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Techno-economic evaluation of redox potential-controlled ethanol fermentation processes
Journal of the Taiwan Institute of Chemical Engineers 43 (2012) 813–819
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Journal of the Taiwan Institute of Chemical Engineers journal homepage: www.elsevier.com/locate/jtice
Techno-economic evaluation of redox potential-controlled ethanol fermentation processes Fei Yu a, Yen-Han Lin b,* a b
Division of Environmental Engineering, University of Saskatchewan, 57 Campus Drive, Saskatoon, SK, Canada S7H 5A9 Department of Chemical Engineering, University of Saskatchewan, 57 Campus Drive, Saskatoon, SK, Canada S7H 5A9
A R T I C L E I N F O
A B S T R A C T
Article history: Received 8 December 2011 Received in revised form 11 May 2012 Accepted 12 May 2012 Available online 15 June 2012
Nine redox potential-controlled operating conditions during ethanol fermentation were evaluated by means of a process simulator. Results show that the lowest unit production cost (0.764 $/kg ethanol) was estimated for 250 g glucose/L among all studied conditions. Controlling the redox potential at 150 mV increases the ethanol yield when glucose concentrations are greater than 250 g/L; while no significant effects were observed at glucose feeds below 250 g/L. For a facility with an annual production capacity of 85–130 million kg ethanol, the shortest payout period of 5.33 years was obtained under 250 g glucose/L conditions, either with or without redox potential control. If 300 g glucose/L is applied, controlling the redox potential at 150 mV is required to limit the process payout period to be less than 6 years. Carbon dioxide disposal options are presented. Selling CO2 as a byproduct can bring in 1.43 million $/year income for an ethanol plant with a capacity of 100 million kg ethanol/year. Capture and transport of CO2 to deep injection sites for geological underground storage is economically unprofitable and adds 4.78 million $/year in processing costs; however, this option results in a net removal of CO2 from the atmosphere, making it environmentally preferable. The presented process model is available upon request. ß 2012 Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
Keywords: Techno-economic evaluation Very-high-gravity fermentation Redox potential control Ethanol CO2 storage
1. Introduction Ethanol is widely used as a fuel, solvent, disinfectant, medicine, and feedstock for the synthesis of other chemical products. Ethanol has a high octane number and high latent heat of vaporization, and it can be blended with gasoline to use as a transportation fuel. More importantly, bio-ethanol has environmental advantages compared to fossil fuels, as the future energy supply must comply with efforts to substantially reduce greenhouse gas emissions [1]. Alcoholic fermentation on industrial scale is mainly a conversion process of glucose to ethanol using active dry yeast (Saccharomyces cerevisiae). In the past few decades, ethanoltolerant strains of S. cerevisiae have become available for industrial fermentation, allowing fermentation under very high concentrations of carbohydrates. Usually, sugar concentrations in excess of 200 g/L are not used under industrial conditions because increasing concentrations of ethanol retard the growth of yeasts and fermentation eventually arrests [2]. However, the industrial yeast strains used in bio-ethanol fermentation can grow, albeit at lower rates, in fermentation broths with initial glucose concentrations of 300 g/L [3]. Generally, very-high-gravity (VHG) fermentation
* Corresponding author. Tel.: +1 306 966 4764. E-mail address: [email protected] (Y.-H. Lin).
means bio-ethanol fermentation with a glucose feeding concentration greater than 250 g/L. In recent years, it is becoming more common for bio-ethanol fermentation to be handled by a process simulator [1,4–7]. The whole fermentation process can be simulated by computers for financial analysis, including capital and operating costs, revenues, earnings, and return on investment. Many relevant fermentation process parameters can be adjusted to facilitate simulations of the industrial process in conjunction with lab data. Process simulations can be conducted for the whole bio-ethanol fermentation process from raw materials, such as corn to ethanol [4,6], or simply the corn milling, liquefaction, and saccharification process [5,8–10]. In some ethanol facilities, CO2 produced during the fermentation process is released to the atmosphere. CO2 can also be captured and sold, although this byproduct typically does not significantly affect economic evaluation [7]. Alternatively, CO2 produced during fermentation can be injected into deep geological formations (aquifers or reservoirs) for geological storage, to reduce CO2 emissions to the atmosphere [11–15]. In this study, data collected from redox potential-controlled fermentations [15] were used to carry out an economical analysis by means of process simulation. A process simulator was used to evaluate operating conditions that provide the highest possible profit from a VHG fermentation process. A simulation model for an ethanol plant with a capacity of 85–130 million kg ethanol/year
1876-1070/$ – see front matter ß 2012 Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.jtice.2012.05.002
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has been developed using Aspen Plus 2006 based on [6], and evaluated using Aspen Icarus Process Evaluator (IPE) 2006. This model is capable of estimating both process and economic parameters, which are consequently used to explore the most profitable redox potential-controlled fermentation settings under VHG conditions. The Aspen Plus model is available upon request. 2. Materials and methods 2.1. Fermentation and redox potential measurement Methods for fermentation and redox potential measurements were reported in our previous study [15]. Briefly, an industrial S. cerevisiae strain (Ethanol RedTM obtained from the Lesaffre Yeast Corp. Milwaukee, MI, USA) was pre-cultured overnight and cultivated in a jar fermenter with a 1-L working volume (model: Omni culture fermenter, New York, NY, USA). The inoculums’ level was 5%, and fermentation was operated in batch mode. Each fermenter was equipped with an autoclavable redox potential electrode that was custom-made and ordered through Cole-Palmer Inc. (12 mm 250 mm, Vernon Hills, IL, USA), and the fermentation temperature was set at 32 8C. Data were acquired by using LabView (Version 8.5, National Instrument, Austin, TX, USA), and a PID control algorithm was implemented to control the redox potential as desired levels: no control, 150 mV, and 100 mV. The agitation rate was kept at 150 rpm for all runs. If the measured redox potential was lower than the set-point value, sterilized air was provided to fermenter to raise the redox potential to the desired level. The fermentation broth was sampled every 6 h. A high performance liquid chromatograph (HPLC) equipped with a refractive index (RI) detector was used to quantify the residual glucose, ethanol, and other metabolites. 2.2. Process description The block diagram of the process model used in this study is illustrated in Fig. 1. This model was modified from [6], and the relevant simulation parameters were determined based on our previous work [15]. This simulation focused on the economical effects of varied glucose feeding concentrations and redox potential controls on ethanol production. In this model, the glucose concentration in the feed stream to the fermenter was manipulated by varying the starch content in
Grain
Milling
the grain stream feeding the milling module (Fig. 1). The milling module is a separation process and the liquefaction module is a heating process, and no chemical reactions are defined in either stage. However, one reaction is defined in the saccharification module: starch þ water ! glusose
The above equation defines the molecular relation of the reaction from starch to glucose, where one molecule of starch and one molecule of water produce one molecule of glucose. Starch in this model is a predefined pure component with a molecular weight of 162.14. It should be mentioned that starch is a polysaccharide which can be hydrolyzed to thousands of glucose molecules. Eq. (1) is not a description of a chemical reaction, but rather the mass relationships of components conversion. In the fermenter, two reactions are defined: glusose ! a CO2 þ a ethanol þ b YDM
YDM ! 1:13635848 protein
(3)
where YDM is a predefined component standing for yeast dry matter [6]. a and b in Eq. (2) are the molar coefficients of the reaction, determined based on results of lab fermentation experiments before simulation. The constant 1.13635848 in Eq. (3) is the predefined mass coefficient calculated according to the predefined molecular weight of YDM and protein [6]. After fermentation, the beer is sent to an aging tank, where most of the CO2 (over 98.7% in the feed) is separated from the beer, and then to a degasser, where further CO2 is removed (70% of the leftover CO2 in the beer). The beer is then sent into the distillation section, which includes a beer column and a rectifier. The top output stream of the degasser is transitioned to a condenser to recover most of the ethanol (around 80% in the feed). This condensed stream is also sent to the beer column for further separation. The beer column is a primary separation process unit, separating most of the ethanol (over 99.7% in its feed stream) from the fermenter’s output stream together with a certain amount of water. This stream, mainly composed of ethanol and water, is then sent to a rectifier connected to a molecular sieve for further ethanol–water separation. The molecular sieve overcomes the limitation of the distillation process to yield the main product
Saccharification
Degas
Age Tank
Fermentor
CO 2 CO 2 Scrubber
Beer Column
Centrifuge
(2)
and
Liquefaction
Condense
(1)
Rectifier
Evaporation
Molecular Sieve
DDGS Dryer
Ethanol
DDGS
Fig. 1. Block diagram for redox potential-controlled very-high-gravity ethanol fermentation.
F. Yu, Y.-H. Lin / Journal of the Taiwan Institute of Chemical Engineers 43 (2012) 813–819
stream with a high ethanol concentration. Molecular sieves are applied to separate the azeotrope of water and ethanol (ethanol:water = 95.6:4.4 (w/w)). With recycling, the ethanol concentration in the output stream reaches over 99.25 wt%. The bottom stream of the beer column is sent to a centrifuge and then a dryer to yield distiller’s dried grains with solubles (DDGS), which is the main byproduct of this ethanol production process. It should be noted that under mill conditions, protein and other solids content in the feed stream to the milling section proportionally change when the starch content is varied. However, because variations of protein and other solids content in the feed stream have no significant influence on economic evaluation results, they remain unchanged in simulated scenarios in order to precisely manipulate the glucose concentration in the feed stream of the fermenter. The top output streams of the aging tank and condenser, which are rich in CO2, are sent to a CO2 scrubber where the liquid portion of the feeds is absorbed by water and the majority of the CO2 (over 99.8%) produced during the fermentation process is gathered for emission, capture, or deep injection. In this model, CO2 produced during the fermentation process is assumed to be captured after treatment in the CO2 scrubber and sold as a byproduct. As discussed below, the captured CO2 stream can also be compressed and transported by pipelines to deep injection sites for geological storage. 2.3. Process design parameters The annual production rate of the process is considered to be 85–130 million kg ethanol/year, depending on the glucose concentration fed to the fermenter. The annual operating time of the plant is designed to be 7920 h (330 days).
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Table 1 Costs used in the economic evaluation. Purchase price ($/kg) Raw materials Corn Water Acid a-Amylase Urea Yeast Products Ethanol Dry DDGS CO2
Selling price ($/kg)
0.248183 0.000044 0.153000 2.250000 0.353020 5.510000 0.724419 0.175334 0.015940
01803, USA). Physical properties of the components were obtained from the Aspen Plus 2006 databank or defined by the user. Material and energy balance calculations were performed by Aspen Plus, and economic evaluation of the process was carried out by the Aspen IPE (Aspen Technology, Inc., 200 Wheeler Road, Burlington, MA 01803, USA). Table 1 lists costs used in the economic evaluation. The purchase price of corn is an average value of the price from the previous six months (September 2010–February 2011) obtained from ‘‘Index Mundi’’ (http://www.indexmundi.com/commodities/ ); selling prices of ethanol and DDGS are also average values of the price from the previous six months (September 2010–February 2011) according to the Economic Research Service of United States Department of Agriculture (ERS/USDA); other costs were obtained from the literature or online searches. In addition, the selling price of the DDGS byproduct stream was calculated according to the stream’s moisture content.
2.4. Reaction coefficients 3. Results and discussion In the simulation, different fermentation conditions were applied by manipulating the reaction coefficients a, b in Eq. (2), as well as its reaction extent. a is the molar ratio of ethanol yield over depleted glucose, which are measured by lab experiments under certain applied conditions; b is dependent on a to ensure mass balance of the reaction. Note that 1.13635848 in Eq. (3) is an approximate value of the molecular weight ratio of YDM (150.13) to protein (132.115). The reaction extent of Eq. (1) was set to 0.99, according to [6]. The reaction extent of Eq. (2) is the mass ratio of depleted glucose over total feed glucose measured under certain applied conditions. The reaction extent of Eq. (3) is fixed at 0.6, according to [4]. 2.5. Simulation tool The simulation model was created using Aspen Plus 2006 (Aspen Technology, Inc., 200 Wheeler Road, Burlington, Massachusetts
During the process simulation, the effects of glucose feeding concentration (200 4.99, 250 3.95, and 300 6.42 g/L) and redox potential settings (no control, 150, and 100 mV) were investigated. Note that the numerical value followed by sign indicates one standard deviation. The general results of the economic evaluation are shown in Table 2, and the breakdown of unit production costs for each investigated case is provided in Table 3. The selected range of glucose concentration is stoichiometrically equivalent to 12–20% (v/v) ethanol. 3.1. Sales analysis The sales analysis results of all scenarios (varied glucose feeding concentrations and redox potential settings) are listed in Table 4. Ethanol is the main product of the process, while DDGS and CO2 are byproducts (selling prices of which are presented in Table 1).
Table 2 Results of the economic evaluation. Different glucose concentrations in the feed stream are denoted as: A = 300 6.42 g/L, B = 250 3.95 g/L, C = 200 4.99 g/L. Different redox potential control levels are denoted as: a = no control, b = 150 mV, c = 100 mV.
Aa Ab Ac Ba Bb Bc Ca Cb Cc
Production rate (106 kg ethanol/year)
Unit production cost ($/kg ethanol)
Annual operation cost (106 $/year)
Total product sales (106 $/year)
124.65 131.93 115.71 118.98 115.84 118.84 86.54 87.68 85.71
0.825 0.780 0.888 0.757 0.777 0.758 0.885 0.873 0.893
102.87 102.93 102.79 90.08 90.06 90.08 76.56 76.56 76.56
117.97 119.45 116.36 106.40 106.24 106.39 84.42 84.53 84.34
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Table 3 Breakdown of unit production costs for each case; all values in $/kg ethanol. Different glucose concentrations in the feed stream are denoted as: A = 300 6.42 g/L, B = 250 3.95 g/L, C = 200 4.99 g/L. Different redox potential control levels are denoted as: a = no control, b = 150 mV, c = 100 mV. Cost item ($/kg ethanol)
Aa
Ab
Ac
Ba
Bb
Bc
Ca
Cb
Cc
Raw material cost Utilities cost Operating labor cost Maintenance cost Operating charges Plant overhead G and A cost
0.738 0.012 0.007 0.001 0.002 0.004 0.061
0.698 0.012 0.007 0.001 0.002 0.004 0.058
0.795 0.012 0.008 0.001 0.002 0.004 0.066
0.676 0.011 0.008 0.001 0.002 0.004 0.056
0.694 0.011 0.008 0.001 0.002 0.004 0.058
0.676 0.011 0.008 0.001 0.002 0.004 0.056
0.788 0.012 0.011 0.001 0.003 0.006 0.066
0.777 0.012 0.010 0.001 0.003 0.006 0.065
0.795 0.012 0.011 0.001 0.003 0.006 0.066
Total
0.825
0.780
0.888
0.757
0.777
0.758
0.885
0.873
0.893
Table 4 Sales analysis for each applied condition. Different glucose concentrations in the feed stream are denoted as: A = 300 6.42 g/L, B = 250 3.95 g/L, C = 200 4.99 g/L. Different redox potential control levels are denoted as: a = no control, b = 150 mV, c = 100 mV.
Aa Ab Ac Ba Bb Bc Ca Cb Cc
Total operating cost (million $/year)
Total product sales (million $/year)
Payout period (years)
102.87 102.93 102.79 90.08 90.06 90.08 76.56 76.56 76.56
117.97 119.45 116.36 106.40 106.24 106.39 84.42 84.53 84.34
6.08 5.71 6.59 5.32 5.35 5.32 8.47 8.39 8.52
Payout period is the expected number of years required to recover the original investment in the project. This parameter indicates the length of time that the facility needs to operate in order to recover the initial capital investment (total capital cost plus working capital). The results shown in Fig. 2 suggest that for an ethanol plant with a capacity of 85–130 million kg ethanol/year,
maintaining the glucose feeding concentration to the fermenter at around 250 g/L results in the shortest payout period of 5.33 years on average, with or without redox potential control. If a glucose feeding concentration of 300 g/L is applied to the fermenter, the redox potential must be controlled at 150 mV to limit the process payout period to less than 6 years. Fermentation processes with glucose feeding concentrations of 200 g/L are estimated to have payout periods of more than 8 years under all evaluated scenarios; this low feed concentration makes the process much less profitable compared to scenarios with higher feed concentrations. 3.2. Effect of glucose feeding concentration Usually, VHG fermentation implies bio-ethanol fermentation with glucose feeding concentration greater than 250 g/L. VHG fermentation is expected to reduce the unit production cost due to high ethanol productivity, but the simulation results suggests otherwise. As shown in Fig. 3, values used are averages of all investigated conditions under the same glucose feeding conditions. The highest glucose loading in the feed stream does not result in the lowest unit production cost. Unexpectedly, the lowest unit production cost (0.764 $/kg ethanol) is obtained when a glucose feeding concentration of 250 g/L is applied. This may be
Fig. 2. Sales analysis of payout period on different glucose feeding concentrations and redox potential controls.
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Fig. 3. Effect of glucose feeding concentration on plant capacity and unit production cost.
due to the difference in ethanol yield (g ethanol/g glucose) under different glucose feeds, as well as the reaction extent of Eq. (2). With higher glucose feeds (300 g/L), the osmotic stress caused by the very high glucose concentration results in yeast cells spending more time and energy adapting themselves to the extreme conditions. Therefore, the ethanol yield decreases as does the profitability of the process. In fact, in all 300 g/L cases, the residual glucose in the beer remains at 14.39 g/L on average, even after the longest fermentation time (48 h); this means the glucose is not efficiently utilized, as reflected in a smaller reaction extent of Eq. (2). Higher glucose loading results in a longer fermentation time, which reduces the VHG fermentation efficiency. Moreover, high residual glucose in the beer means a small reaction extent (a sign of wasted or unspent glucose), which imposes difficulties for downstream processing stages; this is therefore less profitable even though the annual production rate is 5% higher than scenarios with glucose feeding concentrations of 250 g/L. When glucose feeding concentrations are low (200 g/L), the glucose can be completely utilized by yeast cells with a shorter fermentation time; however, the low glucose feeding concentration diminishes the efficiency of the entire process, making it less economically viable. The selling price of the DDGS stream (Table 1) was calculated based on its moisture content and the dry DDGS price. Higher glucose feeds result in higher biomass content and thus less moisture in DDGS byproduct stream. This increases the selling price for the dry DDGS, but not significantly enough to make the whole process more profitable than the scenarios with a moderate glucose feeding concentration (250 g/L). 3.3. Effect of redox potential control To study the effect of redox potential control on the fermentation process and its impact on profitability, two redox potential levels controls of 100 and 150 mV were implemented during VHG fermentation and compared to scenarios without redox potential control. Results suggest that redox potential control can enhance yeast performance and improve fermentation efficiency, thus resulting in higher profit.
The effect of redox potential control on ethanol yield shown in Fig. 4a is consistent with the conclusion of former observations (Figs. 2 and 3) that glucose feeding concentration at 250 g/L results in the highest conversion rate due to the optimal fermentation conditions. At lower glucose feeding concentrations (200 and 250 g/L), redox potential control has no significant influence on ethanol yield. However, the results suggest otherwise at glucose feeding concentrations of 300 g/L. The low ethanol yield when 300 g/L glucose is fed to fermenter might be attributed to osmotic stress resulting from the presence of excess amounts of glucose. Nevertheless, when the redox potential is controlled at 100 mV, the ethanol yield decreases significantly by 8.4% (that is, from 0.4493 to 0.4114 g ethanol/g glucose). In contrast, when the redox potential is controlled at 150 mV, the ethanol yield increases from 0.4114 to 0.4677, 4.1% greater than when no redox potential control is applied. From Fig. 4(a), one can conclude that redox potential control has little to no noticeable effect on ethanol yield at glucose feeding concentrations 250 g/L. However, marked impact on ethanol yield is realized at feeding concentrations of 300 g glucose/L. In other words, redox potential control significantly affects the VHG fermentation process, with control of the redox potential at different levels resulting in different ethanol yields. The optimal redox potential level could be further refined in future work. The effects of redox potential and glucose feeding concentration on the ethanol unit production cost are shown in Fig. 4(b). At feeds of 300 g glucose/L, the unit production cost of ethanol is 0.825 $/ kg when no redox potential control is applied; this value increases to 0.888 $/kg when the redox potential is held at 100 mV, and decreases dramatically to 0.780 $/kg when the redox potential is held at 150 mV. This result is consistent with Fig. 4(a) that shows ethanol yield increases from 0.4114 to 0.4677 g ethanol/g glucose when the redox potential is reduced from 100 to 150 mV. Applying an optimal redox potential control level to the fermentation process may not only increase the ethanol yield in the fermenter and thus reduce the unit production cost, but may also avoid procedural waste of raw material when the VHG fermentation process is applied for higher productivity and profitability.
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CO2 produced during fermentation
Emission into atmosphere
Captured and sold as coproduct
Deep injection into geological formations for storage
Fig. 5. Options for disposal of CO2 during bio-ethanol fermentation.
Fig. 4. Effect of redox potential control on (a) ethanol yield and (b) ethanol unit production cost.
3.4. Disposal of CO2 produced during fermentation During the bioethanol fermentation process, CO2 molecules in equal numbers to ethanol will be produced. For example, at a plant with an annual capacity of 100 million kg ethanol, 95.53 million kg/year of CO2 will be produced. Three options to dispose this CO2 are presented in Fig. 5. Most fermentation facilities emit their CO2 to the atmosphere. This is a wasted resource and, more importantly, is not environmentally preferable as CO2 is one of the major greenhouse gases that causes global warming. In some facilities, CO2 sold for use in carbonated beverages or dry ice production. Selling CO2 as a byproduct of the fermentation process has no significant impact on reducing the production cost of the ethanol [7], but is still profitable for facilities with large CO2 production rates; it is also a more environmental friendly option than discharge to the atmosphere. For a fermentation process such as the one studied here, essentially all gas emissions are CO2 and no further processing is required to recover CO2 [14]. The selling price of industrial level CO2 is estimated at 15 $/ton [7]. For a facility with a capacity of 100 million kg ethanol/year, selling CO2 as a byproduct would bring in 1.43 million $/year as extra income. While selling CO2 as a
byproduct is profitable, it is questionable whether this could be effectively implemented if many ethanol plants were established and saturated the market for CO2. A growing number of commercial-scale enterprises inject CO2 into deep underground geological formations to avoid leakage into atmosphere [11]. Experience from acid-gas injection operations shows CO2 sequestration in geological media is a mature and safe technology that can successfully be expanded and applied to largescale operations to reduce atmospheric CO2 emissions [12]. For the scenario mentioned above, assumptions are a CO2 production rate of 95.53 million kg/year and the plant located 500 km away from the deep injection site. Capture and transportation costs are estimated at 50 $/ton CO2 [14], and thus the CO2 deep injection cost for the plant would be 4.78 million $/year. A shorter transportation distance and larger plant capacity would further reduce the unit cost of CO2 storage and transportation; evaluation parameters can be obtained from various researchers for different scenarios [13,14]. Furthermore, if CO2 generated through fermentation could be stored (e.g., in a geological reservoir), some CO2 taken up during feed crop (e.g., corn) growth would not be released back to the atmosphere but instead be sequestered underground. If this exceeded the fossil carbon emitted during ethanol production, then the production of ethanol would result in the net removal of CO2 from the atmosphere. Notably, deep injection operations for carbon sequestration are applicable to many sites around the world (IEA Weyburn CO2 Monitoring and Storage Project. IEA Greenhouse Gas R&D Programme, 2010). Compression and transport of CO2 to sequestration sites would be an added cost [12]. Acid-gas deep injection operations have been operating in North America since 1989 [11]. McCoy [13] gave some methods to estimate pipeline costs for transportation of large amounts of CO2 based on different flow rates and distances. Using existing pipelines to transport CO2 to sequestration sites or building CO2 generating sources, such as bio-ethanol fermentation plants, near deep injection sites will lower the cost of deep injection. 4. Conclusions In summary, VHG fermentation under 300 g glucose/L feeding conditions did not achieve the expected reduction on unit production cost of ethanol. Modeling results suggest that the most profitable glucose feeding concentration to the fermenter is around 250 g/L among all studied scenarios; this feed value gives the lowest ethanol unit production cost and the shortest process payout period, with or without redox potential control. Application of a VHG fermentation process requires not only an industrial yeast strain to efficiently utilize fermentable substrates within shorter residence time, but also approaches to reuse residual saccharides in the output stream of the fermenter. Redox potential control affects the fermentation process, especially for VHG fermentation. Results suggest that under
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300 g glucose/L scenario, controlling the redox potential at 150 mV during fermentation increases the ethanol yield, thereby considerably reducing the unit production cost under VHG conditions. However, the optimal combination of redox potential control and glucose feeding concentration requires further examination. Because large amounts of CO2 are produced during ethanol fermentation, its capture and sale is profitable for plants with large capacities despite the extra costs of a CO2 recovery system. In addition, CO2 is a major greenhouse gas that causes global warming. However, deep injection as an alternative for the disposal of CO2 produced during fermentation is not economically preferable compared to emitting CO2 to atmosphere or selling it as a byproduct; it is currently, however, the more environmentally friendly option, with potential long-term global benefits. References [1] Ko J, Su WJ, Chien IL, Chang DM, Chou SH, Zhan RY. Dynamic modeling and analyses of simultaneous saccharification and fermentation process to produce bio-ethanol from rice straw. Bioprocess Biosyst Eng 2010;22:195–205. [2] Thomas KC, Ingledew WM. Fuel alcohol production: effects of free amino nitrogen on fermentation of very-high-gravity wheat mashes. Appl Environ Microbiol 1990;56:2046–50. [3] Zhao Y, Lin Y-H. Growth of Saccharomyces cerevisiae in a chemostat under high glucose conditions. Biotechnol Lett 2003;25:1151–4.
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Journal of the Taiwan Institute of Chemical Engineers journal homepage: www.elsevier.com/locate/jtice
Techno-economic evaluation of redox potential-controlled ethanol fermentation processes Fei Yu a, Yen-Han Lin b,* a b
Division of Environmental Engineering, University of Saskatchewan, 57 Campus Drive, Saskatoon, SK, Canada S7H 5A9 Department of Chemical Engineering, University of Saskatchewan, 57 Campus Drive, Saskatoon, SK, Canada S7H 5A9
A R T I C L E I N F O
A B S T R A C T
Article history: Received 8 December 2011 Received in revised form 11 May 2012 Accepted 12 May 2012 Available online 15 June 2012
Nine redox potential-controlled operating conditions during ethanol fermentation were evaluated by means of a process simulator. Results show that the lowest unit production cost (0.764 $/kg ethanol) was estimated for 250 g glucose/L among all studied conditions. Controlling the redox potential at 150 mV increases the ethanol yield when glucose concentrations are greater than 250 g/L; while no significant effects were observed at glucose feeds below 250 g/L. For a facility with an annual production capacity of 85–130 million kg ethanol, the shortest payout period of 5.33 years was obtained under 250 g glucose/L conditions, either with or without redox potential control. If 300 g glucose/L is applied, controlling the redox potential at 150 mV is required to limit the process payout period to be less than 6 years. Carbon dioxide disposal options are presented. Selling CO2 as a byproduct can bring in 1.43 million $/year income for an ethanol plant with a capacity of 100 million kg ethanol/year. Capture and transport of CO2 to deep injection sites for geological underground storage is economically unprofitable and adds 4.78 million $/year in processing costs; however, this option results in a net removal of CO2 from the atmosphere, making it environmentally preferable. The presented process model is available upon request. ß 2012 Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
Keywords: Techno-economic evaluation Very-high-gravity fermentation Redox potential control Ethanol CO2 storage
1. Introduction Ethanol is widely used as a fuel, solvent, disinfectant, medicine, and feedstock for the synthesis of other chemical products. Ethanol has a high octane number and high latent heat of vaporization, and it can be blended with gasoline to use as a transportation fuel. More importantly, bio-ethanol has environmental advantages compared to fossil fuels, as the future energy supply must comply with efforts to substantially reduce greenhouse gas emissions [1]. Alcoholic fermentation on industrial scale is mainly a conversion process of glucose to ethanol using active dry yeast (Saccharomyces cerevisiae). In the past few decades, ethanoltolerant strains of S. cerevisiae have become available for industrial fermentation, allowing fermentation under very high concentrations of carbohydrates. Usually, sugar concentrations in excess of 200 g/L are not used under industrial conditions because increasing concentrations of ethanol retard the growth of yeasts and fermentation eventually arrests [2]. However, the industrial yeast strains used in bio-ethanol fermentation can grow, albeit at lower rates, in fermentation broths with initial glucose concentrations of 300 g/L [3]. Generally, very-high-gravity (VHG) fermentation
* Corresponding author. Tel.: +1 306 966 4764. E-mail address: [email protected] (Y.-H. Lin).
means bio-ethanol fermentation with a glucose feeding concentration greater than 250 g/L. In recent years, it is becoming more common for bio-ethanol fermentation to be handled by a process simulator [1,4–7]. The whole fermentation process can be simulated by computers for financial analysis, including capital and operating costs, revenues, earnings, and return on investment. Many relevant fermentation process parameters can be adjusted to facilitate simulations of the industrial process in conjunction with lab data. Process simulations can be conducted for the whole bio-ethanol fermentation process from raw materials, such as corn to ethanol [4,6], or simply the corn milling, liquefaction, and saccharification process [5,8–10]. In some ethanol facilities, CO2 produced during the fermentation process is released to the atmosphere. CO2 can also be captured and sold, although this byproduct typically does not significantly affect economic evaluation [7]. Alternatively, CO2 produced during fermentation can be injected into deep geological formations (aquifers or reservoirs) for geological storage, to reduce CO2 emissions to the atmosphere [11–15]. In this study, data collected from redox potential-controlled fermentations [15] were used to carry out an economical analysis by means of process simulation. A process simulator was used to evaluate operating conditions that provide the highest possible profit from a VHG fermentation process. A simulation model for an ethanol plant with a capacity of 85–130 million kg ethanol/year
1876-1070/$ – see front matter ß 2012 Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.jtice.2012.05.002
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has been developed using Aspen Plus 2006 based on [6], and evaluated using Aspen Icarus Process Evaluator (IPE) 2006. This model is capable of estimating both process and economic parameters, which are consequently used to explore the most profitable redox potential-controlled fermentation settings under VHG conditions. The Aspen Plus model is available upon request. 2. Materials and methods 2.1. Fermentation and redox potential measurement Methods for fermentation and redox potential measurements were reported in our previous study [15]. Briefly, an industrial S. cerevisiae strain (Ethanol RedTM obtained from the Lesaffre Yeast Corp. Milwaukee, MI, USA) was pre-cultured overnight and cultivated in a jar fermenter with a 1-L working volume (model: Omni culture fermenter, New York, NY, USA). The inoculums’ level was 5%, and fermentation was operated in batch mode. Each fermenter was equipped with an autoclavable redox potential electrode that was custom-made and ordered through Cole-Palmer Inc. (12 mm 250 mm, Vernon Hills, IL, USA), and the fermentation temperature was set at 32 8C. Data were acquired by using LabView (Version 8.5, National Instrument, Austin, TX, USA), and a PID control algorithm was implemented to control the redox potential as desired levels: no control, 150 mV, and 100 mV. The agitation rate was kept at 150 rpm for all runs. If the measured redox potential was lower than the set-point value, sterilized air was provided to fermenter to raise the redox potential to the desired level. The fermentation broth was sampled every 6 h. A high performance liquid chromatograph (HPLC) equipped with a refractive index (RI) detector was used to quantify the residual glucose, ethanol, and other metabolites. 2.2. Process description The block diagram of the process model used in this study is illustrated in Fig. 1. This model was modified from [6], and the relevant simulation parameters were determined based on our previous work [15]. This simulation focused on the economical effects of varied glucose feeding concentrations and redox potential controls on ethanol production. In this model, the glucose concentration in the feed stream to the fermenter was manipulated by varying the starch content in
Grain
Milling
the grain stream feeding the milling module (Fig. 1). The milling module is a separation process and the liquefaction module is a heating process, and no chemical reactions are defined in either stage. However, one reaction is defined in the saccharification module: starch þ water ! glusose
The above equation defines the molecular relation of the reaction from starch to glucose, where one molecule of starch and one molecule of water produce one molecule of glucose. Starch in this model is a predefined pure component with a molecular weight of 162.14. It should be mentioned that starch is a polysaccharide which can be hydrolyzed to thousands of glucose molecules. Eq. (1) is not a description of a chemical reaction, but rather the mass relationships of components conversion. In the fermenter, two reactions are defined: glusose ! a CO2 þ a ethanol þ b YDM
YDM ! 1:13635848 protein
(3)
where YDM is a predefined component standing for yeast dry matter [6]. a and b in Eq. (2) are the molar coefficients of the reaction, determined based on results of lab fermentation experiments before simulation. The constant 1.13635848 in Eq. (3) is the predefined mass coefficient calculated according to the predefined molecular weight of YDM and protein [6]. After fermentation, the beer is sent to an aging tank, where most of the CO2 (over 98.7% in the feed) is separated from the beer, and then to a degasser, where further CO2 is removed (70% of the leftover CO2 in the beer). The beer is then sent into the distillation section, which includes a beer column and a rectifier. The top output stream of the degasser is transitioned to a condenser to recover most of the ethanol (around 80% in the feed). This condensed stream is also sent to the beer column for further separation. The beer column is a primary separation process unit, separating most of the ethanol (over 99.7% in its feed stream) from the fermenter’s output stream together with a certain amount of water. This stream, mainly composed of ethanol and water, is then sent to a rectifier connected to a molecular sieve for further ethanol–water separation. The molecular sieve overcomes the limitation of the distillation process to yield the main product
Saccharification
Degas
Age Tank
Fermentor
CO 2 CO 2 Scrubber
Beer Column
Centrifuge
(2)
and
Liquefaction
Condense
(1)
Rectifier
Evaporation
Molecular Sieve
DDGS Dryer
Ethanol
DDGS
Fig. 1. Block diagram for redox potential-controlled very-high-gravity ethanol fermentation.
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stream with a high ethanol concentration. Molecular sieves are applied to separate the azeotrope of water and ethanol (ethanol:water = 95.6:4.4 (w/w)). With recycling, the ethanol concentration in the output stream reaches over 99.25 wt%. The bottom stream of the beer column is sent to a centrifuge and then a dryer to yield distiller’s dried grains with solubles (DDGS), which is the main byproduct of this ethanol production process. It should be noted that under mill conditions, protein and other solids content in the feed stream to the milling section proportionally change when the starch content is varied. However, because variations of protein and other solids content in the feed stream have no significant influence on economic evaluation results, they remain unchanged in simulated scenarios in order to precisely manipulate the glucose concentration in the feed stream of the fermenter. The top output streams of the aging tank and condenser, which are rich in CO2, are sent to a CO2 scrubber where the liquid portion of the feeds is absorbed by water and the majority of the CO2 (over 99.8%) produced during the fermentation process is gathered for emission, capture, or deep injection. In this model, CO2 produced during the fermentation process is assumed to be captured after treatment in the CO2 scrubber and sold as a byproduct. As discussed below, the captured CO2 stream can also be compressed and transported by pipelines to deep injection sites for geological storage. 2.3. Process design parameters The annual production rate of the process is considered to be 85–130 million kg ethanol/year, depending on the glucose concentration fed to the fermenter. The annual operating time of the plant is designed to be 7920 h (330 days).
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Table 1 Costs used in the economic evaluation. Purchase price ($/kg) Raw materials Corn Water Acid a-Amylase Urea Yeast Products Ethanol Dry DDGS CO2
Selling price ($/kg)
0.248183 0.000044 0.153000 2.250000 0.353020 5.510000 0.724419 0.175334 0.015940
01803, USA). Physical properties of the components were obtained from the Aspen Plus 2006 databank or defined by the user. Material and energy balance calculations were performed by Aspen Plus, and economic evaluation of the process was carried out by the Aspen IPE (Aspen Technology, Inc., 200 Wheeler Road, Burlington, MA 01803, USA). Table 1 lists costs used in the economic evaluation. The purchase price of corn is an average value of the price from the previous six months (September 2010–February 2011) obtained from ‘‘Index Mundi’’ (http://www.indexmundi.com/commodities/ ); selling prices of ethanol and DDGS are also average values of the price from the previous six months (September 2010–February 2011) according to the Economic Research Service of United States Department of Agriculture (ERS/USDA); other costs were obtained from the literature or online searches. In addition, the selling price of the DDGS byproduct stream was calculated according to the stream’s moisture content.
2.4. Reaction coefficients 3. Results and discussion In the simulation, different fermentation conditions were applied by manipulating the reaction coefficients a, b in Eq. (2), as well as its reaction extent. a is the molar ratio of ethanol yield over depleted glucose, which are measured by lab experiments under certain applied conditions; b is dependent on a to ensure mass balance of the reaction. Note that 1.13635848 in Eq. (3) is an approximate value of the molecular weight ratio of YDM (150.13) to protein (132.115). The reaction extent of Eq. (1) was set to 0.99, according to [6]. The reaction extent of Eq. (2) is the mass ratio of depleted glucose over total feed glucose measured under certain applied conditions. The reaction extent of Eq. (3) is fixed at 0.6, according to [4]. 2.5. Simulation tool The simulation model was created using Aspen Plus 2006 (Aspen Technology, Inc., 200 Wheeler Road, Burlington, Massachusetts
During the process simulation, the effects of glucose feeding concentration (200 4.99, 250 3.95, and 300 6.42 g/L) and redox potential settings (no control, 150, and 100 mV) were investigated. Note that the numerical value followed by sign indicates one standard deviation. The general results of the economic evaluation are shown in Table 2, and the breakdown of unit production costs for each investigated case is provided in Table 3. The selected range of glucose concentration is stoichiometrically equivalent to 12–20% (v/v) ethanol. 3.1. Sales analysis The sales analysis results of all scenarios (varied glucose feeding concentrations and redox potential settings) are listed in Table 4. Ethanol is the main product of the process, while DDGS and CO2 are byproducts (selling prices of which are presented in Table 1).
Table 2 Results of the economic evaluation. Different glucose concentrations in the feed stream are denoted as: A = 300 6.42 g/L, B = 250 3.95 g/L, C = 200 4.99 g/L. Different redox potential control levels are denoted as: a = no control, b = 150 mV, c = 100 mV.
Aa Ab Ac Ba Bb Bc Ca Cb Cc
Production rate (106 kg ethanol/year)
Unit production cost ($/kg ethanol)
Annual operation cost (106 $/year)
Total product sales (106 $/year)
124.65 131.93 115.71 118.98 115.84 118.84 86.54 87.68 85.71
0.825 0.780 0.888 0.757 0.777 0.758 0.885 0.873 0.893
102.87 102.93 102.79 90.08 90.06 90.08 76.56 76.56 76.56
117.97 119.45 116.36 106.40 106.24 106.39 84.42 84.53 84.34
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Table 3 Breakdown of unit production costs for each case; all values in $/kg ethanol. Different glucose concentrations in the feed stream are denoted as: A = 300 6.42 g/L, B = 250 3.95 g/L, C = 200 4.99 g/L. Different redox potential control levels are denoted as: a = no control, b = 150 mV, c = 100 mV. Cost item ($/kg ethanol)
Aa
Ab
Ac
Ba
Bb
Bc
Ca
Cb
Cc
Raw material cost Utilities cost Operating labor cost Maintenance cost Operating charges Plant overhead G and A cost
0.738 0.012 0.007 0.001 0.002 0.004 0.061
0.698 0.012 0.007 0.001 0.002 0.004 0.058
0.795 0.012 0.008 0.001 0.002 0.004 0.066
0.676 0.011 0.008 0.001 0.002 0.004 0.056
0.694 0.011 0.008 0.001 0.002 0.004 0.058
0.676 0.011 0.008 0.001 0.002 0.004 0.056
0.788 0.012 0.011 0.001 0.003 0.006 0.066
0.777 0.012 0.010 0.001 0.003 0.006 0.065
0.795 0.012 0.011 0.001 0.003 0.006 0.066
Total
0.825
0.780
0.888
0.757
0.777
0.758
0.885
0.873
0.893
Table 4 Sales analysis for each applied condition. Different glucose concentrations in the feed stream are denoted as: A = 300 6.42 g/L, B = 250 3.95 g/L, C = 200 4.99 g/L. Different redox potential control levels are denoted as: a = no control, b = 150 mV, c = 100 mV.
Aa Ab Ac Ba Bb Bc Ca Cb Cc
Total operating cost (million $/year)
Total product sales (million $/year)
Payout period (years)
102.87 102.93 102.79 90.08 90.06 90.08 76.56 76.56 76.56
117.97 119.45 116.36 106.40 106.24 106.39 84.42 84.53 84.34
6.08 5.71 6.59 5.32 5.35 5.32 8.47 8.39 8.52
Payout period is the expected number of years required to recover the original investment in the project. This parameter indicates the length of time that the facility needs to operate in order to recover the initial capital investment (total capital cost plus working capital). The results shown in Fig. 2 suggest that for an ethanol plant with a capacity of 85–130 million kg ethanol/year,
maintaining the glucose feeding concentration to the fermenter at around 250 g/L results in the shortest payout period of 5.33 years on average, with or without redox potential control. If a glucose feeding concentration of 300 g/L is applied to the fermenter, the redox potential must be controlled at 150 mV to limit the process payout period to less than 6 years. Fermentation processes with glucose feeding concentrations of 200 g/L are estimated to have payout periods of more than 8 years under all evaluated scenarios; this low feed concentration makes the process much less profitable compared to scenarios with higher feed concentrations. 3.2. Effect of glucose feeding concentration Usually, VHG fermentation implies bio-ethanol fermentation with glucose feeding concentration greater than 250 g/L. VHG fermentation is expected to reduce the unit production cost due to high ethanol productivity, but the simulation results suggests otherwise. As shown in Fig. 3, values used are averages of all investigated conditions under the same glucose feeding conditions. The highest glucose loading in the feed stream does not result in the lowest unit production cost. Unexpectedly, the lowest unit production cost (0.764 $/kg ethanol) is obtained when a glucose feeding concentration of 250 g/L is applied. This may be
Fig. 2. Sales analysis of payout period on different glucose feeding concentrations and redox potential controls.
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Fig. 3. Effect of glucose feeding concentration on plant capacity and unit production cost.
due to the difference in ethanol yield (g ethanol/g glucose) under different glucose feeds, as well as the reaction extent of Eq. (2). With higher glucose feeds (300 g/L), the osmotic stress caused by the very high glucose concentration results in yeast cells spending more time and energy adapting themselves to the extreme conditions. Therefore, the ethanol yield decreases as does the profitability of the process. In fact, in all 300 g/L cases, the residual glucose in the beer remains at 14.39 g/L on average, even after the longest fermentation time (48 h); this means the glucose is not efficiently utilized, as reflected in a smaller reaction extent of Eq. (2). Higher glucose loading results in a longer fermentation time, which reduces the VHG fermentation efficiency. Moreover, high residual glucose in the beer means a small reaction extent (a sign of wasted or unspent glucose), which imposes difficulties for downstream processing stages; this is therefore less profitable even though the annual production rate is 5% higher than scenarios with glucose feeding concentrations of 250 g/L. When glucose feeding concentrations are low (200 g/L), the glucose can be completely utilized by yeast cells with a shorter fermentation time; however, the low glucose feeding concentration diminishes the efficiency of the entire process, making it less economically viable. The selling price of the DDGS stream (Table 1) was calculated based on its moisture content and the dry DDGS price. Higher glucose feeds result in higher biomass content and thus less moisture in DDGS byproduct stream. This increases the selling price for the dry DDGS, but not significantly enough to make the whole process more profitable than the scenarios with a moderate glucose feeding concentration (250 g/L). 3.3. Effect of redox potential control To study the effect of redox potential control on the fermentation process and its impact on profitability, two redox potential levels controls of 100 and 150 mV were implemented during VHG fermentation and compared to scenarios without redox potential control. Results suggest that redox potential control can enhance yeast performance and improve fermentation efficiency, thus resulting in higher profit.
The effect of redox potential control on ethanol yield shown in Fig. 4a is consistent with the conclusion of former observations (Figs. 2 and 3) that glucose feeding concentration at 250 g/L results in the highest conversion rate due to the optimal fermentation conditions. At lower glucose feeding concentrations (200 and 250 g/L), redox potential control has no significant influence on ethanol yield. However, the results suggest otherwise at glucose feeding concentrations of 300 g/L. The low ethanol yield when 300 g/L glucose is fed to fermenter might be attributed to osmotic stress resulting from the presence of excess amounts of glucose. Nevertheless, when the redox potential is controlled at 100 mV, the ethanol yield decreases significantly by 8.4% (that is, from 0.4493 to 0.4114 g ethanol/g glucose). In contrast, when the redox potential is controlled at 150 mV, the ethanol yield increases from 0.4114 to 0.4677, 4.1% greater than when no redox potential control is applied. From Fig. 4(a), one can conclude that redox potential control has little to no noticeable effect on ethanol yield at glucose feeding concentrations 250 g/L. However, marked impact on ethanol yield is realized at feeding concentrations of 300 g glucose/L. In other words, redox potential control significantly affects the VHG fermentation process, with control of the redox potential at different levels resulting in different ethanol yields. The optimal redox potential level could be further refined in future work. The effects of redox potential and glucose feeding concentration on the ethanol unit production cost are shown in Fig. 4(b). At feeds of 300 g glucose/L, the unit production cost of ethanol is 0.825 $/ kg when no redox potential control is applied; this value increases to 0.888 $/kg when the redox potential is held at 100 mV, and decreases dramatically to 0.780 $/kg when the redox potential is held at 150 mV. This result is consistent with Fig. 4(a) that shows ethanol yield increases from 0.4114 to 0.4677 g ethanol/g glucose when the redox potential is reduced from 100 to 150 mV. Applying an optimal redox potential control level to the fermentation process may not only increase the ethanol yield in the fermenter and thus reduce the unit production cost, but may also avoid procedural waste of raw material when the VHG fermentation process is applied for higher productivity and profitability.
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CO2 produced during fermentation
Emission into atmosphere
Captured and sold as coproduct
Deep injection into geological formations for storage
Fig. 5. Options for disposal of CO2 during bio-ethanol fermentation.
Fig. 4. Effect of redox potential control on (a) ethanol yield and (b) ethanol unit production cost.
3.4. Disposal of CO2 produced during fermentation During the bioethanol fermentation process, CO2 molecules in equal numbers to ethanol will be produced. For example, at a plant with an annual capacity of 100 million kg ethanol, 95.53 million kg/year of CO2 will be produced. Three options to dispose this CO2 are presented in Fig. 5. Most fermentation facilities emit their CO2 to the atmosphere. This is a wasted resource and, more importantly, is not environmentally preferable as CO2 is one of the major greenhouse gases that causes global warming. In some facilities, CO2 sold for use in carbonated beverages or dry ice production. Selling CO2 as a byproduct of the fermentation process has no significant impact on reducing the production cost of the ethanol [7], but is still profitable for facilities with large CO2 production rates; it is also a more environmental friendly option than discharge to the atmosphere. For a fermentation process such as the one studied here, essentially all gas emissions are CO2 and no further processing is required to recover CO2 [14]. The selling price of industrial level CO2 is estimated at 15 $/ton [7]. For a facility with a capacity of 100 million kg ethanol/year, selling CO2 as a byproduct would bring in 1.43 million $/year as extra income. While selling CO2 as a
byproduct is profitable, it is questionable whether this could be effectively implemented if many ethanol plants were established and saturated the market for CO2. A growing number of commercial-scale enterprises inject CO2 into deep underground geological formations to avoid leakage into atmosphere [11]. Experience from acid-gas injection operations shows CO2 sequestration in geological media is a mature and safe technology that can successfully be expanded and applied to largescale operations to reduce atmospheric CO2 emissions [12]. For the scenario mentioned above, assumptions are a CO2 production rate of 95.53 million kg/year and the plant located 500 km away from the deep injection site. Capture and transportation costs are estimated at 50 $/ton CO2 [14], and thus the CO2 deep injection cost for the plant would be 4.78 million $/year. A shorter transportation distance and larger plant capacity would further reduce the unit cost of CO2 storage and transportation; evaluation parameters can be obtained from various researchers for different scenarios [13,14]. Furthermore, if CO2 generated through fermentation could be stored (e.g., in a geological reservoir), some CO2 taken up during feed crop (e.g., corn) growth would not be released back to the atmosphere but instead be sequestered underground. If this exceeded the fossil carbon emitted during ethanol production, then the production of ethanol would result in the net removal of CO2 from the atmosphere. Notably, deep injection operations for carbon sequestration are applicable to many sites around the world (IEA Weyburn CO2 Monitoring and Storage Project. IEA Greenhouse Gas R&D Programme, 2010). Compression and transport of CO2 to sequestration sites would be an added cost [12]. Acid-gas deep injection operations have been operating in North America since 1989 [11]. McCoy [13] gave some methods to estimate pipeline costs for transportation of large amounts of CO2 based on different flow rates and distances. Using existing pipelines to transport CO2 to sequestration sites or building CO2 generating sources, such as bio-ethanol fermentation plants, near deep injection sites will lower the cost of deep injection. 4. Conclusions In summary, VHG fermentation under 300 g glucose/L feeding conditions did not achieve the expected reduction on unit production cost of ethanol. Modeling results suggest that the most profitable glucose feeding concentration to the fermenter is around 250 g/L among all studied scenarios; this feed value gives the lowest ethanol unit production cost and the shortest process payout period, with or without redox potential control. Application of a VHG fermentation process requires not only an industrial yeast strain to efficiently utilize fermentable substrates within shorter residence time, but also approaches to reuse residual saccharides in the output stream of the fermenter. Redox potential control affects the fermentation process, especially for VHG fermentation. Results suggest that under
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300 g glucose/L scenario, controlling the redox potential at 150 mV during fermentation increases the ethanol yield, thereby considerably reducing the unit production cost under VHG conditions. However, the optimal combination of redox potential control and glucose feeding concentration requires further examination. Because large amounts of CO2 are produced during ethanol fermentation, its capture and sale is profitable for plants with large capacities despite the extra costs of a CO2 recovery system. In addition, CO2 is a major greenhouse gas that causes global warming. However, deep injection as an alternative for the disposal of CO2 produced during fermentation is not economically preferable compared to emitting CO2 to atmosphere or selling it as a byproduct; it is currently, however, the more environmentally friendly option, with potential long-term global benefits. References [1] Ko J, Su WJ, Chien IL, Chang DM, Chou SH, Zhan RY. Dynamic modeling and analyses of simultaneous saccharification and fermentation process to produce bio-ethanol from rice straw. Bioprocess Biosyst Eng 2010;22:195–205. [2] Thomas KC, Ingledew WM. Fuel alcohol production: effects of free amino nitrogen on fermentation of very-high-gravity wheat mashes. Appl Environ Microbiol 1990;56:2046–50. [3] Zhao Y, Lin Y-H. Growth of Saccharomyces cerevisiae in a chemostat under high glucose conditions. Biotechnol Lett 2003;25:1151–4.
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