Assessment of treatment efficiency of constructed wetlands in East Ukraine

Ecological Engineering 83 (2015) 159–168

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Assessment of treatment efficiency of constructed wetlands in East Ukraine Yuriy Vergelesa , Yuliya Vystavnaa,b,* , Andrey Ishchenkoa , Inna Rybalkaa , Lilian Marchandc , Felix Stolberga a O.M. Beketov National University of Urban Economy at Kharkiv, Department of Environmental Engineering and Management, vul. Revolutsii 12, Kharkiv 61002, Ukraine b Matej Bel University in Banska Bystrica, Department of the Environment, Tajovskeho 40, 97401, Slovak Republic c UMR 1202 BIOGECO INRA, Ecologie des Communautés, Université Bordeaux, Bâtiment B2—RdC Est Allée Geoffroy St-Hilaire CS 50023, 33615 Pessac, France

A R T I C L E I N F O

A B S T R A C T

Article history: Received 17 March 2015 Received in revised form 26 May 2015 Accepted 20 June 2015 Available online xxx

The aim of the study was to evaluate the performance of 9 hybrid constructed wetlands (CWs) in the Kharkiv region, East Ukraine. Assessed CWs varied by surface areas (from 760 to 11,000 m2) and treated domestic wastewater discharge (10 m3 day
1 to 700 m3 day
1). Principal macrophyte species used on these CWs were the Reed Phragmites australis (Cav.) Steud., the Wood Bulrush Scirpus sylvaticus L. and the Broad-leaved Cattail Typha latifolia L. The studied CWs demonstrated high removal efficiency on BOD5 (82.6  11%), COD (77.3  9%) and suspended solids (72.1  9%). The removal rates of nitrogen, orthophosphates and surfactants ranged from 9% to 52%. The overall removal efficiency of CWs was dependent mainly on inflow pollutant concentrations, design, maintenance parameters and operating conditions. Comparing to conventional domestic wastewater treatment facilities the CWs showed similar efficiency on the majority of controlled parameters. At the same time the estimated construction and operational costs of CWs were significantly lower compared to the conventional wastewater treatment facilities of similar capacities that makes CWs application feasible for small communities in rural areas. In order to improve the removal capacity of studied wetlands, operational conditions should be adjusted to the inflow concentrations and received wastewater volumes. ã 2015 Elsevier B.V. All rights reserved.

Keywords: Constructed wetlands Ukraine Operating conditions Rural area Treatment costs

1. Introduction Constructed wetlands (CWs) are engineered ecosystems which act as biofilters to eliminate nutrients, pathogenic microorganisms, persistent organic pollutants, xenobiotics and trace elements (TE) from industrial and domestic wastewater streams within a semicontrolled environment (Kadlec and Knight, 1996; Brix, 1997; Maine et al., 2007; Vymazal et al., 2010 Marchand et al., 2010; Zhi and Ji, 2012). A common classification divides CWs according to their hydrology onto: (i) surface flow wetlands, (ii) horizontal subsurface flow wetlands, (iii) vertical subsurface flow wetlands, and (iv) hybrid systems (Vymazal, 2001; Arias and Brown, 2009). A broad range of mechanisms affects organics (Vymazal, 2007; Vymazal and Kropfelova, 2009; Marchand et al., 2010) and TE (Marchand et al., 2010) removal in CWs. Organic matter (OM) is

* Corresponding author at: O.M. Beketov National University of Urban Economy at Kharkiv, Department of Environmental Engineering and Management, vul. Revolutsii 12, Kharkiv 61002, Ukraine. E-mail address: [email protected] (Y. Vystavna). http://dx.doi.org/10.1016/j.ecoleng.2015.06.020 0925-8574/ ã 2015 Elsevier B.V. All rights reserved.

decomposed in CWs with horizontal sub-surface flow by both aerobic and anaerobic microbial processes as well as by sedimentation, filtration of particulate OM and uptake by the consortium plant/microorganisms. Highest removal efficiencies for BOD5 (Biological Oxygen Demand, which represent the amount of dissolved oxygen needed by aerobic biological organisms in a body of water to break down organic material over a 5-day period) and COD (Chemical Oxygen Demand, which indicates the mass of oxygen consumed to degrade OM) were reported in systems treating municipal wastewater while the lowest efficiency was recorded for landfill leachate, partly due to the fact that municipal wastewaters contain predominantly labile organics (Vymazal and Kropfelova, 2009). Processes that affect removal and retention of nitrogen during wastewater treatment in CWs are manifold and include ammonia volatilization, nitrification, denitrification, nitrogen fixation, plant and microbial uptake, mineralization (ammonification), nitrate reduction to ammonium (nitrate-ammonification), anaerobic ammonia oxidation (ANAMMOX), fragmentation, sorption, desorption, burial, and leaching. However, only few processes

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ultimately remove total nitrogen from the wastewater while most processes just convert nitrogen to its various forms. Therefore, different types of CWs may be combined with each other in order to exploit the specific advantages of the individual systems, such as a succession of aerobic and anaerobic conditions (Taylor et al., 2005; Vymazal, 2007). Phosphorus transformations during wastewater treatment in CWs include adsorption, desorption, precipitation, dissolution, plant and microbial uptake, fragmentation, leaching, mineralization, sedimentation (peat accretion) and burial. The major phosphorus removal processes are sorption, precipitation, plant uptake (with subsequent harvest) and peat/soil accretion. However, the first three processes are saturable and soil accretion occurs only in free water surface CWs with an emergent plant. Removal of phosphorus in all types of constructed wetlands is low unless special substrates with high sorption capacity are used (Vymazal, 2007). It is now recommended that nutrients, particularly nitrogen and phosphorus, must be recovered in marketable form (Cai et al., 2013; Miksch et al., 2015). Surfactant are defined as “any organic substance and/or mixture used in detergents, which has surface-active properties and which consists of one or more hydrophilic and one or more hydrophobic groups of such a nature and size that it is capable of reducing the surface tension of water, and of forming spreading or adsorption monolayers at the water–air interface, and of forming emulsions and/or microemulsions and/or micelles, and of adsorption at water–solid interfaces” (AISE, 2013). CWs provide good surfactant abatement (Sima and Holcova, 2011; Tamiazzo et al., 2015). The CWs efficiency depends on inlet contaminants concentrations, hydraulic loading, pH, redox conditions, temperature, and the presence/absence of the consortium plants/bacteria (Kadlec and Wallace, 2008). The elimination of contaminants in influents also depends on the inter- and intra-specific variability of the consortium macrophytes/microorganisms (Brisson and Chazarence, 2009; Marchand et al., 2010, 2014a,b, 2014a,b), climate conditions (Kushck et al., 2003; Maine et al., 2007) and anthropogenic factors (construction type, wastewater quality, operating conditions, etc.) (Saeed and Sun, 2012; Zhi and Ji, 2012). CWs generally show high efficiency in removal of suspended solids (SS), BOD5 and COD whereas removal efficiency regarding nutrients (N and P) is lower and more variable (Song et al., 2006; Garcia et al., 2010). Overall efficiency of CWs regarding removal of a wide range of pollutants has been proved for both warm and cold climates by many studies (Mander and Jenssen 2002a,b; Mander and Jenssen 2002a,b). Moreover, the net lifecycle energy output of CWs can be used for biofuel production and enhanced through optimising the nitrogen supply, hydrologic flow patterns and plant species selection (Liu et al., 2013). Since the 1960s, CWs have been developing in different countries simultaneously and various synonymous names are used to indicate the same class of objects: “man-made wetlands” (Breckenridge et al., 1983), “artificial wetlands” (Gersberg et al., 1984), “reed beds” (Biddlestone et al., 1993), “engineered wetlands” (Zhang et al., 2010) and “bioplato” (Stolberg, 2002). The last name of CWs is mainly used in Ukraine and Russia. In Ukraine CWs have been first developed and applied for purification of polluted surface waters in lakes, rivers and canals yet in 1980s. The first CW (“bioplato”) facilities for domestic wastewater treatment have been designed and constructed in 1998 at the Velyki Prokhody village near the city of Kharkiv (Stolberg, 2002). In 1997–2003, Kharkiv region has been a pilot in implementing the CWs ecological technology to wastewater treatment in small to medium-sized rural communities. Here the Regional Programme on Constructed Wetlands (‘Bioplato’) Implementation for 2011–2015 has been accepted by the Regional

Council that made possible to design and build about 15 treatment facilities of such kind in 2011–2013. Besides this region, CWs were built in several other regions both in the West, Central and East Ukraine during 2003–2014. The further wide implementation of this low-cost, efficient eco-technology in the country could be facilitated with adoption by the Ukrainian Government of the Guidelines on Design and Operation of CWs developed by O.M. Beketov National University of Urban Economy in Kharkiv. During the last decade the number of CWs in Ukraine has increased to somewhat 50 operation sites as these are considered an efficient alternative to conventional wastewater treatment systems, cost-effective and environmentally friendly bio-processes for purification of contaminated water (Magmedov et al., 1995; Rousseau et al., 2004; Paulo et al., 2013; Vera et al., 2013). Most of CWs in Ukraine are operated in small rural settlements which are located far away from the central sewage grid, have limited financial resources and energy supply shortages together with a lack of qualified staff for the maintaining and operating more sophisticated treatment systems (Vera et al., 2013). This work aimed at assessing the performance of CWs in Kharkiv region, Ukraine by (i) monitoring common chemical parameters (pH, BOD5, COD and SS), surfactants, orthophosphates and total nitrogen concentrations) of wastewaters effluents and influents on 9 operated CWs in rural areas; (ii) evaluating the operating conditions of the CWs and their efficiency to treat domestic wastewaters and (iii) comparing their treatment efficiency to the conventional wastewater treatment facilities. 2. Study area 2.1. Environmental conditions All studied CWs are located in the Kharkiv region, East Ukraine. The region (ca. 3000,000 inhabitants, 2014) is one of the most industrialised and urbanised areas of Ukraine. In spite of the high population and industries density, the region suffers from the shortage of available water resources (Vystavna et al., 2012). The climate of the study area is a typical for the Forest-Steppe natural zone i.e. moderate with distinct 4 seasons. The duration of the cold

Fig. 1. The location of the studied “bioplato” CWs (B1–B9) in Kharkiv region, East Ukraine.

Y. Vergeles et al. / Ecological Engineering 83 (2015) 159–168

161

Table 1 Parameters of the studied ‘bioplato’ CWs in Kharkiv region, East Ukraine. Constructed wetland locations

Year of construction

Construction type

Pre-treatment Total treatment area (m2)

Mean wastewater Water residence time discharge, (m3 d
1) (d)

Dominating macrophyte species

Designed Actual B1—Velyki Prokhody village 1998

Hybrid

B2—Zhovtneve village, the prison B3—Borivske village

2004 2004

Modified natural wetland Hybrid

B4—town of Shevchenkove

2011

Hybrid

B5—Chervonyi Oskil village 2007

Hybrid

B6—Semeniv Yar village

2010

760

Settling tank

40

10

15

no

700

700

11

4500

Settling tank

70

15

15

9385

Sand catchers, settling tank

400

400

11

2800

Settling tank

100

60

14

Hybrid

3400

Sand catchers, settling tank

130

80

13

B7—Khorosheve settlement 2011

Hybrid

2750

Settling tank

100

70

13

B8—town of Zolochiv, district hospital

2003

Hybrid

1550

Settling tank

100

20

14

B9—town of Zmiyiv, Paper Mill

2012

Hybrid

1650

Settling tank

80

10

15

11,000

period (winter) varies from 125 to 130 days, and warm period (mid-spring to mid-autumn) is ca. 118–200 days. The coldest month is January (mean temperature
7.3  C). The warmest month is July (mean temperature +20.8  C). The mean annual temperature of the air is +6.9  C, wind velocity is 4.0 m s
1 and humidity is 74% (Vystavna et al., 2012). Annual precipitation varies between 470 and 540 mm with maximum in May–June. It is balanced with annual evaporation and transpiration. Soils are black earth (chernozem) and gray podzolic loess (about 8% of humus). The main water contamination sources are run-off from urban and agricultural areas, untreated wastewaters from small communities, agriculture and industries located on the rural area (Vystavna et al., 2013).

Phragmites australis (Cav.) Steud., Scirpus sylvaticus L., Typha latifolia L. Phragmites australis (Cav.) Steud. Typha latifolia L., Typha angustifolia L., Phragmites australis (Cav.) Steud. Phragmites australis (Cav.) Steud., Typha latifolia L., Scirpus sylvaticus L Phragmites australis (Cav.) Steud., Typha latifolia L., Scirpus sylvaticus L Phragmites australis (Cav.) Steud., Scirpus sylvaticus L., Typha latifolia L. Phragmites australis (Cav.) Steud., Scirpus sylvaticus L., Typha latifolia L. Phragmites australis (Cav.) Steud., Scirpus sylvaticus L., Typha latifolia L. Phragmites australis (Cav.) Steud., Scirpus sylvaticus L., Typha latifolia L.

2.2. Constructed wetlands design The CWs were studied in Kharkiv region, East Ukraine, during summer and fall of 2012. Studied wetlands were located in the different parts of the region (Fig. 1) and were designed to treat domestic wastewaters from small towns and rural settlements (B1, B3, B4, B6 and B9), effluents from hospitals (B7 and B8), prison (B2) and orphan house (B5) (Table 1). Except B2, all 9 studied CWs were equipped with settling ponds in order to remove the particulate substances before wastewaters enter treatment units. The plant species used in CWs were the Reed Phragmites australis (Cav.) Steud., the Wood Bulrush Scirpus sylvaticus L., and

Fig. 2. Typical design of the “bioplato” CWs (A—a vertical flow unit and B—a horizontal subsurface flow unit): 1—influent; 2—sedimentation tank; 3—clarified wastewater; 4— filtering substrate; 5—drainage pipes; 6—macrophytes; 7—drainage and 8—effluent.

0.08 0.54
0.04 0.12 0.02 0.18 1 0.68
0.53
0.47
0.39 0.28 0.38 0.73
0.4 0.12
0.59
0.29

NH4out NH4in pHout

0.22
0.14 0.29 0.16 0.24 0.13
0.29
0.6 0.59 0.66 0.64
0.16 0.14
0.55 0.57 0.53 0.53
0.14
0.56
0.04
0.36
0.1
0.36
0.59
0.59 0.66 0.7 0.54
0.68 0.02
0.74 0.64 0.46

pHin DOout


0.49
0.42
0.42
0.5
0.42
0.49 0.12
0.49 0.38 0.57 0.51
0.5 0.17
0.24 0.5
0.19
0.28
0.26
0.32
0.29
0.34
0.4
0.36 0.95 0.9 0.87
0.05 0.24
0.44

DOin Orth.out


0.01 0.38
0.13 0.05
0.04 0.07 0.73 0.77
0.41
0.4
0.35 0.44 0.56 0.19 0.09 0.1 0.05 0.15 0.05 0.38 0.36 0.34 0.39 0.34 0.09

Orth.in Surf.out

0.27 0.51 0.06 0.37 0.06 0.35 0.28 0.53
0.06
0.21 0.03
0.19
0.49
0.22
0.24
0.27
0.3
0.39
0.49 0.93 0.95
0.22
0.54
0.21
0.34
0.25
0.38
0.47
0.53 0.96
0.12
0.41
0.16
0.25
0.19
0.3
0.53
0.42

Surf.in NO3out NO3in

0.22 0.67 0.03 0.15 0.08 0.21 0.68

NH3out NH3in

0.08 0.54
0.04 0.12 0.02 0.18 0.95 0.71 0.92 0.99 0.93

CODout CODin

0.96 0.57 0.99 0.92 0.94 0.65 0.92

BOD5out BOD5in

Wastewater samples were taken at each site from inlet and outlet points during the period of the extreme oxygen depletion from late July to mid-October 2012 (Vystavna et al., 2012). Each studied site was sampled twice using the grab sampling technique (ISO/TS 13,530:2009). Actual wastewater discharge was measured on-site at inlet and outlet applying the measure jar and stopwatch at time when samples were collected. Where available, the measured values were corrected with the data collected over weekly or monthly operation periods as provided from maintenance dairy books. Samples were taken using the polyethylene bottles (2 L) for the analysis of pH, hardness, mineralization, SS, COD, BOD5, anionic surface active agents (surfactants), orthophosphates (PO43
), ammonium (NH4+), ammonia (NH3+) nitrites (NO2
), nitrates (NO3
), and glass bottles (0.5 L) for the detection of dissolved oxygen (DO) (ISO/TR 10,013:2003). All parameters were tested using standard laboratory procedures and methods and analysis were completed within 24 h of

SSout

3.1. Sampling and analytical method

SSin

3. Materials and methods

Table 2 Correlation between measured parameters in inlets (Xin) and outlets (Xout), Pearson’s criteria (r, the r > /0.75/ is in bold), p < 0.05, N = 9.

The detailed comparison of the removal efficiency between conventional wastewater treatment facilities (WWTF) and CW has been done for the site B7 (Khorosheve settlement), where the WWTF was replaced by the CW in 2010. Khorosheve WWTF was designed to treat a mixture of domestic and hospital influents from the nursing house (ca. 500 persons). These conventional wastewater treatment facilities consisted of a primary treatment (screening, sand removal and primary clarifier) and a secondary treatment (activated sludge with nitrification/ denitrification and secondary clarifier). These treatment facilities were operated for almost 30 years until 2010, when secondary treatment units went out of service and their further reconstruction has been considered unfeasible under current economic conditions. The hybrid CW system (B7) was applied in 2010 to replace secondary wastewater treatment subsystem. Thus, it was able to compare the removal efficiency of WWTF during two last years of operation in 2008–2009 to the removal efficiency of CW during first two years (2011–2012) of its operation.

0.96 0.51

2.3. Comparative performance assessment of constructed wetlands and conventional treatment facilities

0.66

the Broad-leaved Cattail Typha latifolia L. (Table 1). The macrophyte species planted at the studied CWs were collected from local natural wetlands belonging to either the reed-cattail or the sedgereed types of the Phragmites australis (Cav.) Steud. formation where these species are dominant in the vegetation cover (SheliagSosonko et al., 1982). No exotic or invasive wetland species were applied anytime at the studied treatment facilities. All selected wetlands had similar design (Fig. 2) making them a combination of vertical and horizontal flow sections, i.e., hybrid treatment wetland systems (Saeed and Sun, 2012). Water depth on studied CWs was maintained at 0.5–0.8 m and the coarse medium sand filter was used to support the growth of plants (Saeed and Sun, 2012). Except B2, the rest of CWs were built with the polymer film isolation in order to prevent both influents and effluent wastewater infiltration to the soil and groundwater. The size of studied CWs ranges from 760 to 11,000 m2 according to the treatment surface area of beds with the operating wastewater discharge rate is from 10 to 700 m3 day
1 (Table 1). Water residence time for each studied treatment facility is shown as stated in the project documentation (Table 1).

0.22 0.67 0.03 0.15 0.08 0.21 0.68 1
0.42
0.53
0.49 0.53 0.36 0.77
0.36
0.49
0.59
0.6 0.68

Y. Vergeles et al. / Ecological Engineering 83 (2015) 159–168

SSin SSout BOD5in BOD5out CODin CODout NH3in NH3out NO3in NO3out Surf.in Surf.out Orth.in Orth.out DOin DOout pHin pHout NH4in NH4out

162

Y. Vergeles et al. / Ecological Engineering 83 (2015) 159–168

sample collection. The pH was measured in-situ with a portable pH meter (Hanna Instruments1, Germany). Nitrites were determined by coupling diazotation followed by a colorimetric technique (ISO/TS 13,530:2009; ISO/TR 10,013:2003). Ammonia, NH4+ and NO
3 were measured by potentiometry (Orion selective electrodes; sensitivity: 0.01 mg L
1 reproducibility  2%). COD was determined by the open reflux method and biochemical oxygen demand BOD by the 5-day BOD test (ISO 9000:2007; ISO/TR 10,013:2003). Surfactants (expressed as sodium dodecyl sulphate) were analysed by photometric method using the Methylene Blue (ISO 7875-1: 1996). Orthophosphates were analysed with the same method in the presence of ammonium molybdate and brilliant green (ISO/TR 10,013:2003). All laboratory analyses were made at the certified Sanitary and Chemical Laboratory of the Regional Centre of the State Sanitary and Epidemiological Service of Ukraine. 3.2. Treatment efficiency calculation The removal efficiency (RE) of contaminants on studied CWs was estimated as the percent reduction that refers to the decrease of the concentration between the inlet and outlet using the following formula (Song et al., 2006): ! C out DCi ð%Þ ¼ 1
iin  100% (1) Ci

DCi, (%)—percent reduction of i-parameter; Ciout and Ciin are the

inlet and outlet concentrations in mg L
1 of i-parameter. According to the RE, for the purpose of this analysis, the studied CWs were then classified as: low efficiency facilities (RE less than 50%); medium efficiency facilities (RE from 50 to 80%), and high efficiency facilities (RE more than 80%). 3.3. Statistical analysis The correlations between chemical parameters at inlets and outlets from one hand, and between RE (Eq. (1)) and CW design parameters (actual wastewater discharge, total area of planted treatment beds, water residence time) were estimated using the Pearson’s criteria (r) (STATISTICA v. 2010) (Tables 2 and 3). 3.4. Construction costs estimation The construction costs of conventional WWTF and CWs in Ukraine were estimated using price lists provided by the Ukrainian Institute of Ecological Problems (data on 2014).

163

4. Results 4.1. Chemical parameters of influents and effluents At almost all studied CWs, the pH was steady for both inlets and outlets and in the range 7.2–8.7 (Fig. 3). Only at B5, pH decreased from 8.1 at the inlet to 7.0 at the outlet. At the inlets of studied CWs, the mean value of DO in wastewaters was 0.12  0.05 mgO2 L
1 and generally did not exceed 0.5  0.1 mgO2 L
1. At the outlets, this parameter reached up to 1.0  0.2 mgO2 L
1 and for three out of the nine studied outlets (B2, B8 and B9), it increased up to 6.0  1.1 mgO2 L
1 (Fig. 3). The inflow SS contents ranged from 48.4 (B8) to 547.6 mgL
1 (B3). The output values varied between 0.4 mg L
1 (B2) and 104 mg L
1 (B3) (Fig. 3). The high SS content in both inflow and outflow at B3 was linked to the mixing of domestic wastewater with run–off from the settlement. The highest inflow values of BOD5 were found for sites B3, B4 and B6 (Fig. 3) at 1110 mgO2 L
1, 760 mgO2 L
1 and 510 mgO2 L
1 respectively. For the rest of CWs, the inflow BOD5 contents were less than 350 mgO2 L
1. The outflow BOD5 ranged from 7.2 (B5) to 130 mgO2 L
1 (B3). A similar pattern was observed for COD, whose the highest inflow values were detected at B3, B4 and B6 with up to 3500 mgO2 L
1 while for the rest of CWs they were less than 1000 mgO2 L
1 (Fig. 3). Inflow concentrations of ammonia nitrogen showed high variability, from 20.1 mg L
1 (B7 and B9) to 113.7 mg L
1 (B1), as well as outflow values: 1.2 mg L
1 (B2) to 110.8 mgL
1 (B1). Nitrate concentrations in influents were less than 0.5 mg L
1 for all studied CWs, except B9 where it was measured at the level of 1.6 mg L
1. In outlets, nitrates increased in some cases up to 36.8 mg L
1 (B9), 10.7 mg L
1 (B2) and 0.84 mg L
1 (B5) respectively. Total nitrogen increased from 21 mg L
1 (B7 and B9) to 118 mg L
1 (B1) in inlets and from 2 mg L
1 (B9) to 115 mg L
1 (B1) in outlets (Fig. 3). Surfactant input contents ranged from 0.19 mgL
1 (B3) to 0.96 mgL
1 (B9) and output contents from 0.04 mgL
1 (B2) to 0.28 mgL
1 (B6). Orthophosphates concentrations varied between 19 mg L
1 (B7) and 112.5 mg L
1 (B1) in influents and between 9.6 mg L
1 (B9) and 77.6 mg L
1 (B1) in effluents. Strong positive correlations were established between respectively (in brackets the Pearson’s criterion, r) SSin–BOD5in (0.96), SSin–BOD5out (0.94), SSin–CODin (0.95), SSin–CODout (0.95), BOD5in–BOD5out (0.92), BOD5in–CODin (0.99), BOD5in–CODout (0.92), BOD5out–CODin (0.92), BOD5in–CODout (0.99), CODin–CODout (0.93), NO3in–NO3out (0.96), NO3in–surfactantsin (0.93), NO3out– surfactantsout (0.95), NH3in–NH4in (1), NH3out–NH4out (1), NH3in–

Table 3 Correlation between estimated removal efficiency of chemical and construction parameters, Pearson’s criteria (r, the r > /0.75/ is in bold), p < 0.05, N = 9. Parameters

Total treatment area

Designed discharge rate

Actual discharge rate

Water residence time

SS BOD5 COD NH3 NO3 Surf. Orth. NH4 Total treatment area Designed discharge rate Actual discharge rate

0.51 0.4 0.43 0.39
0.3 0.42 0.33 0.38

0.44 0.36 0.35 0.5
0.48 0.5 0.25 0.5 0.93

0.49 0.43 0.42 0.51
0.52 0.52 0.28 0.51 0.93 0.99


0.54
0.47
0.45
0.78 0.83
0.76
0.44
0.78
0.68
0.8
0.83

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Y. Vergeles et al. / Ecological Engineering 83 (2015) 159–168

pH

DO

Average eff. = n/a

Average eff. = n/a

9.0

5.0

B9

8.2 7.8

B4

B8 B1

7.4 7.0

B2

B3

B6

B7

B2

4.0

B8

3.0

8.2

8.6

9.0

B1, B3, B4, B5, B6, B7

0

9.4

0.1

0.2

BOD5 B3 Coutput, mg/L

Coutput, mg/L

80 60

B4 B1 B7 B2 B5 B9

0

400

200

600

800

1000

B4

100

B8

0

1200

B1

B9 B7 B5 B2 500

1000

B8 B2

0

B5 100

B9

B1

100 Coutput, mg/L

Coutput, mg/L

B6 B4

20

80 60

B5

40

300 Cinput, mg/L

400

500

B2

B9 0

600

20

40

Average eff. = 49.5%

B7

20

Coutput, mg/L

Coutput, mg/L

B6 B2

B5

20

40

B3 60

B9

B4

B7 0.1

B3

B9

B8 B5

B2

80

100

0

120

0.2

0.4

Cinput, mg/L

30

NO3

N-NH4 Average eff. = 51.5%

B9 (36.8)

5

Coutput, mg/L

Coutput, mg/L

10

B2 B5 B1,B3,B4,B6, B7,B8

0

0.5

1.0

1.5

0.8

1.0

1.2

2.0

B1

100

20 15

0.6 Cinput, mg/L

Average eff. = n/a

25

120

B1

0.2

B4 0

100

B6

B1

B8

80

Average eff. = 52.2%

0.3

80

40

60 Cinput, mg/L

Surfactants

Orthophosphates

60

B8

B6

B4

B3

B7

20

200

2500

Total Nitrogen

60 40

2000

Average eff. = 50.1%

B3

80

1500

Cinput, mg/L

Average eff. = 72.1%

B1

B3

200

Suspended solids B9

0.6

B6

Cinput, mg/L

120 100

0.5

300

B6

B8

0.4

Average eff. = 77.3%

120

40 20

0.3 Cinput, mg/L

COD

Average eff.= 82.6% 100

B9

2.0 1.0

B5

7.8

7.4

Coutput, mg/L

8.6

2.5

3.0

Cinput, mg/L

80 60

B5

40 20 0

B8

B3

B7

B2

B9 20

B6

B4

40

60

80

100

120

Cinput, mg/L

Fig. 3. Output vs. input contents of suspended solids, BOD5, COD, total nitrogen (estimated as a sum of N from measured NO2
, NO3
and NH4+), orthophosphates, surfactants, N–NH4, NO3, pH and DO at studied CWs (B1–B9) with respective removal efficiency (RE): black circles indicate RE more than 80% mean removal; white circles correspond to RE less than 50% and triangles indicate RE from 50 to 80%.

orthophosphatesout (0.73), NH3out–orthophosphatesout (0.77), NO3in–DOin (0.95), NO3out–DOin (0.9), surfactantsin–DOin (0.87), NO3out–pHin (0.7), orthophosphatesout–NH4in (0.73),

orthophosphatesout–NH4out (0.77), while a negative correlation was reported between orthophosphatesout and pHin (
0.74) (Table 2).

Y. Vergeles et al. / Ecological Engineering 83 (2015) 159–168

165

in the same range at both the input and the output. Some slight decrease (by 23 and 35% respectively) in the influents was observed for SS and orthophosphates while their concentrations in the effluents remained steady. The contents of ammonia nitrogen increased respectively by 50% in the influent and by 56% in the effluent. The RE of BOD5, COD and surfactants after implementation of the low-cost CW technology remained similar to the ones reported for the conventional WWTF (80–93%, 80–90%, and 70– 86%, respectively). The RE of SS in CW decreased (32–63% compared to 55–70% in conventional WWTF) but the difference is statistically insignificant (p > 0.05). Nutrients RE in CW on ammonia nitrogen appeared 2.5 and orthophosphates 1.5 lower compared to WWTF, however it falls to the ranges typically reported for CWs (Rousseau et al., 2004; Song et al., 2006; Vymazal, 2009; Vera et al., 2011) (Table 4). Fig. 4. Arrangement of studied CWs (B1–B9) according to their removal efficiency (%).

5. Discussion

4.2. Removal efficiency of constructed wetlands

5.1. Removal efficiency of constructed wetlands

The RE of organics (COD and BOD5) and SS were higher than 50% for all studied CWs. The average RE of BOD5 was 82.6% with the lowest estimation for B8 (72%) and the highest estimation for B2 (93%) (Fig. 4). The average SS removal was 72.1% for the studied sites (Fig. 3), with the lowest estimations for B7 and B8 (40.5% and 21.0% respectively), and the highest estimations for B2 (99.4%) and B5 (89.5%) (Fig. 4). The average RE of COD was 77.3% (Fig. 3), with the lowest estimations for B8 (60%) (Fig. 4) and the highest estimation for B2 (86%) (Fig. 4). The average RE of total nitrogen was 50.1% and NH4 was 51.5% (Fig. 3). The highest RE of ammonia nitrogen was estimated for B2 (94%) and the lowest estimation for B7 (about 0%) (Fig. 4). The average surfactants removal was 52.2% (Fig. 3), with the lowest estimation for B1 (9%), however facilities B2 and B9 showed high RE (89 and 82% respectively) (Fig. 4). The water resident time had a negative correlation with surfactants (Table 3), NH4 and NH3 removal (respectively r =
0.76,
0.78 and
0.78) but a positive one with NO3
removal (r = 0.83). No clear correlation was found between the removal rates and the total treatment area or the discharge across the studied CWs (Table 3).

Taking into account that all studied CWs had the same construction type, were located in quite similar environmental conditions (temperature, solar radiation and humidity) and were planted with the same macrophyte species (Hijosa-Valsero et al., 2012), it was assumed that differences in RE may be attributed to differences in inflow concentrations (Vymazal 2011; Comino et al., 2013), construction work quality and operational conditions (Saeed and Sun 2012; Vera et al., 2013). All studied CWs were designed to treat domestic type of wastewaters contaminated by organic pollutants. Orthophosphates concentrations in studied CWs were higher than the medium value in urban wastewater with a minor contribution of industrial wastewater (10 mg L
1,Henze and Comeau, 2008). The total nitrogen was higher than the medium value (60 mg L
1) in 4 out of 9 CWs while the total COD and BOD5 were higher than its

4.3. Removal efficiency of constructed wetlands vs. conventional wastewater treatment facilities After a CW replaced the secondary treatment units of the former conventional WWTF, BOD5, COD and surfactants remained

Table 5 Calculated BOD5/COD ratio in inlets (Xin) and outlets (Xout). CW

BOD5/CODin

BOD5/CODout

B1 B2 B3 B4 B5 B6 B7 B8 B9

0.4 0.4 0.5 0.5 0.5 0.5 0.4 0.3 0.5

0.3 0.2 0.4 0.4 0.2 0.4 0.2 0.2 0.3

Table 4 Chemical parameters (mg L
1) of inlets and outlets at conventional WWTF (before replacement with the “bioplato” treatment units), at the Khorosheve nursing house CW (site B7) and comparison to similar treatment facilities. Treatment facilities

Control point

Suspended solids BOD5, (mgO2 L
1) COD, (mgO2 L
1) Ammonia nitrogen, Orthophosphates, Surfactants, (mg L
1) (mg L
1) (mg L
1) (mg L
1)

WWTF (2008–2009)

Inlets Outlets Removal

49.0–51.5 16.0–21.5 55–70%

70.4–84.0 6.7–9.0 87–92%

204–320 30.3–40.8 80–90%

14.7–17.7 2.6–3.1 79–85%

6.0–6.8 2.0–2.5 63–66%

0.28–0.40 0.04–0.11 73–86%

CW (2011–2012)

Inlets Outlets Removal

31.2–48.4 15.2–28.8 32–63%

50.2–82.0 6.0–10.0 80–93%

204–392 39.2–40.8 80–90%

23.6–25.1 14.8–21.8 20–45%

3.3–5.0 2.2–2.7 40–46%

0.18–0.24 0.04–0.14 70–83%

CW China (Song et al., 2006) CW Belgium (Rousseau et al., 2004) CW Czech Republic (Vymazal, 2009) CW Spain (Vera et al., 2011)

Removal Average removal Average removal Removal

64–74% 94% 89% 65–87%

63–77% – 91% 76–96%

60–67% 91% 84% –

35–45% 65% (total N) 19% 48–65% (total N)

22–31% (total P) 52% (total P) 40% (total P) 39–58% (total P)

– – – –

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value (respectively 750 and 350 mg L
1, Henze and Comeau, 2008) in 3 out of 9 CW. The SS content was higher than the medium value in urban wastewater (400 mg L
1) in 2 CWs. The BOD5/COD (Table 5) ratio were in the range 0.3–0.5 at the inlet across studied CWs, indicating average biodegradable OM, and in the range 0.2–0.4 at the outlet, indicating slowly to not biodegradable OM (Srinivas, 2008). But studied CW could effectively reduce the output of COD and BOD5 by respectively 82.5% and 77.3% in average. Such relevant COD and BOD5 removal of the CWs was accomplished by synergism between physical and microbial mechanisms, as reported by Song et al. (2006). The removal of SS was low at B7 and B8CW sites, due to reconstruction of the settling tanks. High SS removal was reported at B2 site where a large patch of natural wetland was included into treatment chain thus facilitating the complexation and sedimentation of organic matter. The B5 showed high SS removal rate due to the well-maintained system of mechanical pre-treatment to avoid the secondary outflow of SS from the treatment units. Ammonia nitrogen RE was variable and lower compared to the removal of SS, BOD5 and COD, but it was in the agreement with data reported from different cases (Garcia et al., 2004; Rousseau et al., 2004; Song et al., 2006; Vymazal, 2011). In CWs, ammonia nitrogen is removed by volatilization, adsorption, plant uptake and nitrification (Song et al., 2006; Vymazal, 2011). The pH of studied CWs was less than 9.0, indicating that the ammonia nitrogen losses through volatilization can be neglected (Song et al., 2006). High ammonia nitrogen RE (more than 80%) was detected at B2 and B9. The B2 had the largest area (11,000 m2) among studied CWs and was vastly covered by natural vegetation (more than 80% of the reed bed) that likely stimulated the ammonia nitrogen uptake by plants. The B9 had very small area and small quantity of wastewaters that together with the high residence time (15 days) facilitated the removal of ammonia nitrogen at higher rates. Another feature of B9 site that may stimulate the nitrification was the highest level of DO which implied high oxygen consumption by plants, microorganisms and (Vymazal 2011). The low RE of ammonia nitrogen at B1 and B8 can be explained by relatively small area of the reed beds (760 m2 and 1550 m2 respectively) and high input concentration of total nitrogen (Vymazal 2011) that was not eliminated by plants uptake (Vymazal 2005). Orthophosphates removal in CWs takes place by plant uptake, accretion of wetland soil, microbial immobilization, retention by root media and precipitation in water column (Song et al., 2006; Vymazal 2011). The B1, B5, B6, B7 and B8 showed low orthophosphates RE (more than 50%). Among them B1 and B7 showed the lowest RE of orthophosphates, possibly, due to the small area of reed beds (Table 1) that was not sufficient for

effective biological treatment. Additionally B1 had the high inflow concentration of total nitrogen and orthophosphates (Comino et al., 2013). The reasons of high inflow concentrations of total nitrogen and orthophosphates were explained by discharge from the local small cheese factory to the CW, which was not initially designed for such type of wastewaters. Surfactants were removed at the efficiency is less than 50% at most of CWs: B1, B3, B4, B6, B7 and B8. The reduction in removal capabilities of CWs is often related to functioning and/or maturation issues (clogging, shading, matrix, saturation, decrease in retention time, appearance of preferential hydraulic pathways, etc.) and the system enhancement and continuous control could increase the RE of CWs (Hijosa-Valsero et al., 2012). Although in this study performance of CWs was not assessed for winter season. The experience obtained from investigating one of the oldest treatment wetland sites in the region at the Velyki Prokhody village (operating since 1998 without any capital renovation) showed that mean pollutant RE did not much depend on the season (Vergeles et al., 2014). Thus, BOD5 removal at this CW facility in 1998–2012 was estimated as 90.74  1.98% in winter vs. 93.23  1.40% in summer, SS were removed at 91.81  6.53 % vs. 88.60  3.80%, ammonia—at 52.70  11.26% vs. 43.47  8.27%, surfactants—at 77.65  4.88% vs. 79.66  5.98%, and RE for Coliforms ranged from 98.35 to 99.90% in both warm and cold seasons (differences are not significant with the Student’s t-test at p > 0.95). Relatively high efficiency of CWs in winter period may be attributed to the influent wastewater temperature ranging from +9  C to +14  C, and the exothermic character of processes of biogenic transformation of organic pollutants involving microorganisms associated with the macrophytes' rhyzosphere. 5.2. Cost effectiveness of CWs vs conventional WWTF Wastewaters of the most of small towns and rural settlements in Ukraine have not been properly treated because of lack of funds for the construction of conventional facilities, shortage in energy supply and obsolescence of conventional wastewater treatment facilities. Today, more attention is paid on the use of CWs as an environment-friendly alternative treatment option. It was compared the construction costs of conventional WWTF and CWs (Fig. 5). It was found that the construction costs of CWs were about a half of those for the conventional facilities, thus making the CWs as a cost-effective technology for the grey water treatment in small communities in Ukraine. At the same time, the conventional WWTF and CWs have comparable RE of BOD5, COD, SS and surfactants. The adjustment of

Fig. 5. The comparison of the construction costs of traditional wastewater treatment facilities and CWs in Ukraine.

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CWs as an ecological engineering system during treatment, i.e., providing for longer residence time, relevant operational conditions, control of inflow concentration, as well as an established microbial community and vegetation might improve the overall efficiency of CWs. It has been noted that not every CWs among the assessed ones in this study was properly supervised and maintained as some communities where the facilities were built assigned a personnel for doing so. In general, higher efficiency was assessed for those CWs where at least a minimum maintenance was applied (e.g., B2, B4, B5, B6, B7, B9 vs. B1, B3, and B8). The minimum maintenance include: (1) keeping unit surface wet but non-flooded while macrophytes emerge, (2) keeping stable wastewater table level as required for summer and winter operation regimes, (3) cleaning sedimentary tanks and removal of excess sludge when needed, (4) measuring wastewater flow rate; (5) regulate extra wastewater volume to prevent treatment units overfilling, (6) overall supervising and keeping the constructed wetland site in proper conditions. Generally, RE of the assessed CWs in East Ukraine showed a good correspondence to the reported in the literature retention rates of common wastewater pollutants in treatment wetlands (e.g., Kadlec and Knight, 1996; Mitsch and Jørgensen, 2004). 6. Conclusions Our results revealed that CWs in Kharkiv region were efficient to remove organics (by BOD5 and COD indicators) and SS from domestic wastewaters of small rural communities. The RE of contaminants at CWs was mainly dependent on inflow concentration, design, maintenance parameters and operating conditions. At the same time the RE of nutrients were less than 50%. The comparisons on the RE of conventional WWTF and CWs showed that CW has the same level of the RE of organics (measured as BOD5 and COD) as WWTF. The lower construction and maintenance costs compared to the conventional WWTF make CWs attractive for the small communities and rural area. But in order to increase the removal capacity of wetlands, operational conditions should be adjusted to the inflow concentrations and received wastewater volume. The further development of the research will be focused on the nitrogen removal in CWs, as it had the high variation in terms of the RE, so the factors of the influence should be additionally studied. Acknowledgements The research has been financed by the Kharkiv Regional State Administration in the framework of the project “The technical audit and control of treatment efficiency of the phytotechnology facilities ‘bioplato’ designed and operated in the Kharkiv region” (Contract N16 of 12.06.2012). One of the author was granted by SAIA, National Scholarship of Slovak Republic. References AISE, 2013. International Association for Soaps, Detergents and Maintenance Products. Guidelines on the Implementation of Detergents Regulation, vol. 2, 3 June 2013. Arias, M.E., Brown, M.T., 2009. Feasibility of using constructed treatment wetlands for municipal wastewater treatment in the Bogota Savannah, Colombia. Ecol. Eng. 35, 1070–1078. Biddlestone, A.J., Gray, K.R., Job, G.D., 1993. Treatment of dairy farm wastewaters in engineered reed bed systems. Process Biochem. 26 (5), 265–268. Breckenridge, R.P., Wheeler, L.R., Ginsburg, J.F., 1983. Biomass production and chemical cycling in a man made geothermal wetland. Wetlands 3 (1), 26–43. Brisson, J., Chazarence, F., 2009. Maximizing pollutant removal in CWs: should we pay more attention to macrophyte species selection. Sci. Total Environ. 407, 3923–3930. Brix, H., 1997. Do macrophytes play a role in constructed treatment wetlands. Water Sci. Technol. 35 (5), 11–17.

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