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Co-digestion of food waste and sludge for hydrogenproduction by anaerobic mixed cultures: Statistical key factorsoptimization

Chakkrit Sreela-or a, Pensri Plangklang a, Tsuyoshi Imai b, Alissara Reungsang a,c,*aDepartment of Biotechnology, Faculty of Technology, Khon Kaen University, A. Muang, Khon Kaen 40002, ThailandbDivision of Environmental Science and Engineering, Graduate School of Science and Engineering, Yamaguchi University,

Yamaguchi 755-8611, Japanc Fermentation Research Center for Value Added Agricultural Products, Khon Kaen University, Khon Kaen 40002, Thailand

a r t i c l e i n f o

Article history:

Received 20 February 2011

Received in revised form

22 May 2011

Accepted 24 May 2011

Available online 25 June 2011

Keywords:

Bio-hydrogen

Co-digestion

Food waste

Sludge

Response surface methodology

Optimization

* Corresponding author. Fermentation ReseaThailand. Tel./fax: þ66 43 362 121.

E-mail address: alissara@kku.ac.th (A. Re0360-3199/$ e see front matter Copyright ªdoi:10.1016/j.ijhydene.2011.05.145

a b s t r a c t

Factors affecting hydrogen production from the co-digestion of food waste and sludge in

batch fermentation by anaerobic mixed cultures were optimized using Response Surface

Methodology with Central Composite Design. Investigated parameters included C/N ratio,

inoculums concentration, Na2HPO4 concentration and Endo nutrient addition. The exper-

iments were conducted in 120 mL serum bottles with a working volume of 70 mL. Results

revealed that the optimum conditions were a C/N ratio of 33.14, inoculums concentration

of 2.70 g-VSS/L, Na2HPO4 concentration of 6.27 g/L and Endo nutrient addition of 7.51 mL/L.

Under the optimal conditions, a maximum hydrogen yield (HY) of 102.63 mLH2/g-VSadded

and specific hydrogen production rate (SHPR) of 59.62 mLH2/g-VSS h were obtained. C/N

ratio and inoculums concentration showed the greatest individual and interactive effects

on HY and SHPR (P< 0.05). Endo nutrient addition also had an individual effect on SHPR

(P¼ 0.0124). The confirmation experiment under optimal condition showed an HY and

SHPR of 101.14 mLH2/g-VSadded and 59.43 mLH2/g-VSS h, respectively. This was only 1.01%

and 1.00%, respectively, different from the predicted values.

Copyright ª 2011, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights

reserved.

1. Introduction fermentation by cyanobacteria, algae, photosynthetic and

As a sustainable energy, hydrogen is a promising alternative

renewable energy and is considered as a clean and environ-

mentally friendly energy. When hydrogen is combusted with

oxygen, water is obtained as a by-product [1]. Hydrogen has

a high energy yield of 122 kJ/g, which is 2.75 times greater than

that of hydrocarbon fuel [2]. Hydrogen production from bio-

logical processes can be divided into two types i.e. photo-

rch Center for Value Adde

ungsang).2011, Hydrogen Energy P

chemosyntheticefermentative bacteria and dark fermenta-

tion by anaerobic bacteria [3]. Hydrogen production from the

dark fermentation process has advantages over the photo-

fermentation process which is a low operating cost because

light is not required and the rate of hydrogen production is

greater [4].

In Thailand, the generation of food waste is about 20,041

tons per day, which accounts for 50% of municipal solid waste

d Agricultural Products, Khon Kaen University, Khon Kaen 40002,

ublications, LLC. Published by Elsevier Ltd. All rights reserved.

i n t e rn a t i o n a l j o u r n a l o f h y d r o g e n en e r g y 3 6 ( 2 0 1 1 ) 1 4 2 2 7e1 4 2 3 714228

[5]. Foodwaste consistsmainly of starch, protein, and fat, with

a small amount of cellulose and hemi-cellulose which are

possible sources for bioenergy production [6]. Due to its high

organic content and its easily hydrolyzable nature, food waste

is a good candidate to be used as the substrate for producing

hydrogen by dark fermentation. However, food waste may

lack of a nitrogen source which is a nutrient essential for

hydrogen production [7]. Therefore, a search for a nitrogen

source to co-digest with food waste in order to achieve

a maximum hydrogen production is needed. Recent research

has been investigating the use of sludge as a substrate to

produce or co-produce renewable energy i.e. hydrogen and

methane by an anaerobic digestion process because of its high

carbon and nitrogen content [8]. Approximately 160 tons of

sludge is generated daily in Thailand [9]. Therefore, a utiliza-

tion of sludge for production of hydrogen is one of the alter-

nate approaches to reduce or get rid of this abundant amount

of waste. Co-digestion of food waste and sludge to produce

hydrogenhas been reported and it was found that the addition

of sludge to food waste supplied a more balanced carbon to

nitrogen (C/N) ratio [10].

The efficiency of hydrogen production is greatly influ-

enced by environmental factors such as temperature, pH,

nutrient, ferrous iron and substrate concentration [11]. Co-

digestion of food waste and sludge to produce hydrogen

may encounter the problem of the inoculums being outgrown

by normal flora in food waste and sludge. Therefore, the

inoculums concentration needs to be optimized. The C/N

ratio is important in a biological process. Microbes require

a proper nitrogen supplement for metabolism during

fermentation [12]. A proper C/N ratio could enhance the

bacterial productivity of hydrogen suggesting that nitrogen

should be supplied at the optimal amount [13]. The pH is also

one of the factors controlling anaerobic biological processes.

A buffer is required to reduce the fluctuation of pH during

hydrogen fermentation because a formation of hydrogen is

always accompanied by volatile fatty acids (VFAs) or

solvents. A failure in pH control from the imbalances of

alkalinity, pH and VFAs concentration might result in an

interruption in hydrogen production [13] and inhibit the

growth of hydrogen producers [14]. Therefore, the addition of

buffer at a suitable concentration to counteract a decrease in

pH would remove this limitation. Another important envi-

ronmental factor affecting hydrogen production is nutrients.

Hydrogen producing bacteria need nutrients for cell biomass

and metabolites production [13]. In addition, nutrient can

increase microbial activity so that they can effectively

convert soluble organic matters into hydrogen [15].

From the aforementioned reasons, it can be seen that in

order to efficiently produce hydrogen there is a need to

optimize these environmental factors. However, it is labo-

rious and time consuming to perform the optimization by

a conventional technique or known as “a one factor at

a time” method [16]. A statistical experimental design

response surface methodology (RSM) can eliminate this

limitation [17]. It is not only a time saving method but also

can minimize the error in determining the effects of

parameters as well as be able to demonstrate the interactive

effects among the tested variables [18]. In this study, RSM

with central composite design (CCD) was used to study the

effects of C/N ratio, inoculums concentration, Na2HPO4

concentration and Endo nutrient addition on hydrogen yield

(HY) and specific hydrogen production rate (SHPR). CCD has

the advantages in term of rotability and the ability to

analyze all the quadratic and interaction effects [19]. In

addition, CCD offers 5 level of factors (i.e. �a, �1, 0, 1, þa)

which facilitating the findings of the optimal point wider

than the other designs [19].

Statistical optimization design on bio-hydrogen produc-

tion has recently been reported in literatures [20e24]. For

instance, Saraphirom and Reungsang [11] studied the factors

affecting bio-hydrogen production from sweet sorghum syrup

by anaerobic mixed cultures using CCD. Lee et al. [21] inves-

tigated the effects of temperature, pH and starch concentra-

tion on fermentative hydrogen production from starch by

mixed anaerobic microflora using RSM. Pan et al. [22] inves-

tigated process parameters on bio-hydrogen production from

glucose by Clostridium sp. Fanp2 using PlacketteBurman

design and BoxeBehnken design. O-Thong et al. [24] investi-

gated factors affecting hydrogen production from palm oil

mill effluent (POME) under thermophilic condition using an

RSMwith CCD. Althoughmany studies have been done on the

effect of environmental factors on hydrogen production from

various kinds of synthetic substrates and wastes but the

information on the statistically optimization of environ-

mental factors on bio-hydrogen production from a co-diges-

tion of food waste and sludge by anaerobic mixed cultures

are still lacking.

Therefore, this research attempted to optimize C/N ratio,

inoculums concentration, Na2HPO4 concentration and Endo

nutrient addition using the RSM with CCD in order to maxi-

mize an HY and the SHPR. The information obtained from

this study could pave the way toward a scaling up of the

hydrogen production process and/or a continuous hydrogen

fermentation process from a co-digestion of food waste and

sludge.

2. Materials and methods

2.1. Preparation of feed stocks

Food waste was collected from a cafeteria on the Khon Kaen

University campus, Khon Kaen, Thailand. The waste was

made up of rice, vegetables, fruits and meats. Bones were

removed from the food waste before being mixed with tap

water at the volumetric ratio of 1:3; it was then ground in

a food blender. The pH of the resulting food waste slurry

was 7.2. Chemical characteristics of the food waste are

shown in Table 1. The resulting food waste slurry was

stored at �17 �C and thawed in the refrigerator before being

used.

The sludge was taken from the dissolved air flotation tank

of the wastewater treatment plant of a food company in the

Northeastern part of Thailand. Dissolved air flotation tank is

used as a pretreatment to remove the debris as well as sludge

from the factory before the influent is sent to the wastewater

treatment plant. The company produces 5000 tons/day of

frozen meat products and 1600 tons/day of ready meals. The

plant handles an average 6500 m3 of wastewater daily and

Table 2 e Experimental variables and levels investigatedby central composite design.

Variable Parameter value

�2 �1 0 1 2

X1: C/N ratio 10.00 20.00 30.00 40.00 50.00

X2: inoculums concentration

(g-VSS/L)

0.74 1.48 2.22 2.96 3.70

X3: Na2HPO4 concentration

(g/L)

2.00 4.00 6.00 8.00 10.00

X4: Endo nutrient addition

(mL/L)

2.50 5.00 7.50 10.00 12.50

Table 1 e Chemical characteristics of food waste andsludge used in this study.

Parameters Food waste (mg/L) Sludge (mg/L)

Total COD 116,000.00 147,000.00

Total nitrogen 840.00 22,790.00

Total phosphate 1.98 2.62

Magnesium 7.94 6.40

Manganese 0.25 0.08

Iron 0.27 1.44

Copper 0.03 0.48

Sodium 36.00 32.44

Cobalt 0.003 0.012

i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n en e r g y 3 6 ( 2 0 1 1 ) 1 4 2 2 7e1 4 2 3 7 14229

generates 70e80 tons of sludge per day. Chemical character-

istics of the sludge are shown in Table 1. The collected sludge

was stored at 4 �C prior the usage.

2.2. Seed sludge and preparation of inoculums

Anaerobic seed sludge was obtained from the full-scale

anaerobic digester of an Upflow Anaerobic Sludge Blanket

(UASB) reactor, which belonged to a brewery company in the

Northeastern part of Thailand. The UASB is used to produce

methane from the wastewater of the beer production process.

The collected sludge was pre-heated at 105 �C for 3 h in

a drying oven (LDO-100E) in order to deactivate methanogens

which are hydrogen consumers. The pH and volatile sus-

pended solids (VSS) concentration of the sludge were 6.8 and

7.4 g/L, respectively.

For inoculums preparation, pre-heated sludge was culti-

vated in food waste at 20 g-COD/L supplemented with 0.5 mL/

L of Endo nutrient solution [25]. The culture was shaken at

150 rpm for 36 h at 30� 2 �C before being used as the inocu-

lums in the batch experiment. After 36 h, the seed sludge was

centrifuged at 12,000 rpm for 5 min, then analyzed for

biomass concentration (in terms of VSS) and used as inocu-

lums at various concentrations according to the design. Endo

nutrient solution used in the bio-hydrogen production

experiment was slightly modified in which it did not contain

NaHCO3. The composition of the Endo nutrient was as follows

(all in mg/L): 5240 NH4HCO3, 125 K2HPO4, 100 MgCl2$6H2O, 15

MnSO4$6H2O, 25 FeSO4$7H2O, 5 CuSO4$5H2O, and 0.125

CoCl2$5H2O. NH4HCO3 in the Endo nutrient solution was used

as the initial alkalinity.

2.3. Bio-hydrogen production

Bio-hydrogen production experiment was conducted in

120 mL serum bottles with a working volume of 70 mL. The

fermentation broth contained different C/N ratio and

concentrations of variables according to the design. Total COD

and total N were used to represent the amount of carbon and

nitrogen, respectively. In order to obtain substrate ingredi-

ents, food waste and sludge were mixed at various ratio so

that the final C/N ratio were 10:1, 20:1, 30:1, 40:1 and 50:1. The

serum bottles were flushed with nitrogen gas to remove

oxygen in the headspace of the bottles in order to create the

required anaerobic condition and capped with rubber stop-

pers. The bottles were incubated at room temperature

(30� 2 �C) and operated in an orbital shaker with a rotation

speed of 150 rpm. At designed time, the total gas volume was

measured by releasing the pressure in the bottles using

wetted glass syringe [26] and then analyzed for gas content by

gas chromatography equipped with a thermal conductivity

detector (TCD). Effluent was collected by using a glass syringe

and analyzed for VFAs and alcohol by gas chromatography

equipped with a flame ionization detector (FID). All treat-

ments were conducted in four replications. The hydrogen

production was continued until the biogas volume could not

be measured.

2.4. Experimental design and data analysis

CCD was used to study the effects of C/N ratio, inoculums

concentration, Na2HPO4 concentration and Endo nutrient

addition on HY and SHPR. The experiments were designed by

the Design Expert version 7.0� software, Stat-Ease Inc., MN,

USA. The ranges and levels of independent input variables are

shown in Table 2. The HY and SHPR were selected as the

dependent output variables. For statistical calculations, the

test factors (Xi) were coded as xi according to the following

transformation equation (Eq. (1)):

xi ¼ ðXi � X0Þ=DXi; (1)

where xi is the coded value of the variable Xi, Xi is the actual

value of the ith independent variable, X0 is the actual value of

Xi at the center point and DXi is the step change value. A

quadratic model (Eq. (2)) [27] was used to evaluate the opti-

mization of C/N ratio, inoculums concentration, Na2HPO4

concentration and Endo nutrient addition:

Yi ¼ b0 þX

bixi þX

biix2i þ

Xbijxixj (2)

where Yi is the predicted responses, xi is the parameters, b0 is

a constant, bi is the linear coefficients, bii is the squared coef-

ficients, and bij is the cross-product coefficients. The response

variables (YHY¼ the HY response and YSHPR¼ the SHPR

response) were fitted using a predictive polynomial quadratic

equation (Eq. (2)) in order to correlate the response variables to

the independent variables [28]. The YHY and YSHPR values were

regressed with respect to C/N ratio (X1), inoculums concen-

tration (X2), Na2HPO4 concentration (X3) and Endo nutrient

addition (X4). Table 3 illustrates the coded values of the vari-

ables, the experimental design and the corresponding results.

Table 3 e Central composite experimental design matrix defining C/N ratio (X1) inoculums concentration (X2), Na2HPO4

concentration (X3) and Endo nutrient addition (X4) for optimizing the fermentative hydrogen production process and thecorresponding experimental results.

Run Parameter HY(mLH2/g-VSadded)

SHPR(mLH2/g-VSS h)

X1 X2 X3 X4 Observed Predicted Observed Predicted

1 2 0 0 0 43.05 43.03 27.92 27.95

2 �1 1 1 �1 57.75 57.72 38.22 32.05

3 �1 1 �1 1 54.59 54.56 16.13 16.79

4 0 0 0 0 95.97 96.79 52.83 55.97

5 1 1 1 1 78.39 78.36 44.43 42.84

6 0 2 0 0 75.45 75.41 44.23 42.26

7 1 �1 �1 �1 33.83 33.80 18.02 14.79

8 0 0 2 0 64.83 64.81 19.29 22.65

9 0 0 0 0 94.21 96.79 55.32 55.97

10 �2 0 0 0 21.77 21.75 9.52 9.75

11 0 0 0 0 98.14 96.79 52.67 55.97

12 1 1 �1 1 76.21 76.22 32.30 38.59

13 �1 �1 1 �1 34.95 34.92 22.97 18.17

14 �1 �1 �1 �1 35.35 35.34 10.31 10.19

15 0 0 0 2 62.39 62.37 42.58 34.47

16 1 1 1 �1 80.07 80.06 39.86 41.50

17 0 0 0 0 96.33 96.79 56.29 55.97

18 0 0 0 0 98.82 96.79 61.57 55.97

19 �1 �1 1 1 33.71 33.70 14.78 17.44

20 1 �1 �1 1 35.23 35.22 14.73 19.17

21 1 1 �1 �1 75.79 75.76 40.67 36.29

22 �1 1 1 1 55.52 55.54 24.51 29.24

23 0 0 �2 0 63.11 63.09 13.56 10.41

24 1 �1 1 1 33.79 33.80 19.02 17.99

25 �1 �1 �1 1 36.27 36.28 10.54 10.42

26 0 0 0 �2 63.15 63.13 24.56 32.90

27 �1 1 �1 �1 54.53 54.58 16.08 18.64

28 0 0 0 0 97.29 96.79 57.13 55.97

29 1 �1 1 �1 34.57 34.54 16.96 14.58

30 0 �2 0 0 11.57 11.61 6.78 8.96

i n t e rn a t i o n a l j o u r n a l o f h y d r o g e n en e r g y 3 6 ( 2 0 1 1 ) 1 4 2 2 7e1 4 2 3 714230

2.5. Analytical methods

Biogas composition was measured by a gas chromatography

(GC-2014, Shimadzu) equipped with a TCD and a 2 m stain-

less column packed with Unibeads C (60/80 mesh). The

operational temperatures of the injection port, the column

oven and the detector were 150, 145 and 150 �C, respectively.Argon was used as the carrier gas at a flow rate of 25 mL/min.

For VFAs and alcohols analysis, the collected effluents were

first centrifuged at 6000 rpm for 10 min then acidified by

0.2 N oxalic acid and finally filtered through a 0.45 m cellu-

lose acetate membrane. The same GCmodel with an FID and

a 30 m� 0.25 mm� 0.25 m capillary column (Stabiwax) was

used to analyze the VFAs and alcohols concentrations. The

temperatures of the injector and detector were 250 �C. Theinitial temperature of the column oven was 50 �C for 2 min;

this was followed by a ramp of 15 �C/min for 12.6 min and

then raised to a final temperature of 240 �C for 1 min. Helium

was used as the carrier gas with a flow rate of 66 mL/min.

Concentrations of total nitrogen, total phosphate, magne-

sium, manganese, iron, copper, sodium, cobalt, VSS, and vola-

tile solid (VS)weremeasuredusing the procedures described in

standard methods [29]. Hydrogen gas production was calcu-

lated fromtheheadspacemeasurementofgascompositionand

the total volume of hydrogen produced, at each time interval,

using themass balance equation (Eq. (3)) [30]:

VH;i ¼ VH;i�1 þ CH;i

�VG;i � VG;i�1

�þ VH;0

�CH;i � CH;i�1

�(3)

where VH,i and VH,i�1 are the cumulative hydrogen gas

volumes at the current (i) and previous time interval (i� 1),

respectively; VG,i and VG,i�1 are total biogas volume at the

current and previous time interval (i� 1); CH,i and CH,i�1 are the

fraction of hydrogen gas in the headspace at the current and

previous time interval (i� 1) and VH is the volume of the

headspace of the serum bottles (50 mL).

2.6. Kinetic analysis

The modified Gompertz equation (Eq. (4)) was used to deter-

mine the cumulative hydrogen production [31].

H ¼ P exp

�� exp

�RmeP

ðl� tÞ þ 1

��(4)

whereH is thecumulativevolumeofhydrogenproduced (mL),Rmis the maximum hydrogen production rate (mL/h), l is the lag-

phase time (h), t is the incubation time (h), P is the hydrogen

production potential (mL) and e is 2.718281828. Parameters (P, Rm

i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n en e r g y 3 6 ( 2 0 1 1 ) 1 4 2 2 7e1 4 2 3 7 14231

and l)wereestimatedusing thesolver function inMicrosoft Excel

version 5.0 (Microsoft, Inc.) as explained by Khanal et al. [32].

3. Results and discussion

3.1. The effects of C/N ratio, inoculums concentration,Na2HPO4 concentration and Endo nutrient addition on HY

The effects of independent variables i.e., C/N ratio (X1), inoc-

ulums concentration (X2), Na2HPO4 concentration (X3) and

Endo nutrient addition (X4) on HY obtained from the

co-digestion of food waste and sludge were investigated.

Regression analysis of the data from Table 3 resulted in the

quadratic equation (Eq. (5)) as follows:

YHY ¼ 96:63þ 5:321X1 þ 15:95X2 þ 0:43X3 � 0:19X4

þ 5:68X1X2 þ 0:29X1X3 þ 0:12X1X4 þ 0:89X2X3

� 0:23X2X4 � 0:54X3X4 � 16:06X21 � 13:28X2

2

� 8:17X23 � 8:47X2

4 ð5Þ

The ANOVA of the model (Table 4) indicated that the model

significantly represents the experimental data (P< 0.0001). A

high determination coefficient (R2) of 0.99 suggested that the

model can explain 99% variability of the response variables. In

addition, the lack of fit of the model was insignificant

(P¼ 1.0000). These results indicated that the effects of inde-

pendent variables on HY in this study can bewell described by

the obtained models. The ANOVA of the model also showed

that the quadratic model terms of all variables and the linear

model terms of the C/N ratio and inoculums concentration are

highly significant (P< 0.0001). This indicates that these terms

greatly affect the HY. Only the interaction model term of C/N

Table 4 e ANOVA of the fitting model for HY and SHPR.

Source YHYa

Sum ofsquares

Degree offreedom

Meansquare

F value P va

Model 18,885.49 14 1348.963 193.2299 <0.00

X1 679.4704 1 679.4704 97.32956 <0.00

X2 6108.85 1 6108.85 875.0517 <0.00

X3 4.4376 1 4.4376 0.635656 0.437

X4 0.897067 1 0.897067 0.128499 0.725

X1X2 516.4256 1 516.4256 73.97449 <0.00

X1X3 1.3225 1 1.3225 0.189439 0.669

X1X4 0.2209 1 0.2209 0.031642 0.861

X2X3 12.6736 1 12.6736 1.815408 0.197

X2X4 0.8836 1 0.8836 0.12657 0.727

X3X4 4.644025 1 4.644025 0.665225 0.427

X12 7070.622 1 7070.622 1012.819 <0.00

X22 4834.072 1 4834.072 692.4483 <0.00

X32 1828.867 1 1828.867 261.9728 <0.00

X42 1965.718 1 1965.718 281.5759 <0.00

Residual 104.717 15 6.981131 e e

Lack of fit 0.003233 10 0.000323 1.54E�05 1.000

Pure error 104.7137 5 20.94275 e e

Total 18,990.2 29 e e e

a YHY¼ the hydrogen yield response.

b YSHPR¼ the specific hydrogen production rate response.

ratio and inoculums concentration had impact on HY indi-

cating by the P value less than 0.05.

Based on the regression analysis of the model (Eq. (5)), the

maximum HY of 102.63 mLH2/g-VSadded could be predicted at

the optimum conditions of 33.14 C/N ratio, 2.70 g-VSS/L inoc-

ulums concentration, 6.27 g/L Na2HPO4 concentration and

7.51 mL/L Endo nutrient addition.

The response surface plots based on Eq. (5), with two

variables kept constant at their optimum values and varia-

tions of the other two variables within the experimental

range, are depicted in Fig. 1. Fig. 1aef is plotted with Na2HPO4

concentration and Endo nutrient addition, inoculums

concentration and Endo nutrient addition, inoculums

concentration andNa2HPO4 concentration, C/N ratio and Endo

nutrient addition, C/N ratio and Na2HPO4 concentration and

C/N ratio and inoculums concentration, respectively, being

kept constant. Each response surface plot has a clear peak

which suggested that the optimum condition fell well inside

the design boundary (Fig. 1).

HY significantly increasedwith the increase in theC/N ratio

from20 to 33.14 and thenHYdecreasedwhen theC/N ratiowas

greater than 33.14 (Fig. 1aec). The C/N ratio is important in the

biological processes by affecting hydrogen fermentation effi-

ciency. A suitable C/N ratio could enhance microbial growth

and substrate utilization, thus improving the hydrogen

production efficiency [33]. It is normally found that microor-

ganisms utilize carbon 25e30 times faster than nitrogen. To

meet this requirement, a C/N ratio of 20e30:1 is needed [12].

Our results showed a similar trend in which the optimumC/N

ratio was 33.14. The optimum C/N ratio varied depending on

types of substrate and microorganism used. A C/N ratio of 74

was optimum for thermophillic hydrogen production from

POME by acclimatized Thermoanaerobacterium-rich sludge [24]

YSHPRb

lue Sum ofsquares

Degree offreedom

Meansquare

F value P value

01 8042.967 14 574.4976 20.63119 <0.0001

01 497.169 1 497.169 17.85418 0.0007

01 1662.9 1 1662.9 59.71756 <0.0001

7 224.5891 1 224.5891 8.065375 0.0124

0 3.68632 1 3.68632 0.132382 0.7211

01 170.2154 1 170.2154 6.112725 0.0259

6 67.56221 1 67.56221 2.426274 0.1402

2 17.1702 1 17.1702 0.616611 0.4445

9 29.44555 1 29.44555 1.05744 0.3201

0 4.255998 1 4.255998 0.15284 0.7013

5 0.944583 1 0.944583 0.033922 0.8563

01 2364.231 1 2364.231 84.90356 <0.0001

01 1578.971 1 1578.971 56.70355 <0.0001

01 2665.763 1 2665.763 95.73209 <0.0001

01 851.5418 1 851.5418 30.58031 <0.0001

417.6911 15 27.84608 e e

0 363.7077 10 36.37077 3.368698 0.0962

53.98342 5 10.79668 e e

8460.658 29 e e e

Fig. 1 e Response surface plots showing the effects of C/N ratio, inoculums concentration, Na2HPO4 concentration and Endo

nutrient addition on HY.

i n t e rn a t i o n a l j o u r n a l o f h y d r o g e n en e r g y 3 6 ( 2 0 1 1 ) 1 4 2 2 7e1 4 2 3 714232

while the hydrogen production from sucrose by anaerobic

mixed cultures was optimized at the C/N ratio of 47 [34].

Without a nitrogen source, hydrogen could not be produced by

Clostridiumbutyricum [12]. Under an excess ofN source (lowC/N

ratio) condition, the substrate wasmostly used for cell growth

resulting in a lowHY. In contrast, the excess of C/N ratio could

decrease hydrogenproduction efficiency because lownitrogen

contents are deficient for cell growth [13].

Fig. 2 e Response surface plots showing the effects of C/N ratio, inoculums concentration, Na2HPO4 concentration and Endo

nutrient addition on SHPR.

i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n en e r g y 3 6 ( 2 0 1 1 ) 1 4 2 2 7e1 4 2 3 7 14233

i n t e rn a t i o n a l j o u r n a l o f h y d r o g e n en e r g y 3 6 ( 2 0 1 1 ) 1 4 2 2 7e1 4 2 3 714234

The HY increased when the inoculums concentration

increased from 1.48 to 2.70 g-VSS/L. However, a further

increased in inoculums concentration to greater than 2.70 g-

VSS/L resulted in a decrease in HY (Fig. 1a, d and e). Using an

inadequate inoculums concentration, the hydrogen producers

in the seed inoculumsmight not be capable of competingwith

indigenous microflora in the substrate. The indigenous

microflora might become dominant and produce the products

that do not relate to hydrogen production or thatmight inhibit

the hydrogen producers thus reducing the HY. In addition, the

increase in inoculums concentration to a concentration

greater than the optimum value might cause a rapid drop of

pH in the fermentation broth. This would make the microor-

ganisms more favorable for solvent production (second

growth phase) and stop the first metabolites production (acids

and gases) [35]. Therefore, the inoculums concentration

should be compatible with the available substrate for maxi-

mizing bacterial activity.

The effects of the Na2HPO4 concentration on HY were not

significant (P¼ 0.4377) (Table 4). The HY increased when

Na2HPO4 concentration increased from 4.00 to 6.27 g/L indi-

cating a positive effect of Na2HPO4 concentration on HY

(Fig. 1b, d and f). Na2HPO4 could improve the hydrogen

production due to its buffering capacity because it can reduce

the pH fluctuation caused by VFAs accumulated in the

fermentation broth, thus enhancing the hydrogen generation

and acidogenesis in the first stage of an acid-gas digestion

system [36,37]. In addition, the P element in Na2HPO4 is

essential for the synthesis of many molecular substances

such as DNA, RNA and ATP [38]. A further increase in Na2HPO4

concentration to greater than 6.27 g/L resulted in a decrease in

HY which may be due to an increase in cytoplasmic osmotic

pressure that occurs at high Na2HPO4 concentration [39].

An increase in Endo nutrient addition from 5.00 to 7.51mL/L

slightly increased the HY (Fig. 1c, e and f). Endo nutrient

contains elements that are essential for cell synthesis and

microbial growth such as Fe, Co2þ, Cu2þ, Mg2þ and Mn2þ. Ironis the most important hydrogen production related trace

element because it forms ferredoxin and hydrogenase, which

directly relate to the hydrogen production process [36]. Co2þ,Cu2þ, Mg2þ and Mn2þ are known as the enzyme cofactor [37].

NH4HCO3 in the Endo nutrient can prevent the fluctuation of

the pH during hydrogen fermentation [40]. However, the

results indicate that HY was decreased when the Endo

nutrient additionwas greater than 7.51 mL/L. This may be due

to the dissolution of bicarbonate in NH4HCO3 could increase

CO2 in the system which therefore decreases the hydrogen

Table 5 e Experimental design and results of confirmation tes

Run Condition X1 X2 X3 X4 HY(mLH2/g-VSadded) (m

e Optimuma 33.14 2.70 6.27 7.51 102.63

26 High 40.00 2.96 8.00 10.00 78.36

18 Medium 30.00 2.22 6.00 7.50 96.79

15 Worst 20.00 1.48 4.00 5.00 35.34

a Based on HY and SHPR.

content in the gas phase. In addition, the high ammonium

concentration can cause adverse effect on microorganisms

[15]. Moreover, Fe and Cu at high concentrations could inhibit

and reduce the activity of hydrogen producers [41,42].

3.2. The effects of C/N ratio, inoculums concentration,Na2HPO4 concentration and Endo nutrient addition on SHPR

Effects of C/N ratio (X1), inoculums concentration (X2),

Na2HPO4 concentration (X3) and Endo nutrient addition (X4) on

SHPR (YSHPR) during the co-digestion of food waste and sludge

were examined. The observed and predicted values of SHPR

are presented in Table 3. Multiple regression analysis was

applied on the data in Table 3 and the obtained second-order

polynomial equation (Eq. (6)) could well explain the SHPR.

YSHPR ¼ 55:97þ4:55X1 þ8:32X2 þ3:06X3 þ0:39X4 þ3:26X1X2

�2:05X1X3 þ1:04X1X4 þ1:36X2X3 �0:52X2X4 �0:24X3X4

�9:28X21 �7:59X2

2 �9:86X23 �5:57X2

4 ð6Þ

It is evident from ANOVA (Table 4) that the quadratic

regression model of YSHPR was highly significant with a low

probability (P< 0.0001) and fit the experimental data well with

the R2 value of 0.95 accompanied by an insignificant lack of fit

model (P¼ 0.0962). The 3 variables i.e., C/N ratio, inoculums

concentration and Na2HPO4 concentration were significant

effect on SHPR (P< 0.05) whereas Endo nutrient addition had

insignificant effect on SHPR (P¼ 0.7211). Results demonstrated

that the only significant interaction effect on SHPR was found

between C/N ratio and inoculums concentration (P¼ 0.0259).

The analysis of Eq. (6) provided the optimum conditions for

SHPR: a C/N ratio of 33.14, an inoculums concentration of 2.70 g-

VSS/L, aNa2HPO4 concentration of 6.27 g/L and an Endonutrient

addition of 7.51 mL/L. The maximum SHPR of 59.62 mLH2/

g-VSSh was obtained under these optimum conditions.

The response surface plots base on Eq. (6) with two vari-

ables being kept constant at their optimum values and vari-

ations of the other 2 variables within the experimental range

are depicted in Fig. 2. Fig. 2aef is plotted with Na2HPO4

concentration and Endo nutrient addition, inoculums

concentration and Endo nutrient addition, inoculums

concentration andNa2HPO4 concentration, C/N ratio and Endo

nutrient addition, C/N ratio and Na2HPO4 concentration and

C/N ratio and inoculums concentration, respectively, being

kept constant. Results indicated a clear peak for each response

surface plot (Fig. 2) which suggested that the optimum

condition fell well inside the design boundary.

t obtained at 144 h (data are gives as mean; n[ 3).

SHPRLH2/g-VSS h)

Butyricacid(g/L)

Aceticacid(g/L)

Propionicacid(g/L)

Formicacid(g/L)

Ethanol(g/L)

59.62 3.88 1.83 0.26 0.06 0.32

42.84 3.69 1.50 0.43 0.13 0.41

55.97 3.74 1.53 0.39 0.09 0.39

10.19 2.82 1.05 0.87 0.30 0.81

Time (h)

0 20 40 60 80 100 120 140

Cum

ulat

ive

hydr

ogen

pro

duct

ion

(mL

)

0

100

200

300

400

500

600

700

Hyd

roge

n yi

eld

(mL

H2/

g-V

S ad

ded)

0

20

40

60

80

100

120

140

Cumulative hydrogen productionHydrogen yield

Fig. 3 e Cumulative hydrogen production and HY in

a confirmation experiment at optimum condition.

i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n en e r g y 3 6 ( 2 0 1 1 ) 1 4 2 2 7e1 4 2 3 7 14235

Fig. 2aec revealed that the SHPR increased significantly

with an increase in the C/N ratio from 20 to 33.14. Conversely,

the SHPR decreased with the further increase of C/N ratio to

over 33.14.

The SHPR increased when the inoculums concentration

was increased from 1.48 to 2.70 g-VSS/L and then decreased

slightly following a further increase in inoculums concentra-

tion (Fig. 2a, d and e).

An increase in Na2HPO4 concentration from 4.00 to 6.27 g/L

resulted in an increase in the SHPR to the maximum value.

The SHPR decreased when the Na2HPO4 concentration was

greater than 6.27 g/L (Fig. 2b, d and f).

Results showed in Fig. 2c, e and f indicated that the SHPR

increasedwhen theEndonutrient additionwas increased from

5.00 to 7.51 mL/L. A further increase in Endo nutrient addition

to greater than 7.51 mL/L resulted in a decrease of the SHPR.

3.3. Optimization and confirmation of the experiments

The analysis of YHY (Eq. (5)) and YSHPR (Eq. (6))models indicated

that in order to simultaneously obtain the maximum HY and

SHPR, the C/N ratio, inoculums concentration, Na2HPO4

concentration and Endonutrient addition should be optimized

at 33.14, 2.70 g-VSS/L, 6.27 g/L and 7.51 mL/L, respectively

(Table 5). Under these optimal conditions, themodel predicted

anHYof 102.63 mLH2/g-VSadded and an SHPR of 59.62 mLH2/g-

VSS h In order to confirm the validity of the statistical

Table 6 e Comparison of HY and SHPR by various types of ino

Inoculums Foodwaste:sludgeratio(v/v)

Inoculumsconcentration

(g-VSS/L)

Bufferconcentration

(g/L)

Anaerobic digester

in a local wastewater

treatment plant

8:2 0.55 NA

Aged refuse from

Shanghai Laogang

Landfill

10:3 NA NA

Anaerobic digester from

a primary anaerobic

digester at the Skyway

Wastewater Treatment

Plant (Burlington,

Ontario, Canada)

1:1 NA K2HPO4 of

7.85 and

KH2PO4

of 16.05

Anaerobic digester

of Upflow Anaerobic

Sludge Blanket (UASB)

reactor of the brewery

company in the

Northeastern part of

Thailand

6.5:1 2.70 Na2HPO4

of 5.82

NA: not available.

experimental strategy, three replications of batch experiments

were conducted under optimal, medium (runs 4, 9, 11, 17, 18,

28), high (run 5) and worst (run 14) conditions (Table 5). The

results of the confirmation experiments are in close agreement

with the predicted values of HY and an SHPR. An HY of

101.14 mLH2/g-VSadded and SHPR of 59.43 mLH2/g-VSS h were

obtained at the optimumcondition. These results ensured that

the obtained models are satisfactory and accurate.

culums in batch experiments.

Nutrient(final

concentration;mg/L)

HY(mLH2/g-VSadded)

SHPR Reference

KH2PO4; 200,

MgCl2$4H2O; 14,

Na2MoO4$4H2O; 2,

CaCl2$2H2O; 2,

MnCl2$6H2O; 2.5,

FeCl2$4H2O; 10

59.2 22.6 mL

H2/g

VSS h

[45]

NA 195.6 94.3 mL

H2/g-

VS h

[10]

NA 112 NA [8]

7.42 mL/L of stock

solution containing

NH4HCO3; 5240,

K2HPO4; 125,

MgCl2$6H2O; 100,

MnSO4; 6H2O; 15,

FeSO4$7H2O; 25,

CuSO4$5H2O; 5,

CoCl2$5H2O; 0.125,

NaHCO3; 6720.

102.6 59.6 mL

H2/g-

VSS h

This

study

i n t e rn a t i o n a l j o u r n a l o f h y d r o g e n en e r g y 3 6 ( 2 0 1 1 ) 1 4 2 2 7e1 4 2 3 714236

The change in the HY and the development of hydrogen

during the fermentation process in the confirmation experi-

ment at the optimum condition are depicted in Fig. 3. The

biogas produced in this study mainly comprised of hydrogen

and carbon dioxide without methane (data not shown). The

short lag phase of 2.4 h of hydrogen production was observed.

A sharply increase in hydrogen production was observed from

2.4 to 48 h after which the hydrogen production increase

gradually (Fig. 3a).

At the end of fermentation, themain SMPswere butyric acid

(61.1%) and acetic acid (28.8%). A small amount of ethanol (5.0%)

propionic acid (4.0%) and formic acid (1.1%) was also detected

(Table 5). The detection of butyric and acetic acids is a good

indicator that efficient hydrogen production was achieved [43].

Theoretically, 4 moles of hydrogen are produced from glucose

concomitantly with 2 moles of acetate, while 2 moles of

hydrogen are produced when butyrate is the main metabolite

[44].Thepresenceofagreateramountofbutyrate thanacetate in

this study indicated that the hydrogen fermentation was buty-

rate type fermentation. Low amounts of ethanol and propionic

acid coincided with the high HY obtained.

The results at the optimum condition in this study were

compared to the results from the literature search of using

food waste and sludge as substrate for hydrogen production

(Table 6). The HY obtained in this study was greater than that

obtained in the study of Shin et al. [45]. However, our HY was

lower than in the study ofMing et al. [10] and Zhu et al. [8]. The

differencesmight be a result of the composition of foodwaste,

sludge as well as the type of seed inoculums.

4. Conclusions

This study successfully used food waste to co-digest with

sludge for a production of hydrogen. The optimum conditions

for hydrogen production from the co-digestion of food waste

to sludge were C/N ratio of 33.14, inoculums concentration of

2.70 g-VSS/L, Na2HPO4 concentration of 6.27 g/L and Endo

nutrient addition of 7.51 mL/L. Under the optimum condi-

tions, the predicted HY and SHPRwere 102.63 mLH2/g-VSaddedand 59.62 mLH2/g-VSS h, respectively. These values were

relatively close to the experimental values of 101.14 mLH2/g-

VSadded and 59.43 mLH2/g-VSS h. The HY and SHPR obtained

from the experiments were only 1.01% and 1.00%, respec-

tively, away from the predicted value.

Acknowledgments

The authors gratefully received the research funds from

Energy Policy and Planning Office, Ministry of Energy,

Research Group for Development of Microbial Hydrogen

Production Process from Biomass, the Higher Education

Research Promotion and National Research University Project

for Thailand, Office of the Higher Education Commission

through Biofuels Research Cluster of Khon Kaen University,

and the Program for Promotion of Basic Research Activities for

Innovative Biosciences and the Special Coordination Funds for

Promoting Science and Technology, Ministry of Education,

Culture, Sports, Science and Technology, Japan. Our

appreciation is given to the Graduate School, Khon Kaen

University for Ph.D. Scholarship to CS.

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