153
Sustain. Environ. Res., 23(3), 153-170 (2013)
Optimization of palm oil mill effluent treatment in an integrated
anaerobic-aerobic bioreactor
Yi-Jing Chan,* Mei-Fong Chong and Chung-Lim Law
Department of Chemical and Environmental Engineering
The University of Nottingham Malaysia Campus
Semenyih 43500, Malaysia
Key Words: Optimization, anaerobic, aerobic, wastewater treatment, palm oil mill effluent (POME)
ABSTRACT
An optimization study on the simultaneous anaerobic and aerobic processes in an integrated anaerobic-aerobic bioreactor (IAAB) treatment system for palm oil mill effluent was conducted for the
first time based on the response surface methodology. Three major constraints of the compliance to
the Malaysian discharge standard (Biochemical Oxygen Demand (BOD) < 100 mg L-1), methane gas
production (methane content > 60%) and stability of the IAAB (pH and total alkalinity of the
anaerobic effluent > 7.0 and > 2,000 mg respectively) were considered in this study. The IAAB's
treatment efficiency, methane gas production and process stability were comprehensively examined
at different levels of three critical parameters (organic loading rates (OLR), MLVSS (mixed liquor
volatile suspended solids) concentration in anaerobic (MLVSSan) and aerobic compartments
(MLVSSa)). It is worth noting that the anaerobic Chemical Oxygen Demand (COD) removals affect
considerably the overall treatment efficiency of IAAB, unless they are maintained under the
appropriate range of 77 to 87%. The IAAB achieved highest overall COD, BOD and total suspended
solids removal efficiencies of > 99% at optimum OLR of 12.8 g COD L-1 d-1, MLVSSan of 40,600 mg
L-1, and MLVSSa of 18,700 mg L-1. The treated effluents were well below the discharge standard with
BOD concentrations of 37 mg L-1. Further pilot scale studies are proposed before implementing into
industrial practice.
.
INTRODUCTION
Palm oil mill effluent (POME) is a voluminous,
high biochemical oxygen demand (BOD) liquid waste
(30,000 mg L-1) [1] which is generally discharged at
75-85 °C. It is a colloidal dispersion of biological
origin and with an unpleasant odour. It has a total
solids content of 5-7% where a little over half is dissolved solids, and the remaining is a mixture of
organic and inorganic suspended solids (SS) in various
forms [2]. These characteristics make it not only
highly polluting but also extremely difficult to be
treated by conventional methods. Without proper
treatment of POME, the effluent will pollute the
watercourses where this effluent is discharged.
.
The current treatment technology of POME comprises biological anaerobic and aerobic digestion or
facultative digestion. However, most of the treatment
plants have difficulties in complying with the dis*Corresponding author
Email: [email protected]
charge standard limits [3]. Therefore, a cost-effective
treatment of POME to an acceptable level for discharge continues to be a major challenge to the industry. Numerous advanced treatment technologies
such as anaerobic filter, anaerobic fluidized bed bioreactor and modified anaerobic baffled bioreactor have
been developed for POME treatment [1]. Nevertheless,
to effectively treat such high strength wastewater, a
combined anaerobic and aerobic process is required.
In this study, an integrated anaerobic-aerobic bioreactor (IAAB) which is a single reactor configuration
with compartmentalization where the first, second and
last compartments are designed for anaerobic, aerobic
and settling processes respectively is employed.
Previous works have shown the technical feasibility
of the IAAB for POME treatment where high overall
removal efficiencies (99%) for Chemical Oxygen
Demand (COD), Biochemical Oxygen Demand (BOD)
and Total SS (TSS) and satisfactory methane yield
(0.24 L CH4 g-1 CODremoved) were achieved at organic
154
Chan et al., Sustain. Environ. Res., 23(3), 153-170 (2013)
loading rate (OLR) of 10.5 g COD L-1 d-1 [1]. However, higher OLR is necessitated in order to reduce the
.
bioreactor volume as well as the capital costs.
There are many factors governing the performance
of the IAAB where optimization is required to maximize its performance at lower operating and capital
cost. From a practical and economic point of view,
optimization of the operating conditions for anaerobicaerobic treatment of POME to yield a lower capital
and operating costs will be beneficial. The traditional
one-at-a-time optimization strategy is simple and
useful for screening and the individual effects of the
factors can be seen on a graph without the need to
revert to more sophisticated statistical analyses [4].
Unfortunately, these procedures are time consuming
and unable to obtain the global optimum because of
the interactions between independent factors. This
limitation can be overcome by using design of experiment (DOE) software which offers a better alternative
to study the effect of variables and their responses
with minimum number of experiments. Response
Surface Methodology (RSM) is a collection of statistical technique for designing experiments, evaluating
the effects of factors and searching for the optimum
conditions of the factors [5]. By using DOE based on
RSM, the total number of experiments can be minimized without the need for studying all possible
combinations of the experiments. Therefore, DOE
could be applied in POME treatment to determine the
.
optimum conditions based on the RSM.
They are few studies reported in the literature on
the application of DOE in POME treatment, such as
application of the RSM to evaluate the interactive
effects of feed flow rate and upflow velocity on the
performance of an up flow anaerobic sludge fixed film
(UASFF) bioreactor [6,7] and optimization studies on
the coagulation-flocculation process [3]. However,
these optimization studies mainly focus on single
anaerobic stage rather than combined anaerobicaerobic stages. In fact, optimization of the combined
anaerobic-aerobic processes is more complex than in
single anaerobic or aerobic bioreactor as the performance of both stages is coupled. These coupled effects
of the combined stages in IAAB must be determined
by conducting the statistical optimization studies in
order to obtain high treatment efficiency with satisfactory methane yield and compliance to the discharge
limit at the lowest operational costs. Hence, the objective of this study is to model, analyze and optimize the
anaerobic and aerobic treatment of POME in the IAAB
by using RSM. The simultaneous effects of three
independent operating variables (OLRan, MLVSS
(mixed liquor volatile SS) concentration in anaerobic
(MLVSSan) and aerobic compartments (MLVSSa))
with 14 interrelated parameters as response were
investigated.
.
Central Composite Rotatable Design (CCRD)
.
The most popular RSM design is the CCRD [8,9].
One major advantage of CCRD is that due to its replicated center point, it can provide excellent prediction capability near the center of the design space
where the presumed optimum is located [10]. In the
case of missing any runs, the accuracy of the remaining runs becomes critical to the dependability of
the model. In this case, CCRD has more runs than
Box-Behnken design with optimal design and thus
makes CCRD more robust to the problems [11]. Based
on the reasons above, CCRD was used to design the
experiments in this study.
.
MATERIALS AND METHODS
.
1. Wastewater Preparation
The POME is obtained from Seri Ulu Langat,
Dengkil, Malaysia and its characteristics are presented
in Table 1. In order to prevent the wastewater from
undergoing biodegradation, it was preserved at temperature less than 4 °C, but above its freezing point.
The required volume was thawed to room temperature
.
(28 °C) before feeding into the reactor.
2. Reactor Configuration, Operation and Start-up .
The basic configuration of the IAAB is depicted in
Fig. 1. The design, operation and start-up procedure of
.
the IAAB can be found elsewhere [12].
.
3. Experimental Design and Analysis
In this study, OLRan and biomass concentration in
both anaerobic and aerobic compartments (MLVSSan
and MLVSSa) were chosen as the independent parameters to be optimized as they are the most critical
operating factors. OLRan was chosen as it combines
the effect of influent COD concentration and feed flow
rate while the MLVSSan and MLVSSa are essential for
efficient biological reaction and development of a
.
flocculent sludge.
The range selection of the OLRan, MLVSSan and
Table 1. Characteristics of POME
Parameter
Units
Average
Range
pH
-
-
4.18-4.7
-1
BOD
mg L
30,100 ± 10,390
19,100-46,700
COD
mg L-1
68,100 ± 7,610
65,000-72,100
mg L
-1
28,900 ± 3,070
24,200-34,300
mg L
-1
780 ± 50
700-920
TP
mg L
-1
VFA
mg L-1
TSS
TN
Oil and Grease
mg L
-1
608 ± 81
690-910
470 ± 240
300-870
10,540 ± 920
8,700-13,800
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Chan et al., Sustain. Environ. Res., 23(3), 153-170 (2013)
Biogas
Air
Gas liquid solid
separator
Deflector
Effluent
Baffle with 45°
turn out angle
Packing
Anaerobic Aerobic
tank
tank
Settling
column
Hopper
Influent
Membrane
diffuser
Fig. 1. Schematic diagram of the IAAB system.
MLVSSa was based on the results obtained from the
previous studies [1]. The study showed that the highest
anaerobic COD removal of 92.6% was achieved at
OLRan of 10.5 g COD L-1 d-1 (corresponding to OLRa
of 0.7 g COD L-1 d-1) while highest aerobic COD removal of 97.3% was achieved at 15 g COD L-1 d-1
(corresponding to OLRa of 3.5 g COD L-1 d-1). However, at OLRan of 15 g COD L-1 d-1, the methane content
and methane yield dropped from 65 to 58% and 0.24
to 0.22 L CH4 g-1 COD removed respectively. Hence, in
order to find the optimum conditions with respect to
effluent quality, methane production and process
stability, the range of 10.5 to 13.5 g COD L-1 d-1
(corresponding to hydraulic retention time (HRT) of
4.9-6.5 d) for OLRan was chosen. Besides, the previous
study [1] also shows that MLVSSan and MLVSSa of
35,000 to 42,000 mg L-1 and 16,000 to 20,000 mg L-1
yielded high COD removals of 70-92 and 86-97%
respectively. Hence, these ranges were selected for
MLVSSan and MLVSSa in the CCRD experimental plan
.
of this study.
The CCRD was established with the help of the
Design Expert 8.0.0 software for the statistical design
of experiments and data analysis. For three variables,
the recommended number of tests at the center was six
[13]. Hence the total number of experiments required
for the three independent variables (OLRan, MLVSSan
and MLVSSa) were obtained as 20 (= 2k + 2k + 6, k =
3), fourteen experiments were enhanced with six
replications to assess the pure error. The low, center
and high levels that defined the range of each variable
are designated as -1, 0 and +1, respectively. Moreover,
the methodology used (CCRD) requires that experiments outside the experimental range previously
defined should be performed to allow the prediction of
the response functions outside the cubic domain (de.
noted as ± á = 1.68).
In order to carry out a comprehensive analysis of
the anaerobic-aerobic process in IAAB, 14 dependent
parameters which are important indicators in terms of
performance and process stability were either directly
measured or calculated. These parameters were COD,
BOD and TSS removal efficiencies in both anaerobic
and aerobic compartment, methane content, methane
yield, anaerobically treated effluent pH, effluent
Volatile Fatty Acid (VFA) and Total Alkalinity (TA),
as well as final treated effluent COD, BOD and TSS
concentrations. For the sake of brevity, the COD, BOD
and TSS removal efficiencies in the anaerobic compartment were referred to anaerobic COD, BOD and
TSS removal efficiencies and the same applies to the
aerobic compartment. Besides, the anaerobic effluent
pH, effluent VFA and TA were meant for the anaero.
bically treated effluent.
In this study, the three independent variables were
coded as A, B, and C. Thus the second order polynomial of Eq. 1 could be presented as follows:
.
Yi = â0 + â1A + â2B + â3C + â11A2 + â22B2 +
â33C2 + â12AB + â13AC + â23BC
(1)
After conducting the experiments, the coefficients
of the polynomial model were calculated using Eq. 1.
The predicted response (Y) was therefore correlated to
the set of regression coefficients (â): the intercept (â0),
linear (â1, â2, â3), interaction (â12, â13, â23) and quadratic
coefficients (â11, â22, â33). Model terms were selected or
rejected based on the p-value with 95% confidence
level. The results were analyzed using analysis of
.
variance (ANOVA) by Design Expert Software.
4. Analytical Methods
.
For anaerobic process, several monitoring parameters were evaluated during the entire operation, including COD, TSS, VSS, TA and VFA concentrations of the effluent, as well as pH, temperature,
MLSSan, and MLVSSan of the anaerobic compartment,
volumetric methane production rate (rCH4) and
methane composition. Whereas for aerobic process,
the COD, TSS, VSS concentration and pH of the
treated effluent, as well as temperature, dissolved
oxygen (DO), MLSSa, and MLVSSa of the aerobic
compartment were analyzed. Analytical determinations
of BOD, COD, TSS, VSS , VFA and Sludge Volume
Index (SVI) were carried out in accordance with the
Standard Methods [14]. The composition of biogas
was measured using a biogas analyzer (GFM 416
series, UK). A titration method with sulphuric acid was
used to determine TA at pH 4.3 as CaCO3 [15]. Biogas
production was measured by using water displacement
method with a 2 L inverted water-filled graduated
cylinder for a period of 1 h, four times a day and
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Chan et al., Sustain. Environ. Res., 23(3), 153-170 (2013)
achieved by recycling a portion of thickened sludge
from the settling compartment at a returned activated
sludge (RAS) flow rate determined based on the
MLVSSRAS. For aerobic compartment, a solids retention time (SRT) of about 20 d was maintained at each
experimental condition through sludge wasting in the
settling compartment at a fixed waste activated sludge
flow rate (QWAS ) of 0.5 L d-1. The DO concentration in
the aerobic compartment was maintained constant at
2.8 mg L-1. Extra precaution was taken to ensure that
the DO level in the anaerobic compartment is close to
zero as the presence of DO will restrain methanogenic
activity and adversely affect the performance of the
anaerobic system [18]. The standard deviation of
operating conditions presented in Table 3 indicates a
good agreement between the designed and actual
.
values.
Based on the general operating conditions of the
IAAB shown in Tables 2 and 3, a three-factor and fivelevel CCRD consisting of 20 experimental runs were
performed and completed in 260 d. The experimental
results of the responses are shown in Table 4 and all
responses values are the experimental steady-state
average value for the particular day was estimated
[16].
.
RESULTS AND DISCUSSION
The general operating conditions of IAAB and
ranges of operating conditions for the optimization
study are presented in Tables 2 and 3, respectively. The
IAAB was maintained in the mesophilic temperature
range at ambient condition of 27 to 29 °C throughout
the study [17]. Although 37 °C was reported as the
optimum temperature for bacterial activity, it is not
practical for tropical countries as it will incur extra
heating cost for the application in the palm oil industry.
For anaerobic system, the recirculation ratio, R was set
at 15, which is the optimum value for achieving a high
rate of contact between the microbes and substrates to
reduce the resistance to mass transfer [1]. In order to
achieve the desired MLVSSan as shown in Table 3,
addition of anaerobic sludge into the system or sludge
wastage from the system was performed. Whereas in
the aerobic system, the adjustment of the MLVSSa was
Table 2. General operating conditions of IAAB
Process
i) Anaerobic
Parameter
Temperature
Van
Unit
Average
Range
°C
28.0 ± 0.5
27.5-29.0
23
23
L
-1
OLRan
g COD L d
-
9.5-14.5
HRTan
d
-
4.9-7.2
Qin
-1
Ld
-1
-
3.2-4.7
32,500-44,300
MLVSSan
mg L
-
pH
R
Qr
-
-
7.1-7.5
15
15
-
45.1-75.4
-
48-1375
-1
Ld
SRTan
ii) Aerobic
-1
d
-1
-1
F/M
Temperature
Va
g COD g MLVSS d
-
0.25-0.39
°C
28 ± 0.5
27.5-29.0
L
24
24
OLRa
g COD L-1 d-1
-
0.65-3.32
HRTa
D
MLVSSa
-
5.2-7.5
-1
-
14,700-21,400
-1
mg L
MLVSSRAS
mg L
-
31,500-49,000
pH
DO
QRAS
-
-
8.4-8.9
mg L
2.8 ± 0.2
2.7-3.0
-1
-
2.6-3.7
QWAS
-1
0.5
0.5
-
19-22
g COD g MLVSS d
-
0.03-0.19
-
65 ± 30
40-125
SRTa
F/M
SVI
-1
Ld
Ld
D
-1
-1
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Chan et al., Sustain. Environ. Res., 23(3), 153-170 (2013)
Table 3. Ranges of operating conditions applied for optimization study
No.
Factor
Designed value in DOE
Measured value during experiment
Standard deviation
1
OLRan
9.5
9.5
± 0.003
10.5
10.5
± 0.011
12.0
12.0
± 0.021
13.5
13.5
± 0.025
14.5
14.5
± 0.008
32,600
32,500
± 151
35,000
35,080
± 127
38,500
38,550
± 59
42,000
42,050
± 67
44,300
44,300
± 32
14,640
14,700
± 93
16,000
16,010
± 26
18,000
18,090
± 103
20,000
20,120
± 132
21,360
21,400
± 98
2
3
MLVSSan
MLVSSa
values. Attainment of the steady state conditions was
ascertained when reactor performance remained
constant for at least five consecutive measurements.
The independent variables levels are presented in
terms of the actual unit in addition to the coded levels
(in parentheses). The coded values for OLRan (A),
MLVSSan (B) and MLVSSa (C) were set at five levels,
i.e., -1.68 (-á), -1 (low level), 0 (central level), 1 (high
.
level) and 1.68 (+ á).
1. ANOVA
.
In order to quantify the curvature effects of the
independent parameters towards the responses, the
data from the experimental results shown in Table 4
were fitted to higher degree polynomial equations
which were embedded in the Design Expert Software
(i.e., two-factor interaction (2FI), quadratic (Eq. 1) and
so on) by applying the factorial regression analysis.
The response data were analyzed based on the default
setting in the software to assess the “goodness of fit”.
The statistical analysis gives several comparative
measures for the model selection, which is generally
based on the low standard deviation, low p values and
high coefficient of determination (R2) statistics [19,20].
Ignoring the aliased model, the quadratic model was
found to be the most appropriate for all the responses.
By selecting the backward elimination procedure to
automatically reduce the terms that are not significant,
the reduced quadratic models for the responses are
.
summarized in Table 5.
Based on the ANOVA results in Table 5, the
models were highly significant with low probability
(Prob > F) values (< 0.0001). It is shown that the
model in terms of independent variables is significant
at the 99% confidence level. In addition, the F-value
of the models implies that the model is significant for
all the responses. The R2 values obtained in the present
study for these response variables were higher than
0.89, indicating that the regression models explained
the treatment process well. In addition, the predicted
R2 values for all the responses were in reasonable
.
agreement with their respective adjusted R2 ones.
Adequate precision (AP) measures the signal to
noise ratio and a ratio greater than 4 is desirable. The
AP for all the responses in this study ranging from 14
to 77 indicates adequate signals for the models and the
models can be used to navigate the design space. As a
general rule, a model can be considered reasonably
reproducible if its coefficient of variance (CV) is not
greater than 10% [21,22]. The responses from Y1 to Y
12 of Table 5 exhibit low values of CV, indicating
good precision and reliability of the experimental
results. Though the CV values for the responses of
Y13 and Y14 (final treated effluent BOD and TSS)
were higher than 10%, the highest CV value achieved
was 17% for response Y14, which was still in the
acceptable range [7,23]. The prediction error sum of
squares (PRESS) is a measure of how the model fits
each point in the design and a low value of PRESS is
desirable [8]. In this case, relatively low PRESS (0 to
7,763) were found for all the responses, with the exception for the response Y8 (effluent TA) (343,900)
and response Y12 (final treated effluent COD)
(154,000). However, these values were still com.
parable to those reported by Beg et al. [21].
2. Analysis and
Performance
Comparison
on
Bioreactor
.
(mg L-1)
(g COD L-1 d-1)
(mg L-1)
C
MLVSSa
(0)12
(0)38500
(0)18000
(0)12
(0)38500
(0)18000
(-1)10.5
(1)42000
(1)20000
(1)13.5
(1)42000
(1)20000
(-1)10.5
(1)42000
(-1)16000
(0)12
(0)38500
(0)18000
(-1)10.5
(-1)35000
(-1)16000
(-1)10.5
(-1)35000
(1)20000
(0)12
(0)38500
(1.682)21364
(0)12
(1.682)44386
(0)18000
(0)12
(0)38500
(0)18000
(1)13.5
(1)42000
(-1)16000
(1.682)14.5
(0)38500
(0)18000
(1)13.5
(-1)35000
(-1)16000
(-1.682)9.5
(0)38500
(0)18000
(0)12.0
(0)38500
(0)18000
(0)12.0
(0)38500 (-1.682)14636
(1)13.5
(-1)35000
(1)20000
(0)12.0
(0)38500
(0)18000
(0)12.0
(-1.682)32614 (0)18000
B
MLVSSan
A
OLRan
86
86
87
85
87
86
95
94
86
86
86
85
76
77
91
86
86
77
86
81
88
88
89
87
895
88
95
95
88
88
88
87
78
79
93
88
88
79
88
83
91
91
92
90
92
91
97
97
91
91
91
90
82
82
96
91
91
82
91
86
63
63
64
62
64
63
65
65
63
63
63
62
58
57
66
63
63
57
63
57
0.24
0.24
0.24
0.24
0.24
0.24
0.25
0.25
0.24
0.24
0.24
0.24
0.22
0.22
0.25
0.24
0.24
0.22
0.24
0.22
7.40
7.40
7.45
7.25
7.45
7.40
7.45
7.45
7.40
7.40
7.40
7.25
7.10
7.20
7.50
7.40
7.40
7.20
7.40
7.35
85
85
65
111
65
85
65
65
85
80
85
111
155
140
45
85
85
140
85
134
4000
4000
4030
3560
4030
4000
4030
4030
4000
4000
4000
3560
2100
2500
4060
4000
4000
2500
4000
3500
95
95
89
96
90
95
89
87
94
95
95
95
98
96
88
95
93
98
95
97
98
98
93
99
94
98
93
91
97
98
98
98
100
99
91
98
96
100
98
100
98
98
94
98
95
98
94
93
97
98
98
98
100
99
92
98
95
100
98
99
Response
Modified equations in terms of coded values with significant terms
Model probability (Prob > F) Model F-value
Anaerobic COD removal
86.20 - 4.56A + 0.84B + 3.63AB - 0.62A2 - 0.62B2
< 0.0001
98.4
Anaerobic BOD removal
87.73 - 4.55A + 0.72B + 3.64AB - 0.65A2 - 0.50B2
< 0.0001
105.0
Anaerobic TSS removal
91.12 - 4.21A + 1.06B + 3.25AB - 0.55A2 - 0.72B2
< 0.0001
218.1
Methane content
63.04 - 2.45A + 1.41B + 1.50AB - 0.31A2 - 1.10B2
< 0.0001
518.3
Methane yield
0.24 - 9.332E - 03A + 5.370E - 03B + 5.714E - 03AB - 1.164E - 03A2 - 4.194E - 03B2
< 0.0001
518.3
Effluent pH
+ 7.40 - 0.12A + 0.013B + 0.013AB - 0.039A2 - 0.012B2
< 0.0001
404.2
Effluent VFA
84.60 + 31.27A - 10.90B - 7.25AB + 4.77A2 + 7.24B2
< 0.0001
149.3
+3992.09 - 534.26A + 216.81B + 265.00AB - 335.98A2 - 99.10B2
Effluent TA
< 0.0001
239.4
94.93 + 3.35A - 0.25B + 0.050C - 0.75AB + 0.63AC - 1.02A2 - 0.85C2
Aerobic COD removal
< 0.0001
26.9
98.04 + 2.85A - 0.20B + 0.038C - 0.67AB + 0.50AC - 1.06A2 - 0.78C2
Aerobic BOD removal
< 0.0001
40.3
97.65 + 2.27A - 0.19B + 0.13C - 0.65AB + 0.53C - 0.70A2 - 0.72C2
Aerobic TSS removal
< 0.0001
60.6
493.75 - 133.11A + 64.62B - 23.87C - 94.79AB - 56.66AC + 31.98A2 + 65.56C2
Final treated effluent COD
< 0.0001
22.2
55.98 - 47.51A + 21.94B - 5.69C - 11.64AB - 10.36AC + 10.21A2 + 20.11C2
Final treated effluent BOD
< 0.0001
53.2
63.70 - 22.21A + 15.97B - 8.89C - 12.12 AB - 14.43AC + 18.25C2
Final treated effluent TSS
< 0.0001
18.6
R2 Addition. R2
0.972
0.962
0.974
0.965
0.987
0.983
0.994
0.993
0.995
0.993
0.993
0.991
0.982
0.975
0.988
0.984
.0.940
0.905
0.959
0.935
0.972
0.956
0.928
0.887
0.969
0.951
0.896
0.848
Pred. R2 AP SD CV (%)
33 0.91 1.07
0.886
34 0.87 1.01
0.893
49 0.57 0.63
0.948
77 0.24 0.38
0.977
77 0.001 0.39
0.977
70 0.010 0.14
0.972
41 2.12 2.21
0.920
48 75.45 2.04
0.950
19 0.99 1.06
0.710
23 0.71 0.73
0.817
28 0.46 0.48
0.893
16 55.37 9.88
0.699
24 11.19 14.60
0.871
14 13.04 17.13
0.634
62
62
180
44
163
59
82
110
88
72
59
63
5
34
165
59
138
14
59
19
PRESS
47.8
43.9
18.7
3.3
0.000
0.006
1333.9
343900
57.4
26.7
9.92
154000
6222.1
7763
72
72
145
60
123
69
58
72
97
68
69
75
21
79
102
69
144
16
69
45
A, first variable, OLRan, B, second variable, MLVSSan, C, third variable, MLVSSa, R2, determination of coefficient, Adj. R2, adjusted R2, Pred. R2, predicted R2, AP, adequate precision, SD, standard deviation, CV, coefficient of
variation, PRESS, predicted residual error sum of squares.
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Table 5. ANOVA results for the studied responses
505
505
972
459
896
480
515
608
579
522
482
509
317
607
778
480
706
374
483
432
Effluent Effluent Aerobic
Final treated Final treated Final treated
Anaerobic Anaerobic Anaerobic Methane Methane yield
Aerobic
Aerobic
(L CH4 g-1 Effluent VFA
TA
effluent COD effluent BOD effluent TSS
COD
BOD
TSS
content
COD
BOD
TSS
pH (mg L-1) (mg L-1) removal (%) removal (%) removal (%) (mg L-1)
removal (%) removal (%) removal (%) (%)
(mg L-1)
(mg L-1)
CODrem.d-1
Responsea
All responses values are the experimental steady-state values taken as the average of 5 consecutive measurements when the deviations between the observed values were less than 5%.
a
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Run
Variable
Table 4. Experimental conditions and results based on CCRD for the study of three variables in coded and actual units
158
Chan et al., Sustain. Environ. Res., 23(3), 153-170 (2013)
Chan et al., Sustain. Environ. Res., 23(3), 153-170 (2013)
The fitted regression models in Table 5 were used
to quantitatively evaluate the effects of the three variables (OLRan (A), MLVSSan (B) and MLVSSa (C)) on the
IAAB performance based on the 14 responses (Y114). The interaction term, AB which involves both the
OLRan and MLVSSan in the anaerobic compartment was
significant for all the responses. This confirms that the
first step to a successful POME treatment is the anaerobic system as it removes most of the organic matter.
Whereas, the interaction term of AC was significant
for responses of aerobic COD (Y9), BOD (Y10) and
TSS removals (Y11), as well as final treated effluent
COD, BOD and TSS concentrations (Y12-13). This
shows the importance of aerobic process to act as a
polishing step to meet the discharge limit in the POME
treatment. It can be seen that there is no interaction
exists for MLVSSan and MLVSSa (BC) in all the
models. This confirms that the concept of compartmentalization is feasible in this combined anaerobicaerobic treatment as it can maintain strict anaerobic
and aerobic conditions and concurrently achieve high
.
treatment efficiency.
Besides, a squared term indicates a curved line
relationship between the responses and squared variables. A2 and B2 were significant for those equations
defining anaerobic COD (Y1), BOD (Y2) and TSS
removals (Y3), methane content (Y4), methane yield
(Y5), anaerobic effluent pH (Y6), VFA (Y7) and TA
(Y8). This again confirms that the anaerobic process is
important in removing most of the organic matter in
POME which leads to the successful treatment of
POME. Also, A2 and C2 were significant for responses
of aerobic COD (Y9), BOD (Y10) and TSS removals
(Y11), as well as final treated effluent COD (Y12) and
BOD concentrations (Y13). This also again confirms
that aerobic system is a polishing step to meet the
discharge limit only if A was properly considered with
.
B due the compartmentalization in IAAB.
The relative contribution of each variable to each
response can be directly measured by the respective
coefficient in the fitted model [22]. A negative sign for
the coefficients (â1s) in the fitted models for all the
responses (except Y6 and Y9 to Y11) indicates that the
level of these responses decreases with increased
levels of variable A (OLRa). In contrast, a positive sign
for the coefficients (â1s) for responses of Y6 and Y9 to
Y11 indicates that the level of these responses increases as variable A (OLRa) increases. Similar evaluation was also applied to variable B and C. A positive
effect of the interaction between the OLRa and
MLVSSan could be seen from the positive sign of the
coefficient (â12) of the AB model term in the fitted
models for responses Y1 to Y6 and Y8. This indicates
that the simultaneous increase of OLRa and MLVSSan
will give increased levels of these responses. Conversely, a negative sign of â12 in Y7 and Y9-Y14 indicates that the values of these responses decrease with
159
the simultaneous increase of OLRa and MLVSSan. This
also applies to AC interaction term. The negative sign
of the coefficient of the quadratic terms, A2 and B2 (for
Y1-Y6 and Y8) and A2 and C2 (for Y9-Y11) indicates
that OLRa, MLVSSan and MLVSSa have negative quadratic effect on these responses. These effects occur
when the levels of these variables are too high or
excessive which eventually decrease the responses,
.
indicating a failure on the IAAB's performance.
2.1. Anaerobic BOD, COD and TSS removal
efficiencies (Responses Y1 to Y3)
It can be seen that the second-order polynomial
model (Table 5) could well describe the trend of the
responses of COD, BOD and TSS removal efficiencies
(Y1 to Y3) as function of the two variables (A and B)
with high R2 (> 0.98). Besides, the values of â1 were
larger than â2 for these responses, which indicates that
OLRan is the more influential parameter than MLVSSan
in the anaerobic COD, BOD and TSS removal
.
efficiencies.
In order to gain a better understanding of the results, 2D contour and 3D response surface plots were
used to analyze the change of the response surface. In
Fig. 2, the contour and response surface were developed as a function of OLRan and MLVSSan concentration while the MLVSSa concentration was kept constant at 18,000 mg L-1, being the central level. Based
on Fig. 2, it is evident that the anaerobic COD, BOD
and TSS removal efficiencies exhibit a similar trend
with respect to the OLRan and MLVSSan concentration.
The COD, BOD and TSS removals declined significantly with increased OLRan. This indicates that OLRan
has a more profound effect on the COD, BOD and TSS
removal efficiencies as compared to MLVSSan, which
further confirms the observation of â1 > â2. Given that
OLR is directly related to substrate concentration and
HRT, the decreased COD, BOD and TSS removals at
high OLRan are mainly due to the decrease in contact
time between bacteria and substrate caused by short
HRT. Besides, the increase of the non-biodegradable
organic load in the influent had also caused substrate
inhibition to the native biomass growth and its metabolic activities [24]. This was substantiated by the
decline in the methane yield (Sec. 2.2). However, the
negative effect of OLRan on the COD, BOD and TSS
removals was reduced when the MLVSSan was increased. This was reflected by the smaller change in
the COD removal efficiencies (9%) at the upper limit
of MLVSSan as compared to that of the lower limit
.
(17%) with the increase of OLRan.
It is interesting to note that the effect of MLVSSan
on the anaerobic COD, BOD and TSS removal efficiencies was varied at different OLRan. At OLRan less
than 11.7 g COD L-1 d-1, the anaerobic COD, BOD and
TSS removal efficiencies decreased with increase in
.
160
Chan et al., Sustain. Environ. Res., 23(3), 153-170 (2013)
42000
(a)
41125
40250
B: MLVSSan
increasing MLVSSan concentration (from 35,000 to
42,000 mg L-1) as higher bacterial population (i.e.,
MLVSSan) is necessary to biodegrade the increased
OLRan efficiently. This observation as well as the
curved contour line in Fig. 2 had confirmed the positive effect of the interaction between OLRa and
MLVSSan (AB interaction term). Therefore, for each
OLRan, appropriate MLVSSan was required to eliminate
the negative effects of organic shock caused by the
high OLRan. Based on these results, the maximum
region of COD, BOD and TSS removal efficiencies
could be obtained at the lower limit of OLRan and
Anaerobic COD removal
MLVSSan. This implies that the MLVSSan of more than
35,000 mg L-1 is considered excessive at low OLRan. In
this case, the organic substances became the limiting
factor for the biodegradation process which was clearly
indicated by the low corresponding Food to Microorganism (F/M) ratio (0.25 g COD g-1 MLVSS d-1). This
had resulted in a decline of microorganisms' metabolism rate until they were in the endogenous respiration
phase with cell lysis taking place. An opposite trend
was observed at OLRan higher than 11.7 g COD L-1 d-1.
This implies that the improvement of treatment
efficiency (approximately 10% in COD removal
efficiency (Fig. 2)) at high OLRan can be achieved by
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(b)
41125
Anaerobic BOD removal
35000
B: MLVSSan
40250
39375
38500
37625
36375
35875
35000
42000
95
90
85
80
75
42000
41125
40250
39375
38500
37625
36750
35875
35000
13.5
13.2
12.9
12.6
12.3
12.0
11.7
11.4
11.1
10.8
10.5
95
90
85
80
75
42000
41125
40250
39375
38500
37625
36750
35875
35000
13.5
12.9
12.3
11.7
11.1
10.5
(c)
41125
Anaerobic TSS removal
B: MLVSSan
40250
39375
38500
37625
36375
35875
35000
10.5
11.1
11.7
12.3
A: OLRan
12.9
13.5
100
95
90
85
80
42000
41125
40250
39375
38500
37625
B: MLVSSan 36750
35875
35000
13.5
12.9
12.3
11.7
11.1
A: OLRan
10.5
Fig. 2. The contour and response surface plots of the (a) COD, (b) BOD (c) TSS removal efficiencies (%) in the
anaerobic compartment as the function of OLRan (g COD L-1 d-1) and MLVSSan concentration (mg L-1) at MLVSSa
of 18,000 mg L-1.
161
Chan et al., Sustain. Environ. Res., 23(3), 153-170 (2013)
.
MLVSSan.
2.2. Methane content and methane yield (Responses
Y4 and Y5)
The methane content and methane yield (Y4 and
Y5 respectively as shown in Table 5) were also
monitored to evaluate the IAAB performance in terms
of methanogenic activity and system stability. Their
contour and response surface plots are presented in
Fig. 3. As shown in Fig. 3a, the methane yield was
more sensitive to the changes in OLRan as compared to
the methane content of the produced biogas in the
anaerobic compartment. As the OLRan was increased
from 9.5 to 14.5 g COD L-1 d-1, a drastic decrease in the
methane yield (from 0.25 to 0.21 L CH4 (STP) g-1
CODremoved) was observed. This was because the
methanogens could not work quick enough to convert
acetic acid to methane at shorter HRT. This further
confirmed the observation of â1 > â2 in the fitted
.
models of Y4 and Y5 (Table 5).
The deterioration of methane yield at the increased
OLRan was also coincided with the decreasing anaerobic COD, BOD and TSS removal efficiencies. This
condition became worsening when the MLVSSan was
.
at its lower limit (35,000 mg L-1), implying the combination of high OLRan and low MLVSSan inhibited the
methanogetic activity. However, the negative impact
of the increased OLRan can be greatly reduced with the
increase of MLVSSan. As shown in Fig. 3b, at low
OLRan (< 11.5 g COD L-1 d-1), the methane yield increased from 0.22 to 0.25 L CH4 (STP) g-1 CODremoved
with the increase of MLVSSan from 35,000 to 39,380
mg L-1 till a maximum value and then decreased.
This indicates that biomass hold-ups in the anaerobic
compartment would promote high activities of
methanogenesis. However, when the MLVSSan concentration is excessive, substrate (POME) becomes a
limiting factor and results in low F/M ratio (< 0.3 g
COD g-1 MLVSS d-1) and thereby inhibiting the
activities of the methanogens. Besides, it has been
observed that low F/M ratios are always associated
with slow BOD removal rates [1,17]. This observation
as well as the curved contour line in Fig. 3 had confirmed the negative quadratic effect of MLVSSan (B2).
Hence, the most favorable condition for maximum
methane yield was found to be at low OLRan and high
MLVSSan which did not exceed the maximum allowable MLVSSan concentration. The methane content also
(a)
42000
Methane composition
41125
B: MLVSSan
40250
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38500
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35875
35000
66
64
62
60
58
56
42000
41125
40250
39375
38500
37625
36750
35875
35000
13.5
12.9
12.3
11.7
11.1
10.5
(b)
42000
41125
0.26
0.25
Methane yield
B: MLVSSan
40250
39375
38500
37625
36375
35875
35000
9.5
10.5
11.5
12.5
13.5
14.5
0.24
0.23
0.22
0.21
0.2
42000
41125
40250
39375
38500
37625
B: MLVSSan 36750
35875
35000
14.5
13.5
12.5
11.5
10.5
A: OLRan
9.5
A: OLRan
Fig. 3. The contour and response surface plots of (a) methane content (%) (b) methane yield (L CH4 (STP) g-1 CODremoved)
in the anaerobic compartment as the function of OLRan (g COD L-1 d-1) and MLVSSan concentration (mg L-1) at
MLVSSa of 18,000 mg L-1.
162
Chan et al., Sustain. Environ. Res., 23(3), 153-170 (2013)
experienced a similar trend. The declining methane
content can be attributed to the higher OLRs which
favors a higher growth rate of the acidogenic bacteria
over the methanogenic bacteria. This had led to the
higher rate of carbon dioxide formation thus reducing
the methane content of the biogas. These results are
compatible with other studies as reported earlier in the
literature [6,7]. Overall, the models had well demonstrated the effects of the variables on the responses
related to methane production with high R2 (> 0.99). .
2.3. Anaerobic effluent pH, TA and VFA concentration
(Responses Y6 to Y8)
.
42000
Throughout the 20 experimental conditions as
shown in Table 4, the IAAB exhibited stability as
evidenced by the low VFA/TA ratio, ranging from
0.016 to 0.074. The second-order polynomial model
(Table 5) could well describe the trend of the responses
of effluent pH, TA and VFA (Y6 to Y8) as a function
of the two variables with high R2 (> 0.98). The OLRan
had negative linear and negative quadratic effects
whilst the MLVSSan had both positive linear and negative quadratic effects on the effluent pH and TA.
Conversely, the VFA experienced an opposite trend.
The contour and response surface plots shown in Fig.
4 confirmed again the expected influence of the
(a)
Anaerobic effluent pH
41125
B: MLVSSan
40250
39375
38500
37625
36375
35875
35000
42000
Anaerobic effluent TA
40250
B: MLVSSan
7.45
7.4
7.35
7.25
7.2
42000
41125
40250
39375
38500
37625
36750
35875
35000
13.5
12.9
12.3
11.7
11.1
10.5
(b)
41125
39375
38500
37625
36375
35875
35000
42000
4500
4000
3500
3000
2500
42000
41125
40250
39375
38500
37625
36750
35875
35000
13.5
12.9
12.3
11.7
11.1
10.5
(c)
41125
Anaerobic effluent VFA
40250
B: MLVSSan
7.5
39375
38500
37625
36375
35875
35000
10.5
11.1
11.7
12.3
A: OLRan
12.9
13.5
160
140
100
80
60
40
42000
41125
40250
39375
38500
37625
B: MLVSSan 36750
35875
35000
13.5
12.9
12.3
11.7
11.1
A: OLRan
10.5
Fig. 4. The contour and response surface plots of the (a) effluent pH, (b) TA (mg L-1) and (c) VFA (mg L-1) in the
anaerobic compartment as the function of OLRan (g COD L-1 d-1) and MLVSSan concentration (mg L-1) at MLVSSa
of 18,000 mg L-1.
163
Chan et al., Sustain. Environ. Res., 23(3), 153-170 (2013)
.
variables on the aforementioned responses.
A relatively strong interaction existed between
OLRan and MLVSSan on the anaerobic effluent TA,
which was reflected by the corresponding p value (p
< 0.0001) and the curvature of the contour (Fig. 4b).
At the highest OLRan (13.5 g COD L-1 d-1) and lowest
MLVSSan (35,000 mg L-1), TA decreased to 2,500 mg
L-1 with a VFA to TA ratio of 0.07. At this stage, slight
accumulation of VFA was observed with effluent VFA
of 155 mg L-1. This had resulted in a slight reduction in
pH (7.2). This condition had a strong influence on the
biogas quality, causing a decrease in the methane con.
tent as discussed in Sec. 2.2.
20000
Aerobic COD removal
(a)
19200
C: MLVSSa
Overall, the anaerobic effluent pH remained quite
stable between 7.1 and 7.5, although the VFA concentrations increased by increasing the OLRs. This was
attributed to the stable TA levels (2,100 to 4,030 mg
L-1) which provided sufficient buffering capacity and
accommodated minor fluctuations without any major
change in pHs. The negative effect of the increase of
OLRan on the effluent pH and TA was reduced by the
increase of MLVSSan (Figs. 4a and 4b). However, at
low OLRan (10.5 g COD L-1 d-1), the increment of
MLVSSan from 35,000 to 42,000 mg L-1 had insignificant effect on the effluent pH and TA. Hence, the
highest achievable level for effluent pH and TA was
18400
17600
16800
98
96
94
92
90
88
13.5
20000
12.9
19200
12.3
18400
11.7
17600
11.1
16800
16000
16000
10.5
(b)
20000
Aerobic BOD removal
102
C: MLVSSa
19200
18400
17600
16800
100
98
96
94
92
13.5
20000
12.9
19200
12.3
18400
11.7
17600
11.1
16800
16000
16000
10.5
(c)
20000
100
Aerobic TSS removal
C: MLVSSa
19200
18400
17600
16800
98
96
94
92
90
13.5
20000
12.9
19200
16000
12.3
18400
10.5
11.1
11.7
12.3
A: OLRan
12.9
13.5
11.7
17600
C: MLVSSa
11.1
16800
16000
10.5
A: OLRan
Fig. 5. The contour and response surface plots of the (a) COD, (b) BOD and (c) TSS removal efficiencies (%) in the
aerobic compartment as the function of OLRan (g COD L-1 d-1) and MLVSSa concentration (mg L-1) at MLVSSan
concentration of 38,500 mg L-1.
164
Chan et al., Sustain. Environ. Res., 23(3), 153-170 (2013)
predicted to be in the region where OLRan and
MLVSSan were at its moderate level.
.
2.4. Aerobic COD, BOD and TSS removal efficiencies
(Responses Y9 to Y11)
The variables of OLRan and MLVSSan have indirect
influences on the aerobic COD, BOD and TSS removal efficiencies. This is because the aerobic BOD,
COD and TSS removal efficiencies are depending on
the OLRa, while OLRa is depending on the performance of anaerobic compartment which is also governed by OLRan and MLVSSan. Hence, A (OLRan), B
.
(a)
42000
Aerobic COD removal
41125
40250
B: MLVSSan
(MLVSSan) , and C (MLVSSa) appeared as the significant terms in the models for aerobic COD, BOD and
TSS removal efficiencies (Y9-Y11) as shown in Table
5. The second-order polynomial model could well
describe the trend of aerobic COD, BOD and TSS
removal efficiencies as a function of the three variables
.
with high R2 (> 0.94).
The effect of OLRan and MLVSSa on the aerobic
BOD, COD and TSS removal efficiencies at central
level of MLVSSan concentration (38,500 mg L-1) is
shown as contours and 3D response surface plots in
Fig. 5. Besides, the effect of OLRan and MLVSSan on
39375
38500
37625
36375
35875
35000
42000
42000
41125
40250
39375
38500
37625
36750
35875
35000
13.5
12.9
12.3
11.7
11.1
10.5
(b)
Aerobic BOD removal
41125
40250
B: MLVSSan
100
98
96
94
92
90
88
86
39375
38500
37625
36375
35875
35000
102
100
98
96
94
92
42000
41125
40250
39375
38500
37625
36750
35875
35000
13.5
12.9
12.3
11.7
11.1
10.5
42000
(c)
41125
100
Aerobic TSS removal
B: MLVSSan
40250
39375
38500
37625
36375
35875
35000
9.5
10.5
11.5
12.5
A: OLR an
13.5
14.5
98
96
94
92
90
13.5
42000
41125
12.9
40250
39375
12.3
38500
11.7
37625
36750
11.1
35875
10.5
B: MLVSSan
A: OLR an
35000
Fig. 6. The contour and response surface plots of the (a) COD, (b) BOD and (c) TSS removal efficiencies in the aerobic
compartment as the function of OLRan (g COD L-1 d-1) and MLVSSan concentration (mg L-1) at MLVSSa
concentration of 18,000 mg L-1.
Chan et al., Sustain. Environ. Res., 23(3), 153-170 (2013)
the aerobic BOD, COD and TSS removal efficiencies
at central level of MLVSSa concentration (18,000 mg
L-1) are presented in Fig. 6. The variation of OLRan and
MLVSSan ranging from 10.5 to 13.5 g COD L-1 d-1 and
35,000 to 42,000 mg L-1 respectively in this study had
resulted in OLRa ranging from 0.65 to 3.32 g COD L-1
.
d-1 (Table 2).
Similar to the anaerobic COD, BOD and TSS removal efficiencies, OLRan is the most influential factor
on the aerobic BOD, COD and TSS removal efficiencies. This was also reflected in their regression coefficients where â1 > â2 and â3 for these responses. The
increment of OLRan from 10.5 to 13.5 g COD L-1 d-1 at
MLVSSa of 16,000 mg L-1 has resulted in the increase
of aerobic COD, BOD and TSS removal efficiencies
from 90 to 96%, 94 to 99%, and 94 to 98% respectively. These percentages were further enhanced to
97, > 99 and 99% at the same OLRan when the MLVSSa
was increased to 20,000 mg L-1. These results confirmed again the expected positive linear effect of
OLRan and MLVSSa (A and C) on the aerobic BOD,
COD and TSS removal efficiencies (Table 5). However, increasing MLVSSa beyond 19,200 mg L-1 at the
upper limit of OLRan (> 12.3 g COD L-1 d-1) resulted in
decline in the COD, BOD and TSS removals. This is
due to the low F/M ratio (< 0.05 g COD g-1 MLVSS d-1)
at the excessive MLVSSa concentration. Besides, this
observation was reflected in the parabolic shape of the
plots in Fig. 5 which further confirmed the negative
quadratic effect exerted by MLVSSa (C2) as shown in
.
Y9 to Y11.
As shown in Fig. 5, the percentages of COD, BOD
and TSS removal increased with the simultaneous increase of MLVSSa and OLRan. This further confirmed
the positive interaction effect between MLVSSa and
OLRan (AC interaction term) as shown in Y9 and Y10
(Table 5). This is due to the fact that high OLRan can
enhance the growth of aerobic culture, while high
MLVSSa can lead to efficient and complete aerobic
.
biodegradation of organic matter.
As shown in the Fig. 6, the aerobic BOD, COD
and TSS removal efficiencies were increased with the
increase of MLVSSan at OLRan of less than 11.7 g COD
L-1 d-1. However, the aerobic BOD, COD and TSS removal efficiencies exhibited a decreasing trend with
the increase of MLVSSan when the OLRan was at its
upper limit (> 11.7 g COD L-1 d-1). This observation
was reflected in the negative sign of the coefficient of
the AB interaction term in Y9-Y11. This is reasonable
as the combination of high OLRan and MLVSSan would
lead to high anaerobic COD, BOD and TSS removal
efficiencies and subsequently to a low OLRa, which is
not favorable for aerobic biodegradation and hence it
led to a low aerobic COD, BOD and TSS removal
efficiencies. Thus it is found that the maximum aerobic
BOD, COD and TSS removal efficiencies fall in the
165
region where OLRan and MLVSSa are in their upper
.
limit whilst MLVSSan is at its moderate level.
2.5. Final treated effluent COD, BOD and TSS
concentrations (Responses Y6 to Y8)
The final treated effluent COD, BOD and TSS
concentrations are the key parameters in many discharge standards for wastewater treatment. In order to
ensure the compliance of the treated effluent to the
Malaysian DoE (Department of Environment) discharge standards, the COD, BOD and TSS concentrations of final treated effluent in this study were measured as the response to the three variables. For the
influent COD, BOD and TSS concentrations of 65,000
to 72,100, 29,600 to 31,600 and 11,000 to 11,800 mg
L-1, the treated effluent COD, BOD and SS concentrations were in the range of 317 to 972, 5 to 176 and 21
.
to 145 mg L-1, respectively.
Figure 7 presents the effects of OLRan and MLVSSa
on the treated effluent COD, BOD and TSS concentrations while MLVSSan was kept at the central level
(38,500 mg L-1). As anticipated, treated effluent COD,
BOD and TSS concentrations decreased as OLRan and
MLVSSa increased. This observation was also reflected
in the negative sign of regression coefficients (â1 and
â3) of A and C linear terms in equations Y12 to Y14.
All the contour curves have a considerable curvature,
implying that the interaction between OLRan and
MLVSSa is significant. The statistical examination of
the coefficients of the models shows that the interaction term (AC) was significant with p value < 0.005.
It was found that the treated effluent COD, BOD and
TSS concentrations were decreased with a simultaneous increase in OLRan and MLVSSa. This agrees
with the negative sign of the coefficient of the AC
in the equation Y12 to Y14 (Table 5). At high
MLVSSa, a more pronounced decreasing effect on the
treated effluent COD, BOD and TSS concentrations
was exerted by the increase of OLRan. This indicates
high MLVSSa concentration is essential to sustain a
high bacterial activity in the aerobic compartment.
Hence, the minimum region of treated effluent COD,
BOD and TSS concentrations was positioned at the
.
upper limit of OLRan and MLVSSa.
.
3. Optimization Analysis
.
There are several important aspects to be considered in the optimization of the anaerobic-aerobic
process. Firstly, operating the IAAB at low OLRan is
perceived as extravagance of capacity and investment
of treatment facility, which is not desirable in term of
economy. Conversely, high OLRan will result in a
smaller bioreactor volume at the expense of poor
anaerobic effluent quality. Second point to be considered is that if high extent of organic matter removal is
accomplished in the anaerobic compartment, inade-
166
Chan et al., Sustain. Environ. Res., 23(3), 153-170 (2013)
quate COD or other nutrients left in the effluent may
not favor the performance of aerobes in the following
aerobic compartment. Hence in the optimization, it is
crucial to ensure sufficient but not excessive COD left
in the anaerobic effluent for effective functioning of
the aerobic compartment. This concurs with the observed results which show that the effects of anaerobic
COD removal efficiency and aerobic COD removal
efficiency are inversely related. To achieve this, the
anaerobic COD removals should be maintained in the
range of 77 to 87%, which require the OLRan of more
than 11.7 g COD L-1 d-1 (Fig. 2a). However, high OLRan
will also inhibit the methanogenesis with a subsequent
20000
Final treated effluent COD
(a)
19200
C: MLVSSa
reduction in the methane production. On the other
hand, maintaining a low MLVSS concentration fails to
sustain a high bioactivity in the bioreactor, while
excessive MLVSS concentration will result in low
COD removal, high aeration requirement, long sludge
settling time and high concentration of SS in the
effluent. In addition, process stability of anaerobic
process as indicated by pH, VFA and TA is also an
important aspect worth considering. It should be
monitored closely to avoid excessive sludge washout
and acidification in the anaerobic compartment. As the
aerobic compartment accepts an effluent directly from
the anaerobic compartment, a significant amount of
18400
17600
16800
1200
1000
800
600
400
200
14.5
20000
13.5
19200
12.5
18400
11.5
17600
10.5
16800
16000
16000
20000
Final treated effluent BOD
(b)
19200
C: MLVSSa
9.5
18400
17600
16800
100
80
60
40
20
0
14.5
20000
13.5
19200
12.5
18400
11.5
17600
10.5
16800
16000
20000
16000
9.5
(c)
Final treated effluent TSS
C: MLVSSa
19200
18400
17600
16800
16000
9.5
10.5
11.5
12.5
13.5
14.5
140
120
100
80
60
40
20
0
20000
19200
18400
17600
16800
C: MLVSSa
16000
14.5
13.5
12.5
11.5
10.5
9.5
A: OLR an
A: OLR an
Fig. 7. The contour and response surface plots of the effluent (a) COD, (b) BOD (c) TSS concentrations (mg L-1) in the
aerobic compartment as the function of OLRan (g COD L-1 d-1) and MLVSSa concentration (mg L-1) at MLVSSan
concentration of 38,500 mg L-1.
167
Chan et al., Sustain. Environ. Res., 23(3), 153-170 (2013)
obligate anaerobes as well as facultative microorganisms will enter the aerobic compartment when the
anaerobic compartment is not in a stable condition,
i.e., low pH, high VFA and low TA. These anaerobes
are unable to adapt quickly to the aerobic conditions
and this may affect the cell population in the aerobic
compartment and lead to a mixed microbial population
of low oxygen utilization and biological activity. The
anaerobic cells will not contribute to COD removal in
the aerobic compartment, but increase the TSS con.
centration or the turbidity in the final effluent.
Thus, it is of great significance to obtain appropriate levels of OLRa, MLVSSan and MLVSSa to increase
the organic matter removals with compliance to the
discharge standards as well as the methane gas production without causing instability of the IAAB. The
optimum condition for POME biodegradation was
determined using the numerical optimization method
in the Design Expert Software Version 8.0.0 (STATEASE, Minneapolis, MN). The desired goal for each
variable (OLRan, MLVSSan, and MLVSSa) in this study
was set as “within the range”. The optimum condition
was identified based on eight critical responses
(aerobic COD, BOD and TSS removal efficiencies,
pH, TA, methane content, methane yield, and treated
effluent BOD concentration), and the desired goals for
the responses were summarized in Table 6. These responses were chosen as they were considered the most
important parameters for reliable representation and
optimization of anaerobic-aerobic treatment process.
Aerobic COD, BOD and TSS removals represent the
substrate metabolized in the aerobic digestion, which
should be more than 95% to meet the discharge limit
according to the results of the previous work [25].
Besides, anaerobic effluent pH represents a critical
environmental parameter for microorganisms (methanogens in particular) and a pH value of higher than 7.0
is required [26]. TA represents buffering capacity to
support methanogenic reactions from inhibition impacts of acidogenic reactions and TA of more than
2,000 mg L-1 is desired in the anaerobic digestion [27].
Methane content and methane yield represent methanogenic activity and they should be more than 60% and
0.24 L CH4 g-1 CODremoved, respectively. Final treated
effluent BOD represents the key parameter to justify
the compliance of the current treatment with the DoE
discharge standard and hence, its value should be
below 100 mg L-1. On the other hand, the anaerobic
COD, BOD and TSS removal efficiencies were set as
'none' as their desired goal. This is due to the maximization of anaerobic COD, BOD and TSS removal
efficiencies that will result in a low OLRa, which is not
favorable for maximum aerobic biodegradation as
mentioned above. The importance of each goal was set
.
at 3 pluses (+++).
The desirability function value was found as 0.78
for this optimum condition. According to the model,
the optimized conditions occurred at OLRan of 12.8 g
COD L-1 d-1, MLVSSan of 40,200 mg L-1, and MLVSSa
of 18,500 mg L-1. This will result in an OLRa of 1.84 g
Table 6. The optimization criteria for the chosen responses
Variables/Responses
A: OLRan
B: MLVSSan
Goals
is in range
is in range
Constraints
10.50-13.5
35,000-42,000
Importance
Unit
-1
-1
g COD L d
3
-1
3
-1
mg L
C: MLVSSa
is in range
16,000-20,000
mg L
3
Anaerobic COD removal
None
-
%
-
Anaerobic BOD removal
None
-
%
-
Anaerobic TSS removal
None
-
%
-
Aerobic COD removal
Maximize
> 95
%
3
Aerobic BOD removal
Maximize
> 95
%
3
Aerobic TSS removal
Maximize
> 95
%
3
Anaerobic effluent pH
Maximize
> 7.0
-
Anaerobic effluent TA
Anaerobic effluent VFA
Methane content
Methane yield
Treated effluent COD
Treated effluent BOD
Treated effluent BOD
Maximize
None
Maximize
Maximize
None
Minimize
None
3
-1
> 2,000
mg L
3
-
mg L-1
-
> 60
%
3
> 0.24
L CH4 g-1 CODremoved
< 100
-
-1
mg L
3
-
-1
3
-1
-
mg L
mg L
168
Chan et al., Sustain. Environ. Res., 23(3), 153-170 (2013)
COD L-1 d-1 and 96, 99 and 98% removal efficiencies
of aerobic COD, BOD and TSS respectively (Table 7).
The predicted final treated effluent BOD concentration
was well below 100 mg L-1, which was at 40 mg L-1.
Besides, the methane content, methane yield, effluent
pH and TA were estimated to be 63%, 0.24 L CH4 g-1
.
CODremoved, 7.33 and 3,770 mg L-1 respectively.
In order to validate the optimum combination of
the variables, confirmatory experiments were carried
out under the set of the optimized variables for a period
of two months. The accuracy of the predicted performance at the optimum condition was checked by
calculating the error and standard deviation for each
response. Table 7 presents the results of the experiments conducted within the optimum conditions. It is
worth noting that these optimum conditions were able
to achieve the desired performance based on the constraints shown in Table 6. The percentage error differences between the experimental and predicted values
as shown in Table 7 were in the range of 0.1 to 9%,
implying that these experimental findings were in
close agreement with the model prediction. As a result,
the model developed was considered to be accurate
.
and reliable.
It is worth noting that the IAAB system achieves
higher overall COD, BOD and TSS removal efficiencies of > 99% at higher OLR of 12.8 g COD L-1 d-1
as compared to Upflow Anaerobic Sludge Bed
(UASB) (90% at OLR of 5.8 g VS L-1 d-1) [28] and
UASFF (93% at OLR of 9.2 g COD L-1 d-1) [7,29]
bioreactors systems. Furthermore, this work demonstrates great improvement on the final treated quality
as compared to the previous study [12], with further
improved reduction of 59% on the treated effluent
BOD concentration (from 90 mg L-1 (previous study)
to 37 mg L-1) being achieved at a higher OLRan (from
10.5 to 12.8 g COD L-1 d-1) (Table 7).
.
CONCLUSIONS
The application of RSM in conjunction with
CCRD to model and optimize the performance of
IAAB was discussed. CCRD was used to design an
experimental program for modeling the effects of
OLR, MLVSS concentration in both anaerobic and
aerobic compartments on the performance of IAAB.
Predicted values from the model equations were found
to be in good agreement with observed values (R2 >
0.81). The results show that the OLR and MLVSS
concentration have significant effects on the IAAB
performance. Under specified constraints driven by
high treatment performance with compliance to the
discharge standards, good stability and high methane
yield, the combination of high OLRan (12.8 g COD L-1
d-1), high MLVSSan (40,200 mg L-1) and moderate
MLVSSa (18,500 mg L-1) concentration gives the
optimum conditions. At this optimum condition, the
IAAB achieved high aerobic COD, BOD and TSS
removal efficiencies of 96, 98, and 99% respectively.
The treated BOD (37 mg L-1) and TSS concentration
(52 mg L-1) were well below the discharge standards.
Besides, good stability was observed in the IAAB with
anaerobic effluent of pH of 7.35 and high TA of 3,900
mg L-1. More importantly, high methane yield of 0.242
Table 7. Verification of experiment at optimum condition
Model response
with CI 95%
Standard
deviation
Error
(%)
85
0.9
0.10
Unoptimized
experimental
values [1]
93
86
86
0.8
0.38
96
%
90
90
0.6
0.08
93
%
Response
Unit
Anaerobic COD removal
%
Optimized
experimental
values
85
Anaerobic BOD removal
%
Anaerobic TSS removal
63
63
0.2
0.84
65
Methane yield
L CH4 g CODremoved
0.24
0.24
0.00
0.84
0.24
Anaerobic effluent pH
-
0.23
7.4
Methane content
Anaerobic effluent VFA
-1
7.35
7.33
-1
101
97
4
4.25
61
-1
mg L
Anaerobic effluent TA
mg L
3900
3770
75
3.48
3010
Aerobic COD removal
%
96
96
1
0.14
94
Aerobic BOD removal
%
99
99
0.7
0.13
95
Aerobic TSS removal
%
98
98
0.5
0.11
949
Final treated effluent COD
mg L-1
417
431
55
3.25
350
37
40
11
8.72
90
52
54
13
2.75
75
Final treated effluent BOD
Final treated effluent TSS
-1
mg L
-1
mg L
Chan et al., Sustain. Environ. Res., 23(3), 153-170 (2013)
L CH4 g-1 CODremoved was achieved. The experimental
data fitted well with the model predicted values with
less than 5% error. This study demonstrates that RSM
and CCRD can be successfully applied to model and
optimize IAAB with the least number of experiments.
This investigation is important for future development
on applications of present technology at larger scale as
well as providing beneficial information to the palm
oil milling industry which adopted anaerobic-aerobic
processes as their POME treatment.
.
ACKNOWLEDGEMENT
The authors gratefully acknowledge the financial
support from The University of Nottingham Malaysia
and Ministry of Science, Technology and Innovation
(MOSTI) Fund.
.
8.
9.
10.
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Discussions of this paper may appear in the discussion section of a future issue. All discussions should
be submitted to the Editor-in-Chief within six months
of publication.
.
Manuscript Received: July 12, 2012
Revision Received: December 23, 2012
and Accepted: January 28, 2013