distillate of 90 – 92 % is
obtained. Finally it is required a non-conventional separation step due to the azeotropic mixture ethanolwater. In bioethanol industry, molecular sieve adsorption seems to be one of the best non-conventional
separation technologies due to its low energy costs (Sanchez-Toro et al., 2009).
3. Methodology
Simulations were performed with Aspen Plus TM software and it was used a feedstream composition of 53.5
% cellulose, 31.1 % hemicellulose and 15.4 % starch. The thermodynamic properties package used was
NRTL model for calculating activity coefficients in the liquid phase and Henry's Law for dissolved gases.
Three cases were simulated as it is shown in Figure 1: Case 1 using SHF technology and Saccharomyces
cerevisiae in fermentation, Case 2 employing SHCF technology with recombinant Zymomonas mobilis,
and Case 3 using SSCF technology with the recombinant Zymomonas mobilis bacterium. All cases were
designed with exactly the same configuration in the following steps: dilute acid pretreatment, overliming
and distillation. Cellulose hydrolysis step in cases 1 and 2 have also both the same configuration.
Figure 1: General diagram of simulated cases. Above: Case 1. Middle: Case 2. Below: Case 3.
3.1 Dilute Acid Pretretment and Overliming
This step was simulated based on the work made by Lee et al. (2011) where dilute acid hydrolysis was
carried out with biomass of Chlorella vulgaris obtaining an optimum temperature of 110 °C and the
following yields: 0.12 g glucose / g biomass, 0.033 g xylose / g biomass, 0.047 g galactose / g biomass
and 0.007 g fructose / g biomass.
Inputs of the dilute acid pretreatment step are: carbohydrates residual biomass of microalgae, water and
sulfuric acid. These streams enter the pretreatment reactor (reaction temperature110 °C). After acid
hydrolysis the stream is cooled and separated into two streams: one with solids (it is sent to the cellulose
hydrolysis step) and the other with liquids that enter overliming step. There dilute acids react with calcium
hydroxide at a temperature of 50 °C, and then calcium sulfate dihydrate (gypsum) is formed and
subsequently removed from the process. The stream free of acid continues to the fermentation step.
3.2 Cellulose Hydrolysis
Case 1 and 2 use separate hydrolysis and fermentation technologies. Because of this both were designed
with one enzymatic hydrolysis to convert cellulose which did not react in the pretreatment step.
In cellulose hydrolysis step enters three streams: one from pretreatment, water and cellulase enzyme. The
mixture is heated to the hydrolysis temperature (48 °C). The glucose-rich mixture leaving the hydrolysis
reactor is separated into two streams: one contains the remaining solids that leaving the process and the
other the glucose which is sent to the stage of fermentation.
3.3 Hydrolysis and Fermentation technologies
Cases 1 and 2 employ separate hydrolysis and fermentation technologies, and differ beetwen them only
by the type of microorganism used in the fermentation step: while case 1 uses the yeast Saccharomyces
cerevisiae, Case 2 uses recombinant Zymomonas mobilis, a bacteria capable of fermenting pentoses and
hexoses simultaneously according to Hamelinck et al. (2003).
For Cases 1 and 2, streams coming from the Cellulose Hydrolysis and Overliming are mixed with ammonia
(nitrogen source) to enter in the fermentation reactor (reaction temperature: 32 °C). Subsequently two
streams are obtained: a gas composed mainly of CO2 and a broth containing mainly ethanol, water and
remaining solids. These solids leave the process and ultimately the other stream composed mainly by
ethanol and water is sent to the distillation step.
In Case 3, the cellulose hydrolysis and fermentation of hexoses and pentoses are performed
simultaneously in a single step using cellulase and recombinant Zymomonas mobilis according to the
process developed by NREL (2002). The fermentation step for Case 3 differs from Case 1 and 2 in two
aspects basically: adding cellulase and fermentation reactor temperature (41 °C).
3.4 Distillation
Distillation step was simulated in Aspen PlusTM and it was designed taking into account the process
proposed by NREL (2011) for corn ethanol distillation.
3.5 Exergeric Evaluation
In this paper it was applied the methodological development for exergy analysis proposed by Dincer and
Rocen (2007) and implemented by Peralta-Ruiz et al. (2012).
Once simulated the three cases in Aspen PlusTM, and having defined the conditions of temperature and
pressure of the reference state at 25 °C and 101.3 kPa, respectively, it was calculated the different kinds
of exergy considering some variables of the flows of matter and energy in the process like enthalpy,
entropy, temperature, composition, etc.
The exergetic efficiency for each case and step was calculated using Eq(1).
(1)
4. Results and discussion
The cases simulated were performed starting from a stream of microalgal residual biomass of 78,953 t / y
with a composition of 53.5 % cellulose, 31.1 % starch and 15.4 % hemicellulose. At the end of the process
the ethanol production (99.5 % pure) was 24,887 t / year, 27,893 t / year and 28,214 t / year for Case 1, 2
and 3, respectively. It means that the highest yield achieved was 0.36 kg of ethanol per kg of residual
biomass for Case 3 (0.31 kg ethanol / kg biomass for Case 1 and 0.35 kg ethanol / kg biomass for Case
2).
As can be checked in Figure 2, Case 3 had the highest overall exergetic efficiency with a value of 31.83%,
followed by Case 2 and 1 with 30.43% and 27.73% respectively. It is also shown in Figure 2 the exergy of
waste and the exergy of utilities (it was calculated assuming the use of cooling water at 15 ° C and low
pressure steam at 5 bar and 152 °C for cooling and heating). It may be reduced exergy losses and to
increase exergetic efficiency if wastes are utilized and energy consumption are minimized.
Figure 2: Exergy analysis results.
The results shown in Figures 3 allow identifying which steps presented the highest exergy losses and the
lowest exergetic efficiencies, so it is possible to know where are required improvements from energy point
of view. As shown in Figure 3, the cases with higher irreversibilities per ethanol kilogram were the cases 1
and 2 (22.35 and 19.94 MJ / kg ethanol respectively) and SSCF fermentation for Case 3 (24.59 MJ / kg
ethanol). In these steps there is an output stream with carbohydrates, nitrogen, enzymes and organisms
which involve exergy losses of 14.99, 17.09 and 18.79 MJ per kilogram of ethanol in cases 1, 2 and 3,
respectively. If this output flow is used in any useful activity (e.g. fertilizer production) then it could be
possible to reduce exergy losses and to improve exergetic efficiency.
Figure 3: Exergy loss per kilogram of ethanol and exergeric efficienties (%) for each step.
Finally, it could also be deduced from the exergy analysis results indicated in Figure 3 that Distillation step
presented lower exergetic efficiency than the steps mentioned in the previous paragraph for all cases
(58,80%, 64,93% y 66,04% for case 1, 2 y 3 respectively). This is due to the energy requirement for
distillation towers.
5. Conclusions
Case 3 show the highest overall exergeric efficiency (31.83%), the highest ethanol production (0.36 kg
Ethanol / kg residual biomass) and the lower exergy loss per kilogram of ethanol (57.83 MJ / kg ethanol)
followed by Case 2 (30.43%, ethanol 0.35 kg / kg residual biomass, 61.73 MJ / kg ethanol) and Case 1
(27.73% ethanol, 0.31 kg / kg residual biomass, 70.37 MJ / kg ethanol).
Cellulose hydrolysis on Cases 1 and 2, and fermentation on Case 3 show the lowest exergetic efficiency of
52.49% and 55.80% respectively.
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