Synergism of natural and constructed wetlands in Beijing, China

Synergism of natural and constructed wetlands in Beijing, China

Ecological Engineering 37 (2011) 128–138 Contents lists available at ScienceDirect Ecological Engineering journal homepage:

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Ecological Engineering 37 (2011) 128–138

Contents lists available at ScienceDirect

Ecological Engineering journal homepage:

Synergism of natural and constructed wetlands in Beijing, China Honggang Zhang a , Baoshan Cui a,∗ , Jianming Hong b,1 , Kejiang Zhang c a

School of Environment, Beijing Normal University, State Key Joint Laboratory of Environmental Simulation and Pollution Control, Beijing 100875, China College of Life Sciences, Capital Normal University, Beijing 100048, China c Department of Civil Engineering, University of Calgary, Alberta, Canada T2N 1N4 b

a r t i c l e

i n f o

Article history: Received 17 January 2010 Received in revised form 4 August 2010 Accepted 7 August 2010 Available online 24 September 2010 Keywords: Integrated wetland system Constructed wetlands Natural wetlands Net water loss Water environmental capacity

a b s t r a c t An integrated wetland system (IWS) including constructed wetlands (CWs) and modified natural wetlands (NWs) for wastewater treatment to replenish water to wetlands located at the Beijing Wetland School (BWS) in Beijing, China, is presented in this paper. The synergistic effects of CWs and NWs on treated water quality are investigated. The IWS is proved to be an effective wastewater treatment technique and a better alternative to alleviate the water shortage for conservation of wetlands based on the monitoring data obtained from October 2007 to 2008. The results show that CWs and NWs play different roles in removing contaminants from wastewater. The COD removal efficiency in CWs is higher than that in modified NWs, whereas the modified NWs can compensate for the deficiency of CWs where a stable and sufficient rhizosphere is not fully formed in the start-up period. All removal rates of COD, TN, and TP in CWs and modified NWs vary from 50 to 70%, while the total removal rate of COD, TN, and TP in IWS is about 85–90%. The operational results show that the maximum area loading of organic pollutants in modified NWs (65 kg/ha d) is slightly higher than the empirical one (60 kg/ha d) recommended by USEPA (2000) for free water surface wetlands. © 2010 Elsevier B.V. All rights reserved.

1. Introduction Wetlands are fewer in Beijing due to unbalanced spatial distribution of water resources compared with other cities, such as Shanghai and Wuhan in China (Zhao et al., 2005, 2006; Gong et al., 2007; Xu et al., 2010). These limited wetlands are facing increasing degradation due to water shortage and pollution. In order to conserve existing wetlands and alleviate the degradation of wetlands, the treated domestic and agricultural wastewater can be considered water sources to replenish water to wetlands (Rios et al., 2009). However, conventional wastewater treatment plants in most rural areas of Beijing are not available due to their high costs for construction and operation (Chen et al., 2008). Constructed wetlands (CWs), which are ecologically engineered system and akin to natural wetlands (NWs), are widely used as a cost-effective approach for different kinds of wastewater treatment (Mitsch and Jorgensen, 1989; Sun et al., 2005; Prochaska and Zouboulis, 2006; Eke and Scholz, 2008). Many successful practices in USA, Finland, Italy, New Zealand, Belgium and Poland have been presented in literature (Kern and Idler, 1999; Newman et

∗ Corresponding author. Tel.: +86 010 58802079; fax: +86 010 58802079. E-mail addresses: [email protected], [email protected] (B. Cui), [email protected] (J. Hong). 1 Tel.: +86 010 68903346; fax: +86 010 68903346. 0925-8574/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.ecoleng.2010.08.001

al., 1999; Schaafsma et al., 1999; Knight et al., 2000; Nguyen, 2000; Koskiaho et al., 2003; Mantovi et al., 2003; Poach et al., 2003; Rousseau et al., 2004a; Tuszynska and Obarska-Pempkowiak, 2008). However, a large number of reports emphasize the removal efficiency of pollutants or nutrients in CWs while ignoring the fact that CWs often need large areas of land and a longer retention time to achieve acceptable effluent water quality (Akratos and Tsihrintzis, 2007). On the other hand, CWs have relatively low or unstable performance in the start-up period due to immature rhizosphere environments (Vymazal et al., 1998). Although CWs can simulate and enhance some functions of NWs, they cannot completely replace NWs in the removal of pollutants due to a lack of diversified plant communities, mature microbial communities, and stable rhizosphere environments. The history of NWs for wastewater treatment can be traced back to 1912 (Kadlec and Knight, 1996). Since then, wetlands have been considered alternatives for wastewater treatment due to their apparent treatment capacities. Many NWs, such as riparian wetlands, are used to reduce the nutrient load of through-flowing water by removing nitrates and phosphorus from surface and subsurface runoff (Zedler, 2003; Hogan et al., 2004; Hogan and Walbridge, 2007). However, some problems of NWs are also obvious, such as lower contaminant load and limited self-purifying capacities. It is assumed that an integrated wetland system (IWS) composed of CWs and NWs based on the principle of complementary

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Fig. 1. Decision support tree for the design of the optimum combination of constructed wetlands and modified natural wetlands.

advantages can achieve greater treatment capacity than any individual system. Thus, how to design and operate the synergistic system of CWs and NWs will be a focus in water quality improvement (Mitsch and Gosselink, 2000; Zedler and Kercher, 2005; Verhoeven et al., 2006). In this paper, an IWS is applied to purify the domestic wastewater discharged from the student dormitories. Treated water will be recharged to wetlands at the Beijing Wetland School (BWS). The objectives of this paper are to (1) develop a design method for IWS used for wetland conservation; (2) determine the efficiency of IWS to treat domestic wastewater; and (3) provide information and transfer knowledge to other wetland conservation projects. 2. Materials and methods 2.1. Background and study area The study IWS was built in BWS in Shunyi District located northeast of Beijing, with a latitude of 40◦ 10 N and a longitude of

116◦ 45 E. This area is located in a north temperate zone with semihumid temperate continental monsoon climate. The total area of wetlands in BWS is 6500 m2 with the open water zones of 3500 m2 . A variety of water birds are often attracted to inhabit or forage in wetlands due to higher diversity of patterns including emerged, submerged, and floating plants together with open water bodies. BWS has become the main place of environmental education for instructors and students from primary and secondary schools in Beijing. Recently, a serious degradation of wetlands has been identified due to the shortage of water sources. Restoration of the degraded wetlands was scheduled by local governments. Some approaches are limited to available water sources. In some cases, groundwater has to be used to maintain the wetlands. To fix the issue of water shortage, wastewater discharged from two students’ dormitories was purified using IWS and then recharged to wetlands. The IWS is located to the north of the dormitories and its total area is approximately 2595 m2 . Wetland monitoring was carried out in July to October 2007 and 2008, when the greatest quantity of wastewa-


H. Zhang et al. / Ecological Engineering 37 (2011) 128–138

Fig. 2. The planning graph of IWS in Beijing Wetland School.

ter was discharged from the dormitories due to an increase of bath water. Fig. 1 shows a decision support tree for the design of IWS including the CWs and the modified NWs.

Open water zones are the main evaporating surfaces in wetlands and a direct means of measuring evaporation is given by: QE = Ao × E × 10−3

(2) (m2 )

2.2. Calculation for net water loss Water supplement for wetlands mainly depended on groundwater to maintain wetland ecosystem in a healthy and stable state before this project was implemented. A variety of processes such as evaporation, seepage, and direct precipitation affect water content in wetlands. The net water loss (Q) is determined based on water balance given by: Q = QE + QS − QP


where QE is the evaporation from wetlands (m3 /d), Qs is the seepage out of wetlands (m3 /d), and Qp is the direct precipitation onto wetlands (m3 /d).

where Ao is area of open water and E is capacity of water surface evaporation (mm/d). The average value of precipitation is computed for each month using data from Beijing Meteorological Bureau by: QP = Ao × P × 10−3


where Ao is area of open water (m2 ), P is precipitation direct onto wetlands (mm/d). Seepage loss is given by: QS = K × A ×



where K is the coefficient of seepage (m/d), A is the area of water bed (m2 ), H is head difference between water surface and underground water table, and L is the seepage distance.

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Table 1 The characteristics of each experimental system, HSF means horizontal subsurface flow; VSF means vertical subsurface flow. System

Area (m2 )

Layer thickness or water depth (cm)


Medium size (mm)



Typha latifolia



Biological Pond Pond A

70 800

15 55 20 15 55 20 Water depth 60–70 Water depth 40–50

Pond B


Water depth 40–60

Gravel (5–15) Gravel (20–40) Gravel (40–50) Gravel (5–15) Gravel (20–40) Gravel (40–50) Soils Soils Soils Soils Soils Soils Soils Soils Soils Soils Soils Soils Soils

Phragmites australis

Eichhornia crassipes Phragmites australis Typha latifolia Iris tectorum Acorus calamus Scirpus validus Typha latifolia Nelumbo nucifera Scirpus triqueter Trapa incisa Nymphoides peltatum Myriophyllum verticillatum Ceratophyllum demersum

2.3. Modification for NWs

actual available area of CWs; ALR is the area loading rates recommended by USEPA (2000) (6000 mg/m2 d).

The design of modified NWs needs to determine whether the site area can meet the requirements of CWs that are necessary to ensure that the water quality of effluent is compliance with the Grade IV (MEPC, 2002). Although BOD5 and COD are widely used as indicators of organic pollutants in wastewater, two key factors must be considered in determining BOD5 : one is the longer duration for BOD5 analysis, another is the disturbance of toxic substances to the determination condition (Reynolds, 2002; Pisarevsky et al., 2005). In this paper, COD rather than BOD5 was used as design parameter to calculate the area of CWs. The area of CWs is determined by Kadlec and Knight (1996): AS = 5.2Qmax (ln C0 − ln Ce )


where AS is the surface area of CWs (m2 ), Ce

is the concentration of COD in effluent (mg/L), C0 is the concentration of COD in influent (mg/L), and Qmax is the maximum inflow of CWs (m3 /d). If available land is smaller than the area calculated from Eq. (5), the NWs will be modified; otherwise the NWs keep the same. 2.3.1. Configuration Ponds A and B were reconstructed to minimize the disturbances to wetlands by properly determine the length-to-width ratio, water depth, and plant conditions (see Fig. 2). The length-to-width ratio of ponds A and B higher than 1:1 helps to minimize short circuiting. In addition, the topographic slope ensures the water flow from ponds A to B by gravity and avoid backwater in modified NWs (USEPA, 2000). The general water depth varying from 30 to 50 cm could meet the design water depth of reconstructed NWs (40–50 cm). The vegetation in ponds A and B mainly consists of Typha latifolia and Phragmites australis, which facilitate pollutant removal (Hill et al., 1997; Koottatep and Polprasert, 1997; Scholz and Xu, 2002). In modified NWs, the open water area was reserved and a variety of wetland plants were planted in shallow water and edge zones. Area loading rate method applied to estimate the least area of reconstructed NWs is given by USEPA (2000): Aw =


2.3.2. Water controlling Water volume directly influences the detention time of wastewater in wetlands. Although the modified NWs receive continuously treated water, its volume varies from 100 to 120 m3 due to the variation of discharged wastewater from dormitories. Thus, a water dam was installed at outlet to regulate water depth and water volume in the modified NWs. The hydraulic retention time (HRT) is given by: t=

Vw Qave


where Vw is available water volume and Qave is the average flow rate. 2.3.3. Plant community To optimize the vegetation structure and enhance plant diversity, wetland plants including five rhizomatic-root plant species, i.e., T. latifolia, P. australis, Acorus calamus, Iris tectorum and Nelumbo nucifera, and two fibrous-root plant species, i.e., Scirpus validus and Scirpus triqueter, were transplanted into the modified NWs. Other plants, such as Trapa incisa, Nymphoides peltatum, Myriophyllum verticillatum and Ceratophyllum demersum, were also used to improve the construction and landscape of wetlands. All plant species were collected from the nearby Han Shiqiao Wetland Nature Reserve BWS (Table 1). 2.4. Design of CWs 2.4.1. Influent and effluent types CWs mainly receive domestic wastewater after preliminary treatment in septic tank. The average inflow concentrations of major water quality parameters are given in Table 2. Effluent COD concentration obtained from Eq. (5) is used as water quality target which was determined by water environmental capacity of modified NWs.


where Aw is the total area of modified NWs (m2 ); Q is the inflow rate (m3 /d), the maximum monthly inflow (Qmax ) is calculated by 120 m3 /d; C is the influent concentration (mg/L), the COD concentration in effluent from CWs is calculated by formula (5) using the

2.4.2. Constructions and configurations The CWs have two parallel pilot-scale units. Each unit encompasses storage pond, horizontal subsurface flow (HSF), vertical subsurface flow (VSF), biological pond, aeration flume, collecting pond, inflow controlling pond and central controlling well (Fig. 3).


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Table 2 Treatment performances of the IWS between 2007 and 2008. 2007

Removal (%) Max Ave Min Influent (mg/L) Max Ave Min Effluent (mg/L) Max Ave Min Water quality IV (mg/L) Water quality III (mg/L)







93 91.2 86.7

93.4 90.9 88.5

96 94.6 93.3

82.7 79.1 74.2

97.1 95.1 92.9

97.9 96.5 96.1

97 84.6 69.1

5.6 4.6 3.1

99 83.4 74.1

100 89.5 81

5.3 4.6 3.4

10.7 7.6 5.3 1.5

0.12 0.23 0.17 0.3

19.1 17.1 15.6

7.1 4.4 2.6

0.29 0.1 0.2




358 306 225 29 26.5 24 30


• Storage pond: The main purpose of the storage pond is further sedimentation. The setting of the storage pond at the initial stage of CWs has the potential to extend the operational life of subsequent units in the scenario of high contents of suspended matters in inflow. • Aeration channel: The aeration channel is used to enhance the dissolved oxygen (DO) in water.

• Subsurface flow (HSF & VSF) CWs: The main advantage of a subsurface flow system is the isolation of the wastewater from animals and humans. Concerns with mosquitoes and pathogen transmission can be greatly reduced with a subsurface flow system. The design parameters of each unit are given in Table 1. • Biological pond: Some floating plants such as Eichhornia crassipes with water depth of 60–70 cm are planted in the biological pond. • Collecting pond: The purposes of the collecting ponds are to collect treated effluent from each group and aerate by cascading flow. • Inflow controlling pond and central controlling well: These are used to control the distribution of influent into the two groups of CWs and regulate the pipelines used in summer, winter and emptying phase, respectively. The down-gradient location of CWs from the inlet to outlet ensures a gravity water flow system. All pilot-scale units are lined with bentonite waterproof blanket with thickness of 0.8 cm. From bottom to top, gravel (size) of 40–50, 20–40, and 5–15 mm with the corresponding depth of 20, 55 and 15 cm was filled in the HSF and VSF. In order to uniformly distribute water over the bed surface and ensure that the movement of water in each cell a cross the maximum distance from inflow point to outflow one, several sizes of PVC pipes (20, 10 and 7 cm in diameter) with perforated tubes (0.8 cm in diameter) were used to distribute the wastewater flow evenly into each unit. Active elbow pipes were placed at the outlet points for each cell to control water level and sample effluent. Outlet gate

Fig. 3. The plan of constructed wetlands, where HSF means horizontal subsurface flow; VSF means vertical subsurface flow; the arrow direction is the direction of water flow.

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Table 3 Design parameters calculated by different formulas. Net water loss (m3 /d)

QE 7.1

QS 103

QP 6.7

Q 103.4

Formula (5)

C0 (mg/L) 306 306

Ce (mg/L) 30 109b

As (m2 ) 1449a 595c

Formula (6)

Q (m3 /d) 120 120

C (mg/L) 109 100d

Formula (7)

Vw (m3 ) 975

Qave (m3 /d) 110

Qmax (m3 /d) 120 120 ALR (mg/m2 d) 6000 6000 t (d) 8.9

a b c d e

Aw (m2 ) 2180 2000e

The land area requirement of CWs calculated by formula (5). The concentration in effluent from CWs with area of 595 m2 calculated by formula (5). The actual area of CWs. The COD concentration of water environmental capacity of modified NWs with area of 2000 m2 calculated by formula (5). The actual area of modified NWs.

valves located at the centre of the bottom plate for each group unit of CWs were set to adjust outflow and collect outflow sample water. During this study, all units receive the same flow rates. The hydraulic loading rate (HLR) is determined by: HLR =

Qave AS


where Qave is the average flow and As is the surface area. The 0.6-m wide footprint of the upper embankments was also designed to provide easy access for maintaining and monitoring as well as checking for any water leakage, slippage or distortion. A small pool filled with gravels (size) of 40–50 cm around the main CWs was set to collect runoff and storm water from adjacent fields. Fences were installed around CWs to restrict humans and livestock to access. 2.4.3. Planting Each subsurface flow unit of CWs was planted with T. latifolia and P. australis initially with a density of eight plants (approximately 40 cm in height for each plant) per square meter in April 2007. Planting of macrophytes was conducted by hand into substrates with the depth of 10–15 cm. 2.5. Water quality monitoring The variation of discharged wastewater from the students’ dormitories was identified. The maximum and minimum occurred respectively from July to October and from November to March. During the less wastewater period, wastewater was stored in septic tanks and treated by intermittent operation of IWS. In this study, the monitoring of IWS was mainly conducted from July to October 2007 and 2008. Water quality monitoring stations were installed at the inlet and outlet of CWs. Two sampling points in modified NWs were also identified (see Fig. 2). Treated water samples were collected twice a month with two parallel samples using plastic containers. Samples were transported to the laboratory in BWS and analyzed immediately for TN, TP and COD using the method presented in the Standard Method for Examination of Water and Wastewater (MEPC and WWMAA, 2002). The treatment efficiency is calculated by the percent removal (R) for each parameter given by: R=


Ce Ci

× 100


where Ci and Ce are the influent and effluent concentrations of pollutants (mg/L), respectively. The mean value of two samples was

used to calculate the removal rate for each parameter to eliminate the error caused by sampling. 2.6. Statistical analyses Independent-samples t-test and Paired-samples t-test were implemented to determine any significant difference in removal percentages between two periods (2007 and 2008) and between Pond A and Pond B at the level of p ≤ 0.05. Pearson’s correlation coefficient (r) was calculated on the basis of linear dependence between two variables (the pollutant concentration in inflow and the removal efficiency) and the correlations among removal efficiencies for COD, TN, and TP were also analyzed. Statistical analysis was performed by using Microsoft Office Excel and the computing package called Statistical Package for Social Science (SPSS 16.0 for Windows, SPSS Inc., IL, USA). For all tests, water monitoring data distributions were tested for normality. If data was not normally distributed, it was log-transformed and tested for normality. All data were normally distributed after transformation. 3. Results 3.1. Design parameters of IWS In this study, the average quantity of wastewater from two student dormitories (110 m3 /d) can compensate the wetland water loss (103.4 m3 /d) (Table 3). Due to the restriction of available land, the actual area of CWs (595 m2 ) is smaller than the required one (1449 m2 ) according to Eq. (5). Thus, the COD concentration in effluent of CWs does not comply with the Grade IV water quality standards (30 mg/L). In order to ensure effluent water quality and minimize construction costs and environmental disruption, it is necessary to transform the natural wetlands. Effluent from CWs was discharged into pond A and further flowed into pond B with sufficient assimilative capacity. Results show that the actual area of enhanced NWs can reach 2000 m2 where the water environmental capacity of 100 mg/L is lower than the COD concentration (109 mg/L) of effluent from CWs in 2007, and the area loading rates is 6540 mg/m2 /d. The HRT of modified NWs is about 6.6 d with water depth of 40–50 cm and the theoretical HRT of CWs is about 2.5 d. The HLR of CWs is about 0.24 m/d obtained from Eq. (8). On the other hand, a dozen species of water birds in wetlands, such as Gallinula chloropus, Ixobrychus sinensis, Acrocephalus orientalis and Tachybaptus novaehollandiae, were identified. Moreover, some nests of G. chloropus and A. orientalis were also found after the IWS was constructed. This indicates that the pattern of


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Table 4 Correlation analysis between influent concentration and removal efficiency of each system. System COD CWs Pond A Pond B TN CWs Pond A Pond B TP CWs Pond A Pond B *

Pearson correlation

Sig. (two-tailed)

0.752* 0.574* 0.719*

0.032 0.037 0.045

0.501 0.524 0.536

0.252 0.182 0.17

−0.166 0.331 0.576

0.694 0.423 0.135

Significant level p = 0.05, n = 32.

Table 5 Correlation matrix of removal efficiency between COD, TN and TP.

COD Pearson Correlation Sig. (two-tailed) TN Pearson Correlation Sig. (two-tailed) TP Pearson Correlation Sig. (two-tailed) **





0.561** 0.004

−0.068 0.753

0.561** 0.004


0.283 0.180

−0.068 0.753

0.283 0.180


Correlation is significant at the 0.01 level (two-tailed), n = 32.

modification, the increase of plant diversity, and the optimization of vegetation communities improve landscape heterogeneity and habitat diversity of wetlands. 3.2. Removal efficiency of IWS Treatment performances of IWS are summarized in Table 2. The results show that the average removal efficiencies of TN and TP in 2008 are higher than that in 2007. COD removal rate is about 79% which is lower than that in 2007. The average removal efficiencies of IWS for COD, TN and TP are 85, 93 and 95%, respectively, in monitoring period. According to EQSSWC (MEPC, 2002), the concentration of COD in effluent can meet the requirement of Grade IV water quality standards (30 mg/L) and TP concentration is in compliance with the Grade III water quality standards (0.3 mg/L). For each component of IWS (CWs and NWs), the removal rate of COD shows the significantly positive correlation (p ≤ 0.05) with the inflow concentration, whereas the removal rates of TN and TP are not obviously correlated with the inflow concentration (Table 4). The correlations among removal efficiencies for COD, TN, and TP are shown in Table 5. The removal efficiency of COD is positively correlated with that of TN with a correlation coefficient of 0.561 (p ≤ 0.01). However, the correlations between the removal efficiencies for TN and TP, as well as COD and TP are not clear. 4. Discussion 4.1. IWS design In this research, a proper ecological engineering approach is carried out to improve the design and management of IWS. It is important to determine the area under the specified water volume and HRT, which is closely related to the removal performance of IWS (Nahlik and Mitsch, 2006; Carty et al., 2008). The overall area of IWS is determined based on the COD concentration in influent and area loading rate of COD. As the actual area of CWs is smaller

than the calculated area, water quality of effluent of CWs is not in compliance with the Grade IV water quality standards recommend by EQSSWC (MEPC, 2002). The increase of the area of CWs will significantly increase the construction costs. Moreover, increase of the area of CWs need to cut down dozens of trees with 13–18 cm diameter at breast height (DBH) or destroy natural wetlands more than 1000 m2 in BWS. These will potentially cause the deterioration of environment. Thus final water quality mainly depends on the modification of NWs. Although the area of both CWs and modified NWs are smaller than the calculated area, the COD concentration in effluent of IWS meets the expected goal. This result reveals that the actual area of IWS is optimal than the calculated area. This also implies that the area of wetlands should be determined based on the target pollutants together with the influent and effluent concentrations. In our study, organic pollutants are primary objective for the wastewater treatment. Many previous studies demonstrated that the principal design criteria leading to adequate effluent water quality from wetlands is determined by target pollutants (Masi et al., 2002; Vymazal, 2005; Li et al., 2009). For example, 13 wetland systems in Waterford (Ireland) all consider the phosphorus as target pollutant (<1 mg/L in effluent) (Scholz et al., 2007). The area ratio between different systems is important when various kinds of wetland systems are combined together to achieve higher treatment efficiency. In Italy, for example, two hybrid wetland systems with different area ratios (480 m2 :850 m2 for HSF to free water surface wetland and 180 m2 :102 m2 :148 m2 for VSF to HSF to free water surface wetland, respectively) were successfully used for concentrated winery wastewater treatment (Masi et al., 2002). Higher COD load (4044.9 and 1003.2 mg/L) was designed for each wetland system and the removal efficiency is more than 90% for each one. The area ratios between different systems are determined not only based on target pollutant, also depend on hydraulic loading, filling depth, and the basin slope. While in this research, in addition to these factors, the limited land and construction costs are also considered in determination of the area ratio between the CWs and NWs. HRTs for modified NWs and CWs are 6.6 and 2.5 d, respectively, which are consistent with the recommended value reported by Wood (1995), who presented that HRT for subsurface flow CWs should fall into the range of 2–7 d. It should also be noted that the HLR (0.24 m/d) for this CWs is higher than the range value (0.025– 0.05 m/d) presented by Brix (1994) for vertical flow wetlands. The optimization of plant communities can not only increase biodiversity in IWS, but also improve the treatment efficiency (Brix, 1997; Alvarez and Becares, 2008; Cheng et al., 2009). Two kinds of aquatic vascular plants (T. latifolia and P. australis) in CWs benefit pollutant removal processes (Hill et al., 1997; Koottatep and Polprasert, 1997). These two species have evolved to enable their own to root in substrates with little or no available oxygen and grow vertically through the water column with most of their leaves in air. It should be emphasized that lack of proper management at the beginning of operation such as water level controlling can lead to lower aquatic plant coverage and the spread of grasses. Some researchers stated that the shallow water (<100 mm) will enhance the establishment of grasses and weeds, which can restrict the growth of the macrophytes (McCuskey et al., 1994; Scholz and Lee, 2005). Some previous studies also show that the management of water depth is particularly important to facilitate optimal water treatment (Dunne et al., 2005a,b; Scholz, 2007). 4.2. Removal efficiency Wastewater in wetlands is purified by complex processes including the interaction among aquatic plants, micro-organisms,

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water and soil (Scholz and Xu, 2002; Scholz et al., 2007). The average removal efficiency of COD (79.1%) is lower in 2008 than that (91.2%) in 2007 (Fig. 4a) due to the relatively low influent organic loading rate of CWs (average 83.4 mg/L) (Yalcuk and Ugurlu, 2009). Lower organic loading is caused by an underground Micro-Organism Treatment system which is installed between septic tank and IWS to reduce organic concentration in wastewater to achieve the requirements of water environmental capacity of modified NWs and extend the service life of IWS in April 2008. Analysis of Pearson’s correlations shows that the relationship between influent concentration and removal efficiency of COD in IWS is statistically important (p < 0.05, r = 0.57–0.75) (Table 4), the result is consistent with previous studies (Korkusuz et al., 2005; Li et al., 2008). In our research, the removal rates of TN are not apparently correlated with the inflow concentrations (Table 4) due to the relatively higher TN influent concentration (Kadlec and Knight, 1996; Tanner et al., 1998). The lower removal rates in CWs (approximately 59% seen in Fig. 4b) are mainly due to the unstable redox process in rhizosphere and plant roots (average depth of only 10–20 cm), which are not extensive for microbial attachment and oxygen transport (Stottmeister et al., 2003; Wu et al., 2008). Moreover, the bed body with 90 cm deep in CWs results in relatively less aerobic condition. This limits the nitrification rates and leads to lower removal efficiency of nitrogen (Yalcuk and Ugurlu, 2009). The nitrogen removal ability is also affected by the low coverage and biomass of the plants in CWs (Wu et al., 2008). Mechanisms of phosphorus removal in wetlands include sedimentation, plant uptake, peat accretion, and sorption reactions (Reddy et al., 1999; Braskerud, 2002; Koskiaho et al., 2003). In our research, no significant difference of the removal efficiencies between each system of IWS (Fig. 4c) is identified, while the removal rates are relatively stable in CWs. It is possible that the gravel selected as substrates may improve TP removal rate due to the fine medium providing higher specific surface area for phosphorous adsorption (Lin et al., 2002; Van de Moortel et al., 2009). In Fig. 4c, one can observe that although CWs are still in the startup period, the TP removal efficiency reaches 62.4%, which is in compliance with the value of 60–70% presented by Vymazal (2007). As shown in Table 5, the relationship between the removal efficiency of COD and TN is statistically significant. This might be induced by the higher loading rates of organic compounds, which lead to lower oxygen content and then the anaerobic degradation of organic compounds occurs (Cooper et al., 1996). At the same time, as carbon source, the decomposed organic compounds can provide energy for denitrifying bacteria to promote the denitrification which is one of the most important ways for nitrogen removal in wetlands (Yalcuk and Ugurlu, 2009). Whereas the removal efficiencies of TN and COD are not clearly correlated with TP removal rate, implying that although biological degradation plays a role in the removal of phosphorus in wetlands (Behrends et al., 2001; Sun et al., 2005), the predominant way of phosphorus removal is physical and chemical processes. It should be noted that although the monitoring is carried out from July to October in this study, the operation of IWS in the rest of the year, especially in cold weather, is also considered in system design. Subsurface flow (HSF&VSF) CWs and the pipe arrangement ensure IWS can be used in cold weather. The temperature and seasonal conditions can affect both physical and biological activities within the wetland system (Werker et al., 2002). Kadlec and Knight (1996) presented that nitrogen removal in CWs is a temperature dependent process. The subsurface flow CWs in IWS is more suitable for colder climate condition as the treatment occurs below the ground surface, and where bacterial communities are thereby insulated from the cold air. Higher fluctuation of NH4 + –N, NO3 − –N and


Fig. 4. Correlation analysis between influent concentration and removal efficiency of IWS. Lines indicate removal efficiency and histograms indicate the influent concentration of each unit; CWc is influent concentration of CWs; pond Ac is influent concentration of pond A; pond Bc is influent concentration of pond B; CWr is removal efficiency of CWs; pond Ar is removal efficiency of pond A; pond Br is removal efficiency of pond B.


H. Zhang et al. / Ecological Engineering 37 (2011) 128–138

TN during different seasons were identified by Li et al. (2008). They found that the removal efficiencies of NH4 + –N and TN are the lowest in winter compared with that in other seasons. However, they also stated that there are no statistically significant seasonal differences between COD removal efficiencies during the 12-month investigation. Whereas Maehlum and Stalnacke (1999) found that the removal efficiencies for N, P and COD are all lower than 10% in cold weather compared to those in warm periods. Generally, Beijing’s cold climate in winter challenges the operation of IWS because its functional maturity in pollutants removal is not well established over the first winter, and may not be improved until the end of the first growing season. The improvement in pollutant removal is attributed to development of a mature system, stable microbial population, and plant establishment (Wallace et al., 2001). Thus further monitoring is required in order to improve the IWS performance in future operation. 4.3. Implication for wetland conservation The IWS receives significant wastewater. The effluent from IWS is discharged into pond C and pond D for the compensation of water consumption of wetlands. Although COD concentration in effluent from CWs is a little higher than water environmental capacity of the modified NWs in 2007, the final effluent meets the expected goals. The result indicates the maximum area loading of organic pollutant in modified NWs (65.4 kg/ha d) is slightly higher than that presented in USEPA (2000) (60 kg/ha/d). This might have resulted from that emerged and submerged plants, soil surface, and the water column are almost completely colonized by biofilms before the start of the modification and these conditions recover quickly after the modification (Poe et al., 2003; Rousseau et al., 2004b). Thus, there are many favorable conditions for the removal of pollutants such as diversified plant communities and reasonable plant community structures, mature microbial communities and stable rhizosphere environments in modified NWs (USEPA, 2000; Garcia et al., 2005; Verhoeven et al., 2006; Carty et al., 2008). After the application of IWS for 2 years, water shortage and water quality in wetlands have been obviously improved. The removal performance of IWS is better than that presented in Gunes and Tuncsiper (2009). In their study, a system consisted of a combination of buried sand filtration and subsurface flow constructed wetlands was used to treat wastewater with 85.9 mg/L for TN and 8.94 mg/L for TP in the village of Ileydagi and the average removal values observed during a 14-month period were 85% for TN and 69% for TP. The design of IWS not only avoids the deficiency of using CWs or NWs solely, but also enhances the synergistic effects of constructed and natural ecosystem on wastewater treatment. The modified NWs play a crucial role in keeping better removal efficiency in the start of CWs where rhizosphere has been not well established. Moreover, the shallow water flow with open water zones can provide aerobic conditions and sufficient time for microbial metabolic activity and enhance the nitrification rates (Gearheart, 1992; USEPA, 2000). Based on the same water quality target, the IWS covering 2595 m2 can save much costs than single CWs which cover an area of 1449 m2 . This is caused by the modification of NWs in IWS which reduces the inevitable costs of earthwork and construction. Considering the total investment divided into 20 years of lifetime, the average construction cost per unit of wastewater volume treated is 0.272 RMB/m3 for IWS and 0.661 RMB/m3 for single CWs (Table 6). The main costs of IWS are earthwork and construction, and others are planting and labor costs. The total excavation cost for 2595 m2 of IWS is about 10411.5 RMB, where CWs account for 94%, depending on the depth of CWs (about 1.5 m) and unit price of earthwork

Table 6 Cost comparison between integrated wetland system and constructed wetlands.


Area (m ) Earthwork (m3 ) Earthwork costa (RMB) Construction cost (RMB) C/Tb (RMB/m3 ) a b



2595 946.5 10411.5 208,250 0.272

1449 2173.5 23908.5 507,150 0.661

11 RMB/m3 . C/T construction cost per unit of wastewater volume treated.

(11 RMB/m3 ) (Table 6). While the earthwork cost for modified NWs is only 594 RMB, as the modification of edge zones of NWs requires less soil to be moved. Construction costs of IWS mainly come from the construction of CWs including costs of membrane, substrate, pipes, and other facilities. The costs of planting are smaller because the plants removed from NWs being modified are replanted into the CWs. These minimize the cost of plant purchase. 5. Conclusions The performances of IWS for domestic wastewater treatment are investigated in this paper. In the IWS, wastewater discharged from septic tank first flows into the CWs and then is further treated in the modified NWs. Generally, the total removal rate of COD, TN, and TP is about 85–90% in the IWS. The IWS provides sufficient purified water to replenish wetlands. The synergistic effects of the IWS are comparable to that of any single system (CWs or NWs). The results indicate that the application of the integrated treatment system is economically and environmentally feasible, which can fix the issues of water shortage and wastewater problem simultaneously, implying that IWS has a significant potential in conservation of wetlands. Acknowledgements The research was financially supported by National Natural Science Foundation (U0833002), the program from Beijing Municipal Science & Technology Commission (D07040600770701-8), and Scientific Research Foundation of Beijing Normal University (No. 2009SD-24). The authors would like to acknowledge postgraduates Bingbing Jiang and Jingjing Ruan from the College of Life Science, Capital Normal University, for their help in data collection. The authors also acknowledge the contributions of two anonymous reviewers and the editor-in-chief for their constructive comments which significantly improve the quality of this paper. References Akratos, C.S., Tsihrintzis, V.A., 2007. Effect of temperature, HRT, vegetation and porous media on removal efficiency of pilot-scale horizontal subsurface flow constructed wetlands. Ecol. Eng. 29, 173–191. Alvarez, J.A., Becares, E., 2008. The effect of vegetation harvest on the operation of a surface flow constructed wetland. Water SA 34, 645–649. Behrends, L., Houke, L., Bailey, E., Jansen, P., Brown, D., 2001. Reciprocating constructed wetlands for treating industrial, municipal and agricultural wastewater. Water Sci. Technol. 44, 399–405. Braskerud, B.C., 2002. Factors affecting phosphorus retention in small constructed wetlands treating agricultural non-point source pollution. Ecol. Eng. 19, 41–61. Brix, H., 1994. Use of constructed wetland inwater pollution control:historical development, present status, and future perspectives. Water Sci. Technol. 30 (8), 209–223. Brix, H., 1997. Do macrophytes play a role in constructed treatment wetlands? Water. Sci. Technol. 35, 11–17. Carty, A., Scholz, M., Heal, K., Gouriveau, F., Mustafa, A., 2008. The universal design, operation and maintenance guidelines for farm constructed wetlands (FCW) in temperate climates. Bioresour. Technol. 99, 6780–6792. Chen, Z.M., Chen, B., Zhou, J.B., Li, Z., Zhou, Y., Xi, X.R., Lin, C., Chen, G.Q., 2008. A vertical subsurface-flow constructed wetland in Beijing. Commun. Nonlinear Sci. Numer. Simul. 13, 1986–1997.

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