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Efficacies of inocula on the startup of anaerobic reactors
treating dairy manure under stirred and unstirred conditions
Pramod K. Pandey a,*, Pius M. Ndegwa b, Michelle L. Soupir a, J. Richard Alldredge c,
Marvin J. Pitts d
a
Department of Agricultural & Biosystems Engineering, Iowa State University, Ames, IA, 50011, USA
Department of Biological Systems Engineering, Washington State University, Pullman WA, 99164 -6120, USA
c
Department Statistics,Washington State University, Pullman, WA 99164-3144, USA
d
School of Mechanical and Materials Engineering, Washington State University, Pullman, WA 99164-2920, USA
b
article info
abstract
Article history:
Inocula play an important role in anaerobic reactor startup by balancing the populations of
Received 24 December 2009
Syntrophobacter and methanogens. Such balances make syntrophic metabolism thermody-
Received in revised form
namically feasible in anaerobic digestion. In this study, the effect of inocula on the perfor-
19 February 2011
mance of dairy manure digestion was investigated by analyzing the change in volatile fatty
Accepted 4 March 2011
acids (VFA), total solids (TS), volatile solids (VS), specific biogas production (SGPR), and
Available online 6 May 2011
specific methane production (SPMP) as well as scanning and transmission electron micrographs. The study was performed at four treatments. Treatment one was granular sludge
Keywords:
(GM); treatment two was non-granular sludge (SM); treatment three was mixed culture from
Inocula
an anaerobic lagoon (LM); while the fourth treatment (the control denoted MM) did not
Anaerobic digestion
receive any exogenous inocula. In addition, stirred and unstirred conditions were main-
Dairy manure
tained in the reactors to determine their effect on reactor startup. Performance ranking
Mixing
based on the SGPR and SPMP of treatments (in descending order) was: GM, SM, LM and MM
Syntrophobacter
under stirred conditions. Under unstirred conditions, performance ranking (also in
Methanogens
descending order) was: SM, GM, LM, and MM. Results of the examination of microcolonies in
the granular, non-granular sludge, and dairy manure suggest that syntrophic juxtaposition
of methanogens and Syntrophobacter in granular inoculum was common while it was less
visible in non-granular sludge, and completely absent in dairy manure.
Published by Elsevier Ltd.
1.
Introduction
The United States is the largest energy consumer in the world
[1] and obtains most of its energy from non-renewable fossil
fuels. In principle, the country could significantly reduce
consumption of non-renewable energy by using “waste
products” such as dairy manure as a source of energy. Dairy
manure is a renewable energy source in many less-developed
countries, where economic conditions limit the availability of
fossil fuel. This utilization of animal waste as an energy
* Corresponding author. Tel.: þ1 515 894 2210; fax: þ1 515 894 4250.
E-mail address: [email protected] (P.K. Pandey).
0961-9534/$ e see front matter Published by Elsevier Ltd.
doi:10.1016/j.biombioe.2011.03.017
source has been realized via anaerobic digestion that converts
animal waste into biogas, which is subsequently used as fuel
for heating and cooking. Besides generating biogas for energy
use, the anaerobic process also reduces pathogens and
produces stabilized slurry to be used as fertilizer in land
applications [2]. In the U.S., dairy cattle generate an estimated
2 1012 kg of solid waste annually [3] and could provide
a significant source of renewable energy in the form of
methane. If this volume of dairy waste can be used for biogas
production, it has a potential to generate around 8 1010 m3 of
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Nomenclature
GM
SM
LM
MM
F/M
a
VFA
TS
VS
SEM
treatment in which manure and granule was
mixed
treatment in which manure and non e granular
sludge was mixed
treatment in which manure and anaerobic lagoon
culture was mixed
treatment which did not receive any exogenous
inoculum
food to microorganisms ratio
ratio between VFA and bicarbonate alkalinity
volatile fatty acids
total solids
volatile solids
scanning electron micrographs
biogas annually (annual solid waste: 2 1012 kg; biogas yield:
0.040 m3/kg) with an energy value of 1.6 1012 MJ (caloric
value of biogas: 20 MJ/m3) [4]. Given that one person in the U.S.
uses about 361303 MJ primary energy [1] annually, biogas
produced from dairy waste can thus fulfill the annual energy
need of 4.42 million people. However, so far manure is largely
underutilized as a fuel source because of the problem and
complexity involved in the anaerobic digestion process
required for gas production.
Anaerobic digestion is a conversion of biodegradable
material that involves hydrolysis, acidogenesis, acetogenesis,
and methanogenesis processes. Hydrolysis/acidogenesis
process involves the conversion of biodegradable material into
volatile fatty acids (VFA) such as acetate, butyrate and propionate [5]. During the acetogenesis process, VFA is converted
into acetate, hydrogen, and carbon dioxide. Methanogenesis
process involves the conversion of acetate into methane and
carbon dioxide. Table 1 shows the syntrophic and methanogens population of granule, manure and sludge. Compared
to granule and sludge samples, manure samples constitute
a higher number of syntrophic bacteria such as propionate and
butyrate degraders. The aceticlastic methanogens are reported
to be higher in sludge samples than granule and manure
samples, and hydrogenotrophic methanogens are reported to
TEM
SPMP
SGPR
TAN
VSfeed
VSinocula
COD
Msae
Mbac
Dsv
Dsb
Msar
Msp
Synw
transmission electron microscope
specific methane production
specific gas production rate
total ammonia nitrogen
volatile solids in feed (manure)
volatile solids in inocula
chemical oxygen demand
Methanosaeta spp.
Methanobacterium spp.
Dsulfovibrio spp.
Desulfobulbus spp.
Methanosarcina spp.
Methanospirillum spp.
Syntrophobacter wolinii
be less in sludge samples than granule and manure samples.
While, acetogenesis and methanogenesis can be considered as
the major rate-limiting steps during anaerobic digestion of
complex waste (cattle manure), the VFA produced by hydrolysis/acidogenesis can depress the acetogenesis and methanogenesis [5,6]. To balance the VFA production and
consumption, a balance population of these two groups of
microorganisms (acetogens and methanogens) is required. If
hydrogenotrophic methanogens fail to consume the H2
produced during acetogenesis, accumulation of H2 concentrations occurs, which results in increased H2 partial pressure.
The increased H2 partial pressure limits the anaerobic
biodegradation of VFA [2,7,8,9,10]. To start gas production in
reactors (reactor startup), a balanced population ratio of acetogens and methanogens is required. The requirements of
a balanced population and the slow growth rate of methanogens are the major problems in reactor startup. The initial
1e3 weeks are considered as the reactor startup period, in
which biomass acclimatizes and grows in a new environment
[11,12,13]. The slow growth rate of methanogens extends the
time required for establishing a dynamic equilibrium between
acetogens and methanogens, which results in an accumulation of intermediate degradation products (VFAs and dissolved
H2) [14]. Excess VFAs inhibit the growth rate of methanogens by
Table 1 e Microbial community population in inocula.
Bacterial groups
Syntrophic (A)
*Propionate degraders
Butyrate degraders
Methanogens (B)
**Aceticlastic methanogens
Hydrogenotrophic methanogens
Granulara
MPN/mL granules
Manure %
SSU rRNA
Sludge %
SSU rRNA
Granule % of
(A þ B)
Manure % of
(A þ B)
Sludge % of
(A þ B)
3 108
1 108
1.03b
0.49b
1.04b
0.42b
4.68
1.52
37.73
17.95
9.25
3.74
3 109
3 109
0.21c
1.0c
9.59c
0.19c
46.88
46.88
7.69
36.63
85.32
1.69
*Sum of Syntrophobacter fumaroxidans, Syntrophobacter pfennigii and Syntrophobacter wolinii.
**Sum of Methanosarcina spp. and Methanosaetaceae
a Granule grown on starch industry waste water in mesophilic conditions. Maximum Possible Numbers (MPN) was used due to unavailability of
16S rRNA probes data on granule sludge [51,10].
b Microbial analysis of inoculum, expressed as percentage of specific SSU rRNA of total SSU rRNA (% SSU rRNA) [26].
c Methanogenic population levels in inocula, expressed as percentage of specific SSU rRNA of total SSU rRNA (% SSU rRNA) [8].
2707
b i o m a s s a n d b i o e n e r g y 3 5 ( 2 0 1 1 ) 2 7 0 5 e2 7 2 0
lowering pH [15], which results in delayed startup or failure of
the digester. Therefore, during the startup, the microbial
community should contain sufficient levels of methanogens to
avoid these problems. Poor startup in anaerobic treatment
systems can lead to prolonged period of acclimation [16] and
ineffective removal of organic matter [8]. Several studies
reported that successful startup was related to a number of
factors e.g., seed sludge source, initial loading rate, hydraulic
retention time (HRT) or solids retention time (SRT) [8]. Extensive research has been done on the effect of initial loading rate,
HRT, and SRT on anaerobic digestion. However, relatively little
research has been reported on the effect of different inocula on
startup of anaerobic digester treating dairy manure.
The duration of startup phase depends on the type of
inocula and feed materials. Several studies emphasize the
importance of inocula in anaerobic digestion [17,18]. The use
of anaerobic digester’s sludge treating municipal waste water
as an inocula is found to be suitable for the startup of the
mesophilic anaerobic digester [19,8]. The use of granular
sludge as inocula has been found to be suitable for treating
pharmaceutical waste water [20]. However, the use of granular
sludge in dairy manure treatment has not been reported.
Despite a number of available studies suggesting the use of
inocula for startup of the reactors [21], an exact specification
or a study which mainly focused on selection of inocula for
anaerobic digestion of treating dairy manure is lacking. The
objective of this study was to investigate reactor startup using
different inocula as well the effect of stirring during startup
phase.
2.
Materials and methods
2.1.
Dairy manure (feed stock) characteristics
Raw dairy manure (pH 6e7) was collected from the Knott Dairy
Centre at Washington State University in Pullman, WA and
then stored at 20 C. Just before the treatments preparation,
the samples were transferred from 20 C to 4 C. The feed
was prepared by diluting the raw manure with water to
desired feed concentrations (TS 2.5%, g/g). The feed was then
sieved with a mesh of 850 mm (USA standard test sieve, No 20,
S/N 04106855, Fisher Scientific Company) to remove large
debris and fiber in order to minimize blockage of the lab-scale
reactors. The characteristics of dairy manure used in this
study are presented in Table 2. Determinations of chemical
oxygen demand (COD), TS, VS, and TAN were performed
according to Standard Methods [22].
2.2.
Inocula
Three types of inocula were compared in this study. One;
granular seeds, which were collected from a UASB reactor
treating potato starch waste at Penford Food Ingredients Co,
Richland, WA. Prior to being fed to the UASB reactor, the
stream of potato starch waste was taken through a settling
tank to allow solid particles to settle. Subsequently, liquid
portion with a BOD of 4000 mg/L was fed to UASB reactors at
a rate of 220 gallon/day. The UASB reactor with 4 h of
hydraulic retention time produced about 1 million cubic feet
of biogas per month and disposed the effluent with BOD of
100 mg/L. Two: Non-granular sludge of anaerobic digester,
which was collected from the Pullman Sewage Treatment
Plant, Pullman, WA. This treatment plant serves a population
of approximately 24,360 and uses activated sludge waste
water treatment with chlorine disinfections. The solids
handling process consists of dissolved air flotation unit,
gravity thickener for primary slide, sludge equalization tank,
anaerobic digesters, and sludge holding tank. The average
inflow is about 3.5 million gallon per day with an average BOD
of 154.56 mg/L, and the treatment facility effluent BOD is
about 4 mg/L. Three: Mixed anaerobic culture seed, which was
collected from an anaerobic dairy waste lagoon located at the
Knott Dairy Center, Washington State University, Pullman,
WA. The 5900 m2 anaerobic lagoon receives flushed manure
from a dairy with a herd of approximately 250 cows (milking
cows and heifers) and approximately 80 calves. The waste
consisting of feces, urine, bedding materials, and milking
parlor waste is scraped into a manure pit from where it is
subsequently flushed and delivered to a solids separator using
recycled waste water. After the solid separator has removed
solids of greater than 0.3 cm diameter, the waste water is
pumped to the lagoon. The supernatant water from this
lagoon was used as inocula. All inocula were stored in 20 C
and were transferred to 4 C just prior to treatments preparation. The inocula characteristics are shown in Table 2.
2.3.
Experimental design
The study was designed to investigate the efficacy of granular
and non-granular sludge as well as the effect of mixing on the
startup of anaerobic reactors. Inocula availability and possibility to use in full-scale reactors were the criteria for selecting
the types of inocula for this study. Three different inocula and
a control were investigated in mixed and non-mixed reactor
startups. The experiment had the following four inocula
treatments for the stirred and unstirred conditions mixed
Table 2 e Characteristic of inocula and dairy manure.
Parameter
TS (g/g)
VS (g/g)
COD (mg/l)
TAN (mg/l)
Total VFA (mg/l)
Granular sludge
6.32 0.36
5.37 0.36
46393 2383
327 9
ND
Non-granular sludge
2.53 1.88 45303 887 302 Diluted manure was used for treatment preparations.
0.19
0.08
1343
36
12
Mixed culture
1.62
1.30
21750
430
351
0.11
0.10
962
25
11
Diluted manure
2.25 1.68 30304 452 1130 0.17
0.09
1242
22
25
Raw manure
15.9 0.6
13.9 0.6
ND
ND
ND
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with dairy manure into ratio of 1:4: (1) granular inoculum
(GM), (2) sludge inoculum (SM), (3) anaerobic lagoon (LM), and
(4) pure dairy manure (MM) with no exogenous inoculum (the
control). In vitro anaerobic digestion tests were carried out in
identical batch reactors having a working volume 125eml
(Serum bottles, Scientific Instrument Services, Ringoes, NJ).
The reactors were sealed with a thick rubber septum and then
flushed with a gas mixture of 80% N2 and 20% CO2 for 5 min.
Each treatment used 10 reactors resulting in 40 reactor units
for stirring and 40 non-stirred reactor units. An orbital shaker
(New Brunswick Scientific, Edison, NJ) at 125 rpm was used for
stirring the reactors. The anaerobic digestion was carried out
for ten days at 35 C. Digested slurry from one of the reactors
(out of the 10 used per treatment) was used for digestion
analysis every day; the reactor was subsequently discarded.
The gas produced was measured with a gas tight glass syringee35 ml (Micro-Mate, interchangeable hypodermic syringe,
Popper & sons, Inc. New Hyde Park, New York) and collected in
a test viale10 ml (Labco Limited High Wycombe, 10 ml) every
day. The gas was released after the volume measurement to
avoid build-up of high pressure in the reactor that would lead
into leakage of gas. This procedure was replicated in all the
4 treatments and 10 days of experimentation. Specific biogas
production (SGPR, volume of biogas produced per ton of initial
volatile solids per day), volatile fatty acids (VFA), pH, alkalinity, a (VFA to alkalinity ratio) [8,23], total solid (TS), volatile
solid (VS), and total ammonia nitrogen (TAN) were measured
in all treatment to evaluate the effect of inocula in reactor
startup. The schematic of the experimental setup is presented
in Fig. 1.
Varian FID for CH4, Varian TCD for CO2, and a De2 pulsed HID
mode discharge detector for H2S measurement. The GC was
equipped with a switching valve (A3C6UWT) with 1 mL
sample loop and a column (Varian 180 180 Hayesep Q 80/100
Mesh Silcosteel and nitrogen as carrier gas) for CO2 and CH4
measurement. A switching valve (A3C6UWT) with 0.25 mL
sample loop and a column (Varian 50 m 0.53 mm 4 mm
SilicaPlot and helium as carrier gas) were used for H2S
measurement. The oven and the TCD temperature were kept
at 80 and 120 C, respectively. GC was calibrated with 99.9%
pure CH4, CO2, H2S and H2 standards.
2.4.2.
2.4.3.
2.4.
Laboratory analyses
2.4.1.
Methane content
Gas samples were withdrawn from the headspace of test vials
and were injected into a Varian CPe3800 gas chromatograph
(GC) for measuring the biogas contents (methane and carbon
dioxide). The GC was equipped with following detectors:
Scanning electron microscope analysis
Samples were first fixed overnight at 4 C with 2% paraformaldehyde, 2% glutaraldehyde and anaerobic 0.05 M
cacodylate buffer for performing Scanning Electron Microscope (SEM). The fixed samples were washed three times in an
anaerobic 0.05 M cacodylate buffer and then, 1% osmium
tetroxide (1e2%, for 1 h) was used for fixing. The samples were
then dehydrated with a graded series of ethanoledistilled
water mixture (30e100% v/v) and placed in 100% ethanol. The
samples were dried by the criticalepoint drying method
before sputterecoating with gold particles. The samples were
mounted on aluminum stubs and sputter coated in a Polaron
E5100 (VG Microtech), with platinum/palladium target (60:40).
The samples were then examined in a JEOL JSMe5800 LV
scanning electron microscope.
2.4.4.
Fig. 1 e Schematic diagram of experimental setup.
Volatile fatty acids
The concentrations of volatile fatty acids (acetic, butyric and
propionic acids) were determined using Dionex Ion chromatograph (DX-500 IC). The IC was equipped with AS-3500 autosampler. A small sample (feedstock, inoculum and digested
slurry) was centrifuged at 12,000 rpm for 6 min. After centrifuging, supernatant was filtered through a 0.2emmeporeesize
filter before injection into an IC. The Peak Net R software
controlled the injection. A detector (ED 40 electrochemical
detector) and a column (4 250 mm Carbon Pacä PA 10 analytical column) were used for analyzing VFA concentrations.
Elution was initiated with 10% (v/v) water and 90% (v/v) 52 mM
NaOH for 27.10 min, with 100 ml of sample injected at 0.10 min.
The elute flow rate was 1.2 ml/min with the pressure between
1500 and 3000 psi. The IC was calibrated with pure acetate,
butyrate and propionate standards. A verification test was
performed after every 10esample analyses.
Transmission electron microscope analysis
Samples prepared for transmission electron microscope (TEM)
were washed with 0.1 M phosphate buffer (pH 7.2) and fixed in
0.1 M phosphate buffer (pH 7.2) containing 2.5% glutaraldehyde for 12e16 h at 4 C. The fixed samples were rinsed three
times (10 min each) at ambient temperature in 0.1 mM phosphate buffer (pH 7.2) and postfixed with 1% Osmium Tetroxide
(OSO4) in the same buffer. The sample were then rinsed in
0.1 mM phosphate buffer, and dehydrated through a graded
series (30e100%) of ethanol solutions, ethanoleacetone
mixture (1:1, for 10 min) and through 100% acetone (two times,
10 min each). Dehydration was followed by sample filtration.
A mixture of acetone and spurrs (1:1, for 1 h) and 100% spurrs
(for 12e15 h) was used for filtration. Resin was changed prior
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to embedding. Samples were embedded in Polybed 812 (Polyscience, Inc., Warrington, Penn.). Thin sections were cut with
ReicherteJung ultramicrotomes for resin sections and poststained with uranyl acetate and lead citrate. The samples
were then examined in a JEOL 1200eEX, which was equipped
with digital camera and X-ray microanalysis system.
s
Yijku ¼ mþai þbj þðabÞij þew
iju þgk þðagÞik þðbgÞjk þðabgÞijk þekðijuÞ
Statistical analyses
A mixed linear model was developed to examine and compare
responses (biogas production) over time. The three factors
examined in a completely randomized design (CRD) model
were: (1) incubation period, (2) inoculum type (treatments),
and (3) stirring conditions. The “PROC MIXED” function of SAS
Stirred reactors
350
350
Specific biogas production rate ( m 3 biogas/ t VS)
Biogas (ml/batch)
150
100
200
150
100
50
50
0
0
2
8000
4
6
8
GM
SM
LM
MM
6000
4000
2000
0
140
2
4
6
8
10
GM
SM
LM
MM
100
8000
4
6
8
D
10
GM
SM
LM
MM
6000
4000
2000
0
0
2
4
6
8
60
40
10
80
60
40
20
0
0
4
6
8
Days of incubation
10
GM
SM
LM
MM
100
20
2
F
120
80
0
2
140
E
120
0
10
C
0
GM
SM
LM
MM
250
Fraction of CH4 (%)
Biogas (ml/batch)
200
0
B
300
GM
SM
LM
MM
250
Fraction of CH4 (%)
Unstirred reactors
A
300
(1)
Where: Yijku is biogas production in uth reactor (u ¼ 1,.,10) at
ith treatment level (i ¼ 1,., 4); jth stirring level ( j ¼ 1(stirred),2
(unstirred); and on the kth day (k ¼ 1,.,10). The m is overall
mean biogas production; ai is deviation of the response at ith
treatment level from m; bj is deviation of the response at jth
stirring level from m; gk is deviation of the response on the kth
Specific biogas production rate ( m 3 biogas/ t VS)
2.5.
9.1 (SAS Institute Inc., Cary, NC) was used for the analysis of
the repeated measurements. Rank transformation approach
was used to transform the data to a form more closely
resembling a normal distribution framework [24]. Significance
was defined by p < 0.05. The developed statistical model for
analyzing daily biogas production is presented in Eq. (1).
0
2
4
6
8
Days of incubation
Fig. 2 e Gas profile of stirred and unstirred reactors.
10
2710
9.37
Aa
13.02
BC a
13.22
CD a
20.93
DE a
NM
7.99
Ab
7.50
AB a
11.89
AC b
1.51
Db
2.28
Aa
8.70
Ba
23.77
Ca
11.41
Aa
30.88
Ab
7.66
Ba
7.75
Bb
2.32
Cb
15.11
Aa
7.31
Ba
25.19
Ca
10.29
Da
NM
23.74
Aa
10.50
Bb
21.78
Ab
1.75
Cb
21.87
Aa
8.87
Ba
32.36
Ca
8.08
DB a
18.89
Aa
12.00
Ba
20.65
Ab
3.81
Cb
18.48
Aa
10.59
Ba
32.71
Ca
6.39
Da
13.55
Ab
11.67
Aa
28.38
Ba
3.08
Cb
MM
SM
LM
M ¼ Mixing.
NM ¼ No mixing.
Data are compared for individual day column.
Means in columns with different capital letters are significantly different at p < 0.05.
Means in rows with different small letters are significantly different at p < 0.05.
21.58
Aa
10.65
Ba
30.57
Ca
7.67
Da
9.21
Ab
11.29
Bb
31.31
Cb
3.36
Db
32.24
Aa
14.27
Ba
47.61
Ca
8.07
Da
8.77
Ab
9.50
Ab
32.64
Bb
0.00
Cb
25.01
Aa
11.37
Ba
40.60
Ca
6.76
Da
5.11
Ab
4.22
Ab
24.74
Bb
0.00
Cb
32.22
Aa
12.61
Ba
35.11
Ca
5.44
Da
1.00
Ab
0.40
AB a
9.70
Cb
0.00
Bb
54.80
Aa
1.50
Ba
19.70
Ca
8.30
Da
GM
biogas production (ml)
NM
M
NM
M
NM
M
NM
M
NM
M
NM
M
Day 5
Day 4
Day 3
Day 2
Day 1
TRT
Table 3 e Repeated measures analysis of daily gas production.
The cumulative biogas production (Fig. 2A and B), specific
biogas production (Fig. 2C and D), and fraction of CH4 in biogas
(Fig. 2E and F) were used to evaluate inocula performances.
The repeated measure analysis of biogas production among
the treatments is presented in Table 3. Comparison of biogas
production is made among the treatments under both stirred
and unstirred conditions. Under stirring conditions, during
first two days of incubation period, biogas production in GM
treatments was significantly higher than in the other treatments, and both GM and SM treatments produced biogas
significantly higher than the LM and MM treatments. Under
unstirred conditions, biogas productions in GM and LM were
not significantly different. However, SM treatments produced
significantly higher amount of biogas than the other treatments. Overall, mixing increased gas production significantly
among all treatments during the first four days except in the
LM treatment, which produced almost similar amount of
biogas in both stirring and unstirred conditions on first day.
Subsequently, however, the biogas production in stirring
condition was higher than the unstirred condition.
In stirred reactors, the maximum specific biogas production (SGPR) ( p < 0.05) for GM, SM, LM, and MM treatments was
obtained on Day 1, 4, 10 and 10, respectively. The highest
methane content in biogas of GM (77 1.04), SM (71 0.87), LM
(37 3.64), and MM (33 1.37%) treatments was on Day 1, 3, 8
and 8, respectively.
In unstirred reactors, the maximum biogas yield for GM,
SM, LM, and MM treatments was obtained on Day 8, 3, 6 and
10, respectively. The highest methane content in biogas of GM
(67 1.46), SM (70 0.66), LM (32 3.03), and MM (32 0.94%)
treatments was on Day 10, 5, 8 and 10, respectively. Compared
to other treatments, the gas production was delayed until Day
4 in MM treatments.
The effects of mixing on treatment performance are
shown in Figs. 2, 3 and 4. The mixing in anaerobic digestion is
considered to be important and its effects are discussed
extensively [27]. The study on effect of mixing which deals
with inoculation and startup period, however, is rare. The
Day 6
M
Inocula performances
NM
Day 7
M
Day 8
Startup period (time required to start biogas production) in
anaerobic process is considered to be very critical [8] for
anaerobic digester. This study is focused on the startup period
of anaerobic digestion. Since the initial active biomass (population of Syntrophobacter and methanogens) plays a key role
in catalyzing the anaerobic process [7,9,25,26], the performance of inocula (which was used as an initial active biomass
to start the anaerobic process) was evaluated.
3.1.
M
M
Results and discussion
NM
Day 9
3.
Day 10
day from m; (ab)ij is an interaction term between ith treatment
level and jth stirring level; (ag)ik is an interaction term
between ith treatment level and kth day; (bg)jk is an interaction term between jth stirring level and kth day; (abg)ijk is
a threeeway interaction term from ith treatment level, jth
s
stirring level, and kth day. The ew
iju and ekðijuÞ are mutually
w
independent random errors; eiju wNð0;sw2 Þ and eskðijuÞ wNð0;ss2 Þ.
13.92
Ab
9.01
Bb
13.29
Aa
3.96
Cb
b i o m a s s a n d b i o e n e r g y 3 5 ( 2 0 1 1 ) 2 7 0 5 e2 7 2 0
2711
b i o m a s s a n d b i o e n e r g y 3 5 ( 2 0 1 1 ) 2 7 0 5 e2 7 2 0
effect of mixing varies at different anaerobic stages (e.g.,
startup and steady state). In addition, it is altered by many
other factors such as type of waste, type of inocula and
changing food e microorganisms ratio (F/M) [27], which was
evident in this study, too. In stirred condition, both GM and SM
treatments produced better biogas than other treatments.
However, under unstirred condition the SM treatment performed better than GM treatment, which indicates that stirring effect may vary for different inocula. The low gas
production in treatments (GM, LM, and MM) under unstirred
condition could have been the result of inadequate mixing to
encourage the distribution of enzymes and microorganisms
throughout the reactor [26,27,28,29]. The better performance
of SM treatment in both stirred and unstirred reactors could
be the result of higher level of aceticlastic methanogens (Table
1) [8,26,29]. In contrast to the stirred treatment, granule
VFA, Acetate (mg/lit)
5000
5000
Stirred
Unstirred
4000
4000
3000
2000
2000
1000
1000
0
0
2
4
6
8
0
10
5000
2
4
4000
8
3000
3000
2000
2000
1000
1000
0
0
2
4
6
8
10
Stirred
Unstirred
4000
0
2
Days of incubation
VFA, Propionate (m g/lit)
6
10
5000
SM
Stirred
Unstirred
0
4
MM
6
8
10
Days of incubation
5000
5000
Stirred
4000
GM
Stirred
4000
3000
3000
2000
2000
1000
1000
0
0
2
4
6
8
0
10
LM
Unstirred
Unstirred
0
VFA, Propionate (m g/lit)
LM
Stiired
Unstirred
GM
3000
0
VFA, Acetate (mg/lit)
settling in the unstirred treatment might have lowered the
rate of the process. Higher settling characteristics of granule
[8,10] may have resulted in poor contact between feed and
inoculum. However, in some aspects, settling of the granule
may be considered an advantage because it retains active
biomass in the reactor [30]. Therefore, for a continuous or
semi e continuous reactor, granules could be the best inocula,
where a need to retain the active microorganism in the reactors for a longer time is necessary.
The volatile fatty acids (VFA) concentration in the GM, SM,
LM, and MM treatments are shown in Figs. 3 and 4. Two
different patterns of VFA concentrations were evident for GM
and MM treatments under stirred and unstirred conditions. In
the stirred GM treatment, the VFA accumulation was
comparatively very low, and the gas production was higher
(with higher methane content). Under unstirred conditions,
2
4
6
8
10
5000
5000
Stirred
4000
Unstirred
SM
3000
3000
2000
2000
1000
1000
0
0
0
2
4
6
8
Days of incubation
10
Stirred
4000
MM
Unstirred
0
2
4
6
8
Days of incubation
10
Fig. 3 e Acetate and propionate concentrations in GM, SM, LM, and MM treatments.
2712
b i o m a s s a n d b i o e n e r g y 3 5 ( 2 0 1 1 ) 2 7 0 5 e2 7 2 0
VFA, Butyrate (mg/lit)
5000
5000
Stirred
4000
Unstirred
3000
2000
2000
1000
1000
0
0
2
4
6
8
10
5000
Stirred
4000
3000
0
VFA, Butyrate (mg/lit)
GM
LM
Unstirred
0
2
4
6
8
10
5000
SM
Stirred
Unstirred
4000
Stirred
Unstirred
4000
3000
3000
2000
2000
1000
1000
0
MM
0
0
2
4
6
8
10
Days of incubation
0
2
4
6
8
10
Days of incubation
Fig. 4 e Butyrate concentrations in GM, SM, LM, and MM treatments.
the initial increase in VFA concentration continued until Day 5
in the GM treatment, and until Day 10 in the MM treatment.
The initial increase in the VFA concentrations indicates
activity of hydrolytic and fermentative bacteria [8]. Compared
to the GM and MM treatments, the VFA concentration was
relatively the same in the SM and LM treatment under both
stirred and unstirred conditions. As shown in Fig. 3, acetate
was the main accumulated fatty acid. Compared to stirred
conditions, the acetate concentration was higher in the GM
and MM unstirred conditions. The acetate formation in
anaerobic process is a result of propionate and butyrate
conversion into acetate through syntrophic association [31].
The syntrophic association between propionate and butyrate
edegrading bacteria with methanogens have previously been
reported [10]. Table 5 shows the reactions and the free energy
0
change (D G0 ) during syntrophic metabolism. Such association, however, requires the favorable thermodynamics [32]
and balanced population of methanogens as well as syntrophobacter. The whole anaerobic process starts with the syntrophic fermentative bacteria, which degrades propionate and
butyrate (reaction 1e2) into the acetate and H2. However,
these reactions are endogenic and thermodynamically unfavorable, unless the product, H2, is kept at low concentrations
[7,32,33]. At low H2 concentrations endogenic reactions
become exogenic (a thermodynamically favorable) [32]. This
low concentration of H2 in anaerobic process is maintained by
the hydrogenotrophic methanogens (reaction 3). These
methanogens use the H2 to reduce CO2 to CH4 [32]. Finally,
acetate is converted into methane by an exogenic process
(reaction 4).
Table 1 shows the reported syntrophobacter and methanogens in granule, sludge and dairy manure. Out of the
combined population of methanogens and syntrophobacter,
granule consists of 93.76% methanogens (aceticlastic 46.88%
and hydrogenotrophic 46.88%). The sludge mostly consists of
aceticlastic methanogens (85.32%). Manure mainly consists of
propionate and butyrate degraders [8,26]. The low population
of methanogens could have been the reason for higher acetate
accumulation in the MM treatments. In the GM and SM
treatments, the low level of syntrophobacter and higher level
of methanogens may have caused the low VFA concentrations
and higher biogas production. The higher population of syntrophobacter may have caused the higher level of VFA in both
the LM and MM treatments, which may have been the reason
for low biogas production (Figs. 2, 3, and 4).
Table 4 shows VFA/alkalinity ratio, which is denoted
by a. The a indicates the balance between production and
consumption of VFA [8]. Values of a less than 1.0 indicate
acceptable ratios while values higher than the 1.0 signify
imbalance between VFA production and consumption in the
reactor, which may upset the anaerobic process [23]. PoggiVaraldo and Oleszkiewicz [23] and Griffin [8] proposed that an
increase in the a-values precedes a pH decrease, making it
possible to predict an imbalance before the VFA concentrations or pH reveal the instability.
The a values were calculated for GM, SM, LM, and MM
treatments under stirred and unstirred conditions. In stirred
conditions, the lowest a value (0.07 0.12) was found in the
treatment GM. This treatment produced the highest amount
of gas. The second lowest a value (0.10 0.10) was found in the
SM treatments, which produced second highest amount of
gas. In LM and MM treatments, a-values were 0.56 0.12 and
0.69 0.18, respectively. The treatment with the lowest avalue produced overall the highest amount of gas. Similar
results were observed under unstirred conditions. The SM
treatment produced the highest amount of gas and had the
lowest a-value (0.11 0.10). The highest a-value was observed
in the MM treatment, which also produced the lowest amount
of gas. Our results suggest that a-values can be used as indicators of potential biogas production in both stirred and
2713
b i o m a s s a n d b i o e n e r g y 3 5 ( 2 0 1 1 ) 2 7 0 5 e2 7 2 0
Table 4 e Performance of treatments under stirred and unstirred conditions.
Characteristics of
treatments over
10 days of incubation
Acetic acid (mg/lit)
Propionate (mg/lit)
Butyrate (mg/lit)
Total VFA (mg/lit)
Alkalinity (mg/lit)
pH
TS (%)
VS (%)
VS/TS
TAN (mg/lit)
VSfeed/VS inoculum, F/M)
SPMP (ml CH4/g VS)
Alpha (a)
SGPR (m3/t VS day)
a
TS Change (%)
a
VS Change (%)
Stirred
1
2
Unstirred
3
4
2
1
GM
SM
LM
MM
GM
SM
LM3
MM4
326 58
327 234
186 ND
651 478
3559 516
5.8 0.5
1.64 (0.3)
1.19 (0.25)
0.73
386 97
0.31
1677 932
0.07 0.12
2215 1198
13
15
356 87
292 114
166 56
703 157
3823 292
6.9 0.6
1.71(0.32)
1.22(0.25)
0.71
587 48
0.89
1466 412
0.11 0.10
1960 651
45
43
1036 290
785 212
302 45
2096 443
3786 15
6.9 0.4
2.25(0.19)
1.45(0.50)
0.64
510 42
1.29
225 93
0.56 0.12
959 353
þ19
þ20
1025 281
794 220
263 114
2083 517
3024 181
5.9 0.5
1.76(0.17)
1.29(0.14)
0.73
460 45
1
106 72
0.69 0.18
694 329
18
21
1532 761
676 116
365 94
2469 976
4635 484
6.5 0.5
1.42(0.18)
0.72(0.24)
0.51
661 106
0.31
597 541
0.62 0.18
1213 23
21
70
356 107
252 105
205 ND
600 233
3743 42
6.9 0.6
1.73(0.33)
1.21(0.28)
0.7
549 41
0.89
943 418
0.11 0.10
1318 95
28
61
978 251
655 198
285 36
1892 522
3793 84
6.8 0.4
2.27(0.20)
1.61(0.15)
0.71
519 41
1.29
217 110
0.50 0.13
812 355
þ23
þ28
1859 439
704 142
327 77
2890 04
3342 99
6.3 0.1
2.15(0.23)
1.57(0.18)
0.73
379 49
1
26 21
1.23 0.10
147 117
30
33
Superscripts in treatments (GM, SM, LM and MM) are performance ranking based on the specific biogas production (SGPR) and specific methane
production (SMP).
Treatments were prepared using 25% inocula and 75% feed (manure).
The results of 10 day incubation were used to calculate the average and standard deviation (SD). ND indicates not determined.
Total VFAs equals the sum of acetate, propionate, and butyrate.
a Positive sign indicates increase while negative sign indicates decrease in TS or VS.
unstirred conditions. The MM unstirred treatment, with avalue of 1.23 (>1.0; the threshold of stability) produced the
lowest amount of gas. Griffin [8] reported use of NaHCO3 for avalues higher than 1.0 to prevent reactor’s instability. Sung
[35] proposed that a-values of about 0.10 can be considered as
an indication for stable operation of mesophilic anaerobic
digester. Our results corroborate Sung’s recommendations. In
our study, a-values were either less than 0.10 or about 0.10 in
the GM and SM treatments. These two treatments produced
higher amount of gas than the other treatments.
Under stirred conditions, the average pH value in the GM
treatment was 5.8 0.5. The pH-values ranged from 4.71 to
6.68 in the GM treatment; from 5.5 to 7.70 in the SM treatment,
from 6.44 to 7.43 in the LM treatment, and from 5.47 to 6.76 in
the MM treatment. Generally, the pH-values were higher than
6.0 during most of the incubation period for all treatments
except GM stirred. The GM reactor, however, performed the
best. Under unstirred conditions, the pH value ranged from
5.58 to 7.08, 5.8e7.64, 5.94e7.37, and 6.27e6.54, in the GM, SM,
LM, and MM treatments, respectively. In previous studies,
Zhang et al. [36] reported pH-values ranging between 6.1 and
6.8 during anaerobic of dairy manure, while Sung [35] reported
pH-values ranging between 7.2 and 7.75 in mesophilic dairy
manure anaerobic digestion. In our studies, pH-values usually
ranged between 6.0 and 7.5. In general, low pH-values coincided with high a-values in most of the treatments. These
results are similar to Sung’s [35] results, who compared pH
and a-values in thermophilic and mesophilic anaerobic
digestion.
The average TS and VS contents in all the treatments as
well their respective changes during the treatments under
stirred and unstirred conditions are shown in Table 4. The
reductions in TS and VS were calculated as a percentage of the
difference between initial and final concentrations against
the initial concentrations. Under stirred conditions, TS and
VS decreased in all treatments except the LM treatments. The
respective decrease in TS and VS were 13 and 15% in the GM
treatment; 45 and 43% in the SM treatment; and 18 and 21% in
the MM treatment. In the LM treatment, the TS and VS
increased by19 and 20%, respectively. In previous studies,
Sung [35] also reported increase in TS and VS when reactors
were performing poorly. In our studies, the LM treatment
performance was relatively poor. Dugba and Zhang [37]
reported TS reductions ranging between 6 and 28% and VS
reductions ranging between 8 and 30% for dairy waste mesophilic anerobic digestion. The Dugba and Zhang study evaluated the impacts of organic loading rates on TS and VS
removal and indicated that TS and VS reduction varied with
loading rates. Their study also emphasized that longer incubation period may be required for significant TS and VS
reduction in dairy waste digestion. Under unstirred conditions, the respective reductions in TS and VS were 21 and 71%
in the GM treatment; 28 and 61% in the SM treatments; and 30
and 33% in the MM treatments. In contrast, the TS and VS in
the LM treatment increased by 23 and 28%, respectively. In
general, approximately 5% more decrease in VS was observed
compared to the decrease in TS in most of the treatments
except GM and SM unstirred treatments. In GM and SM
unstirred treatments, VS decreases were 70 and 61%, while
decreases in TS were only 21 and 28%, respectively. High
microbial activity in these two treatments may have increased
VS reduction as well as improved gas production. These
treatments produced higher amounts of gas than other
unstirred treatments. Dugba and Zhang [37] also noticed that
improved performance resulted in greater VS reduction.
The VS/TS ratios for stirred and unstirred conditions are
shown in Table 4. In GM and SM stirred treatments, the VS/TS
ratios were higher than in the unstirred treatments. Both the
2714
b i o m a s s a n d b i o e n e r g y 3 5 ( 2 0 1 1 ) 2 7 0 5 e2 7 2 0
GM and the SM treatments produced more gas in stirred
conditions than in the unstirred conditions. In the LM stirred
treatment, the VS/TS ratio as well as biogas production were
lower than in the unstirred conditions. In the MM treatment,
biogas production was comparable in both stirred and unstirred
conditions, and VS/TS ratio remained same in both conditions.
Based on the performance of the treatments, a ranking of
suitable inocula was developed for inocula selection. The
performance criteria were amount of gas production,
methane content, and the onset of the gas production. Table 4
shows the performance ranking of the treatments. The
ranking (from higher to low) for stirred and unstirred is GM,
SM, LM, and MM, and SM, GM, LM, and MM, respectively.
3.2.
Microscopic examination of inocula
Scanning Electron Microscope (SEM) and Transmission Electron Microscope (TEM) examinations were performed on
inocula (granular sludge, non-granular sludge and dairy
manure) to determine the distribution of microbial population.
The morphology of methanogens and other anaerobic microorganism published elsewhere [38,39,40,41,42,43,44,45,46]
were used to identify the specific microorganisms in inocula.
Granular inocula were spherical in shape and dark black in
color. The diverse syntrophic colonies consisting of methanogens bacteria were present in the granules. Fig. 5A illustrates
the external surface of granular inocula, whereas Fig. 5B illustrates a section of the granule. Randomly distributed cavities
and holes with openings of 5e15 mm in diameter with microbial
lining of Methanobacterium-like and Methanothrix-like bacteria
were common (Fig. 5C), which facilitate gas or substrate
transport from outer surface to inner part or vise versa [10].
While Methanobacterium are autotrophic organisms that grow
under high H2 - pressure and consume H2 and CO2, Methanothrix
are aceticlastic organisms, that play an important role in
granule formation and use acetate [8,9]. The granule surface
was predominant with two types of rods: small plump rods
(Fig. 5C,D) and bamboo shaped small and long filamentous rods
(Fig. 5D). Plump rods resembled Methanobacterium-like (Mbac)
bacteria and bamboo shaped rods (Fig. 5D,E) resembled Methanosaeta (Msae; also knows as Methanothrix) - like bacteria
[9,31]. Sectioned granule structures show the honeycomb
structures at the centers (Fig. 5F) of the granules. These honeycombed networks are believed to be dead cells of the Methanothrix [44], which are responsible for acetate consumption. In
the center of the granule, diatom like structures (Fig. 5G,H)
were also found. These could be the viable diatoms enmeshed
in granules that survived the extreme anaerobic dark environment [47,48]. TEM micrographs show the juxtaposing
microcolonies in the granule (Fig. 6G). The colonies consisted of
Methanospirillum (Msp)-like, Methanobacterium (Mbac)-like, and
Methanosaeta (Msae)-like microorganisms (Figs. 6G, 7AeB). In
addition, the colonies of Desulfobulbus (Dsb)-like fat rods and
Dsulfovibrio-like (Dsv) (resembling half-moons and rough
spheres) were observed occasionally. Also, the sheath like
structure resembling Methanospirillum-like bacteria [31],
hydrogen e and formate e utilizing bacteria [49],were
randomly distributed (Figs. 6G and 7B).
Microbial distribution in non-granular inoculum was
different than in the granules. In the sludge, the bundles of
rodlike structures (Fig. 5I) consisting of Methanosaeta-like
bacteria were observed. The long filaments, identical to
Methanosaeta, were abundant, which is common in sludge
[29,46]. Filaments fused together resembling Methanosaeta-like
bacteria, forming long rope-like structures, were predominant
(Fig. 6A and B). These rope-like structures resembled Methanosaeta fibers [34]. The Methanosaeta fibre serve as initial
nuclei for granule formation in anaerobic migrating blanket
reactor (AMBR) and Upflow Anaerobic Sludge Blanket (UASB)
[46]. Presence of Methanosaeta fibre in sludge, however, has not
been reported. More observations of the sludge collected from
different sludge digesters is needed to confirm that Methanosaeta fibre formation exists in non-granule forming reactors.
TEM
micrographs
show
the
presence
of
Methanobrevibactor-like rods (Fig. 7C) in non-granular sludge.
These bacteria were in juxtaposition with other anaerobes.
Sulfate reducing bacteria such as Dsulfovibrio and Desulfobulbus-like bacteria were observed in juxtaposition with
Methanobrevibactor-like rods (Fig. 7D). Presence of Dsulfovibrio
and Methanothermus fervidus bacteria presence in sludge are
reported elsewhere [43]. Usually, Dsulfovibrio spp. form syntrophic association with the H2 utilizing bacteria (Methanobrevibactor) to produce acetate [31]. In addition, the
juxtaposition of propionate degraders such as Syntrophobacter
wolinii (Synw)-like and Methanobrevibactor-like bacteria with
occasional presence of Methanospirillum-like and Methanobacterium - like bacteria was noted.
In dairy manure, the Syntrophobacter-like bacteria were
abundant. Dairy manure had less methanogens compared to
sludge and granule inocula. In addition to Syntrophobacter and
methanogens, dairy manure exhibited other structures such
as ciliates and cocci. The cocci rods (25e40 mm in diameter)
along with other cells and fibrous material were predominant
on the surface of dairy manure (Fig. 6D). Some diamondshaped structures resembling Ostracodinium obtusum ciliates
[42] were deeply embedded in the fibrous material (Fig. 6E).
Structure of Syntrophobacter-like and Methanobrevibactor-like
bacteria were present in unattached form (Fig. 8A,B). Methanobrevibactor are the main methanogens in dairy manure [40],
however, Methanosarcina-like bacteria along the cist with
holes and cavity were also noted occasionally (Fig. 6F). Methanobrevibactor are considered to be hydrogen and carbon
utilizing bacteria and play an important role in methane
formation (reaction 4 of Table 5). There are some reported
studies which describe the somatic association between
rumen’s ciliates and methanogens [50]. TEM micrographs
show the random distribution of Syntrophobacter and methanogens (Figs. 7F, 8A and 8B). Fig. 7F shows the presence of
Syntrophobacter and small rods resembling the Methanobrevibacter-like bacteria.
Unlike in granules and sludge inocula, microcolonies
formation was completely absent or very rare in manure and
Syntrophobacter-like were more abundant (8A and 8B). Low
population of methanogens may have been the main reason
for delayed biogas production in MM treatments. In addition,
higher growth rate of Syntrophobacter than methanogens may
have further imbalanced the populations [27], which is
a reasonable explanation for observed low and delayed biogas
production in MM treatments. In granule inoculum, the
juxtaposition of Syntrophobacter-like (propionate degrader)
b i o m a s s a n d b i o e n e r g y 3 5 ( 2 0 1 1 ) 2 7 0 5 e2 7 2 0
2715
Fig. 5 e SEM of the granular sludge (AeH) and non-granular sludge (I). (A) External and (B) internal texture. (C) Cavities and
hole surrounded with small plump rods (Methanobacterium-like) and long rods (Methanosaeta-like) at surface. (D)
Aggregation of small plump rods at internal surface (Methanobacterium-like). (F)Honey comb structure, which believed to be
formed by Methanosaeta-like bacteria. (G & H) Structures resembling diatoms was in the center of granules. (I) Bundle of rodlike structures in non-granular sludge.
2716
b i o m a s s a n d b i o e n e r g y 3 5 ( 2 0 1 1 ) 2 7 0 5 e2 7 2 0
Fig. 6 e SEM micrographs of non-granular sludge (AeC), dairy manure (DeF) and a TEM micrograph of the granule showing
the rods and cells (G). (A) Shows the small and long rods embedded in the film. (B) Rope, which resembling Methanosaeta e
fibre. (C) Formation of long chain by Methanosaeta-like bacteria. (D) Micrographs showing long rods, short plump rods, and
small cocci in the surface of dairy manure. (E) Ciliate-like structure in dairy manure in deep penetration of straw cells. (F)
Methanosarcina-like structure in dairy manure (G) TEM micrographs of low magnifications illustrating the microcolonies of
different bacterial cells in granule.
b i o m a s s a n d b i o e n e r g y 3 5 ( 2 0 1 1 ) 2 7 0 5 e2 7 2 0
2717
Fig. 7 e TEM micrographs of granule (AeB), non-granular sludge (CeE) and low magnification of manure (F). (A) Shows the
juxtaposition syntrophic association in granule. (B) Shows the syntrophic growth of Dsulfovibrio-like (Dsv) and
Methanobacterium-like (Mbac) cells. (C) Methanobacterium-like (Mbac) cells. (D) Juxtaposition syntrophic association of
Methanobacterium, Desulfobulbus and Dsulfovibrio-like in sludge. (E) Dispersed (not in microcolonies) growth of
Methanobacterium, Desulfobulbus and methanosaeta-like bacteria. (F) Show the abundance of syntrophobacter-like bacteria.
Fig. 8 e TEM micrograph of high magnifications. (A) Shows the Methanosaeta (Msae), Desulfobulbus (Dsb), and
Methanobacterium-like (Mbac) structure. (B) Contrast to granule, unorganized growth of cells in manure.
2718
b i o m a s s a n d b i o e n e r g y 3 5 ( 2 0 1 1 ) 2 7 0 5 e2 7 2 0
Table 5 e Syntrophic reactions.
Step
Reactions
D G0’(kJ/mol)a
Involve Anaerobes
þ76.1
Syntrophic or proton- reducing acetogenic bacteria
such as Syntrophobacter fumaroxidans
[32]
Syntrosphospora bryantii,
Syntrophomonas wolfei [32,33]
Acetate production in syntrophic metabolisms
1
CH3CH2COO- þ 3H2O / CH3COO- þ HCO3- þ Hþ þ 3H2
Propionate / acetate (endogonic)
CH3CH2CH2COO- þ 2H2O / 2 CH3COO- þ Hþ þ 2H2
Butyrate / acetate (endogonic)
H2 consumption
3
4H2 þ HCO3- þ Hþ / CH4 þ 3H2O
H2 / Methane (exogonic)
Acetate consumption
4
CH3COO- þ H2O / CH4 þ HCO3Acetate / Methane (exogonic)
2
þ48.6
135.6
31.0
Hydrogenotrophic methanogens
[32,33]
Methanosaetaceae,
Methanosarcina [8,32,33]
a Change of standard Gibbs free energy in syntrophic metabolisms [32].
with Methanobrevibactor-like bacteria, and Syntrophomonas-like
(butyrate degrader) with Methanobrevibactor-like bacteria may
have balanced the production and consumptions VFA and H2,
which have resulted in higher methane production.
Compared to granules, the sludge exhibited a smaller number
of microcolony formations between Syntrophobacter and
methanogens, however, the higher availability of methanogens such as Methanosaeta may have helped in lowering
VFA level and producing higher methane.
SEM and TEM images were instrumental for comparing the
different microbial shapes in granular, non-granular inocula
and manure samples, and provided information on bacteria
juxtaposition and association. For example, SEM images of
granules showed that the external surfaces had abundant
loosely associated rod shape structures (Fig. 5C) around the
cavities, while the inner structures were more enmeshed and
condensed and bacteria strongly fused together. In digested
non-granular sludge, the bacteria aggregated around solid or
fibrous particles and a thin film was observed (Fig. 5I), which
signify that there could be biofilm formation during digestion.
In manure samples, bacteria were more dispersed, and
juxtapositions are not as prominent as in granules and
digested sludge. The TEM images, for example, Fig. 7A,
showed that bacteria in granules were more closely associated
and one group of bacteria was surrounded by the other
(Fig. 7B). In digested sludge (Fig. 7D) bacteria were slightly
farther apart but a thin film, which could be biofilm, surrounded the bacteria. In fresh undigested manures (Fig. 7E)
bacteria were more independent and showed no indication of
film formation.
Molecular based technology such as 16 sRNA is more
appropriate for quantifying total number of bacteria. However,
SEM and TEM images are more useful for elucidating the
juxtaposition and syntrophic association among the various
groups. These images were helpful in clarifying the population
variation on the external and internal surface of granules and
biofilm formations. Several reports have been published,
which explore the 16 sRNA techniques. Hwang et al. [52] used
this technique to evaluate methanogenic population in
anaerobic digestion of swine waste water; while Ike et al. [53]
studied population dynamics during startup treating industrial food waste using the same technique. Others including
Shin et al. [54,55] and Lee et al. [56] have also used this
technique: Shin et al. [55] performed comprehensive microbial
analysis in food waste-recycling waste water, while Lee et al.
[56] provided quantitative analysis of methanogens in batch
digesters treating different waste water. These studies were
important in understanding population dynamics. In view of
this, future work conducted over varying digestion periods and
digestion performance should combine SEM and TEM imaging
and quantitative microbial analysis using 16 sRNA to enhance
understanding microbial dynamics and interaction at optimal
performance conditions. The idea of optimizing the ratio
between syntrophic and methanogens population, which we
propose in this study, would need further work. Future work
should focus on providing precise quantification of these two
groups of bacteria at optimal conditions. This information has
the potential of enhancing anaerobic digester startup and
subsequent operation.
4.
Conclusions
The efficacies of three different inocula in the anaerobic
reactor startup treating dairy waste water were investigated
under stirred and unstirred conditions. The results from this
study suggest that selection of inocula is critical for anaerobic
reactor startup. Overall, stirring enhanced the biogas production and lowered accumulation of the VFA. Stirring was more
effective in GM and MM treatments than the SM and LM
treatments. Scanning Electron Microscope (SEM) and Transmission Electron Microscope (TEM) analyses revealed abundant aceticlastic and hydrogenotrophic methanogens in
granules, which may have provided ideal conditions for Syntrophobacter to efficiently degrade propionate and butyrate
without VFA accumulation. This could explain better biogas
production and low VFA levels in treatments when granule was
used as inoculum. Similarly, in SM treatments, a higher level of
aceticlastic methanogens in the digested sludge, which
consumes acetate, may have played crucial role in reducing the
VFA accumulation and enhancing digestion performance. In
MM treatments, low population of methanogens and higher
population of Syntrophobacter may have lowered the biogas
production and increased the level of VFA in the startup period.
The SEM and TEM images showed the variation in juxtaposition and bacteria population level in different inocula, and
b i o m a s s a n d b i o e n e r g y 3 5 ( 2 0 1 1 ) 2 7 0 5 e2 7 2 0
these were linked with biogas production in corresponding
treatments demonstrating the importance of syntrophic
association and population level of different groups of bacteria
in anaerobic digester performance. Future work should focus
on providing better estimation of total population in each
inocula using molecular based techniques such as 16 sRNA
coupled with the SEM and TEM image analysis to enhance
understanding of syntrophic interactions and role of each
group of bacteria in anaerobic digestion.
[15]
[16]
[17]
Acknowledgments
[18]
This study was conducted with financial support from Dr.
Shulin Chen’s Research Program (Dr. Chen is a Professor of
Biological System Engineering at Washington State University).
[19]
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