Faezeh MahdaviMazdeh, Master thesis 2013-2014,

Faculty of Bioscience Engineering
Academic year 2013 – 2014
Investigating flocculation and discrete settling behaviour
of activated sludge by means of particle size analysis
Faezeh Mahdavi Mazdeh
Promotor: Prof. dr. ir. Ingmar Nopens
Tutor: ir. Elena Torfs
Master’s dissertation submitted in partial fulfillment of the requirements
for the degree of Master in Environmental Sanitation

Copyright
This in an unpublished M.Sc. thesis and is not prepared for further distribution. The author
and the promoter give the permission to use this thesis for consultation and to copy parts of it
for personal use. Every other use is subject to copyright laws, more specifically the source
must be extensively specified when using results from this thesis.
Ghent, 17 January 2014
The Promoter: The Author:
Prof. dr. ir. Ingmar Nopens Faezeh Mahdavi Mazdeh

II
Acknowledgement
It is hard to believe that I am writing the last word of my thesis. This research work would
not have been possible without support of many great people.
First of all, I would like to show my special appreciation and thanks to my Promoter, Prof. dr.
ir. Ingmar Nopens for giving me the opportunity to complete this research work under his
supervision at BIOMATH, UGent. I am very grateful to my tutor, Elena Torfs, BIOMATH,
UGent, for her motivation, enthusiasm and great knowledge. Her guidance helped me in
research work and writing up of this dissertation.
I am also greatly thankful to Giacomo Bellandi and Tinne De Boeck for their help in
experimental work in BIOMATH Laboratory.
Last but not the least, I would like to acknowledge with my heart to my family for their
encouragements and motivations and for their endless love. Finally, I would like to express
my thanks to my beloved friend, Mohammad who supported me during this work. His love,
patience and ambition reinforced me to finish this work.
Faezeh

III
Summary
Nowadays, the steady growth of the population causes an increased use of water and
subsequent increase in the quantities of wastewater. Hence, an appropriate wastewater
treatment is required. The main objective of wastewater treatment is to decrease pollutants to
acceptable levels consequently avoiding severe negative consequences to the public health or
the natural environment. The activated sludge process as a form of secondary treatment
generally removes contaminants through two process parts: a biological tank and a secondary
settling tank (SST). The objective of an SST is to separate the effluent from the microbial
mass and other particles that have the ability to settle out from the water (Mancell-Egala et
al., 2012). The clarification efficiency of a SST as the final phase of the biological
wastewater treatment is an important aspect in the performance of the wastewater treatment
plant (WWTP).
At very low sludge concentrations, particles with a low flocculating tendency will settle
individually. This settling is called the discrete settling regime and occurs in the upper region
of the SST. Since there is no interaction between particles, the settling velocity will be a
function of individual floc properties such as porosity, density and size (Vesilind, 2003). A
main problem in the study of the sludge settling behaviour is to determine this discrete
settling behaviour since no clear relation with the concentration of activated sludge exists. At
these low concentrations, the smaller, more slowly settling particles cannot settle in the SST
and therefore remain in the supernatant. These particles should be attached to other particles
in order to settle with larger particles and thus be removed. Hence, the activated sludge
flocculation has a significant role in the effectiveness of the clarification process.
Consequently, detailed knowledge of Particle Size Distribution (PSD) is required to better
describe the discrete settling and flocculation process. For this reason, the Ankersmid Eye-
Tech (The Netherlands) was used as an analyser to evaluate the floc size distribution of the
sludge samples.
In the first part of this work, a modified DSS/FSS test was performed to investigate the
influence of shear (force) on floc size and to follow the formation and break-up of activated
sludge flocs under different amounts of shear. The results showed that mixing prior to settling
has a significant effect on the (de)flocculation state of the particles and decreases the total

IV
number of particles in the supernatant after 30 minutes of settling. However, applying a very
high mixing intensity (96-100 rpm) increases the break-up of the activated sludge in the
sample. Moreover, it was found that physical parameters such as temperature have a
significant effect on the (de)flocculation state of particles. At lower temperatures, activated
sludge particles show more flocculating tendency resulting in better settling.
In the second part of this work, a new measurement device was built to study the discrete
settling behaviour in different particle size classes. This measurement device consists of a
settling column of approximately 9 liters and sampling points at different depths along the
column. A total of sixteen sampling holes were located at four various heights in the column.
Different sampling techniques were tried and compared to a sample collected from the top of
the settling column. Finally, the best sampling technique was selected with care in order to
ensure that the measurements were not influenced by wall effects or sample disturbances.
Depending on the initial concentration of activated sludge in the settling column, different
settling behaviours were observed through analysis of the changes in PSD at different times
during the settling process. At high concentrations, hindered settling, discrete settling and
differential settling can be observed. At very low concentration, two types of settling were
observed (differential settling and discrete settling). During the experiments, subsequent
settling of different groups of particles was observed. Discrete settling of particles can be
described in approximately in 5 classes and after 2 hours only very small particles (less than
100 µm) remained in the supernatant. These particles with low settling tendency thus need to
be captured by flocculation in the flocculation well of the clarifier. The results of this new
measurement device allow to calculate the discrete settling velocity for different size classes
which will lead to a better understanding of the settling behaviour in an SST.

V
List of abbreviations
WWTP Waste Water Treatment Plants
SST Secondary Settling Tank
BOD Biological Oxygen Demand
SS Suspended Solids
ESS Effluent Suspended Solids
SLR Solids Loading Rate
SOR Surface Overflow Rate
VZS Zone Settling Velocity
EPS Extracellular Polymeric Substances
PSD Particle Size Distribution
PIV Particle image Velocimetry
CCD Central-Composite Designs
CIS Computerized Inspection System
IMAN Automatic Image Analysis system
IE Inhabitant Equivalents
MLSS Mixed Liquor Suspended Solids
ESS Effluent Suspended Solids
DSS Dispersed Suspended Solids
FSS Flocculated Suspended Solids
LOT Laser Obscuration Time

VI
Contents
Acknowledgement................................................................................................................................ II
Summary .........................................................................................................................................III
List of abbreviations ............................................................................................................................V
1. INTRODUCTION....................................................................................................................1
2. LITERATURE REVIEW........................................................................................................2
2.1.Wastewater Treatment .........................................................................................................2
2.1.1.Primary treatment.......................................................................................................2
2.1.2.Secondary treatment...................................................................................................2
2.1.3.Tertiary treatment.......................................................................................................3
2.2The secondary settling tank...................................................................................................3
2.2.1.Thickening function in the secondary settling tank....................................................5
2.2.2.Sludge storage function in the secondary settling tank..............................................5
2.2.3.Clarification function in the secondary settling tank..................................................5
2.3.Classification of the sludge settling behaviour ....................................................................6
2.4.Determination of the settling velocity of sludge ..................................................................8
2.4.1.Measurements of the hindered settling velocity.........................................................9
2.4.2.Measurements of the compression settling velocity.................................................11
2.4.3.Measurements of the discrete settling velocity ........................................................11
2.5.Activated sludge flocculation.............................................................................................14
2.5.1.Composition of sludge flocs.....................................................................................14
2.5.2.Flocculation mechanisms.........................................................................................15
2.6.Particle size analysis ..........................................................................................................16
3. MATERIALS AND METHODS ..........................................................................................19
3.1.Activated sludge samples...................................................................................................19
3.2.Experimental set-ups..........................................................................................................19
3.2.1.Mixed Liquor Suspended Solids (MLSS) test..........................................................19
3.2.2.Dispersed Suspended Solids /Flocculated Suspended Solids (DSS/FSS) test .........20
3.2.3.Settling column test..................................................................................................22
3.2.4.Particle sizing using the Eye-Tech...........................................................................23
4. RESULTS AND DISCUSSION ............................................................................................28
4.1.DSS/FSS test......................................................................................................................28
4.1.1.Destelbergen WWTP results....................................................................................30
4.1.2.Eindhoven WWTP results........................................................................................36
4.1.3.Roeselare WWTP results .........................................................................................41

VII
4.2.Settling column test............................................................................................................45
4.2.1.Sampling techniques ................................................................................................45
4.2.2.Settling column results.............................................................................................48
4.2.2.1.Settling column test results at point 1...........................................................49
4.2.2.2.Settling column test results at point 3...........................................................60
5. CONCLUSIONS AND PERSPECTIVES............................................................................65
5.1. Conclusions .....................................................................................................................65
5.2. Perspectives.....................................................................................................................66
Bibliography........................................................................................................................................68

CHAPTER 1
1
1. INTRODUCTION
The activated sludge process is the most widespread process for the biological treatment of
wastewater. The final step in this process is the separation of sludge flocs from the effluent in
a secondary settling tank (SST). Therefore, the SST as a clarifier has a significant function in
a wastewater treatment plant (WWTP) and has to produce a clean effluent. When the SST
fails, this will have a significant effect on the overall performance of a WWTP.
The operation and control of SSTs is still an important performance-limiting factor in
conventional WWTPs. The efficiency of the latter depends on the flocculation of the
microorganisms in large, dense flocs that settle fast, thus separating the sludge from the
treated water. Therefore, the settling behaviour of the sludge is a crucial factor in
understanding the performance of the solid-liquid separation.
At lower concentrations, as can be found in the upper region of an SST, the particles are too
far apart to sense each other and the settling velocity will depend on the size and density of
each individual floc and not on their concentration. Each particle will thus settle at its own
characteristic velocity (Ekama et al., 1997). This top region of an SST is of particular interest
since particles that settle poorly here, will be carried over the overflow weir causing a
deterioration of the effluent quality. In order to accurately describe the settling behaviour in
this region, information on the changes of the floc size distribution needs to be included.
The flocculation of activated sludge is a significant process for the effectiveness of the
treatment process and it is especially important for small and discrete particles which settle
individually. So, improving knowledge on the flocculation process is an important
requirement for optimal biological wastewater treatment. Therefore, the first objective of this
thesis is to evaluate the effect of different shear forces on the (de)flocculation state of
particles in the supernatant liquid above by means of particle size analysis.
The second objective is to build a novel measurement device to investigate the discrete
settling behaviour of the activated sludge and to determine the settling velocities of different
particle classes by means of particle size analysis during batch settling in a column. This
detailed data will significantly aid in understanding the settling behaviour of sludge particles
at low concentrations which will subsequently lead to improved predictions of the effluent
concentrations.

2
CHAPTER 2
2
2. LITERATURE REVIEW
2.1. Wastewater Treatment
Nowadays, an increased use of water causes a subsequent increase in the production of
wastewater. Hence, an appropriate treatment of the wastewater is necessary both with respect
to the human health and the protection of the environment. Depending on the source of the
wastewater, its composition consists of a combination of dissolved and particulate
compounds. Large amounts of organic and inorganic matters, pathogens and microorganisms
are frequently present in wastewater. The main objective of wastewater treatment is to
decrease these contaminants to acceptably low concentrations thus averting harmful effects to
the public health or the natural environment.
The treatment of municipal wastewater consists of a combination of physical, chemical and
biological processes (Tchobanoglous et al., 2003). In a WWTP, these process units are
grouped in primary, secondary and tertiary treatments. A schematic overview of the
wastewater treatment process is given in Figure 2.1.
2.1.1. Primary treatment
Primary treatment typically consists of physical operations (such as screening, fat removal
and primary settling of sand) to remove a portion of the settleable solids, organic matter,
large trash and grit from the wastewater. Almost 25 to 50% of the Biochemical Oxygen
Demand (BOD5), 50 to 70% of the suspended solids (SS), and 65% of the oil and grease are
removed during this treatment step (FAO, 1992).
2.1.2. Secondary treatment
Activated sludge process as a form of secondary treatment typically involves a biological
treatment to remove biodegradable organic matter, suspended solids and nutrients through
two process units: a biological tank and a secondary settling tank (SST). In the biological
tank a mixed culture of microorganisms, called activated sludge, converts the organic matter
into biomass. The tank is aerated to keep the sludge in suspension and to provide the
microorganisms with oxygen for the conversion of the organic matter. After the biological
tank, the sludge is transported to the SST where it is allowed to settle in order to produce a
clean effluent. Part of the sludge is recycled to the aeration tank; the rest is transported for
sludge processing and/or removed as sludge waste.

3
CHAPTER 2. LITERATURE REVIEW
3
2.1.3. Tertiary treatment
Tertiary treatment is the next step after the secondary treatment. It consists of additional
processes (such as granular medium filtration or microscreens) to remove residual suspended
solids. By using stronger and more advanced treatment processes wastewater effluent
becomes even cleaner in this step.
Figure 2.1: Overview of a biological wastewater treatment facility (Nopens, 2005)
2.2. The secondary settling tank
In the activated sludge process, the treated wastewater needs to be separated from the
biological sludge mass in order to produce a clear final effluent (Ekama et al., 1997). The
objective of a SST or clarifier is to facilitate the gravitational separation of the microbial
mass and other particles from the treated water that either get enmeshed in the mixed liquor
or have the ability to settle out from the water (Mancell-Egala et al., 2012). As the final step
of the activated sludge-based biological wastewater treatment the SST is therefore one of the
most critical processes in a WWTP.
Circular and rectangular settling tanks are the main types of tanks found in WWTPs.
A schematic of half a circular secondary settling tank is shown in Figure 2.2. The sludge from
the biological tank enters the SST through a central inlet pipe. In the SST particles can settle

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4
gravitationally and therefore form a sludge blanket at the bottom of the tank. The bottom of
the basin has a small slope; a scraper transmits the sludge towards the sludge hopper where it
is removed with the underflow. Part of this sludge is recycled to the aeration tank and the
remainder is removed as sludge waste. The clean effluent flows over the edge at the top of the
tank. Furthermore, the placement of baffles in the system prevents the short circuiting of the
flow between the inlet and effluent overflow and thus ensures a minimal residence time in the
tank.
Figure 2.2: Schematic view of a half circular secondary settling tank
Rectangular settling tanks are basins which are rectangular in cross sections. In these
clarifiers, water flows horizontally through a long basin.
The SST plays an essential role in the performance of the activated sludge process. It
combines several functions: it works as a clarifier to produce a low effluent suspended solids
(ESS) concentration, a sludge thickener to provide a continuous underflow of biological
sludge mass to return to the aeration tank and a sludge storage tank to store sludge during
peak flow conditions.
The settling tank should succeed in all of its functions otherwise SS can escape from the
clarifier to the effluent resulting in a poor effluent quality. Moreover, the loss of solids can
result in less sludge to be returned to the biological reactor which will influence the
performance of the entire treatment plant.
Hence, it is essential to concentrate on understanding the functions of the SST in order to
control and optimize its operation in a wastewater treatment plant.

5
5
2.2.1. Thickening function in the secondary settling tank
The thickening capacity of the SST is controlled by the tank’s geometry, the flow rates, the
settleability and compactability of the sludge, and the concentration of the solid particles in
the biological tank. It requires the majority of the sludge mass (over 98%) that enters the SST
to settle at sufficiently high concentrations in order to produce a thickened underflow to be
returned to the biological reactor (Nopens, 2005). Failing to achieve the thickening function,
the treatment plant capacity will noticeably decrease because less sludge is recycled to the
biological reactor. Furthermore, well compacted solids decrease the costs related to sludge
disposal and dewatering processes.
2.2.2. Sludge storage function in the secondary settling tank
Wet weather events are extremely stressing conditions in treatment plants due to an increased
Solids Loading Rate (SLR) and Surface Overflow Rate (SOR). Under these conditions,
sludge will be moved from the aeration tank to the SST. In order to prevent loss of sludge, the
SST needs to be able to store this extra sludge.
This storage function is mainly ensured by a proper design of the SST. According to the
literature, two noticeably different designs are introduced to cope with this increased flow
rate into the SST. The first technique to deal with solids inventory transfer is to arrange extra
tank volume for storage (Ekama et al., 1997; De Clercq, 2003). Another possible method is
aeration tank settling (Reardon, 2005). During peak flow conditions, the suspended solids are
allowed to settle in the aeration tank causing less sludge to enter the SST.
2.2.3. Clarification function in the secondary settling tank
According to Ekama et al. (1997), the thickening function has been studied and considered
more than the clarification function although this function of SSTs is an equally vital
component as thickening. The clarification efficiency of the SST depends on the capability to
capture the activated sludge particles that enter the SST in the sludge blanket and is
consequently a critical aspect in the performance of the WWTP.
Failure with respect to clarification behaviour of the SST may result in increased
concentration of ESS. The annual mean ESS concentrations should be less than the
acceptable level.

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6
Several factors influence the clarification function and therefore the performance of the SST.
These factors include: design features such as external dimensions of the clarifier (e.g.
surface area, depth), internal features of the SST for instance inlet structure, outlet structure,
sludge collection, baffle arrangement, hydraulic disturbances (e.g. short-circuiting or
resuspension of sludge particles due to high velocity currents), thickening overloads because
of high sludge blankets, denitrification processes in the SST (Ekama et al., 1997) and the
flocculation state and flocculation tendency of the activated sludge (biological and physical
flocculation). With respect to this last factor it is not only important to produce flocs of
sufficient mass to settle in the SST but also to reduce the concentration of small, discrete
solids that do not have enough mass to settle in the SST (Nopens, 2005). A more detailed
explanation of flocculation behaviour is given in section 2.5.
2.3. Classification of the sludge settling behaviour
As mentioned above, the ability of sludge particles to flocculate and form dense flocs, which
can settle rapidly and be separated in the secondary clarifier, depicts the efficiency of the
WWTP.
The effectiveness of sludge settling depends on a number of factors. Although, the physical
factors such as hydrodynamics will of course influence the sludge settling, the settling
behaviour of the sludge is also a crucial factor in understanding the performance of the solid-
liquid separation. This settling behaviour is dependent on the sludge concentration throughout
the system and on the flocculation tendency of the sludge particles. In this section, details
concerning the settling behaviour of sludge will be discussed.
According to the concentration and the flocculation tendency of particles, four classes of
settling can be distinguished (Ekama et al., 1997). The four different settling regimes are
illustrated in Figure 2.3 and will be explained in more detail.
The first class is called the discrete settling regime. This regime is characterized by very low
sludge concentrations and a low flocculating tendency. At these low concentrations, the
particles will settle individually. This class is represented at the top left part of Figure 2.3 and
is also known as clarification. Discrete settling occurs in the upper region of the SST and
because the concentration is too low for interaction between particles, the settling velocity

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7
will be a function of individual particle properties such as porosity, density and size
(Vesilind, 2003).
Class II or discrete flocculent settling (in the top right region of Figure 2.3) will also take
place at low solids concentrations but when the particles show a strong flocculating tendency,
thus forming dense individual flocs which will finally settle faster. This process occurs in the
upper middle region of the SST. This type of settling is also known as clarification. Since
there is no interaction between particles, the settling velocity will depend on individual
particle properties.
Class III or hindered settling (the middle area in Figure 2.3) occurs when the concentration of
particles increases. This class of settling is known as zone settling in which sludge particles
can settle as one mass with the same velocity in the same direction because of inter-particle
forces. Because of a high concentration of sludge particles the fluid tends to move upwards as
the sludge mass moves downwards. As a result, there is a relatively clear layer of supernatant
liquid above the particles. This type of settling occurs in the lower middle region of the SST
and the settling rate in this zone is a function of sludge concentration regardless of the size or
density of the individual solids. In this type of settling, the concentration of particles is not
high enough for actual contact and activated sludge particles only sense each other indirectly.
At even higher concentrations the particles come in physical contact with each other and start
to form a compression layer at the bottom region of the SST. The mechanical contact creates
a compressive stress which squeezes the particles together causing the water to move
upwards. The settling regime is known as class IV settling or compression settling and is
illustrated in the bottom area of Figure 2.3.

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8
Figure 2.3: Schematic representation of the different settling regimes (Ekama et al., 1997)
2.4. Determination of the settling velocity of sludge
Based on the above, different settling regimes can be characterized at different locations in a
SST. These settling regimes are mostly dependent on the nature and concentration of the
solids and the interaction between the activated sludge particles (Tchobanoglous and Burton,
1991). The settling in a SST can be typically classified into three types, (1) discrete settling at
low concentrations (including discrete non-flocculent settling and flocculent settling); (2) the
zone settling (hindered settling); and (3) the compression settling. These three types of
settling in a SST are shown in Figure 2.4.
To evaluate the performance of a SST, it is essential to describe the settling behaviour in
these different regimes. Subsequently, several methods aim to determine the settleability of
the activated sludge by measuring the sludge settling rate in order to find a mathematical
relation between sludge velocity and sludge properties.
Figure 2.4: Different settling regions of the activated sludge in a SST

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9
2.4.1. Measurements of the hindered settling velocity
As long as the sludge concentration is sufficiently high (above 600-700 mg L-1
), hindered
settling occurs. In this regime, the settling velocity is independent of the individual particle
properties but it is only a function of the local sludge concentration. Thus, each particle is
hindered by other particles and the settling of each particle is influenced by the existence of
other particles (non-stokian hindered).
To measure hindered settling velocity, batch settling tests can be performed (Vanderhasselt
and Vanrolleghem, 2000). In a batch settling test the height of solid/liquid interface is
determined as a function of time. At first, the initial sludge sample is allowed to settle in the
column for a specific time. Next, the procedure is done at a lower sludge concentration and a
new batch settling curve is recorded. This experiment is repeated till a set of settling curves at
different sludge concentrations are obtained (see Figure 2.5). The linear slope of each curve
gives information on the hindered settling velocity at that concentration.
Figure 2.5: Batch settling tests (left) and settling curves obtained from batch settling tests (right)
(Vanderhasselt and Vanrolleghem 2000)
There have been numerous studies to determine the exact relation between the hindered
settling velocity and the concentration of activated sludge. Consequently, a number of
theoretical and empirical models for the hindered settling velocity have been reported in the
literature (Vesilind, 1968; Dick and Young, 1972; Vaerenbergh, 1980; Takács et al., 1991;
Cho et al., 1993; Watts et al., 1996, Lakehal et al., 1999; Vanderhasselt et al., 2000; Giokas et
al., 2003; Zhang et al., 2006; De Clercq et al., 2008). From these, the most widely accepted
are the functions by Vesilind and Takács.

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10
The zone settling velocity (VZS) defined by Vesilind is expressed as:
(2.1)
where X is the solids concentration; k and n are two settling parameters which can be
estimated from the slopes of the batch settling curves. The exponential function by Vesilind
as a function of the activated sludge concentration is shown in Figure 2.6.
Figure 2.6: Settling velocity as a function of the activated sludge concentration based on Vesilind function
(Vesilind, 1968)
It should be noticed that Vesilind’s equation applies only to hindered settling conditions. At
lower concentrations (as occur in the upper layers of the SST) the settling velocity predicted
by Vesilind will exceed the actual settling velocity of the particles (dashed line in Figure 2.7).
This is why Takács et al. (1991) altered the Vesilind’s settling velocity function to obtain
better predictions of the settling velocity of particles at low concentrations (see Figure 2.7).
The settling velocity by Takács et al. is expressed as:
(2.2)
In which vsj is settling velocity of the solids particles (m d-1
); v0 is maximum settling velocity
(m d-1
); rh is settling parameter characteristic of the hindered settling zone (m3
g-1
); rp is
settling parameter characteristic of low solids concentration (m3
g-1
); X*j is X-Xmin; Xmin is
minimum suspended solids concentration (g m-3
).

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11
The first part of equation (2.2) presents the settling velocity of the large and well flocculated
particles and the second part of equation (2.2) reflects a velocity correction for smaller and
slowly settling particles (Takács et al., 1991).
Note that the physical properties of activated sludge flocs and solid-liquid interaction have
not been considered in the empirical models of Vesilind and Takács (De Clercq et al., 2007).
Figure 2.7: Settling velocity model in different sludge concentration (Takács et al., 1991)
2.4.2. Measurements of the compression settling velocity
Compression settling takes place as the settled solids are squeezed under the weight of
overlying particles at elevated activated sludge concentrations (above 3-7 g L-1
).
Compression settling is important since it influences the thickening of the sludge. To measure
compression settling, De Clercq et al. (2005) measured complete solids concentration profiles
during batch settling tests by means of non-destructive techniques such as gamma-ray. From
these experiments a function was derived to describe compression settling (De Clercq et al.
2008).
2.4.3. Measurements of the discrete settling velocity
Above the sludge blanket the concentration of sludge is significantly lower and the regime of
discrete settling prevails. In this regime the settling velocity is determined by individual floc
properties such as density, size, etc. In discrete settling, when an individual floc falls through
a fluid due to gravity, the terminal velocity of the particle follows Stokes settling velocity
regarding to stokes’ law (Stokian settling).
(2.2)

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In which V is settling velocity (m s-1
); s is mass density of particle (kg m-3
); is mass
density of the fluid (kg m-3
); d is diameter of the particle (m); g is gravitational acceleration
(m s-2
); μ is dynamic viscosity (kg m-1
s-1
).
In discrete flocculent settling three dominant forces will act on the particles: gravity,
buoyancy, and drag. However, activated sludge particles are not completely spherical and the
porosity of the particles will also play a main role in predicting the settling velocity (Kinnear,
2002).
A main problem in the study of the sludge settling behaviour is to determine the settling
velocity of sludge at low concentrations because of no clear relation with the concentration of
activated sludge. However, accurately describing the discrete settling regime is of particular
importance to predict the effluent concentrations in a SST.
As explained above, Takács et al. (1991) tried to describe the sludge settling behaviour at low
concentrations by modifying the hindered settling velocity function as indicated in Figure 2.7.
However, even though this function gives more realistic effluent predictions than the function
by Vesilind, it is not able to accurately predict the discrete settling behaviour of sludge since
the settling velocity of sludge at low concentrations is not dependent on the sludge
concentration but on individual particle properties. Hence, it is merely a trick to mimic the
settling behaviour but no fundamental solution.
Because of the difficulty to study the sludge settling behaviour at low concentration (below
0.6 g L-1
) (Mancell-Egala et al., 2012), often the zone settling velocity functions are used to
describe the settling process at low concentrations either by directly modifying the functions
(Takacs et al., 1991; Dupont and Dahl, 1995) or by defining particles with different settling
velocities (Dupont and Henze, 1992; Lyn et al., 1992; Otterpohl and Freund, 1992;
Mazzolani et al., 1998, Zhang et al., 2006).
More recently, numerous studies have been performed aiming at the development of reliable
models that would suitably estimate the value of the discrete settling velocities of activated
sludge in a settler (Kinnear, 2002, 2004; Griborio, 2004; McCorquodale, 2004; De Clercq,
2003; Griborio et al., 2008). Some studies have developed a settling column to measure
discrete settling velocities for different floc sizes and calculated the discrete settling velocity
based on a settling velocity function (Griborio, 2004). Kinnear (2002) developed a pilot

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13
experiment for settling behaviour and described how the multiphase computational fluid
dynamic model incorporated a flocculent settling velocity. However, no generally accepted
solution to describe the discrete settling behavior seems to exist to date.
Mancell-Egala et al. (2012) compared predictions of the Vesilind settling function to data of
measured discrete settling velocities done by Kinnear (2002) and McCorquodale (2004). This
comparison is shown in Figure 2.8.
Figure 2.8 reveals that different discrete settling velocities can be measured for different
sludge samples and different floc sizes. This confirms that models which relate the discrete
settling velocity to sludge concentration are not an accurate representation of the settling
behavior of discrete particles occurring in a SST. Different conditions of measurements
(environment and equipment) as well as the characteristics of the individual particles can
influence the settling behavior of discrete particles. Therefore, considerable attention should
be paid to the investigation of accurate measurement techniques and suitable modeling
equations in order to describe the discrete settling behaviour.
Figure 2.8: Vesilind Equation and Measured Discrete Velocities depicted in this graph to illustrate the
sharp discontinuity exhibited in settling velocities when settling type changes after Kinnear 2010
(Mancell-Egala et al., 2012).

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2.5. Activated sludge flocculation
As mentioned above, the discrete particles show different settling velocities depending on
their size and density. After settling, a part of these particles cannot settle in the SST and
therefore remains in the supernatant. Because of this, the smaller, more slowly settling
particles should be adhered to other particles in order to settle with larger, more rapidly
settling particles and thus be removed. The purpose of activated sludge flocculation is to form
flocs from fine individual particles. Large and dense flocs can settle rapidly and incorporate
the discrete particles that normally would not settle alone. For this reason, the flocculation of
activated sludge plays a critical role in the effectiveness of the clarification process (Biggs
and Lant, 2000) and the settling of discrete particles in the upper layer of a settler. In order
for the activated sludge process to operate successfully, it is essential to obtain a flocculent
biomass that settles rapidly and compacts properly in the SST (Grady et al., 1999).
The flocculation of activated sludge is a very complex process, including physical, chemical
and biological phenomena (Govoreanu, 2004). Flocculation is a transport step that brings
about the collisions between the destabilized and individual particles needed to form larger
particles that can be removed readily by settling or filtration (Tchobanoglous et al., 2003).
This section discusses the composition of activated sludge flocs and their flocculation
mechanisms.
2.5.1. Composition of sludge flocs
Activated sludge flocs contain a complex mixture (see Figure 2.9) of different
microorganisms, dead cells, particulate organic and inorganic matters and extracellular
polymeric substances (EPS) (Nopens, 2005). The structure of flocs is very heterogeneous and
the size varies from a few to about 1000 μm (Li and Ganczarczyk, 1990, 1991). Several
authors reported different ranges of floc sizes for mixed liquor activated sludge (Parker et al.,
1970; Li and Ganczarczyk, 1991; Andreadakis, 1993; Jorand et al., 1995; Mikkelsen, 2001).
The knowledge about the structure of flocs is important since it determines floc size and
density and finally it will affect the sludge removal efficiency during the settling process.

15
15
Figure 2.9: Image of an activated sludge floc (left) and its composition (right) (Govoreanu, 2004).
The overall floc structure is formed through physicho-chemical interactions between
microorganisms, inorganic particles (silicates, calcium phosphate and iron oxides), EPS and
multivalent cations (Ca2+
, Mg2+
). EPS encloses the microbial cells and plays a significant role
in binding the floc constituents together (Snidaro et al., 1997). However, not only the
physico-chemical aspects must be taken into account, also the changes in properties of the
sludge floc due to microbial activities must be considered.
The microorganisms in the activated sludge consist of a large variety of heterotrophic
bacteria, fungi, protozoa and metazoa. From a flocculation point of view the microorganisms
can be divided into two groups: filamentous species and floc-forming species. The negative
effect of filamentous bacteria on sludge settling is clear. Because protrude from the flocs may
form open structured flocs which cause poor settling. Moreover, filamentous bacteria also
have a positive influence on sludge settling because the floc structure can filter out small
particles which improves the clarification efficiency. So, a good balance between filamentous
and floc forming bacteria is essential for a well settling and compacting floc (Sezgin et al.
1978).
2.5.2. Flocculation mechanisms
As a result of its complex structure, several factors might interact and influence the floc
formation in the activated sludge process. This makes it difficult to thoroughly evaluate or
successfully quantify the mechanisms of flocculation.
Different phases of floc formation take place during the flocculation process. At the start,
particle growth is prevailing in which particles mix by coagulation and their size enhances
quickly. As flocculation continues, the flocs form large, porous and open structures that are

16
16
more sensitive to break down by liquid shear (Spicer et al., 1996). According to Thomas et al.
(1999), the mathematical demonstration of flocculation has usually been based on
considering the mechanism as two distinct phases: transport and attachment. The transport
step, leading to the collision of two particles, can be achieved by several processes: (1) the
random thermal “Brownian” motion of particles (microflocculation or perikinetic flocculation
for particles in the size range from 0.001 to about 1 μm), (2) the forced velocity gradients
from mixing (macroflocculation or orthokinetic flocculation for particle sizes greater than 1
or 2 μm) and (3) the differences in the settling behaviour of individual activated sludge
particles (differential settling) (Tchobanoglous et al., 2003).
Numerous studies have been presented in the literature to describe and characterize the
activated sludge flocculation mechanisms. Parker et al. (1970, 1971, and 1972) illustrated the
convenience of a flocculation zone prior to the final settling step. Biggs et al. (2000)
presented and evaluated an experimental technique to monitor activated sludge flocculation
and changes in floc size during the settling. They specifically focussed on the influence of
shear on flocculation. Moreover, several experimental methods were described considering
the effect of different factors (e.g. cations and polymers) on the flocculation process (Liu et
al., 2003; Haisong et al., 2012).
The knowledge related to the flocculation process of activated sludge can be enhanced only
by a careful analysis of the different factors, physico-chemical aspects, and composition of
the sludge flocs that affect the process. Additionally, changes in environmental conditions
must be taken in account. Moreover, the structure of the activated sludge is a significant
parameter in floc formation which influences the effectiveness of the clarification process.
Govoreanu (2004) considered and analyzed the effect of important factors (e.g. temperature,
cations, dissolved oxygen and activated sludge concentrations) on the flocculation process.
Van Dierdonck et al. (2013) investigated the sensitivity of a well flocculated system and
monitored the bioflocculation process through an extensive set of parameters, including
microscopic image analysis.
2.6. Particle size analysis
Based on the above, one of the important parameters with respect to the performance of an
SST is the flocculation behaviour of the activated sludge flocs. Above the solids blanket
where the discrete settling mechanism prevails, knowledge about floc sizes is of crucial

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17
importance. Consequently, detailed knowledge of size distribution of activated sludge flocs is
required for better understanding of the activated sludge settling and flocculation process and
more effective control of the process performance.
A Particle Size Distribution analysis (PSD) is a measurement to determine and report
information about the size and range of a set of particles. Because of the very extensive PSDs
and very heterogenous structure of the activated sludge floc, measurements of the particle
size are a complex task (Govoreanu, 2004).
Several methods have been applied to analyze the size of activated sludge flocs. The
microscopy technique (Barbusinski and Koscielniak, 1995) is an excellent method to directly
examine the activated sludge flocs. In manual microscopy technique, elaborate sample
preparation is required and only a small number of particles can be studied. Recently, novel
techniques allow connecting a microscope to automated image analysis software for faster
assessment of floc properties (Mesquita et al., 2009).
Another method used for determination of the activated sludge floc size distribution is the
Coulter Counter (Andreadakis, 1993). Because of some limitations, this technique is applied
only for small particles and in steady state condition.
Ganczarczyk (1994) used a photographic technique in order to determine the settling
behaviour of a single particle. A more recent, advanced technique is the so-called Particle
Image Velocimetry (PIV), which applies a central-composite designs (CCD) video camera to
analyse the particles on-line and subsequently calculate the settling velocity of particles.
Computerized Inspection System (CIS) devices (combining laser and video channels) were
used successfully to characterize floc size and observe the settling properties and the shape of
activated sludge in a secondary clarifier (Hiligardt and Hoffman, 1997).
Agrawal and Pottsmith (2000) utilized in-situ laser diffraction to determine particle size
distributions in the discrete settling zone. In addition, De Clercq et al. (2002) developed a
focused beam reflectance method (FBRM) to measure in-situ the floc size distribution in a
secondary sedimentation tank of a WWTP.
Biggs and Lant (2000) investigated activated sludge flocculation using a light scattering
instrument (Malvern Mastersizer/E); Nopens et al. (2002) used the laser light diffraction

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18
technique by using a Malvern Mastersizer to monitor the flocculation dynamics of activated
sludge. Houghton et al. (2002) determined the PSD of primary and waste activated sludge by
using laser diffraction through the Malvern Mastersizer 2000. Govoreanu et al. (2004)
coupled three devices: a Mastersizer (Malvern, UK), a CIS-100 (Ankersmid, Belgium) and an
automated image analysis system (IMAN) to characterize the PSD of activated sludge flocs.
As can be seen from the above, the floc size or size distribution of activated sludge has often
been described in studies by a range of measurement techniques. However, less importance
has been given to the influence of the measurement technique on the outcomes (Govoreanu et
al., 2004). In particle size analysis different results can be achieved because of the application
of numerous devices with a broad range of measurement principles. Therefore, care should be
taken when interpreting the data of activated sludge analysis from a specific measurement
device (Govoreanu et al., 2004).

19
CHAPTER 3
19
3. MATERIALS AND METHODS
3.1. Activated sludge samples
The activated sludge and secondary effluent samples were collected from three different
WWTPs: the WWTPs of Destelbergen (Belgium), Roeselare (Belgium) and Eindhoven (The
Netherlands). All three of these WWTPs treat domestic wastewater by using the activated
sludge process. The activated sludge samples were taken from the aeration tanks or from the
splitting works after the aeration tank.
The WWTPs of Destelbergen and Roeselare have a biological capacity of 59,600 and 65,700
inhabitant equivalents (IE) respectively. Next to the sludge from these WWTPs, sludge from
the WWTP of Eindhoven was used. The Eindhoven WWTP is the third largest treatment
plant of The Netherlands with a biological capacity of 750,000 IE. The treated water
discharges to the Dommel River.
The activated sludge samples collected from the WWTPs were brought in 10 L plastic
containers to Ghent University and the experiments were performed at the Biomath
laboratory. Hence, the alteration of sludge properties due to the transportation and storage
should be considered. Furthermore, a measurement campaign was carried out at the WWTP
of Roeselare in order to decrease the influence of transport on the settling properties of the
sludge.
3.2. Experimental set-ups
3.2.1. Mixed Liquor Suspended Solids (MLSS) test
To measure the suspended solids concentration in the supernatant of the sludge samples, the
Mixed Liquor Suspended Solids (MLSS) test was applied. For this approach, a MLSS-test
was performed by taking the following steps:
1. Three fiber glass filters were used and each filter was rinsed three times with distilled
water using a Buchner funnel to suck the water.
2. The rinsed filters were transferred to aluminum dishes and placed in the oven at a
temperature of 105°C for at least two hours.

20
CHAPTER 3. MATERIALS AND METHODS
20
3. The dried glass-fiber filters were cooled in a desiccator for at least 1 hour. A desiccator is
an airtight jar to protect the filters from water vapour in the atmosphere and remove
traces of water which could not be removed after the drying period in the oven.
4. After the filters were cooled down, they were weighed on a balance. The balance was
located close to the desiccator to avoid re-uptake of water during transport of the filters.
The measured weight was the weight of empty filters (m1).
5. Subsequently, each fiber glass filter was placed on the Buchner funnel apparatus to filter
200ml of supernatant of the activated sludge sample.
6. Afterwards, the filters were put in the oven again for minimum two hours and in the
desiccator for 1 hour.
7. Finally, the dried filters with sample (m2) were weighed by getting them one by one out
of the desiccator.
The MLSS concentration can be determined by means of Equation 3.1:
(3.1)
3.2.2. Dispersed Suspended Solids /Flocculated Suspended Solids (DSS/FSS) test
Wahlberg et al. (1995) proposed a procedure which determines the efficiency of flocculation
and/or hydraulics in a given SST, the so called DSS/FSS test. The DSS/FSS test can be
grouped in three parts: the Effluent Suspended Solids (ESS) test, the Dispersed Suspended
Solids (DSS) test, and the Flocculated Suspended Solids (FSS) test.
The DSS test is a test in which the sample is settled for 30 minutes and the remaining
concentration (DSS) in the supernatant is measured after this time (measuring method was
initially developed by Parker et al., 1970). The FSS test is a test in which the mixed liquor
sample is flocculated for 30 minutes in a paddle stirrer with rotational velocities of 50 rpm
and then settled for 30 minutes. After this, the concentration in the supernatant (FSS) is
measured.
Using the DSS and/or FSS test has been proven to be a useful technique in several studies: it
allows to assess flocculation and deflocculation processes in transmission channels (Parker et
al., 1970; Parker and Stenquist, 1986; Das et al., 1993), to determine the influence of
hydraulic disturbances in the aeration basin on the effluent non settleable sludge particles

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21
(Parker et al., 1970; Das et al., 1993), to determine the benefits of a flocculation procedure in
decreasing ESS in a WWTP (Wahlberg et al., 1994) and to identify failure mechanisms.
Kinnear (2000) provided a DSS/FSS troubleshooting matrix (Table 3.1) which shows the
cause of the poor performance under various testing scenarios (Kinnear, 2000). The
clarification failure can thus be investigated by analyzing three samples (ESS, DSS and FSS).
Table 3.1: Flocculated Suspended Solids/Dispersed Suspended Solids Troubleshooting Matrix
ESS High and: FSS
HIGH LOW
DSS HIGH Biological Flocculation Physical Flocculation
LOW Not Possible Hydraulics
In this thesis, the influence of stirring the sample (shear) on the (de)flocculation process was
investigated for sludge samples from three different WWTPs. The experiments were
performed in two parallel settling jars with approximately a height of 21 cm and a width of
13 cm. The square settling jars were selected for this experiment because this configuration
avoids the formation of a vortex and thus eliminates the requisite for any in-vessel baffling
(Ekama et al. 1997).
First, a DSS test was performed. In this test, each jar was filled by approximately 2 liters of
activated sludge sample from the aeration tanks (without dilution). The sludge sample was
mixed carefully to keep it homogeneous before pouring it in the settling jars. The sample was
allowed to settle for 30 minutes after which the supernatant liquid above was collected by a
manual pipette for further analysis with the Eye-Tech (see section 3.2.4). The process is
shown in Figure 3.1.
Secondly, an FSS test was performed. In this test, the sludge samples in the settling jars
(same sludge samples were used to compare the results) were first allowed to flocculate for
30 minutes by mixing with a 3-bladed stirrer at four different rotational velocities (rpm) (see
Figure 3.2). After the flocculation fase, the mixing was stopped and the sludge was allowed
to settle for 30 minutes. Finally, the supernatant liquid above was collected with a manual
pipette for further analysis with the Eye-Tech (see section 3.2.4). In this thesis, 4 rotational
speeds were applied: (1) the lowest speed of 37-42 rpm, (2) the standard speed of 47-52
(Parker et al., 1970), (3) the rotational speed of 68-73 rpm and (4) the highest rotational speed
of 96-100 rpm. The different rotational speeds were controlled by an electrical mixer.

22
22
Figure 3.1: Photograph of settling jars used for the Dispersed Suspended Solids (DSS) test
Figure 3.2: Photograph of the electrical mixer used for Flocculated Suspended Solids (FSS) test
3.2.3. Settling column test
A new measurement device was built to investigate the discrete settling behaviour of the
activated sludge and to determine the settling rates of different particle classes. This
measurement device consisted of a settling column of approximately 9 liters with a central
tube diameter of 150 mm and sampling points at different heights along the column. The
settling column was built from plexiglass (PMMA). The wall thickness and diameter of each
sampling point are 5 mm and 20 mm respectively. A total of sixteen sampling holes were
located at four different depths in the column. At each depth 4 holes were spread equally over

23
23
the diameter of the settling column. The dimensions and a schematic view of the settling
column are shown in Figure 3.3.
This device allows taking frequent samples (of approx. 5ml) at different heights in the
settling column by switching the sampling locations at one depth between the 4 sampling
holes along the diameter. Subsequent samples can be taken independently of hydraulic
disturbances that might have been caused by prior sampling.
Figure 3.3: The dimensions and schematic representation of the settling column
3.2.4. Particle sizing using the Eye-Tech
The measurement of floc size distribution gives useful information to evaluate the particle
occurrence frequency in different particle size ranges. Consequently, it may lead to a more
significant understanding of the activated sludge process during the wastewater treatment. In
this thesis, to evaluate the floc size distribution of the activated sludge samples, the
Ankersmid Eye-Tech (The Netherlands) was used as an analyser. The Eye-Tech applies high
resolution floc size and shape analysis and also calculates the sludge concentrations. A
general overview of the set-up is shown in Figure 3.4.
By using the Eye-Tech, it becomes possible to quantify and characterize the structural
properties of the activated sludge flocs as well as to analyze the flocculation dynamics under
the effect of various process parameters.

24
24
Figure 3.4: A general overview of the Eye-Tech
The Eye-Tech combines two different methods of analysis of PSD characterization in a single
instrument: (1) laser channel and (2) video channel (see Figure 3.5).
Figure 3.5: Dual measurement channels of the Eye-Tech
A laser channel provides size measurements based on a unique time domain measurement
called Laser Obscuration Time (LOT). The measurement set-up consists of a He-Ne laser
beam. A single particle in the sample is scanned by a rotating wedge prism (at constant
rotating speed: 200 Hz). As the tangential velocity is identified, the size of each particle can
be determined from the duration of the beam obscuration signal. The LOT is directly related
to the diameter of particle by the following equation (3.2):
(3.2)

25
25
where D is particle diameter; vT is tangential velocity of the laser beam; Δt is time of
obscuration (time of transition).
A particle size measurement based on LOT is shown in Figure 3.6. Moreover, the device
measures in 600 discrete size intervals, resulting in a high resolution PSD. The laser channel
measurement range is 0.1 - 2000 µm.
Figure 3.6: Particle size measurement based on LOT
The video channel of the Eye-Tech is another analysis channel which allows for PSD and
shape characterisation by displaying images of moving particles and analysing them with
image analysis software. For precise characterization of non-spherical particles such as
sludge flocs, two-dimensional shape information is necessary. In order to provide the true
characterisation of activated sludge particles, a CCD video camera microscope of the device
provides images for processing. The images are passed through a frame card for analysis and
are showed on a monitor and then stored for later processing. The video channel allows the
user to set up a precise Dynamic Image Analysis, which results in an accurate description of
particles in all different shapes (non-spherical particles). The device also provides a diverse
selection of lenses with different magnifications. The video channel measurement range is 1 -
1200 µm.
In this thesis, the sludge samples to be analysed were placed into cuvettes with dimensions of
12.5×12.5×45 mm and a volume of 3 mL. The cuvette was then immediately put into the
magnetic stirrer cell of the Eye-Tech in which the magnetically driven mixer maintains the
particles in suspension during measurement.

26
26
Because of the different shapes of the activated sludge particles, the visibility of particles
throughout the measurement, the grouping of particles based on size or shape, and no
assumption of particle sphericity the video channel was chosen to analyse the particles in the
samples.
The Eye-Tech gives a report of the equivalent area diameter and average feret diameter data
based on the number, surface and volume mean diameter of activated sludge particles. The
equivalent area diameter only calculates one-dimensional property of a particle and states it
to a sphere particle in order to conclude one unique number for the diameter. Thus, for a
given non-spherical particles such as activated sludge, more than one equivalent area
diameter should be defined. Average feret diameter determines three various equivalent
diameters for a non-spherical particle (see Figure 3.7).
Figure 3.7: Definition of feret diameter
The mean is the most used average diameter and demonstrates the center of gravity of the
distribution. Different means can be defined for a given size distribution (Allen, 1997).
The equations to define mean diameters are expressed below.
Volume-based mean diameter:
[ ]
∑ ( )
∑ ( )
(3.2)
Volume-based mean diameter equals the diameter of the sphere which has similar volume as
a given particle.

27
27
Surface-based mean diameter:
[ ]
∑ ( )
∑ ( )
(3.3)
Surface-based mean diameter equals the diameter of the sphere which has the similar surface
area as a given particle.
Number-based mean diameter:
[ ]
∑ ( )
∑ ( )
(3.4)
Number-based mean diameter equals the diameter of the sphere which has the similar number
as a given particle. It means, a particle can be defined using a single number (the diameter)
since each dimension is identical. This description is useful for a spherical particle.

28
CHAPTER 4
28
4. RESULTS AND DISCUSSION
4.1. DSS/FSS test
One problem in the biological wastewater treatment process is poor flocculation properties
causing the formation of small and light flocs (Jin et. al, 2003). Formation of large, dense and
strong flocs is required for good settling. Flocculation of activated sludge is therefore an
important process for the effective functioning of the treatment process (Biggs and Lant,
2000) and specifically it is important to capture small particles which show poor individual
settling properties. The PSD of activated sludge in a SST is dynamic and affected by
turbulent shear. Particles may flocculate under low shear levels and break up when exposed
to high shear levels.
The objective of this section is to investigate the effect of different shear forces on the settling
behaviour by analyzing the changes in floc size distribution during a DSS/FSS test using a
particle size analyser (Eye-tech). It should be noticed that this test was slightly modified with
respect to a standard DSS/FSS test. Instead of only measuring concentrations in the
supernatant, in this work particle size analysis were performed to gain extra information on
the size distribution of particles in the supernatant of the settling jars after applying different
rotational velocities.
A DSS/FSS test combined with particle size analysis (section 3.2.2) provides a useful means
of following the formation and break-up of activated sludge flocs under different mixing and,
hence, shear conditions.
This modified DSS/FSS test was performed on activated sludge collected from the aeration
tanks of the WWTPs of Destelbergen (Belgium), Roeselare (Belgium) and Eindhoven (The
Netherlands). For each WWTP, samples were collected at two different days. Each
measurement was done in two parallel settling jars (No.1 and No.2). The experiments were
performed no later than 24 hours after sampling.
Different rotational speeds were applied and the consequent (de)flocculation of activated
sludge was investigated by means of PSD analysis. The first FSS experiment (FSS test 1)
investigated the effect of a low mixing intensity (37-42 rpm). The second experiment (FSS
test 2) investigated the standard rotational speed (47-52 rpm); the third experiment (FSS test

29
CHAPTER 4. RESULTS AND DISCUSSION
29
3) investigated the rotational speed of 68-73 rpm and, finally, the fourth experiment (FSS test
4) investigated a very high mixing intensity (96-100 rpm).
For each test, the PSD in the supernatant of the settling jars was measured with the Eye-Tech
video channel. The samples were taken after 30 minutes of settling and not diluted for
measurement. As mentioned before, because of the different shapes of activated sludge (non-
spherical particles) the average feret diameter was used to plot the volume distribution
histogram and cumulative distribution against size ranges (µm).
In order to monitor the absolute changes in PSD, the absolute number of particles in each size
class was calculated from the raw Eye-Tech counting data to plot the number of particles
(logarithmic scale) against size ranges (µm).
Based on equation (4.1) and (4.2), it can be explained that the volume distribution histogram
emphasizes large particles (by raising r to the 3rd
power) whereas small particles are not
noticed to the same degree as larger particles. Moreover, the absolute value is required
instead of percentage in order to determine absolute changes of PSD instead of only relative
changes. To investigate the effect of shear (force) on the (de)flocculation state of sludge
particles during the clarification process, it is essential to consider the changes of size of the
small particles. Thus, the graphs of the number of particles (logarithmic scale) against size
range (µm) are shown to interpret the influence of different rotational speeds on activated
sludge samples.
(4.1)
(4.2)
In which V is volume-based diameter; N is number of particles; r is the diameter of particles.
In order to depict the results clearly, the graphs of the number of particles against size range
(µm) only show particles in the range between 2 and 100 µm and the graphs of the volume
distribution (%) only illustrate the results between 2 and 250 µm. This was chosen because
the most useful information required for interpretation is present in these size ranges.
Particles larger than 100 µm are only present in very low numbers.

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30
4.1.1. Destelbergen WWTP results
Based on the above, the volume distribution histogram and absolute number histogram are
plotted for the DSS and FSS tests performed with sludge from the WWTP of Destelbergen.
The volume distribution (%) and cumulative distribution (%) of the DSS test and FSS test 1
(37-42 rpm) are shown in Figure 4.1. This figure indicates that for a rotational speed of 37-42
rpm, the size distribution shifts to the smaller size ranges (between 2 and 70 µm) and the
spread of the distribution narrows.
Figure 4.1: The effect of rotation speed of 37-42 rpm on volume distribution (%) in the supernatant after
30 min. of settling (settling jar No.1)
However, since the volume histogram (%) shows only relative changes, the absolute number
of particles for each size range was calculated. These results are illustrated in Figure 4.2 and
show that by mixing the sludge sample for half an hour at a rotational speed of 37-42 rpm, an
absolute decrease of smaller and larger particles can be observed in the supernatant after
settling.
Based on the results of the absolute number values, it was found that mixing resulted in better
settling of the sludge shown by a significant reduction of total number of particles in the
supernatant (29301 particles for the DSS test versus 11288 particles for FSS test 1).
By comparing the distributions of the absolute particle numbers, it can be seen that even
though the number of particles in each class is reduced by the mixing, this reduction is
relatively larger for the bigger particles than for the smaller particles. This explains the shift
which was also observed in the volume distribution (%).

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31
Figure 4.2: The effect of rotation speed of 37-42 rpm on total number of particles in the supernatant after
The experiment was repeated in parallel in a second settling jar. The results confirm the
observations that were made for the previous experiment (see Figure 4.3 and 4.4).
Figure 4.3: The effect of rotation speed of 37-42 rpm on volume distribution (%) in the supernatant after

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32
The observed changes in the PSD for the rotational speed of 37-42 rpm can be explained as
follows: the relatively low mixing condition increases the aggregation of activated sludge,
causing the formation of larger flocs that settle well resulting in a decrease in number of
particles in the supernatant.
The results of these first experiments confirm that to investigate the effect of different mixing
conditions on the PSD, the absolute number distribution provides more relevant information
than the volume distribution (%). Hence, for the interpretation of the results in the remainder
of this section, only the graphs of the number of particles against size range (µm) are shown.
A second FSS test was performed at a higher rotational speed (47-52 rpm). Figure 4.5
illustrates the distribution of number of particles obtained from the FSS tests at two different
rotational velocities. It was found that applying a higher rotational speed increases the
reduction of total number of particles in the supernatant sample. It caused the total number of
particles to change from 11288 for the test at 37-42 rpm to 7882 for the test at 47-52 rpm.
This reduction in number of particles is highest for the small sizes ranges (between 2 and 58
µm).
Thus, stirring the sample has an influence on very small size ranges of particles causing
collisions between small particles and the formation of large flocs which will improve the
overall settleability.

33
33
In a third FSS test, the rotational speed was further increased to 68-73 rpm. Again, a decrease
in total number of particles in the supernatant was found (see Figure 4.6). However, the
changes in total number of particles are much less pronounced (from 7882 to 7102). Smaller
size classes still show a decrease in absolute number when a stirring speed of 68-73 rpm is
applied. However, the larger size classes show approximately a steady state condition. This
can be explained as follows: when the shear (force) increases, the floc-breakage increases as
well as floc formation until a steady-state floc size is obtained.
Each of the experiments above was conducted in parallel in a second settling jar at the same
time. Also here, it was found that mixing the sample prior to settling resulted in a decrease in
total number of particles. The changes in total number of particles are summarized in Table

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34
4.1. The changes in PSD showed similar trends as for the first experiment and are not
indicated here.
Table 4.1: The absolute total number of particles in the supernatant of each test of experiment 1 of
Destelbergen WWTP
Settling Jar No.1 Settling Jar No.2
DSS test 29301 24235
FSS test 1 (37-42 rpm) 11288 9238
FSS test 2 (47-52 rpm) 7882 7417
FSS test 3 (68-73 rpm) 7102 7319
To investigate whether the observed effects are consistent in time, the DSS/FSS tests were
repeated with a sludge sample taken at a different day (approximately 1 month later). During
this second sampling day the temperature and flow rates were in the same range as on the
first sampling day. Similar effects could be observed when different stirring conditions were
applied. The changes in total number of particles are displayed in Table 4.2.
Table 4.2: The absolute total number of particles in the supernatant of each test of experiment 1 of
Destelbergen WWTP
DSS test 23673 27875
FSS test 1 (37-42 rpm) 8505 13608
FSS test 2 (47-52 rpm) 8105 12716
FSS test 3 (68-73 rpm) 7205 11622
The effect of mixing at different speeds prior to flocculation was investigated on different
samples collected on two different days. From these experiments, it has been illustrated
repeatedly that activated sludge flocculation is considerably affected by shear with an
increase in shear (up to 68-73 rpm) leading to improved flocculation and a decrease in total
number of particles in the supernatant (specifically the number of particles in the small size
ranges).
Previous results showed that for a mixing intensity of 68-73 rpm the flocculation state
reaches approximately a steady state between aggregation and break-up.

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To determine the influence of higher shear (forces) on the deflocculation due to break-up, the
experiment was also conducted at a rotational speed of 96-100 rpm and compared to the
flocculation state at 68-73 rpm. For this test, a third sample was collected. The total number
of particles in the supernatant after the DSS test equaled 9652. It should be noticed that the
total number of particles after this DSS test is a lot lower compare to the tests with previous
samples. This indicates that the collected sludge sample from the aeration tank was already
much more flocculated compared to the samples used in the previous experiments.
After performing a FSS test with a rotational speed of 68-73 rpm, the total number of
particles equaled to 9172, demonstrating a reduction of total number of particles in the
supernatant liquid due to the aggregation of small particles into flocs. Then the FSS test was
repeated with the highest speed (96-100 rpm) and the total number of particles increased to
12301. It can be seen that by applying this high rotational speed, the flocculation state
decreased significantly. The changes in PSD are shown in Figure 4.7. This Figure shows an
increase in particles of almost all size classes due to the break-up of sludge flocs resulting in
worse settling properties.
Figure 4.7: The effect of rotation speed of 96-100 rpm on total number of particles in the supernatant
after 30 min. of settling (settling jar No.1)
Moreover, similar effects have been observed when a rotational speed of 96-100 rpm was
applied to a parallel settling jar (No.2). Also here, floc break-up was observed by a large
increase in particles.
From this section it can be concluded that after 30 minutes of settling in a DSS tests, the
absolute number of particles in the supernatant is still high (see Tables 4.1 and 4.2). The
activated sludge samples from the aeration tank did not settle very well. By applying stirring

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conditions, the number of particles decreased significantly. This illustrates that the sludge
from WWTP of Destelbergen shows a good tendency to flocculate. Gentle mixing of the
sludge before settling can significantly improve the quality of the supernatant. The best
results were obtained with a mixing intensity of 68-73 rpm. Applying a higher mixing speed
will cause floc break-up to dominate over aggregation leading to a decrease in supernatant
quality. As mentioned before, at the third time of sampling, the DSS test was performed with
better flocculated sludge (total number of particles: 9652). This sludge sample shows not
much tendency to flocculate further and thus does not benefit as much from mixing before
settling.
4.1.2. Eindhoven WWTP results
DSS/FSS tests were performed on activated sludge samples collected from the Eindhoven
WWTP to determine the effect of shear (force) on the (de)flocculation state. The experiments
were performed approximately 24 hour after sampling from the aeration tank. The DSS/FSS
tests were repeated with samples from 2 different sampling days (approximately 2 months
apart). The procedure of the tests was similar to the Destelbergen experiment (section 4.1.1).
Figure 4.8 demonstrates the results of the DSS test and FSS test 1 (37-42 rpm) for the first
sample. This Figure shows a decrease in the number of particles in the supernatant in the
entire size range after settling. The absolute total number of particles changed from 6700 for
the DSS test to 3253 for the FSS test 1. The PSD of both the DSS test and the FSS test 1
shows a large decrease in small particles and large particles. This reduction in the number of
particles is larger for the smaller particles than for the larger particles.

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In the next FSS test at a rotational speed of 48-53 rpm (FSS test 2), a further decrease in total
number of particles (from 3253 to 2610) was observed. However, this change is not as
pronounced as for the FSS test at a rotational speed of 37-42 rpm. The distribution of
particles shows a decrease of small and big particles. These changes of number of particles
are shown in Figure 4.9.
Also, for the highest rotational speed of 68-73 rpm (FSS test 3), the total number of particles
decreased slightly in the supernatant liquid above (from 2610 to 2380) (see Figure 4.10).
However, when looking at the distribution, it can be seen that the PSD is approximately at a
steady state.
This experiment was repeated in parallel in a second settling jar at the same time. The results
show similar trends as for the first settling jar. Table 4.3 indicates the changes of total number

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of particles for both settling jars at different rotational speeds. Based on the results, it can be
explained that the mixing condition under different rotation velocities (from 37-42 rpm to 68-
73 rpm) increases the flocculation state of activated sludge, resulting in a decrease in number
of particles in the supernatant.
Table 4.3: The absolute total number of particles in the supernatant of each test of Eindhoven WWTP
DSS test 6700 5842
FSS test 1 (37-42 rpm) 3253 4976
FSS test 2 (48-53 rpm) 2610 4306
FSS test 3 (68-73 rpm) 2380 3127
When we compare these results to the results of the WWTP of Destelbergen, it can be seen
that the total number of particles after the DSS tests is much lower for the Eindhoven sludge,
indicating a much better flocculated sludge. It shows that both activated sludge samples of
Eindhoven and Destelbergen showed good flocculating tendency. The results indicate that
these sludge samples still need to flocculate because a further reduction in total number of
particles can be observed after applying shear (force). However, since the Eindhoven sludge
sample was already better flocculated the changes of PSD after mixing are not as large as for
the Destelbergen results (see Table 4.3).
Also for this WWTP, to investigate whether the observed effects are constant in time,
DSS/FSS tests were conducted again with a sludge sample taken at a different day. Similar
stirring conditions were applied. Again, the same effects could be observed when a rotational
speed of 37-42 rpm was applied to both settling jars (i.e. a drop in total number of particles
from 5184 for the DSS test to 3462 for FSS test 1 in settling jar No.1): the relatively low
mixing condition improves the overall settleability.
But, the results did not show similar effects on the sample at the higher rotational speeds.
After applying a higher rotational speed of 48-53 rpm, both settling jars demonstrated
different results of the influence of stirring on the sample. Furthermore, the total number of
particles in the supernatant increased at a rotational speed of 68-73 rpm (settling jar No.1 and
No.2). Specifically, this increase in number of particles is relatively higher in the very small
size ranges (the total number of particles is 3673 for the FSS test 3). Figure 4.11 indicates the
changes in PSD of number of particles derived from the FSS tests at two different rotational

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speeds. Compared to the previous experiment, the sludge shows increased break-up at lower
mixing velocities. Hence, this second sludge sample shows much more sensitivity to shear
(force) than the sample that was taken two months earlier.
The flocculation process of the activated sludge can be influenced by different physico-
chemical factors (Govoreanu, 2004). For instance, environmental conditions (i.e.
temperature) and/or process parameters will affect the floc formation and break-up (Torfs,
2012). Because of this reason, the data related to the Eindhoven WWTP at the two different
sampling days was collected to understand the cause of these changes in PSD.
Based on the measurements of the WWTP, the total flow of the WWTP is 90,000-110,000
m3d-1 under normal dry weather conditions. In both sampling days there has been an amount
of rain weather flow which caused dilution of wastewater. The first sampling day, the total
flow on the WWTP was approximately 201,600 m3
d-1
and the second sampling day it was
172,500 m3
d-1
. The other parameters such as dry matter were constant in both of sampling
days.
Temperature measurements in the aeration tank show that the weather during the month of
the first sampling time was much colder compared to the second time: 11.71°C on day 1 and
18.20°C on day 2 respectively. The results above show that the sludge collected during a cold
period was less sensitive to deflocculation by shear (force) than sludge collected during a
warmer period.

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Studies showed that temperature has a complex influence on the flocculation state of
activated sludge. Govoreanu (2004) investigated the behaviour of the activated sludge at
different temperature. Figure 4.12 illustrates the observed trend in floc size at temperatures of
5°C, 15°C and 25°C. It can be seen from Figure 4.12 that an increase in floc size was
observed when the temperature was 5°C and a decrease in particle size was detected when the
temperature was increased to 25°C. This confirms the observations that were made in this
work.
Figure 4.12: The effect of temperature on the activated sludge floc size (Govoreanu, 2004)
Two hypotheses may explain this behaviour of the activated sludge. Changes in temperature
may influence transport or collision rates of the flocs due to changes in viscosity. When
temperature increases, viscosity decreases, improving the mixing behaviour and developing
Brownian motion of small particles (<1 µm). However, this is mainly important for very
small particles and not noticed to be significant in flocculation of activated sludge compared
with the other mechanisms (Torfs, 2012). Next to the viscosity effect, the physical and
chemical properties of the activated sludge are influenced by temperature (Govoreanu 2004).
According to Sutherland (1988) and Wilen (1999), temperature can influence the physical
properties of the EPS and the function of EPS.
Based on the above, it can be seen that temperature has a significant effect on the
(de)flocculation process of the activated sludge. This explains why the activated sludge
sample at 11.71°C temperature shows better settlleability than the sample collected at
18.20°C.

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A final experiment was conducted at a rotational speed of 96-100 rpm and compared to the
flocculation process at 68-73 rpm. After performing a FSS test with a rotational speed of 96-
100 rpm, the total number of particles in the supernatant increased drastically. The changes in
PSD are indicated in Figure 4.13. The distribution of particles shows a large increase of
particles in all size ranges due to floc break-up.
4.1.3. Roeselare WWTP results
The same DSS/FSS tests were applied on sludge samples collected from the WWTP of
Roeselare (Belgium). Again, the results of a first experiment show that by mixing the sludge
sample for half an hour at a rotational speed of 37-42 rpm, a decrease of small particles can
be observed in the supernatant of both settling jars. It was found that mixing resulted in better
settling of the sludge shown by a reduction of total number of particles in the supernatant.
The same experiment was repeated with a different sample collected at a different day
(second experiment). The results confirm the observations that were made for the previous
experiment. The observed reductions of total number of particles in the supernatant are due to
the aggregation of small particles and the formation of large flocs.
The changes in total number of particles after DSS and FSS tests with a rotational speed of
37-42 rpm are summarized in Table 4.4.

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Table 4.4: The absolute total number of particles in the supernatant of each test of Roeselare WWTP
First experiment Second experiment
Settling jar
No.1
Settling jar
No.2
Settling jar
No.1
Settling jar
No.2
DSS test 14939 7766 31518 30834
FSS test 1(37-42 rpm) 2944 3883 25376 24686
FSS test 2(48-53 rpm) 4550 4148 27071 25999
The results for the FSS test at 37-42 rpm for the first experiment show similar trends as the
results from the WWTP of Destelbergen. Therefore, they are not discussed in detail here. The
results of the second experiment deviate somewhat from previous observation and are shown
in more detail in Figure 4.14. This Figure shows that applying shear (force) has only a small
effect on the amount of very small particles. However, mixing at a low rotational speed of 37-
42 rpm has a profound effect on the larger particle classes.
A second FSS test was performed at a higher rotational speed (48-53 rpm). Compared to the
first FSS test, increasing the shear (force) caused an increase in total number of particles in
the supernatant (see Table 4.4). The changes in PSD are displayed in Figure 4.15. This Figure
shows that increasing the rotational speed to 48-53 rpm has a significant effect on the size
distribution of small particles and the total number of small particles increased in the
supernatant. Larger size classes still show a small decrease in absolute number when a
stirring speed of 48-53 rpm is accomplished.

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43
Moreover, similar effects have been observed for the first experiment (Table 4.4). Also here,
it can be seen that as the rotational speed increased to 48-53 rpm, the flocculation state
decreased because of floc-breakage.
These results show a large difference in initial flocculation state between the two different
samples collected from the WWTP of Roeselare. The second sample has a very bad initial
flocculation state and a poor tendency to flocculate. Moreover, both samples are very
sensitive to shear when the mixing intensity is increased to 48-53 rpm (shown by an increase
in the number of very small particles in the supernatant).
To investigate this further, the DSS/FSS tests were repeated with a sludge sample taken at a
different day (third experiment). For this sample, the total number of particles in the
supernatant after DSS test equaled to 4981. After performing FSS tests with rotational speeds
of 48-53 rpm and 68-73 rpm, the total number of particles equaled to 4044 and 3434
respectively. Also here, it was found that stirring the sample resulted in a decrease in number
of particles in the supernatant because of the aggregation of small particles into the large
flocs.
Then the FSS test was conducted with the highest velocity (96-100 rpm) and the total number
of particles increased to 5180. Again, the flocculation process decreased quickly due to
break-up of activated sludge flocs. The changes in PSD for this third experiment thus show
very similar trends as for the Destelbergen results (section 4.1.1) and are not shown here.
A lot of variation in both initial flocculation state and flocculation tendency could be
observed among the different samples from the WWTP of Roeselare.

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In the first and second experiments, the absolute number of particles was high after DSS tests
(see Table 4.4) and also the sludge flocs were more shear sensitive when the rotational speeds
increased. This may be because the activated sludge flocculated poorly and/or cohesion
between particles was not strong enough (low floc strength) and with a little increase in shear
(force), particles were separated easily (floc break-up).
In the third experiment, on the other hand, the total number of particles was very low
compared to the previous experiments. This means that the activated sludge sample from the
aeration tank was flocculated very well before the settling process. Also, the sludge sample
was not very sensitive to shear (force) with increasing the rotational velocities and the
aggregation of particles occurred instead of floc break-up.
From the results in this section, it can be concluded that the sludge of the WWTP of
Destelbergen is not very well flocculated in the aeration tank and does not show good settling
properties (the total number of particles is relatively high after half an hour settling during a
DSS test). However, the flocculation state and settleability can be improved a lot by applying
mixing. The optimum result is for the rotational speed of 68-73 rpm. These samples are thus
not sensitive to shear (force) and still need flocculation before settling.
The samples of the WWTP of Eindhoven are much better flocculated compared to the
WWTP of Destelbergen. Also for these sludge samples, the settleability can be improved by
applying mixing to flocculate the sludge further before settling. The changes in PSD are not
as large as for samples of Destelbergen. Moreover, temperature has a significant influence on
the floc formation and break-up. Results showed that lower temperature increases the
flocculation state of activated sludge and resulted in stronger flocs. This means that when
operating a SST in the same way in winter and summer can lead to different (de)flocculation
behaviour and hence different ESS.
The samples of the WWTP of Roeselare showed large variations in flocculation state,
flocculation tendency and sensitivity compared to the other two WWTPs. The flocculation
state for all samples could be improved by applying a rotational speed of 37-42 rpm prior to
settling. For this WWTP, no information on environmental conditions for different sampling
days was available. Thus, the reason of these variations in flocculation state after applying the
different rotational velocities cannot be explained.

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4.2. Settling column test
4.2.1. Sampling techniques
Investigating the discrete settling behaviour of activated sludge requires the selection of an
appropriate sampling technique. In order to select the best way of sampling, different
techniques (differing in diameter of the sampling tube (ST1 vs ST2) and distance from the
inner wall (ST3)) were used to sample from the top holes of the settling column (see Figure
4.16).
Figure 4.16: Schematic representation of the different investigated sampling techniques in the settling
column
These different techniques were compared to a reference sample collected with a manual
pipette from the top of the settling column. Finally, one sampling technique was chosen with
care in order to make sure that the measurements are not biased by wall effects or sample
disturbances.
A sludge sample from the aeration tank of the WWTP of Destelbergen was diluted
approximately 4-5 times until the concentration was low enough for discrete settling to occur.
This diluted sludge sample was then poured into the settling column.
To investigate whether wall effects or disturbances due to the sampling channel have an
influence on the results, samples were taken with the first sampling technique and with the
manual pipette simultaneously and the PSD results of the first sampling technique were

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46
compared with the PSD results of the sample collected with a manual pipette. The average
feret diameter data were used to plot the volume distribution histogram and absolute total
number histogram (logarithmic scale) against size ranges (µm). The same procedure was then
applied to the other sampling techniques (ST2 and ST3).
During sampling by the first or the second technique, it should be considered that some
particles will settle inside of the sampling tube after a while. These particles should be
removed from inside of the tube before representative sampling can be started. Moreover, the
time of sampling is not a critical parameter in this step since the goal is the selection of the
best way of sampling hereby decreasing the effect of different factors such as sampling
disturbance or wall effects.
The resulting PSD for the different sampling techniques are shown in Figures 4.17-4.22.
Figure 4.17: The volume distribution (%) of two different techniques of sampling in the settling column
along with cumulative distributions
Figure 4.18: The total number of particles of two different techniques of sampling in the settling column

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By comparing each sampling technique with a sample that was taken with a manual pipette
(reference) from the center of the settling column, it can be concluded that sampling with the
syringe (ST3) shows large differences to the reference sample. This might be due to sampling
disturbance during transport through the long sampling channel. Hence, this technique is not
considered reliable to measure discrete settling of activated sludge particles.
From the results of the other methods it can be concluded that the second sampling technique
yields very reliable results. The result shows approximately the same distribution as for the
sample that was taken from the center of the settling column. The distribution of the particles
shows good correspondence in all size ranges (see Figure 4.19 and 4.20). The total number of
particles for ST2 and the manual pipette (reference sample) equaled to 23831 and 23547
respectively.
All three sampling techniques are able to accurately measure particles with a diameter less
than 100 µm. However, the second sampling technique shows the best representation of
complete particle size ranges. Thus, from the results in this section, it can be decided that to
determine the discrete settling of particles, the second sampling technique is an accurate
sampling technique creating no significant sample disturbance or wall effects. This test was
repeated three times and similar results were observed.
4.2.2. Settling column results
To investigate the discrete settling behaviour of sludge during settling in the settling column,
the selected sampling technique (ST2) was built at each hole of the settling column at three
different depths (points 1, 2 and 3). Point 1 is located at the top of the settling column. Point 2
and point 3 were located at lower depths in the column. The lowest sampling location (point

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4) was not considered for measurement because this point is always located in the sludge
blanket and therefore does not provide information about discrete settling (see Figure 3.3).
The constructed settling column allows collecting detailed data of the settling behaviour of
particles with different size classes in time. By extending the experiment for long enough
settling times, the settling behaviour of both large flocs and small particles can be quantified.
Moreover, collecting samples at different depths throughout the settling column allows
investigating changes in PSD not only in time but also in space. This kind of measurement
will significantly help to understand the settling and flocculation behaviour of sludge
particles at low concentration which will lead to improved predictions of effluent
concentrations.
For this purpose, activated sludge collected from the WWTP of Roeselare was diluted 5
times. Samples were collected from 3 sampling heights of the settling column at the same
time to follow the changes in PSD at different depths. The concentration of the sludge in the
settling column at the start of the experiment was measured by an MLSS test.
For the same reasons as mentioned in section 4.1.1, only the absolute number distributions
are shown since these provide the most valuable information.
4.2.2.1. Settling column test results at point 1
The concentration of activated sludge equaled to approximately 2.93 g L-1
and the
concentration of sludge in the settling column at the start of test equaled to approximately
0.590 g L-1
. According to Mancell-Egala et al. (2012), this concentration is approximately
near the settling transition concentration (500-600 mg L-1
) where the settling type is changing
from hindered settling to discrete settling.
The changes in the distribution of the absolute particle numbers during the first minutes of
settling at the top of the settling column (point 1) are shown in Figure 4.23. A more detailed
representation can be found in Figure 4.24. It can be seen that the number of particles
decreases in all size classes in the top region during the first 2 minutes of settling. No
significant changes can be observed between 2 and 3 minutes of settling.

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Figure 4.23: Total number of particles at the highest sampling location (point 1) in the settling column
after specific times of settling
Figure 4.24: Detailed changes in total number of particles at the highest sampling location (point 1) in the
settling column after specific times of settling
Figure 4.24 indicates that only a few particles larger than 300 µm remain in the top region of
the column after 3 minutes of settling. This settling behaviour of sludge can be explained as
follows: during the first minutes of settling, the sludge concentration is higher than the
limiting concentration and particles are still close enough together so they do not settle
independently of one another. Thus, hindered settling occurs during these first minutes of
settling. Due to the high concentration of sludge, each particle is hindered by other particles

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and settling of each particle is affected by other sludge particles. All particles of different size
ranges thus settle with the same settling velocity.
The changes in size distribution after 3-10 minutes of settling at the highest sampling location
are illustrated in Figure 4.25. Based on the result, particles with a diameter larger than 250
µm start to decrease between 5 and 10 minutes of settling and consequently all particles
larger than approximately 250 µm have disappeared from the top of the column after 10
minutes of settling (see Figure 4.26). No significant changes in number of particles can be
observed in the smaller size classes. Small changes in the number of particles in these classes
might be due to hydraulic disturbances.
Figure 4.25: Total number of particles at the highest sampling location (point 1) in the settling column
after specific times of settling

Faezeh MahdaviMazdeh, Master thesis 2013-2014,

Faezeh MahdaviMazdeh, Master thesis 2013-2014,

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