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ISBN 978-952-62-1178-7 (Paperback)ISBN 978-952-62-1179-4 (PDF)ISSN 0355-3213 (Print)ISSN 1796-2226 (Online)

U N I V E R S I TAT I S O U L U E N S I SACTAC

TECHNICA

U N I V E R S I TAT I S O U L U E N S I SACTAC

TECHNICA

OULU 2016

C 566

Elisa Koivuranta

OPTICAL MONITORING OF FLOCS AND FILAMENTS IN THE ACTIVATED SLUDGE PROCESS

UNIVERSITY OF OULU GRADUATE SCHOOL;UNIVERSITY OF OULU,FACULTY OF TECHNOLOGY

C 566

ACTA

Elisa Koivuranta

C566etukansi.kesken.fm Page 1 Wednesday, April 6, 2016 12:52 PM

A C T A U N I V E R S I T A T I S O U L U E N S I SC Te c h n i c a 5 6 6

ELISA KOIVURANTA

OPTICAL MONITORING OF FLOCS AND FILAMENTS IN THE ACTIVATED SLUDGE PROCESS

Academic dissertation to be presented, with the assent ofthe Doctoral Training Committee of Technology andNatural Sciences of the University of Oulu, for publicdefence in the Oulun Puhelin auditorium (L5), Linnanmaa,on 20 May 2016, at 12 noon

UNIVERSITY OF OULU, OULU 2016

Copyright © 2016Acta Univ. Oul. C 566, 2016

Supervised byProfessor Jouko NiinimäkiProfessor Mirja IllikainenDoctor Tuomas Stoor

Reviewed byProfessor Eugénio FerreiraProfessor Ilse Smets

ISBN 978-952-62-1178-7 (Paperback)ISBN 978-952-62-1179-4 (PDF)

ISSN 0355-3213 (Printed)ISSN 1796-2226 (Online)

Cover DesignRaimo Ahonen

JUVENES PRINTTAMPERE 2016

OpponentDocent Yrjö Hiltunen

Koivuranta, Elisa, Optical monitoring of flocs and filaments in the activated sludgeprocess. University of Oulu Graduate School; University of Oulu, Faculty of TechnologyActa Univ. Oul. C 566, 2016University of Oulu, P.O. Box 8000, FI-90014 University of Oulu, Finland

Abstract

Flocculation plays a critical role in the activated sludge process, where flocs are removed bysettling and where unsatisfactory flocculation is resulting in poor effluent quality. Control andoperation of the process is also challenging as it is sensitive to external and internal disturbances.Furthermore, stricter environmental demands are also being placed on wastewater treatment anddischarge quality thus solutions are needed to improve the current systems.

A novel optical monitoring method employing a tube flow and a CCD camera was developedto characterize the flocs and filaments of the sludge, and the method was tested on samples fromfull-scale activated sludge plants. An online device operating on the same principle was alsodeveloped and this was tested over a period of eight months at municipal wastewater treatmentplant.

Optical monitoring was employed in the laboratory to study the breakage of activated sludgeflocs. Based on the image analysis data, in the industrial plant the major breakage process waslarge-scale fragmentation. In the two municipal plants, it was surface erosion. The flocs had morefilaments and were more irregular in shape in the industrial plant, which could be the reason forthe large-scale fragmentation.

The effect of floc morphology on the effluent clarity of the activated sludge process wasstudied in the industrial and municipal activated sludge plants by optical monitoring over periodsof three months and eight months, respectively. The changes in floc morphology took place slowlyin both plants. Four major factors that correlated with the purification results were the size andshape of the flocs and the quantities of small particles and filaments. The image analysis resultssuggested that the settling problem that occurred during the test periods in the industrial plant wascaused by dispersed growth, whereas that in the municipal plant was caused by filamentousbulking. In conclusion, it is possible to use the developed method online in order to analyse thestate of flocculation. Thus the method could be useful when developing online monitoringapplications for quantifying floc characteristics and for diagnosing the causes of settling problemsin the wastewater treatment plants.

Keywords: biological flocs, filamentous bacteria, floc breakage, floc morphology,flocculation, image analysis, settling properties, wastewater

Koivuranta, Elisa, Flokkien ja rihmojen optinen kuvantaminenaktiivilieteprosessissa. Oulun yliopiston tutkijakoulu; Oulun yliopisto, Teknillinen tiedekuntaActa Univ. Oul. C 566, 2016Oulun yliopisto, PL 8000, 90014 Oulun yliopisto

Tiivistelmä

Aktiivilieteprosessissa flokkulaatiolla on merkittävä rooli, sillä muodostuneet flokit poistetaanprosessista laskeutuksen avulla. Siten huono flokkulaatio johtaa puhdistetun jäteveden kiintoai-nemäärän lisääntymiseen. Prosessin säätö ja operointi on kuitenkin hankalaa, sillä aktiivilie-teprosessi on herkkä ulkoisille ja sisäisille häiriöille. Jätevedenpuhdistukseen liittyvät ympäristö-vaatimukset ja päästöehdot vesistöihin ovat myös tiukentuneet, joten uusia menetelmiä tarvitaanparantamaan nykyisiä prosesseja.

Tässä työssä kehitettiin uusi, optinen kuvantamismenetelmä karakterisoimaan flokkeja ja rih-moja. Menetelmä hyödyntää putkivirtausta ja CCD-kameraa ja sitä testattiin aktiivilietelaitostennäytteillä. Lisäksi kehitettiin samaa periaatetta noudattava online-laitteisto, jota testattiin kah-deksan kuukauden ajan.

Optista kuvantamista testattiin laboratoriossa flokkien hajoamistutkimuksessa. Kuva-analyy-situlosten perusteella kahden kunnallisen aktiivilietelaitoksen flokit hajosivat pintaeroosioonperustuvan mallin mukaan ja teollisen aktiivilietelaitoksen flokit hajosivat fragmentaatiomallinmukaan. Teollisen aktiivilietelaitoksen flokeissa oli enemmän rihmoja ja ne olivat epäsäännölli-semmän muotoisia, mikä voi olla syynä flokkien fragmentaatioon.

Flokkien morfologian vaikutus jäteveden puhdistustuloksiin tutkittiin teollisessa (kolmenkuukauden ajan) ja kunnallisessa (kahdeksan kuukauden ajan) aktiivilietelaitoksessa optisellakuvantamismenetelmällä. Molemmissa laitoksessa muutokset flokkien morfologiassa tapahtui-vat hitaasti. Neljä tärkeintä tekijää, jotka korreloivat puhdistustulosten kanssa, olivat flokkienkoko ja muoto sekä pienten partikkelien ja rihmojen määrä. Kuva-analyysitulosten perusteellalaskeutumisongelma teollisessa jätevesilaitoksessa johtui flokinmuodostajabakteerien liian pie-nestä määrästä ja kunnallisessa jätevesilaitoksessa rihmamaisten bakteerien liikakasvusta.Yhteenvetona voidaan todeta, että kehitettyä menetelmää on mahdollista käyttää online-mittari-na sekä sen avulla voidaan arvioida flokkulaation tilannetta. Siten menetelmää on mahdollistahyödyntää flokkien ominaisuuksien karakterisoinnissa ja arvioidessa jätevedenkäsittelylaitoksenlaskeutumisongelmien aiheuttajaa.

Asiasanat: biologiset flokit, flokin hajoaminen, flokin morfologia, flokkulaatio,jätevesi, kuva-analyysi, laskeutumisominaisuudet, rihmamaiset bakteerit

Dedicated to Pihla & Oona

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Acknowledgements

The research work reported in this thesis was performed in the Fibre and Particle

Engineering Research Unit at the University of Oulu during the years 2010-2015.

The research was provided and carried out as part of the Measurement, Monitoring

and Environmental Efficiency Assessment (MMEA), research programme of

CLEEN (Cluster for Energy and Environment) Ltd. Financial support from Maa-

ja vesitekniikan tuki ry, Kaupallisten ja teknillisten tieteiden tukisäätiö, Tauno

Tönning foundation and the Riitta and Jorma J. Takanen Foundation is also

gratefully acknowledged.

I would like to express my gratitude to my former principal supervisor, Jouko

Niinimäki, current Rector of the University of Oulu, for the opportunity to perform

this interesting study and for his encouragement throughout the research. I would

also like to thank my supervisors, Dr. Tuomas Stoor for his valuable comments and

guidance throughout this work, and Professor Mirja Illikainen for all her support

when finalizing this thesis.

I am grateful to the reviewers of the thesis, Professor Ilse Smets of the

University of Leuven and Professor Eugénio Campos Ferreira of the University of

Minho, for their valuable feedback. Sincere thanks also go to Malcolm Hicks for

revising the English language of this thesis.

I would also thank Dr. Antti Haapala and Jukka Keskitalo for their help and

guidance at the beginning of my research career, and special thanks also go to the

personnel of Valmet, especially Joni Hattuniemi, for technical support and advice

during these years. I would similarly like to thank the staff of the Viikinmäki

wastewater treatment plant and the Control Engineering Research Unit at the

University Oulu for their fruitful cooperation.

I thank all my colleagues at the Fibre and Particle Engineering Research Unit

for their help, support and encouragement during these years. In particular, I would

thank Dr. Terhi Suopajärvi, my co-worker in the “sludge industry”, for good time

we have had in the laboratory, in the office and in our free time.

I wish to thank my parents Kaisu and Sakari and my brother Erkki-Olavi, for

their support and encouragement in my life. Finally, I wish to express my deepest

and warmest gratitude to my husband Juuso and our lovely daughters, Pihla and

Oona, whose love and support has meant everything to me.

Oulu, April 2016 Elisa Koivuranta

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Abbreviations

AR Aspect ratio

ASP Activated sludge process

BOD Biochemical oxygen demand

CCD Charge-coupled device

COD Chemical oxygen demand

DO Dissolved oxygen

DEQ Equivalent diameter

DSVI Diluted sludge volume index

EPS Extracellular polymer substance

FF Form factor

MOFI Floc measurement environment

SRT Sludge retention time

SVI Sludge volume index

SS Suspended solids

TSS Total suspended solids

WWTP Wastewater treatment plant

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List of original publications

This thesis is based on the following publications, which are referred throughout

by their Roman numerals:

I Koivuranta E, Keskitalo J, Haapala A, Stoor T, Sarén M & Niinimäki J (2013) Optical monitoring of activated sludge flocs in bulking and non-bulking conditions. Environmental Technology 34(5): 679–686.

II Koivuranta E, Keskitalo J, Stoor T, Hattuniemi J, Sarén M & Niinimäki J (2014) A comparison between floc morphology and the effluent clarity at a full-scale activated sludge plant using optical monitoring. Environmental Technology 35(13): 1605–1610.

III Koivuranta E, Stoor T, Hattuniemi J & Niinimäki J (2015) On-line optical monitoring of activated sludge floc morphology. Journal of Water Process Engineering 5: 28–34.

IV Koivuranta E, Suopajärvi T, Stoor T, Hattuniemi J & Niinimäki J (2015) Use of optical monitoring to assess the breakage of activated sludge flocs. Particulate Science and Technology 33(4): 412–417.

The author of this thesis was the primary author of the above publications, being

mainly responsible for experimental design, data analysis and reporting of the

results. The co-authors participated in the design and development of the optical

monitoring and image analysis methods and also made valuable comments on the

manuscripts.

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15

Table of contents

Abstract

Tiivistelmä

Acknowledgements 9 Abbreviations 11 List of original publications 13 Table of contents 15 1 Introduction 17

1.1 Background ............................................................................................. 17 1.2 Activated sludge process ......................................................................... 17 1.3 Floc formation ......................................................................................... 19

1.3.1 Flocculation disturbances ............................................................. 20 1.4 Floc strength and breakage...................................................................... 22

1.4.1 Measurement of floc strength ....................................................... 24 1.5 Wastewater quality and settleability parameters ..................................... 25 1.6 Characterisation of activated sludge flocs ............................................... 26

1.6.1 Floc size ........................................................................................ 27 1.6.2 Floc shape ..................................................................................... 28

2 The problem and the aims of the research 31 2.1 The research problem .............................................................................. 31 2.2 Aims of the present work ........................................................................ 31 2.3 Outline of the thesis ................................................................................ 31

3 Materials and methods 33 3.1 Materials ................................................................................................. 33 3.2 Methods ................................................................................................... 35

3.2.1 Floc measurement environment (MOFI) ...................................... 35 3.2.2 Online optical monitoring device ................................................. 36 3.2.3 Image analysis .............................................................................. 37 3.2.4 Settling velocity ............................................................................ 38 3.2.5 Dilution ......................................................................................... 39 3.2.6 Repeatability test .......................................................................... 39 3.2.7 Floc breakage procedure ............................................................... 39

3.3 Tests in the wastewater treatment plants ................................................. 40 3.3.1 Industrial wastewater treatment plant ........................................... 40 3.3.2 Municipal wastewater treatment plant .......................................... 40 3.3.3 Performance of the wastewater treatment plants .......................... 40

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3.3.4 Statistical analysis ........................................................................ 41 4 Results and discussion 43

4.1 Development of the optical monitoring................................................... 43 4.1.1 Repeatability of optical monitoring .............................................. 43 4.1.2 Effect of dilution ........................................................................... 44 4.1.3 Variation in floc morphology between the wastewater

treatment plants ............................................................................ 45 4.1.4 Variation in floc morphology in different settling

situations ....................................................................................... 45 4.1.5 Short-term variations in floc morphology .................................... 48

4.2 Breakage of activated sludge flocs .......................................................... 49 4.2.1 Breakage factor ............................................................................. 51

4.3 Test at the wastewater treatment plants ................................................... 51 4.3.1 The purification efficiency of biological treatment during

trials .............................................................................................. 52 4.3.2 Effect of influent composition on floc morphology ..................... 53 4.3.3 Effect of floc morphology on clarity of the effluent ..................... 55 4.3.4 Poor settling situations in the activated sludge plants .................. 59 4.3.5 Statistical analysis ........................................................................ 60

5 Conclusions 63 References 65 Original publications 73

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1 Introduction

1.1 Background

Flocculation plays a critical role in most wastewater treatment plants (WWTPs),

especially those employing the activated sludge process (ASP). ASP is a typical

process in both municipal and industrial WWTPs in which microorganisms are

used to degrade the organic matter in wastewater to form flocs, which are removed

by settling (Mesquita et al. 2013; Jassby et al. 2014). Unsatisfactory settling

performance due to poor flocculation nevertheless remains a common problem in

most activated sludge plants, resulting in poor effluent quality, reduced system

capacity and increased capital and operating costs (Wilén et al. 2008; Jones &

Schuler 2010; Jassby et al. 2014). Like most biological processes, the ASP is also

sensitive to external and internal variations and has temporally variable

characteristics (Sarraguça et al. 2009; Mesquita et al. 2011a), that make its control

and operation challenging, especially since we still lack an online method for

measuring floc characteristics (Dierdonck et al. 2012). Moreover, increasingly

strict environmental demands are being placed on water discharged from WWTPs

(Bourgeois et al. 2001; Vanrolleghem & Lee 2003; Sarraguça et al. 2009) so that

novel solutions are needed to improve and enhance the current systems. It is thus

conceivable that online optical monitoring of flocs morphology could lead to a

better understanding of bioflocculation and would open up new possibilities for

operating and controlling the ASP.

1.2 Activated sludge process

The ASP was developed simultaneously in Massachusetts, USA, and Manchester,

England, around 1913-1914 (Tchobanoglous et al. 2003) and the same principle is

still used in modern activated sludge plants. It consists of two stages, a biological

stage (aeration basin) and a physical stage (secondary clarifier) (Martins et al. 2004). The main target is to promote the growth of microbial populations that will

degrade organic matter to biomass, carbon dioxide and water. These

microorganisms flocculate spontaneously in the aeration tanks and are removed by

settling in the sedimentation tanks. (Zartarian et al. 1997; Martins et al. 2004). Most

of the concentrated sludge is recycled while a small part is wasted (Smets et al. 2006). Thus the outcome of the ASP is treated wastewater (effluent), return

18

activated sludge and waste activated sludge (Christensen et al. 2015). The basic

principle of the process is presented in Figure 1.

Fig. 1. A typical activated sludge process.

The efficiency of the ASP is highly dependent on how good a solid-liquid

separation is achieved, which is in turn affected by the size distribution, structure,

density and strength of the flocs (Klausen et al. 2004; Peeters et al. 2011;

Christensen et al. 2015). Flocs are highly porous, irregularly shaped and loosely

connected aggregates composed of smaller primary particles (Jarvis et al. 2005b)

and in ASP they are made up of a variety of microorganisms (primarily bacteria)

together with organic and inorganic particles (Wilén et al. 2008; Wágner et al. 2015). The particles in an ASP are usually divided into two groups: flocs, which

are typically 25-1000 µm in diameter, and primary particles, which are

approximately 0.5-5 µm in diameter (Wilén et al. 2003a). The primary particles are

mostly single bacteria and or colloidal materials which are hard to separate by

settling and thus easily escape into waterways (Mikkelsen and Keiding 2002). It

has been found previously that most particles have a diameter lower than 5 µm,

whereas the majority of the volume is found in the flocs, with a diameter in the

range 68-183 µm (Schmid et al. 2003). A microscopic image of activated sludge

flocs is presented in Figure 2.

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Fig. 2. Activated sludge flocs.

1.3 Floc formation

Floc formation in the ASP is a complex phenomenon with mechanisms that are still

poorly understood (Biggs & Lant 2002; Grady et al. 2011). Activated sludge flocs

in general have a heterogeneous, fractal-like structure and they are kept together by

Derjaguin-Landau-Verwey-Overbeek (DLVO) forces (van der Waals and

electrostatic forces), non-DLVO forces (bridging, hydrophobic forces) and physical

entanglement (Wágner et al. 2015; Christensen et al. 2015). However, biological

aggregates cannot be regarded simply as inert aggregates obeying the general

colloid-chemical laws, because the biological mechanisms interact with in a

dominant way (Klausen et al. 2004).

Activated sludge consists primarily of biological flocs that are formed by

growth of microorganisms (Christensen et al. 2015) thus the balance of the bacterial

population particularly affects floc formation (Motta et al. 2001; Mesquita et al. 2010). The main types involved are floc-forming and filamentous bacteria (Amaral

& Ferreira 2005; Wágner et al. 2015). Floc-forming bacteria, are bound together,

principally by extracellular polymeric substances (EPS) (Motta et al. 2003; Wágner

et al. 2015). EPS consist of polysaccharides, proteins, humic compounds and other

cellular ingredients (Nguyen et al. 2008; Christensen et al. 2015) and have a high

negative charge, which binds the different floc constituents together by electrostatic

forces, (Wilén et al. 2003b; Nguyen et al. 2008), while filamentous bacteria also

form a network which serves as a free surface to which bacteria can become

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attached (Motta et al. 2003; Mesquita et al. 2011a; Wágner et al. 2015). When the

floc-forming and filamentous bacterial populations are balanced, large, dense,

strong, compact flocs are built up and the sludge will settle well (Motta et al. 2001;

Amaral & Ferreira 2005; Wágner et al. 2015). The structure of activated sludge

flocs is illustrated in Figure 3.

Fig. 3. The structure of activated sludge flocs.

Apart from the bacterial balance, the cations such as Mg2+, Ca2+ and Fe2+ also play

a role in the flocculation process. Ions such as calcium and magnesium are

commonly found in natural water systems while iron is commonly used as

coagulating and phosphorous-removing agent (Sanin & Vesilind 2000; Nguyen et al. 2008; Wen et al. 2015). These cations can form bridges between the negatively

charged functional groups of the EPS (Peeters et al. 2011; Dierdonck et al. 2013).

In addition, changes in physico-chemical factors such as pH can also influence the

inter-particle forces existing between floc constituents (Wilén et al. 2008).

1.3.1 Flocculation disturbances

Flocculation disturbances in the ASP are often caused by disruption of the bacterial

population balance, which affect the floc structure (Grijspeerdt & Verstraete 1997;

Contreras et al. 2004; Banadda et al. 2005; Jenné et al. 2007; Amaral et al. 2013;

Mesquita et al. 2013). In filamentous bulking an excessive quantity of filamentous

bacteria contribute to the formation of large, irregular, open flocs (Cenens et al. 2000; Motta et al. 2003; Martins et al. 2004; Amaral & Ferreira 2005; Turtin et al. 2006; Mesquita et al. 2011a; Wágner et al. 2015) whereas a lack of filamentous

bacteria will result in small, compact, roughly spherical flocs, or pinpoint flocs

(Grijspeerdt & Verstraete 1997; Gray 2004; Amaral & Ferreira 2005; Mesquita et al. 2011a; Amanatidou et al. 2015). Similarly, an excessive quantity of floc-forming

bacteria can overproduce EPS and thus lead to the formation of weak, buoyant flocs,

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in what is known as zoogleal bulking (Gerardi 2002; Turtin et al. 2006; Mesquita

et al. 2011a), whereas small quantities of floc-forming bacteria will produce only

small, dispersed flocs, or dispersed growth (Comas et al. 2003; Amaral & Ferreira

2005). The presence of primary particles in particular is due to the formation of

pinpoint flocs or the growth of dispersed bacteria (Wilén et al. 2003a). The main

characteristics of the various disturbances and their effects on floc morphology are

presented in Figure 4.

Fig. 4. The most common sludge problems.

The competition between floc forming and filamentous bacteria is affected by many

factors, such as variation of influent temperature and composition and flow rate

(Motta et al. 2003). For example, a 20% to 30% increase in wastewater loads was

observed in Nordic countries, which can affect to the bacteria balance (Brault et al. 2011). The filamentous bacteria are slowly growing organism compared to the non-

filamentous bacteria (Turtin et al. 2006). The most common factors that promote

the growth of filamentous bacteria are limitation of substrate (carbon, nitrogen and

phosphorous) and low dissolved oxygen (DO) concentrations in the ASP (Motta et al. 2003; Contreras et al. 2004; Rossetti et al. 2005; Brault et al. 2011; Wágner et

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al. 2015). Low temperature also favours the growth of filamentous bacteria (Knoop

and Kunst 1998).

Disturbances in the ASP are often caused by the operators´ inability to rapidly

detect and correctly diagnose the changes in biomass and bacteria population shifts

(Brault et al. 2011). Thus, remedial actions are sometimes needed to prevent the

escape of solids into the waterways, but there is no universal strategy for prevent

the occurrence of these situations (Mielczarek et al. 2012). In general terms, there

are two strategies for controlling poor settling situations: involving specific or non-

specific methods (Rossetti et al. 2005). The non-specific methods include

chlorination, ozonation and the application of hydrogen peroxide, which

particularly affects the growth of filamentous bacteria. The use of these methods is

questionable, however, as they can form undesirable by-products such as

halogenated organic compounds. (Martins et al. 2004) Other way to affect the

growth of filamentous bacteria is the addition of polyaluminium chloride, although

it is a high-cost chemical and its use increase the sludge production (Roels et al. 2002; Rossetti et al. 2005). However, these methods do not remove the cause of

poor settling situation and their effect is only temporary. The same also applies to

other short-term control methods such as decreasing the sludge retention time

(SRT). (Martins et al. 2004; Rossetti et al. 2005) The SRT represents the average

period of time during which the sludge has remained in the ASP (Tchobanoglous et al. 2003) and it can alter the proportions of floc forming and filamentous bacteria

present in the sludge (Amanatidou et al. 2015). However, other specific methods,

such as improving DO and substrate concentrations, have a preventive effect when

the aim is to maintain the proper bacterial population balance in the ASP (Xie et al. 2007), e.g. in the case of the filamentous bulking by suppressing filamentous

bacteria and selectively support the growth of floc forming bacteria (Contreras et al. 2004). The challenge in this case, however, is to find the right operational

conditions for achieving this aim because activated sludge is a result of slow

dynamics that are difficult to monitor (Brault et al. 2011).

1.4 Floc strength and breakage

Floc strength is an important operational parameter when the aim is to achieve

efficient removal of flocculating particles in the solid-liquid separation process.

Although unit processes in wastewater treatment are generally designed to

minimise floc breakage, it is the case in reality that flocs break up into smaller

particles due to shear forces active during aeration, dewatering and pumping, for

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example. (Jarvis et al. 2005a; Liu et al. 2005) Although reflocculation may occur,

the breakage of flocs will finally lead to increased concentrations of suspended

solids (SS) in the effluent, as small particles settle more slowly than larger particles

of a similar density (Wilén et al. 2003a).

The breakage of flocs depends greatly on the intensity of shear and on floc

strength, which is not a well-defined concept (Yukselen & Gregory 2004). Floc

strength is dependent on the inter-particle bonds between the components of the

flocs (Klausen et al. 2004; Jarvis et al. 2005a). However, the complexity of floc

components and their dissimilar structure make the floc strength difficult to

determine (Jarvis et al. 2005a; Sheng et al. 2008). Moreover, it is also shown in the

study of Klausen et al. (2004) that shear resistance of different bacterial

microcolonies has a large variation.

Floc breakage will occur if the stress applied to the surface of a floc is larger

than the bonding strength within the floc (Jarvis et al. 2005a; Li et al. 2007). It can

therefore be assumed that increased floc compaction will improve floc strength, as

it will increase the number of bonds holding the floc together (Jarvis et al. 2005a).

The generally accepted view is that there are two models of floc breakage: surface

erosion and large-scale fragmentation (Fig. 5) which are assumed to be linked to

different types of stress, fragmentation being thought to arise from tensile stress

acting across the whole floc and erosion from a shear stress acting tangentially to

the floc surface (Yukselen & Gregory 2004; Jarvis et al. 2005a). Surface erosion

involves the removal of small particles from the parent floc, resulting in an increase

in the concentration of small particles, while in large-scale fragmentation the parent

floc is broken into pieces without any increase in the concentration of small

particles (Jarvis et al. 2005a). Thus different breakage modes produce different size

distributions after breakage, therefore providing a method to determine whether

erosion or fragmentation has occurred (He et al. 2012). In addition, the time scales

of these two breakage models are different: fragmentation occurs immediately after

the occurrence of the critical stress and surface erosion occurs over a longer period

of time (Vassileva et al., 2007).

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Fig. 5. Floc breakage models.

1.4.1 Measurement of floc strength

Despite the critical nature of floc strength, no standardized test for it has been

established so far (Li et al. 2007), although many techniques have been used, e.g.

in the shear sensitivity test of Mikkelsen and Keiding (2002) where activated sludge

samples were subjected to shear treatment and the turbidity of the supernatant was

measured, thus reflecting the dispersed primary particle concentration. Turbidity

measurements were also used in the procedure of Zita & Hermansson (1994), while

Seka & Verstraete (2003) compared sludge volume values in mixed and non-mixed

samples in order to demonstrate that this ratio is affected by floc strength. In

general, there are two fundamental approaches for floc strength measurements:

macroscopic measurement of the energy required for floc breakage, and

microscopic measurement of individual flocs. It is difficult to compare these

methods, as they measure floc strength in different ways. (Jarvis et al., 2005)

A breakage factor, the ratio of floc size before and after breakage, is one simply

way to evaluate floc strength. The higher the values of the breakage factor, the less

sensitive the flocs are to breakage. The breakage factor is not a constant and it

depends on the shear force applied during breakage. Thus breakage factors can only

be compared between cases with similar breakage conditions. On the other hand,

the breakage factor is a relatively quick and easy method for determining floc

strength. (Jarvis et al., 2005)

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1.5 Wastewater quality and settleability parameters

Although online monitoring of wastewater quality parameters has been an object

of interest for many years, the monitoring at most WWTPs is still infrequent and

takes place by grab sampling, in which offline analyses of water quality indicators

such as biological oxygen demand (BOD), chemical oxygen demand (COD) and

SS are performed (Bourgeois et al. 2001; Widsten 2003; Sarraguça et al. 2009). In

addition to providing vital information on the quality of treated wastewater and

treatment efficiency, these measurements also demonstrate that WWTP meets

discharge norms (Bourgeois et al. 2001).

The BOD is a measure of the amount of dissolved oxygen required for the

biochemical oxidation of the organic solutes in 5 or 7 days (Vanrolleghem & Lee

2003) and it is mainly used as a proof of compliance with relevant legislation

(Bourgeois et al. 2001). COD measures the amount of organic components in the

wastewater. The limitations of the tests, however, are that BOD measurement

requires time and the COD test on its own is unable to differentiate between

biodegradable and biologically inert organic matter and it produces liquid

hazardous waste (Vanrolleghem & Lee 2003). However, the usefulness of these

parameters for controlling ASP is questionable as they provide only a snapshot of

the ASP (Sarraguça et al. 2009). In addition, these traditional methods are

expensive, labour intensive and time-consuming (Mesquita et al. 2016).

The settleability of activated sludge has been expressed in a variety of ways.

The most common approach, largely due to its simplicity, is to calculate some

version of the sludge volume index (SVI) test (Schuler & Jang 2007). This index is

traditionally calculated as the volume occupied by a biomass sample after 30 min

of settling, divided by the dry weight of that biomass (in mL/g). Higher SVI values

are therefore taken to indicate poor settling properties in the sludge (Schuler &

Jassby 2007). Other approaches used are the diluted SVI (DSVI) method, in which

the sample is diluted, and the stirred SVI method, in which the sample is slowly

stirred during the test. These methods are less sensitive to the solids concentration

than is the traditional SVI test (Vanrolleghem & Lee 2003). The SVI itself is a non-

specific measurement, however, and its normal range of values varies in every

WWTP, making comparisons between WWTPs difficult (Jin et al. 2003; Brault et al. 2011). In addition, it is not a straightforward measurement, as various

disturbances in the biomass settleability can affect the SVI measurement in

different ways (Amaral et al. 2013) and the result may not be representative of the

actual settling processes in a sedimentation tank (Dierdonck et al. 2013). Also the

26

determination of the SVI cannot be performed timely for purposes of online

monitoring (Amaral et al. 2013).

Another way of defining the settling capacity is to measure the SS content of

the effluent, which will reveal the actual purification level (Liao et al. 2001; Jenné

et al. 2005; Dierdonck et al. 2013). With lower concentration of SS in the effluent

the more efficient the separation is and thus the better flocculation is expected to

be (Sobeck & Higgins 2002). The usefulness of both SVI and SS measurements is

nevertheless limited, as they only reveal poor settling properties but do not indicate

the cause of the settling problem (Dierdonck et al. 2012).

The lack of suitable sensors for online monitoring and control may be one

reason why the automation of wastewater systems is not as well-developed as that

of many other industrial processes. Moreover, straightforward extrapolation of

laboratory measurements is unlikely to provide a meaningful or correct picture of

the process. (Bourgeois et al. 2001) Therefore a new analytical technique is needed

for determining the state of an ASP process.

1.6 Characterisation of activated sludge flocs

A breakthrough in characterisation of flocs and identification of most common

sludge abnormalities, especially filamentous bulking, can be seen in several studies

(Grijspeerdt & Verstraete 1997; Motta et al. 2001; Motta et al. 2002; Liwarska-

Bizukojc 2005; Perez et al. 2006; Jenné et al. 2007; Mesquita et al. 2009a;

Mesquita et al. 2009b; Mesquita et al. 2011b; Boztoprak et al. 2015; Dunkel et al. 2015). Moreover, previous studies have stated that the morphological parameters

of flocs are more sensitive to track changes in sludge settleability than the

conventional SVI methods (Grijspeerdt & Verstraete 1997; Banadda et al. 2005;

Boztoprak et al. 2015) although the quantification of floc morphology using simple

geometry is difficult due to their highly irregular three-dimensional structure and

delicate nature (Chu & Lee 2004; Jarvis et al. 2005b).

Most efforts so far have been devoted to calculating floc size and shape from

magnified microscopic images, although it is still difficult to use these methods in situ (Chu & Lee 2004). Moreover, traditional microscopic methods are laborious

and time-consuming (Jarvis et al. 2005b; Liwarska-Bizukojc 2005; Dunkel et al. 2015), although the widespread use of automated image analysis for this purpose

has made the characterization of flocs faster and more objective, quantitative and

reproducible (Costa et al. 2013; Liwarska-Bizukojc et al. 2015). In addition, the

image analysis program has the advantage that it can measure an almost infinite

27

number of floc size and shape parameters (Motta et al. 2003; Jarvis et al. 2005b;

Liwarska-Bizukojc 2005). Other methods for characterizing floc size in particular

in chemical flocculation studies is use of a nephelometric turbidity meter (Cheng

et al. 2008) and a commercial digital camera systems (Juntunen et al. 2014).

However, these measurements are incapable of recognizing filaments, which

constitute one main factor in activated sludge flocs.

The morphological parameters of activated sludge flocs can be divided into

two groups: parameters that describe floc size and parameters that describe their

shape, mainly with respect to circularity (Liwarska-Bizukojc et al. 2015). In

addition, image analysis plays an important role in the quantification of filamentous

bacteria, which are also an essential element in the activated sludge process. In

general, a key parameter expressing the number of filamentous bacteria is the total

filament length per image (Liwarska-Bizukojc 2005). Also the ratio filament

length/floc area is a commonly used indicator for the relative abundance of

filaments with respect to flocs (Motta et al. 2001; Liwarska-Bizukojc 2005). In

most studies the filament length is correlated with some version of SVI

measurement (Motta et al. 2001; Jenné et al. 2005; Banadda et al. 2005; Boztoprak

et al. 2015). Dunkel et al. (2015), for example, showed a correlation between

filament length and DSVI and the study of Banadda et al. (2005) found that the

filament length increases at the same time as the SVI. However, in the study of

Motta et al. (2001) there was no global relation between SVI and the total filament

length although increases of SVI were clearly identified.

1.6.1 Floc size

There are many ways of determining floc size (Jenné et al. 2002; Jarvis et al. 2005b;

Liwarska-Bizukojc 2005):

– Length (the longest dimension of a floc),

– Length and height (the longest dimensions in the horizontal and vertical planes),

– Area (assessed by counting the pixels that constitute the floc),

– Perimeter (total length of the pixels forming the boundary between the floc and

the background), or

– Equivalent diameter (Deq) of a sphere that is equivalent to the floc, e.g. having

the same surface area.

28

1.6.2 Floc shape

An indication of the shape of a floc can be provided as follows (Grijspeerdt &

Verstraete 1997; Jenné et al. 2002; Liwarska-Bizukojc 2005):

– Aspect ratio (AR) is the ratio of the length of the floc to its height, i.e. it

describes how elongated the floc is,

– Form factor (FF) is the ratio of the area of the floc to that of a circle with the

same perimeter, and

– Roundness (RO) is the ratio of the area of the floc to the area of a circle with a

diameter equal to the length of the floc.

The AR is dimensionless and ignores certain features such as the smoothness of

boundaries. On the other hand, particles with more irregular boundaries have a

longer perimeter relative to their surface area, and thus have a smaller FF. Thus the

FF is affected by the irregularity of the particle´s boundary and it is 1 for a perfect

circle and less than 1 for any other shape. In addition, RO is also 1 for a perfect

circle, but as it uses the length of the floc, it is more sensitive to how elongated the

floc is rather than how irregular its outline is (Russ 1990; Jenné et al. 2002; Jenné

et al. 2007).

To illustrate the differences between the various shape and size parameters,

their values are calculated for certain simple geometric shapes and for an imaginary

floc in Table 1.

29

Table 1. Floc shape parameters for certain geometric shapes and for an imaginary floc.

Shape Length Perimeter Area AR Deq RO FF

1 3.14 0.79 1 1 1 1

1 3 0.43 1.15 0.74 0.55 0.60

1 2.83 0.50 1 0.80 0.64 0.79

1 3 0.50 2 0.80 0.64 0.70

1 4.15 0.60 1.32 0.88 0.76 0.44

30

31

2 The problem and the aims of the research

2.1 The research problem

Although good flocculation is necessary for the proper functioning of an activated

sludge process, there is still a lack of methodology for quantifying flocculation

online (Jenné et al. 2002; Dierdonck et al. 2012). Thus, at the moment problems

with flocculation make themselves known only when solids have already escaped

into the surrounding waterways. With online measurement of flocs’ characteristics

it should become possible to respond more rapidly to disturbances in flocculation

and thus prevent pollutant discharge. In addition, the daily monitoring of flocs

would allow researchers to identify relationships between flocculation and sludge

settling properties.

2.2 Aims of the present work

The aim of this work was to develop a method for characterizing floc morphology

and to gain an understanding of the phenomena behind floc formation in the ASP.

The focus was on floc morphology and the effect of flocs on the settling properties

of activated sludge.

1. The first target was to develop a novel imaging method for characterizing

activated sludge flocs that can also be used online.

2. The second aim was to use this method to analyse the formation and breakage

of activated sludge flocs.

3. Finally, correlations were sought between the morphological parameters of

flocs and the settleability performance of the activated sludge.

2.3 Outline of the thesis

The author´s work on the optical monitoring of activated sludge flocs and filaments

consisted of development of the necessary methodology and its utilization. A short

introduction to the topic is presented in Chapter 1 and the aims of work are stated

in Chapter 2. The methods and materials used are presented in Chapter 3 and the

development of the optical monitoring technique is presented in Section 4.1,

followed by a discussion of floc breakage in Section 4.2 and an account of the

utilization of the method in Section 4.3. Finally, the conclusions are set out in

32

Chapter 5. An outline of the thesis in relation to the original scientific publications

is provided in Figure 6.

Fig. 6. Structure of the thesis based on the original scientific publications.

33

3 Materials and methods

3.1 Materials

Activated sludge samples were taken from three full-scale WWTPs, two of which

were municipal WWTPs and one an industrial WWTP for pulp mill effluent. Each

used a slightly different method, as presented in Table 2.

Table 2. Description of wastewater treatment plant processes.

WWTP Source of wastewater Description of process Average amount of water

treated (m3/day)

Municipal WWTP 1 Domestic (85%),

industrial (15%)

Simultaneous

precipitation in ASP

280 000

Municipal WWTP 2 Mainly domestic Preprecipitation, ASP and

postprecipitation

41 300

Industrial WWTP Mainly pulp mill effluent Activated sludge process 32 000

Both municipal WWTPs use mechanical, biological and chemical processes. The

method used at municipal WWTP 1 is a simultaneous precipitation in ASP where

the ferrous sulphate is added to the grit removal and aeration tanks. After ASP the

municipal WWTP 1 uses biological filter which consists of a bed of coarse porous

media on which a biological film grows and converts ammonia to nitrate. A

simplified schematic illustration of the municipal WWTP 1 is presented in Fig. 7.

The used methods at municipal WWTP 2 are grit removal, direct chemical

precipitation, where polyaluminium chloride is added before primary

sedimentation and postprecipitation with ferrous sulphate before secondary

sedimentation and a biological filtration. A simplified schematic of municipal

WWTP 2 is presented in Fig. 8. Municipal WWTP 1 has eight parallel lines for the

activated sludge process, each with its own sludge handling system, and WWTP 2

has three parallel lines. The legal discharge limits are < 75 mg/L for COD and < 15

mg/L for SS at WWTP 1 and < 125 mg/L for COD and < 35mg/L for SS at WWTP

2.

34

Fig. 7. A simplified schematic of municipal WWTP 1.

Fig. 8. A simplified schematic of municipal WWTP 2.

The industrial WWTP treats effluent from a mill producing about 340 000 tonnes

of fully oxygen-bleached chemical kraft pulp annually. It is a fully aerobic activated

sludge plant consisting of a screening, a primary sedimentation, a neutralization

stage, a flow equalization stage, an aeration tank and a secondary sedimentation.

The nutrient used in the industrial WWTP is urea, because the wastewater contains

enough phosphorous. A simplified schematic of industrial WWTP is presented in

Fig. 9. The legal discharge limit at the industrial WWTP is < 45t/d for COD, or

around 1400 mg/L calculated from the average amount of water treated daily.

Fig. 9. A simplified schematic of industrial WWTP.

The samples from each WWTP were collected from an aeration tank and analysed

on the sampling day, except for the sample from municipal WWTP 1 in the

breakage and dilution study, which was analysed the following day due to the long

35

distance between the WWTP and the laboratory. This sample was kept in an ice

cooler during transportation.

3.2 Methods

3.2.1 Floc measurement environment (MOFI)

The floc measurement environment (MOFI) is a small-scale research system for

use in the laboratory to analyse floc morphology. It includes a tube flow imaging

with a CCD (charge-coupled device) camera having a 5.0 mm x 3.7 mm (1392 x

1040 pixels) image sensor with a pixel size around 3.6 µm x 3.6 µm. The imaging

of particles takes place in an imaging cuvette through which the diluted sample is

pumped. The dilution ratio of samples was either 1:100 or 1:200, depending on the

sludge concentration as the aim of the dilution was to avoid overlapping flocs. It is

possible to either recycle the sample in the MOFI after imaging or to dispose of it.

It is also possible to filter successive samples with the MOFI and obtain on-line

drainage or dewatering data. Filtration analysis was not used in this work, however.

The structure of the MOFI is presented in Figure 10.

Fig. 10. Structure of the floc measurement environment (MOFI) (Paper Ⅰ, © Taylor &

Francis Online 2013).

36

3.2.2 Online optical monitoring device

The online optical monitoring device consists of a sample handling unit, an imaging

unit and a control PC and electronics unit. The imaging unit is equipped with an

industrial camera, a LED light source and a cuvette. The cuvette is planar and is

specially designed to ensure a laminar sample flow. The CCD has a 4.4 mm × 3.3

mm (1296 pixels × 966 pixels) sensor with a pixel size of 3.4 µm × 3.4 µm and is

focused on the centre of the cuvette, with its depth of field covering the whole

imaged volume. The sample is pumped to the online optical monitoring device from

the wastewater process by a large grinder pump via a pipeline, from which it is

taken to the sample container. It is then transferred to the imaging unit by a

peristaltic pump and diluted with tap water at a ratio of 1:100. The PC and

electronics unit controls the pump and valves with synchronic image acquisition.

There is also a constant water flow between the measurement cycles, and the device

is cleaned chemically once a month to prevent biofilm growth. The structure of the

online optical monitoring device is presented in Figure 11.

Fig. 11. The online optical monitoring device for imaging activated sludge flocs (Paper

Ⅲ, © Elsevier 2015).

37

3.2.3 Image analysis

An image processing and analysis program for automated analysis of the images

obtained by optical monitoring was developed using MATLAB 7.8.0 (MathWorks

Inc., Natick, MA). The basic principle of this program is presented in Figure 12. A

more accurate description of the program is presented in Paper I.

Fig. 12. Steps in the image analysis.

The image analysis program calculates specific parameters for each image, e.g. the

particle area, number of particles and various shape factors. In this thesis, flocs are

expressed in terms of the equivalent diameter Deq calculated from the projected area

A, using Eq. (1):

(1)

Shape factors are calculated only for particles greater than 100 µm2 in size, as the

boundaries of small particles are difficult to define at the given level of resolution.

Roundness (RO) is calculated using Eq. (2) and the form factor (FF) using Eq. (3)

(Russ 1990):

πareaDeq

×= 4

Image capturing in the tube flowCCD Camera, computer with image grabber

Background removalBy dividing the sample images by a background image

Separating floc and filaments into two binary imagesIncreasing contrast, creating negative images, median filtering,

creating a binary image and dilating the image to separate flocs and filaments

Removal of objects that cannot be considered proper flocs orfilaments

Particles touching image borders, air leaks, out-of-focus particles, small debris

38

(2)

(3)

Total filament length was also calculated by summing the length of the filaments

in the image. In addition, the ratio of the total filament length to total floc area in

an image was also calculated.

An example of the image analysis is presented in Figure 13.

Fig. 13. Example of an image analysis, in which the flocs are marked in blue and the

filaments in red.

3.2.4 Settling velocity

The multi-sample analytical centrifuge LUMiFuge was used to analyse the initial

settling velocity of the samples in the preliminary tests. This centrifuge allows the

settling properties of samples to be determined under the influence of various

2

4

lengthareaRO

××=

π

2

4

perimeterareaFF ×= π

39

centrifugal forces. The intensity of the transmitted near-infrared light as a function

of time and position is measured over the entire length of the sample, which makes

it possible to determine the settling velocity. The samples were centrifuged at 79 g

(800 rpm) for 8 min and the settling speed after the first 10 s was calculated. At

least four parallel measurements were made and the standard deviation was 5%.

3.2.5 Dilution test

To determine the appropriate dilution for the online optical monitoring device and

the effects of different dilutions on the floc morphology, samples from the

municipal WWTP 1 were tested with the MOFI. The samples were diluted with

deionised water at ratios of 1:50, 1:100 and 1:200 for a total volume of 2 L. The

samples were gently stirred after dilution to avoid floc breakage. They were then

passed through the imaging unit and disposed of after imaging.

3.2.6 Repeatability test

The repeatability of the optical monitoring was tested by repeating the sample

dilution (at a ratio 1:200) and filming 30 times with the MOFI so that one session

includes at least 250 images and 20 000 individual flocs. The images were analysed

with the automated image analysis program and the standard deviations of the

shape factors, filaments, particle areas and numbers of particles were determined.

3.2.7 Floc breakage procedure

The floc breakage was investigated with the MOFI. Samples were collected from

the three WWTPs (Table 2) and diluted with deionised water at a ratio of 1:100 for

a total volume of 2 L. They were then passed through the imaging unit and recycled

back into a beaker using a centrifugal pump with a rotation speed of the pump of

1400 rpm. The experiments were continued for 2 min.

Breakage factor

The breakage of the activated sludge flocs was characterized using the breakage

factor described by Wang et al. (2009):

(4) %1001

2 ×=sizesizefactorBreakage

40

where size1 is the equivalent diameter of the flocs before breakage and size2 the

equivalent diameter after breakage.

3.3 Tests in the wastewater treatment plants

3.3.1 Industrial wastewater treatment plant

Floc morphology in the industrial WWTP was studied with the MOFI over a period

of three months. Activated sludge samples were taken from the aeration tank 2-5

times per week except during the maintenance stoppage at the mill (which lasts one

week). During the stoppage, the aeration tanks were emptied and a small amount

of activated sludge was left at the bottom of the tanks so that the process could be

started up again afterwards. The trial began in May 2012 and a total of 34 samples

were collected.

Imaging of the samples took place on the day of sampling. Before the imaging,

all the samples were diluted 1:200 with deionised water, so that the total volume

was 2 L. Approximately 350-400 images were taken of each sample. Since a single

image would typically contain around 80 individual flocs, over 28 000 flocs were

analysed in each sample.

3.3.2 Municipal wastewater treatment plant

Floc morphology in the municipal WWTP 1 was studied with the online optical

monitoring device over a period of eight months. All the samples were diluted

approximately 1:100 automatically with tap water before imaging, and videos of

the samples were saved approximately twice a day for five days a week. A single

video contained about 1000 images and each image showed around 150 flocs. Thus

almost 300 000 flocs were analysed daily, providing sufficient data for statistically

reliable results. The trial began in late May 2013 and lasted 8.5 months.

3.3.3 Performance of the wastewater treatment plants

The influent composition at the industrial WWTP was measured once a week and

the effluent quality daily in the plant’s own laboratory by collecting grab samples.

41

The measurements taken were the TSS (total suspended solids) and COD (Eaton et al. 2005) and DSVI (Grijspeerdt & Verstraete 1997).

The influent composition and effluent quality of the ASP at the municipal

WWTP 1 were monitored twice a week for COD (SFS 5504:1988) and SS (SFS-

EN 872-2005). These parameters were measured by collecting grab samples from

each line once an hour every day.

3.3.4 Statistical analysis

Univariate linear correlation analyses were performed between the SS or TSS

content of the effluent biologically purified water and the morphological

parameters of the flocs. Pearson’s product momentum correlation coefficient (rp)

was used for the linear estimations of strength and direction between two

parameters. The coefficient rp falls between -1 and +1, where -1 indicates a perfect

negative correlation, +1 a perfect positive correlation and 0 the absence of any

correlation. Correlations were considered statistically significant at a 95%

confidence interval (p >0.05).

42

43

4 Results and discussion

4.1 Development of the optical monitoring

The development of a device for the optical monitoring of flocs started from a

laboratory version (MOFI) and continued to an online device. The basic principle

was the same in both methods: that the only pretreatment required should be

dilution with water and that imaging should then take place in the tube flow. The

aim of the optical monitoring was to provide an insight into floc morphological

characteristics and the presence of certain filaments. However, due the simplicity

no information about microbial community could be received and also it limits the

visualisation of filamentous bacteria to those outside of flocs.

The development of an optical monitoring method for characterizing floc

morphology is constrained by certain criteria that must be taken into account. First

of all, the method must recognize differences in floc morphology and it must

produce statistically reliable results. Moreover, the imaging of separate flocs in the

tube flow requires a high dilution, and dilutions performed in an online optical

monitoring device are not as accurate as those taking place in a laboratory

environment. Thus the effect of dilution on floc morphology must be studied

separately. Also the sampling frequency in the online system must be studied.

4.1.1 Repeatability of optical monitoring

The repeatability of the optical monitoring was tested with the MOFI, yielding the

results presented in Table 3.

Table 3. Mean values and standard deviations of the image analysis.

Morphological parameter Mean value Standard deviation [%]

Filament length/floc area [1/mm] 7.32 2.74

Form factor 0.51 2.17

Roundness 0.50 1.40

Aspect ratio 1.88 1.06

Mean area of particles [µm2] 3027 5.19

Total no. of particles per image 312 6.41

As these results show, the standard deviations of the parameters characterizing floc

morphology and filament length/floc area ratio are minor. Thus these measurements

44

can be regarded as constituting a statistically reliable means of measuring floc

morphology. The advantage of optical monitoring with tube flow is that it can

easily provide images of a substantial quantity of flocs, which makes the results

more reliable. By comparison, in microscopic studies, Boztoprakt et al. (2015)

analysed 49 images, Grijspeeerdt and Verstraete (1997) 200 objects per sample,

Contreras et al. (2004) 2000 particles per sample, Smets et al. (2006) 50 images

per sample (Smets et al. 2006) and Mesquita et al. (2011a, 2009a, 2009b) 150-200

images per sample. Moreover, in the study of Jenné et al. (2002) it was standardized

that 50 images are sufficient for representative quantification of flocs and filaments.

Thus with optical monitoring the amount of analyzed flocs per sample (over 20 000

per sample) can be considered as remarkably large.

4.1.2 Effect of dilution

Dilution of the sample is necessary for adequate floc characterization (Mesquita et al. 2010; Costa et al. 2013), although some breakage of flocs is inevitable as a result.

In addition, optical monitoring requires a much higher dilution than traditional

microscopic analysis, due to the tube flow. Dilution in previous studies using

microscopic methods has been around 1:5 (Grijspeerdt & Verstraete 1997; Costa et al. 2009a; Costa et al. 2009b; Mesquita et al. 2010). If the dilution is insufficient,

the particles will be overlaid and thus underestimated (Costa et al. 2013). The

effects of different dilutions in optical monitoring are presented in Table 4.

Table 4. Effects of dilution on floc morphology.

Dilution Equivalent diameter

[um]

Filament length/ floc

area [1/mm]

Roundness Aspect ratio

1:50 75.6 4.35 0.52 1.94

1:100 73.0 4.52 0.54 1.93

1:200 74.0 4.39 0.54 1.94

As seen in Table 4, there are no significant differences in floc morphology between

these dilutions indicating that if dilution varies in the online optical monitoring

device, it will not notably affect the floc morphology. However, it must be noted

that because dilution is so much higher in optical monitoring system than in

traditional microscopic methods, the optical monitoring is not fully comparable to

results obtained with other methods.

45

4.1.3 Variation in floc morphology between the wastewater treatment

plants

The floc morphologies of the three WWTPs (Table 2) were compared by analysing

samples with the MOFI. The results are presented in Table 5.

Table 5. Morphology of flocs from the three different wastewater treatment plants.

Wastewater

treatment plant

Equivalent

diameter [um2]

Filament

length/floc area

[1/mm]

Form factor Aspect ratio Proportion of

small particles

[%]

Municipal 1 71.7 4.46 0.56 1.91 45.6

Municipal 2 71.2 0.61 0.53 1.80 30.9

Industrial 76.2 6.50 0.42 1.98 42.5

It has been pointed out previously that there is a wide variation in floc morphology

between sludges taken from WWTPs that differ in design and process operating

conditions (Wilén et al. 2003a; Mielczarek et al. 2012; Liwarska-Bizukojc et al. 2015). In the present instance, there is a difference in filament length/ floc area ratio

with by far the highest value recorded at the industrial WWTP and the clearly

lowest at the municipal WWTP 2. The reason for the low amount of filaments in

the municipal WWTP 2 could be that this plant also uses polyaluminium chloride,

which affects the growth of filamentous bacteria (Xie et al. 2007), while the reason

for high amount of filaments may lie in filamentous bulking, which is a common

problem, especially in pulp and paper mill WWTPs (Tsang et al. 2006; Brault et al. 2011), and, in view of the large numbers of filaments, might also be a problem here.

Filamentous overgrowth affects the structure of the flocs, as they can be larger and

more irregular than in a normal situation (Mesquita et al. 2011b). Here the flocs

were slightly larger in the industrial WWTP and more irregularly shaped. In this

case, the proportion of small particles was clearly smallest in municipal WWTP 2

and largest in municipal WWTP 1. The reason for the large quantity of small

particles may be that the sample from that WWTP was analysed on the following

day because of transportation, so that some floc breakage may have already

occurred.

4.1.4 Variation in floc morphology in different settling situations

The effect of floc morphology on the settling velocity was studied with 8 samples

taken from the industrial WWTP, 4 of which were taken when the process had

46

problems in sludge settling and gave poor purification results (bulking sludge),

while the other 4 were taken when the process was functioning normally and the

purification results were satisfactory (non-bulking sludge). Averages for the TSS

content of the effluent from the secondary sedimentation, the percentage removal

of COD in the ASP and the DSVI for both bulking and non-bulking sludge

situations are presented in Table 6. These analyses clearly show the differences in

purification results between bulking and non-bulking situations.

Table 6. Average purification values in bulking and non-bulking situations.

Performance measurement Bulking sludge Non-bulking sludge

TSS in the effluent [mg/L] 360 20

COD removal in the activated sludge process [%] 35 67

DSVI [mg/L] 442 160

The morphology of the activated sludge flocs was studied in the MOFI, measuring

a minimum of 28 000 individual flocs in each sample at a dilution ratio of 1:200.

The morphological parameters were compared with the settling velocities of the

samples as measured by analytical centrifugation (LUMiFuge). The main results of

the image analysis and the initial settling velocities of the sludge are presented in

Figure 14.

47

Fig. 14. Comparison of the image analysis results with the initial settling velocity of the

activated sludge (modified from Paper Ⅰ, © Taylor & Francis Online 2013).

As can be seen in Fig. 14, the initial settling velocity was clearly lower in a bulking

sludge situation, which correlates well with the poor purification results for the ASP

48

as a whole, as shown in Table 6. In this case the particles were smaller in the bulking

sludge situation and there were more of them. In addition, the flocs was clearly

different in shape, their aspect ratio being higher in a bulking situation, which

means that they were more elongated, and the form factor was lower, implying that

they had greater roughness and were more fragile. In addition, the filament

length/floc area ratio was greater in this situation. Thus poor settling was in this

case most probably caused by filamentous bulking, which held the flocs apart and

lowered the settling speed.

4.1.5 Short-term variations in floc morphology

The short-term variations in activated sludge floc morphology and the filament

length/floc area ratio were tested to approximate the sampling frequency of online

optical monitoring device. To this end, samples were taken once an hour and the

results are presented in Figure 15.

Fig. 15. Short-term variations in floc morphology and filament length/floc area at the

municipal wastewater treatment plant 1 (modified from Paper Ⅲ, © Elsevier 2015).

The results showed no significant variations in floc morphology during the day

measured, indicating that the sampling frequency 1-2 times a day, 5 times a week

during the test in the municipal WWTP 1 is adequate for optical monitoring. These

results are supported by a previous study which revealed that settling properties did

not considerably change during the day (Vanrolleghem et al. 1996).

49

4.2 Breakage of activated sludge flocs

The breakage of activated sludge flocs is interesting, as it also has an effect on the

purification process. In addition, some breakage of flocs is inevitable during online

optical monitoring, especially during pumping and dilution. Thus the MOFI was

also used here for studying the breakage of flocs, yielding the results presented in

Figures 16 and 17. To clarify the results, the first 30 s of breakage is shown by

calculating average values derived from 20 images in order to highlight the changes

in floc morphology. After that, a steady-state situation was achieved.

Fig. 16. Equivalent diameter and the quantity of small particles during breakage

process (Paper Ⅳ, © Taylor & Francis Online 2015).

To determine which breakage model was dominant at each WWTP, the

morphological parameters of the flocs were compared during the breakage process.

Large-scale fragmentation and surface erosion have different characteristics, as

large-scale fragmentation means that the parent flocs break up into smaller flocs,

immediately reducing the average floc diameter, and the proportion of small

particles remains the same or increases slightly, whereas in surface erosion the

quantity of small particles increases. In addition, surface erosion usually takes more

time than large-scale fragmentation. (Jarvis et al. 2005a; Vassileva et al. 2007)

In the light of the results in Figure 16, large-scale fragmentation seems to be

the dominant breakage model in the sample from the industrial WWTP, as the

equivalent diameter of the flocs decreased soon after the breakage process started.

In addition, the proportion of small particles remained the same during the breakage

process. By contrast, surface erosion seemed to be the major breakage process in

the sample from municipal WWTP 2, where the equivalent diameter and the

proportions of small particles were stable at first, after which the quantity of small

particles in particular increased and the equivalent diameter of the flocs decreased.

0 5 10 15 20 25 3066

68

70

72

74

76

Eq

uiva

lent

dia

met

er (

μm)

Time (s)

Industrial Municipal 1 Municipal 2

0 5 10 15 20 25 3030

32

34

36

38

40

42

44

46

48

Pro

port

ion

of s

ma

ll pa

rtic

les

(%)

Time (s)

Industrial Municipal 1 Municipal 2

50

The sample from municipal WWTP 1 differed from the others in that the equivalent

diameter of the flocs started to grow at first, indicating the presence of flocculation,

but the proportion of small particles remained the same during then breakage

process, indicating that flocculation was occurring between flocs. After a while the

equivalent diameter of the flocs started to decrease and the proportions of small

particles increased. Thus the breakage process after flocculation was most probably

surface erosion.

Fig. 17. Shapes of flocs during breakage processes (Paper Ⅳ, © Taylor & Francis Online

2015).

The factors (aspect ratio and form factor) changed only slightly during the breakage

process, as seen in Figure 17. The results suggest that surface erosion dominated

the breakage process in the presence of rounder flocs (municipal WWTPs), as

might have been the case in the material of Wilén et al (2003), who found that good

floc strength was achieved with rounder flocs

In a previous study Yuan & Farnood (2010) found that large-scale

fragmentation dominated the breakage of activated sludge flocs. Our results lead

us to conclude that the breakage process varied between the WWTPs. Wilén et al. (2003) also found a great deal of variation in floc strength between samples taken

from treatment plants of different designs and employing different process

conditions. The reasons for the different breakage processes might lie in differences

in floc morphology. The samples from the industrial WWTP contained more

filaments which can be a major cause of large-scale fragmentation as filamentous

bacteria bind smaller flocs together. The bond is not strong enough, however, and

the flocs are broken into pieces. Wilén et al. (2003) also observed that flocs

containing large numbers of filaments are generally less cohesive, thus confirming

this interpretation. The flocs in the samples from the municipal WWTPs were much

0 5 10 15 20 25 301.70

1.75

1.80

1.85

1.90

1.95

2.00

Asp

ect

ratio

Time (s)

Industrial Municipal 1 Municipal 2

0 5 10 15 20 25 300.40

0.42

0.44

0.46

0.48

0.50

0.52

0.54

0.56

0.58

0.60

For

m f

acto

r

Time (s)

Municipal 2 Municipal 1 Industrial

51

rounder and contained far less filaments than those in the sample from the industrial

WWTP, which may possibly explain the surface erosion observed in the breakage

processes.

4.2.1 Breakage factor

Since the breakage factor is commonly used as a means of comparing floc strengths

(Wang et al. 2009; Wang et al. 2011; Cheng et al. 2011) breakage factors were also

calculated for the present samples, yielding the results presented in Table 7.

Table 7. Breakage factors for the various samples.

Wastewater treatment plant Breakage factor

Municipal 1 97.6

Municipal 2 93.4

Industrial 94.0

The differences in the breakage factors indicate that the flocs were strongest at

municipal WWTP 1, possibly due to the occurrence of flocculation at the beginning

of the breakage process. Interestingly, the samples from municipal WWTP 2 and

from the industrial WWTP showed similar floc strengths, although their breakage

models seemed to be different. This demonstrates that the disadvantage of the

breakage factor is that it does not take into account which breakage model is

dominant.

Imaging floc breakage with the MOFI provides more detailed information than

methods that are based mainly on the floc size before and after breaking.

Conversely, the disadvantage of this method is that it is impossible to pinpoint the

relative influence on the flocs of pumping versus the hydrodynamics forces caused

by the recycling procedure. There are nevertheless several kinds of forces that can

break flocs in real ASP, so that from a practical point of view, it may be important

to analyse which breakage process is most typical in each individual WWTP.

4.3 Test at the wastewater treatment plants

The optical monitoring device was tested in both industrial WWTP (with MOFI)

and municipal WWTP (with the online device) in order to study the effect of floc

morphology on effluent clarity and the impact of the composition of the influent on

52

floc formation. In addition, the aim was to find out the reason for the poor settling

properties.

4.3.1 The purification efficiency of biological treatment during trials

The typical approach to analysing the effectiveness of the ASP is to measure either

SS or TSS and COD of the effluent after settling. With good floc formation an

activated sludge will settle well and there will be less solids in the effluent. The

composition of the effluent after settling as observed during these tests is presented

in Figures 18 and 19.

Fig. 18. Composition of the effluent at the industrial WWTP after secondary

sedimentation.

In the industrial WWTP there was clearly an unstable situation after the

maintenance stoppage, as the TSS and COD values were markedly higher. This

instability (TSS over 40 mg/L and COD over 600 mg/L) lasted for approximately

20 days and was followed by stable conditions with good purification results (TSS

under 20 mg/L and COD under 500 mg/L).

53

Fig. 19. The composition of the effluent at municipal WWTP 1 after secondary

sedimentation.

The ASP at municipal WWTP 1 also has different settling situations, although the

purification results were better than in the industrial WWTP. In this case figures of

around 10-20 mg/L were recorded in normal situations (in May to early June,

September to October, and January), while in very good situations they fell below

10 mg/L (end of June to August) and in poor situations they were above 20 mg/L

(end of October to December). The COD content after biological treatment was

normally around 40-55 mg/L, so that figures below 40 mg/L may be regarded as

very good and ones in excess of 50 mg/L as poor. It must be noted, however, that

the purification results in both trials were below the legal discharge limits with only

a few exceptions.

4.3.2 Effect of influent composition on floc morphology

The influent composition (after mechanical treatment) was compared with the floc

morphology as measured by optical monitoring; yielding the results presented in

Figures 20 and 21.

May Jun Jul Aug Sep Oct Nov Dec Jan0

20

40

60

80

100

SS COD

Month

SS

(m

g/L

)

0

20

40

60

80

100

CO

D (

mg

/L)

54

Fig. 20. Composition of mechanical purified water in the industrial WWTP as compared

with the equivalent diameter of flocs and filament length/ floc area ratio.

Fig. 21. Composition of mechanical purified water in municipal WWTP 1 as compared

with the equivalent diameter of flocs and filament length/ floc area ratio (modified from

Paper Ⅲ, © Elsevier 2015).

The COD values of the influent were much higher in the industrial WWTP than in

the municipal WWTP 1, and the filament length/floc area ratio was also higher. As

seen in Figure 18 there was clearly an unstable situation at the industrial WWTP

after maintenance stoppage, and there were few additional peaks in the COD of the

influent as seen in Figure 20. Otherwise, there was no clear correlation between

filament length/ floc area ratio or the equivalent diameter of flocs and the

composition of the influent, so that it is not likely that the influent composition

caused the unstable situation.

In the municipal WWTP 1, there seemed to be a slight correlation between the

composition of the influent and filament length/floc area ratio (Figure 21). The

composition of influent may have caused a bacterial imbalance, as filamentous

bulking in particular has been linked to low organic matter content (Martins et al.

55

2004; Turtin et al. 2006; Jones & Schuler 2010; Mielczarek et al. 2012) which may

also have occurred in this case, as the filament length/floc area ratio started to grow

as the COD values dropped, while filament length/floc area ratio began to decrease

as COD increased. Similar results have also been obtained in previous studies

(Wilén et al. 2008; Peng et al. 2012), where increased organic loading had a

positive effect on solid–liquid separation properties.

Apart from the influent composition, seasonal variations can also explain the

poor settling properties as low temperature favours a growth of filamentous

bacteria (Knoop and Kunst 1998; Rossetti et al. 2005). Jones & Schuler (2010), for

instance, found that filament length was greater during cold weather, which was

also true in the tests conducted at municipal WWTP 1. However, the tests at the

industrial WWTP were carried out from May to end of July, so that the poor settling

situation in that case cannot be attributed to seasonal variation.

4.3.3 Effect of floc morphology on clarity of the effluent

The main results arising from the comparison of floc morphology with effluent

clarity as measured in terms of the solid contents are presented in Figures 22-27.

Fig. 22. Effect of floc size and the proportion of small particles on effluent clarity at the

industrial WWTP (modified from Paper Ⅱ, © Taylor & Francis Online 2014).

56

Fig. 23. The effect of floc size and the proportion of small particles on effluent clarity at

the municipal WWTP 1 (modified from Paper Ⅲ, © Elsevier 2015).

It is in general desirable to have large, dense flocs that settle rapidly (Jenné et al. 2007). In the present work the flocs were divided into two groups by size: flocs

with an equivalent diameter greater than 25 µm and small particles with an

equivalent diameter less than 25 µm. Interestingly, the size of the flocs did not seem

to affect the purification results during the tests at the industrial WWTP as much as

did the quantity of small particles (Figure 22). Also, the quantity of small particles

was particularly high after the maintenance stoppage. By contrast, there seemed to

be a correlation between purification effectiveness and the size of the flocs during

the tests in the municipal WWTP 1, as better purification was also achieved with

bigger flocs (Figure 23). In addition, there were less small particles present,

although the difference was not particularly significant. Interestingly, good

purification results were also achieved with smaller flocs in municipal WWTP 1

(in June-July) indicating that their density was greater in that case. Similar results

were also reported by Peng et al. (2012), who also achieved good settleability with

smaller flocs having a compact structure. Also in a previous study a linear

relationship between floc area and TSS was found (Liwarska-Bizukojc & Bizukojc

2005). However, the correlation is not linear in the full-scale WWTPs based on

these results.

57

Fig. 24. Effect of floc shape on effluent clarity at the industrial WWTP (modified from

Paper Ⅱ, © Taylor & Francis Online 2014).

Fig. 25. Effect of floc shape on effluent clarity at the municipal WWTP 1 (modified from

Paper Ⅲ, © Elsevier 2015).

Floc shape was quantified in terms of roundness and the aspect ratio. The industrial

WWTP (Figure 24) and municipal WWTP 1 (Figure 25) showed similar results, as

with more round and compact flocs better purification was achieved. This could

also explain why good settling properties were achieved with smaller flocs (in the

case of municipal WWTP 1), as they were more compact, and why poor settling

properties were recorded with normal-sized flocs (in the case of the industrial

WWTP), as they were more elongated and had more irregular boundaries. These

results differed from those reported earlier (Mielczarek et al. 2012; Liwarska-

Bizukojc et al. 2015) where the measurement of floc shapes in full-scale WWTPs

was found to be less useful than the measurement of floc diameter or area.

58

Fig. 26. Effect of filament length/floc area ratio on effluent clarity at the industrial WWTP

(modified from Paper Ⅱ, © Taylor & Francis Online 2014).

Fig. 27. Effect of filament length/floc area ratio on effluent clarity at the municipal

WWTP 1 (modified from (modified from (Paper Ⅲ, © Elsevier 2015).

Filaments are interesting as they indicate that an overgrowth of filamentous bacteria

could lead to filamentous bulking, and it was this that attracted us to determine the

quantities of filaments present. However, it should be noted that filamentous

bacteria can be smaller in diameter than the pixel size employed in optical

monitoring, so that not all the filaments would have been visible in the imaging

system (Eikelboom 2000; Martins et al. 2004). Interestingly, the poor settling

situation observed in the industrial WWTP (Figure 26) differed from that in

municipal WWTP 1 (Figure 27), as huge numbers of filaments were present in the

latter case whereas the numbers in the former case were unexceptional. This

indicates that the poor settling situations in the two cases had different causes.

59

The differences in morphological parameters in the industrial WWTP may be

illustrated by means of the three situations depicted in Figure 28. At the beginning

of the tests the flocs were large and there were plenty of filaments, but after

maintenance stoppage they were smaller and somewhat irregular, only to become

large again by the end of the tests. Likewise the three microscopic images from

municipal WWTP 1 presented in Figure 29, show distinctly larger flocs in the

sample taken in August, as also seen in the optical monitoring results.

Fig. 28. Sections of images from image analysis program (550 x 550pixels) taken at the

industrial WWTP before the stoppage (left), during an unstable situation (middle) and

during a stable situation (right) (Paper Ⅱ, © Taylor & Francis Online 2014).

Fig. 29. Three microscopic images from a municipal WWTP 1.

4.3.4 Poor settling situations in the activated sludge plants

When analysing the causes of poor settling situations it is important that all

morphological factors are taken into account. Based on the optical monitoring,

unstable situations in the industrial WWTP were most likely caused by dispersed

60

growth, because the flocs were small, the numbers of filaments were normal, the

numbers of small particles were high and the flocs were non-spherical and irregular.

In addition, with lower SRT the higher amount of small flocs (Liwarska-Bizukojc

et al. 2015) and dispersed growth can exist (Grady et al. 2011) as was the situation

after the maintenance stoppage, confirming the results obtained by optical

monitoring.

In the case of municipal WWTP 1, however, more filaments were found in the

poor settling situation than in a normal situation. Furthermore, no clear difference

was found in terms of the quantity of small particles, indicating that the settling

problem was caused by filamentous bulking, where flocs are typically described as

being larger than those found in normal situations (Turtin et al. 2006; Mesquita et al. 2011b). In the case of this municipal WWTP, however, smaller flocs were

generated in a poor settling situation. Even so, in view of the fact that flocs are

easily broken by large-scale fragmentation when the quantity of filaments is high,

the floc size could also have been affected by this factor in the present case. In

addition, Dierdonck et al. (2012) found that a low loading rate also caused floc

fragmentation, whereas a high loading rate caused floc erosion. Likewise, the

present findings revealed that a decrease in influent loading rate exerted a negative

effect on the settling properties of the activated sludge, whereas no significant

difference was found in the quantity of small particles. This result indicates that

large-scale fragmentation may have occurred either during the ASP or during the

optical monitoring. Also, Wilén et al. (2008) and Mielczarek et al. (2012) have

found that flocs were much more open and irregularly shaped during the winter, a

result similar to that obtained here in municipal WWTP 1.

It seems that changes in floc morphology take place slowly, as observed also

earlier on a laboratory scale by Grijspeerdt & Verstraete (1997). There also seems

to be correlation between floc morphology and effluent clarity, indicating that

method developed here is suitable for analysing the state of an ASP and thus has a

potential for leading to the development of a monitoring application for controlling

plant performance and diagnosing the causes settling problems.

4.3.5 Statistical analysis

Although statistical analysis was used to confirm the results of the image analysis,

it must be noted that the correlations are most probably not linear, so that the results

are only approximate. In a normal situation the delay between the optical

monitoring measurement and the effluent from secondary sedimentation is about

61

13 hours, and the slowness of the variation in floc morphology also means that the

morphological parameters have been correlated with the next day’s purification

results. The results of the statistical analysis are presented in Table 8.

Table 8. Pearson´s correlation (rp) and p-values for the linear correlations between the

morphological parameters of flocs and TSS content (in the industrial WWTP) and SS (in

the municipal WWTP 1) after biological purification.

Morphological

parameter

TSS (Industrial) SS (Municipal 1)

rp p n rp p n

Filament

length/floc

area

-0.599 0.000 34 0.725 0.000 57

Equivalent

diameter

-0.690 0.000 35 -0.065 0.636 57

Roundness -0.135 0.446 35 -0.520 0.000 57

Aspect ratio 0.530 0.001 35 0.615 0.000 57

Proportion of

small particles

0.473 0.004 35 0.217 0.126 57

In the case of the industrial WWTP the proportion of small particles and the aspect

ratio are positively correlated with the TSS content of the effluent while the

equivalent diameter and filament length/floc area ratio are negatively correlated.

Only roundness failed to show a statistically significant correlation with the TSS

content of the effluent.

In the case of municipal WWTP 1 the statistical analysis showed a clear

positive correlation between filament length/floc area ratio and the SS content of

the effluent after biological treatment. This finding confirms that the poor

purification situation was most probably caused by filamentous bacteria. A

correlation was also found between the shape factors and SS content, indicating

that non-spherical flocs have an effect on purification efficiency. Interestingly, no

significant correlation was found between the equivalent diameters of the flocs and

the SS content, although the flocs were larger in a good settling situation than in a

poor one. This poor correlation can be attributed to differences in normal settling

situations, because the same purification results were achieved with large, non-

spherical flocs as with small, round flocs. A previous study by Smets et al. (2006)

also showed that filament length and floc shape were better predictors of activated

sludge settleability than was the equivalent diameter of the flocs. Thus when

assessing ASP status and analysing the causes of settling problems it is necessary

62

to consider all the factors relevant to the ASP (size, shape, number of small particles

and filaments).

Based on the image analysis results obtained with the online device, Tomperi

et al. (2016) developed a simple model for predicting the SS level in the effluent

using a nonlinear scaling method. It was shown that the results of online optical

monitoring can be used to forecast the quality of biologically treated wastewater,

therefore the optical monitoring could be a valuable tool for monitoring the process,

maintaining stable operating conditions and avoiding environmental risks (Tomperi

et al. 2016).

In the case of municipal WWTP 1 the samples were taken from only one line

even though the plant has eight parallel lines, but a correlation seemed to exist

between the floc morphology and the purification results despite the fact that the

results were compared with the purification outcomes on all the lines. More

accurate information could nevertheless have been obtained by comparing the floc

morphology with the settling properties of the same process line, or by measuring

the morphology of the flocs in all the lines. Also, more specific information about

floc morphology and inside filaments, for instance, could be achieved with a higher

resolution camera, which would be a great advantage, especially in analysing the

bacteria population balance.

63

5 Conclusions

The aims of this thesis were to develop a novel online optical monitoring device

for quantifying floc morphology at wastewater treatment plants and to use the

resulting method to find correlations between floc morphology and effluent clarity,

thereby providing information on floc formation in the activated sludge process.

The optical monitoring of flocs in tube flow with a CCD camera enabled

differences in floc morphology to be recognized in a laboratory floc measurement

environment and when using an online optical monitoring device. It was thus

confirmed that the use of tube flow and a CCD camera for characterizing activated

sludge flocs has a potential for serving as a monitoring and control method in

wastewater treatment plants.

Optical monitoring was also used to analyse the breakage of activated sludge

flocs from three wastewater treatment plants, whereupon the results suggested that

this analytical procedure gives more accurate information on which breaking model

is dominant than does the traditional method in which floc size is measured before

and after breakage. It can be concluded from these results that both large-scale

fragmentation and surface erosion can take place in activated sludge flocs

depending on their morphology.

The optical monitoring method was tested in the evaluation of floc formation

in industrial and municipal wastewater treatment plants in order to determine the

effects of floc morphology on the activated sludge process. Good and poor settling

situations were encountered in both wastewater treatment plants, providing a

possibility for analysing variations in the process by means of optical monitoring.

The plants differed in terms of the cause of their poor settling situations. The most

likely cause in the industrial wastewater treatment plant being dispersed growth, as

there was plenty high incidence of small, irregular particles compared with the

municipal wastewater treatment plant, where the most likely cause was filamentous

bulking, as there were large numbers of filaments present. Thus the method

developed here is not only suitable for recognizing differences in the morphology

of flocs but can also provide a tool for analysing the causes of poor settling

situations.

In conclusion, there were differences in the correlations between floc

morphological parameters and effluent clarity that could be attributed to various

flocculation disturbances in the wastewater treatment plants. Thus the factors that

should be taken into account when analysis the state of an activated sludge process

are the sizes and shapes of the flocs, the quantity of small particles and the lengths

64

of the filaments present. The results obtained here suggest that the method is

suitable for quantifying all these factors and can be used as an instantaneous

monitoring system or for forecasting the quality of biologically treated wastewater,

although more work still has to be done in this field.

65

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Original publications

I Koivuranta E, Keskitalo J, Haapala A, Stoor T, Sarén M & Niinimäki J (2013) Optical monitoring of activated sludge flocs in bulking and non-bulking conditions. Environmental Technology 34(5): 679–686.

II Koivuranta E, Keskitalo J, Stoor T, Hattuniemi J, Sarén M & Niinimäki J (2014) A comparison between floc morphology and the effluent clarity at a full-scale activated sludge plant using optical monitoring. Environmental Technology 35(13): 1605–1610.

III Koivuranta E, Stoor T, Hattuniemi J & Niinimäki J (2015) On-line optical monitoring of activated sludge floc morphology. Journal of Water Process Engineering 5: 28–34.

IV Koivuranta E, Suopajärvi T, Stoor T, Hattuniemi J & Niinimäki J (2015) Use of optical monitoring to assess the breakage of activated sludge flocs. Particulate Science and Technology 33(4): 412–417.

Reprinted with permission from Taylor & Francis (Ⅰ, Ⅱ, Ⅳ) and Elsevier (Ⅲ)

Original publications are not included in the electronic version of the dissertation.

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OPTICAL MONITORING OF FLOCS AND FILAMENTS IN THE ACTIVATED SLUDGE PROCESS

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