Optimization of Fed-Batch Fermentation with in Situ Ethanol Removal

Dec 28, 2017 - ... the optimization and experimental validation of sugar cane ethanol production by fed-batch fermentation with in situ ethanol remova...
0 downloads 0 Views 668KB Size
Download PDF
Article Cite This: Energy Fuels XXXX, XXX, XXX−XXX

pubs.acs.org/EF

Optimization of Fed-Batch Fermentation with in Situ Ethanol Removal by CO2 Stripping J. L. S. Sonego, D. A. Lemos, A. J. G. Cruz, and A. C. Badino* Chemical Engineering Graduate Program, Federal University of São Carlos, C.P. 676, 13565-905 São Carlos, SP Brazil ABSTRACT: One way of overcoming the substrate and ethanol inhibition effects in the industrial ethanol production process is to use fed-batch fermentation coupled with an ethanol removal technique. This work describes the optimization and experimental validation of sugar cane ethanol production by fed-batch fermentation with in situ ethanol removal by CO2 stripping. The optimization employing a genetic algorithm (GA) was used to find the optimum feed flow rate (F) and the ethanol concentration (CE0) in the medium at which to initiate stripping, in order to obtain maximum ethanol productivity. Conventional ethanol fermentation employing the optimum feed flow rate was performed with must containing 257.1 g L−1 of sucrose (180 g L−1 of total sucrose concentration), resulting in achievement of an ethanol concentration of 82.2 g L−1. The stripping fed-batch fermentation with high total sucrose concentration (260−300 g L−1) or 371.4−428.6 g L−1 in the must feeding was performed with optimal values of the feed flow rate and the ethanol concentration (CE0) in the medium at which to initiate stripping. At the highest sucrose feed (total concentration of 300 g L−1), the total ethanol concentration reached 136.9 g L−1 (17.2 °GL), which was about 65% higher than the value obtained in fed-batch fermentation without ethanol removal by CO2 stripping. This strategy proved to be a promising way to minimize inhibition by both the substrate and ethanol, leading to increased sugar cane ethanol production, reduced vinasse generation, and lower process costs.

■

INTRODUCTION There is increasing attention focused on the production of liquid biofuels from renewable feedstocks, in order to meet the global energy demand and reduce greenhouse gas emissions. Ethanol, which exhibits clean combustion, is the liquid biofuel most widely used in the transport sector.1,2 The United States and Brazil together produce around 86.0 billion liters of ethanol annually, accounting for 87% of worldwide production.3,4 According to the Brazilian National Company of Supply, the 2016/2017 sugar cane harvest produced 38.69 million tons of sugar and 27.8 billion liters of ethanol, about 28% of global production.5 In Brazilian distilleries, ethanol is produced by fermentation of musts containing sugar cane sugars. The concentration of total fermentable sugars is about 20° Brix (∼180 g L−1 of total reducing sugars, TRS).6 In the distilleries annexed to sugar factories, the must is prepared by mixing sugar cane juice and molasses (a coproduct of the sugar factory) or using molasses diluted with water. In autonomous distilleries, the must consists only of sugar cane juice.4 In terms of the fermentation process, around 85% of distilleries use the fed-batch mode, while only 15% use the continuous mode.7 Another characteristic of this fermentation process is that the yeast is recycled (the Melle−Boinot process), resulting in a high cell density in the fermentation vat (10−15% w v−1).7 The fed-batch fermentation takes place in a set of large-volume vats with offsets in the fermentation cycles, for periods of 6−12 h, at temperatures in the range 32−35 °C. The final ethanol concentration in the fermentation broth is up to 11% (v v−1), corresponding to average ethanol yields of 90−92%, relative to the theoretical conversion.8,9 In industrial fed-batch ethanol fermentation, the inoculum composed of a yeast suspension usually represents around 25− 30% of the total volume of the fermentation vat. In this © XXXX American Chemical Society

fermentation mode, the sugar cane must is fed until the vat is full (fed-batch stage), with feeding times that are usually between 4 and 6 h. After filling, the process is completed by batch fermentation until sugar exhaustion (batch stage).6,10 The use of a fed-batch process avoids negative effects of substrate inhibition on Saccharomyces cerevisiae growth and ethanol production. According to Thatipamala et al.11 and Zhang et al.,12 inhibitory effects are not observed at substrate concentrations up to 150−160 g L−1. However, in Brazilian distilleries, the use of the fed-batch operational mode results in concentrations of substrate in the vat that usually do not reach these values, hence overcoming the negative effects of substrate inhibition on the yeast.6 Due to the inhibition by substrate and ethanol, the fermentation processes employed in the Brazilian ethanol industry require a low substrate concentration (∼180.0 g L−1) and as a consequence produce a final wine with low ethanol concentration. Hence, a higher energy input is necessary to produce the hydrous ethanol (95 °GL) that is used as vehicular fuel.13 The low concentration of ethanol obtained results in the generation of large volumes of vinasse (between 10 and 15 L of vinasse per liter of ethanol)14 and steam consumption of around 2.6 kg per kg of ethanol produced.13 Moreover, large vats are needed to ensure sufficient ethanol production, which results in high investment costs. The high concentrations of sugars and ethanol in conventional fermentation broths decrease cell viability, compromising the fermentative process.15 One way to overcome these substrate and ethanol inhibition effects is to use fed-batch Received: October 4, 2017 Revised: December 14, 2017

A

DOI: 10.1021/acs.energyfuels.7b02979 Energy Fuels XXXX, XXX, XXX−XXX

Article

Energy & Fuels fermentation with in situ ethanol removal by CO2 stripping.10 This gas stripping technique is attractive due to its relative simplicity and the selective removal of volatile compounds in clean forms. It does not remove nutrients from the broth and does not harm the cells during the fermentation.16,17 Furthermore, an important feature is that large amounts of carbon dioxide are produced during the industrial fermentation process (around 425 L of CO2 per L of ethanol, at the process pressure and temperature), enabling the use of a zero-cost stripping gas. Previous studies have used gas stripping for the removal of ethanol during continuous fermentation, enabling the use of high concentrations of glucose in the feed and the attainment of high ethanol productivities.18−21 More recent studies have modeled the stripping of ethanol and batch ethanol fermentation with CO2 stripping using sucrose as substrate.22−24 The use of gas stripping has also been evaluated in the acetone−butanol−ethanol (ABE) production process, allowing the use of higher substrate concentrations in the feed solution.16,25−27 In our recent work, a mathematical model was proposed for the description of fed-batch fermentation with ethanol removal by CO2 stripping, with validation of the model using experimental data.10 The results showed that use of the stripping technique together with the fed-batch fermentation process enabled both substrate and ethanol inhibition effects to be overcome. Fermentations were performed with the total sucrose concentration up to 240.0 g L−1, starting the CO2 stripping after 3 h of fermentation (at CE ∼ 40 g L−1), with total substrate consumption after 12 h of the process. However, this condition resulted in a maximum substrate concentration (CS) of 139.3 g L−1 at the end of the filling time (fixed at 5 h). It was therefore evident that in order to use musts with high substrate concentrations, it would be necessary to adjust the feed flow rate (F) of the must, as well as the ethanol concentration (CE0) for starting the CO2 stripping. The literature reports studies that have used optimization tools to define the substrate feed rate profile that maximizes the final amount of ethanol during conventional fed-batch ethanol fermentation.28−30 However, no reports were found concerning the optimization of fed-batch fermentation with ethanol removal by CO2 stripping. In this work, a genetic algorithm (GA) was used to determine the optimal values of both must feed flow rate (F) and the ethanol concentration in the medium (CE0) for starting the CO2 stripping, in order to maximize the ethanol volumetric productivity (PE) in fed-batch fermentation with in situ ethanol removal by CO2 stripping. The optimization tool used enabled evaluation of fermentations with higher total sucrose concentrations in the must (260, 280, and 300 g L−1), overcoming the effects of substrate and ethanol inhibition.

■

the sugar cane must used in Brazilian distilleries. The medium was prepared using analytical grade reagents and contained sources of carbon, nitrogen, phosphorus, potassium, and magnesium, simulating the composition of sugar cane molasses and supplying the nutritional requirements of the yeast. Sucrose was used as feedstock in the fedbatch fermentations. However, substrate (S) was considered the total reducing sugars (TRS), obtained as the sum of glucose and fructose after total inversion of sucrose by yeast invertase. The culture medium contained 5.6 g L−1 KH2PO4, 1.4 g L−1 MgSO4·7H2O, 6.8 g L−1 yeast extract, 5.32 g L−1 urea, and variable amounts of total sucrose (180.0, 260.0, 280.0, and 300.0 g L−1). The initial pH of the fermentation broth was adjusted to 4.6 by adding hydrochloric acid (1.0 mol L−1). In the experiments using 260−300 g L−1 of sucrose, the amounts of KH2PO4, MgSO4.7H2O, yeast extract, and urea were increased by 20.0%.23 Experimental Procedure. As described by Sonego et al.,10 the initial (inoculum) volume of 1.5 L (corresponding to 30% v v−1), containing 75 g (dry weight) of yeast previously hydrated for 30 min in 500 mL of water, was fed into the vat and agitated at 250 rpm. The composition of the inoculum did not include any sucrose or ethanol (CS0 = CE0 = 0 g L−1). A 3.5 L sample of culture medium (70% v v−1) containing sucrose and other reagents (must with sucrose concentrations of 257.1, 371.4, 400.0, and 428.6 g L−1, respectively) was then fed until the vat was full (fed-batch stage), at a feed flow rate (F) defined by the optimization algorithm. The fermentation proceeded until substrate exhaustion (batch stage). A commercial antifoaming agent (Qualifoam, diluted 1:10) was added at the start of the process to prevent excessive foam formation. In the conventional fed-batch fermentation without ethanol stripping, the broth was agitated at 250 rpm throughout the entire process. The temperature was maintained at 34.0 °C by circulating water from a water bath through the bioreactor jacket. Samples of 30 mL were withdrawn on an hourly basis. The must was fed to the vat at a constant volumetric flow rate (F), so the broth volume (V) increased linearly with time, according to eq 1 V = V0 + F·t

(1)

where V0 is the initial volume (L) and F is the feed flow rate of the must (L h−1). The optimized fed-batch fermentations with ethanol removal by CO2 followed the same procedure described for conventional fermentation. However, the mechanical agitation was turned off after the start of ethanol stripping with CO2. The specific CO2 flow rate (ϕ = 2.5 vvm) employed in the ethanol fermentations was adopted from the work of Sonego et al.10 The CO2 flow rate was adjusted using a mass flow controller (GFC 37, Aalborg). Assays were carried out using the feed flow rate of the must (F) and the ethanol concentration for starting the CO2 stripping defined by optimization based on a genetic algorithm (GA). The conventional fed-batch fermentation (CF) and fed-batch stripping fermentations (SF) with ethanol removal by CO2 were performed in duplicate. Analytical Methods. Cell concentrations (on a dry mass basis) were determined after centrifugation of the samples at 10 000 rpm and 4 °C for 10 min. The precipitates were washed twice with distilled water and were then dried at 80 °C for 24 h. The concentrations of sucrose, glucose, fructose, and ethanol in the supernatants were determined using an HPLC (Waters, USA) equipped with a refractive index detector and a Sugar-Pak I column (300 × 6.5 mm, 10 μm, Waters) maintained at 80 °C. Ultrapure water was utilized as the eluent, at a flow rate of 0.5 mL min−1.23 Solutions of sucrose, glucose, fructose, and ethanol, at concentrations between 0.1 and 8.0 g L−1, were used as standards for calibration. Mathematical Modeling of the Conventional Fed-Batch Fermentation. As proposed by Sonego et al.,10 the mathematical modeling of the fed-batch fermentation considered an initial stage of must feeding until the vat was filled (fed-batch stage), followed by a stage in batch mode. During the stage of must feeding, assuming that the generation of the product (ethanol) was associated with cell growth, and considering the variations in volume (V) and feed flow rate (F), the mass balances for cells (X), substrate (S), and ethanol

MATERIALS AND METHODS

Equipment. The conventional and optimized fed-batch fermentations with ethanol removal by CO2 were performed as described by Sonego et al.,10 using a jacketed bubble column pneumatic bioreactor with 5 L working volume.31 The bioreactor was modified with a mechanical agitation system to ensure adequate mixing of the fermentation broth before the start of the CO2 stripping. Microorganism and Culture Medium. Commercial lyophilized Saccharomyces cerevisiae (AB Brasil Indústria e Comércio de Alimentos Ltda, Brazil) was used in this study. The characteristics of the culture medium employed in the fermentations were similar to B

DOI: 10.1021/acs.energyfuels.7b02979 Energy Fuels XXXX, XXX, XXX−XXX

Article

Energy & Fuels

where kE is the ethanol removal rate constant (h−1), kw is the water removal rate constant (h−1), and ρw is the specific mass of water (g L−1). After the must feeding (batch stage):

(E) in the conventional fed-batch fermentation (F ≠ 0) and the batch fermentation (F = 0) could be described by eqs 2−5 dC X Fy i = jjjμ − zzz·C X dt V{ k

dC X 1 dV y i = jjjμ − · zzz·C X dt V dt { k

(2)

ij 1 dCS F F yz = CSF· − jjjj ·μ· C X + · CSzzzz dt V V k YX/S {

ij 1 yz dCS 1 dV = − jjjj ·μ· C X + · · CSzzzz dt V dt k YX/S {

(3)

YE/S dC E F = ·μ·C X − ·C E dt YX/S V

(4)

dV =F dt

(5)

μ = μmax ·

(K

S

+ CS +

CS 2 KIS

)

ij C E yzz zz ·jjjj1 − j C Emax zz k {

n

(6)

J = max(PE = C ET/t T)

C X f ·Vf − C X 0·V0 (Vf − V0)·CS F − CS f ·Vf

(7)

C Ef ·Vf (Vf − V0)·CS F − CS f ·Vf

(8)

ij 1 yz dCS F 1 dV = CS F· − jjjj · μ· C X + · · CSzzzz dt V V dt k YX/S { YE/S dC E 1 dV y i = ·μ·C X − jjjkE + · zzz·C E dt YX/S V dt { k

(kE·C E + k w ·(ρw − C E))·V dV =F− dt ρw

(17)

For stripping fed-batch fermentation, the total ethanol concentration (CET, ethanol in the broth + ethanol removed by CO2 stripping) was obtained using eq 18, where the first term represents the mass of ethanol in the broth at the end of the fermentation and the second term represents the mass of ethanol removed by CO2 stripping.

where the subscripts “0” and “f” refer to the initial and final times, respectively, and the subscript “F” refers to the feed stream. Mathematical Modeling of the Fed-Batch Fermentation with in Situ Ethanol Removal by CO2 Stripping. The mathematical model of the fed-batch fermentation with ethanol removal by CO2 employed mass balance equations for cells (X), substrate (S), and ethanol (E), considering the removal of ethanol (E) and water (W) by the CO2 stream, as well as changes in the broth volume (V). Based on the literature, the classical first-order model was used to describe the removal of ethanol and water from the fermentation broth.10,23 As proposed by Sonego et al.,10 the model used for the fed-batch fermentation with ethanol removal by CO2 could be described by eqs 9−16. During the must feeding (fed-batch stage): dC X 1 dV y i = jjjμ − · zzz·C X dt V dt { k

(16)

In the range of ethanol concentrations employed in this study (40− 80 g L−1), the specific mass of the hydroalcoholic solution was considered to be very close to that of water at 34 °C (ρW = 994 g L−1).34 Changes in CX, CS, and CE during the course of the fermentation were determined by numerical resolution of the set of differential eqs (eqs 9−16) using an algorithm based on the Runge− Kutta method and implemented in Scilab software (version 5.5.2). Optimization of the Conventional and Fed-Batch Fermentation with in Situ Ethanol Removal by CO2 Stripping. The optimization strategy consisted of finding the optimal values of the feed flow rate of the must (F) and the concentration of ethanol (CE0) for starting the CO2 stripping, in order to maximize the objective function (J), defined as the volumetric ethanol productivity (PE, in g L−1 h−1). PE was calculated as the total ethanol concentration (CET) at the end of the fermentation divided by the total time of the process (tT). The objective function to be maximized is given by eq 17.

where μmax is the maximum specific cell growth rate (h ), KS is the saturation constant (g L−1), KIS is the substrate inhibition constant (g L−1), CEmax is the maximum concentration of ethanol after which cell growth ceased, and n is a dimensionless constant. The global cell and ethanol yield coefficients, YX/S and YE/S, were determined using eqs 7 and 8

YE/S =

(15)

(kE· C E + k w · (ρw − C E))· V dV =− dt ρw

−1

YX/S =

(14)

YE/S dC E 1 dV y i = ·μ·C X − jjjkE + · zzz·C E dt YX/S V dt { k

where CX is the cell concentration (g L−1), μ is the specific cell growth rate (h−1), CS is the limiting substrate concentration (g L−1), obtained from the sum of the glucose and fructose (TRS) concentrations, CSF is the substrate concentration in the must feeding (g L−1), CE is the ethanol concentration (g L−1), YX/S is the cell yield coefficient (gX gS−1), and YE/S is the ethanol yield coefficient (gE gS−1). The hybrid Andrews−Levenspiel kinetic model32,33 was used to describe the cell growth, considering inhibition by both substrate and product (eq 6) CS

(13)

tf

C ET =

C Ebf ·Vbf + ∫ kE· C E· V ·dt t 0

Vbf

(18) −1

where CEbf is the final ethanol concentration in the broth (g L ), Vbf is final broth volume (L), V is the broth volume (L), and the subscripts “0” and “f” refer to the initial and final stripping times, respectively. The genetic algorithm (GA) used to perform the optimization interacted with the objective function (J) setting for the feed flow rate of the must (F) and the ethanol concentration (CE0) for starting the CO2 stripping. The optimization was carried out with Scilab software (version 5.5.2), using the GA with 100 generations.

■

RESULTS AND DISCUSSION Optimization of Conventional Fed-Batch Ethanol Fermentation. The cell and ethanol yield coefficients (YX/S and YE/S) were calculated using eqs 7 and 8. The kinetic parameters μmax, KS, KIS, CEmax, and n, and the stripping parameters kE and kW, were as described previously.10 Table 1 presents the values of the yield coefficients and parameters employed in this work. The mathematical model for the conventional fed-batch fermentation (CF), together with the kinetic parameters of the adopted growth model and the yield coefficients (Table 1),

(9)

(10)

(11)

(12) C

DOI: 10.1021/acs.energyfuels.7b02979 Energy Fuels XXXX, XXX, XXX−XXX

Article

Energy & Fuels

rate (F) of 1.00 L h−1. In the work of Sonego et al.,10 values of 9.0 and 9.1 g L−1 h−1 were obtained for conventional fed-batch fermentation with feed flow rate of the must (F) of 1.17 and 0.70 L h−1, respectively, in both cases using a total sucrose concentration of 180.0 g L−1. Hence, use of the genetic algorithm successfully optimized the conventional ethanol fedbatch fermentation (CF). Optimization of the Fed-Batch Ethanol Fermentation with CO 2 Stripping. The modeling of the ethanol fermentation with CO2 stripping (eqs 9−16) employed the kinetic and stripping parameters (Table 1) together with the optimization algorithm in order to determine the best values of the feed flow rate of the must (F) and the concentration of ethanol (CE0) for starting CO2 stripping. The genetic algorithm (GA) provided the following optimized conditions: • SF1 (260.0 g L−1 total sucrose): F = 0.56 L h−1 and CE0 = 34.18 g L−1 • SF2 (280.0 g L−1 total sucrose): F = 0.51 L h−1 and CE0 = 35.24 g L−1 • SF3 (300.0 g L−1 total sucrose): F = 0.44 L h−1 and CE0 = 34.48 g L− The conditions obtained in the optimization procedure were evaluated using experimental stripping ethanol fermentations with CO2 (SF). Figures 2−4 show comparisons of the simulated (lines) and experimental (symbols) values obtained in the ethanol

Table 1. Values of Cell and Ethanol Yield Coefficients and Kinetic and Stripping Parameters Used in the Optimization Step yield coefficients

values

YX/S (gX gS−1) YE/S (gE gS−1) kinetic parametersa

0.0415 ± 0.0022b 0.452 ± 0.006b values

μmax (h−1) KS (g L−1) KIS (g L−1) CEmax (g L−1) n (−) stripping parametersa

0.125 ± 0.002 25.1 ± 1.8 131.8 ± 9.3 86.1 ± 1.7 0.22 ± 0.03 values

kE (h−1) kW (h−1)

0.0656 ± 0.0016 0.00443 ± 0.00002

a

Values obtained from Sonego et al.10 bStandard deviation of the mean (SD).

was used in conjunction with the genetic algorithm (GA) to determine the optimum feed flow rate of the must (F). The optimization indicated that a feed flow rate of 1.0 L h−1 was required for maximum ethanol productivity. In order to validate the condition defined by the optimization, a conventional fed-batch fermentation (CF) was carried out with a sucrose feed at concentration of 180.0 g L−1. Figure 1 compares the experimental and simulated values obtained for the cell (CX), substrate (CS), and ethanol (CE)

Figure 2. Comparison between simulated (line) and experimental values of cell concentration (Cx: green closed boxes), substrate concentration (Cs: red closed diamonds), and ethanol concentration (CE: blue closed circles; CET: blue dashed line) for optimized CO2 stripping fed-batch fermentation with 260.0 g L−1 total sucrose (SF1). Optimized values: F = 0.56 L h−1; CE0 = 34.18 g L−1.

Figure 1. Comparison between simulated (line) and experimental values of cell concentration (Cx: green closed boxes), substrate concentration (Cs: red closed diamonds), and ethanol concentration (CE: blue closed circles) for conventional fed-batch fermentation (CF) with 180.0 g L−1 total sucrose and an optimized must feed flow rate of F = 1.0 L h−1.

fermentations with CO2 stripping. The model described by Sonego et al.10 was adequate to predict the behavior of the optimized stripping fermentations employing high sugar concentrations in the substrate. Figure 2 presents the results of the optimization of stripping fermentation SF1 with a feed flow rate of F = 0.56 L h−1 and ethanol concentration at the beginning of the CO2 stripping of CE0 = 34.18 g L−1. For this condition, the maximum concentration of the substrate in the fermentation broth was 105.2 g L−1 at the end of the vat filling, with a total sucrose concentration in the feed of 260.0 g L−1. The maximum

concentrations. The hybrid Andrews−Levenspiel model provided an excellent description of the behavior of the conventional ethanol fed-batch fermentation. The maximum substrate concentration in the broth at the end of the vat filling stage was 99.4 g L−1. Total substrate consumption occurred at 9 h of fermentation, when the ethanol concentration in the broth was 82.2 g L−1. An ethanol productivity of 9.1 g L−1 h−1 was obtained for the total sucrose concentration of 180.0 g L−1 and the optimum vat filling flow D

DOI: 10.1021/acs.energyfuels.7b02979 Energy Fuels XXXX, XXX, XXX−XXX

Article

Energy & Fuels concentration of ethanol in the fermentation broth was 72.0 g L−1. Complete consumption of the substrate occurred after 13 h of fermentation, resulting in an ethanol productivity of 9.0 g L−1 h−1 (Table 2). Table 2. Comparison of the Performances of the Optimized Conventional Fermentation (CF) and the Optimized CO2 Stripping Fermentations (SF) fermentations variables

unit

CF

SF1

SF2

SF3

Cs0 feed flow rate of the must CE at the start of CO2 stripping maximum CS in the vat (at the end of filling) maximum CE in the fermentation broth CET at the end of fermentation

g L−1 L h−1

183.4 1.0

258.6 0.56

277.1 0.51

304.2 0.44

g L−1

−

34.18

35.24

34.48

g L−1

99.4

105.2

122.7

131.0

g L−1

82.2

72.0

78.2

78.1

g L−1

82.2

116.4

124.7

136.9

°GL g L−1 h−1

10.4 9.1

14.6 9.0

15.8 8.9

17.2 8.6

volumetric ethanol productivity (PE)

Figure 4. Comparison between simulated (line) and experimental values of cell concentration (Cx: green closed boxes), substrate concentration (Cs: red closed diamonds), and ethanol concentration (CE: blue closed circles; CET: blue dashed line) for optimized CO2 stripping fed-batch fermentation with 300.0 g L−1 (SF3) total sucrose. Optimized values: F = 0.44 L h−1; CE0 = 34.48 g L−1.

optimization algorithm, the feed flow rate of the must was F = 0.44 L h−1, and the ethanol concentration at the beginning of the CO2 stripping was CE0 = 34.48 g L−1. The maximum concentration of the substrate in the fermentation broth was Cs = 131.0 g L−1 at the end of the filling stage, and the maximum concentration of ethanol in the fermentation broth was 78.1 g L−1. Complete consumption of the substrate occurred after 16 h of fermentation, resulting in an ethanol productivity of 8.6 g L−1 h−1 (Table 2). The ethanol concentrations (CE) for initiation of CO2 stripping, obtained using the optimization algorithm (Table 2), were around 35.0 g L−1 for the stripping fermentations with high substrate concentrations in the must (SF1, SF2, and SF3). The beginning of the gas stripping using the range of values indicated by the optimization was justified by the fact that inhibition by ethanol at lower concentrations is not significant. According to Aiba et al.35 and Sonego et al.,10,23 it is only at concentrations above 40.0 g L−1 that ethanol begins to significantly affect cell growth and the rate of ethanol production. Lemos et al.36 reported similar ethanol concentration in the broth (∼40.0 g L−1) for starting ethanol removal in liquid−liquid extractive batch ethanol fermentation. Thus, the fed-batch fermentation starting the ethanol removal by CO2 stripping at an ethanol concentration in the broth near CE = 40.0 g L−1 provides a greater reduction of the ethanol inhibition effect, enabling fermentations to be performed with a more concentrated must. According to Thatipamala et al.11 and Zhang et al.,12 substrate inhibition in yeast cells becomes more significant at concentrations higher than around 150.0−160.0 g L−1. The feed flow rates obtained using the optimization algorithm kept the substrate concentration in the vat below 150.0 g L−1, even when the sucrose concentration in the feed was 300.0 g L−1 (SF3). In the stripping fermentation performed with 300.0 g L−1, the feed flow rate was F = 0.44 L h−1. For this condition, the maximum substrate concentration reached in the vat was 131.0 g L−1. In ethanol production by fed-batch fermentation with a feed flow rate (F) of 0.7 L h−1 and total sucrose concentration

Figure 3 presents the results of the optimization of stripping fermentation SF2, performed with a total sucrose concen-

Figure 3. Comparison between simulated (line) and experimental values of cell concentration (Cx: green closed boxes), substrate concentration (Cs: red closed diamonds), and ethanol concentration (CE: blue closed circles; CET: blue dashed line) for optimized CO2 stripping fed-batch fermentation with 280.0 g L−1 (SF2) total sucrose. Optimized values: F = 0.51 L h−1; CE0 = 35.24 g L−1.

tration in the feed of 280 g L−1. In this assay, the optimized values of the feed flow rate of the must and the ethanol concentration at the beginning of the stripping were F = 0.51 L h−1 and CE = 35.24 g L−1, respectively. For this condition, the maximum substrate concentration in the fermentation broth reached Cs = 122.7 g L−1 at the end of the must feeding. Complete consumption of the substrate occurred after 14 h, and the ethanol productivity was 8.9 g L−1 h−1 (Table 2). Figure 4 shows the results for stripping fermentation SF3 with a feed total sucrose concentration of 300 g L−1. Using the E

DOI: 10.1021/acs.energyfuels.7b02979 Energy Fuels XXXX, XXX, XXX−XXX

Article

Energy & Fuels in the feed of 240.0 g L−1, Sonego et al.10 obtained a maximum substrate concentration of 139.3 g L−1 at the end of filling of the vat. It can therefore be seen that the substrate feed flow rate has a substantial influence on the performance of fed-batch fermentation with ethanol removal by CO2 stripping. Establishment of a suitable feed flow rate (F) by optimization enables regulation of the concentration of the substrate in the vat, making it possible to minimize the inhibition by the substrate during the initial fermentation stage. The use of the optimization algorithm therefore allowed adjustment of the feed flow rate (F) and the ethanol concentration for initiation of stripping (CE0) for each substrate concentration evaluated, hence maximizing the ethanol productivity at the end of the fermentations. The maximum ethanol concentrations in the broths in fedbatch stripping fermentations SF1, SF2, and SF3 were 72.0, 78.2, and 78.1 g L−1, respectively (Table 2). These values were lower than the maximum ethanol concentration after cell growth ceases (CEmax = 86.1 g L−1), indicating the possibility of performing fermentation with a total sucrose concentration of up to 300.0 g L−1 (428.6 g L−1 in the must feeding). Moreover, these ethanol concentrations in the broth at the end of the stripping ethanol fermentations were very similar to the values obtained in Brazilian distilleries using the conventional fermentation process. This means that the wine resulting from stripping fermentation carried out with concentrated substrate in the must could be sent to the distillation step without compromising the efficiency of the process. According to Basso et al.,6 the concentration of substrate in the must usually employed in Brazilian distilleries is around 18−22° Brix (∼160−180 g L−1), which results in an ethanol concentration in the wine at the end of the fermentation of around 10 °GL (∼80.0 g L−1). However, with the optimization of the stripping fed-batch fermentation, it was possible to use a 44.4% more concentrated substrate (SF1: 260.0 g L−1 total sucrose), resulting in a total ethanol concentration of 14.6 °GL. When a 55.5% more concentrated substrate was used (SF2: 280.0 g L −1 total sucrose), the total ethanol concentration reached 15.8 °GL. It was also possible to perform a stripping fermentation using a 66.6% more concentrated substrate (SF3: 300.0 g L−1 total sucrose). In this assay the total ethanol concentration reached 17.2 °GL, corresponding to an increase of 65.4%, relative to conventional fermentation without ethanol removal. Sonego et al.10 evaluated ethanol production by stripping fed-batch fermentation using a fixed feed flow rate (F) of 0.7 L h−1, feeding the vat with sucrose up to a concentration of 240.0 g L−1, and obtained a total ethanol concentration of 14.0 °GL. The results demonstrate that fed-batch fermentation allows control of the substrate concentration in the vat, minimizing the effect of substrate inhibition. This, together with gas stripping, makes it possible to minimize the inhibition by ethanol, due to its removal during the fermentation process. The advantage of the optimized fed-batch fermentation with ethanol by CO2 stripping was that it provided an increase in ethanol production, while maintaining the ethanol concentration in the fermentation broth below 80.0 g L−1. An increase of the ethanol concentration in the wine reduces the viability of yeast cells, and it is well-known that the maintenance of high cellular viability is essential in fermentation processes with yeast cell recycling.9 Sonego et al.10 showed that fermentations with ethanol stripping by CO2 resulted in higher cell viability at the end of the fermentations, compared to conventional

fermentations (without gas stripping). Therefore, the process with ethanol removal by CO2 is a promising technology for application in fermentative ethanol production processes with cells recycling. Another advantage of the optimized stripping fed-batch fermentation with high sucrose concentration (up to 300 g L−1) is related to the significant reductions in the volume of vinasse generated, the quantity of wine to be distilled, and the amount of steam used in the distillation stage. According to Lopes et al., 4 a wine with ethanol concentration of 8.0 °GL (∼63 g L−1) results in 11.9 L of vinasse for each liter of ethanol, while when the concentration of ethanol in the wine reaches 16.0 °GL, the vinasse generated decreases to 5.4 L per liter of ethanol produced. Therefore, considering the ethanol produced in stripping fed-batch fermentation SF3 (17.2 °GL), the volume of vinasse generated would be less than 5.4 Lvinasse per Lethanol produced. The vinasse generated in Brazilian distilleries is used in plantations as fertilizer and for irrigation, so the generation of smaller volumes of this material can reduce the costs associated with transportation and application. A higher concentration of sucrose in the must fed in the vat, with consequently a higher total CE at the end of the fermentation, results in the economization of steam in the distillation step. Wine at 8 °GL requires around 2.5−2.6 kg of steam for each liter of ethanol produced.37 An ethanol concentration of 17.2 °GL (SF3) would require about 1.4 kgsteam per Lethanol produced, representing an energy saving of up to 46%. In the context of the Brazilian industry, fed-batch ethanol fermentation using CO2 as stripping gas appears to offer a new approach for reducing the inhibitory effects of substrate and ethanol on yeast cells. It enables the use of high sucrose concentrations and employs the CO2 produced during the ethanol fermentation process itself, resulting in lower overall sugar cane ethanol production costs.

■

CONCLUSIONS The use of a genetic algorithm enabled determination of the optimal values of the feed flow rate of the must and the ethanol concentration in the medium for initiation of stripping, in order to minimize the inhibitory effects related to the substrate and ethanol. With the optimization of the fed-batch fermentation with ethanol removal by CO2 stripping, it was possible to feed the fermenter with a must containing a high sucrose concentration of up to 428.6 g L−1 (300.0 g L−1 total sucrose). The resulting total ethanol concentration of 136.9 g L−1 (17.2 °GL) represented an increase in ethanol production of 65.4%, compared to conventional fermentation without ethanol stripping by CO2. In addition, the use of high concentrations of sucrose in the fed must result in increased ethanol production for the same vat volume, with significant reductions in vinasse generation and steam consumption in the distillation step and maximization of the volumetric ethanol productivity.

■

AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Phone: 55 16 3351-8001. ORCID

A. C. Badino: 0000-0001-8350-9846 F

DOI: 10.1021/acs.energyfuels.7b02979 Energy Fuels XXXX, XXX, XXX−XXX

Article

Energy & Fuels Notes

(26) Xue, C.; Zhao, J.; Lu, C.; Yang, S.-T.; Bai, F.; Tang, I.-C. Biotechnol. Bioeng. 2012, 109, 2746−2756. (27) Rochón, E.; Ferrari, M. D.; Lareo, C. Biomass Bioenergy 2017, 98, 153−160. (28) Hong, J. Biotechnol. Bioeng. 1986, 28, 1421−1431. (29) Huang, W.-H.; Shieh, G. S.; Wang, F.-S. Chem. Eng. Technol. 2010, 33, 1488−1494. (30) Rocha, M.; Mendes, R.; Rocha, O.; Rocha, I.; Ferreira, E. C. Expert Syst. Appl. 2014, 41, 2186−2195. (31) Badino, A. C.; Cerri, M. O.; Hokka, C. O. Sistema reacional pneumático e uso do mesmo. Brazil Patent PI0701608-5, 2007. (32) Andrews, J. F. Biotechnol. Bioeng. 1968, 10, 707−723. (33) Levenspiel, O. Biotechnol. Bioeng. 1980, 22, 1671−1687. (34) Perry, R. H.; Green, D. W.; Maloney, J. O. Perry’s Chemical Engineers’ Handbook; McGraw Hill: New York, 1997. (35) Aiba, S.; Shoda, M.; Nagatani, M. Biotechnol. Bioeng. 1968, 10, 845−864. (36) Lemos, D. A.; Sonego, J. L. S.; Boschiero, M. V.; Araujo, E. C. C.; Cruz, A. J. G.; Badino, A. C. Biochem. Eng. J. 2017, 127, 128−135. (37) Vicente, F. A.; Seleçaõ , C. F. Avaliaçaõ e Utilizaçaõ de uma Levedura Personalizada para a Produçaõ de Etanol. Ph.D. Thesis, São Paulo State University (UNESP), São José do Rio Preto, SP, Brazil, 2015.

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS The authors are grateful for the financial support provided by CAPES (National Council for the Improvement of Higher Education, Brazil), FAPESP (São Paulo State Research Foundation, Brazil, grant 2012/50046-4), and CNPq (National Council for Scientific and Technological Development, grant 431460/2016-7).

■

REFERENCES

(1) Dias, M. O. S.; Modesto, M.; Ensinas, A. V.; Nebra, S. A.; Filho, R. M.; Rossell, C. E. V. Energy 2011, 36, 3691−3703. (2) Mohd Azhar, S. H.; Abdulla, R.; Jambo, S. A.; Marbawi, H.; Gansau, J. A.; Mohd Faik, A. A.; Rodrigues, K. F. Biochem. Biophys. Reports 2017, 10, 52−61. (3) Renewable Fuels Association (RFA), 2016. Industry Statistics: World Fuel Ethanol Production, available at http://www.ethanolrfa. org/resources/industry/statistics/ (accessed Jun, 2017). (4) Lopes, M. L.; Paulillo, S. C.; Godoy, A.; Cherubin, R. A.; Lorenzi, M. S.; Giometti, F. H. C.; Bernardino, C. D.; Amorim Neto, H. B.; Amorim, H. V. d. Braz. J. Microbiol. 2016, 47, 64−76. (5) Companhia Nacional de Abastecimento (CONAB). Acompań April 2017; Vol. 3, hamento da Safra Brasileira; CONAB: Brasilia, Safra 2016/17, no. 4, pp 1−77. (6) Basso, L.; Basso, T.; Rocha, S. Biofuel Prod.-Recent Dev. Prospect. 2011, 1530, 85−100. (7) Godoy, A.; Amorim, H. V.; Lopes, M. L.; Oliveira, A. J. Int. Sugar J. 2008, 110, 175−181. (8) Wheals, A. E.; Basso, L. C.; Alves, D. M. G.; Amorim, H. V. Trends Biotechnol. 1999, 17, 482−487. (9) Amorim, H. V.; Lopes, M. L.; de Castro Oliveira, J. V.; Buckeridge, M. S.; Goldman, G. H. Appl. Microbiol. Biotechnol. 2011, 91, 1267−1275. (10) Sonego, J. L. S.; Lemos, D. A.; Pinto, C. E. M.; Cruz, A. J. G.; Badino, A. C. Energy Fuels 2016, 30, 748−757. (11) Thatipamala, R.; Rohani, S.; Hill, G. A. Biotechnol. Bioeng. 1992, 40, 289−297. (12) Zhang, Q.; Wu, D.; Lin, Y.; Wang, X.; Kong, H.; Tanaka, S. Energy Fuels 2015, 29, 1019−1027. (13) Morandin, M.; Toffolo, A.; Lazzaretto, A.; Maréchal, F.; Ensinas, A. V.; Nebra, S. A. Energy 2011, 36, 3675−3690. (14) Mohana, S.; Acharya, B. K.; Madamwar, D. J. Hazard. Mater. 2009, 163, 12−25. (15) Cray, J. A.; Stevenson, A.; Ball, P.; Bankar, S. B.; Eleutherio, E. C.; Ezeji, T. C.; Singhal, R. S.; Thevelein, J. M.; Timson, D. J.; Hallsworth, J. E. Curr. Opin. Biotechnol. 2015, 33, 228−259. (16) Lu, C.; Zhao, J.; Yang, S.-T.; Wei, D. Bioresour. Technol. 2012, 104, 380−387. (17) Park, C.-H.; Geng, Q. Sep. Purif. Methods 1992, 21, 127−174. (18) Taylor, F.; Kurantz, M. J.; Goldberg, N.; Craig, J. C. Biotechnol. Prog. 1995, 11, 693−698. (19) Taylor, F.; Kurantz, M. J.; Goldberg, N.; Craig, J. C. Biotechnol. Bioeng. 1996, 51, 33−39. (20) Taylor, F.; Kurantz, M. J.; Goldberg, N.; Craig, J. C., Jr. Appl. Microbiol. Biotechnol. 1997, 48, 311−316. (21) Taylor, F.; Marquez, M. A.; Johnston, D. B.; Goldberg, N. M.; Hicks, K. B. Bioresour. Technol. 2010, 101, 4403−4408. (22) Silva, C. R.; Esperança, M. N.; Cruz, A. J. G.; Moura, L. F.; Badino, A. C. Chem. Eng. Res. Des. 2015, 102, 150−160. (23) Sonego, J. L. S.; Lemos, D. A.; Rodriguez, G. Y.; Cruz, A. J. G.; Badino, A. C. Energy Fuels 2014, 28, 7552−7559. (24) Ponce, G. H. S. F.; Moreira Neto, J.; De Jesus, S. S.; Miranda, J. C.; de, C.; Maciel Filho, R.; Andrade, R. R.; Wolf Maciel, M. R. Biochem. Eng. J. 2016, 110, 152−161. (25) Ezeji, T. C.; Qureshi, N.; Blaschek, H. P. Appl. Microbiol. Biotechnol. 2004, 63, 653−658. G

DOI: 10.1021/acs.energyfuels.7b02979 Energy Fuels XXXX, XXX, XXX−XXX