Optimization of Hydrogen Production by Response Surface

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Optimization of hydrogen production by response surface methodology using gamma irradiated sludge as inoculum Yanan Yin, and Jianlong Wang Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.6b00262 • Publication Date (Web): 28 Apr 2016 Downloaded from http://pubs.acs.org on May 3, 2016

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Optimization of hydrogen production by response surface methodology using gamma irradiated sludge as inoculum Yanan Yin1, Jianlong Wang1,2 * 1 Collaborative Innovation Center for Advanced Nuclear Energy Technology, INET, Tsinghua University, Beijing 100084, P. R. China 2 Beijing Key Laboratory of Radioactive Waste Treatment, INET, Tsinghua University, Beijing 100084, P. R. China

∗ Corresponding author Full post address: Neng Ke Lou, Tsinghua University, Beijing 100084, P. R. China

Tel.: +86 10 62784843 Fax: +86 10 62771150 E-mail address: [email protected]

∗ Corresponding author. Tel.: +86 10 62784843; fax: +86 10 62771150. E-mail address: [email protected] 1

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Abstract The temperature, initial pH and substrate concentration on fermentative hydrogen production was optimized by the Box-Behnken design using gamma irradiated sludge as inoculum, and the fermentation process was analyzed at optimal conditions. The experimental results showed that the maximum cumulative hydrogen production was 3000 mL H2/L medium and hydrogen yield was 1.81 mol H2/mol glucose at 32.9 ℃, initial pH=7.92 and glucose concentration=17.0 g/L. Highest hydrogen production rate was accompanied with the exponential growth of microorganisms. The mixed cultures underwent the mixed-acid type fermentation in the first 10 h and then changed to acetate butyrate pathway until the end of fermentation. Hydrogen yield showed positive relationship with acetate generation during the fermentation process. Key words: fermentative hydrogen production; response surface methodology; optimization; gamma irradiation

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1. Introduction As an important resource, hydrogen is attracting worldwide attentions not only for its essential function in fertilizer and petroleum industries but as a promising fuel candidate [1]. Hydrogen can be generated through various methods, for example the traditional methods like steam reforming of hydrocarbons, partial oxidation of fossil fuels, electrolysis of water, etc. and newly developed hydrogen production from renewable sources [2-6]. Among these methods biological dark fermentation owns advantages due to its environmental benefit and high hydrogen production rates [7]. Pure or mixed cultures have been used for fermentative hydrogen production, and mixed cultures were more preferable for process simplicity. Furthermore, mixed cultures can be more efficient and economical in hydrogen generation when low-value wastes are used as substrate [8-11]. To be further developed, hydrogen production through biological fermentation is restricted by its limited hydrogen production rate and yield comparing with thermochemical method. Lots of efforts have been made to increase hydrogen yield and hydrogen production rate in the dark fermentation process, such as controlling community structure of inoculum and optimizing operation parameters [12-14]. For the inoculum preparation, various methods were studied to enrich hydrogen producers and inhibit hydrogen consumers coexist in the mixed cultures. These methods include heat shock [15], acid [16], base [17], aeration [18], methanogen inhibitors [19-21], microwave [22], ultrasonication [23], UV radiation [24], electric field [25], and load shock [26] and so on. Gamma irradiation was explored as an innovative pretreatment method in screening hydrogen producers from digested sludge in our previous study, and it showed superiority over traditional pretreatment methods like heat shock, acid and base treatment both in cumulative hydrogen production and hydrogen production rate [27-29]. Since fermentative hydrogen production is a complex metabolic process, which can be affected by many factors, such as temperature, pH, substrate concentration, C/N 3


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ratio and various trace elements [12]. Appropriate temperature can promote hydrogen production rate, suitable pH can help improve hydrogen yield through affecting microbial metabolism pathway. Substrate concentration and the C/N ratio can affect both microbial diversity and metabolic pathway. Various trace elements are vital constitutes of essential enzymes for hydrogen production. Lots of studies have been conducted to optimize the fermentation conditions [30-32]. The optimization methods include one-factor experimental design and multifactor experimental design. Multifactor experimental designs like Orthogonal design, the Plackette-Burman design and response surface methodology are used in hydrogen production process for it can be less laborious and time-consuming considering various influencing factors. Furthermore, to determine the interaction effects among variables and give closer confirmation of the influencing factors, response surface methodology has been extensively used in optimizing hydrogen production process. Most widely used designs of response surface methodology include central composite design (CCD) and the Box-Behnken design (BBD) [33-35]. Observation of hydrogen production and metabolites generation at different time intervals can help us take a closer insight into the metabolic pathway for fermentative hydrogen production, and then to deduce the relationship among hydrogen generation, biological growth and metabolites production. It was found that Clostridium species follow butyrate-type fermentation throughout the fermentation process [36-38], and enteric bacterium undergoes mixed-acid fermentation [39]. However, few studies have explored the metabolic process of hydrogen generation by mixed cultures. In this study, gamma irradiation pretreated sludge was used as inoculum for fermentative hydrogen production, three process parameters including temperature, initial pH and substrate concentration were optimized using response surface methodology with a Box-Behnken design (BBD). Furthermore, the metabolites generation and the association of hydrogen production with microbial growth were analyzed at optimal conditions.

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2. Materials and methods 2.1 Seed sludge and pretreatment Anaerobic sludge collected from a primary anaerobic digester located in Beijing (China) was used as inoculum. The pH and volatile suspended solids (VSS) of the digested sludge were determined to be 7.50 and 2.42 g/L, respectively. The sludge was stored at 4 ℃ until being used. Seed sludge was pretreated by gamma irradiation to inhibit the non-hydrogen producers. Radiation source was supplied by the Institute of Nuclear and New Energy Technology (INET), which was a

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Co-source with around 1.26×1015 Bq. For the

pretreatment process, 100 mL of anaerobic sludge was put in a sealed bottle and irradiated with a dose rate of 286 Gy/min. The absorbed dose was 5 kGy (17.5 min) and the irradiation process was performed at ambient temperature (around 25 ℃). 2.2 Three-factor Box-Behnken design and response surface analysis Three-factor Box-Behnken design [40] was used to examine the interaction effect of independent variables on response. Temperature (X1), initial pH (X2) and substrate concentration (X3) were taken as independent variables, while cumulative hydrogen production was chosen as the response variable. The levels of the variables and the experimental design are shown in Table 2. A quadratic model (Equation (1)) was used to fit the experimental data obtained from Table 1.

(1) Where Y is the corresponding response variable, Xi (i=1, 2, 3) are the actual values of the independent variables. A series of designed experiments were conducted to obtain an optimal response and determine the values of An (n=0, 1, 2, 3, 12, 13…). The Design Expert (Version 8.0.6, Stat-Ease Inc., Minneapolis, USA) software package was used for experimental design, regression and response surface analysis. 2.3 Hydrogen production process 5


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2.3.1

Inoculum preparation

Before being used as inoculum, gamma irradiation pretreated digested sludge was pre-cultured in 150 mL Erlenmeyer flasks to cultivate the microorganisms. Each 10 mL of pretreated sludge were inoculated in 90 mL medium that contains 5 g glucose, 1 g peptone, 0.05 g yeast extract and 10 mL of nutrient solution. The composition of nutrient solution is same as previously reported [27-29]. The initial pH was adjusted to 7.0 by 1 mol/L HCl and 1 mol/L NaOH. The flasks were flushed with nitrogen gas for 5 min to create the anaerobic condition and then placed in a reciprocal shaker (100 r/min) at 36 ℃ for 36 h. After the enrichment process, the mixtures were centrifuged at 4000 r/min for 5 min to get the inoculum. The inoculum was washed by 0.9% NaCl solution for 3 times before being used in the following batch experiments. 2.3.2

Optimization of hydrogen production

According to experimental design in Table 1, batch tests were performed in 150 mL Erlenmeyer flasks with working volume of 100 mL. Silicone rubber stoppers were used to avoid gas leakage from the bottles. The pH value of different batches was adjusted by 1 mol/L HCl and 1 mol/L NaOH. Temperature was maintained by a constant temperature reciprocal shaker (100 r/min). Glucose was used as the sole carbon source, 10 mL of pre-cultured seed sludge and 10 mL nutrient solution were added in each bottle. Before the incubation, nitrogen gas was passed through the culture medium for 3 min to provide the anaerobic conditions. All the batch tests were performed in duplicate. 2.3.3

Hydrogen production under the optimum condition The hydrogen production with gamma irradiation pretreated digested sludge

under the optimized conditions (temperature 32.9 ℃, pH 7.92, glucose concentration 17.0 g/L and 10 mL nutrient solution for each 100 mL medium) were then studied. A set of eleven 150 mL flasks working volume of 100 mL in duplicate were used in the experiment. Two bottles were removed every 2-8 h (according to the hydrogen production rate) to analysis different parameters during the hydrogen production process, such as cumulative hydrogen production, glucose degradation rate, cell dry weight (CDW), change in pH and volatile fatty acids (VFA). 6


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2.4 Analytical methods The volume of biogas produced was determined at room temperature (25 ℃) by measuring the water displaced by the gas produced. The fraction of H2 in the biogas was measured by a gas chromatograph (model 112A, Shanghai, China) and the volatile fatty acids (VFA) were analyzed using an ion chromatograph (Dionex model ICS 2100) [41, 42]. The pH value was obtained by Thermo Orion 8103BN, USA. The concentration of glucose was determined using DNS colorimetric method [43]. The volatile suspended solids (VSS) of the digested sludge was determined according to the standard methods [44]. Cell dry weight (CDW) was measured as following: cells were centrifuged at 4000 r/min for 5 min to be separated from the medium, and then washed twice with 0.9% NaCl solution, dried at 95 ℃ for 48 h to constant weight.

3. Results and discussion 3.1 Optimization of hydrogen production using Box–Behnken design (BBD) Table 1 showed the comparison of different pretreated inoculum on fermentative hydrogen production. Substrate of all the experiments listed are 10 g/L glucose and experiments were conducted at mesophilic conditions (35-37 ℃). It can be seen that 5 kGy dose gamma irradiation pretreated sludge showed superiority over other traditional methods both in cumulative hydrogen production and hydrogen yield. Table 1 In present study, 5 kGy gamma irradiation pretreated digested sludge was employed as inoculum to produce hydrogen from glucose under different operational conditions such as temperature (25-40 ℃), initial pH (5-10) and initial glucose concentration (5-20 g/L) in batch mode. Three factors with three levels of Box-Behnken response surface design (BBD) were adopted to investigate and optimize the effect of process variables on cumulative hydrogen production. The design matrix of the variables (temperature (X1/x1), initial pH (X2/x2) and glucose concentration (X3/x3)) along with the experimental values of the corresponding response variable (cumulative hydrogen production (Y)) in the uncoded and coded 7


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units are shown in Table 2. The response function in terms of actual factors (equation (2)) was obtained by using equation (1) to fit the experimental data of cumulative hydrogen production.

(2)

Table 2

Analysis of variance (ANOVA) was used to examine the significance of the fitting model, along with the linear effect, quadratic effect and interactive effect of the variables. Higher F-value indicates an adequate description of the variation about its mean. P-values (Prob > F) less than 0.0500 indicate model terms are significant while greater than 0.1000 indicate the model terms are insignificant. As shown in Table 3, the model F-value of 17.08 and P-value of 0.0030 imply the model was significant. There was only 0.30 % chance that a “Model F-value” this large could occur due to the noise. Coefficient of determination (R2) was 0.9685, which can explain 96.85% variability of the response variable. Thus, equation (2) could be used in this study to describe the effect of temperatures, initial pH and substrate concentrations on cumulative hydrogen production significantly. ANOVA of the fitting model also showed that the linear effect of substrate concentration, interactive effect between initial pH and substrate concentration, and quadratic effect of all three variables had a great impact on cumulative hydrogen (P < 0.05). However, linear effect of temperature and initial pH, interactive effect between temperature and initial pH, and between temperature and substrate concentration on cumulative hydrogen production were not significant (P > 0.05), indicating that these terms held little influence on cumulative hydrogen production. Subsequently, the maximum cumulative hydrogen production of 2853 mL/L medium was estimated from equation (2) at the temperature of 32.9 ℃, the initial pH of 7.92 and the glucose concentration of 17.0 g/L. The optimal conditions for hydrogen production were different from our previous study that used heat-shock treated digested sludge as inoculum [45], which may due to the difference of 8


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dominant microorganisms present in differently pretreated mixed cultures.

Table 3

Response surface analysis shows the interactions between two variables by keeping the other one at its optimum level for hydrogen production. As shown in Fig. 1, A1 and A2, B1 and B2, and C1 and C2 were plotted with substrate concentration, initial pH and temperature being kept constant at 17.0 g/L, 7.92 and 32.9 ℃, respectively. A clear peak point can be found in each response surface plot, which indicates the maximum cumulative hydrogen production could be achieved inside the design boundary of all three variables. A critical analysis of the response surface plots reveals a significant interaction between initial pH and temperature on cumulative hydrogen production (Fig. 1 A), which means that different temperatures were favored for hydrogen production when the mixed cultures were set into different initial pH environment. In case of the interaction between substrate concentration and temperature, cumulative hydrogen production was observed to increase with the increase of glucose concentration, and reached its maximum at glucose concentration of 17.0 g/L, as shown in Fig. 1 B, further increase of substrate concentration led to a little decrease in cumulative hydrogen production, which may because of the substrate inhibition. A similar conclusion was also drawn by Wang and Wan [45]. It worth mentioning that the lower glucose concentration preferred for hydrogen production at lower temperature while higher glucose concentration preferred at higher temperature. One possible reason is that different temperatures are favored by different microbial species and enzymes, resulting in the change of metabolism pathway of the mixed consortia and further led to the different hydrogen production process. Similar phenomenon was observed in case of interaction between substrate concentration and initial pH. As shown in Fig. 1 C, when the initial pH of the medium was at a low level, maximum cumulative hydrogen production was obtained at lower glucose concentration. However, highest hydrogen production was achieved at maximal glucose concentration when initial pH was 10. This phenomenon indicates that higher initial pH can help decrease the effect 9


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of substrate inhibition. Since the fermentative hydrogen production is accompanied with the accumulation of volatile fatty acids (VFA), which can lead to the pH decrease [46]. Higher initial pH can help to dissolute the formed VFA, leading to the alleviation of product inhibition. From Fig. 1 we can see that temperature, initial pH and substrate concentration all had significant influence on hydrogen production. Temperature affects the microbial activity greatly, and low temperature may inhibit the vital enzymes for hydrogen production and lead to both low hydrogen production rate and low substrate utilization rate. Although there is no final conclusion of optimal temperature for fermentative hydrogen, best hydrogen productions were always obtained at around 37 ℃ for mesophilic reactions and 55 ℃ for thermophilic reactions [12]. pH affects the electric charge on the cell membrane, which influences both microbial enzyme activity and nutrient absorption. The optimum pH for fermentative hydrogen production ranges from pH 4.5 to 9, pH lower than 4.5 can lead to the deterioration of microorganisms and further suppress the hydrogen production process [47]. Thus, with a low initial pH, the decrease of pH can easily prevent substrate from being further used for hydrogen production. Increase of substrate concentration to a certain extent can usually lead to the increase of hydrogen production. However, too high concentration results in quick pH decrease, accumulation of VFA and other metabolites that may inhibit hydrogen producers, leading to low hydrogen production.

Figure 1

3.2 Hydrogen production at optimal conditions Based on the experiments described above, fermentative hydrogen production by gamma irradiation pretreated digested sludge was carried out under optimized conditions (temperature 32.9 ℃, pH 7.92, glucose concentration 17.0 g/L) in batch mode. As shown in Fig. 2 a, fermentation process finished in 24 h fermentation, maximum cumulative hydrogen production of 3000 mL/L medium and hydrogen 10


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yield of 1.81 mol H2/mol glucose was achieved. Substrate utilization was accompanied with hydrogen production and the degradation rate reached 78.1% at the end of fermentation. The maximum cumulative hydrogen production was higher than we have obtained (2647 mL/L) in the previous study since the operation conditions were optimized [28, 29]. However, the hydrogen yield and substrate degradation rate were all lower, possible reason is high substrate concentration resulted in the incomplete degradation and conversion of glucose to hydrogen. Many studies have found that the improvement of substrate concentration can lead to the decrease of hydrogen yield and substrate degradation [35, 48, 49]. Fig. 2 b depicts the microorganism growth during the fermentation process. The cell growth was consistent with the hydrogen generation and substrate consumption. The bacteria entered the exponential growth phase directly without experiencing a lag phase, it may because of the inoculum was precultured for 36 h before being inoculated for hydrogen production. Similar phenomenon was also observed by Harun et al. [39] and Abdeshahian et al. [36]. Our previous studies also found that lag time of hydrogen production can be shortened prominently through preculturing the inoculum [28, 29]. Besides, the optimized conditions and sufficient nutrients in culture medium could also attribute to early exponential phase [39, 50]. The exponential phase continued up to10 h and followed by stationary phase, which lasted for 14 h. The hydrogen production was consistently maintained throughout the exponential and stationary phase, and higher hydrogen production rate was obtained when the microorganisms were at their exponential phase (Fig. 2 c). Studies done by Abdeshahian et al., Singh et al. and Wang et al. had come to the same conclusion with fermentative hydrogen production inoculated a Clostridium strain, thermosaccharolyticum strain and a newly isolated hydrogen-producing strain, respectively [36, 51, 52]. However, different phenomenon was observed by Harun et al. who employed Enterobacter cloacae as inoculum, got highest hydrogen production rate both at exponential and stationary phase [39]. After 24 h, the bacteria entered the decline phase and hydrogen production terminated accordingly. Fig. 2 d depicts the hydrogen yield at different fermentation time intervals. The 11


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highest hydrogen yield was achieved in the first 4 h, and fluctuated in the following 20 h. The significant difference of hydrogen yield can be attributed to the change of metabolic pathways by the mixed cultures at different time intervals.

Figure 2

As demonstrated in Fig. 3 a, with the accumulation of hydrogen, formation of acidic metabolites and decrease of pH happened correspondingly. The pH showed a significant decline from 7.92 to 4.77 during the first 6 h, and then dropped gradually to around 4.5 in the following 20 h and stayed consistent. Similar trend has also been observed by Harun et al. [39] and Singh et al. [51], which may due to the accumulation of volatile fatty acids. Over the time, drop of pH inhibited both microorganism growth and hydrogen production, no more hydrogen was produced when pH value achieved 4.5. Similar phenomenon has been reported in literature [39, 53, 54]. Fig. 3 b depicts the generation of volatile fatty acids at different time intervals during the hydrogen production process. It can be seen that in the first 10 h, formic acid, acetic acid, propionic acid and butyric acid were all produced during this period, indicating that the culture followed mixed acid pathway. Then, in the following 14 h, acetic acid and butyrate acid were accumulated as the main soluble metabolites, indicating that the fermentation transformed to acetate butyrate pathway. Possible reason is that in the first 10 h, nutrients and pH conditions are suitable for microbial growth and metabolism, the culture was rich in biodiversity, leading to various metabolism pathway and mixed acids generation. However, after 10 h fermentation, with the accumulation of soluble metabolites, pH decreased and substrate depleted, lots of microbes were inhibited. As demonstrated in our previous study, the mixed culture showed great microbial diversity after gamma irradiation pretreatment while after fermentation process, Clostridium species became dominant and occupied over 90 % [27], which has been reported to undergo butyrate-type fermentation [36-38].Thus, the formation of various acids in the first 10 h shows the active effect of 12


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diverse bacteria, and acetate butyrate pathway in the late phase was due to the dominant performance of Clostridium species. No generation of formic acid after 8 h may be due to the low pH induced activity of formate-hydrogen lyase [55].

Figure 3

Lots of studies have proved the relationship between metabolites generation and hydrogen production process [46, 56]. Studies done by Badiei et al. have shown a positive relationship between hydrogen and butyrate generation[57], and in this study, highest hydrogen production rate of 262.5 mL/L/h was achieved when butyrate acid was continuously generated (Fig. 2 c). Furthermore, hydrogen yield (Fig. 2 d) also showed a similar trend with the generation of acetic acid. Highest hydrogen yield was corresponded with the peak generation of acetic acid during the process. As widely accepted that the theoretical maximum hydrogen production of 4 mol can be produced from 1 mol of glucose in acetate type fermentation, thus it’s reasonable for the positive correlation between hydrogen yield and acetate generation.

4. Conclusions Gamma irradiated sludge was used as inoculum for fermentative hydrogen production and operational conditions were optimized by response surface methodology with a Box-Behnken design. Optimal conditions for hydrogen production were estimated to be 32.9 ℃, initial pH of 7.92 and glucose concentration of 17.0 g/L. Cumulative hydrogen production of 3000 mL H2/L medium, hydrogen yield of 1.81 mol H2/mol glucose and substrate degradation rate of 78.1% were achieved at optimal conditions. During the fermentation process, hydrogen generation and hydrogen production rate was highest at the exponential growth of microorganisms. Mixed cultures followed mixed-acid type fermentation in the first 10 h and changed to acetate butyrate pathway in the following 14 h. Hydrogen yield showed positive relationship with acetate generation during the process. 13


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5. Acknowledgements The research was supported by the Program for Changjiang Scholars and Innovative Research Team in University (IRT-13026). The authors would also like to thank the financial support provided by the National Natural Science Foundation of China (51338005).

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[15]. Wang JL, Wan W, Comparison of different pretreatment methods for enriching hydrogen-producing bacteria from digested sludge. Int J Hydrogen Energ 2008; 33: 2934-2941. [16]. Lee MJ, Song JH, Hwang SJ, Effects of acid pre-treatment on bio-hydrogen production and microbial communities during dark fermentation. Bioresour Technol 2009; 100: 1491-1493. [17]. de Sá LRV, Cammarota MC, de Oliveira TC, Oliveira EMM, Matos A, Ferreira-Leitão VS, Pentoses, hexoses and glycerin as substrates for biohydrogen production: An approach for Brazilian biofuel integration. Int J Hydrogen Energ 2013; 38: 2986-2997. [18]. Ren NQ, Chua H, Chan SY, Tsang YF, Wang YJ, Sin N, Assessing optimal fermentation type for bio-hydrogen production in continuous-flow acidogenic reactors. Bioresource Technol 2007; 98: 1774-1780. [19]. Dohme F, Machmüller A, Wasserfallen A, Kreuzer M, Ruminal methanogenesis as influenced by individual fatty acids supplemented to complete ruminant diets. Lett Appl Microbiol 2001; 32: 47-51. [20]. Hu B, Chen SL, Pretreatment of methanogenic granules for immobilized hydrogen fermentation. Int J Hydrogen Energ 2007; 32: 3266-3273. [21]. Ray S, Saady N, Lalman J, Diverting Electron Fluxes to Hydrogen in Mixed Anaerobic Communities Fed with Glucose and Unsaturated C18 Long Chain Fatty Acids. J Environ Eng 2009; 136: 568-575. [22]. Singhal Y, Singh R, Effect of microwave pretreatment of mixed culture on biohydrogen production from waste of sweet produced from Benincasa hispida. Int J Hydrogen Energ 2014; 39: 7534-7540. [23]. Elbeshbishy E, Hafez H, Nakhla G, Enhancement of biohydrogen producing using ultrasonication. Int J Hydrogen Energ 2010; 35: 6184-6193. [24]. Wang H, Fang M, Fang Z, Bu H, Effects of sludge pretreatments and organic acids on hydrogen production by anaerobic fermentation. Bioresource Technol 2010; 101: 8731-8735. [25]. Jeong D, Cho S, Shin H, Jung K, Application of an electric field for pretreatment of a seeding source for dark fermentative hydrogen production. Bioresour Technol 2013; 139: 393-396. [26]. O-Thong S, Prasertsan P, Birkeland N, Evaluation of methods for preparing hydrogen-producing seed inocula under thermophilic condition by process performance and microbial community analysis. Bioresour Technol 2009; 100: 909-918. [27]. Yin YN, Wang JL, Changes in microbial community during biohydrogen production using gamma irradiated sludge as inoculum. Bioresour Technol 2016; 200: 217-222. [28]. Yin YN, Hu J, Wang JL, Enriching hydrogen-producing bacteria from digested sludge by different pretreatment methods. Int J Hydrogen Energ 2014; 39: 13550-13556. [29]. Yin YN, Hu J, Wang JL, Gamma irradiation as a pretreatment method for enriching hydrogen-producing bacteria from digested sludge. Int J Hydrogen Energ 16


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Energy & Fuels

Figure Captions

Figure 1 Response surface plot and corresponding contour plot for cumulative hydrogen production Figure 2 The profile of hydrogen production at optimal conditions: (a) cumulative hydrogen production and substrate degradation; (b) cell growth; (c) hydrogen production rate; (d) hydrogen yield. Figure 3 The profile of soluble metabolites during hydrogen production: (a) total volatile fatty acid and pH changes; (b) volatile fatty acids generation at different time intervals.

Table 1 Comparison of differently pretreated inoculum on hydrogen production Table 2 Experimental design for optimizing fermentative hydrogen production process and the corresponding experimental results Table 3 ANOVA of the fitting model for cumulative hydrogen production

19


Energy & Fuels

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Figure 1

20


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Energy & Fuels

Figure 2

21


Energy & Fuels

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Figure 3

22


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Energy & Fuels

Table 1

Pretreatment methods

Pretreatment conditions

Heat shock

1.39

[28]

Heat shock Heat shock Acid

100 ℃ for 15 min 1784.5 100 ℃ for 15 min 2154 121 ℃ for 20 min 1895 pH 3 for 24 h 1136

1.78 -1.19

[15] [58] [28]

Acid Base Base

pH 3 for 24 h pH 10 for 24 h pH 11 for 24 h

-1.72 --

[58] [28] [58]

Chloroform

2% Chloroform 530 for 24h Continuous 802 aeration for 24 h

0.69

[15]

0.86

[15]

2245

1.96

[58]

1539 2647 2145

1.05 2.15 1.74

[29] [29] [29]

Aeration Aeration Gamma irradiation Gamma irradiation Gamma irradiation

Repeated aeration for 12 h 0.5 kGy dose 5 kGy dose 10 kGy dose

Cumulative hydrogen production (mL/L)

519 2013 1341

Hydrogen References yield (mol H2/mol glucose)

23


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Table 2

Run

Temperature (℃)

Initial pH

Glucose

Cumulative

concentration

hydrogen

(g/L)

production (mL/L)

X1

x1

X2

x2

X3

x3

Y

1

40

1

10

0

12.5

-1

0

2

25

-1

7.5

1

20

0

1100

3

25

0

5

0

12.5

0

0

4

40

1

7.5

-1

5

0

850

5

40

-1

5

-1

12.5

0

0

6

32.5

0

7.5

1

12.5

1

2680

7

25

-1

7.5

0

5

-1

770

8

32.5

1

5

1

20

0

520

9

32.5

0

10

-1

5

-1

220

10

40

0

7.5

0

20

0

1750

11

32.5

-1

10

0

20

1

2200

12

25

0

10

-1

12.5

1

280

13

32.5

0

7.5

0

12.5

0

2700

14

32.5

1

7.5

0

12.5

1

2750

15

32.5

0

5

1

5

-1

250

24


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Energy & Fuels

Table 3

Sum of

Degree of

Mean

Source

P-value F-Value

Squares Model

freedom

(Prob>F)

Square

152114.00

9

16901.55

17.08

0.0030

X1

253.12

1

253.125

0.26

0.6345

X2

4656.12

1

4656.125

4.71

0.0822

X3

15138.00

1

15138.00

15.30

0.0113

X1X2

196.00

1

196.00

0.20

0.6749

X1X3

812.25

1

812.25

0.82

0.4065

X2X3

7310.25

1

7310.25

7.39

0.0419

X12

49683.69

1

49683.69

50.21

0.0009

X22

80876.31

1

80876.31

81.73

0.0003

X32

6906.69

1

6906.692

6.98

0.0459

Residual

4947.75

5

989.55

4921.75

3

1640.583

126.20

0.0079

26.00

2

13.00

157061.70

14

Lack

of

Fit Pure Error Total

25


Optimization of Hydrogen Production by Response Surface

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