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Criticaldesignparametersofsubsurfaceflowconstructedwetlandsfortheremovaloforganicmicropollutantsfromwastewater
Ekaterina Naipal
March 2014
Wageningen University, Wageningen
Supervisors:
Peter van der Maas
Alette Langenhoff
Examiners:
Huub Rijnaarts
CONFIDENTIAL
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Abstract
The field of organic micro pollutants removal by Constructed wetlands is less explored than the
application of constructed wetlands on the removal of biological oxygen demand and
Nitrogen/Phosphorus. This study was conducted to evaluate the removal efficiency of sub‐surface
flow constructed wetlands for pharmaceuticals and personal care products and formulate
recommendations for a sub‐surface flow constructed wetlands with an improved removal of
pharmaceuticals and personal care products and the conventional pollutants (biological oxygen
demand, total suspended solids and Nitrogen/Phosphorus).
Two sampling campaigns were conducted in 2013, one in July and the other in November in vertical
flow constructed wetlands at four different locations. During these sampling campaigns samples
were taken to measure the concentrations of the pharmaceuticals and personal care products (29
different compounds) and the conventional pollutants (biological oxygen demand, total suspended
solids and Nitrogen/Phosphorus) in the influent and effluent. The performance of the wetlands was
analysed from these concentrations.
The removal of the pharmaceuticals and personal care products was very efficient (≥90%) for the
compounds that were classified as easily biodegradable in literature. Overall the removal rates were
in accordance with the biodegradation rates from literature. The average removal efficiencies
reached in activated sludge systems from other studies were similar to the removal efficiencies
reached in this study, for the readily and partially biodegradable pharmaceuticals and personal care
products. A significant correlation between the loading rate and the removal rate was found for the
majority of the pharmaceuticals and personal care products. The area of the wetland and the flow
rate of the feed water can be adjusted to reach higher loading rates and consequently reach a higher
removal rate, because of the significant correlation found between these two variables. As for the
limiting design parameters, the literature proposed HRT. The estimated HRT for the four wetlands
are in the range of 7.5‐12 days. These values are much higher than the ones reported in literature.
The removal of biological oxygen demand, chemical oxygen demand and total suspended solids was
efficient in all wetlands, while nitrogen and phosphorus removal showed some variability in the
removal efficiencies.
Keywords: Waste water treatment, sub surface flow constructed wetlands, personal care products,
pharmaceuticals, design parameters.
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Contents Abstract ................................................................................................................................................... 2
Acknowledgements ................................................................................................................................. 4
1. Introduction ..................................................................................................................................... 5
2. Methodology ................................................................................................................................... 8
2.1 Literature research ........................................................................................................................ 8
2.2 Data collection for performance evaluation ................................................................................. 8
2.3 Results evaluation ....................................................................................................................... 11
3. Constructed Wetlands and waste water treatment ..................................................................... 12
3.1 General characteristics of Constructed Wetlands ....................................................................... 12
3.2 Description of design parameters that affect removal mechanisms .......................................... 16
3.3 Relations between the design parameters and the removal efficiencies of PPCPs .................... 19
3.4 Common problems in the design of SSFCWs .............................................................................. 20
3.5 Removal mechanisms of organic micro pollutants ..................................................................... 21
3.6 Removal kinetics of organic micro pollutants ............................................................................. 23
3.7 Nitrogen (N) and removal ............................................................................................................ 24
3.8 Phosphorus (P) removal .............................................................................................................. 25
3.9 Removal of BOD .......................................................................................................................... 26
4. Performance evaluation of full scale CWs ......................................................................................... 26
4.1 PPCP removal .............................................................................................................................. 27
Influence of design parameters on PPCP removal ........................................................................ 27
Comparison with literature values ................................................................................................ 36
4.2 BOD, COD and TSS removal ......................................................................................................... 39
4.3 Nitrogen removal ........................................................................................................................ 41
4.4 Phosphorus removal evaluation .................................................................................................. 44
5. Discussion .......................................................................................................................................... 47
6. Conclusion ......................................................................................................................................... 50
7. Recommendations............................................................................................................................. 52
References ............................................................................................................................................. 53
Abbreviations .................................................................................................................................... 56
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Acknowledgements
I would like to express my appreciation in the first place to my supervisors Peter van der Maas and
Alette Langenhoff. They guided me through writing my thesis in a very supportive and patient way.
Their enthusiasm towards their profession was always a motivation for me to improve my work. My
special appreciation to Alette, because she made time and effort to go through my thesis report and
give critical comments even though she was in a critical health condition. I wish her a quick recovery.
To Peter: Thank you for introducing me to the subject of organic micro pollutants removal by
constructed wetlands. I find it a very interesting topic and worthy of continuing with this in my future
career if I get the possibility.
I also want to thank the department of Environmental Technology of Wageningen University. They
provided me with the facilities to study and write my thesis in a nice ambience.
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1. Introduction
Water treatment is a relevant topic for research since the world’s scarce fresh water reservoirs are
being threatened by the pollution with waste water streams from industrial and municipal areas. Our
study focuses on Identifying critical design parameters of a sub‐surface flow wetland to remove
organic micro pollutants. The focus is made on pharmaceuticals and personal care products (PPCPs),
but the conventional pollutants in domestic waste water: biological oxygen demand (BOD), chemical
oxygen demand (COD), total suspended solids (TSS), Nitrogen and Phosphorus are also taken into
account. This chapter describes the fundamental characteristics of this topic to emphasize the
relevance and significance of this study. Furthermore, the aim, the objectives and the research
questions to our research are presented.
Pollutants in domestic waste water
Wastewater contains nutrients in large concentrations (mainly nitrogen and phosphorus). Discharge
of nutrient rich water into natural water systems can result in eutrophication. In addition, pathogenic
bacteria can be present, causing diseases. Pathogen removal form wastewater streams is therefore
very important. Besides the nutrients and pathogens, municipal waste water also contains a lot of
organic matter, expressed as biological oxygen demand (BOD). Primarily microorganisms break down
organic matter by using oxygen. In other words, BOD is the amount of oxygen needed for the
microorganisms to break down the organic matter in the water. BOD needs to be treated as well,
because a high BOD concentration results in accelerated microbial growth and subsequently in
anaerobic conditions. Water without enough dissolved oxygen cannot support aquatic life. Finally,
waste water streams also have to be treated for suspended solids, because they increase turbidity
levels of the water. Turbid water is not a healthy environment for aquatic life, because it decreases
the abundance of food for the fish and can result in decreased reproduction in some fish species
(Lloyd, 1987).
The pollutants mentioned above (nutrients, BOD and suspended solids) are commonly found in
domestic waste water and in relatively high concentrations. Waste water is primarily treated from
these pollutants in order to be considered safe for discharge in the environment.
However, domestic waste water also contains another pollutant in lower concentration that can be
harmful to the environment: organic micro pollutants (OMP) in the form of pharmaceutical residues,
drug metabolites, pesticides, dyes, explosives, phenolic compounds, petroleum hydrocarbons, and
hormones (Heberer, 2002; Dordio et al., 2013). After discharge into surface waters these organic
micro pollutants can enter freshwater catchments that serve for drinking water mining. OMP that
enter freshwater systems can be harmful to aquatic organisms, but for also for public health after a
long‐term ingestion of contaminated drinking water (Daughton and Ternes, 1999).
Constructed wetlands
These OMP’s are not completely removed in activated sludge treatment plants (Heberer, 2002; Avila
et al., 2013). Nowadays there is a growing interest in applying constructed wetlands (CWs) as a
treatment system for waste water streams, mainly due to their flexible and relatively easy
implementation. Studies have shown CWs to have a potential to remove OMP from waste water and
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reach removal efficiencies as high as activated sludge systems (Avila et al., 2013; Hijosa‐Valsero et al.,
2010; Matamoros et al., 2005). They are therefore an interesting competitor of conventional waste
water treatment plants. CWs are built wetlands that imitate a natural system. The application of CWs
on the removal of various compounds has been investigated broadly. It is already known what
possibilities CWs offer for the treatment of domestic waste water from nutrients (nitrogen and
phosphorus) BOD, suspended solids and pathogens. Data can be found in literature on removal
efficiencies, removal mechanisms and rates and design recommendations for these pollutants (Avila
et al., 2013; Clara et al., 2005; Heberer, 2002; Hijosa‐Valsero et al. 2010; Joss et al., 2006; Majewski
et al., 2011; Matamoros et al., 2007; Matamoros and Bayona, 2006; Simpa et al., 2010; Verlicchi et
al., 2012). However, the application of CWs on the removal of OMP has been poorly investigated. As
a consequence, the applicability of CWs on the removal of OMP in waste water is not well known at
the moment. Therefore it is important to determine the design parameters of CWs that are critical
for improving their removal efficiency for OMP.
The application of CWs to remove OMP in domestic waste water is challenged by the efficient OMP
removal in activated sludge water treatment plants and in advanced water treatment systems.. The
advanced water treatment systems are ultra sound bioreactors, membrane bioreactors and
ozonation and those are known to remove OMP to a certain extent (Avila et al 2013). Still, CWs have
several advantages over these advanced treatment systems, because of the following reasons:
Advanced water treatment systems are more expensive to setup and to maintain, because
they are constructed of many distinct and expensive parts (like membranes in the membrane
bioreactor) and they need addition of chemicals to induce the removal processes (oxidizing
agents for ozonation). Pre‐treatment might be necessary to avoid damage to sensitive parts.
CWs have a self‐sustaining operational process, whereas advanced water treatment systems
must be maintained and serviced.
CWs can be applied on small and large scale and on all types of waste water (with additional
pre‐treatment when necessary). This makes them flexible in application.
The design of SSFCWs allows for the coexistence of aerobic an anaerobic zone and therefore the
coexistence of anaerobic and aerobic microorganisms. CWs allow for the use of different types of soil
and gravel material to maximize physical‐chemical removal of pollutants. All these condition in one
system allow for the coexistence of various microenvironments in one system. This is very
advantageous to remove PPCPs (Hijosa‐Valsero et al., 2010) This suggests that CWs definitely must
be able to degrade PPCPs to a certain extent. The results from this study together with literature
data will indicate to which extent the degradation can be achieved and also the results will provide a
comparison with other treatment systems like activated sludge.
In our research we focus on SSFCWs. Their characteristics and their operating process will be
described in the next chapters.
Aim:
Determine the critical design parameters of a SSFCW for the removal of organic micro pollutants and
to a lesser extend nitrogen, phosphorus, BOD and TSS from domestic and agricultural waste water.
Research questions:
What are the mechanisms and rates for removal of organic micro pollutants?
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What is the performance of the wetlands on BOD, TSS, nitrogen and phosphorus removal?
Which design parameters are critical for enhancing the removal efficiency of organic micro
pollutants, BOD, TSS, nitrogen and phosphorus in SSFCWs?
Which design parameters are limiting to the treatment process?
The next chapter presents Methodology that is used in this research..
Chapter 3 gives an elaborated description of literature review with a description of CW in general,
removal mechanisms and kinetics of OMP and the removal mechanisms of nitrogen, phosphorus,
BOD and pathogens. Chapter four presents the results of the sampling campaigns and the analysis of
the collected data. Chapters 5, 6 and 7 present discussion, conclusions and recommendations
respectively.
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2. Methodology
This chapter gives detailed information about the methodology used in this study to collect data for
answering the research questions. The methodology consists of the following steps:
Literature research
Data Collection
Results evaluation
In the following paragraphs all the above mentioned steps are described in detail.
2.1Literatureresearch
In the literature research studies are include that evaluated the removal of PPCPs in CWs and in
activated sludge systems. Theory on removal mechanisms for PPCP degradation in CWs and theory
on removal kinetics will be used to get an understanding of the processes involved in removing the
PPCPs from waste water. From these processes design parameters important for degrading PPCPs
can be determined. During results analysis special attention will be paid to the design parameters
that are pointed out to be critical according to literature. The data on removal efficiencies from these
previously conducted studies will be used to compare with the results from this study. Any
differences can indicate a possibility for improvement by adjusting design parameters.
2.2Datacollectionforperformanceevaluation
To collect the necessary field data two sampling campaigns were performed in four different
wetlands. The first sampling campaign was conducted in the period of 14 to 19 June 2013 and the
second sampling campaign was conducted in the period of 4 to 8 November 2013. The sampling
locations were SSFCWs, already several years in operation. The four locations are:
Groningen (Location A) Culemborg (Location B)
Erica Hotel (Location C)
Single house (Location D)
All the CWs are designed and build by the company Brinkvos. This company uses the same guidelines
to design all their wetlands. The overall design of these wetlands is presented as a scheme in figure 1.
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Figure 1. Typical design of wetlands built by Brinkvos
Brinkvos uses sand as granular medium with a thin top layer of shells and also a bottom layer of
shells. In between these layers the pipes for supplying influent and collecting effluent are placed.
Brinkvos uses reeds as plants.
Table 1. Dimensions of the SSFCW
Dimension Location A Location B Location C Location D
Type wetland VFCW VFCW VFCW VFCW
Area (m2) 1000 1500 210 30
Depth (cm) 100 100 100 100
Volume (m3) 1000 1500 210 30
Flow (m3/h) 1.042 1.042‐1.292 0.35 0.044
Type waste water Grey water Grey water Grey water+
septic tank
effluent
Grey water+
septic tank
effluent
Table 2 presents the three categories with the collected and analysed measurements:
Water quality parameters
Nutrients
PPCPs
Table 2. Categories of collected data during sampling campaigns
Water quality data PPCPs (µg/L) Nutrients
BOD Carbamazepine Kjedahl nitrogen (mg N/L)
COD Ibuprofen Nitrite NO2‐N (mg N/L)
DO Sulfamethoxazole Nitrate NO3‐N (mg N/L)
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pH Atenolol Total nitrogen (mg N/L)
Temperature Diclofenac Total Phosphate PO4‐P (mg P/L)
Conductivity Ketoprofen
Naproxen
Paracetamol
Metoprolol
Propranolol
Sotalol
Lidocaine
Avobenzon
Benzalkonium chloride
Benzophenone‐3
Bisphenol A
Bisphenol A diglycidyl ether
Bisphenol F diglycidyl ether
Butylparaben
Ethylparaben
Methylparaben
Phenylbenzimidazole sulfonic acid
Propylparaben
Triclocarban
Triclosan
2,4‐dichloorfenol
Hexylcinnamaldehyde
2‐ethylhexylsalicylaat
Galaxolide
Tonalide
4‐methylbenzylidene Camphor
Ethylhexyl Methoxycinnamate
Methyltriclosan ()
Octocrylene ()
Caffeine ()
The list of PPCPs presented in table 2 was composed based on the PPCPs that could be analysed by
the laboratory that performed the analysis of PPCPs.
Except from the data collected in the field, literature data was also collected form previously
performed studies on this topic. Literature research was done on:
Mechanisms and rates for the removal of organic micro pollutants, nitrogen, phosphorus,
BOD, TSS.
Relationship between removal mechanisms/rates and design parameters for the
improvement of removal efficiency
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2.3Resultsevaluation
This part is about analysing the collected data to answer the research questions. The collected data
from the monitoring campaign together with the information form literature review is used to
determine critical design parameters of SSFCWs for the removal of BOD, COD, N/P and PPCPs. The
data mentioned in table 6 is analysed to evaluate the performance of the wetlands and ultimately to
evaluate how design parameters affect the performance of the wetland in removing BOD, COD, N/P
and PPCPs. The analysis is performed according to the following structure:
1. Evaluation of removal of conventional pollutants BOD, COD, TSS and N/P) by:
a. Comparing removal efficiency and effluent concentrations for BOD, COD, N/P
between the different locations.
2. Evaluation of PPCP removal
a. Measuring the average removal rate and removal efficiency of the PPCPs .
b. Comparing removal efficiencies of PPCPs in our study with literature data (taking into
consideration the influent and effluent concentration). This will give an immediate
impression on the ability of SSCWs to remove PPCPs.
3. Analysis of the influence of design parameters on PPCP removal
a. Analyse how the design parameters pointed out by literature, are of significance in
this study.
b. Plotting removal rates against specific loading rates for PPCPs. From this can be
derived if there is a trend between these variables. The loading rate is dependent on
design parameters area and flow rate. If a significant trend between the removal arte
and the loading rate is found, these design parameters might be used to influence
the PPCP removal.
c. Observing difference in result of removal efficiency/rate of a certain PPCP at a
certain location. Any deviations in the trend must be caused by design parameter(s)
that deviate for that certain location at that time. These design parameters can be
categorized as critical in influencing the removal efficiency of that particular PPCP.
The focus of this study is on the removal of PPCPs. That is the reason for analysing the design
parameters only in relation to the removal of the PPCPs. The collected data of the other pollutants
(BOD, COD, N/P) is only used to evaluate if the wetlands are performing well. If not,
recommendations will be given to adjust this.
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3. ConstructedWetlandsandwastewatertreatment
3.1GeneralcharacteristicsofConstructedWetlands
Introduction to Constructed wetlands
As mentioned in the Introduction, CWs are wetlands that imitate a natural wetland system. This
chapter presents different types of constructed wetlands and the design of a constructed wetland
with its main components will be discussed.
CWs are generally divided into three groups (Kadlec & Wallace 2009; Tsihrintzis and Gikas 2010):
Horizontal sub‐surface flow wetlands (HSSFW)
Vertical flow wetlands (VFW)
Free water surface flow wetlands (FWSW)
In HSSFWs the water is delivered from the storage tank into the bed of the wetland in a horizontal
manner (figure 2). In a VFW the influent enters the bed form the surface of the wetland and flows
vertically till it reaches the bottom of the bed. Hereafter it is collected in pipes and flows further in a
horizontal stream (figure 3). HSSFWs and VFWs belong together to the category of sub‐surface flow
constructed wetlands (SSFCWs), because they have both the characteristic of water flowing through
the gravel medium and not on the surface. FWSW are the simplest case of wetlands where the
waste water flows on the surface with either floating plants or emergent plants (figure 4). FWSWs
have a clearly visible and measurable water level. In HSSFWs and VFWs the water flows in between a
gravel medium that can consist of gravel, sand or adsorptive material. In this case the water level is
not visible.
Figure 2. Horizontal Flow Constructed Wetland (Vymazal, 2007)
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Figure 3. Vertical Flow Constructed Wetland (Vymazal, 2007)
Figure 4. Two types of free water surface Flow Constructed Wetland (Vymazal, 2007)
Differences between HFCWs, VFCWs and FWSWs
One difference between HFCWs and VFCWs is their oxygen availability (Randerson, 2006). In HFCWs
the wastewater is pumped into the wetland from the storage tank, right into the gravel medium of
the bed. Therefore it does not have contact with the outside air and thus does not take oxygen into
the bed. Oxygen reaches the wetland through diffusion of oxygen form the surface to the water in‐
between the gravel in the bed and through the roots of the plants. By this limitation of oxygen in
HFCWs, some pollutant removal mechanisms are limited. In VFCWs on the other hand, oxygen is also
supplied to the system together with the water that enters the wetland through the surface of the
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bed and flows downwards through the layers of the bed (Randerson, 2006). In VF wetlands the water
is distributed over the surface area of the wetland by pipes. During the infiltration to the bottom, the
water is able to dissolve oxygen that is present in the pores of the surface layers of the wetland.
Another difference between HFCWs and VFCWs concerns their hydraulic conductivity (VROM/Kiwa,
1998). In HFCWs an adequate hydraulic conductivity is harder to achieve than in VFCWs. This is
because in HSSFWs the hydraulic conductivity depends on the slope of the bed, whereas in VFWs,
the water is moved through the bed by gravity force from surface to bottom. Also the hydraulic
conductivity depends on the type of material used as medium in the bed. Sand is less suitable for
HFCWs, because the horizontally formed pores collapse more easily than the vertically formed pores
in VFWs. To avoid this problem, the medium of the HSSFW has to have a sand‐clay mix to support the
growth of plants and also gravel to support the formation of pores (VROM/Kiwa, 1998).
FWSW significantly distinguishes itself form the HFCW and the VFCW due to the absence of
gravel/sand medium that serves as a filter in the HFCW and the VFCW. In FWSW with emergent
plants soil on the bottom of the bed is only present to support the roots of the plants.
The interconnected biological system of a CW
This report focuses on HSSFWs and VFWs, because they can remove pollutants more efficiently than
other types of CWs. The combination of plants, the porous medium and the microorganisms is the
reason for that. HSSFWs and VFWs are composed of three main components: plants, soil and
microbes. These three components are interconnected like depicted in figure 5.
Figure 5. The interconnected biological system of a CW (Randerson, 2006)
The soil provides support to the roots of the plants. It is also the support material on which the
microorganisms live, in the form of biofilms. If the soil or gravel also has adsorbing properties it
contributes to the removal of pollutants from the wastewater by adsorbing them. The plants feed on
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the nutrients that are supplied by the waste water and on small organic molecules that are produced
when organic matter from the wastewater is broken down by the microbes. This altogether severs in
the removal of pollutants.
Design of a SSFCW
HFCWs and VFCWs consists of the following parts (Akratos et al,. 2007):
Inflow tank
Inflow pump
Porous medium
Plants
Effluent tank
The Influent tank receives the wastewater from the sources of production and gradually pumps it
into the porous medium of the bed. The main part of a SSFCW is the bed, which consists of the
porous media and the plants (see figure 6). The porous medium, consist of gravel of various sizes.
The porous medium filtrates the wastewater. Large particles settle on the gravel or are retained due
to friction. Another main purpose of the gravel is to act as supporting material on which
microorganisms can grow into a biofilm. The microorganisms remove pollutants form the
wastewater by breaking them down. The porous medium can also adsorb pollutants if it can act as an
adsorbent (like activated carbon). Plants are also an integral part of the SSFCWs, because they also
contribute to the pollutants removal. By taking up nutrients (nitrogen and phosphorus) they reduce
the overload of nutrients in the waste water. The effluent tank receives the treated water and stores
it until it can be discharged into the environment.
Figure 6. A schematic representation of a sub‐surface flow constructed wetland (Akratos et al., 2007)
Design parameters of constructed wetlands
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3.2Descriptionofdesignparametersthataffectremovalmechanisms
This paragraph discusses how the removal can be enhanced by adjusting the design of a SSFCW. The
design parameters that will be discussed in this chapter will be divided into the following categories:
Hydraulic design parameters
Wetland dimensions
Granular medium
Plants
Table 3 presents the design parameters that belong to these categories.
Table 3. Design parameters
Hydraulic
design
parameters
Wetland
characteristics
Granular medium Plants
HRT Water depth Effective grain size Type of plants
Hydraulic
conductivity
SRT Mineral content Presence vs.
absence of plants
Hydraulic design parameters
Hydraulic retention time (HRT) is an important design parameter affecting the effluent water quality
(Hijosa‐Valsero et al., 2010; Rai et al., 2013; Verlicchi et al., 2013). The HRT is the average residence
time of the water in the wetland. The HRT can be defined by equation 4 (Kowalik et al., 2004).
tr = HRT (d)
V = capillary capacity of the wetland (equal to water volume of the bed) (m3)
Q = flow rate (m3/d)
HRT has to be long enough to allow the removal processes to take place: settlement of suspended
solids, adsorption and biodegradation/transformation of suspended and dissolved organic
compounds. If that doesn’t happen, the pollutants will be washed out with the effluent. Rai (2013)
showed that a HRT of 12 hours leads to a decrease in NO3‐N, NH4‐N, PO4‐P, BOD and TSS with
49.2%, 33.5%, 33.6%, 6.6% and 15.3% respectively. It also resulted in an increase in DO. Li et al.
(2014) reports an average HRT of 1‐2 days for VFCWs .
Hydraulic conductivity (with unit m/d) is a parameter that indicates the ease with which water can
flow through the gravel bed. It depends on the available volume of the wetland. The available
volume is a sum of all the empty spaces and the pores in the bed. In other terms: the hydraulic
conductivity states the relation between friction and water velocity (Kadlec & Knight, 1996). In order
to be able to calculate the hydraulic conductivity we must make a distinction between two types of
(4)
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flow regime: laminar and turbulent flow. In a SSFCW the size of the granular media is determining for
the type of flow regime (Kadlec & Knight, 1996). The hydraulic conductivity is an important design
parameter, because it determines how well the wetland functions as a filter or how clogged the
wetland is (a constraint to efficient filtering from suspended solids). For waste waters with a high TSS
concentration the hydraulic conductivity must be higher compared to waste waters with a lower TSS
concentrations, to allow passing through of the water and prevent clogging.
Temperature (Zhang et al., 2012b)
Dissolved oxygen
Nitrification and microbial respiration for the breakdown of organic matter depend on the DO
concentration in water. The loading rate of organic matter should not exceed the aeration capacity of
the wetland (Al‐Omari and Fayyad, 2003). Thus, the minimal required DO concentration to assure a
efficient removal of organic matter depends on the loading rate of the organic matter. The higher the
loading rate, the higher the DO must be (Al‐Omari and Fayyad, 2003).
CWs often have both aerobic and anaerobic sections in their bed. The top section can still be aerobic
as oxygen can penetrate through the pores. For CWs with a deep bed the DO can be improved by
using aquatic plants with a large root system (Rai et al., 2013). Aquatic plants facilitate their
submerged root system with oxygen by transferring oxygen from the leaves to the roots. The part of
the oxygen not utilized by the roots, the rest is released in the surrounding environment. The water
receives additional DO by this system. Rai et al showed that stabilized CWs (CWs that have been in
operation for 6 months) had the highest DO concentration. This aspect of increasing DO is important
for the aerobic removal mechanisms.
Wetland characteristics
Increasing the water depth can increase the effluent COD concentration. Garcia et al (2005) explains
that shallow beds allow energetically more favourable biochemical reactions to take place for the
removal of COD. Also, with increasing depth, the DO concentration decreases, impeding the oxygen
depending reactions. In other words: water depth influenced the redox conditions of the bed. Like
Garcia et al. (2005), Matamoros and Bayona (2006) also state that the water depth influences the
removal efficiency. They explain it with the higher redox potential that is reached in shallower beds.
Sludge retention time (SRT) defines the time that the microorganisms (in the form of sludge) are
retained in the system (Clara et al., 2005). This time depends on the maximum grow rate of
microorganisms: The higher the maximum grow rate the faster they reproduce and consequently
they do not need to be retained in the system as long as slow growing microorganisms (Clara et al.,
2005). The SRT is therefore an important design parameters for all waste water treatment plants
(WWTPs) that perform on biodegradation/transformation of pollutants. The SRT of WWTPs
determines which microorganisms will be retained and which will be washed out. This influences the
specific removal pathways that can take place in the WWTPs. High SRTs support the variety of
removal pathways that can take place and therefore also supports the removal of a broader variety
of pollutants with accordingly lower effluent concentrations of pollutants.
The minimal SRT for the removal of PPCPs has to correspond with the SRT for N, P, and BOD a
removal (Clara et al., 2005). If the SRT for PPCPs is much higher a choice must be made between the
18
removal of the usual pollutants and PPCPs depending on the maximal SRT that can be applied in the
waste water treatment system of interest. In conventional WWTPs like activated sludge systems,
excess sludge is being removed to maintain a constant available volume for the waste water. In CWs
on the other hand the sludge is not being removed on purpose. The removal of sludge in CWs is only
dependent on the decay rate of the microorganisms. This results in SRT much higher than in
activated sludge systems, membrane bioreactors and other WWTPs depending on sludge retention.
Granular medium
Important characteristics of the granular medium in the wetland are (Arias et al., 2001; Li e al., 2014):
1. Size of granular medium ==> hydraulic conductivity
2. Mineral content ==> physio‐chemical removal mechanisms
1. Size of granular medium
Beds with smaller gravel size showed better effluent quality and higher removal efficiency (Garcia et
al., 2005). This can be explained due to the higher available area on the smaller gravel, which allows
for more microorganisms to attach onto it. Arias et al. (2001) explains another impact of the granular
size on the pollutant removal mechanisms: change in hydraulic conductivity. The hydraulic
conductivity is a measure for the filtration capacity of the wetland (elaborated under ‘hydraulic
design parameters earlier in this paragraph).
2. Mineral content
Ca, Mg, Fe and Al are the minerals that have a role in physio‐chemical removal mechanisms of
phosphorus (Arias et al., 2001). Phosphor is removed mainly by plant uptake and incorporation into
the matrix of Al and Fe colloids (Rai 2013).
Plants
In the first place the roots of the plants are very useful for oxygen supply and for the uptake of
nutrients. As mentioned in chapter 4, plants take up soluble forms of nitrogen and phosphorus. This
is one of the removal mechanisms for nutrients from waste water. Furthermore, plants can aid the
removal of PPCPs like caffeine (Hijosa‐Valsero et al. 2010). A downside of plants in a CW is that they
take up some of the available space in the bed. This can lead to an increased friction force on the
water flow, which will reduce the hydraulic conductivity (Pedescoll et al., 2013). Ranieri et al. (2011)
adds to this that plants form an obstruction for photolytic reactions in the wetland, because they
cover the surface of the wetland and prevent sunlight to reach the water. Photolytic reactions are
possible removal mechanisms for PPCPs like paracetamol (Ranieri et al., 2011). But light attenuation
by the plants can also be an advantage, because this prevents algae to grow (Brix 1997). Despite the
disadvantages, plants aid in the removal of pollutants in many ways and their presence is very
important.
Rai (2013) showed a correlation between the water quality and the development of plants in the
wetland. Reduction of BOD, TSS, TDS, N/P increased the growth of the plants. A settlement tank
might be important in the first stage of the CW, for at least 6 months after it has been build, because
during this time the plants still have to grow. Until they are full‐grown their maximum removal
capacity is not reached. Also they are more vulnerable to toxins during this time (Rai et al., 2013).
19
3.3RelationsbetweenthedesignparametersandtheremovalefficienciesofPPCPs
In this paragraph we describe which design parameters mentioned in paragraph 5.1 influence the
removal processes of PPCPs.
Relation between HRT and half‐life of PPCPs
Verlicchi et al. (2012) mentions 2 sources that agree on the fact that only the removal of
biodegradable pharmaceuticals is influenced by the HRT. Biodegradable pharmaceuticals need a
specific time (half‐life) to reduce their concentration with a half. If the HRT is lower than the half‐life,
the pharmaceutical compound will be removed inefficiently, because it has not been allowed to stay
in the system long enough to be degraded. For slow degradable compounds, the HRT is not
influential, because their half‐life is very long. The half‐life of a compound can therefore be
considered to be the minimum residence time of a compound in the wetland. The half‐life can be
calculated by the following relationship (Verlicchi et al., 2012):
t1/2 = (ln2/k), where
t1/2 = half life
k = loss rate constant
k = ln(Cinf/Ceff)/t
Relation between DO and biodegradability of PPCPs
Dissolved Oxygen (DO) is a measure for the redox potential of the CW. Usually higher redox values
promote the degradation of PPCPs, but for some PPCPs, anaerobic conditions are favourable (Hijosa‐
Valsero et al. 2010). Thus a system combining both aerobic and slightly anaerobic conditions would
allow the removal of a broader scope of PPCPs. DO is also important for the microbiological
degradation of BOD and TSS.
Ibuprofen is removed mainly by aerobic biodegradation. This can be translated into the availability of
oxygen to be the determining parameter for the removal of this compound. Adjusting the design to
increase the DO in the system can be achieved by:
keeping bed depth low enough to achieve homogenous distribution of oxygen
Adding plants to the wetland
Hydrophobicity
Hydrophobicity is an important characteristic of PPCPs to predict the extent to which they will be
retained in the gravel bed. The more hydrophobic the PPCPs are, the better they will bind to the
organic matter on the gravel medium. Matamoros and Bayona (2006) investigated polycyclic musks
as hydrophobic organic micro pollutants. They showed that polycyclic musks strongly bind to the
biofilm in the gravel bed and therefore are efficiently removed.
The effect of the SRT on the biological degradation of PPCPs
(5)
(6)
20
The SRT is also a design parameter affecting the removal of PPCPs (Clara et al, 2005). In CWs the SRT
is much higher than in conventional treatment systems, as described in paragraph 5.1. Morvannou
(2012) reports a SRT of 5‐10 years for a VFCW. Biological degradation of PPCPs depend on the
diversity and amount of active biomass in the system (microbial population) (Joss et al., 2006;
Majewski et al., 2011). Diversity of microbial population leads to a higher specific microbial activity
and ultimately to a higher removal efficiency (Kimura et al., 2007). The sludge age (SRT) is the main
design parameter that influences these characteristics of the active biomass (Joss et al., 2006;
Majewski et al., 2011; Simpa et al., 2010; Radjenovic et al., 2009).
The effect of the SRT on the biological degradation of PPCPs in indirect. The SRT influences the
characteristics of microbial population and through these modifications, the effects on the biological
removal rates of PPCPs become visible. This indirect effect of the SRT on the biological removal rates
of PPCPs has two sides to it. The first results in stimulation of the removal rate while the other results
in slowing down of the removal rate.
A higher SRT means that the sludge is retained a longer time in the system and has therefore more
time to grow. This aids in the development of a more diverse microbial population (Joss et al., 2006).
Majewsky et al. (2011) adds to this that the effect of the SRT and thus sludge age is only visible on
the removal of moderately biodegradable compounds. Readily biodegradable compounds and
extremely persistent compounds do not depend on the sludge age. A variable, used to describe the
available food to the active biomass is the food to microorganisms ratio (F/M). As the primary
substrate is considered to be OM, the F/M ratio is preferred to be lower. This means that there is not
enough primary substrate available to all microorganisms. This will make them more tempted to
degrade the PPCPs. To achieve a lower F/M ratio, the active biomass in the treatment system must
be abundant and especially concentrated, which is also favoured by a longer SRT (Simpa et al., 2010).
Majewsky et al. (2011) presents the negative effect of an increasing SRT on the PPCP removal rate in
an activated sludge system. Increasing SRT leads to a decrease in the heterotrophic biomass fraction.
Autotrophic biomass utilizes inorganic compounds as energy source and CO2 as carbon source. Very
important autotrophs in CWs are the nitrifying bacteria that convert ammonia into nitrite and nitrite
into nitrate. Heterotrophic bacteria utilize the BOD as carbon and energy source. Autotrophs are
slow‐growing populations, while heterotrophs are fast growing populations. In an activated sludge
system an increasing SRT leads to die‐off of the heterotrophic bacteria due to depletion of the
organic carbon source. The autotrophs on the other hand keep growing, because they do not depend
on organic carbon as an energy source. This results in the negative effect of SRT on the PPCP removal
in activated sludge systems. The SRT in CWs can reach 5‐10 years, because there is no removal of
excess sludge as in an activated sludge system. In CWs the sludge is only removed from the system
by decay. CWs receive BOD in a continuous way, so there is no depletion of this energy source for the
heterotrophs in CWs. Thus the negative effect of an increasing SRT is negligible for CWs.
3.4CommonproblemsinthedesignofSSFCWs
For an operating SSFCW clogging is the main threat. Pedescoll et al. (2013) mentions clogging of the
gravel in the bed as a significant problem in operating CW. Clogging is caused by precipitating solids
in the gravel medium, the formation of bio‐film and the occupation of the pores by the roots of the
plants. So although precipitation, bio‐film formation and plant growth are also removal processes
21
they can become a problem over time. Clogging reduces the total pore volume (effective volume of
the bed) and therefore also alternates the hydraulic conductivity of the gravel medium. Hydraulic
conductivity is an important parameter in CWs, because the waste water has to flow through the bed
(although very slow to allow for the removal mechanism to take place) so that the treatment cycle of
the wetland can proceed. If the hydraulic conductivity is very low, the water will be stagnant in the
wetland. Pedescoll et al (2013) mentions several design parameters that can be adjusted to slow
down the clogging process. Those parameters are: organic loading rate, inlet and outlet position and
type of plants. The higher the organic loading rate the higher the accumulation of solids at the inlet
region. This is the case, because organic matter is mostly present as colloids and particles. So if the
organic loading rate will be reduced, clogging will reduce too.
3.5Removalmechanismsoforganicmicropollutants
Waste water streams contain OMP in the form of pharmaceutical residues, drug metabolites,
pesticides, dyes, explosives, phenolic compounds, petroleum hydrocarbons, and hormones (Heberer,
2002; Dordio et al., 2013). The extent to which removal mechanisms are capable of eliminating the
PPCPs depends on the type and design of the WWTP. The physico‐chemical properties of the
compound and the characteristics of the waste water that enters a WWTP is not variable or only to
limited extent. However, the design of the WWTP can be adjusted to reach higher removal
efficiencies of pollutants in the waste water. To understand which characteristics of the WWTP to
adjust, the removal mechanisms and kinetics of PPCP removal should be understood. By finding the
main removal mechanisms the critical design parameters can be selected to support these removal
mechanisms and their kinetics.
It has been showed that these compounds are not completely removed in waste water treatment
plants (Heberer, 2002). SSFCWs have the ability to treat water from the OMP (Hijosa‐Valsero et al.
2010). In this chapter the application of SSFCWs on the removal of OMP is described. Literature on
removal mechanisms and kinetics is presented.
The elimination of PPCPs in WWTPs occurs through the following processes (Simpa et al., 2010; Clara
et al., 2005; Verlicchi et al., 2013; Randerson, 2006; Matamoros and Bayona, 2006):
Biodegradation
Sorption
Air‐stripping
Photo‐transformation
Abiotic transformations
Biodegradation
In the biodegradation process micro pollutants are consumed as co‐substrates, as the ‘main food’ for
microorganisms are large organic molecules expressed as BOD (Kreuzinger et al., 2004). Verlicchi et al
(2013) mentions what parameters the biodegradation depends on:
kbiol = rate constant of biological break down reaction
structure of the OMP molecules
22
Different OMP differ in the kbiol as they are broken down by different microorganisms and by
different pathways. The next paragraph elaborates further on the biodegradation are and its values
for PPCPs. The structure of a compound aids in its biodegradability when the compound has specific
functional groups that are of importance in the metabolic pathways for microorganisms.
Biodegradatio has been selected by many studies to be the main mechanism ( Verlicchi et al., 2013;
Randerson, 2006).
Sorption
The sorption to organic matter is also an important removal mechanism for PPCPs (Matamoros and
Bayona 2006). Sorption has two mechanisms that it takes into account: absorption and adsorption.
Absorption depends on whether the compound is hydrophobic or hydrophilic and it is taken up to
the structure of the absorbing compound. Adsorption is determined by the polarity of the compound
and the surrounding environment and the interaction between the compound and the adsorbing
surface is of electrostatic interactions. Absorption of a compound is determined by the Kow (octanol‐
water partitioning) constant and the adsorption by the pKa (dissociation) constant. One constant that
takes both into account and thus represents the affinity of a compound for sorption is the Kd (solid‐
water partitioning) coefficient (Simpa et al., 2010). In several studies sorption is mentioned to be of
less significance in the removal of PPCPs, because these were observed to have a low Kd value (Simpa
et al., 2010).
Air‐stripping
Air‐stripping is the mechanism by which a compound is eliminated from the waste water through
aeration. Thus the compound leaves the system through volatilization. Air‐stripping is an important
removal mechanism in WWTP with high aeration flow rates. Membrane bioreactors (MBR) are
WWTPs with high aeration flow rates which are applied to clean the membrane (Simpa t al., 2010).
For SSFCWs this removal mechanism is of little significance, because there is very little contact
between the waste water and the air and no aeration.
Photo‐transformation
Ranieri et al. (2011) studied the removal of paracetamol in SSFCWs with and without plants and with
difference in flow rate. They found photolytic reactions to be responsible for the major part of the
removal of paracetamol. This mechanisms is unfortunately negligible for SSFCWs with a planted
surface.
Abiotic transformations
The structure is overall determining the fate of chemicals in the environment. It does not only
influence the abiotic transformation of a compound, but also the ability to be degraded or adsorbed
to a surface. The structure of a molecule determines its ability to persist in the environment or its
ability to react with other chemicals. The structure also determines the vulnerability of a compound
to certain physical and chemical characteristics of the environmental compartment where it is
present (e.g. pH, redox potential, DO).
23
Table 4 presents some pharmaceuticals and the removal mechanisms by which they are removed.
Table 4. Main removal mechanisms for some PPCPs
Compound Main removal mechanism
Ibuprofen Aerobic biodegradation (Verlicchi et al., 2013)
Diclofenac Anaerobic degradation (reductive
dehalogenation) (Verlicchi et al., 2013;
Matamoros and Bayona, 2006)
Ketoprofen Biodegradation (Matamoros and Bayona, 2006)
Naproxen Aerobic biodegradation (in absence of oxygen:
anoxic degradation) (Verlicchi et al., 2013)
Carbamazepine Adsorption onto organic surfaces (Verlicchi et
al., 2013)
Paracetamol Photo‐transformation (Ranieri et al., 2011)
3.6Removalkineticsoforganicmicropollutants
The removal of PPCPs in conventional activated sludge systems (CAS), activated sludge systems with
a sludge concentration of 1500‐3500 mg/L, is observed to be pseudo first order reactions (Gray,
2010; Joss et al., 2006; Majewsky et al., 2011; Maurer et al., 2007). The degradation rate is a function
of 2 variables: the concentration of the PPCP in the water and the sludge concentration in the
treatment system (see equation below). But because the concentration of sludge (biomass) is much
higher than the PPCP concentration, this variable is assumed to be constant. Thus the biodegradation
of PPCPs is only depending on the concentration of the PPCP in the water.
= Kbiol * Xbh * Co (Majewsky et al., 2011)
Where:
ΔCt = change of the concentration of the PPCP (mg/L)
Δt = a period in time (d)
Kbiol = biodegradation rate (L gSS‐1 d‐1)
Xbh = active biomass expressed as suspended solids (gSS L‐1)
Co = initial soluble concentration of PPCP (mg/L)
This equation is used in batch experiments to estimate the biodegradation rate of PPCPs in CAS
systems. It must be noted that the biodegradation rates are different in other treatment systems.
This difference is mainly caused by the difference in SRT and HRT. These two design parameters
influence the contact time between the compound and the sludge and the characteristics of the
biomass.
Different PPCPs differ in the kbiol as they are broken down by different microorganisms and by
different pathways. Table 5 shows the biological degradation rates of several PPCPs in CAS.
24
Table 5. Degradation constants for PPCPs in CAS treatment systems
Compound Degradation rate constant Kbiol CAS (L gSS‐1 d‐1) Reference
Carbamazepine
≤ 0.01 Joss et al., 2006; Majewsky et
al., 2011
Ibuprofen 21‐35 Joss et al., 2006
Sulfamethoxazole
≤ 0.1; 0.25‐0.3 Joss et al., 2006; Majewsky et
al., 2011
Atenolol 0.98 Maurer et a., 2007
Diclofenac
≤ 0.1; 0.25‐0.3 Joss et al., 2006; Majewsky et
al., 2011
Naproxen 1‐1.9 Joss et al., 2006
Paracetamol
58‐80; 0.4‐1.7 Joss et al., 2006; Majewsky et
al., 2011
Metoprolol 0.82 Maurer et a., 2007
Propranolol 0.55 Maurer et a., 2007
Sotalol 0.41 Maurer et a., 2007
Caffeine 1.5‐2 Majewsky et al., 2011
Joss et al. (2006) proposed the following classification of the removal rates of PPCPs according to
their biological degradation rate:
No removal: Kbiol < 0.1
o Carbamazepine, sulfamethoxazole, diclofenac
Partial removal: < 0.1Kbiol < 10
o Atenolol, naproxen, metoprolol, propanolol, sotalol, caffeine
More than 90% removal: Kbiol > 10
o Ibuprofen, paracetamol
In the Results chapter there will be reflected to these biodegradation values together with the
observed removal efficiencies in this and in other studies.
3.7Nitrogen(N)andremoval
Total nitrogen in domestic wastewater can be divided into four groups: organic nitrogen; nitrite (NO2‐
N), nitrate (NO3‐N), and ammonia (NH4‐N) (Gray et al., 2000). Nitrogen is removed in the first place
by bacteria (Akratos et al., 2007). The plants in the CW also take up nitrogen, as it is a necessary
nutrient for them. The ionic form of nitrogen (ammonia) is removed from the water stream by
adsorption to the medium the bed and volatilization.
Akratos et al. (2007) also mentions a study in which was determined that total Kjedahl nitrogen (TKN)
and ammonia removal strongly depends on the hydraulic retention time (HRT): higher HTR results in
a lower effluent concentration for ammonium and TKN.
Organic nitrogen is nitrogen that is incorporated into organic molecules like amino acids. The organic
nitrogen is broken down into ammonium by the process of ammonification. Subsequently, the fate of
ammonium in the wetland is determined by the nitrifying bacteria, which live around the roots of the
25
plants and utilize oxygen (Akratos et al., 2007). They use this oxygen to oxidize the ammonium into
nitrite and nitrate. Nitrate and nitrite diffuse into the water‐saturated zone of the wetland. This zone
is anaerobic, and the denitrifying bacteria anaerobically convert nitrate and nitrite into nitrogen gas.
This is when nitrogen leaves the system.
Low oxygen concentrations and high carbon concentrations can limit the nitrification process, as the
nitrifying bacteria need carbon to grow and oxygen to respire. Unfortunately, this is often the case in
constructed wetlands. Wastewater often contains large amounts of carbon from the organic
compounds and low amounts of dissolved oxygen due to the high BOD. This results in incomplete
nitrification of ammonium, making it impossible to initiate denirtification. As a result, the nitrogen
removal process in SSCWs is often not efficient enough to reach acceptable levels of nitrogen in the
effluent (Gray et al 2000).
Figure 7. Overview of the fate of Nitrogen in a CW (Randerson, 2006)
3.8Phosphorus(P)removal
For P removal, the same mechanisms are important as for N‐removal:
Bacterial uptake
Plant uptake
Adsorption
In addition to that, P is also removed through precipitation. If the P reacts with ferricoxyhydroxide or
carbonate, it can react into crystals and then precipitate. Bacteria and plants only take up P in the
form of PO34‐. Adsorption and precipitation can affect all types of P containing compounds.
Adsorption is thus an important removal mechanism for P. The removal efficiency of a CW can be
manipulated by changing the substrate in the bed. Different substrates have different adsorption
26
capacity for P. In the next part of this paragraph, a review will be presented about different substrate
possibilities to enhance the P removal.
Wallostonite is can be used as substrate in the bed of a CW to enhance the removal of phosphorus.
The removal efficiency of soluble phosphorus forms depend on their residence time in the system.
Shale is another medium type that can be used to enhance phosphorus removal, recommended by
Drizo et al. (2000). Except for its adsorbing properties for phosphorus, it also supports plant growth.
Gray et al. (2000) recommends maerl (calcified seaweed) as substrate in the medium for the removal
of phosphorus. Akratos et al. (2007) mentions that the removal efficiency for phosphorus in this
study was the highest found in literature due to the very high phosphorus‐adsorbing capacity of
maerl. Maerl can also stimulate growth of the plants in the CW. Gray et al. (2000) also mentions 2
commonly used media and their disadvantage:
Natural soils are able to remove P up to 98%, but this medium is susceptible to clogging due
to their low hydraulic conductivity
River gravel has a high hydraulic conductivity and thus does not clog, but their P removal is
less efficient, because of their low surface area and low adsorption capacity. For efficient P
removal iron rich gravel is advised
Xu et al. (2006) studied the adsorption of phosphorus to several different medium types (sands,
bentonite, soil, fly ash and furnace slag). He showed that the sands adsorbed very poor compared to
furnace slag and fly ash.
Phosphorus precipitates in wetlands with a high pH, containing high calcium amounts and in
wetlands with a low pH containing high aluminium and iron concentrations (Gray et al. 2000). These
elements react with P to form precipitates.
The soluble forms of phosphorus are taken up by the plants in the wetland. Gray et al. (2000) This
emphasizes the importance of plants in a wetland to remove the soluble phosphorus.
3.9RemovalofBOD
BOD removal in SSFCWs is a spontaneous process. It is removed by microbial activity. Biological
Oxygen demand (BOD) is a measure of the amount of organic matter present in the waste water.
Organic matter in waste water is consumed by aerobic bacteria. Because the aerobic bacteria need
oxygen to break down the organic matter, the amount of oxygen that is being consumed in a water
system can be translated into the amount of organic matter present in the system.
4.PerformanceevaluationoffullscaleCWs
This chapter evaluates the performance of the wetlands from the collected data during the two
sampling campaigns. The performance of the wetlands is evaluated based on their capacity to
27
remove the pollutant groups BOD, COD, TSS, nitrogen, phosphorus, and PPCPs. BOD, COD, TSS,
nitrogen and phosphorus removal in the wetlands is analysed in the first sections of this chapter. The
performance of CWs on the removal of these pollutants has already been extensively studied. Also
the CWs are already being applied in many cases to treat waste water from BOD, COD, TSS, nitrogen,
phosphorus. The analysis of the results on the removal of these pollutants in this study will be kept
brief to focus on the removal of PPCPs. PPCP removal in CWs is still limited, especially the application
of VFCWs to remove PPCPs. To understand how the VFCWs perform on the removal of PPCPs, the
PPCP removal is analysed in more detail than the other pollutant groups in the last paragraph. The
results will point out whether the design parameters of a VFCW can be adjusted to enhance this
performance.
4.1PPCPremoval
In this paragraph the PPCP removal in the wetlands is evaluated to find out the capacity of the
wetlands to remove this pollutant group and find out what design parameters can be adjusted to
reach a more satisfying removal.
InfluenceofdesignparametersonPPCPremoval
First, the removal rate of all PPCPs was plotted against their specific loading rate. Figure 8, 9 and 10
are three examples of these graphs. This relationship gives a first indication of the dependence of the
removal of a certain compound on its specific loading rate. If there is zero dependence the slope of
the graph is 1. This also means that the removal is always equal to the loading rate and therefore the
removal efficiency is 100%. With a slope approaching zero, the conclusion is that the compound is
very poorly removed from the waste water. Table 6 shows all the PPCPs that showed to have a
strong linear relationship (R2>0.75) between the removal rate and the specific loading rate.
Figure 8. Butylparaben: removal rate vs. specific loading rate
28
Figure 9. Ethylhexyl methoxycinnamate: removal rate vs. specific loading rate
Figure 10. Caffeine: removal rate vs. specific loading rate
Table 6. PPCPs with a linear relationship between specific loading (g/m2/d) rate and removal rate
(g/m2/d)
Slope R2 Remarks (outliners and remarkable points)
Ibuprofen 0.89 1
Atenolol 0.82 0.94 Location A 1 has no detected removal rate
Naproxen 0.77 0.93 Location A 1 has no detected removal rate
Paracetamol 0.99 1
Butylparben 0.95 1 Location A 1
Etylparben 0.91 1
Methylparben 0.88 1
Phenylbenzimidazole sulfonic acid 0.28 0.96
Propylparben 0.99 1
Hexyl cinnamaldehyde 0.96 1
2‐ethylhexyl salicylate 0.85 1
29
Galaxolide 0.97 1
Tonalide 0.90 0.99
Ethylhexyl methoxycinnamate 0.99 1
Location A 1 had a RR of a factor 100 higher than
the other points
Octocryleen 1 1
Caffeine 0.98 1 Location A 1 has highest SLR and RR
The graphs with a slope approaching 1 (>0.95) are the PPCPs that have a nearly complete removal in
the wetlands. Their removal rate is always nearly equal to their loading rate. The removal efficiency
of these compounds is therefore always close to 100%, regardless the specific loading rate and
removal rate.
Assuming high correlation coefficients (R2 >0.75) to indicate strong correlations between the specific
loading rate and the removal rate, all the compounds in table 6, with 2,4‐dichlorophenol as
exception, to show very strong correlation. The strength of the correlation indicates the strength of
the relationship between two variables (in this case specific loading rate and removal rate). By
analysing the slope and the correlation coefficient together, conclusions can be made on how to
predict the removal rate from the specific loading rate.
Table 7 shows the compounds that had zero to negative removal rates in the wetlands. The low
removal efficiency of carbamazepine, diclofenac and ketoprofen was expected, because this
pharmaceutical compound was also found to be very poorly removed in wetlands studied in other
studies (Verlicchi et al., 2013; Zhang et al., 2012b; Matamoros et al., 2007; Matamoros and Bayona,
2006; Heberer, 2002).
Sotalol however, has a slope of 1, which indicates a removal efficiency of 100%, regardless the
influent/effluent concentrations. However, it must be noted for this compound that there were only
two positive removal rates (with one of them negligible as it was 40 times lower than the second
point). With only one positive pint this relationship cannot be assumed as relevant. That is why this
compound is classified in the group of zero to negative removals.
All the compounds in table 7 also have a low correlation coefficient, indicating that there is no
significant dependence of the removal rate on the specific loading rate. For these compounds can be
said that there is no relationship between the two variables, thus they are poorly removed in all
cases. The exception to this are sotalol and lidocaine. It must be noted however that because most of
their points are zero or below zero for the removal rate, these relationships are assumed to be
insignificant.
Table 7. Compounds that show poor removal.
slope R2 Outliners
Carbamazepine 0.18 0.19
Sulfametoxazole ‐ ‐ Zero removal rate for every point
Diclofenac ‐ ‐ Zero removal rate for every point
Ketoprofen ‐ ‐ Zero removal rate for every point
Propranolol 0.47 0.53 Location C 1 is the only point with a positive removal
rate
Sotalol 1.06 0.83 Location C 2 is the only point with a positive removal
30
rate
Lidocaine ‐1.04 0.97 Linear negative line (assumed to be zero removal for all
points)
Bisfenol A 0.03 0.02 Location C 2 and Location D 1 points with much higher
removal rate
4‐methylbenzylidene
camphor
0.01 0 Location C 1 is the only point with a positive removal
rate
Methyltriclosan 0 0.02 Zero removal rate for every point
All the compounds with a slope approaching 1 (>0.95) and a correlation coefficient higher than 0.75
are spontaneously removable compounds that reach removal efficiencies approaching 100% for
every specific loading rate.
All the compounds with a slope lower than 0.5 and a correlation coefficient lower than 0.5 are
compounds with removal rates not dependent on the specific loading rate and always reaching low
removal efficiencies. They are therefore the poorly removable compounds.
Table 8 gives a qualitative overview of the removal efficiencies of all compounds for each wetland
and for both sampling campaigns separately. This overview gives insight in which locations are
accountable for a better/worse removal of compounds and which compounds present a consistent
removal in all wetlands.
Table 8. Wetland performance on PPCP removal: classification based on removal efficiency
Location
D 1
Location
D 2
Location
B 1
Location
B 2
Location
A 1
Location
A 2
Location
C 1
Location
C 2
carbamazepine 0 0 0 0
ibuprofen +++ +++ +++ +++ ++ + +++ ++
sulfametoxazole
Atenolol ++ + + ++
diclofenac ++ 0
ketoprofen
naproxen + +++ 0 ++ + +
paracetamol ++ +++ +++ +++ +++ +++ +++ +++
metoprolol 0 + + ++ + ++
propranolol + 0
Sotalol 0 ++ 0 +++
Lidocaine 0 0 0 0 0 0 0 0
bisfenol A ++ 0 ++
butylparben 0 ++ +++ +++
etylparben + ++ ++ +++ + +
methylparben ++ 0 + + ++ +++ +++
phenylbenzimidazole
sulfonic acid +++ +++ + 0 + 0 +
propylparben ++ +++ +++ +++ +++ +++
triclosan +++ + +++ +++ +++
31
2,4‐dichlorophenol ++ ++ ++ +
hexyl cinnamaldehyde ++ +++ +++
2‐ethylhexyl salicylate + ++ ++ ++ ++ +
galaxolide + ++ +++ +++ +++ +++ +++ +++
tonalide + + + +++ ++ + 0
4‐methylbenzylidene
camphor
ethylhexyl
methoxycinnamate + +++ ‐ +++ ‐ ++
methyltriclosan ‐ 0 ‐ ‐ ‐
octocryleen +++ ‐ +++ ‐ +++ ‐ +++ ‐
caffeine +++ +++ +++ +++ +++ +++ +++ +++
Removal efficiency Sign in table 11
0‐30% 0 No removal
30‐70% + Moderate removal
70‐90% ++ Efficient removal
>90% +++ Very efficient removal
‐ Not determined
Both influent and effluent < DL No value for removal efficiency
Only effluent < DL Removal efficiency > calculated value
The green highlighted cases are not considered in the evaluation of this table, because these are the
points for which both influent and effluent concentration was below the detection limit, which
means that the removal efficiency could not be determined . The blue highlighted cases are the ones
that have effluent concentrations below the detection limit. This means that these are the point for
which the actual removal efficiency is most probably higher than the calculated removal efficiency.
The encircled cases are the ones that stand out for the particular compound.
The compounds that show efficient to very efficient removal in the majority of the cases are:
Ibuprofen
Paracetamol
Galaxolide
Octocryleen
Caffeine
This result is in agreement with the results of the correlation tests. All the compounds with a
correlation coefficient of 1 and a slope of higher or equal to 0.98 (which indicates 100 percent
removal) are also the compounds that showed an efficient to very efficient removal in all the
wetlands. The nearly complete removal of these compounds under all conditions might be an
indication that the removal mechanism for these compounds is similar to the removal mechanisms
for the main substrate for biological metabolic pathways (BOD and COD).
The compounds that show no removal in almost all the wetlands during and both samplings are:
32
Carbamazepine
sulfametoxazole
diclofenac
ketoprofen
propranolol
sotalol
lidocaine
bisfenol A
4‐methylbenzylidene camphor
methyltriclosan
These compounds are also the compounds in table 4, showing no correlation and no removal.
The compounds not mentioned above showed very varying removal efficiencies between the
different locations and different sampling.
However, there are some exceptions to the two groups mentioned above. Some cases stand out by
having variant removal efficiency. These cases are important to discuss as they might suggest which
design parameters might influence the removal efficiency.
Ibuprofen showed efficient to very efficient removal in all cases except form one: Location A
sampling 2. This case has a moderate removal efficiency. Diclofenac: Location B 2 is the only case
with a positive removal efficiency. And this removal efficiency is 83% (classified as efficient). All the
other cases showed no removal (0% removal efficiency). A possible explanation for this one variant
removal efficiency in ibuprofen and diclofenac could be a fluctuation in the influent concentration of
diclofenac in a period of two weeks to one month before the sampling. For each sampling campaign
the influent and effluent samples were taken at the same date and same time. However, the effluent
that complements these influent concentrations only exits the system after the HRT has passed. This
cause could be the argument for the compounds that have no more than one or two varying cases
like diclofenac, ibuprofen, methylparaben, ethylparaben and triclosan. Naproxen and methylparaben
showed very varying removal efficiencies from zero to moderate to very efficient. This variation
showed no relation with the specific loading rate or influent concentration and could probably be
explained by differences in biomass activity. Sulamethaxazole did not show any removal in the
wetlands, because the influent concentration was always measured below the detection limit.
Atenolol showed a consistent removal of moderate to efficient. Ketoprofen did not show any
removal in the wetlands, because the influent concentration was always measured below the
detection limit. Paracetamol showed efficient removal in all cases. This is due to the higher influent
concentrations (thus higher loading rates) compared to the other compounds. This is also true for
Caffeine. These two compounds are the most abundantly present in the waste water. Sotalol showed
two cases with efficient and very efficient removal efficiency amongst the other cases who all had
zero removal. Metoprolol also has two cases with a higher removal efficiency than the others. The
cases for metoprolol however are not the same locations as for sotalol. These two compounds
belong to the same type of pharmaceuticals: the β blockers (Maurer et al., 2007).
The specific loading rate did not seem to have an effect on the PPCPs individually. But overall can be
determined that the compounds with a higher specific loading rate achieved higher specific removal
rate. This is due to the higher influent concentrations that lead to higher loading rates. The loading
rates were higher for the PPCPs that had a higher influent concentration. This means that the
removal rate will be higher when the influent concentrations increase. The influent concentration is
33
not an adjustable variable as it depends on the domestic waste water streams. Furthermore, the fact
that the influent and effluent samples were taken at the same time could be an explanation for the
differences between cases for many partially and poorly removed compounds.
HRT estimation
Wynn and Liehr (2001) mention a general porosity of 0.3 (30% water volume) in sub‐surface
constructed wetlands. We use this value for the porosity to estimate the HRT of the four wetlands in
this study.
Table 9. HRT estimation
Dimension Location A Location B Location C Location D
Volume (m3) 1000 1500 210 30
Water volume =
30%*Volume (m3)
300 450 63 9
Flow (m3/h) 1.042 1.1671 0.35 0.044
HRT (hrs) 287.91 385.60 180 204.55
HRT (days) 12 16.07 7.5 8.5
Li et al. (2014) reports an average HRT of 1‐2 days for VFCWs . The estimated HRTs for these
wetlands is by far higher that Li et al. 2014 reports. This could be due to the use of a broad variety of
different material as granular medium and different plants in the different wetlands. The estimated
HRT’s indicate that the contact time between the granular medium and the waste water must be
sufficient and HRT cannot be a limiting design parameter for the degradation of the PPCPs. A high
HRT can either be supportive for the removal efficiency by providing enough contact time.
1 The average value of the given values in table 3.
34
Figure 11. Comparison of the average removal efficiencies for PPCPs between sampling campaign 1 and sampling campaign 22
2 The average for each wetland excludes all points with both influent and effluent lower than the detection limit. Also it has to be noted that these average values for the removal efficiency are all minimum values. Because the effluent concentrations in most of the many compounds was measured to be smaller than the detection limit, the resulting removal efficiency is higher than the calculated value.
35
For most compounds the difference between the sampling campaigns is relatively small. There is only a significant difference between the removal
efficiency of sulfamethoxazole, naproxen, metoprolol and 2,4 ‐ dichlorophenol. The first three compounds had a higher efficiency during the second
sampling and 2,4 – dichlorophenol during the first sampling.
36
Comparisonwithliteraturevalues
In this paragraph a comparison is given between previously conducted studies on the removal of
PPCPs in waste water treatment plants. In the first part of this paragraph, a comparison is given
between a study on PPCP removal in a VFCW and this study. Further, to analyse the performance of
different types of WWTPs, a comparison will be given for four types of treatment plants.
Literature values for the removal of PPCPs in SSFCWs are mostly studied for HFCWs. Table 10 shows
the results form one study that analysed the performance of a VFCW. These values are used to
compare the results from this study. This comparison can give insight in the variability of removal
efficiencies between wetlands and ideas to improve poor performances of PPCP removal.
Table 10. PPCP removal in a VFCW
Pharmaceutical
compound
Average influent concentration (µg/L)
Removal efficiency (%)
Results from this study
Matamoros et al., 2007
Results from this study
Matamoros et al., 2007
carbamazepine 0.03 2.06 ‐32.59 26 ±14
ibuprofen 5.49 11.7 >91.06 99 ±1
diclofenac 0.02 0.82 ‐2.08 73 ± 3
ketoprofen 0.02 0
naproxen ≤0.50 1.57 >34.47 89 ±5
galaxolide 26.26 5.62 >84.92 90 ±1
tonalide ≤0.34 0.99 >54.20 82 ±1
caffeine 280.60 48.40 99.37 99 ±1
Matamoros et al (2007) is the one study that also studied the removal of PPCPs in VFCWs. The
removal efficiencies in Matamoros et al (2007) were much higher than the removal efficiencies in the
wetlands of this study. Only caffeine presented the same removal efficiency of 99% in both studies.
Ibuprofen also has high removal efficiency in the wetlands studied in this case and approaches the
99% removal observed by Matamoros et al (2007). Caffeine and Ibuprofen are being reported as a
highly biodegradable due to their abundant use and their biodegradability (Matamoros et al., 2007;
Matamoros and Bayona, 2006).
PPCPs that are observed to be poorly removed are called recalcitrant. The PPCPs that belong to this
group are reported to be diclofenac, carbamazepine and ketoprofen (Matamoros et al., 2007;
Matamoros and Bayona, 2006; Heberer, 2002). These three compounds are also the ones that
showed very low removal efficiencies in our sampling campaigns (zero to negative removal
efficiencies).
37
Table 11. Literature review on removal efficiencies of PPCPs
This study CAS3 MBR1 SSFCWs4
Carbamazepine ‐158.93 ‐8 ± 23 0 ± 11 5.49 ± 13.80
Diclofenac ‐8.33 21 ± 41 34 ± 25 24.99 ± 25.96
Ibuprofen > 91.06 93.5 ± 7 97.3 ± 3 44.96 ± 36.28
Ketoprofen < detection
limit
47 ± 21 72 ± 23 13.86 ± 25.35
Naproxen > 45.96 66 ± 23 85 ± 10 52.01 ± 32.82
Sulfamethoxazole < detection
limit
33 ± 64 73 ± 11 15.895
Atenolol > 65.33 44 ± 32 71 ± 5 47.823
Metoprolol > 53.20 23 ± 21 44 ± 12 10.993
Propranolol ‐325.00 59 72 ± 6 38.893
Sotalol ‐744.90 55 ± 14 42 ± 11 5.263
Galaxolide > 84.92 52.00 ± 22.37
Tonalide > 54.20 57.00 ±18.34
Caffeine > 99.36 86.78 ± 14.52
This table shows a comparison for average PPCP removal efficiencies between different treatment
plants. The values for the CAS and the MBR are taken from Simpa et al. (2010). That article made a
comparison between literature values for CAS and MBR and presented the average removal
efficiencies for different compounds. The average values for SSCWs are calculated form the removal
efficiencies given in 4 different studies. Among these 4 studies there is only one study that was
performed with a VFCW. The other three were HFCWs. The standard deviation shows how much the
results of different studies deviate from the calculated average value. However, it must be noted that
still this standard deviation does not give the complete variability of the observed removal
efficiencies, because the standard deviations of the each study independently is not taken into
account in this table. This is the remark that Simpa et al (2010) also gives when comparing the
average removal efficiencies he calculated for PPCPs between CAS and MBR systems.
Carbamazepine and Diclofenac have shown the lowest removal efficiencies in all systems. As
mentioned before, these compounds are classified as recalcitrant. Their removal is not affected by
either biodegradation or sorption. This result is in agreement with the biodegradation rates
presented in chapter 3. In chapter 3 the biodegradation rate of these two compounds was below 0.1
and classified in the poorly removable PPCPs.
Ketoprofen was also classified as recalcitrant. However, this compound presented efficient removal
in MBR systems. Simpa et al. (2010) For this study the measured influent and effluent concentrations
were below the detection limit of the measurement apparatus, so no conclusions can be made on
the removal of ketoprofen in this case.
In general, the recalcitrant compounds carbamazepine, diclofenac and ketoprofen show lower
removal efficiencies sin the CWs compared to the CAS and MBR systems. These compounds are
3 Simpa et al., 2010 4 Average values from Matamoros and Bayona, 2006, Verlicchi et al., 2013, Matamoros et al., 2007 and Hijosa‐Valsero et al., 2010 5 Only one reference study (Verlicchi et al., 2013)
38
recalcitrant, because their biodegradation rates are low. Thus they are poorly removed by
microorganisms. The removal efficiencies presented by table 10 support this statement for CWs. The
relatively higher removal of these compounds in CAS and MBR might be due to Ibuprofen showed a
very high removal in all the treatment systems, except for in the SSFCWs. When analysing the
removal efficiency of ibuprofen in the 4 studies that were used to calculate the average removal
efficiency, the only near complete removal of this compound is observed in the one study that was
conducted in a VFCW (Matamoros et al., 2007). VFCWs might be therefore more suitable for the
removal of readily degradable PPCPs than HFCWs. The biodegradation rate of this compound (as
observed in CAS systems) is very high and classified as more than 90% removed in CAS systems (see
chapter 3). This high removal is also shown to be observed in almost all the systems.
Atenolol and Metoprolol showed significantly higher removal efficiencies in this study compared to
removal of Propanolol and Sotalol. These four compounds belong to the same group of β‐blockers,
but they differ according to their biodegradation rate. Propanolol and Sotalol have a lower
biodegradation rate than Atenolol and Metoprolol (Maurer et al., 2007). The removal efficiencies
form this study are in agreement with the findings of Maurer et al (2007), as there is a significant
lower removal observed for sotalol and propanolol than for atenolol and metoprolol. Also the
biodegradation rates (presented in chapter 3) are with a factor of 2 lower for propanolol and sotalol
compared to atenolol and metoprolol, which indicates that the first two compounds are slowly
degradable. This pattern of a lower removal for propanolol and sotalol is not shown for the CAS, the
MBR system and the SSFCWs form other studies. This might indicate that CAS and MBR systems
promote the removal of these compounds through other additional mechanisms than only
biodegradation. Sorption to biofilm is an alternative removal mechanism as Maurer et al (2007)
presented these compounds as lipophilic.
According to the biodegradation rate, caffeine was classified as partially removed in CAS systems.
However, caffeine is by far one of the most abundantly used compounds, and is therefore found in
the highest concentrations in waste water. The higher concentrations make this compound more
available to microorganisms compared to the other much diluted PPCPs. This results in a more rapid
biodegradation of this compound.
39
4.2BOD,CODandTSSremoval
The composition of the waste water, with regards to the BOD, COD and TSS concentrations in the
influent are first presented in the following graphs.
Figure 12. Influent BOD concentration Figure 13. Influent COD concentration
Figure 14a. Influent TSS concentration Figure 14b. Influent TSS concentration
without Location D sampling 2
As figure 14 shows, Location D sampling 2 has an influent concentration much higher than the other
locations, which makes it difficult to distinguish the other locations from each other. Figure 14b
excludes the data from Location D sampling 2, to make the variation between the other data visible.
Figures 15 to 20 show the performance of the four different wetlands during the two sampling
campaigns for BOD, COD and TSS.
0
50
100
150
200
250
300
350
400
Influent concentration (mg/L)
Sampling 1
Sampling 2
0
500
1000
1500
2000
Influent concentration (mg/L)
Sampling 1
Sampling 2
0
200
400
600
800
1000
1200
Influent concentration (mg/L)
Sampling 1
Sampling 2
0102030405060708090
Influent concentration (mg/L)
Sampling 1
Sampling 2
40
Figure 15. Effluent BOD concentration Figure 16. BOD removal efficiency
For the performance of the wetlands on BOD removal, figure 15 shows that the removal efficiency is
very high (> 95%) for all the wetlands.
Figure 17. Effluent COD concentration Figure 18. Effluent COD removal efficiency
As BOD is a fraction of COD, we expect the same results for the performance of the wetlands on COD
removal. This is also the case, with figure 14 showing removal efficiencies higher than 95% in all the
cases. The high variation in the influent concentrations of BOD and COD between the wetlands (see
figure 12 and 13) does not reflect in the effluent concentration. This means that the removal of BOD
and COD in a VFCW is efficient, regardless the influent concentration.
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0Effluent concentration (mg/L)
Sampling 1
Sampling 2
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
Effluent concentration (mg/L)
Sampling 1
Sampling 2
41
Figure 19. Effluent TSS concentration6 Figure 20. Effluent TSS removal efficiency
The performance of the wetlands on TSS removal is consistent for all wetlands during both sampling
campaigns except for 2 cases: Location A 2 and Location B 1. These two cases are the only ones that
have an effluent concentration higher than the detection limit of the measurement method (3 mg/L).
Location B has a higher TSS effluent concentration during the first sampling, but the removal
efficiency stayed constant. This is the result of a higher TSS loading during the first period compared
to the second period.
The very high effluent concentration in Location A 2 corresponds with the poor TSS removal depicted
by figure 20. The removal efficiency of the Location A wetland shows a negative removal efficiency
during sampling campaign 2, which indicates an increase of TSS in the effluent. One cause of this
could be clogging of the wetland. If the wetland of Location A was clogged, TSS removal would be
inefficient. However, this cause less probable if we look at the other parameters: BOD and COD were
efficiently removed in the wetland of Location A during the second sampling. If the wetland was
clogged the removal of BOD and COD also must have been affected.
The influent TSS concentrations in figure 14 shows that Location D sampling 2 had by far the highest
influent TSS. To evaluate if this has had an effect on the removal efficiency, there must have been
taken samples from the effluent a few days later to take into account the hydraulic retention time. In
this case the effluent samples have been taken at the same time as the influent samples. Thus, the
effluent and influent concentrations are not directly related to each other. This is a point of
discussion that is elaborated on further in chapter 8.
4.3Nitrogenremoval
In this paragraph the effluent requirements of total nitrogen (TN) in the wetlands is evaluated. The first
following graph gives a comparison of the TN influent concentration in the different wetlands. Then, Figure 22
and 23 give a comparative overview of the performance of the four wetlands on TN effluent concentration and
TN removal efficiency respectively.
6 For figure 15 must be noted that all the cases showing an effluent concentration of 3 mg/L in figure 16 are actually < 3mg/L (detection limit).
0.02.04.06.08.0
10.012.014.016.018.0
Effluent concentration
(mg/L)
Sampling 1
Sampling 2
42
Figure 21. Influent TN concentration
As depicted by the figure above, the influent concentration varies highly between the wetlands and is the
highest for the Location D. The same pattern is also true for the effluent concentrations as seen in figure 22.
Because the influent and effluent concentration show the same pattern, there might be a relationship between
these two variables. This is evaluated and elaborated further in figure 23.
Figure 22. Effluent TN concentration Figure 23. TN removal efficiency
Total nitrogen shows effluent concentrations to be the highest in Location C and in the Location D.
This could be explained by the very high total nitrogen concentration in the influent of these
locations compared to the other wetlands. As shown in figure 23 there is a linear relationship
between the TN influent concentration and the effluent concentration. Correlation coefficients
higher than 0.75 indicate strong relationships between two variables. The linear relationship
between the TN influent concentration and the effluent concentration has a correlation coefficient of
0.89, which indicates that the linear relationship is strong. Thus it can be concluded that the effluent
concentration depends on the influent concentration. The removal efficiency on nitrogen removal in
the wetlands is dependent on the influent concentration.
0
20
40
60
80
100
120
140
160Influent concentration (mg/L)
Sampling 1
Sampling 2
0.010.020.030.040.050.060.070.080.090.0100.0
Effluent concentration (mg/L)
Sampling 1
Sampling 2
43
Figure 24. Relationship between influent and effluent concentration for total nitrogen
The slope of the linear relationship in figure 24 indicates the average effluent to influent ratio of TN.
One point that stands out in both figure 23 and figure 24, is the point of Location D sampling 1.
Figure 23 shows that it has the lowest removal efficiency than all the other locations and in figure 24
this point is also the one that lays the furthest form the linear line.
Table 12 shows the constituents of total nitrogen in the influent and effluent of the four wetlands
during both sampling campaigns.
Table 12. Constituents of total nitrogen in the influent and effluent
Ratio (%) Nkj/TN Ratio (%) NO2‐N/TN Ratio (%) NO3‐N/TN
Sampling 1
Location A Effluent 26.9 2.38 69.23
Influent 100.0 0.13 <0.45
Location B Effluent 100.0 <1.00 <20.00
Influent 100.0 0.08 <1.11
Location C Effluent 9.7 0.42 90.32
Influent 100.0 0.03 <0.14
Location D Effluent <0.5 <0.01 100.00
Influent 100.0 0.15 0.87
Sampling 2
Location A Effluent 37.5 0.75 62.50
Influent 100.0 0.12 <0.56
Location B Effluent ≤100.0 1.20 ≤20.00
Influent 100.0 0.14 <2.00
Location C Effluent 6.7 0.05 93.48
Influent 100.0 0.02 <0.14
Location D Effluent <0.7 <0.01 100.00
Influent 100.0 0.01 <0.07
44
It must be noted that the sum of all percentages has to be 100% (% Nkj/TN + % NO2‐N/TN +% NO3‐
N/TN =100%). However, this is not the case for all the locations in table 11. The reason for that is that
the concentrations below the detection limit (D.L.) were assumed to be equal to the detection limit
(D.L. NO3‐N = 0.1 mg N/L; D.L. NO2‐N = 0.05 mg N/L; D.L. Nkj = 0.5 mg N/L; D.L.TN = 0.5 mg N/L ).
Nitrite makes up 0‐2% of all the nitrogen in all the wetlands and for both sampling campaigns. This
indicates that the nitrification process always took place and was completed, converting the NO2
into NO3. Nitrate stayed in the water as dissolved and was not converted into nitrogen gas to leave
the system, thus no denitrification took place. Therefore we see an increase of more than 96% for
nitrate in all the wetlands (Table 12).
Table 12 further shows that nitrate formed more than 90% of the total nitrogen in the effluent water
of Location C and the Location D. These numbers are much higher than for the other two wetlands,
because of the high TN influent concentrations. The TN influent concentrations were much higher in
Location C and Location D, because these wetlands receive effluent water from the septic tanks. This
water has much higher nutrient contents than grey water.
Location B showed a removal of more than 90% during both sampling campaigns for total nitrogen
(Table 13). The removal of total nitrogen for Location B is equal to the decrease in Kjeldahl nitrogen.
This means that the nitrification/denitrification processes were both completed in this wetland. For
the other 3 wetlands this is different. Table 13 shows an increase in nitrate nitrogen of more than
95% for the other 3 wetlands in both samplings. These results indicate that the removal of nitrogen
in these wetlands in hampered by the absence of the denitrification process. The denitrification
process takes place in anoxic conditions. If there is enough oxygen dissolved in the water of the
wetland the bacteria will use oxygen as an electron acceptor for their metabolic pathways. Absence
of oxygen leads the bacteria to substitute nitrate for oxygen as an electron acceptor.
Table 13. Removal efficiency of nitrogen constituents
Increase NO3 (%) Decrease in Nkj (%) Decrease in TN (%)
Sampling 1
Location A 98.89 84.1 41
Location B 0.00 94.4 94
Location C 99.64 95.8 56
Location D 98.96 99.55 16
Sampling 2
Location A 96.67 90.0 73
Location B 0.00 90.0 90
Location C 99.77 95.8 38
Location D 99.87 99.7 49
4.4Phosphorusremovalevaluation
In this paragraph the effluent requirements of total phosphorus (TP) in the wetlands is evaluated.
Figure 25 presents the influent composition of the different wetlands with regard to TP. Figure 26
45
and 27 give a comparative overview of the performance of the four wetlands on TP effluent
concentration and TP removal efficiency respectively.
Figure 25. Influent TP concentration
Figure 26. Effluent TP concentration Figure 27. Effluent TP removal efficiency
The effluent concentration for total phosphorus was the highest for the wetlands of Location C and
the Location D. The corresponding removal efficiencies were therefore the least for these wetlands.
The relationship between the influent concentration and the effluent concentration for TP is less
linear (R2=0.78). This indicates that there is a less strong relationship between the influent and the
effluent concentration.
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
18.0
20.0
Influent concentration (mg/L)
Sampling 1
Sampling 2
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
Effluent concentration (mg/L)
Sampling 1
Sampling 2
46
Figure 28. Relationship between influent and effluent concentration for total phosphorus
When evaluating the nutrient removal, TN and TP together, the Location D and Location C showed
the highest effluent concentrations and the lowest removal efficiencies compared to the other two
wetlands. This might be caused by the fact that these two wetlands also receive effluent water from
the septic tank. This water contains a lot of nutrients, more than grey water, which results in a higher
nutrient loading rate.
47
5.Discussion
Correlation tests between biodegradation constant and specific removal rate
Literature review in chapter 4 mentioned the biodegradation constants for several PPCPs in AS. This
parameter describes the quantity of a PPCP that is biodegraded by one gram of biomass in one day.
The higher the biodegradation constant, the easier biodegradable the compound is. Because this
parameter is an indication of the biodegradability and biodegradation being the main removal
mechanism for PPCPs, it is directly related to the specific removal rate (mg/m2/d) of a compound,
assuming that the amount of biomass does not change with the area. Compounds with a higher
biodegradation constant should reach a higher specific removal rate in case their loading rate does
not differ significantly. Therefore can be assumed that the biodegradation constant is proportional to
the specific removal rate. To check if this assumption is true a correlation test could be done, to
check if there is indeed a correlation between the removal rate and the biodegradation constant.
This test has not been done in this study, because of the following reasons:
The biodegradation constants from literature are only true for activated sludge systems
The biodegradation constants must be determined experimentally for each case distinctively
However, the biodegradation constant were used to classify the PPCPs as proposed by Joss et al.
(2006). The PPCPs that were classified as not removable according to their biodegradation rate, were
also observed to have no removal in almost all cases in this study (carbamazepine, sulfamethoxazole,
diclofenac). The PPCPs that were classified as partially removed according to their biodegradation
rate, were also observed to have no to incomplete removal in our study (atenolol, naproxen,
metoprolol, propanolol, sotalol). The PPCPs that were classified as very readily removed, were
alsoobserved to achieve very high removal efficiencies(>80%) in our study ( Ibuprofen and
paracetamol). These compounds are the most abundant once in waste water. An exception to this
classification is caffeine. According to its biodegradation constant it is classified as partially
removable. However, in this study it showed removal efficiencies higher than 95% in all cases and
should therefore be in the class of very readily removable compounds. The reason for this difference
could be the very high concentration in which caffeine was present in the waste water that entered
the wetlands, which made this compound more available to biomass than the compounds with a
lower influent concentration.
Design parameter: SRT
The improvement in the design parameters of CWs must address in the first place the improvement
of biodegradation of the PPCPs. This can be done by adjusting the design parameters to achieve the
desired contact time between sludge and PPCPs, F/M ratio and microbial diversity. The most
important design parameter to influence the degradation of PPCPs, mentioned in literature of
different types of waste water treatment plants is the SRT. The SRT is not a design parameter that
can be adjusted in CWs. It is definitely long enough to ensure a certain contact time between
biomass and PPCPs.
Design parameter: HRT
To reach a more sufficient contact time, the HRT should be adjusted. Using porous material with a
higher pore volume per unit of total volume, the HRT can be increased. For the studied wetlands this
means that the type of sand must be changed. Coarser material has a lower chance of clogging than
48
porous media with very thin pores. One must be cautious using too coarse material to improve the
pore volume, because this can result in less space for attachment of the biofilm. An alternative for
increasing the pore volume, while keeping the amount of space for attachment of biofilm, is adding
material with micro pores, like activated carbon. The HRT for wetlands is most accurate when the
water volume of the wetland is determined experimentally. The water volume of a SSFCW is equal to
the pore volume. The pore volume depends on the grain size of the sand, but also the plant roots
create and take up space and biofilm formation takes up pore space. The HRT in this study was not
measured experimentally, but estimated from an assumed value from literature for porosity of the
granular medium. The results from these estimated HRT values were more than 3 times higher than
the general assumed HRT for VFCWs. This is a very convenient, because it enables a very long contact
tie between biomass and waste water.
Another issue concerning the HRT is the fact that the HRT was not taken into account during the
sampling campaigns. For each sampling campaign the influent and effluent samples were taken at
the same date and same time. This method does not take into consideration the HRT. As the water is
retained for some time in the wetland after it enters the system as influent, the effluent that
complements these influent concentrations only exits the system after the HRT has passed. However,
the effluent samples were taken on the same time as the influent concentrations. The calculated
removal rates and removal efficiencies are based on the measured influent and effluent
concentrations during the 2 sampling campaigns which did not take into account the HRT. This could
be an explanation for the high negative values for the removal efficiencies of some PPCPs. Still an
assumption can be made that the waste water stream that leaves the households does not differ in
its composition over time, so the influent of the wetlands is constant in its composition over time
Critical design parameters in this study
The theoretical relationships between the design parameters discussed in paragraph 3.2 and the
removal efficiency of PPCPs could not all be tested in practice by this study. The cause for this is that
the design parameters were mostly similar for the four wetlands, as they are designed and build by
the same company (Brinkvos). The first parameter is the water depth. As Brinkvos designs all the
wetlands with the same depth, there was no difference in water depth between the wetlands. The
DO, type of plants and grain size was also the same for all the wetlands. The only difference was the
total volume of the wetland, the area of the wetland, the flow rate and the influent concentrations of
the pollutants. These were the parameters that got the focus of this study to analyse the
performance of the CWs.
There are still some significant differences in removal efficiency of PPCPS between the four wetlands.
The design parameters studied did not explain these differences. There might be unknown design
parameters still not mentioned in literature that are critical for the removal of PPCPs in SSFCWs.
Discussion on table 11
The qualitative analysis of the wetlands’ performance on PPCP removal was presented in table 11.
This table should elucidate the cases that deviate from the overall pattern for each compound to be
able to analyse which design parameters could have caused these deviations. This table showed that
the PPCPs which are reported in literature to be poorly removed are also the one with zero to 30 %
removal efficiency and with minimal deviations. Further analysis of compounds that did have
significant deviations showed no direct relations with design parameters.
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Applicability of CWs on the PPCPs removal compared to alternatives
Literature data show that MBR system reached by far higher removal efficiencies for almost all the
PPCPs in common with this study. However, MBR systems are more expensive to install and
maintain. MBR systems may be useful for the removal of PPCPs from waste water streams with
higher concentration, where a high removal efficiency is necessary. CW showed to be able to
remove PPCPs and are therefore applicable for the treatment of domestic waste water on a small
scale from PPCPS. Activated sludge systems showed similar to slightly higher removal efficiencies
than the CWs. For the treatment of domestic waste water on a large scale, activated sludge systems
would perform better in removing PPCPS.
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6.Conclusion
The conclusions are focussed on the research questions that were mentioned in the Introduction.
The conclusions are formulated to answer the research questions to the extent that the results of the
study allow.
What are the mechanisms and rates for removal of organic micro pollutants, BOD, TSS,
nitrogen and phosphorus?
o The main removal mechanism for PPCPs in VFCWs is most probably biodegradation
as the observed removal efficiencies are directly proportional to the biodegradation
rates from literature.
o According to literature the main removal mechanism for BOD, COD and nitrogen is
also biodegradation. CWs support biodegradation actively through supplying enough
attachment area for the microorganisms on the sand grains and the plant roots. The
plants provide oxygen which is necessary for the biodegradation of BOD and COD.
The biodegradation is observed to be satisfactory in all the wetlands.
Which design parameters are critical for enhancing the removal efficiency of organic micro
pollutants, BOD, TSS, nitrogen and phosphorus in SSFCWs?
o A significant correlation between the loading rate and the removal rate was
observed for the majority of the PPCPs measured in this study. The loading rate
depends on the influent concentration, the feed water flow rate and the wetland
area. This means that the area of the wetland and the flow rate of the feed water
can be adjusted to reach higher loading rates and consequently reach a higher
removal rate.
o The loading rate was also observed to have an influence on the removal rate of the
nutrients (nitrogen and phosphorus). The Location D and Location C showed the
highest nutrient concentrations in the effluent and the lowest removal efficiencies
compared to the other two wetlands. This might be caused by the fact that these
two wetlands also receive effluent water from the septic tank (which was fed with
black water), which increases the nutrient loading into the wetland.
o The nearly complete removed PPCPs are in accordance with the PPCPs mentioned in
literature to have a high biodegradation rate and efficient removal in other waste
water treatment systems. For these readily removable compounds the design
parameters are not critical, the long SRT of the wetlands is enough to allow nearly
complete removal.
o The design of the wetlands as executed by Brinkvos supports nearly complete
removal of BOD and COD (> 95%). The TSS removal is also observed to be >60%. This
number is high enough when the effluent water does not exceed the threshold limit
for TSS in effluent water form waste water treatment plants.
Which design parameters are limiting to the treatment process?
o According to literature data, a possible design parameter to limit the removal of
PPCPs could be the HRT. However, the HRT was not determined experimentally, but
estimated with an assumption for the porosity form literature. This estimation
resulted in HRTs that were with a factor of more than 3 higher than the reported HRT
values for other VFCWs. This is remarkable, because a high HRT can either be
51
supportive for the removal efficiency by providing enough contact time between
biofilm and waste water or it can result in overflowing of the wetland.
o The ratio of nitrate to total nitrogen in the effluent was observed to be high in all
wetlands, indicating the absence of the denitrification process in the wetlands. As
denitrification is an anoxic process that converts nitrate into nitrite, the absence of it
might be due to high DO in the wetland. To attain the presence of both nitrification
and denitrification in the wetland, the bed must have an aerobic zone and an anoxic
zone. If the bed is not deep enough the anoxic zone will not be present. Therefore a
shallow water depth might be a limiting factor nitrogen removal in a wetland.
o In literature clogging is mentioned as a major concern for SSFCWs. Clogging was not
observed in the four sampled wetlands. However, there is a chance it might have
occurred in the wetland of Location A, because Location A showed an increase in TSS
in the effluent during the second sampling campaign.
.
52
7.Recommendations
In this last chapter we present recommendations on how this research subject could be approached
to further answer the research questions.
Which design parameters are critical for enhancing/limiting the removal efficiency of organic
micro pollutants, BOD, TSS, nitrogen and phosphorus in SSFCWs?
o Perform continuous sampling of the influent and effluent water of the wetland to
analyse the trend in the concentration for: change in time and statistical analysis for
correlation and regression between parameters. This can give more support on the
(in) dependence of the removal efficiency on some design parameters.
o Further research to understand the characteristics of the biomass in CWs. As
mentioned in the report, the biomass is important in degrading the PPCPs. Biomass
has to be concentrated, preferably to have little flocks (for more specific surface) and
diverse in microbial populations. Insight in these characteristics for the biomass in
CWs can provide ideas on improvement of it.
o Except for the design parameters of the CWs, also the characteristics of the
compounds influence the removal efficiency. It can be therefore be recommended to
evaluate the chemical properties that have a enhancing/limiting effect on the
removal efficiency is necessary to make
Alternative applications:
o PPCPs fall into the category of OMP. Another group of OMP are the pesticides used
in agricultural fields. The irrigation water that enters the creeks and canals thus
contains a certain amount of these pesticides. To fully understand the potential of
CWs to removed OMP, pilot plants can be built to treat the effluent from agricultural
fields to study the removal of pesticides.
53
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Abbreviations
Abbreviation Description
CWs Constructed wetlands
SSFCWs Sub‐surface flow constructed wetlands
HFCW Horizontal flow constructed wetlands
VFCWs Vertical flow constructed wetlands
PPCPs Pharmaceuticals and personal care products
OMP Organic micro pollutants
BOD Biological oxygen demand
COD Chemical oxygen demand
TSS Total suspended solids
N/P Nitrogen/Phosphorus
DO Dissolved oxygen
Redox Reduction‐oxidation
HRT Hydraulic retention time
SRT Solids retention time
MBR Membrane bioreactor
CAS Conventional activated sludge
WWTPs Waste water treatment plants