domestic wastewater treatment using batch-fed constructed wetland and predictive model development...
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Process Biochemistry 43 (2008) 297–305
Domestic wastewater treatment using batch-fed constructed wetland and
predictive model development for NH3-N removal
S.Y. Chan a,*, Y.F. Tsang a, L.H. Cui b, H. Chua a
a Civil & Structural Engineering Department, The Hong Kong Polytechnic University, Hong Kong SAR, Chinab Department of Environment and Resources, The South China Agricultural University, Guangzhou, China
Received 3 September 2007; received in revised form 28 November 2007; accepted 14 December 2007
Abstract
In this study, the performance of a pilot-scale batch-fed constructed wetland in treating domestic wastewater from small community was tested.
The principal of the system capitalizes on the pollutant removal mechanisms of the soil–plant–microbial interactions of constructed wetlands, and
the system operation was integrated with the rhythmical movement of wastewater and air that similar to the operation of conventional sequencing
batch reactor. Based on the hydraulic loading of 0.91 m3/m2/day and the daily maximum contact time of 18 h, the system could achieve around
60% removal efficiency for carbonaceous matters. The removals of ammonia nitrogen and phosphorus were about 50 and 40%, respectively, while
the removal of total suspended solids was approaching 80%. Mathematical models were developed to describe ammonia nitrogen degradation in
the batch-fed constructed wetland. Three analytical approaches including multivariate regression, first-order kinetics and mass balance analysis
were done. Prediction model was formulated to predict the system removal efficiency of ammonia nitrogen.
# 2007 Elsevier Ltd. All rights reserved.
Keywords: Domestic wastewater; Batch-fed; Constructed wetland; Ammonia nitrogen; Predictive model; Coal slag; Cyperus alternifolius
1. Introduction
Domestic wastewater is mainly composed of organic
matters, nutrients and suspended solid. In the treatment process
of domestic wastewater, the removals of organic matters and
nutrients are critical to judge the performance of the treatment
process. The type of wastewater treatment systems being
utilized is a matter of consideration based on the targeted
pollutants to be eliminated, the volume of domestic wastewater
and hence the size of the served population, the local financial
budget and the geographical characteristics [1]. Most waste-
water treatment systems in rural areas with low-dense
population are characterized by low capital investment and
operating cost. Common domestic wastewater treatment
methods in rural areas capitalize on microbial degradation.
They include waste stabilization pond, wastewater storage and
treatment reservoir, upflow anaerobic sludge blanket reactor,
biofilter, aerated lagoon, oxidation ditch and constructed
wetland [2]. However, these treatment systems are limited to
* Corresponding author. Tel.: +852 27666027; fax: +852 23346389.
E-mail address: [email protected] (S.Y. Chan).
1359-5113/$ – see front matter # 2007 Elsevier Ltd. All rights reserved.
doi:10.1016/j.procbio.2007.12.009
application in rural areas with small wastewater flows due to
their large land requirements and relatively less promising
pollutant treatment efficiencies.
In this study, the principle of the treatment system
capitalized on the pollutant removal mechanisms of the soil–
plant–microbial interactions of constructed wetlands. Simulat-
ing a wetland ecosystem, the treatment system can make use of
the assimilation capacity of soil and aquatic plants to remove
both pollutants and nutrients without additional energy demand
[3]. To have prolonged and satisfying pollutant removal
efficiencies, no matter constructed wetlands or other biological
filters need to be rested periodically to allow breakdown of
accumulated organic matter. It is because resting of beds allows
aeration and reduces the likelihood of anoxia. Drying of beds is
occasionally required to enhance performance [4,5]. So the
process design of the studied system has integrated the resting
of bed in a single bed as a time sequence. Different to the
conventional continuous flow bed, the system is a batch-fed
constructed wetland integrated with the rhythmical movement
of wastewater and air like that of a sequencing batch reactor [6].
The operating conditions, such as contact time, temperature and
loading of wastewater to the system, were studied specifically
for the removal of carbon, nitrogen and phosphorus that are
Table 1
Durations of different operating stages
Phase Duration (h)
Fill 4 4 4 4 4
React 18 12 6 3 0
Draw 2 2 2 2 2
Idle 0 6 12 15 18
Total: 24
S.Y. Chan et al. / Process Biochemistry 43 (2008) 297–305298
abundant in domestic wastewater. Predictive models using
multivariate regression, first-order kinetics and mass balance
approaches were also developed for ammonia nitrogen
removal.
2. Materials and methods
2.1. System description
The pilot-scale experiment was carried out onsite in the South China
Agricultural University (SCAU), Guangzhou, People’s Republic of China. A
portion of domestic wastewater from local sewer serving 800 households in the
campus was drained to the batch-fed constructed wetland as influent during the
operation period. Three identical tanks were constructed in parallel near a pond
in the campus of SCAU. Each system was made of concrete with the dimensions
of 5.0 m in length, 3.0 m in width and 1.8 m in depth. Means of experimental
data were calculated from the data from these three identical tanks. Coal slag,
which is the waste residue from burning coal for electricity generation in
Guangdong areas [7], was filled up in the system as the supporting medium. The
uses of this industrial waste or by-product in wastewater treatment served the
purposes of operating economically viable industrial and wastewater treatment
processes for protection of the environment and public health. The porosity and
the density of coal slag were 0.5 � 0.17 and 1.818 � 0.425 kg/L, respectively.
50–100 mm stones were placed around the influent distributor and the effluent
collector pipes to reduce the potential of clogging. The empty bed volume of
each system is 27 m3 with an effective volume of 13.6 m3. The wastewater was
drained into the inlet zone, and then passed through the perforated partition into
the bed matrix. The outlet valves of the systems were at the bottom of the
systems on the other side (Fig. 1). Plants were introduced into the coal slag bed
to imitate the main components of constructed wetland. Clumps of whole plants
of Cyperus alternifolius were planted into the systems with a density of 3–
4 plant/m2. This wetland plant was selected due to its long root system which
can be up to 2 m. The extensive root system could enhance dissolved oxygen in
root zone of planted system and facilitate pollutant degradation process.
2.2. System operations
Different from conventional constructed wetland, the system studied was
a batch reactor. The operating cycle was similar to conventional sequencing
batch reactor, which involves ‘‘fill’’ phase, ‘‘react’’ phase, ‘‘draw’’ phase and
‘‘idle’’ phase [8], but without ‘‘aerate’’ phase. During the operation, waste-
water was pumped into coal slag bed in the ‘‘fill’’ phase and retained in the bed
in the ‘‘react’’ phase. Pollutant removal processes took place in the bed matrix
of such attached-growth system, main removal mechanisms including phy-
sical adsorption and biochemical degradations occurred on the coal slag
surface and the biofilm established on it, as well as certain level of plant
uptake. The batch systems were operated with different durations of ‘‘react’’
Fig. 1. Side view of the batch-fed constructed wetland.
phase (0, 3, 6, 12 and 18 h). Table 1 shows the durations of different phases
accordingly. The systems were operated with a cycle of 24 h from May 2005
to March 2006. The resulting hydraulic loading was at a rate of 0.91 m3/m2/
day. Seasonal variation was considered as the pilot-scale experiment was
carried out in outdoor. In this experiment, the months from May 05 to
September 05 having mean temperature from 22.7 to 25.3 8C were classified
as warm period while from November 05 to March 06 having mean tem-
perature from 9.8 to 19.1 8C were classified as cool period. The five contact
times (‘‘react’’ phase) were tested for their effects on pollutant removal in
both warm and cool periods. Every contact time was tested for a 2-month
period with 1 month in warm period and 1 month in cool period.
2.3. Analytical methods
Samplings of influent and effluent of the systems were done on every run.
Mean of data from three identical systems was calculated for each run.
Analyses of COD, BOD5, NH3-N, TP and TSS were performed following
the Standard Methods [9]. Removal efficiencies were obtained by calculating
the percentages of pollutant removal from the influent concentrations. Tem-
peratures of wastewater were recorded onsite. Dissolved oxygen (D.O.) levels
at different depths of the pilot systems were measured using a portable D.O.
meter (YSI Model no. 51). Statistical and mathematical software including
SPSS 10.0, Datafit 8.0 Okadale and Igor Pro 5.03 were used for model
development and performance predictions. The surface characteristic of coal
slag was observed under Philips XL 30 Esem-FEG Environmental Scanning
Electron Microscope (SEM).
3. Results and discussions
3.1. Overall performance
Table 2 shows the influent characteristics of the raw sewage
entering the systems. According to the classification of Metcalf
and Eddy [10], with the mean concentration of ammonia
nitrogen of 32.71 � 8.37 mg/L, the wastewater was regarded as
having a medium strength of nitrogen content. Before system
operation, approximately 4–5 months were spent in the start-up
period to allow extensive plant root and biofilm development on
Table 2
Means of Influent and effluent characteristics over the operation period
Parameter Mean Standard deviation
pH 7.21 0.27
Sewage temperature (8C) 20.47 4.16
BOD5 (mg/L) 27.59 12.98
COD (mg/L) 80.82 31.52
NH3-N (mg/L) 32.71 8.37
TKN (mg/L) 35.56 9.69
Nitrate (mg/L) 4.85 4.56
TP (mg/L) 2.61 0.99
TSS (mg/L) 23.26 8.73
D.O. (mg/L) 1.40 1.04
Fig. 2. Biofilm establishment on coal slag surface.
Fig. 4. Effects of contact time on different pollutant removal efficiencies in the
pilot-scale system.
Table 3
p-Values of different pollutant removal efficiencies in warm and cool periods
Contact time (h)
0 3 6 12 18
NH3-N 0.023 0.040 0.048 0.000 0.209
BOD5 0.917 0.317 0.034 0.005 0.994
COD 0.290 0.337 0.710 0.219 0.737
TP 0.688 0.372 0.137 0.771 0.248
TSS 0.205 0.458 0.067 0.775 0.758
S.Y. Chan et al. / Process Biochemistry 43 (2008) 297–305 299
the coal slag in the systems. Wastewater was fed into the
system intermittently during the start-up period. The establish-
ment of biofilm on the surface of the coal slag was confirmed by
SEM (Fig. 2) and it reflected the accomplishment of the start-
up period after around 4 months [11]. Steady ammonia
nitrogen concentration in the effluent was also achieved after
around 4 months of start-up period (Fig. 3), the constant
removal showed the existence of regenerative biodegradation
function of the biofilm on the coal slag surface. Based on the
hydraulic loading of 0.91 m3/m2/day and the daily maximum
contact time of 18 h, the system could achieve around 60%
removal efficiency for BOD5. The removals of ammonia
nitrogen and phosphorus were about 50 and 40%, respectively,
while the removal of total suspended solids was approaching
80% (Fig. 4). C. alternifolius has showed satisfactory growth
throughout the study period. The plants have been harvested
once during the middle of the study period. Symbiotic
relationship between the plants and the microorganisms in the
rhizosphere was existed to enhance pollutant degradation [12],
but in-depth investigation of it was out of the scope of this
Fig. 3. Trend of ammonia nitrogen concentration in influent and effluent during
the start-up period.
study. No clogging of substrate was observed around 1-year
operation due to the relatively low concentration of TSS in
the influent that has passed the sedimentation tank as the
pre-treatment.
Removals of COD, BOD5, TP and TSS were not
significantly different in warm and cool periods (ANOVA, p-
values >0.05, n = 100), but the removal efficiencies of NH3-N
were significantly different between warm and cool periods
regardless of the contact times (ANOVA, p-values <0.05,
n = 100) (Bold values in Table 3). Temperature has determinant
effect on the degradation of ammonia nitrogen in the batch-fed
constructed wetland.
3.2. Effects of sequencing batch mode
The availability of oxygen in the filter bed matrix is often
assumed to be the key factor restricting the removal rates of
BOD5, COD and NH3-N [13]. Different pollutant removal
processes are favoured in specific ranges of dissolved oxygen
concentrations. Carbonaceous BOD removal is favoured with
D.O. level of 1–2 mg/L, nitrification is facilitated with D.O.
level of 2–3 mg/L while denitrification is facilitated with D.O.
level <0.5 mg/L. And nitrification took place in all locations
where D.O. levels were higher than the critical threshold of
0.5 mg/L [14]. The average D.O. concentration in the batch-fed
constructed wetland was 2.10 � 1.18 mg/L. With the D.O.
usually over 0.5 mg/L, nitrification was favoured to convert
ammonia nitrogen into nitrate in the batch-fed biofilm reactor
by microbial actions.
S.Y. Chan et al. / Process Biochemistry 43 (2008) 297–305300
The batch-fed constructed wetland was a gravel-based
system integrated with the periodic feeding like that of a
sequencing batch reactor. The air drawn into sequencing batch
beds during the ‘‘draw’’ phase was used as an oxygen source to
biodegrade the pollutants. The oxygen transport and consump-
tion rate in the beds could be greatly improved by the
rhythmical water and air movement in the bed matrix [15].
Moreover, during the ‘‘idle’’ phase, resting of beds allowed air
to get into the bed for aeration and reduce the likelihood of
anoxia. Drying of beds is occasionally required to enhance
performance. These alternating phases of ‘‘feed’’ and ‘‘rest’’
are fundamental to control the growth of the attached biomass
on the adsorbing medium, to maintain aerobic conditions
within the filter bed and to mineralize the organic deposits.
Besides the removal of nitrogen, Miller and Wolf [16] have
shown that P adsorption capacity of vertical filtration bed can be
regenerated if the system is allowed to rest and dry. In other
words, intermittent loadings are feasible to enhance N and P
removals.
3.3. Model development of ammonia nitrogen removal
Fig. 5 shows the ammonia nitrogen removal efficiency with
different contact times, it reflected the extent of nitrification
process achieved in the batch-fed constructed wetland with
regard to the duration of contact time. Ammonia nitrogen
removals were also significantly different in warm and cool
periods of the study (Table 3). In order to find out the optimal
operating conditions of the current system design, mathema-
tical models were developed to predict the precise ammonia
nitrogen removal efficiency with various contact time under
various temperature ranges. Prediction models were developed
based on ammonia nitrogen removal only because ammonia
nitrogen is one of the most dominant pollutants in domestic
wastewater. No equation for phosphorus mass balance was done
because sources and sinks of phosphorus is mainly dependent
on adsorption and desorption. Three types of modelling
including multivariate regression, first-order kinetics and mass
balance were developed, so as to understand the underlying
removal mechanism of ammonia nitrogen through different
Fig. 5. Ammonia nitrogen removal efficiency with different contact times in
warm and cool periods.
approach. Table 4 lists the state variables and their descriptions
in the models.
3.3.1. Multivariate regression model
Since the performance of the batch-fed constructed wetland
was influenced by many factors, such as climate, hydraulic
condition, vegetation, water quality, oxygen level, microbiol-
ogy and influent concentration. Multivariate regression is
attempted for the purpose of finding the latent factors that may
affect and control the system operation and the relationships
between the removals of pollutants and the controlling factors
can be established. While the elimination of ammonia nitrogen
is mainly dependent on nitrification, which is governed by
growth of chemoautotrophic nitrifying bacteria, pH, tempera-
ture, concentration of ammonia nitrogen in the influent and
dissolved oxygen level. BOD5 is also a governing factor of
nitrification because the availability of oxygen within the
system is related to BOD5 concentration, the heterotrophic
bacteria will outgrow the nitrifiers when BOD5 is readily
available [17]. Thus, the elimination of ammonia nitrogen in
the system is then the function of several factors as follows:
ðNH3-NÞout¼ f ððNH3�NÞin;CT;D:O:;Temp;BODinÞ (1)
The multivariate regression model generated by SPSS for
predicting NH3-N concentration in effluent is shown as follows:
ðNH3-NÞout¼ 2:233 þ 0:623ðNH3-NÞin� 0:484CT
þ 0:228D:O:Correlationcoefficient ¼ 0:74 (2)
The model showed that (NH3-N)out was proportional to
(NH3-N)in and dissolved oxygen, but negatively proportional to
contact time. Temperature and BOD concentration did not
significantly affect the nitrification process from the result of
regression analysis of the pilot-scale data. Fig. 6 shows
the fitness of the measured effluent concentrations with the
predicted effluent concentrations. The model predicted
the variability of the ammonia nitrogen in the effluent with
the correlation of 0.74.
The multivariate regression model was used for modeling
the relationship between the controlling factors using a linear
equation. Nonlinear analytical technique—first-order kinetics
was used to develop the next model.
3.3.2. First-order kinetics model
The growth of the nitrifying bacteria is expressed as a first-
order reaction of maximum growth rate and concentration of
organisms [18]. Kadlec [19] described that the kinetics purports
to represent the wetland output concentrations in response to
influent concentration. The first-order rate model, which is a
non-linear relationship, is widely used to design constructed
wetlands and to predict removal performance for pollutants
[20]. The first-order kinetics of ammonia nitrogen removal is as
follows:
dðNH3-NÞdt
¼ �kðNH3-NÞ (3)
Table 4
State variables in the model
State variable Description Units
V Reactor volume L
Q Flow rate L/h
(NH3-N)out Ammonia nitrogen concentration of effluent mg/L
(NH3-N)in Ammonia nitrogen concentration of influent mg/L
CT Contact time h
m Growth rate h�1
mmax Maximum specific growth rate of nitrifier h�1
k Reaction rate coefficient h�1
rA Rate of substrate utilization mg/L h
Ks Half saturation constant of nitrification mg/L
mmax(p) Maximum specific growth rate of plant h�1
Km Half saturation constant of plant uptake of ammonia nitrogen mg/L
Yx/s Yield coefficient of nitrifier mg biomass/mg substrate
Yx/s(p) Yield coefficient of plant mg biomass/mg substrate
Ko Half saturation constant of D.O. mg/L
T Temperature 8Cu Temperature coefficient Dimensionless
D.O. Dissolved oxygen level mg/L
X Biomass concentration mg/L
Xp Plant biomass concentration mg/L
S.Y. Chan et al. / Process Biochemistry 43 (2008) 297–305 301
The first-order kinetics model generated by fitting the ammonia
nitrogen removal data in Datafit 8.0 Okadale is as follows:
ðNH3-NÞout ¼ 0:6867ðNH3-NÞine�0:0243ðCTÞ
Correlation coefficient ¼ 0:79 (4)
The model showed that (NH3-N)out was proportional to (NH3-
N)in, and exponential to contact time. Fig. 7 shows the fitness of
the first-order kinetics model. The R2 value between the
measured and the predicted ammonia nitrogen effluent con-
centrations was 0.75. It showed the certainty that the correlation
was not due to randomness of the data. Controlling factors
Fig. 6. Fitness of predictions from the multivariate regression model.
including temperature, D.O. and BOD5 were excluded by the
modeling process.
3.3.3. Mass balance model
Both multivariate regression and first-order kinetics models
utilized a ‘‘black box’’ approach to predict the ammonia
nitrogen removal in the system. Both models focused on the
overall performance of a system and the major removal
mechanisms were not taken into account. The third model was
developed in this study using mass balance of increased
complexity. A mass balance (also called a material balance) is
an accounting of materials entering and leaving a system [21].
Fig. 7. Fitness of predictions from the first-order kinetics model.
S.Y. Chan et al. / Process Biochemistry 43 (2008) 297–305302
A mass balance model was developed in order to simulate and
investigate the nitrification process occurred in the batch-fed
constructed wetland. Monod’s model which relates the growth
rate of microorganism (nitrifier) to the concentration of a single
growth-controlling substrate (NH3-N)in via two parameters, the
maximum growth rate (mmax) and the substrate affinity constant
(Ks) [13], was adopted here in Eq. (5),
m ¼ mmaxðNH3-NÞinKs þ ðNH3-NÞin
(5)
While the mass flow of ammonia nitrogen in the batch-fed
constructed wetland can be written as in Eq. (6),
(6)
In a batch-growth culture system, a portion of substrate is
converted to new cells. And the growth rate of nitrifier is related
to the rate of NH3-N utilization by nitrifier with a yield
coefficient (Yx/s). Yx/s is defined as the ratio of mass of cell
formed to the mass of substrate consumed, and it is measured
during any finite period of logarithmic growth [10]. In addition,
similar relationship exists with the yield coefficient of plant (Yx/
s(p)) applied to the plant uptake kinetics of ammonia nitrogen in
the batch-fed constructed wetland according to Michaelis–
Menten equation [22,23]. Hence, the overall rate of NH3-N
utilization (rA) in the batch-fed constructed wetland by nitrifiers
and plant uptakes were comprised of 2 components as follows:
Rate of NH3-N utilization by nitrifiers
¼ � 1
Yx=s
mmaxðNH3-NÞinKs þ ðNH3-NÞin
ðxÞ ðMonod0s equationÞ (7)
Rate of NH3-N utilization by plants
¼ � 1
Yx=sðpÞ
�mmaxðpÞðNH3-NÞinKm þ ðNH3-NÞin
ðxpÞ ðMichaelis�Menten equationÞ
(8)
Additionally, seasonal variation of temperature was proved
to have significant effect on nitrification process. The Van’t
Hoff–Arrhenius equation provides a generalized estimate of
temperature effects on biological reaction rates [10]. The
growth rate of Nitrosomonas bacteria also responses to
substrate concentration and dissolved oxygen concentration
according to Monod-type function.
Considering the effects of temperature and dissolved
oxygen, and putting Eqs. (7) and (8) into Eq. (6), the mass
balance model based on the nitrification by nitrifier and the
plant uptake for the removal of ammonia nitrogen in
wastewater was developed as in Eq. (9),
VdðNH3-NÞ
dt¼ QðNH3-NÞin � QðNH3-NÞout
� V
�1
Yx=s
mmaxðNH3-NÞinKs þ ðNH3-NÞin
ðxÞ��
D:O:
Ko þ D:O:
�uT�20
ðNitrificationÞ
� V
�1
Yx=sðpÞ
mmaxðpÞðNH3-NÞinKm þ ðNH3-NÞin
�ðxpÞ
ðPlant uptakeÞ
(9)
And for batch reactor,
Q ¼ 0 and V is constant; (10)
And
dðNH3-NÞdt
¼ DðNH3-NÞDt
¼ ðNH3-NÞout � ðNH3-NÞinCT
(11)
Putting Eqs. (10) and (11) into Eq. (9), the model was modified
as follows in Eq. (12):
ðNH3-NÞout ¼ ðNH3-NÞin � CT
�1
Yx=s
mmaxðNH3-NÞinKs þ ðNH3-NÞin
ðxÞ�
��
D:O:
Ko þ D:O:
�uT�20
��
1
Yx=sðpÞ
mmaxðpÞðNH3-NÞinKm þ ðNH3-NÞin
�ðxpÞ ¼ CT
(12)
The final valid model obtained by fitting experimental data into
Eq. (12) with Datafit 8.0 Okadale is as follows:
ðNH3-NÞout ¼ ðNH3-NÞin � ðCTÞ�
1
Yx=s
mmaxðNH3-NÞinKs þ ðNH3-NÞin
ðxÞ�
��
D:O:
Ko þ D:O:
�uðT�20Þ
Correlation coefficient ¼ 0:92 (13)
The final mass balance model (Eq. (13)) indicated that the
most important factors affecting growth rate of nitrifier were
substrate concentration in the influent, contact time, dissolved
oxygen and temperature. The effect of plant uptake was
excluded in the final mass balance model. The mass balance
model development found that the plant uptake function
represented by Michaelis–Menten equation was not significant
in the ammonia nitrogen degradation process in the batch-fed
constructed wetland. Even though, it may not be appropriate to
totally neglect the role of plant in the bed system, as apart from
Table 5
Coefficients of nitrification in the mass balance model
Coefficients mmax (day�1) Ks (mg/L) Ko (mg/L) u
Value in the model 0.0064 8.947 0.026 1.032
Typical value 0.008 1.3 0.2 1.04
Metcalf and Eddy (2003).
Table 6
Results of sensitivity analysis
Parameters Units Assigned range Assigned value Perturbation Sx
(NH3-N)in mg/L 14.45–51 32.73 +1% 1.323(+)
�1% 1.322(+)
Average 1.323(+)
CT h 0–18 9 +1% 0.336(�)
�1% 0.336(�)
Average 0.336(�)
T 8C 14.47–28.61 21.54 +1% 0.280(�)
�1% 0.278(�)
Average 0.279(�)
D.O. mg/L 0.2–3.28 1.74 +1% 0.006(�)
�1% 0.006(�)
Average 0.006(�)
(+) indicates a positive relation between the changes in the parameters and the
change in the model output. (�) indicates an inverse relation between the
changes in the parameters and the change in the model output.
S.Y. Chan et al. / Process Biochemistry 43 (2008) 297–305 303
direct plant uptake, plants could facilitate the pollutant removal
processes by possible oxygen release from the root zone to the
surrounding adsorbing medium [24]. Also, additional surface
area for microbial attachment is also provided by plant in
wetland systems [25]. In some plants, degradation of
contaminants occurs when root exudates (e.g. simple sugars,
alcohols and acids) stimulate proliferation of microbial
communities in the rhizosphere. This is known as rhizo-
enhanced degradation. Roots also de-aggregate the soil matrix,
allowing aeration and promoting biodegradation [26]. Plant is
still regard as an important component in such filter bed system.
The correlation coefficient of the mass balance model was
0.92, which was the highest among the three types of models
being tested. Mass balance approach is able to determine the
sources and sinks of nitrogen in the system, and allows the
understandings of the types of removal mechanisms involved as
well as their significance. Referring to the final mass balance
model in Eq. (13) and in order to increase the removal of
ammonia nitrogen in the batch-fed constructed wetland, factors
including influent concentration, contact time, dissolved
oxygen and temperature have to be considered in priority.
Table 5 shows the typical kinetics coefficients of the
nitrification process with the comparison of the values obtained
from the mass balance model. The biomass (x) of a typical fixed
bed reactor from literature is 800 mg/L [18] while the typical
value of Yx/s in nitrification process is 0.2 [10]. The calculated
Fig. 8. Fitness of the predicted values from the mass balance model.
value of mmax in the batch-fed constructed wetland was 0.0064
day�1. The value was comparable to the typical values in
literature. Fig. 8 shows the fitness of the measured effluent
concentration with the predicted effluent concentration from
the mass balance model. The R2 value of the fitness was 0.75.
The findings were as good as those in other similar modelling
studies using data from pilot-scale experiment with the range of
R2 value from 0.7 to 0.8 [27].
3.3.4. Sensitivity analysis
The sensitivity of the ammonia nitrogen mass balance model
was tested using the four parameters: influent ammonia
nitrogen concentration (NH3-N)in, contact time (CT), tempera-
ture (T) and dissolved oxygen (D.O.) (Table 6). Except the
concentration of ammonia nitrogen in influent showing a
positive relationship with the model output, contact time,
temperature and dissolved oxygen were all showing a negative
relationship with the model output. An overview of the most
sensitive components in the model can be obtained through the
sensitivity analysis [28]. The sensitivity of the influent
ammonia nitrogen concentration was the largest at +1.323
(+1%) and +1.322 (�1%), so the model was the most sensitive
to it. The Sx value of contact time was bigger than that of
Fig. 9. Contour plot for ammonia nitrogen removal prediction at sewage
temperature in a range of 9.8 8C < T < 20 8C.
Fig. 10. Contour plot for ammonia nitrogen removal prediction at sewage
temperature in a range of 20.0 8C � T < 35 8C.
S.Y. Chan et al. / Process Biochemistry 43 (2008) 297–305304
temperature, but the model was less sensitive to these two
parameters than to the influent ammonia nitrogen concentra-
tion. Lastly, the model was the least sensitive to dissolve
oxygen as the Sx value was only about 0.006 (�1%).
3.4. Applications
To cope with different wastewater demands and desired
effluent qualities, contour plots were prepared from the mass
balance predictive model. The predictions of treatment
efficiencies were done for two temperature ranges, with regard
to the recorded temperature range in the studied areas. Figs. 9
and 10 show the predicted removal efficiencies of ammonia
nitrogen at sewage temperature in a range of
9.8 8C < T < 20 8C and in a range of 20.0 8C � T < 35 8C,
respectively. The required contact time for achieving desired
levels of removal efficiencies could be predicted under different
influent concentrations.
4. Conclusions
The batch-fed constructed wetland was a modified biofilter
system that integrated with sequencing batch-feeding mode and
with the presence of plants. The system could achieve desirable
removal efficiencies of BOD5, NH3-N, TP and TSS in the pilot-
scale experiment of this study. The predictive models
developed in this study provide guidance to system design
for different wastewater treatment purposes and demands with
different ammonia nitrogen loadings and desired removal
efficiencies in suburban areas. With its ease of operation and
low-cost requirement, the system provides an alternative
domestic wastewater treatment tool in suburban populated
area where is out of the coverage of the municipal sewage
treatment network. Moreover, the selection of plant species and
supporting media in the system can be varied according to
different local characteristics, in order to fulfil both environ-
mental and financial considerations in different areas.
Acknowledgments
The Hong Kong Polytechnic University Research Grant and
the Hong Kong Research Grants Council are hereby acknowl-
edged for the financial supports.
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