Optimizing the impact of temperature on bio-hydrogen production from food waste and its derivatives under no pH control using statistical modelling

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Abstract. The effect of temperature on bio-hydrogen production by co-digestion of sewerage sludge with food waste and its two derivatives, i.e. noodle waste and rice waste, was investigated by statistical modelling. Experimental results showed that increasing temperature from mesophilic (37 °C) to thermophilic (55 °C) was an effective mean for increasing bio-hydrogen production from food waste and noodle waste, but it caused a negative impact on bio-hydrogen production from rice waste. The maximum cumulative bio-hydrogen production of 650 mL was obtained from noodle waste under thermophilic temperature condition. Most of the production was observed during the first 48 h of incubation, which continued until 72 h of incubation. The decline in pH during this interval was 4.3 and 4.4 from a starting value of 7 under mesophilic and thermophilic conditions, respectively. Most of the glucose consumption was also observed during 72 h of incubation and the maximum consumption was observed during the first 24 h, which was the same duration where the maximum pH drop occurred. The maximum hydrogen yields of 82.47 mL VS−1, 131.38 mL COD−1, and 44.90 mL glucose−1 were obtained from thermophilic food waste, thermophilic noodle waste and mesophilic rice waste, respectively. The production of volatile fatty acids increased with an increase in time and temperature in food waste and noodle waste reactors whereas they decreased with temperature in rice waste reactors. The statistical modelling returned good results with high values of coefficient of determination (R2) for each waste type and 3-D response surface plots developed by using models developed. These plots developed a better understanding regarding the impact of temperature and incubation time on bio-hydrogen production trend, glucose consumption during incubation and volatile fatty acids production.

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Biogeosciences, 12, 6503–6514, 2015
www.biogeosciences.net/12/6503/2015/
doi:10.5194/bg-12-6503-2015
© Author(s) 2015. CC Attribution 3.0 License.

# Optimizing the impact of temperature on bio-hydrogen production from food waste and its derivatives under no pH control using statistical modelling

C. Arslan 1,2,* , A. Sattar 1,* , C. Ji 1 , S. Sattar 3 , K. Yousaf 1 , and S. Hashim 4

1College of Engineering, Nanjing Agricultural University, Nanjing, China
2Department of Structures and Environmental Engineering, University of Agriculture, Faisalabad, Pakistan
3Environmental Sciences and Engineering, GC University Faisalabad, Pakistan
4Department of Hydrology and Water Resources, Hohai University, Nanjing, China
*These authors contributed equally to this work.

_Correspondence to:_ C. Ji (chyji@njau.edu.cn, arslanakrampk@hotmail.com)

Received: 6 July 2015 – Published in Biogeosciences Discuss.: 11 August 2015
Revised: 12 October 2015 – Accepted: 27 October 2015 – Published: 13 November 2015

Abstract. The effect of temperature on bio-hydrogen production by co-digestion of sewerage sludge with food waste
and its two derivatives, i.e. noodle waste and rice waste,
was investigated by statistical modelling. Experimental results showed that increasing temperature from mesophilic
(37 ◦ C) to thermophilic (55 ◦ C) was an effective mean for increasing bio-hydrogen production from food waste and noodle waste, but it caused a negative impact on bio-hydrogen
production from rice waste. The maximum cumulative biohydrogen production of 650 mL was obtained from noodle
waste under thermophilic temperature condition. Most of the
production was observed during the first 48 h of incubation,
which continued until 72 h of incubation. The decline in pH
during this interval was 4.3 and 4.4 from a starting value
of 7 under mesophilic and thermophilic conditions, respectively. Most of the glucose consumption was also observed
during 72 h of incubation and the maximum consumption
was observed during the first 24 h, which was the same duration where the maximum pH drop occurred. The maximum
hydrogen yields of 82.47 mL VS −1, 131.38 mL COD −1, and
44.90 mL glucose −1 were obtained from thermophilic food
waste, thermophilic noodle waste and mesophilic rice waste,
respectively. The production of volatile fatty acids increased
with an increase in time and temperature in food waste and
noodle waste reactors whereas they decreased with temperature in rice waste reactors. The statistical modelling returned
good results with high values of coefficient of determination

( _R_ 2 _)_ for each waste type and 3-D response surface plots developed by using models developed. These plots developed
a better understanding regarding the impact of temperature
and incubation time on bio-hydrogen production trend, glucose consumption during incubation and volatile fatty acids
production.

1 Introduction

Anaerobic digestion, as a waste management approach, has
been in practice for more than a century (McCarty, 1981). It
is widely used to treat a variety of solid wastes and wastewater on a small scale as well as on an industrial scale. It has
multiple advantages like 30–50 % reduction in waste volume as well as production of valuable byproducts such as
methane and hydrogen (Lin et al., 2011). A large amount of
organic fraction of municipal solid waste or food waste is
produced every year around the world. During 2010, production of food waste in China reached 352 Mt and the major
contributor was canteens and restaurants (Tai et al., 2011;
Wang et al., 2013). The food waste contains more than 80 %
volatile solids (VS) that are biodegradable solids and can be
converted into hydrogen or methane easily (Shin et al., 2004;
Zhang et al., 2007; Zhu et al., 2008). Several studies represent an increase in bio-hydrogen production from food waste
due to the addition of buffers and minerals. Although such

Published by Copernicus Publications on behalf of the European Geosciences Union

6504 C. Arslan et al.: Optimizing the impact of temperature on bio-hydrogen production

addition can maintain a specific pH and nutrimental required
for optimum bio-hydrogen production, but it also increases
the cost of production (Nielsen et al., 2001; Han, 2004).
The cost of production can be reduced by adding sewage
sludge as a source of _Clostridium_ mix culture (Fang et al.,
2006). Nutritional deficiency in food waste was also balanced by adding sewage sludge that made food waste more
suitable for bio-hydrogen production (Shin et al., 2004). It
means that integrated waste management can be done at a
wastewater treatment plant by co-digestion of sewage sludge
and food waste. Although sewerage sludge is a good source
of _Clostridium_ mix culture, it also contains hydrogen consumers like methanogens. Heat treatment is mostly opted to
deactivate hydrogen consumers. The traditional method of
placing sewage sludge in boiling water is now no longer
in practice and is replaced by microwave heating that provide more uniform heating as compared to the boiling water
method (Luo et al., 2010; Wang et al., 2011; Duangmanee et
al., 2007). The temperature and time for heat treatment varied from 75 to 121 ◦ C for 15 min to 2 h, but 100 ◦ C for 15 min
was mostly reported (Li and Fang, 2007; Fang et al., 2006).

Carbohydrate-rich wastes like food waste are suitable for
_Clostridium_ species as stoichiometrically it can produce two
moles of hydrogen from one mole of hexose (Payot, 1998).
Theoretically, 553 mL hydrogen can be produced by 1 g
of polysaccharides if it is totally converted into acetate.
The highest practical yield of 346 mL g −1 carbohydrate was
achieved by Fang et al. (2006) by using rice as a source of
carbohydrate (78 %), pre-treated sewage sludge as a source
of _Clostridium_ and adding a variety of nutrients. Rice waste
and noodle waste has 40 % share in the total food waste produced in China (Shiwei, 2005). The noodle waste is also rich
in carbohydrates, but still there is no research reported on
bio-hydrogen production from noodle waste.

Temperature and pH have a great impact on the smooth
running of AD (Saraphirom and Reungsang, 2010). Most
of the studies reported bio-hydrogen production under
mesophilic as well as thermophilic conditions and few were
reported under psychrophilic conditions. Lu et al. (2011)
developed microbial electrolysis cells (MECs) that could
be operated at 9 ◦ C by using _Geobacter_ _psychrophilus_ as
dominating population and achieved a hydrogen yield of
0.62 m 3 H2 m −3 d −1 . Heidrich et al. (2013) further modified
MECs to a pilot-scale MEC and achieved bio-hydrogen production of 0.015 LH2 L −1 d −1 at 25 ◦ C. On the other end, under mesophilic and thermophilic conditions, there is no need
for such sophisticated technology and a better bio-hydrogen
yield can be achieved by simple reactors or by lab scale batch
experiments. The temperature shift from mesophilic to thermophilic conditions can change the rate of hydrogen production during anaerobic digestion (Li and Liu, 2012; Saripan and Reungsang, 2014). Whereas hyper-thermophilic provide better pathogenic destruction but it also decreased the
bio-hydrogen production (Sahlström, 2003; Yokoyama et al.,
2007). Keeping the same temperature but changing the initial

pH from 7 to 8, the bio-hydrogen yield was changed from
64.48 to 55 mL VS −1 under no pH control conditions (Lin
et al., 2013b; Nathao et al., 2013). The same yield was increased to 70 mL VS −1 when pH was manually controlled
for food waste under thermophilic conditions, which represents the impact of pH management (Shin et al., 2004). The
hydrogen production by anaerobic digestion will be further
improved if pH lies in the range of 5 to 6 (Radjaram and Saravanane, 2011). The pH of food waste lies in the range of
4 to 5, which further decreases by the production of volatile
fatty acids (VFA) to such a level that can inhibit the bacterial growth. The pH can be controlled by automatic pH controllers, addition of nutrients and buffers, manual monitoring and control (Yasin et al., 2011; Zhu et al., 2008; Kim et
al., 2004). But all these methods increased the cost of operation. Along with cost, maintaining pH at specific point is not
suitable especially when mix culture is used as the response
of different microbial stream could be different to same pH
level. So, by co-digestion, the pH of the anaerobic digestion
process can be improved and it can be further adjusted to a
desired initial value by adding HCl or NaOH. After adjusting
the desired initial pH under co-digested conditions, the biohydrogen production can be achieved under no pH control
conditions, which can reduce the cost of operation (Fang et
al., 2006).

The yield of bio-hydrogen is calculated by dividing the
cumulative hydrogen produced by VS, chemical oxygen demand (COD) or glucose (Chen et al., 2006; Dong et al., 2009;
Fang et al., 2006). The yields are misleading if calculated in
terms of added or start up values of VS, COD and glucose
as it seems quite impossible that the whole of added material
is converted into hydrogen. In this regard the removal quantities of such parameters are the best option to calculate the
yield.

The optimization played an important role in bio-hydrogen
production and its application with respect to incubation time
in combination with temperature is an important factor to get
the maximum output with minimum intake of energy. In order to achieve this purpose, statistical modelling is an important tool to study the impact within the experimental range
and can be further used for the development of response surface plots (Jo et al., 2008).

This study was designed to investigate the impact of temperature on bio-hydrogen production from co-digestion of
sewerage sludge with food waste and its carbohydrate-rich
derivatives i.e. rice waste and noodle waste with the help
of statistical modelling. The response surface methodology
was employed to study the impact of time and temperature
on bio-hydrogen production, glucose consumption and VFA
production. The pH during incubation was not controlled and
the drop of pH during anaerobic digestion was also studied to
find an optimum pH range of bio-hydrogen production from
food waste derivatives.

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C. Arslan et al.: Optimizing the impact of temperature on bio-hydrogen production 6505

2 Material and methods

2.1 Batch experiment for bio-hydrogen production

The waste was collected from student dining at the Nanjing Agricultural University. The food left on the plates after
lunch/dinner consisted of rice, noodles, meat, bones, potato
and other vegetables. At first, bones and other foreign materials were removed and left over waste was treated as food
waste. The food waste was then ground in a meat grinder
with an equal amount of water and a resultant slurry was
used for bio-hydrogen production (Reungsang et al., 2013).
Rice and noodles were removed from collected waste and
converted into slurry in the same way opted for food waste.
The sludge was obtained from a settling channel and it was
washed with tap water and sieved to remove foreign materials (Nathao et al., 2013). The sludge was placed in a preheated oven at 100 ◦ C for 15 min, so that hydrogenotrophic
methanogens could be deactivated (Li and Fang, 2007).
Some important properties of feed stock and sewerage sludge
are enlisted in Table 1.

Two series of experiments were conducted in duplicate in
550 mL digesters with working volume of 400 mL (Hu et al.,
2014). In order to achieve 10 % initial TS concentration, water was added along with feedstock and sewerage sludge in
the digesters. The feedstock and sewerage sludge were added
in equal proportion. As the pH of food waste was not so
high even after co-digestion with sewage sludge, the initial
pH within reactor was less than 7 which was carefully raised
to 7 with the help of 3M NaOH solution (Zhu et al., 2008).
Series I was to observe the bio-hydrogen production under
mesophilic temperature (37 ◦ C) and series II was to investigate the impact of thermophilic temperature (55 ◦ C) on biohydrogen production potential of feed stock in comparison
with that produced under mesophilic conditions.

2.2 Chemical analysis

The volume of bio-hydrogen produced was measured by
displacement of 3 % NaOH solution. This concentration of
NaOH can remove other gases and water vapours (Fang et
al., 2006; Lin et al., 2013a; Saraphirom and Reungsang,
2010). Other parameters like TS, VS, COD, VFA and alkalinity were measured according to standard methods (APHA,
2005). For glucose detection, phenol sulphuric acid method
was used (Lay and Fan, 2003).

2.3 Assay methods

Modelling of hydrogen production was done by Modified
Gompertz equation (MGE), which was used for cumulative
bio-hydrogen measurement (Ramos et al., 2012)

where _H_, _t_, _P_, _R_ m, _λ_ and _e_ represent cumulative
bio-hydrogen production (mL), incubation time (h), biohydrogen production potential, maximum bio-hydrogen production rate (mL h −1 ), lag phase duration (h) and 2.71828
respectively. The values of _H_, _t_, _P_, _R_ m were solved by using
curve fitting tool in (ver. 2010a).

In this study, the effects of different types of food waste,
temperature and incubation time on bio-hydrogen and VFA
production as well as on glucose consumption, were analysed
by full quadratic model as shown below (Kim et al., 2008; Jo
et al., 2008)

- _n_

_Y_ = _a_ 0 +

- _n_

_i_ =1 _aiXi_ +

_n_

_i_ =1 _aiiX_ _i_ 2

_i_

- _n_

_i<j_ =2 _aij_ _XiXj_ _,_ (2)

- _n_

_i_ =1

where _Xi_ and _Xj_ are the controlled parameters, which influence _Y_ and _a_ 0, _aii_, _aij_, are the offset term, linear and
quadratic coefficients respectively. As the waste types are
different, so the above model is used, including waste type
( _n_ = 3) and excluding waste type ( _n_ = 2).

3 Results and discussion

3.1 Effect of temperature and time on bio-hydrogen
production

A comparison of actual and MGE modelled bio-hydrogen
production under mesophilic and thermophilic conditions is
shown in Fig. 1, which shows an early start of bio-hydrogen
production in food waste and noodle waste as compared to
rice waste. This early production was quantified with the help
of MGE as _λ_ shown in Table 2, which clearly shows that the
highest lag phase belongs to rice waste under both temperatures. The bio-hydrogen production in food waste continued
until 72 h of incubation and this time period for food waste
was higher than that observed for noodle waste, but still the
cumulative bio-hydrogen production of food waste was the
lowest as compared to the other two waste types. Looking
at the _R_ m values, it is clear that food waste has the lowest
mesophilic _R_ m value of 6.688 mL h −1 among all three wastes
that ultimately caused the cumulative bio-hydrogen production to decrease. Only the _R_ m value is not responsible for
higher yield as the highest mesophilic _R_ m of 21.05 mL h −1

belongs to noodle waste, but the cumulative bio-hydrogen
production of noodle waste was found to be smaller than
rice waste having _R_ m value of 16.52 mL h −1 . The rice waste
has a higher production because it produced bio-hydrogen
for 96 h as compared to noodle waste which produced until 60 h. In fact, mesophilic bio-hydrogen production in noodle waste decreased considerably after 24 h of incubation as
compared to thermophilic bio-hydrogen production where
the decrease was observed after 36 h of incubation. That is
12 h active duration increased the cumulative bio-hydrogen
production from noodle waste under thermophilic temperature even after observing the fact that the _R_ m values are very

- _R_ m _e_ ��
_(λ_ - _t)_ + 1 _,_ (1)
_P_

_H_ = Pexp

- exp

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6506 C. Arslan et al.: Optimizing the impact of temperature on bio-hydrogen production

Table 1. Properties of test materials.

Parameter Unit Sludge Food waste Rice waste Noodles waste

TS % 58.59 30.32 39.88 31.54
VS % 2.87 26.9 39.30 28.51
Glucose g L −1 2.49 65.77 79.65 63.73
COD g L −1 50 147.5 105 132
Total Alkalinity mg L −1 3700 550 500 450
VFA (mg L −1 ) mg L −1 13 950 2475 9000 1500
pH - 7.1 4.5 5.3 4.3

close to each other. It can be seen in Fig. 2 that the difference in active duration was due to pH as it was dropped from
7 to 4.6 in the noodle waste reactor during the first 12 h under mesophilic temperature and it was further dropped to 4.4
whereas a pH drop in thermophilic reactor was 5.3 to 4.9 in
the same duration. On the other end, pH drop in rice waste reactor under thermophilic conditions was higher as compared
to mesophilic temperature, which ultimately reduced the cumulative bio-hydrogen production that was found in agreement with the finding of Fang et al. (2006). The reduction in
bio-hydrogen production with low pH is due to homoacetogenic bacteria, which are more active at low pH (Ramos et
al., 2012; Schiel-Bengelsdorf and Dürre, 2012). The trend
for pH drop with temperature in food waste reactors was
opposite to other reactors and _R_ m increased to a value of
26.42 mL h −1 when temperature was shifted from mesophilic
to thermophilic. This increase is due to _Thermoanaerobac-_
_terium_ _thermosaccharolyticum_ that grow at higher temperature in food waste and produce more hydrogen (Shin et al.,
2004). As a whole, _R_ m values found in the present study were
higher than those reported in previous studies (Fang et al.,
2006; Ramos et al., 2012).
The volume of bio-hydrogen production with time was
used to fit in a quadratic model by using solver function MS
Excel and the resultant equation obtained was

700

600

500

400

300

200

100

FW, 37°C RW, 37°C NW, 37°C
FW, 37°C, M RW, 37°C, M NW, 37°C, M

0 12 24 36 48 60 72 84 96 108 120

Time (h)

700

600

500

400

300

200

100

FW, 55°C RW, 55°C NW, 55°C
FW, 55°C, M RW, 55°C, M NW, 55°C, M

_Y_ = 202 _._ 83 + 56 _._ 86 _x_ 1 + 73 _._ 38 _x_ 2 + 8 _._ 5 _x_ 3 − 22 _._ 5 _x_ 1 2

+ 243 _._ 25 _x_ 2 2 − 113 _._ 8 _x_ 3 2 − 23 _._ 75 _x_ 1 _x_ 2 − 1 _._ 86 _x_ 1 _x_ 3

- 30 _._ 38 _a_ 9 _x_ 2 _x_ 3 _(R_ 2 = 0 _._ 5576 _,F_ = 19 _._ 921 _),_ (3)

where _Y_ is the predicted bio-hydrogen production; _x_ 1, _x_ 2
and _x_ 3 are the coded values of incubation time, waste type
and temperature respectively. There is a poor relationship between actual and predicted value as the coefficient of determination ( _R_ 2 _)_ was calculated to be 0.5576, which can explain only 55.76 % variability of the response. The diversity
among waste type is the main reason for such a low value
and this value could be at a higher level if the same waste
was used in different proportions as reported in other studies
(Kim et al., 2008; Jo et al., 2008). To overcome this problem,
quadratic model was again developed for each waste type and
the following equations were obtained:

0 12 24 36 48 60 72 84 96 108 120

Time (h)

Figure 1. Mesophilic and thermophilic bio-hydrogen production
with time.

Food waste: _Y_ = 281 _._ 75 + 57 _._ 25 _x_ 1 + 62 _._ 25 _x_ 2

- 22 _x_ 1 2 − 25 _._ 25 _x_ 1 _x_ 2 _(R_ 2 = 0 _._ 9858 _F_ = 278 _._ 06 _)_ (4a)

Noodle waste: _Y_ = 472 _._ 5 + 97 _._ 5 _x_ 1 + 42 _._ 5 _x_ 2

- 25 _x_ 1 2 + 62 _._ 5 _x_ 1 _x_ 2 _(R_ 2 = 0 _._ 9011 _F_ = 36 _._ 44 _)_ (4b)

Rice waste : _Y_ = 167 _._ 5 + 71 _._ 5 _x_ 1 − 49 _._ 5 _x_ 2

- 43 _x_ 1 2 − 16 _._ 5 _x_ 1 _x_ 2 _(R_ 2 = 0 _._ 7922 _F_ = 15 _._ 26 _),_ (4c)

where _x_ 1 and _x_ 2 are the coded values of time and temperature. All _F_ values represented that the regression model obtained are statistically significant. The _F_ value of food waste

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C. Arslan et al.: Optimizing the impact of temperature on bio-hydrogen production 6507

Table 2. Kinetic parameters and bio-hydrogen yield.

Hydrogen yield

Waste Temperature _P_ _R_ m _λ_ _R_ 2 mL g −1 VS mL g −1 VS mL g −1 COD mL g −1 glucose
Type (mL) (mL h −1 ) (h) Fed Removed Removed Removed

FW 37 ◦ C 283.7 6.688 6.949 0.9971 17.59 80.11 47.28 18.02
55 ◦ C 350.1 26.42 11.39 0.9965 21.57 82.47 67.33 25.63
RW 37 ◦ C 614.3 16.52 31.29 0.9819 32.76 56.36 66.77 44.90
55 ◦ C 130.2 6.325 21.1 0.9997 6.94 29.66 26.04 8.68
NW 37 ◦ C 437.9 21.05 3.047 0.9987 15.26 23.40 109.48 27.65
55 ◦ C 656.9 20.41 5.935 0.9955 22.89 38.15 131.38 40.33

Table 3. Comparison of bio-hydrogen yield.

Feed Inoculum Yield Initial Optimum pH Temperature References
stock pH pH Management ( ◦ C)

Food waste Sludge 64.48 mL H2/VSfed 7 4.8–6.4 Not controlled 37 Lin et al. (2013b)
Food waste Sludge 250 ml H2/VSremoved 6.5 6.5–5.2 Not controlled 26 Tawfik et al. (2011)
Food waste Kitchen 148 ± 42 mL H2/CODremoved 5 ± 03 5 ± 0.3 Manually Controlled 40 Tawfik and El-Qelish (2014)
wastewater
Food waste Sludge 70 mL H2/VS 5.5 5.5 Manually Controlled 55 Shin et al. (2004)
Rice waste Sludge 71 mL H2/VS 7 7 Not controlled 37 Okamoto et al. (2000)
Rice waste Sludge 134 mL H2/VS 5.5 5.5 Manually Controlled 37 Dong et al. (2009)
Food waste Sludge 55 mL H2/VS 7 6 Not controlled 55 Nathao et al. (2013)
Rice waste Sludge 346 mL H2 g −1 carbohydrates 4.5 4.5 Manually Controlled 37 Fang et al. (2006)
Noodle Industry Anaerobic 1.47 mol H2 mol −1 hexose 4.5–8.5 5.2 Controlled 35 Mizuno (2000)
wastewater microflora
Food waste Sludge 44.83 mL H2 g −1 COD 8 8–4.5 Not Controlled 55 Wongthanate and
Chinnacotpong (2015)
OFMSW Sludge 205 ml H2 g −1 VS added 5.5 5.5 Automatic pH controller 55 Chu et al. (2008)
Food waste Sludge 82.47 mL g −1 VSremoved 7 7–4.4 Not Controlled 55 This study
Noodle waste Sludge 131.38 mL g −1 CODremoved 7 7–4.4 Not Controlled 55 This study
Rice waste Sludge 44.90 mL g −1 glucoseremoved 7 7–4.3 Not Controlled 37 This study

7.5

6.5

5.5

4.5

3.5

FW, 37°C RW, 37°C NW, 37°C
FW, 55°C RW, 55°C NW, 55°C

0 12 24 36 48 60 72 84 96 108 120

Time (h)

production as a response by using the above-mentioned equations. The 3-D and 2-D curves of the calculated response
showed the interaction of incubation time and temperature
in Fig. 3a–c. For food waste, it is clear that the gas production increases with time and temperature from 115 mL at the
starting end to 354 mL at the extreme modelled conditions.
Between 0 and 24 h of incubation, bio-hydrogen production
increased with an increase in temperature for food waste,
i.e. 115 mL of bio-hydrogen was produced at 37 ◦ C that increased to 76.09 and 152.17 % at 46 and 55 ◦ C, respectively.
During the next 24 h of incubation, bio-hydrogen production
reduced with the increase in temperature, i.e. 114.5 mL biohydrogen was produced at 37 ◦ C and 30.78 and 91.22 % reduction was observed at 46 ◦ C and 55 ◦ C, respectively. Even
after reduction in bio-hydrogen production between 24 and
48 h of incubation, the cumulative bio-hydrogen production
increased with an increase in temperature from food waste.
The impact of temperature and time can be better viewed in
2-D contour (Fig. 3a), which shows that the increase in temperature increases bio-hydrogen production more at 24 h as
compared to 72 h of incubation. It also revealed the fact that
the first 24 h are important for bio-hydrogen production from
food waste under thermophilic temperatures and the next 24

Figure 2. Effect of temperature on pH drop during incubation.

is much higher as compared to other values; this is because of
the coefficient of determination that explained 98.58 % variability. The quadratic model obtained from rice waste was
not perfectly fit, but it can better explain results as compared
to the model developed for all waste types as a whole.

The three-dimensional (3-D) response surfaces and twodimensional (2-D) contours were developed within the experimental range for each waste type by taking bio-hydrogen

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6508 C. Arslan et al.: Optimizing the impact of temperature on bio-hydrogen production

are important for production under mesophilic temperature,
which is in agreement with findings of Shin et al. (2004).
Although noodle waste also produced more bio-hydrogen at
elevated temperature, the time effect was opposite to that observed for food waste. The bio-hydrogen production in noodle waste during 0–24 h was 350 mL at 37 ◦ C that was 5.4 and
10.81 % decreased at 46 and 55 ◦ C, respectively. But in the
next 24–72 h, there was an increase of 178.57 and 357.14 %
at 46 and 55 ◦ C, respectively .

As far as rice waste was concerned, temperature has a negative impact on bio-hydrogen production. Between 24 to 48
h, the bio-hydrogen production in rice waste was 131 mL at
37 ◦ C, 114.5 mL at 46 ◦ C and 98 mL at 55 ◦ C. In next 24h, the
bio-hydrogen production was reduced to 65.65 %, 75.11 %
and 87.76 % at 37 ◦ C, 46 ◦ C and 55 ◦ C, respectively. The
reduction in bio-hydrogen production for rice waste was in
agreement with previous findings (Fang et al., 2006). The 2D contours in Fig. 3b and c differentiate the impact of temperature with time on bio-hydrogen production for noodle
waste and rice waste as the contour patterns are quite opposite to each other.

3.2 Effect of temperature on bio-hydrogen yield

The bio-hydrogen yield was calculated by dividing the _P_
value on Table 2 with VSfed, VSremoved, CODremoved and
glucoseremoved. The bio-hydrogen yield calculated on the basis of VSfed lay in the range achieved by Lin et al. (2013b)
and temperature impact on yield was the same as observed
for _P_ . The yield on the basis of VSconsumed represented uptake efficiency of VS during anaerobic digestion. The increase in _P_ with temperature for food waste was 23.41 %
whereas the yield increased by 2.86 % only that indicated
the efficient removal of VS at higher temperature. The biohydrogen yield calculated for FW on the basis of VSremoved
lay in the range used by Kim et al. (2004). Using the same
scale of VSremoved, bio-hydrogen yield for rice waste decreased 47.37 % with an increase in temperature, whereas the
decrease in _P_ was 78.81 % that represented a decrease in removal of VS at elevated temperature which was in agreement
with the findings of Fang et al. (2006). As compared to food
waste and noodle waste, the increase in _P_ and yield calculated by VSremoved was close, but it revealed the fact that VS
removal efficiency slightly decreased at an elevated temperature.

When the yield measuring scale was shifted from
VSremoved to CODremoved, the results represented quite a different picture of temperature impact. The increase in temperature from 37 to 55 ◦ C increased 42.41 % bio-hydrogen yield
calculated on the basis of CODremoved for food waste. The
increase in bio-hydrogen production due to same increase in
temperature from 37 to 55 ◦ C was 23.37 %. Such a difference
in yield and production increment represented a decrease in
COD removal efficiency at an elevated temperature for food
waste. For rice waste, the decrease in yield was 61 %, which

Figure 3. Three-dimensional response plots for bio-hydrogen production (a) Food waste, (b) Noodle waste, (c) Rice waste.

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C. Arslan et al.: Optimizing the impact of temperature on bio-hydrogen production 6509

FW, 37°C RW, 37°C NW, 37°C
FW, 55°C RW, 55°C NW, 55°C

ously defined notation as

0 24 48 72 96 120

Time (h)

Figure 4. Glucose consumption during incubation under mesophilic
and thermophilic temperature.

was close to a 78 % decrease in _P_ . Increasing temperature
also increased the yield for noodle waste to 20 %, which was
smaller than the increase in _P_, representing a higher rate of
COD removal at elevated temperature. All the bio-hydrogen
yields calculated on the basis of CODremoved lay in the range
calculated by Tawfik and El-Qelish (2014).

Glucose removal efficiency for food waste decreased with
an increase in temperature as the increase in _P_ was 23.41
against 42.19 % when bio-hydrogen yield was calculated on
the basis of glucoseremoved. Whereas the change in yield for
noodle waste and rice waste was close to the change observed
for _P_ . The decrease in glucose concentration was close to
that observed in previous studies (Abdeshahian et al., 2014;
Kapdan and Kargi, 2006). The yield calculated on a glucose basis was further studied on a daily basis and it was
observed that the highest yield of 33 mL glucoseremoved −1 for

0–24 h duration belonged to noodle waste under mesophilic
condition. During the next 24 h period, the highest yield of
400 mL glucose − removed 1 was achieved by noodle waste un-
der thermophilic temperature, which was close to the finding of Fang et al. (2006) but still smaller than the theoretical yield of 553 mL g −1 carbohydrate. The yield for rice
waste also increased under both temperatures but it was much
higher at mesophilic as 184.37 mL glucose − removed 1 against

24.99 mL glucose − removed 1 at thermophilic temperature. During
24 to 72 h of incubation, the yield in all reactors reduced except noodle waste under mesophilic conditions. As a whole,
24–48 h duration of incubation was found to be more important for bio-hydrogen production from glucose. The production of glucose modelled by quadratic equation using previ

_Y_ = 13 _._ 504 − 0 _._ 604 _x_ 1 + 0 _._ 095 _x_ 2 − 0 _._ 831 _x_ 3 + 0 _._ 066 _x_ 1 2

- 5 _._ 469 _x_ 2 2 + 0 _._ 609 _x_ 1 _x_ 2 + 0 _._ 238 _x_ 1 _x_ 3 − 1 _._ 131 _x_ 2 _x_ 3

_(R_ 2 = 0 _._ 6959 _F_ = 64 _._ 07 _)._ (5)

As the coefficient of determination is not so high so quadratic
modelling was done for each waste type as

Food waste : _Y_ = 7 _._ 820 − 3 _._ 561 _x_ 1 + 0 _._ 412 _x_ 2

+ 1 _._ 554 _x_ 1 2 + 1 _._ 094 _x_ 1 _x_ 2 _(R_ 2 = 0 _._ 9713 _F_ = 270 _._ 81 _)_ (6a)

Noodle waste : _Y_ = 8 _._ 697 − 1 _._ 601 _x_ 1 + 0 _._ 055 _x_ 2

+ 0 _._ 439 _x_ 1 2 − 0 _._ 307 _x_ 1 _x_ 2 _(R_ 2 = 0 _._ 7994 _F_ = 31 _._ 89 _)_ (6b)

Rice Waste : _Y_ = 21 _._ 817 − 3 _._ 1 _x_ 1 − 0 _._ 938 _x_ 2

- 0 _._ 323 _x_ 1 2 − 0 _._ 354 _x_ 1 _x_ 2 _(R_ 2 = 0 _._ 715 _F_ = 20 _._ 07 _)._ (6c)

The 3-D response plots and contours for glucose removal
were developed by the above models (Fig. 5). It was observed that in the first 24 h of incubation, the rate of utilization of glucose increased, with an increase in temperature up
to 55 ◦ C for food waste, decreased for noodle waste, and remained almost unaffected for rice waste. The sequence for
glucose utilization rate was in the rank of NW > FW > RW.
Between 24 and 48 h, glucose utilization rate decreased for
food waste and increased for noodle and rice waste under
mesophilic and thermophilic conditions. Between 48 and
72 h, rate of utilization remained the same as previous one
but rank was slightly changed as FW > RW > NW. With an
increase in temperature, between 24 and 72 h, the rate of glucose utilization decreased for food waste but increased for
noodle and rice waste. As a whole, the glucose consumption
at the end of incubation was higher at 37 ◦ C as compared to
55 ◦ C for food waste. At the end of incubation, noodle waste
and rice waste represented quite opposite picture of glucose
consumption with temperature as observed for food waste.
The contours represented a better understanding for glucose
consumption and the contour varied in different manners for
each waste type as shown in Fig. 5.

3.3 Effect of temperature on VFA production

The VFA revealed an increase with time as reported by
Lin et al. (2013b), which is shown in Fig. 6. In the present
study, it is observed that VFA in food waste and noodle
waste increased with an increase in temperature from 37
to 55 ◦ C but decreased for rice waste that lay in the range
calculated by Shin et al. (2004). It can be seen in Fig. 6
that between 24 and 48 h, an increase in VFA was much
higher in food waste under thermophilic conditions as compared to mesophilic conditions. During the same interval,
bio-hydrogen production almost ceased in the thermophilic
food waste reactor whereas it was continuously producing in
mesophilic food waste reactor. One of the possible reasons
for this reduction is the conversion of glucose to VFA at

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6510 C. Arslan et al.: Optimizing the impact of temperature on bio-hydrogen production

9000

8000

7000

6000

5000

4000

3000

2000

1000

FW, 37°C RW, 37°C NW, 37°C
FW, 55°C RW, 55°C NW, 55°C

Figure 5. Three-dimensional response plots for glucose consumption (a) Food waste, (b) Noodle waste, (c) Rice waste.

0 24 48 72 96 120

Time (h)

Figure 6. Increase in VFA concentration with time under
mesophilic and thermophilic temperatures.

this stage by homoacetogenic bacteria that reached up to
such a level where bio-hydrogen production was not feasible
under thermophilic conditions, whereas the VFA production
in the mesophilic FW reactor was much smaller than that
observed under thermophilic reactor, because of which
production continued in the mesophilic reactor (Zhang
et al., 2014). The higher concentration of VFA together
with low pH can be inhibitory to bacteria that can cause
unfavourable physical changes in the cell. By such physical
changes, excessive energy is required to pump ions and
that energy can be available at a higher temperature. So it
increased the yield at elevated temperatures, as observed
in the case of food waste and noodle waste (Gottschalk,
1986; Zoetemeyer, 1982; Switzenbaum, 1990). The higher
concentration of VFA can also be used as an indicator for
higher production of bio-hydrogen as observed by Dong et
al. (2009). In the present study, the order to VFA production
and cumulative bio-hydrogen production was the same i.e.
NW55 ◦ C > RW37 ◦ C > NW37 ◦ C > FW55 ◦ C > FW37 ◦ C > RW37 ◦ C.

The quadratic model was tried to fit for VFA production
data in the same way as opted for glucose and the resultant
equation was as follows:

_Y_ = 1795 _._ 82 + 686 _._ 16 _x_ 1 − 300 _._ 51 _x_ 2 + 641 _._ 13 _x_ 3

+ 4 _._ 94 _x_ 1 2 + 658 _._ 51 _x_ 2 2 + 127 _._ 30 _x_ 1 _x_ 2 + 33 _._ 26 _x_ 1 _x_ 3

- 319 _._ 25 _x_ 2 _x_ 3 _(R_ 2 = 0 _._ 5975 _F_ = 41 _._ 56 _)._ (7)

Here, again the coefficient of determination is not so high
due to the variability of waste type, so the model was repeated for each waste as

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C. Arslan et al.: Optimizing the impact of temperature on bio-hydrogen production 6511

Food waste : _Y_ = 2362 _._ 67 + 458 _._ 15 _x_ 1 + 545 _._ 05 _x_ 2

- 12 _._ 88 _x_ 1 2 + 2 _._ 76 _x_ 2 2 − 22 _._ 42 _x_ 1 _x_ 2

_(R_ 2 = 0 _._ 8654 _F_ = 51 _._ 44 _)_ (8a)

Noodle waste : _Y_ = 4196 _._ 48 + 1464 _._ 56 _x_ 1

+ 772 _._ 876 _x_ 2 − 163 _._ 19 _x_ 1 2 + 224 _._ 98 _x_ 1 _x_ 2

_(R_ 2 = 0 _._ 8415 _F_ = 42 _._ 48 _)_ (8b)

Rice waste : _Y_ = 3258 _._ 94 + 756 _._ 62 _x_ 1 − 1147 _._ 22 _x_ 2

- 303 _._ 1 _x_ 1 2 − 390 _._ 28 _x_ 1 _x_ 2

_(R_ 2 = 0 _._ 9430 _F_ = 132 _._ 37 _)._ (8c)

The 3-D response plots and contours for VFA production on
the basis of the above models are shown in Fig. 7. The 3D contours for food waste and noodle waste seem almost
same but the contour lines for both varied in a different manner. Although the production of VFA increased with time
and temperature in all reactors but the intensity of change
is different for each waste type as observed in Fig. 7. It can
be observed from Fig. 7 that the production of VFA has increased for food waste and noodle waste when temperature
was increased from 37 to 55 ◦ C. Although with time, the
VFA concentration increased, but the rate by which VFAs
produced was decreased with time, i.e. VFA production between 24 and 48 h was greater than that produced between
48 and 72 h and this trend continued until 120 h for food
waste and noodle waste. As a whole, more VFA was produced between 24 and 120 h under mesophilic temperature
as compared to thermophilic temperature in food waste reactor, but as a whole, mesophilic VFA production was found
to be less than that of thermophilic as reported by Gadow et
al. (2012). It is because of the fact that between 0 and 24 h duration, thermophilic VFA production was much higher than
that produced under mesophilic conditions in food waste.
By controlling the VFA production during this interval, the
yield of bio-hydrogen can be increased for FW as it stopped
too early in thermophilic food waste reactor as compared to
mesophilic food waste reactor. Thermophilic VFA production was higher than mesophilic VFA production in noodle
waste reactor. On the other end, mesophilic VFA production
was higher than that produced under thermophilic conditions
for RW and VFA increased with time in the same manner as
observed for food waste under 40 ◦ C. Between 40 and 55, ◦ C,
the VFA trend for rice waste remained the same as of food
waste until 96 h after which it started to decrease until 120 h.

4 Conclusion

Food waste and its two major derivatives, i.e. noodle waste
and rice waste, were co-digested with sewerage sludge
to produce bio-hydrogen with an initial pH of 7 under
mesophilic and thermophilic conditions. The pH was not

Figure 7. Three-dimensional response plots for VFA production (a)
Food waste, (b) Noodle waste, (c) Rice waste.

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6512 C. Arslan et al.: Optimizing the impact of temperature on bio-hydrogen production

controlled throughout the incubation. The most effective VS
removal was observed in noodle waste reactor that produced the highest experimental cumulative bio-hydrogen of
656.5 mL under thermophilic conditions. The food waste
possessed the highest bio-hydrogen yield calculated on the
basis of VSremoved that represents an efficient conversion of
VS into bio-hydrogen. The increase in temperature within
the studied range increased the bio-hydrogen production in
food waste and noodle waste reactors. The rice waste reactor represented the negative impact of increasing temperature on bio-hydrogen and VFA production. Thermophilic
conditions should be preferred for bio-hydrogen production
as most of the time food waste is used as feed stock. The
quadratic modelling returned good results that were close
to experimental ones, when it was done for each waste type
of bio-hydrogen, VFA production and glucose removal. The
response surface plots and contour plots within the experimental range adequately explained the effect of temperature
and time on studying parameters and helped to develop better
understanding regarding the variation among the studied parameters especially when the different treatments represented
similar trends. VFA production in rice waste reactor changes
the trend after 40 ◦ C that was identified only due to quadratic
modelling. The lowest limit of pH for bio-hydrogen production was identified as 4.3 and 4.4 for mesophilic and thermophilic temperatures respectively.

_Author contributions._ C. Arslan and A. Sattar, designed the research and performed all the lab works. C. Ji provided the financial
and technical support for designing and conducting research as well
as supervised the whole research process. S. Sattar developed and
customized 3-D surface plots and assisted in manuscript preparation. K. Yousaf assisted the lab works and analysis. S. Hashim performed the statistical analysis. C. Arslan wrote the manuscript with
comments from all authors and A. Sattar finalized the manuscript
under the supervision and guidelines of C. Ji.

_Acknowledgements._ We thank K. Chen for providing lab facilities;
H. Fang, Y. P. Huang and J. B. Kang for their help during lab work;
I. A. Mari for field work and technical assistance; F. A. Chandio
and F. Ahmad for helpful discussion and critical review. We extend
our thank to Higher Education Commission, Pakistan, China
Scholarship council and the College of Engineering, Nanjing
Agricultural University, Nanjing for supporting and providing
research facilities for this study.

Edited by: T. Treude

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