Bioresource Technology 104 (2012) 367–372
Contents lists available at SciVerse ScienceDirect
Bioresource Technology
journal homepage: www.elsevier.com/locate/biortech
Process model and economic analysis of ethanol production from sugar beet
raw juice as part of the cleaner production concept
Damjan G. Vučurović ⇑, Siniša N. Dodić, Stevan D. Popov, Jelena M. Dodić, Jovana A. Grahovac
Faculty of Technology, Department of Biotechnology and Pharmaceutical Engineering, University of Novi Sad, Boulevard cara Lazara 1, 21000 Novi Sad, Serbia
a r t i c l e
i n f o
Article history:
Received 16 July 2011
Received in revised form 13 October 2011
Accepted 22 October 2011
Available online 4 November 2011
Keywords:
Biofuels
Ethanol
Model
Economics
Fermentation
a b s t r a c t
The batch fermentation process of sugar beet processing intermediates by free yeast cells is the most
widely used method in the Autonomous Province of Vojvodina for producing ethanol as fuel. In this study
a process and cost model was developed for producing ethanol from raw juice. The model can be used to
calculate capital investment costs, unit production costs and operating costs for a plant producing 44 million l of 99.6% pure ethanol annually. In the sensitivity analysis the influence of sugar beet and yeast
price, as well as the influence of recycled biomass on process economics, ethanol production costs and
project feasibility was examined. The results of this study clearly demonstrate that the raw material costs
have a significant influence on the expenses for producing ethanol. Also, the optimal percentage of recycled biomass turned out to be in the range from 50% to 70%.
Ó 2011 Elsevier Ltd. All rights reserved.
1. Introduction
Ethanol has experienced unseen levels of attention due to its
value as fuel alternative to gasoline, the increase of oil prices,
and the climatic changes, besides being a renewable and sustainable energy source, efficient and safe to the environment (Mussatto
et al., 2010). The processing of sugar beet toward bioethanol could
be a convenient process, but is important to emphasize that, to be a
viable alternative, bioethanol must present a high net energy gain,
have ecological benefits, be economically competitive and able to
be produced in large scales without affecting the food provision
(Šantek et al., 2010). Although ethanol production process models
by different techniques and from different resources such as sugarcane (Quintero et al., 2008), corn (Kwiatkowski et al., 2006; Li et al.,
2010; Lin et al., 2011a,b), wheat (Francis, 2006), soybean (Sequeira
et al., 2008), barley (Nghiem et al., 2011), lignocellulosic feedstock
(Morales-Rodriguez et al., 2011) and even glycerol (Posada and
Cardona, 2010) are more frequent, the favourable and most accessible resource for the region of Southeastern Europe is sugar beet
(Icoz et al., 2009; Krajnc et al., 2007).
According to Van der Poel et al. (1998) the sucrose content in
raw juice is between 13.5% and 19.5%. However, the sugar content
of raw juice from domestic sugar factories is significantly lover
(11.0–14.0%) due to the bad quality of sugar beet, which is a result
of inappropriate application of agrotechnical measures over the
past few decades (Milić et al., 2006). For this reason significantly
⇑ Corresponding author. Tel.: +381 21 4853682; fax: +381 21 450413.
E-mail address: dvdamjan@uns.ac.rs (D.G. Vučurović).
0960-8524/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved.
doi:10.1016/j.biortech.2011.10.085
greater amount of water is being used during the extraction of sugar from sugar beet cassettes and therefore a low concentration of
sucrose in raw juice is inevitable (Hinkova and Bubnik, 2001).
The Autonomous Province of Vojvodina has great potential for
producing energy from renewable resources. Energy production
from renewable resources in the Autonomous Province of Vojvodina is in the early stages and therefore requires an adequate approach and strategic planning (Dodić et al., 2010). Together with
the technological modernisation and energy efficiency increase,
the use of renewable energy resources is one of the priorities and
the Autonomous Province of Vojvodina as part of the Republic of
Serbia, which is a signatory to the Kyoto Protocol, has committed
to increase the share of energy produced from renewable resources
from 1% to 20% by 2012.
The Republic of Serbia has about 5.092 million ha of agricultural
land (0.68 ha per capita) of which 4.218 million ha is arable land
(0.56 ha per capita), which is above the standards of European
countries. About 10% of arable land belongs to the state and
state-owned enterprises, while 90% is privately owned (Bulletin
523, 2010). Suitable soil and climatic conditions allow the development of diversified agricultural plants, i.e. the cultivation of cereals, industrial crops, fruits and vegetables, seed and planting
material and medicinal plants.
The total sugar consumption per capita is about 25–30 kg which
is, in the Republic of Serbia, on an annual basis about 240,000 tons
of sugar. However, production capacities of domestic sugar factories are much higher than the total sugar consumption. Since the
estimates for 2011 for sugar beet yield are 48 Mg/ha, a total sugar
beet production of 3206,919 Mg or about 480,000 Mg of produced
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D.G. Vučurović et al. / Bioresource Technology 104 (2012) 367–372
sugar is expected (Report SRB233 PO15, 2011). This means that besides the annual sugar consumption of 240,000 Mg and the maximum annual export of sugar to the EU of 180,000 Mg there is
still a surplus of 60,000 Mg of sugar, i.e. 520,000 Mg of raw juice
that can be used for bioethanol production.
The work presented here, thus, provides a simulation solution
for a bioethanol production plant with minimal waste generation.
A sensitivity analysis was also performed to examine the effect of
sugar beet and yeast price on the final ethanol production cost. The
effect of the amount of recycled biomass on process economics was
also examined. The process and cost models were developed using
SuperPro DesignerÒ software version 6.0 (Intelligen Inc., Scotch
Plains, NJ), a simulation programme that is able to estimate both
process and economic parameters.
2. Methods
2.1. Process overview
The simplified process flow sheet of ethanol production from
sugar beet raw juice is shown in Fig. 1. During campaign, the raw
juice generated after the extraction of sugar beet cassettes in a sugar production plant is charged directly into the fermentor. Since
sugar beet is harvested for a short period each year, long term storage is required to provide feed to the factory. However, raw juice is
known for its low storability and easy decomposition by the action
of microorganisms (Dodić et al., 2009) so raw juice needs to be
concentrated by multiple effect evaporators to a high sugar concentration to reduce storage volume and inhibit microbial growth.
These evaporators are taken into account in this process model
(not shown in Fig. 1) even though they are part of the sugar factory,
which is located near the ethanol production plant. Therefore, during the rest of the year, the concentrated raw juice needs to be diluted before use.
Commercial baker’s yeast Saccharomyces cerevisiae is used as
the biocatalyst, i.e. will ferment sugars to ethanol and other
by-products. Six vessels are used in stagger mode as fermentors.
After fermentation the broth is sent to centrifugation for biomass
separation. The solid fraction, mostly containing yeast cells, is then
split in two ways, one going back as inoculum for the following
fermentation process and the other is sent to further processing.
The fractions of recycled biomass, that were considered in this
work, are 10%, 30%, 50%, 70% and 90%. On the other hand, the liquid
fraction of the centrifugation operation is sent to distillation and
molecular sieve adsorption to recover ethanol and produce 99.6%
ethanol. Distillation is accomplished in two columns. The first column removes the dissolved CO2 and most of the water, while the
second concentrates the ethanol to a near azeotropic composition.
All the water from the nearly azeotropic mixture is removed by vapour phase molecular sieve adsorption. Finally, the 99.6% pure ethanol vapour is cooled by heat exchange, condensed and pumped to
storage.
Fermentation vents (off gas containing mostly CO2, water and
also some ethanol) as well as the beer column vent are scrubbed
in a water scrubber, recovering nearly all of the carbon dioxide.
The bottoms from the first distillation contain all the unused organic matter (sources of sugar, nitrogen, etc.). This stillage is concentrated in a multiple effect evaporator using waste heat from
the distillation. The concentrated syrup from the evaporator is
mixed with the portion of the split biomass not sent back to the
fermentation section and fed to a rotary drum dryer where it is
dried to produce the co-product which will be sold as animal feed.
On the other hand, the evaporated condensate from the stillage
concentration operation is mixed together with the bottoms from
the second distillation, the liquid outlet of the molecular sieves
and the liquid outlet of the scrubber, and reused as process water,
due to the relatively low content of organic matter in these
streams. One twentieth of this water is sent back to the scrubber,
while the rest is used for diluting the concentrated raw juice (from
storage) before fermentation.
2.2. Process design
Input data and data on operating conditions of the examined
process are obtained from literature, while equipment and process
data are obtained directly from the SuperPro Designer software.
The raw juice requirement for the plant is 300 Mg per batch,
which is obtained by dividing the potential annual surplus of raw
juice in Vojvodina (Report SRB233 PO15, 2011) with the maximum
number of batches per year predicted by the model. The fermentable sugar content in the raw juice is set to 12.5% by diluting the
concentrated storage juice, since this concentration proved to be
Fig. 1. Simplified process flow diagram of ethanol production from sugar beet raw juice.
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D.G. Vučurović et al. / Bioresource Technology 104 (2012) 367–372
optimal for ethanol production from raw juice (Popov et al., 2010).
Ash and protein content in the raw juice is set to 0.03% and 0.01%,
respectively, according to the average composition of raw juice
from several domestic sugar production plants (Popov et al., 2010).
Initial inoculum concentration is set to be about 10% of biomass
quantity in relation to the amount of cultivation media. Fermentation is conducted in six 385,000 L (16.5 m height and 5.5 m diameter) vessels. The process time is 20 h and the set temperature is
28 °C for the sugar fermentation. The reactions and conversions
in the process of fermentation are defined by Popov et al. (2010).
The effective ethanol concentration in the fermentation broth is
6.15% while the sugar concentration is 0.23%.
Fermentation broth is sent to a disc-stack centrifuge in order to
remove most of the biomass (throughput 157,000 L/h). The biomass stream is then split (throughput 20,000 kg/h) and one part
(base case 50%) is sent to drying while the other is sent back to
the fermentation section. After centrifugation the liquid fraction
is sent to a distillation column with a height of 13.4 m and diameter 5.3 m, that operates in a mode to remove the CO2 and as little
ethanol as possible overhead, while removing about 86% of water
to the bottoms (Aden et al., 2002). The reflux ratio is 3:1. The overhead of the distillation column is vented and contains 91.61% CO2,
8.13% ethanol and 0.25% water. All of the CO2 and only 3.97% of
ethanol are vented here. Over 96% of the ethanol fed is removed
as a 33.6% mixture with water.
The ethanol mixture with water is removed as a vapour side
draw from the column and fed directly to the rectification column
which has a working volume of 4900 L. A vapour overhead mixture
of 92.5% ethanol is obtained while the composition of the bottoms
is 0.31% ethanol. Only 0.6% of the ethanol fed is lost in this
operation.
Overhead vapour from the rectification column is fed to the
molecular sieve adsorption unit. The adsorption column removes
95% of the water (Aden et al., 2002). The 99.6% pure ethanol is
cooled to 20 °C by heat exchange with a heat transfer area of
280 m2 and finally pumped to storage. The heat transfer agent is
chilled water while the heat transfer coefficient is 860.44 W/m2 K.
A scrubber with a volume of 25,500 L (height 12.8 m and diameter 1.6 m) is used to remove ethanol and water from the fermentation and distillation vents so as to recover pure CO2. The stillage
from the distillation column is concentrated in the evaporator with
a heat transfer area of 75.6 m2 and saturated steam as transfer
agent, removing over 90% of water which is used as process water
after condensation. Part of the biomass sent to drying is mixed
with the syrup obtained after evaporation (throughput 22,400 kg/
h) prior to being sent to drying. The drying is carried out in a rotary
drum with a drying capacity of 996 kg/h, drum area 85.5 m2 and air
as drying gas (Kwiatkowski et al., 2006). Rectification bottoms and
molecular sieve liquid outputs are mixed with an operating
throughput of 59,000 kg/h and then mixed with the evaporation
condensate and the scrubber liquid outlet giving a total of
280,000 kg/h process water that can be recycled. One part
(15,000 kg/h) of this water is reused in the scrubber, while the rest
is used to dilute the concentrated raw juice for the following fermentation process.
The design basis is 34.8 million kg (44 million l) of 99.6% pure
ethanol per year, which is produced from 564,000 Mg of raw juice.
The cost model reflects economic conditions in the second half of
2010.
2.3. Process analysis
Economic analysis was performed for the proposed process
model and is given as an executive summary of project indices.
Sensitivity studies were also performed for this process model at
various sugar beet costs and yeast costs. The cost of sugar beet se-
lected for this study ranged from $0.017/kg to $0.029/kg. This
range was selected because of the fluctuations of its purchase price
in the period of 2000–2009 (Price Report, 2010). Yeast cost depends from the quantity needed, so its purchase price offered from
a local yeast production plant ranged from $1.144/kg to $1.43/kg.
Finally, the influence of the biomass split factor on economic
parameters was examined.
3. Results and discussion
3.1. Economic analysis
The results of the economic analysis are shown in Table 1. The
individual components (capital investment cost, operating cost and
unit production cost) are discussed in the following paragraphs.
The total capital investment cost for this production plant is obtained by adding together the values of the direct fixed capital
(DFC), working capital and start-up and validation costs. DFC represents the sum of the total plant cost (TPC) and costs for contractor’s fees and contingency (CFC). Further, the TPC consists of the
total plant direct cost (TPDC) and the total plant indirect cost
(TPIC). While the TPIC depends on the costs for engineering and
construction, the TPDC expenses include the costs for equipment
purchase, installation, process piping, instrumentation, insulation,
Table 1
Economic analysis of the proposed process model.
Capital investment cost ($)
Direct fixed capital DFC = TPC + CFC ($)
Total plant cost TPC = TPDC + TPIC ($)
Total plant direct cost TPDC ($)
Equipment purchase cost ($)
Fermentors ($)
Disc-stack centrifuge ($)
Batch distillation vessel ($)
Scrubber ($)
Rectification column ($)
Molecular sieves ($)
Evaporators ($)
Rotary drum dryers ($)
Condenser ($)
Unlisted equipment ($)
Installation ($)
Process piping ($)
Instrumentation ($)
Insulation ($)
Electrical ($)
Buildings ($)
Yard improvement ($)
Auxiliary facilities ($)
Total plant indirect cost TPIC ($)
Engineering ($)
Construction ($)
Contractor’s fee & contingency CFC ($)
Contractor’s fee ($)
Contingency ($)
Working capital ($)
Start-up and validation cost ($)
68,778,000
64,080,000
55,722,000
34,826,000
10,896,000
3000,000
1475,000
478,000
57,000
525,000
2700,000
548,000
966,000
57,000
1090,000
4644,000
3269,000
4141,000
327,000
1090,000
4685,000
1634,000
4141,000
20,896,000
8707,000
12,189,000
8358,000
2786,000
5572,000
1494,000
3204,000
Operating cost ($/year)
Raw materials ($/year)
Yeast ($/year)
Raw juice ($/year)
Facility-dependent ($/year)
Labour ($/year)
Laboratory/QC/QA ($/year)
Utilities ($/year)
Electricity ($/year)
Steam ($/year)
Chilled water ($/year)
Co-production
20,982,000
2037,000
424,000
1612,000
7068,200
6968,100
278,500
7427,200
4118,600
995,600
2313,000
2797,000
Unit production cost ($/kg)
0.603
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electrical, building, yard improvement and auxiliary facilities. The
purchasing cost for major equipment items listed in Table 1 is
based on offers from the suppliers of equipment or taken from
the report of Aden et al. (2002). If the capacities of the equipment
in the model were different from the equipment capacities offered
by the suppliers, the cost was corrected by using the Rule of Sixtenths (Dysert, 2003). The following equation expresses this rule:
CB ¼ CA
0:6
SB
SA
ð1Þ
where CB is the approximate cost ($) of equipment having size SB (L,
m3, or whatever) and CA is the known cost ($) of equipment having
corresponding size SA (same units as SB). Besides capacity, the type
of construction material and specific characteristics of the equipment can change the purchasing equipment cost (Nghiem et al.,
2011).
The estimated capital cost for this case is $68,778,000, which is
over $20 million more than the capital costs determined for a corn
to ethanol production plant by Kwiatkowski et al. (2006). This difference exists because this group of authors had an industry feedback to estimate the total capital investment cost as approximately
three times the sum of individual equipment purchase cost and
installation expenses. By applying the same calculation method
as Kwiatkowski et al. (2006) to this case the capital cost data would
match, i.e. the capital investment would be nearly the same.
Operating costs are calculated by summing the raw material
and utility costs, costs that are facility-dependent (equipment
availability, maintenance, insurance, local taxes, etc.), labour costs
and laboratory, quality control (QC) and quality assurance (QA) expenses, and subtracting a credit for the sale of co-products (Table 1). Compared to the annual ethanol production costs from
molasses (Sobočan and Glavič, 2000), the operating costs of producing ethanol from raw juice are slightly lower. This difference
exists due to the fact that molasses is a by-product, while raw juice
is a intermediate product of sugar beet processing, i.e. molasses is
obtained from raw juice after its purification (micro and ultra filtration), concentration (evaporation) and multistage crystallization. In other words, the operating costs are higher for molasses
to ethanol production because of these additional operations.
The primary feedstock for the facility is raw juice. Yeast that ferments the glucose into ethanol and carbon dioxide is also required.
The quantities of materials required are provided by the process
model and their unit costs have been incorporated into the model.
Information about various feedstock prices can be collected from
the Statistical Office of the Republic of Serbia.
Electricity, steam and chilled water are the utilities required in
the process. Utility requirements of the various equipment operations are calculated and summed within the programme. These
utilities are treated as purchased utilities and the unit costs for
each of them were set based on 5 year average market prices.
The 5 year average market prices (2009–2005) of steam ($2.10/
Mg), chilled water ($0.30/Mg) and electricity ($0.10/kWh) are obtained from the annual reports of the Power Industry of Serbia1
and used in the process model.
Three products are produced in the conversion of raw juice to
ethanol. They are ethanol as the main product, and animal feed
and carbon dioxide as co-products. The ethanol can be sold to be
blended with fossil fuels. Current pricing for it is available from
the Biomass Action Plan (2010). The assumed ethanol price in this
work is 0.75 $/kg (0.59 $/L). The animal feed is sold and its value
is strongly dependent on its protein content and is related to the
value of other protein-based animal feeds. The animal feed pro1
Power Industry of Serbia, Annual Reports from 2005 till 2009. Database at http://
www.eps.rs/Pages/FolderDocs.aspx?list=Godisnji%20Izvestaji, accessed at June 2011.
duced in this process has a protein content of approximately 21%
and its value, based on its proteins content, is estimated to be
$0.07/kg (Belyea et al., 2004). The second co-product, carbon dioxide, is economically viable only if it is collected from the scrubber
and sold to a third party at the plant site for further purification
and distribution to the food processing companies and manufacturers of carbonated beverages. In this case its value to the ethanol
producer is $15 per metric ton (Kwiatkowski et al., 2006).
A breakdown of the costs to produce ethanol with the values
used in this model case is illustrated in Fig. 2. It shows that the unit
production cost of ethanol is approximately $0.603/kg, which corresponds with the results reported by Sobočan and Glavič (2000).
Fig. 2 also shows that the income from the sale of animal feed reduces the ethanol production costs, and is a major factor in operating costs. Since the cost of sugar beet can fluctuate due to market
and weather conditions, the influence of sugar beet cost was also
examined in the sensitivity study.
3.2. Sensitivity study
For this process model the simulation software gave an executive summary of the project calculating the project indices shown
in Table 2. Gross margin represents a company’s total sales revenue minus its cost of goods sold, divided by the total sales revenue,
expressed as a percentage. This number represents the proportion
of each dollar of revenue that the company retains as gross profit.
For this process the gross margin is 18.01%, which means the company would retain $0.18 from each dollar of revenue generated.
The ROI (Return of Investment) is a performance measure used
to evaluate the efficiency of an investment. ROI is a very popular
metric because of its versatility and simplicity. That is, if an investment does not have a positive ROI, then the investment should not
be undertaken. The length of time required to recover the cost of an
investment can be calculated on the basis of the ROI. Table 2 shows
that the payback time is approximately 7.5 years, which is quite
acceptable. NPV (Net Present Value) represents the difference between the present value of cash inflows and the present value of
cash outflows. It is used to analyse the profitability of an investment through considering the time-value of the earned money, because a dollar that is earned in 5 years time has a lower value than
a dollar earned today (Heinzle et al., 2006). If the NPV of a prospective project is positive (like in Table 2) with assuming a discount
interest of 7%, it should be accepted and realised. The IRR (Internal
Rate of Return) is a discount rate often used in capital budgeting
that makes the NPV of all cash flows from a particular project equal
to zero. In other words the higher a project’s IRR, the more desir-
Fig. 2. Ethanol production cost breakdown.
D.G. Vučurović et al. / Bioresource Technology 104 (2012) 367–372
Table 2
Project indices of the ethanol production process model.
Project indices
Value
Gross margin (%)
Return on Investment (%)
Payback time (years)
Internal Rate of Return after taxes (%)
Net Present Value at 7.00% ($)
18.01
13.41
7.46
7.73
2955,000
371
able it is to undertake the project. This project yields an after-tax
IRR of 7.73%, with income taxes set to 40%. Based on these results,
with a project lifetime of 25 years and depreciation period of
10 years with a salvage value 5% DFC, this project represents a very
attractive investment, i.e. the examined system is economically
viable.
The influence of sugar beet and yeast price on ethanol production costs is shown in Fig. 3. It can be seen that lower sugar beet
and yeast costs result in lower unit production costs. Also, the sugar beet cost has a much higher impact on the expenses of producing ethanol.
However, depending on the market conditions the management
can regulate the split factor and decide how much biomass is going
to drying (animal feed) or back to fermentation after centrifugation. The effect of the biomass split factor on economic parameters
is shown in Fig. 4. By recycling more biomass reduces the quantity
of yeast needed for fermentation and lowers the costs for purchasing yeast (even if the price is higher for smaller quantities) but on
the other hand causes lower income for selling animal feed (coproduct). Still, the total revenues vary only by $1,000,000 per year
depending on the split factor. However, the ethanol production
costs are higher with the increase of recycled biomass. Because
of the greater curve slope of the unit production cost for the values
of the split factor in the range from 50% to 70% and based on the
highest IRR this range would be optimal for varying the biomass
split factor.
4. Conclusion
Fig. 3. The effect of sugar beet and yeast cost on ethanol production cost.
The process model developed here reflects the base case for a
44 million l/year fuel ethanol plant. A cost model has been developed for economic analysis of this ethanol production from sugar
beet raw juice. A sensitivity study has been performed to examine
the effects of sugar beet and yeast costs on ethanol production
costs. The effect of the amount of recycled biomass on process economics was also examined. The benefits of obtaining lower unit
production costs due to lower prices of sugar beet and yeast were
clearly demonstrated. The optimal percentage of recycled biomass
proved to be between 50% and 70%.
Acknowledgements
This study is part of the project (TR-31002) which is supported
by the Ministry of Education and Science of Serbia. The authors are
grateful for the financial support.
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