investigating flocculation and discrete settling...

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This in an unpublished M.Sc.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

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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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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.

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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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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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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.

http://www.google.be/search?hl=en&sa=X&rlz=1R2WQIA_enBE524&biw=1366&bih=513&tbm=bks&q=inauthor:%22P.+Aarne+Vesilind%22&ei=nnMvUaauJueM0wXtv4GoDw&ved=0CCwQ9AgwAA

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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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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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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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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

http://en.wikipedia.org/wiki/Earth%27s_gravity

http://en.wikipedia.org/wiki/Dynamic_viscosity

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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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14

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.

http://www.sciencedirect.com/science/article/pii/S0043135499004315

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



17


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


18


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

21


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.

http://en.wikipedia.org/wiki/Surface

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


32


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

34


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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39

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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41

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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44

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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47






48


48


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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49

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.



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52



Figure 4.27 illustrates the changes in number of particles in all size classes after 10-30

minutes of settling. This figure shows a decrease in number of particles after 30 minutes of

settling. As can be seen in Figure 4.28, all particles larger than 200 µm have already settled

from the top of the column after 30 minutes of settling. Moreover, a decrease in small

particles (100-200 µm) and very small particles with a diameter less than 100 µm can be

observed in the supernatant. This decrease in the smaller size classes can be due to

differential settling or drag forces created by the settling of larger particles. Differential

settling is caused by the fact that larger particles can pass toward smaller particles during

settling and some small particles will be able to collide with and attach to the larger particles

causing them to settle as a whole.

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53





The changes in PSD after 30 minutes-2 hours of settling at the top of the settling column are

shown in Figure 4.29. It can be seen that almost all the particles larger than approximately

100 µm disappear after 2 hours due to discrete settling. All of these particles are removed

from the top of the settling column between 1 and 2 hours.

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54

As can be seen in Figure 4.30, the number of very small particles (less than 100 µm) does not

significantly change during 2 hours of settling. This class shows no tendency to settle and

will therefore remain in the supernatant and influence the performance of an SST in WWTP.

Thus, for these very small particles, flocculation before discharging as an effluent will have a

significant impact.





To see the effect of the settling column on settling of the activated sludge particles, the PSD

of remaining particles in the top region of the settling column (point 1) after 2 hours of

settling is compared with the size distribution of effluent which is discharged from the SST of

the WWTP of Roeselare. The average hydraulic residence time (HRT) in the SST during

sampling was 1.5 hour. This is shorter than the total settling time in the column. The total

number of particles in the effluent and the top region of settling column after 2 hours of

settling equaled to 4567 and 4435 respectively. The different PSDs are shown in Figure 4.31.

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As can be seen, the size distribution of very small particles (between 12 and 60 µm) for both

samples show very good correspondence. Some particles larger than 100 µm can be observed

in the effluent but are not present in the settling column after 2 hours of settling. This can be

due to the longer settling time in column (2 hours vs. HRT of 1.5 hour in the SST) or

hydraulic effects.

Figure 4.31: Number of particles in the effluent and the top region of settling column (point 1) after 2

hours of settling

To investigate the reproducibility of this test, the settling column test was repeated a second

time with a sludge sample taken on a different day. The concentration of sludge in the settling

column at the start of the experiment equaled approximately 0.390 g L-1

.

The change in the distribution of the number of particles between the start of the experiment

and 2 hours of settling are shown in Figure 4.32.

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56


after specific times of settling (second time)

It can be seen that the number of particles reduces in all size ranges in the top region of

settling column between the start of the experiment and 10 minutes of settling. The sludge

concentration at the start of the experiment is high enough for hindered settling to take place.

Results indicate however, that the measured concentration in the settling column is much

lower than the settling transition concentration as determined by Mancell-Egala et al. (2012).

However, this threshold concentration is also related to the flocculation state of the sludge

and can vary significantly.

A decrease in number of particles with a diameter larger than approximately 200 µm and a

small reduction in number of particles with a diameter less than 200 µm can be observed after

1 hour of settling in point 1. This change in distribution of particles can be explained by the

fact that the concentration of particles becomes low enough for discrete settling to occur.

Settling of particles is now no longer dependent on the sludge concentration and particles

start to settle individually. Moreover, the larger particles contact with the smaller particles

during settling and these small particles will be able to attach to the larger particles and are

removed from the top of settling column (differential settling).

Between 1 and 2 hours after the start of the experiment, all particles with a diameter larger

than 120 µm are removed from the top of the column. A small reduction can be seen in

number of particles with a diameter less than 100 µm. This reduction might be caused by

differential settling. These very small particles (less than 100 µm) are not further removed

from the top area of the column and remain in the supernatant.

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57

Finally, the same sludge sample was used as for the previous experiment to investigate the

discrete settling behaviour at lower initial sludge concentrations. The concentration of sludge

at the start of experiment was measured with an MLSS test and equaled to approximately

0.130 g L-1

. Figure 4.33 illustrates the changes in PSD during the first minutes of settling at

the highest sampling location in the settling column. Based on the result, no significant

changes in number of particles can be seen after 0-3 minutes of settling. This result shows

that hindered settling no longer occurs during the first minutes of the settling at the top area

of the column due to the very low concentration of sludge (0.130 g L-1

). This confirms that in

this case the transition threshold from hindered to discrete is lower than reported in the

literature (Mancell-Egala et al., 2012).



The distribution of the absolute particle numbers after 3-10 minutes of settling at point 1 of

the settling column is shown in Figure 4.34. This figure shows discrete settling starts after 5-

10 minutes of settling. Particles with a diameter larger than approximately 220 µm are

removed from the top region of settling column. Also a small reduction in number of very

small particles (less than 100 µm) and small particles (between 100 and 200 µm) can be

observed after 10 minutes of settling. This can be due to differential settling or the differences

in density of particles (some particles could have a higher density than the other particles)

(see Figure 4.35).

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58





The changes in PSD at the top region of the settling column after 10-40 minutes are

illustrated in Figures 4.36 and 4.37. No significant changes in number of particles can be

observed between 10 and 40 minutes of settling.

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59





From the results of the settling column tests at the two different sampling days, it can be

concluded that at higher initial sludge concentrations, hindered settling occurs during the first

minutes of settling. When the time of settling increases, discrete settling will start with

consecutive removal of different groups of particles according to their size. All particles

larger than 250 µm disappear from the top region after approx. 10 minutes of settling. After

30 minutes to 1 hour all of the particles larger than 200 µm are removed from the

supernatant. After 2 hours particles between 100 and 200 µm are removed and only very

small particles (less than 100) remain in the top of the column. These small particles show a

low tendency to settle. Hence, for these particles approximately less than 100 µm,

flocculation before discharging as an effluent is a vital process as well as avoiding their

production due to imposed shear.

In the third experiment with a lower concentration of sludge, only two types of settling were

observed. Particles are completely dispersed and no hindered settling is observed. Settling

will start immediately in the discrete regime. Moreover, larger particles pass to smaller

60


60

particles during settling and some of these particles can settle with other particles (differential

settling).

In this thesis, the results of point 2 are not considered. This sampling point is located in

higher hydraulic disturbance causing too many variations in the results. For this reason, the

interpretation of the results becomes more difficult. Hence, the results related to the lowest

sampling location (point 3) are further investigated to follow settling behaviour of particles

with respect to different heights in the column.

4.2.2.2. Settling column test results at point 3

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

. The changes in PSD during the first minutes of settling at the lowest sampling

location (point 3) in the settling column are shown in Figure 4.38. A more detailed

representation can be found in Figure 4.39. As can be seen, the number of particles decreases

in all size ranges during these first minutes of settling. From these results, it can be seen that

during the first minutes of settling a decrease in all particle classes is occurring due to

hindered settling.

Figure 4.38: Total number of particles at the lowest sampling location (point 3) in the settling column


61


61

Figure 4.39: Detailed changes in total number of particles at the lowest sampling location (point 3) in the


Figure 4.40 illustrates the changes in number of particles after 3-7 minutes of settling at point

3 in the settling column. This figure shows a further decrease in all size ranges between 3 and

5 minutes of settling indicating that hindered settling is still occurring. No further changes in

PSD can be observed between 5 and 7 minutes of settling. The time of hindered settling at

this point is longer than at the top of the settling column. This is due to the settling of

particles from the top part of the column which will pass toward this region (point 3) later.



62


62



Between 7 minutes and 1 hour of settling no significant changes in PSD can be observed.

Figure 4.42 shows the changes in size distribution of particles during the last hours of settling

at point 3. As can be seen, almost all particles larger than approx. 270 µm are removed from

point 3 after 1 hour 40 minutes of settling. Moreover, all particles larger than 220 µm are

removed after 2 hours. The number of small particles (between 100 and 200 µm) show a

small decrease due to the differential settling and/or discrete settling (see Figure 4.43). This

result shows that small particles less than 220 µm remain at this area and do not settle after 2

hours of settling. From the previous results it can be seen that particles with a diameter

between 100 and 220 µm settle from the top of the column after 2 hours of settling. So, the

experiment was not long enough to see their removal from point 3.

63


63





These results allow us to calculate the discrete settling velocity for different size classes by

means of Equation 4.3:

(4.3)

where X is the distance between point 1 and point 3; T is the time of settling; Vs is the

discrete settling velocity.

64


64

For example, the average time of settling (T) for particles larger than 270 µm is

approximately 1 hour, 20 minutes and distance between the highest sampling location and the

lowest sampling location (X) in the settling column equals to 0.37 m. Hence, the calculated

settling velocity of these particles is approximately 0.278 m hr-1

. Moreover, the average time

of settling for particles larger than 220 µm is approximately 1 hour, 50 minutes. So, the

calculated settling velocity is around 0.202 m hr-1

. According to equation (2.2), for a particle

diameter of approximately 250 µm and s of 1.02-1.05 g ml-1

respectively, Stokes’ law

predicts a velocity of 4.500 m hr-1

. The settling velocities according to Stokes’ law are thus

much higher than the velocities measured in the column. This could indicate a very low

density of the sludge flocs in the samples or the fact that discrete settling is reduced by

hydraulic effects.

From the results of this section, it can be concluded that this new sampling technique allows

collecting detailed data of the discrete settling behaviour of activated sludge with different

size classes in time. It was shown that the discrete settling behaviour can be described by

approximately 5 size ranges. Moreover, this constructed settling column allows investigating

changes in size distribution of particles at different depths of the column and finally this kind

of detailed information will significantly aid in determining the discrete settling velocity of

particles with different size ranges which will consequently lead to understand the complex

settling and flocculation behaviour of sludge particles in an SST.

65

CHAPTER 5

65

5. CONCLUSIONS AND PERSPECTIVES

5.1. Conclusions

The first aim of this thesis was to investigate the effect of different shear forces on floc

formation and break-up by analyzing the changes in PSD during the (de)flocculation process

using the Eye-Tech as a particle size analyser. PSD analysis provided useful information on

changes in number of particles in the supernatant of settling jars after applying different

mixing intensities prior to settling (DSS/FSS tests). The main conclusions which can be

drawn from these investigations are summarized below.

The activated sludge samples of the WWTP of Destelbergen were not well flocculated and

also not very sensitive to shear (force). The flocculation state could be improved by applying

mixing before settling. The best result was observed at a rotational speed of 68-73 rpm.

Also, for the activated sludge samples of the WWTP of Eindhoven, the flocculation state

could be improved by applying mixing prior to settling. However, the initial flocculation state

of these sludge samples was much better compared to the samples of the WWTP of

Destelbergen. The activated sludge sample showed increased flocculation up to a rotational

speed of 68-73 rpm. Moreover, temperature played a significant role in the floc formation and

settleabilty of this activated sludge. Results presented that lower temperatures increased the

floc formation of activated sludge. This means that when operating a SST in different

seasons, this can lead to different (de)flocculation behaviour and hence different ESS.

The flocculation state for samples of the WWTP of Roeselare could be improved only by

applying the lowest rotational velocity (37-42 rpm) prior to settling.

Applying the highest rotational speed of 96-100 rpm increased the floc break-up in all

samples of three WWTPs.

It can be concluded that mixing before settling is very important to improve the settling

process if it is applied gently (too much mixing will cause break-up). Good design of inlet

structure and flocculation well is therefore an important aspect in the overall performance of

a SST.

66

CHAPTER 5. CONCLUSIONS AND PERSPECTIVES

66

The second objective of this work was to build a novel settling column to investigate the

discrete settling behaviour of the activated sludge. This new measurement device allowed to

take samples at different heights in the settling column and to determine discrete settling rates

of different particle size. Moreover, the changes in PSD were followed in time which helps in

understanding the evolution of discrete settling behaviour throughout the top section of the

column.

At high initial activated sludge concentration, three types of settling could be observed during

settling. During the first minutes of settling, hindered settling was taking place. When the

time of settling increased, sequential settling of different groups of particles could be

observed. After 2 hours only very small particles (less than 100 µm) remained in the top of

the column (point 1). From this experiment it can be derived that the discrete settling

behaviour of activated sludge can be described by approx. 5 different size classes.

At very low initial sludge concentrations, no hindered settling was observed and the

experiment immediately started in the discrete settling regime.

Moreover, the changes in PSD were investigated at different heights along the column. At the

lowest sampling location, again hindered settling was observed during the first minutes of

settling were observed. The duration of hindered settling at this sampling location is longer

than at the top of the settling column (point 1). This is due to settling of particles from the top

part of the column which pass at this location at a later time instant. For longer settling times

(up to 2 hours) discrete settling and some differential settling could be observed. Finally, this

test allowed determining the discrete settling velocity for different size classes. This detailed

data will lead to understand settling velocities of different classes of activated sludge in an

SST and provide useful information in order to support further investigations.

5.2. Perspectives

A modified DSS/FSS test was developed to follow changes in PSD in the supernatant liquid

above after applying different mixing intensities (form low to high rotational velocities prior

to settling). However, in the current work no information on the effluent concentration was

considered. Further research is necessary to measure PSD in the effluent for each sampling

time and compare with the PSD results of the DSS/FSS tests. Moreover, it is important to

67

CHAPTER 5. CONCLUSIONS AND PERSPECTIVES

67

investigate the effect of different mixing times (e.g. 10, 20 and 30 minutes) on

(de)flocculation process in further work.

Furthermore, it would be interesting to consider the influence of other physical and chemical

parameters (such as activated sludge concentration and calcium concentration) on the

(de)flocculation state beside the effect of shear (force).

As mentioned in section 5.1, the settling column test aids in understanding the discrete

settling behaviour of particles of different size classes in a SST and consequently predicting

the effluent concentration. Experiments were performed during 2 hours of settling. This time

of settling demonstrates the settling of particles for different size classes very well at the top

of the settling column (point 1). Further work, including longer settling times (more than 2

hours) is necessary to observe discrete settling of all particle classes at the lower sampling

locations (point 2 and point 3).

The discrete settling velocity is not dependent on the sludge concentration but on individual

particle properties such as porosity, density and size. So, it could be interesting to measure

density and porosity of particles during settling and the role of these properties could be

further investigated in relation to a better prediction of the settling behaviour.

Finally, this measurement technique provides high quality data of the discrete settling process

that can be used as input to coupled flocculation-CFD model to obtain better prediction of

ESS concentration.

68

68

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