Influent fractionation using a respirometric method for...

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Faculty of Bioscience Engineering

Academic year 2013 – 2014

Influent fractionation using a respirometric method for the characterisation of primary sedimentation

Ellen Vanassche Promotor: Prof. dr. ir. Ingmar Nopens Tutor: ing. Youri Amerlinck

Master’s dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Environmental Sanitation and

Management


The author and the promoter give the permission to use this thesis for consultation and to copy parts of it for personal use. Every other use is subject to the copyright laws, more specifically the source must be extensively specified when using results from this thesis. De auteur en de promotor geven de toelating dit afstudeerwerk voor consultatie beschikbaar te stellen en delen ervan te kopiëren voor persoonlijk gebruik. Elk ander gebruik valt onder de beperkingen van het auteursrecht, in het bijzonder met betrekking tot de verplichting uitdrukkelijk de bron te vermelden bij het aanhalen van resultaten uit dit afstudeerwerk. De promotor De auteur Prof. dr. ir. I. Nopens Ellen Vanassche

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WOORD VOORAF

Het tot stand brengen van een eindwerk is een leerrijke en boeiende opdracht maar verliep niet altijd even gemakkelijk. Het schrijven van dit eindwerk was echter nooit gelukt zonder de hulp van heel veel mensen. In de eerste plaats wil ik mijn promotor Ingmar Nopens bedanken voor de kans die hij me gegeven heeft om in zijn labo dit eindwerk te maken. Verder wil ik mijn begeleider Youri Amerlinck bedanken voor het vele verbeterwerk en de uitleg die hij me geduldig gaf . Graag wil ik ook alle mensen van het labo bedanken voor hun hulp en de aangename werksfeer. In het bijzonder denk ik aan Tinne en Giacomo, die altijd klaar stonden om mij te helpen. Zonder mijn collega-‐thesisstudenten Hélène, Stijn en Chaïm zou ik bijlange niet zoveel plezier beleefd hebben in het labo. Bedankt ook aan Maud en Merel voor alle fijne ontspanningsmomenten. Tenslotte wil ik mijn ouders en Gert in de bloemetjes zetten omdat ze mij in alles wat ik doe altijd steunen. Ellen

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TABLE OF CONTENTS

LIST OF ABBREVIATIONS ................................................................................................... IV

SUMMARY ........................................................................................................................ VI

SAMENVATTING .............................................................................................................. VII

INTRODUCTION ................................................................................................................. 1

1 LITERATURE REVIEW .................................................................................................... 3

1.1 Primary sedimentation .......................................................................................... 3

1.1.1 Types of sedimentation ........................................................................................... 3

1.1.2 Design of ideal sedimentation tank ......................................................................... 5

1.1.3 Circular tanks .......................................................................................................... 7

1.1.4 Sedimentation tank performance ........................................................................... 8

1.1.5 Design considerations ............................................................................................. 8

1.2 Activated sludge modelling .................................................................................... 9

1.2.1 Introduction ............................................................................................................. 9

1.2.1.1 The carbonaceous fraction ............................................................................................ 9

1.2.1.2 The Nitrogenous fraction ............................................................................................ 11

1.2.1.3 The phosphorus fraction ............................................................................................. 11

1.2.2 Processes in ASM2d ............................................................................................... 12

1.2.2.1 Hydrolysis processes ................................................................................................... 12 1.2.2.2 Processes of facultative heterotrophic organisms ...................................................... 12 1.2.2.3 Processes of phosphate accumulating organisms ....................................................... 13 1.2.2.4 Nitrification processes ................................................................................................. 13 1.2.2.5 Chemical precipitation of phosphates ........................................................................ 13

1.3 Wastewater characterisation ................................................................................ 14

1.3.1 Biological characterisation .................................................................................... 14

2 MATERIAL AND METHODS .......................................................................................... 18

2.1 Measurement campaigns at full-‐scale WWTPs ...................................................... 18

2.1.1 WWTP of Roeselare (Belgium) .............................................................................. 18

2.1.2 WWTP of Eindhoven (The Netherlands) ................................................................ 18

2.2 Respirometer ........................................................................................................ 20

2.2.1 Introduction ........................................................................................................... 20

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2.2.2 Experimental setup ............................................................................................... 21

2.2.3 Experimental protocol for respirometric analysis ................................................. 21

2.2.3.1 Flowing gas – static liquid ........................................................................................... 22 2.2.3.2 Static gas – static liquid ............................................................................................... 24

2.3 Simulation software: WEST ................................................................................... 26

3 RESULTS AND DISCUSSION .......................................................................................... 27

3.1 Analysis of the respirogram ................................................................................... 27

3.2 Acetate as substrate ............................................................................................. 28

3.3 Glucose as substrate ............................................................................................. 31

3.4 PST influent and effluent as substrate ................................................................... 32

3.4.1 Evaluation respirogram ......................................................................................... 32

3.4.1.1 Direct evaluation method ........................................................................................... 32 3.4.1.2 WEST ........................................................................................................................... 33

3.4.2 Dry weather conditions ......................................................................................... 35

3.4.2.1 One-‐day measurement campaign ............................................................................... 35 3.4.2.2 Weekly measurements ................................................................................................ 36

3.4.3 Wet weather conditions ........................................................................................ 37

3.4.3.1 Batch test with diluted sludge ..................................................................................... 39 3.4.3.2 Batch test with concentrated sludge .......................................................................... 40 3.4.3.3 Comparison between the different respirograms ....................................................... 42 3.4.3.4 Batch test with larger volume of wastewater ............................................................. 42 3.4.3.5 Static gas -‐ static liquid respirometry .......................................................................... 43

3.4.3.5.1 Acetate as substrate .............................................................................................. 43 3.4.3.5.2 Wastewater as substrate ...................................................................................... 44

4 CONCLUSIONS AND PERSPECTIVES .............................................................................. 47

5 REFERENCES ................................................................................................................ 49

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LIST OF ABBREVIATIONS

ASM Activated sludge model A Area of top of sedimentation basin in settling zone (m2) ATU Allylthiourea BOD Biological oxygen demand COD Chemical oxygen demand CODdeg Amount of readily biodegradable COD added to the batch reactor (mg COD/l) CS Total biodegradable COD concentration of the sample (mg COD/l) CSO Combined Sewer Overflow CSR Total biodegradable COD concentration in the reactor (mg COD/l) CTKN Total Kjeldahl nitrogen CTN Total nitrogen concentration CTP Total phosphorus concentration DO Dissolved Oxygen Δ02 Change in oxygen concentration (mg/l) due to substrate degradation ΔtS Time needed to degrade the biodegradable substrate present in sample (s) EBPR Excess biological phosphorous removal h Distance from water surface (m) h0 Depth of settling zone in sedimentation basin (m)

hS Height of particle from bottom of sedimentation basin at position entering settling zone (m)

IUWS Integral urban water system IWA International Water Association kLa The oxygen transfer coefficient LDO Led dissolved oxygen N.A. Not available OR Overflow rate (m3/m2.h) OUR Oxygen uptake rate OURend Endogenous oxygen uptake rate OURex Exogenous oxygen uptake rate PAO Phosphorous accumulating organism PE Person equivalent PHB Polyhydroxybutyrate PST Primary settling tank Q Wastewater flow rate (m3/h) r Distance measured from centre of sedimentation basin (m) r0 Radius of inlet zone and settling zone of sedimentation basin (m) ri Radius of inlet zone of sedimentation basin (m) rpm Revolutions per minute S Soluble S0 Initial substrate concentration (g/l)

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SA Volatile fatty acids SF Readily fermentable-‐ biodegradable organic substrate SI Inert, non-‐biodegradable soluble organics SN2 Dinitrogen SNH4 Ammonium-‐ and ammonia-‐nitrogen SNO3 Nitrate-‐ and nitrite-‐nitrogen SO Dissolved oxygen concentration (mg/l) SO,eq Saturated steady oxygen level (mg/l) SO,t0 Dissolved oxygen concentration of the solution before aeration is restarted

(mg/l) SPO4 Soluble inorganic phosphorus Ss Soluble readily biodegradable substrate STKN Soluble Kjeldahl nitrogen STP Soluble phosphorus t Settling time (h) τ Hydraulic detention time of sedimentation basin (h) TSS Total suspended solids v0 Terminal settling velocity (m/h) vc Particle settling velocity (m/h) vf Fluid velocity (m/h) VFA Volatile fatty acids VR Volume of the batch reactor (l) vS Particle settling velocity smaller than vc (m/h) VWW Volume of the wastewater used in the experiment (l) WDD Waterboard de Dommel WEST World-‐wide Engine for Simulation, Training and automation WFD Water Framework Directive WWTP Wastewater Treatment Plant X Particulate X0 Initial biomass concentration (g/l) XAUT Nitrifying, autotrophic biomass XH Heterotrophic biomass XI Particulate organics XMeP Metal-‐phosphate XPAO Phosphorus accumulating organisms XPHA Poly-‐hydroxy-‐alkanoate XPP Polyphosphate Xs Slowly biodegradable substrate XTKN Particulate Kjeldahl nitrogen XTP Particulate phosphorus YH Heterotrophic yield coefficient (mg cell COD/mg COD)

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SUMMARY

This work focuses on the role of the primary settling tank (PST) in wastewater treatment. The fact that the PST changes the wastewater fractions during the sedimentation process is often overlooked. However, this is a very important aspect for the determination of the organic loading that has to be treated in the succeeding biological treatment process. This thesis concentrates on respirometric measurements to characterize the different COD fractions of the wastewater. First of all, ‘flowing gas -‐ static liquid’ respirometric batch measurements were performed with acetate and glucose as substrate. By dosing a known amount of readily biodegradable COD to the batch reactor, the results obtained with the respirometer could be validated. For both substrates, the concentration of readily biodegradable substrate could not be totally recovered from the respirogram. This possibly suggests that a higher yield value than the default value of 0.67 g COD/g COD has to be used for the calculations. Calculation of the yield from the obtained respirograms gives a value of 0.80 g COD/g COD and 0.91 g COD/g COD for acetate and glucose respectively. This possibly suggests the occurrence of storage, however no storage tail was observed. This could indicate the occurrence of both growth and storage processes simultaneously. Secondly, respirometric measurements were performed on polluted wastewater sampled during dry weather conditions. Results of the one-‐day measurement campaign show that the PST reduces the biodegradable COD load, as expected. However, the results of the weekly measurement campaigns show the opposite effect, namely a higher biodegradable COD load after primary settling. This could be caused by short-‐circuiting or improper sludge withdrawal. Further investigation is needed to get more insight on the impact and influence of the primary settler in wastewater treatment. Moreover, simulation experiments in WEST were performed to mimic the respirometric profiles obtained after addition of wastewater to the batch reactor. It can be concluded that simulation of the experimental data is possible. Finally, respirometric measurements were performed on dilute wastewater sampled during wet weather conditions. The ‘flowing gas -‐ static liquid’ respirometric protocol seemed not suitable for the determination of the biodegradable COD concentration in the wastewater samples. Changing the initial substrate to biomass ratio did not yield significant improvement. Finally another respirometric principle, namely ‘static gas -‐ static liquid’ respirometry was performed. First, this method was validated by adding a known amount of readily biodegradable acetate. Parameter estimation experiments in WEST yielded the best results. However, the estimated results underestimate the actual dosed COD concentration. This possibly indicates the occurrence of storage. However, this approach seems not useful for the determination of the biodegradable COD concentration in wastewater due to the presence of slowly biodegradable substrate (XS). The XS fraction was probably not completely degraded before a new sample was dosed to the activated sludge. Therefore the activated sludge was not yet in the endogenous state. However, endogenous conditions of activated sludge in the beginning of each measurement cycle are crucial for a correct determination of the biodegradable substrate present in a dosed sample.

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SAMENVATTING

Dit eindwerk bestudeert de rol van de primaire bezinkingstank in het afvalwaterzuiveringsproces. Er wordt vaak geen rekening gehouden met de invloed van de primaire bezinkingstank op de verschillende biodegradeerbare fracties in het afvalwater. Dit is echter heel belangrijk voor de bepaling van de organische belasting die in het verdere biologische zuiveringsproces moet behandeld worden. Dit eindwerk richt zich op de respirometrische karakterisatie van de verschillende CZV (chemisch zuurstof verbruik) fracties van het afvalwater. Eerst en vooral, werden ‘flowing gas -‐ static liquid’ respirometrische metingen uitgevoerd met acetaat en glucose als substraat. Door een gekende hoeveelheid van deze snel afbreekbare stoffen toe te voegen aan het reactorvat, kunnen de resultaten die verkregen worden met de respirometer gevalideerd worden. Na afleiding van de snel afbreekbare substraat (SS) concentratie uit het respirogram werd vastgesteld dat de berekende waarden lager waren dan de werkelijk gedoseerde concentratie. Een mogelijke verklaring hiervoor is dat er bij de berekeningen van de SS concentratie een hogere heterotrofe opbrengstcoëfficiënt (YH) dan de standaardwaarde (0.67 g CZV/g CZV) moet gebruikt worden. Na afleiding van de YH uit de respirogrammen, werd voor acetaat en glucose een waarde van respectievelijk 0.80 g CZV/g CZV en 0.91 g CZV/g CZV bekomen. Deze hoge waarden kunnen wijzen op de vorming en omzetting van reservestoffen, hoewel dit niet duidelijk zichtbaar was in het respirogram. Er was namelijk geen typische opslag-‐‘staart’ te zien. Dit kan wijzen op het feit dat de opslag van reservestoffen en de groei aan biomassa tegelijkertijd plaatsvinden en niet kunnen onderscheiden worden in het respirogram. Vervolgens werden respirometrische metingen uitgevoerd met afvalwater, bemonsterd tijdens droog weer, als substraat. Uit de resultaten van de eendaagse meetcampagne blijkt dat de primaire bezinkingstank, zoals verwacht, de organische belasting reduceert, niettegenstaande de resultaten van de wekelijkse meetcampagnes het tegenovergestelde beweren. Uit deze data kan afgeleid worden dat de organische belasting na de primaire bezinkingstank groter is. Dit kan veroorzaakt worden door kortsluitstromen en onvoldoende verwijdering van het geaccumuleerde slib in de tank. Om meer inzicht te verkrijgen in de rol van de primaire bezinkingstank in het afvalwaterzuiveringsproces, moet bijkomend onderzoek uitgevoerd worden. Daarnaast werden simulatie-‐experimenten uitgevoerd in WEST om de zuurstofprofielen die verkregen werden na dosering van de afvalwaterstalen na te bootsen. Hieruit kon besloten worden dat simulatie van de experimentele data mogelijk was. Tenslotte werden metingen uitgevoerd met verdund afvalwater, bemonsterd tijdens regenweer, als substraat. De ‘flowing gas -‐ static liquid’ methode lijkt echter niet geschikt voor de bepaling van de concentratie van het biologisch afbreekbaar substraat in sterk verdund afvalwater. Het aanpassen van de initiële substraat-‐biomassa verhouding, leverde geen betere resultaten op. Daarnaast werden experimenten uitgevoerd volgens het ‘static gas -‐ static liquid” principe. Deze methode werd eerst gevalideerd door een gekende hoeveelheid acetaat te doseren. Parameterschatting in WEST leverde de beste resultaten op, niettegenstaande telkens een lagere waarde dan de werkelijk gedoseerde concentratie verkregen werd. Dit kan wijzen op de vorming en omzetting van reservestoffen. Deze methode lijkt echter ook niet geschikt voor de bepaling van de

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biodegradeerbare substraat concentratie in afvalwater door de aanwezigheid van traag afbreekbaar substraat (XS). Deze XS-‐fractie was waarschijnlijk niet volledig afgebroken door de micro-‐organismen vooraleer een nieuw staal werd gedoseerd aan het reactorvat. Hierdoor waren de micro-‐organismen in het actief slib nog niet in de endogene respiratiefase. Voor een correcte bepaling van de biodegradeerbare substraat concentratie is het nochtans van cruciaal belang dat de micro-‐organismen in endogene toestand zijn voordat nieuw substraat wordt toegevoegd.

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INTRODUCTION

Wastewater treatment can be defined as the manipulation of water from various sources to remove pollutants or reduce them to an acceptable level. In this way, a water quality that meets specified standards set by a regulatory agency is obtained (Crittenden et al., 2005). Over the years, wastewater engineering has progressed from collection and open dumping to collection and treatment prior to reuse. Nowadays, the activated sludge process has been applied worldwide in wastewater treatment plants. In this biological process wastewater is mixed with a concentrated suspension of microorganisms (the activated sludge). These organisms purify the wastewater by degrading the pollutants. Since several decades, activated sludge models (ASMs) have been developed to simulate these processes. Since 2007, a close collaboration was set up between Waterboard De Dommel (WDD) and Ghent University (BIOMATH) to model the Wastewater Treatment Plant (WWTP) of Eindhoven. This WWTP is the largest treatment plant of WDD and the third largest treatment plant of the Netherlands with a treatment capacity of 750,000 Person Equivalent (PE). The WWTP discharges effluent into the Dommel, a relatively small and sensitive river flowing through Eindhoven (The Netherlands). The river runs from the Belgian border (South) into the river Meuse (North). The WWTP of Eindhoven treats the wastewater of 10 municipalities. Under conditions of heavy rainfall, overflows as a result of combining sewage and rainfall water occur because the maximum capacity of the combined sewer system is reached. Approximately 200 combined sewer overflows (CSO) are situated along the Dommel. Due to the discharge of effluent from the WWTP and the CSOs, the Dommel does not meet the requirements set by the Water Frame Directive (WFD) (2000/60/EC). This directive was implemented in the year 2000 and aims to obtain a good ecological and chemical status of all surface water by 2015 in all European member states (Amerlinck et al., 2013). To meet the requirements, WDD set up a research project two years ago, named KALLISTO (Benedetti et al., 2013). The purpose of this project is a smart improvement of the surface water quality of the river Dommel in a cost-‐effective manner. The focus is to avoid oxygen dips and ammonia peaks caused by combined discharges of the biologically treated WWTP effluent, a rainwater settling tank at the WWTP and over 200 CSOs within the Eindhoven area. By monitoring, modelling and controlling water flows and pollutions in combination with adequate technical and infrastructural measures, WDD tries to meet the goals of the project (Amerlinck et al., 2013; Benedetti et al., 2013; Cierkens et al., 2012). With the aid of the WWTP model of Eindhoven the effects of proposed measures on the effluent quality and operation of the total system can be evaluated. This model has been integrated within a model of the integral urban water system (IUWS) of Eindhoven. It is this IUWS model that the WDD uses for the global optimization (Amerlinck et al., 2013; Benedetti et al., 2013; Cierkens et al., 2012). The model of the WWTP of Eindhoven is composed of different submodels of all subunits in the WWTP (Cierkens et al., 2012). This thesis will focus on the role of the primary settling tank (PST) in wastewater treatment. Primary settling has often been neglected, although previous studies showed that typical wastewater ratios, like biodegradable to unbiodegradable ratio, are modified by primary treatment (Bachis et al., 2014). In order to improve the WWTP model special attention needs to be given to the primary

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sedimentation tanks because the current models are not able to describe system behavior. To simulate the different processes, the wastewater is divided into several fractions, which requires an intensive wastewater characterisation. Objectives The objective of this thesis is to characterize the wastewater of primary settlers in view of improving the WWTP model of Eindhoven under different weather conditions (dry and rain weather). This thesis focuses on the biological characterisation of the different COD fractions of the wastewater based on respirometric analysis. The influence of primary settlers on the wastewater COD fractions is investigated by comparing these fractions in inlet and outlet samples taken from primary settlers. Special attention will be given to the respirometric analysis of wastewater sampled during wet weather conditions. Outline First of all, a literature review is given in chapter 1. The first section deals with the principles and different types of sedimentation. The general layout of a sedimentation tank is discussed, including the different design considerations. The second part gives an overview of the activated sludge models. Special attention is given to the ASM2d model, which serves as a basis for the WWTP model for the biological processes. In the last section, the principle of respirometry is explained and an overview of different methodologies is given. In the second part, the different materials and methods used during this thesis are described. First of all, a description is given of the layout of the different WWTPs where measurements campaigns took place. Then an overview of the respirometric protocol is presented, including a description of the methods used to obtain the different COD fractions. Finally, the modelling software is introduced. In the third part, the obtained results are presented. Firstly, the applied method for evaluation of the respirograms is discussed. Thereafter the respirometric measurements of acetate and glucose are interpreted. In the next section, the measurements of wastewater of real full-‐scale WWTPs are presented. A distinction is made between the results obtained for wastewater sampled during dry weather conditions and wet weather conditions. First of all, the results of the wastewater sampled during dry weather conditions are discussed. The different COD wastewater fractions of the influent and effluent of the PST are illustrated and compared. Thereafter, the different efforts to characterize the dilute wastewater sampled during wet weather conditions are presented. The ratio of initial substrate to initial biomass is adapted and a ‘static gas -‐ static liquid’ approach is applied. Finally, in the last part the general conclusions that can be drawn from the results are presented. Moreover, some suggestions and ideas for further research are given.

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1 LITERATURE REVIEW

1.1 Primary sedimentation

Primary sedimentation is a preliminary step in the further processing of the wastewater. Some WWTPs use mechanically cleaned sedimentation tanks of standardized circular or rectangular design. The primary settling tanks are designed to reduce the suspended solids content by removing the readily settleable solids and floating material. Approximately 50 to 70% of the suspended solids and 25 to 40% of the biological oxygen demand (BOD) are removed. This helps to reduce the load on the secondary biological reactors (Metcalf and Eddy, 2003; Riffat, 2013). Rules and regulations of local control authorities, local site conditions, size of the plant and the experience and judgement of the engineer determine the type of clarifier selected. Two or more tanks should be provided in order to allow for downtime due to cleaning or maintenance and to enable continuous operation (Riffat, 2013; Tchobanoglous et al., 2003).

1.1.1 Types of sedimentation During the sedimentation process, suspended particles heavier than water are separated, by gravitational settling (Metcalf and Eddy, 2003). Wastewater consists of a wide variety of suspensions ranging from a very low concentration of nearly discrete particles to a high concentration of flocculent solids. These suspensions have different settling characteristics and are separated into four categories based on their concentration and morphology, as shown in Figure 1-‐1 (Crittenden et al., 2005; Riffat, 2013).

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Figure 1-‐1: Relationship between settling type, concentration, and flocculent nature of particles (Crittenden et al., 2005)

1) Type I: discrete particle settling

Discrete particles are those whose size, shape and specific gravity do not change with time (Peavy et al., 1985). This type of sedimentation refers to settling of discrete particles in dilute suspensions in relatively low concentrations (≤ ~ 200 mg/l). Discrete particles will not readily flocculate and settle as individual entities because of the low particle concentration. Moreover they do not significantly interact with neighbouring particles. An example of this type of settling is encountered in wastewater grit chambers and in clarification of certain industrial wastes (e.g., sand and gravel washings) (Crittenden et al., 2005; Metcalf and Eddy, 2003; Montgomery, 1985; Riffat, 2013).

2) Type II: flocculent settling

Flocculent particles are those with a tendency to flocculate as they come in contact with other particles during the sedimentation process. Flocculation is caused by two phenomena:

Water displaced from pores as particles settle and

compress Particles compact as settling proceeds

Type IV Compression

settling

Type III Hindered Or zone settling

Type I Discrete particle

settling

Particles settling without influencing other particles

Type II Flocculant settling

Differential flow paths

Flocculant particles

Particle con

centratio

n, m

g/l

1000

Discrete Flocculant Particle morphology

3000

20

0

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a) Due to presence of particles with different settling velocities, faster settling particles overtake the slowly settling particles and flocculate with them.

b) Velocity gradients in the liquid cause particles in a region of a higher velocity to flocculate with those in adjacent stream paths moving at slower velocities. However, this occurs to a lesser degree in a PST.

This leads to particles increasing in size, shape and mass, thus resulting in particles with a larger settling rate. This type of sedimentation is observed in PSTs during the removal of suspended solids, in the upper portion of secondary clarifiers and in clarifiers following coagulation-‐flocculation (Crittenden et al., 2005; Montgomery, 1985; Riffat, 2013).

3) Type III: hindered settling or zone settling

This type of settling refers to sedimentation of particles in suspensions of intermediate concentration (~ 200 mg/l -‐ 1000 mg/l). Interparticle forces tend to hinder the settling of adjacent particles by decreasing the settling velocity. This type of settling is mostly observed in secondary clarifiers following biological treatment. The influent of the PSTs is not often of sufficient particle concentration to encounter zone settling (Montgomery, 1985; Riffat, 2013).

4) Type IV: compression settling

Compression settling occurs in highly concentrated suspensions, where due to the high concentration (~ 1000 -‐ 3000 mg/l) a structure is formed and settling can occur only by compression of that structure caused by the weight of the particles. Compression settling is observed at the bottom of secondary clarifiers following activated sludge reactors and also in solid thickeners (Riffat, 2013).

1.1.2 Design of ideal sedimentation tank An ideal sedimentation tank is designed to completely remove the particles with a specified settling velocity vo. All particles with a terminal settling velocity greater than vo will be completely removed, while particles with a lower settling velocity will be fractionally removed. Let us consider an ideal circular clarifier as shown in Figure 1-‐2. The settling zone extends from radius ri to r0 and the wastewater flow rate is Q. The flow paths of two particles, P1 and P2, are illustrated, along with their horizontal and vertical components of velocity. The fluid enters the basin in the centre of the basin (inlet zone) through the settling zone and its velocity changes according to the following equation (Crittenden et al., 2005; Metcalf and Eddy, 2003):

𝑣! =𝑄

2𝜋 𝑟 − 𝑟! ℎ! (1-‐1)

where vf = fluid velocity, m/h Q = flow rate, m3/h r = distance measured from centre of basin, m ri = radius of inlet zone, m h0 = depth of settling zone, m

Figure 1-‐2 shows the flow path of particle 1, starting at the top of the inlet zone and entering the sludge zone just before the outlet zone. The settling velocity vc of particle 1 and the distance it has settled are related as follows:

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ℎ = 𝑡𝑣! =𝜋 𝑟! − 𝑟!! ℎ!

𝑄𝑣! (1-‐2)

where h = distance from water surface for particle 1 (Figure 1-‐2), m t = settling time, h vc = particle settling velocity, m/h

Discrete particles follow a parabolic path in a circular sedimentation basin. Particles with a settling velocity greater than or equal to vc will be completely removed. The settling velocity and the overflow rate are related as follows:

𝑣! =ℎ!𝜏=

ℎ!𝑄𝜋 𝑟! − 𝑟!! ℎ!

=𝑄

𝜋 𝑟! − 𝑟!!=𝑄𝐴= 𝑂𝑅 (1-‐3)

where h0 = depth of settling zone, m τ = hydraulic detention time of basin, h

Q = flow rate, m3/h r0 = radius of settling zone and inlet zone, m ri = radius of inlet zone, m

A = area of top of basin in settling zone, m2 vc = particle settling velocity, m/h

OR = overflow rate, m3/m2.h Assuming the inlet zone is homogenous, particles can enter the settling zone at any height hs. Particles with a settling velocity vs greater than or equal to the critical settling velocity vc will be completely removed irrespective of the starting height because they will reach the sludge zone before they exit the basin. Particles with a settling velocity less then vc may also be removed but their starting position is of critical importance. Particles at the top of the basin will not be removed as they will pass through the settling zone and exit in the outlet zone. On the other hand, particles starting at height hs and lower will be removed because they will enter the sludge zone before exiting the basin, as shown in Figure 1-‐2. The fraction of particles that will be removed is equal to:

𝐹𝑟𝑎𝑐𝑡𝑖𝑜𝑛 𝑜𝑓 𝑝𝑎𝑟𝑡𝑖𝑐𝑙𝑒𝑠 𝑟𝑒𝑚𝑜𝑣𝑒𝑑 =ℎ!ℎ!

=ℎ! 𝜏ℎ! 𝜏

=𝑣!𝑂𝑅

=𝑣!𝑣! (𝑣! < 𝑣!)

(1-‐4)

where hs = height of particle from bottom of tank at position entering settling zone, m

vs = particle settling velocity smaller than vc, m/h other terms are defined above (Crittenden et al., 2005; Metcalf and Eddy, 2003; Riffat, 2013).

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Figure 1-‐2: Analysis of particle settling in an ideal circular sedimentation tank: (a) plan view of circular sedimentation tank and (b) particle trajectory of discrete particles in settling zone of circular sedimentation tank (Crittenden et al., 2005)

1.1.3 Circular tanks Conventional primary sedimentation tanks used in wastewater treatment are of rectangular, circular, or square configuration. Only circular tanks will be discussed because the WWTPs of Roeselare and Eindhoven used in this work both have circular sedimentation tanks. The design of primary clarifiers is determined by the detention time, the overflow rate and the weir loading rate (Riffat, 2013). The diameter of the circular basins is normally calculated on the basis of the overflow rate (Montgomery, 1985). As shown in Figure 1-‐3, the wastewater typically enters in the center of the basin to obtain a radial flow pattern. The inlet structure normally consists of a circular weir around the influent vertical rise pipe, which is designed to distribute the water uniformly over the entire cross section of the tank. The inlet weir provides space for energy dissipation and directs the flow downward into the depths of the settling tank where particles are removed (Metcalf and Eddy, 2003; Montgomery, 1985; Riffat, 2013). The bottom of the basin is sloped to form an inverted cone. The solids, which settle out, are removed by scrapers that move along the bottom of the tank, into a hopper located near the center. There, they are withdrawn by sludge pumps (Heynderickx and Defrancq, 2013; Metcalf and Eddy, 2003; Montgomery, 1985). The outlet structure normally consists of a single, V-‐notch weir constructed at the outside perimeter of the tank. Baffles near the outlet and surface-‐skimming devices are usually not provided, unless the influent water has problems with debris and flotable material (Montgomery, 1985).

Effluent launder (Outlet zone) Inlet zone

r0 r

ri

dh dr

Particle 1

Particle 2 vf1 vf2 vs1 = vc

vs2 Settling zone

Sludge zone

Inlet zon

e

Outlet zon

e h

h0

hS Effluent

Influent

Flow rate Q

Settling zone

Area, A

(a) (b)

8

Figure 1-‐3: Circular sedimentation tank with central feed (Riffat, 2013)

1.1.4 Sedimentation tank performance Typical performance curves for the BOD and total suspended solids (TSS) removal in primary sedimentation tank, as a function of the detention time and BOD concentration has been established. But the fact that the PST changes the wastewater characteristics through the sedimentation process is often overlooked. Larger, more slowly biodegradable suspended solids settle first, while the soluble fraction remains in the primary tank effluent. Values describing the removal efficiencies of PSTs for the different COD fractions of wastewater have rarely been reported in literature. Nevertheless the removal efficiency of PSTs is very important for the determination of the organic loading that has to be treated in the succeeding biological treatment process (Metcalf and Eddy, 2003).

1.1.5 Design considerations The efficiency of a sedimentation tank for the removal of BOD and TSS is reduced by (1) eddy currents formed by the inertia of the incoming fluid, (2) wind-‐induced circulation cells formed in uncovered tanks, (3) thermal convection currents, (4) cold or warm water leading to the formation of density currents that move along the bottom of the basin and warm water rising and flowing across the top of the tank and (5) thermal stratification in hot arid climates (6) outlet currents and (7) currents due to the movement of equipment within the basin (e.g. sludge collection mechanisms). The impact of these effects depends on the material being removed and its characteristics (Metcalf and Eddy, 2003). Due to these effects, many parameters, such as overflow rate, detention period, weir-‐loading rate, shape and dimensions of the basin, inlet and outlet structures and sludge removal systems need to be considered during the design of a sedimentation basin (Crittenden et al., 2005; Metcalf and Eddy, 2003). The most important design parameters for PSTs are (1) detention time, (2) overflow rate, and (3) weir loading rate. Sedimentation tanks are designed for average flow rate conditions. During peak flow conditions, flow rates can be 2 to 6 times the average rates. Hence the detention period gets reduced due to an increase in overflow rate and consequent overloading for a short period. Because of this, equalization tanks can be build ahead of the PSTs to provide an uniform loading and thereby maximizing the PST efficiency and reducing the load on downstream biological processes (Riffat, 2013). Overflow rate or surface loading rate: the surface loading rate represents the hydraulic loading expressed as cubic meter per square meter of surface area per day, m3/m2.d. The type of

Drive motor Walkway

Skimmer

Flow

Sludge scraper

Effluent overflow weir

Flow

Influent well

Sludge Influent

9

suspension to be separated determines the loading rate. After establishing the area of the tank, the detention period is determined by the water depth. Based on average flow, typically a detention time of 1.5 to 2.5h is achieved. It is important that overflow rates are low enough to ensure adequate performance at peak flow conditions (Metcalf and Eddy, 2003). Detention time: PSTs have normally a detention period of 1.5 to 2.5 h based on the average rate of wastewater flow. Shorter detention periods lead to less removal of suspended solids and are sometimes used for preliminary treatment ahead of biological treatment units. In colder climates, the detention time necessary to achieve an adequate efficiency is higher than in tropical climates. Lower temperatures increase the water viscosity and subsequently retard particle settling. Thus, in cold climates, safety factors need to be considered in clarifier design to ensure adequate performance (Metcalf and Eddy, 2003).

Weir loading rates: In general, there is no evidence that weir loading rates have a significant influence on the efficiency of PSTs. Typically the weir loading is 250 m3/m.d (Metcalf and Eddy, 2003).

Scour velocity: the horizontal velocities through the tank should be kept low enough to avoid the resuspension of settled particles (Metcalf and Eddy, 2003).

1.2 Activated sludge modelling

1.2.1 Introduction In 1983 the International Water Association (IWA) assigned a task group to review modelling of activated sludge systems incorporating COD removal, nitrification and denitrification. In 1987 the Activated Sludge Model No. 1 (ASM1) was introduced. A drawback of this model was that it did not include excess biological phosphorous removal (EBPR). Some microorganisms, present in the activated sludge, have the ability to take up phosphorus in excess of that required for growth (Melcer et al., 2003). Therefore in 1995 a new model ASM2 was introduced that included a new type of microorganisms, namely phosphorous accumulating organisms (PAOs). ASM2d is a minor extension of ASM2 and takes into account that PAOs can use cell internal organic storage products for denitirification while ASM2 assumes that PAOs only grow under aerobic conditions (Henze et al., 1999). In 1999 a new model of the ASM family was developed, namely ASM3. It modifies the conceptual model of ASM1 and introduces storage of organic substrates as a new process. Additionally, the death-‐decay process for heterotrophic organisms is substituted by an endogenous respiration process whereby hydrolysis is independent of the electron donor (Melcer et al., 2003).

1.2.1.1 The carbonaceous fraction

Carbonaceous material measured by BOD or COD analyses is critical to the activated-‐sludge process design. Higher concentrations of degradable COD or BOD cause (1) a larger aeration basin volume, (2) more oxygen transfer needs, and (3) greater sludge production (Metcalf and Eddy, 2003). COD was chosen as the most suitable model component for defining the carbonaceous substrates as it provides a link between electron equivalents in the organic substrate, the active biomass and the oxygen utilized (Cokgör et al., 1998). In ASM2 and ASM2d models, the total influent COD of the wastewater is divided into nine fractions. Figure 1-‐4 shows the most important influent COD fractions, which are used as component variables in activated sludge models (Pasztor et al., 2008).

10

(i) In the model, the total influent COD is divided into soluble (S) and particulate (X) components. All particulate model components must be electrically neutral, while soluble components can have an ionic charge.

(ii) The COD is further subdivided into biodegradable organic matter and non-‐biodegradable matter. The inert, non-‐biodegradable soluble organics (SI) and particulate organics (XI) cannot be degraded within the treatment plants considered. They are either part of the influent or may be produced by hydrolysis of particulate substrates (Xs) or during biomass decay (XI), respectively.

(iii) The biodegradable matter is further divided into soluble readily biodegradable substrate (Ss) and slowly biodegradable substrate (Xs). The readily biodegradable substrate was introduced as a component in ASM1 but is, in ASM2d, substituted by the sum of readily (fermentable) biodegradable organic substrate (SF) and Volatile Fatty Acids (VFA) (SA). The readily (fermentable) biodegradable organic substrate is directly available for biodegradation by heterotrophic organisms. The volatile acids are fermentation products, considered to be acetate for all stoichiometric computations where in reality an entire range of other fermentation products are possible. The slowly biodegradable substrate has a high molecular weight, is colloidal or particulate and can only be degraded after external hydrolysis.

(iv) Finally, the heterogeneity of the biomass is expressed by three kinds of organisms: the nitrifying, autotrophic biomass (XAUT), the heterotrophic biomass (XH) and the phosphorus accumulating organisms (XPAO). The nitrifiers are responsible for nitrification by oxidizing ammonia-‐ and ammonium nitrogen (SNH4) directly to nitrate (SNO3). The heterotrophs hydrolyse particulate substrates Xs and can use all degradable organic substrates under all relevant environmental conditions. The phosphorus accumulating organisms stands for the ‘true’ biomass and do not include the cell internal storage products polyphosphate (XPP) and poly-‐hydroxy-‐alkanoate (XPHA). It is assumed that these organisms grow in anoxic and aerobic conditions.

Summarising, The total COD balance in the model ASM2d consists of the following components (Henze et al., 1995, 1999):

𝐶𝑂𝐷 !"! = 𝑆! + 𝑆! + 𝑆! + 𝑋! + 𝑋! + 𝑋! + 𝑋!"# + 𝑋!"# + 𝑋!"# (1-‐5)

11

Figure 1-‐4: Influent COD fractions in ASM models (Henze et al., 1999; Pasztor et al., 2008)

1.2.1.2 The Nitrogenous fraction

In ASM2 it is stated that there is in general no need to characterize the nitrogen fractions in as much detail as for organic matter. One reason for this is that the major part of the nitrogen in wastewater is present as ammonia, which has no coupling to the organic components. For the organic part of the nitrogen, it is sufficient to use fixed nitrogen fractions for the various COD components (Henze et al., 1995). The autotrophic oxygen demand and the required denitrification capacity are determined by the amount of nitrogen available for oxidation (Roeleveld and van Loosdrecht, 2002). The total nitrogen concentration (CTN) in municipal wastewater is the sum of the total Kjeldahl nitrogen (CTKN) and nitrate-‐ and nitrite-‐nitrogen (SNO3):

𝐶!" = 𝐶!"# + 𝑆!"! = 𝑋!"# + 𝑆!"# + 𝑆!"! (1-‐6) The influent TKN consists of ammonia and organic nitrogen (Metcalf and Eddy, 2003). Equation 1-‐6 shows that the total Kjeldahl nitrogen can be written as the sum of the particulate Kjeldahl nitrogen (XTKN) and the soluble Kjeldahl nitrogen (STKN). The particulate Kjeldahl nitrogen is all the nitrogen bound to the organic particulate fractions, except for XPHA (Henze et al., 1995). The soluble Kjeldahl nitrogen is dominated by ammonium-‐nitrogen, SNH4, which is readily available for bacterial synthesis and nitrification (Metcalf and Eddy, 2003). 1.2.1.3 The phosphorus fraction

As for the nitrogen fraction, there is no need to characterize the phosphorus fraction in as much detail as for organic matter. It is often sufficient to couple a fixed phosphorus fraction to the various COD fractions. The total phosphorus concentration (CTP) in raw municipal wastewater is the sum of the particulate phosphorus (XTP) and the soluble phosphorus (STP):

𝐶!" = 𝑋!" + 𝑆!" (1-‐7)

Soluble non-‐ biodegradable

SI

Particulate non-‐ biodegradable

XI

Readily Biodegradable

Ss

Slowly Biodegradable

Xs

Total influent COD

Biodegradable COD Biomass COD Non-‐ biodegradable COD

Autotrophic XAUT

Heterotrophic

XHET

P-‐accumulating

XPAO

Non VFA SF

VFA SA

= In all ASM models

= In ASM2d

12

The particulate phosphorus includes inorganic metal phosphorus (XMeP) and organic phosphorus (Henze et al., 1995). The metal-‐phosphate, MePO4 (XMeP) results from binding phosphorus to the metal-‐hydroxides. It is assumed that this component is composed of FePO4, for all stoichiometric computations (Henze et al., 1999). The soluble phosphorus consists of soluble inorganic phosphorus (SPO4) and soluble organic phosphorus.

1.2.2 Processes in ASM2d

1.2.2.1 Hydrolysis processes

Slowly biodegradable substrates (XS) cannot be utilized directly by microorganisms and must be converted to fermentable, readily biodegradable matter (SF). This occurs by means of external enzymatic reactions, which are called hydrolysis processes and can only be catalysed by heterotrophic organisms. It is assumed that due to hydrolysis a small fraction of inert organic material SI is released. Typically hydrolysis processes occur at the surface in close contact between the organisms, which provide the hydrolytic enzymes, and the slowly biodegradable substrates. There is experimental evidence that ‘hydrolysis’ reactions depend on the available electron acceptors. Three hydrolysis processes are considered in ASM2d:

(i) Aerobic hydrolysis of slowly biodegradable substrate when there is enough dissolved oxygen present

(ii) Anoxic hydrolysis of slowly biodegradable substrate under anoxic conditions when there is little dissolved oxygen and enough nitrate present. This process is typically slower than aerobic hydrolysis.

(iii) Anaerobic hydrolysis of slowly biodegradable substrate under anaerobic conditions when there is no dissolved oxygen and little nitrate present. This process is slower than aerobic hydrolysis.

Because of the assumption that the fraction of nitrogen in the slowly biodegradable matter is constant, there is no need to include a separate hydrolysis process for the particulate organic nitrogen as was the case in ASM1 (Henze et al., 1999).

1.2.2.2 Processes of facultative heterotrophic organisms

Heterotrophic organisms XH are responsible for the hydrolysis of slowly biodegradable substrate (XS), the aerobic degradation of fermentable organic substrates (SF) and of fermentation products (SA), anoxic oxidation of SF and SA, denitrification and anaerobic fermentation of SF to SA. Finally, the heterotrophic organisms undergo decay and lysis. The aerobic growth of heterotrophic organisms on SF and on SA requires oxygen, nutrients; SNH4 and SPO4, and possibly alkalinity; SALK. During the aerobic growth, the heterotrophs produce suspended solids; XTSS. The anoxic growth of the heterotrophs on SF and SA require nitrate, SNO3, as the electron acceptor. It is assumed that all nitrate, SNO3, is reduced to dinitrogen, SN2. During the fermentation process readily fermentable biodegradable substrates, SF are transformed into negatively charged fermentation products SA, and therefore alkalinity, SALK is used to keep the electrical continuity. Finally the lysis of the heterotrophic organisms is the sum of all decay and loss processes, like endogenous respiration, lysis, predation, etc.. The electron acceptor determines its rate (Henze et al., 1999).

13

1.2.2.3 Processes of phosphate accumulating organisms

The phosphate accumulating organisms (PAO) accumulate phosphorus in the form of poly-‐phosphate XPP. In ASM2, it was assumed that PAO could not denitrify but experimental evidence has shown that some of them can denitrify. This denitrification capacity of the PAO had been implemented in the ASM2d model but there is not any consideration of the importance of glycogen as cell internal organic storage material. The PAO can grow under aerobic (SO2 > 0) as well as anoxic (S02 ≈ 0, SNO3 > 0) conditions. It is assumed that the PAO only grow on cell internal stored organic materials, XPHA. These XPHA are stored using the energy, which becomes available from the hydrolysis of poly-‐phosphate, XPP. This process proceeds under anaerobic conditions, but has also been reported under aerobic and anoxic conditions. Therefore the model does not contain inhibition terms for SO2 and SNO3. The PAO gain energy from the aerobic or anoxic respiration of XPHA to store ortho-‐phosphate, SPO4, in the form of cell internal poly-‐phosphates, XPP. When the phosphorus content of the PAO becomes too high, the storage of XPP stops. This is modelled by using an inhibition term of XPP storage, which becomes active as the ratio XPP/XPAO comes close to the maximum allowable value of KMAX. It is assumed that PAO grow in aerobic and anoxic conditions only on cell internal organic storage products XPHA. Moreover it is considered that these organisms consume ortho-‐phosphate, SPO4, as a nutrient for the production of biomass since phosphorus is continuously released by the lysis of XPP. It is known that PAO may also grow on soluble substrates (e.g. SA), but it is unlikely that these substrates become available under aerobic or anoxic conditions in a biological nutrient removal plant. That is why in the model this possibility is neglected. Lysis of PAO entails death, endogenous respiration and maintenance and results in the loss or decay of all fractions of PAO; the organisms itself XPAO, the poly-‐phosphate, XPP and the cell internal organic storage products, XPHA. These three lysis processes are modelled as first-‐order reactions relative to the component, which is lost. The cell internal storage products are assumed to decay to ortho-‐phosphate, SPO4 and fermentation products SA (Henze et al., 1999).

1.2.2.4 Nitrification processes

Nitrification is modelled as a one-‐step process, from ammonium SNH4 directly to nitrate SNO3. The intermediate component, nitrite, is not included in the ASM2d model. The nitrifying organisms only grow under aerobic conditions. Because of the production of nitrate, the alkalinity reduces. The autotrophic organisms can also take up phosphorus into the biomass. Lysis of nitrifying organisms is the sum of all decay processes and is modelled in analogy to the process of lysis of heterotrophic organisms. The decay products of lysis (XS and ultimately SF) are only available for heterotrophic organisms. Therefore, the endogenous respiration of nitrifiers becomes manifest as an increased growth and oxygen consumption of heterotrophs (Henze et al., 1999).

1.2.2.5 Chemical precipitation of phosphates

Chemical precipitation of phosphorus can be caused by the reaction between metals, which are naturally present in wastewater, and soluble ortho-‐phosphate, SPO4. A very common process for phosphorus removal is the simultaneous precipitation of phosphorus via the addition of iron or aluminium salts, sometimes in combination with biological phosphorus removal in cases where the

14

carbon to phosphorus ratio is unfavourably small. It is assumed that precipitation and redissolution are reverse processes, which are in equilibrium at steady state according to:

𝑋!"#$ + 𝑆!"! ↔ 𝑋!"# The assumption is made that XMeOH and XMeP are composed of ferric hydroxide, Fe(OH)3, and ferric-‐phosphate, FePO4, respectively (Henze et al., 1999).

1.3 Wastewater characterisation

Due to the development of activated sludge models (ASMs), there is a much better understanding of different treatment processes but it requires a more intensive wastewater characterisation (Roeleveld and van Loosdrecht, 2002). These ASMs incorporate mathematical expressions that represent the biological interactions, based on hypotheses proposed for the biological processes occurring within the system (Melcer et al., 2003). The wastewater COD is divided into biodegradable and non-‐biodegradable fractions and further subdivided according to their solubility or degradation rate (S and X). A great variety of characterisation methods were developed since the division between the different fractions is somehow arbitrary (Roeleveld and van Loosdrecht, 2002). The two most commonly used processes are the biological and physical-‐chemical methods (Pasztor et al., 2008). In practice, often a combined approach is used to get an estimation of the concentrations of all components. In this thesis, the focus is on biological characterisation of the wastewater, so only biological methods will be discussed.

1.3.1 Biological characterisation In the biological methods, the fractionation of the organic matter is based on its rate of degradation (Henze, 1992). These biological methods can mainly characterise the biodegradable components and the microbial biomass in the wastewater. The non-‐biodegradable components can be determined by a combination of physical-‐chemical and biological tests (Petersen, 2000). The biological characterisation method measures the biomass response during substrate degradation in either a continuous flow or batch type experiment (Pasztor et al., 2008). The biomass response can be monitored by recording the utilization rate of the dissolved oxygen or nitrate, which is closely related to the quality and quantity of available substrate in the system (Spanjers, 1993). A method that is often used is respirometry and is defined as the measurement and interpretation of the respiration rate of activated sludge under well-‐defined experimental conditions. The respiration rate is expressed as the amount of oxygen per unit of volume and time that is consumed by the microorganisms. A WWTP has to control two important biochemical processes: biomass growth and substrate consumption. The fact that respiration rate is associated to these two processes, makes respirometry a valuable method for controlling, modelling and monitoring the activated sludge process (Spanjers, 1996). Respirometry can provide information about the specific activity of (certain fractions of) the biomass, the composition of the wastewater (concentration, fractionation and toxicity) and interactions of the biomass with the wastewater components (Copp et al., 2002). Therefore different experimental protocols have been developed to obtain information about these parameters. For the characterisation of the biodegradable COD fraction in wastewater, respirometry is considered as the reference method (Fall et al., 2011). Respirometers are devices that measure the ‘respiration’ of living organisms (Young and Cowan, 2004) and are used to measure and interpret the oxygen uptake rate of activated sludge (Gernaey et

15

al., 2001). All types of respirometers consist of a reactor in which activated sludge from the WWTP and, optionally, wastewater or a specific substrate are brought together and a device measuring the biomass response during substrate degradation. The biomass response can be monitored by measuring the uptake of oxygen, ammonium and nitrate or the formation of nitrate, carbon dioxide, methane, etc.. This thesis will focus on measuring the rate at which the biomass takes up oxygen. Respirometers can be classified into eight basic principles according to the phase where oxygen is measured (gas or liquid) and whether or not there is an exchange of these phases with the environment (flowing or static). The liquid phase contains biomass and dissolved oxygen that is transported to the microorganisms, while the gas phase contains oxygen, which is transferred to the liquid phase. Mostly the oxygen is measured in the liquid phase with an electrochemical DO sensor (Barnett et al., 1998). In literature, a lot of batch and flow-‐through respirometric protocols have been proposed (Chudoba et al., 1992; Ekama et al., 1986; Kappeler and Gujer, 1992; Spanjers and Vanrolleghem, 1995; Spérandio and Etienne, 2000; Wentzel et al., 1995). The research of Dold et al. (1980) provided the first information that directed to the discrimination between readily and slowly biodegradable COD. One of the first methods, proposed by Ekama et al. (1986), is the flow-‐through activated sludge method. The principle is based on the evaluation of the oxygen uptake rate in an activated sludge process operated under a daily cyclic square-‐wave load pattern. Drawbacks of this method are the cost and difficulty of operation. For procedures using batch experiments, activated sludge acclimatised to the wastewater has to be used. Ekama et al. (1986) recommended two batch methods for determining the readily biodegradable COD (SS) in the influent: (1) the aerobic batch reactor method and (2) the anoxic batch reactor method. A lot of other batch experiment protocols have been recommended where a certain amount of activated sludge is mixed with a known volume of substrate and the oxygen uptake rate is analysed. Figure 1-‐5 shows the typical set-‐up and principle of a respirometer using an aerated batch reactor.

Figure 1-‐5 illustration of the (a) set-‐up (Kappeler and Gujer, 1992) and (b) principle of a respirometer (Nopens, 2010) using an aerated batch reactor

These methods monitor the oxygen uptake rate versus time and allow the calculation of some model parameters, such as maximum respiration rates, saturation coefficients, concentrations of the components in the added sample, yield coefficients, etc.. (Brouwer et al., 1998; Cokgör et al., 1998; Kappeler and Gujer, 1992; Spanjers et al., 1999; Wentzel et al., 1995). A difficulty for the batch experiments is that the quality and the kind of kinetic information is influenced by the ratio of the

(a) (b)

DO

Time

Mixer

DO sensor Temperature sensor

Aeration stone Water bath

16

initial substrate concentration to initial biomass concentration (S0/X0). This ratio determines whether or not cell multiplication will take place during exogenous substrate removal. At a low S0/X0 ratio, a relatively high amount of biomass is supplied with a low quantity of substrate. Then the initial energy level is low as well, and thus insufficient for different synthetic reactions, which take place during cell replication (e.g. enzyme, protein and nucleic acids syntheses). Under these conditions, the biomass increases mostly due to the synthesis of storage polymers. Consequently, the increase in cell mass reflects only the increase in molecular polymer content (Chudoba et al., 1992; Ekama et al., 1986; Kappeler and Gujer, 1992). A low S0/X0 ratio leads to short-‐term experiments. A high S0/X0 ratio allows the growth of microorganisms leading to a difficult interpretation of the multicomponent kinetics (Chudoba et al., 1992). By a trial and error procedure, the optimal S0/X0 ratio can be determined and depends on the origin and characteristics of the wastewater and biomass (Chudoba et al., 1992; Ekama et al., 1986; Kappeler and Gujer, 1992; Xu and Hultman, 1996). This thesis concentrates on getting more insight into the effect of primary settling tanks on the different wastewater fractions. Table 1-‐1 and Table 1-‐2 give an overview of the COD fractions of raw and primary (settled) wastewater determined by respirometric methods found in literature. According to the data, the ratio of readily biodegradable substrate to the total wastewater COD ranges between 5.0 -‐ 27.0% in raw wastewater and 7.0 -‐ 31.8% in primary wastewater. The ratio of slowly biodegradable substrate to the total wastewater COD ranges between 13.0 -‐ 58.0% in raw wastewater and 4.0 -‐ 43.0% in primary wastewater. The data show much variability and from this it can be concluded that a further investigation into the impact of primary settling on the wastewater COD fractions is needed. Table 1-‐1: Overview of readily biodegradable COD fractions (SS) and slowly biodegradable COD fractions (XS) in raw wastewater.

Country, region

Type of wastewater

Treatment capacity (m3/d)

SS/CODTOT (%)

XS/CODTOT (%) Reference

Pinedo, Spain Domestic and industrial 119,264 27.0 N.A. Gatti et al.

(2010)

Abaran, Spain Domestic and industrial 2694 17.0 N.A. Gatti et al.

(2010) Monterrey, Mexico

Domestic and industrial 432,000 5.0 N.A. Fall et al.

(2011) Istanbul, Turkey Domestic 319,680 9.0 N.A. Cokgör et al.

(1998)

Switzerland Domestic and industrial Pilot plant 9.0 58.0 Kappeler and

Gujer (1992) Lundtofte, Denmark N.A. N.A. 20.0 40.0 Henze (1992)

Quyang, China Domestic 75,000 6.9 − 10.3 23.9 -‐ 37.0 Zhou et al. (2008)

Bailonggang, China

Domestic and industrial 2,000,000 9.0 -‐ 13.8 16.1 -‐ 37.3 Zhou et al.

(2008) The

Netherlands Industrial and domestic N.A. 26.0 28.0 Roeleveld and

van

17

Loosdrecht (2002)

Hungary Industrial and domestic N.A. 21.9 49.8 Pasztor et al.

(2008)

Sweden N.A. Pilot plant 27.0 33.0 Xu and Hultman (1996)

South Africa N.A. N.A. 20.0 13.0 Ekama et al. (1986)

Istanbul Domestic N.A. 10.0 20.0 Orhon et al. (2002)

Table 1-‐2 Overview of readily biodegradable COD fractions (SS) and slowly biodegradable COD fractions (XS) in primary wastewater

WWTP Type of wastewater

Treatment capacity (m3/day)

SS/CODTOT (%)

XS/CODTOT (%) Reference

Monterrey, Mexico

Domestic and industrial 432,000 7.0 N.A. Fall et al.

(2011)

Denmark N.A. N.A. 24.3 N.A. Pasztor et al. (2008)

Switzerland N.A. N.A. 31.8 N.A. Pasztor et al. (2008)

Hungary N.A. N.A. 28.6 N.A. Pasztor et al. (2008)

Lundtofte, Denmark N.A. N.A. 29.0 43.0 Henze (1992)

South-‐Africa N.A. N.A. 28.0 4.0 Ekama et al. (1986)

Istanbul Domestic N.A. 19.0 38.0 Orhon et al. (2002)

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2 MATERIAL AND METHODS

2.1 Measurement campaigns at full-‐scale WWTPs

2.1.1 WWTP of Roeselare (Belgium) The WWTP of Roeselare was established in 1996 and has a treatment capacity of 65,700 PE. As shown in Figure 2-‐1, the incoming wastewater first passes through screens to remove the large objects like, plastics, cans, etc.. Subsequently, the water is treated in an aerated sand trap to remove sand and gravel by sedimentation. The effluent of the sand trap is divided over two parallel primary sedimentation tanks, to partly remove suspended solids. After this treatment step the water flows to a contact tank, after which it continues to two activated sludge tanks where nitrification and denitrification occurs. Thereafter the mixed liquor is distributed to four secondary sedimentation tanks where sedimentation of the sludge happens. The sludge is withdrawn for dewatering to reach a dry matter content of 25%. Finally the dewatered sludge is either burned in an incinerator in Bruges or is further dried.

Figure 2-‐1: Layout of the WWTP of Roeselare, Belgium

Every week on Monday morning, samples of wastewater were taken at the inlet and outlet of the primary sedimentation tank and sludge samples were obtained from the biological compartment. On March 12th, 2014 a one-‐day measuring campaign was carried out. For this, two automatic samplers with built-‐in refrigerator (4°C) were used on-‐site the treatment plant. One sampler was placed before the PST and the other after the PST. Composite time samples were taken. Every 2 minutes 100 ml wastewater was sampled during 4 hours. These samples were taken to the lab and stored at 4°C.

2.1.2 WWTP of Eindhoven (The Netherlands) The WWTP of Eindhoven was built in 1960 and has become the largest treatment plant of Waterboard De Dommel and the third largest in The Netherlands. It has a treatment capacity of

1. Screw pumps 2. Screens 3. Sand traps 4. Equalization tanks 5. Primary

sedimentation tanks 6. Contact tank 7. Aeration tanks 8. Secondary

sedimentation tanks 9. Flow meter 10. Sludge recycle

screw pumps 11. Sludge thickeners 12. Sludge buffer tanks 13. Sludge treatment Water Recirculation Primary excess sludge Secondary excess sludge

19

750,000 PE and treats each day on average 170,000 m3, corresponding with 6,000 m3/h. The incoming wastewater is treated in three parallel lines, each consisting of a primary settler, an activated sludge tank and four secondary settlers. Each line has a maximum hydraulic load of 26,250 m3/h. In case of heavy rainfall, an extra load of 8,750 m3/h can be treated mechanically by a pre-‐settling tank before it is discharged in the River Dommel. The WWTP has a modified UCT (University of Capetown) configuration for biological removal of COD, N and P, containing biological tanks of 7 meter deep. Figure 2-‐2 illustrates the layout of one activated sludge tank, consisting of an inner ring, a middle ring and an outer ring corresponding respectively to an anaerobic tank, an anoxic tank and a partially aerated tank (Amerlinck et al., 2013). First, the mixed liquor passes through the anaerobic tank, which is a plug flow reactor with four compartments in series. Then the mixed liquor enters the anoxic middle ring and finally it passes through the partially aerated tank. Membrane plate aerators in certain locations provide the aeration, which divide the tank in a facultative aerobic/anoxic ring. There exist two different aeration packages: the ‘summer package’ and the ‘winter package’. The ‘summer package’ provides the aeration under normal dry weather conditions and is constantly active. The ‘winter package’ can be switched on during winter time and wet weather conditions when the first package is not sufficient (Amerlinck et al., 2013; Cierkens et al., 2012). Samples of activated sludge from the biological compartment, samples of wastewater at the inlet and outlet of the PST and samples of the effluent were taken at the WWTP of Eindhoven. The wastewater samples were stored in the lab at 4°C and the activated sludge was aerated overnight to reach endogenous conditions.

20

Figure 2-‐2: Schematic of a biological tank of the WWTP of Eindhoven (Amerlinck et al., 2013)

2.2 Respirometer

2.2.1 Introduction Respirometers are devices that measure the ‘respiration’ of living organisms (Young and Cowan, 2004) and are used to measure and interpret the oxygen uptake rate of activated sludge (Gernaey et al., 2001). All types of respirometers consist of a reactor in which activated sludge from the WWTP and, optionally, wastewater or a specific substrate are brought together and a device measuring the rate at which the biomass takes up oxygen. Mostly the oxygen is measured in the liquid phase with an electrochemical DO sensor (Barnett et al., 1998). The oxygen uptake rate is then calculated by making a general mass balance for oxygen over the liquid phase (Gernaey et al., 2001) and consists of two components: the endogenous oxygen uptake rate (OURend) and the exogenous oxygen uptake rate (OURex). OURend is the oxygen uptake rate related to maintenance in absence of readily biodegradable substrate while the exogenous oxygen uptake rate is the oxygen uptake needed to degrade a substrate (Petersen, 2000).

Influent

Winter Aeration Package

Inner ring

Middle ring

Outer ring

Summer Aeration Package

21

2.2.2 Experimental setup The respirometric analysis focuses on measuring the dissolved oxygen concentration and determination of the oxygen uptake rate (OUR) by preliminary establishment of the respirometer kla value. The respirometer is made up of a titrimetric and a respirometric unit. Figure 2-‐3 shows the general flow scheme of a respirometer.

Figure 2-‐3: Respirometer setup

The respirometric unit consists of a 2L double-‐glass vessel, kept at a constant temperature of 20°C by a cooling system (Lauda Alpha RA8; VWR) that pumps water through the heat-‐jacked reactors. Different results would be obtained at different temperatures, because biochemical reaction rates are temperature-‐dependent (Metcalf and Eddy, 2003). With the aid of a Led dissolved oxygen (LDO) probe (LnPro68701/12/220; Mettler Toledo, Elscolab) and pH probe (GA405-‐DXK-‐S8/120 PN: 104054287; Mettler Toledo, Elscolab) the oxygen concentration and pH can be measured on-‐line. The sludge is constantly mixed at a speed of 100 rpm and aerated with the aid of an aeration stone at a constant airflow rate. The titrimetric unit is composed of one 1L Acid mariotte bottle, one 2L base mariotte bottle, one Gilson pump (Minipuls 3; Analis) and two solenoid valves that dose the titrimetric solution to the reactor. The Gilson pump recycles around the acid solution of 1M HCl and the base solution of 1M NaOH. The solenoid valve is open when the pH in the reactor deviates more then 0.1 units from the pH set point of 7.5. Then, base or acid is dosed to the reactor. When the valves are closed, the titrimetric solution is recycled back to the corresponding mariotte bottle.

2.2.3 Experimental protocol for respirometric analysis The software used for monitoring and control of the data acquisition of the biological processes occurring in the reactor is LabView (National Instruments, USA). First the respirometer was set up as described above (2.2.2 Setup). Thereafter the pH probe and LDO probe were calibrated. These are

22

connected respectively to a pH transmitter (Knick Stratos 2401) and an oxygen transmitter (M400 Type 2). These transmitters are communicating 4-‐20 mA signals to the software program on the computer. Subsequently the acid and base dosage system was calibrated by collecting the volume of acid and base dosed during 35 subsequent pulses.

2.2.3.1 Flowing gas – static liquid

During this type of respirometric analyses the batch reactor is continuously aerated. Mixed liquor of the biological tank from the WWTP of Eindhoven (operated by ‘Waterboard de Dommel’) or Roeselare (operated by Aquafin NV) was aerated overnight until the endogenous respiration phase was reached. Then the reactor was filled with 1.9l of mixed liquor. The next step was to calculate the OUR online according to the following equation:

𝑑𝑆!𝑑𝑡

= 𝑘!𝑎 × 𝑆!,!" − 𝑆! − 𝑂𝑈𝑅 (2-‐1)

This equation includes an aeration term and a term representing the oxygen uptake rate (OUR) by the microorganisms. The OUR is the sum of the OURend and OURex, SO,eq is the equilibrium dissolved oxygen concentration, SO the measured dissolved oxygen concentration and kLa the oxygen transfer coefficient. When substrate is lacking, OURex becomes zero and only endogenous OUR is present. In this case continuous aeration allows the oxygen concentration in the reactor to reach a saturated steady oxygen level (SO,eq), representing the equilibrium between oxygen transfer and endogenous respiration. Therefore equation 2-‐1 becomes:

𝑂𝑈𝑅!"# = 𝑘!𝑎 × 𝑆!,!" − 𝑆! (2-‐2) S0,eq is determined by aerating the mixed liquor in the reactor for approximately 30 min until a stable equilibrium concentration is reached. The kLa value is determined by a dynamic gassing out method. First, the aeration is stopped until a dissolved oxygen concentration of 1.5-‐2 mg/L is reached (Bandyopadhyay and Humphrey, 2009). Then the aeration is started again and equation 2-‐1 becomes:

𝑑𝑆!𝑑𝑡

= 𝑘!𝑎 × 𝑆!,!" − 𝑆! (2-‐3)

After integrating equation 2-‐3, the following equation is obtained: ln 𝑆!,!" − 𝑆!,!" − ln (𝑆!,!" − 𝑆!,!!)

𝑡!= −𝑘!𝑎 (2-‐4)

where SO, t0 represents the DO concentration of the oxygen depleted solution before the aeration is restarted. By plotting ln(SO,eq -‐ SO,tx) versus time, kLa can be deduced as the negative slope of this curve. This parameter is very import for the evaluation of respirometric parameters. Different factors, such as gas flow, bubble size, reactor dimensions, stirring of mixed liquor (turbulence), temperature of mixed liquor, and air pressure, etc. have a major influence on kLa. Therefore the following conditions must be ensured during the determination of this parameter (Ros et al., 1988):

a. A constant airflow through the whole experiment b. A reactor with known volume and shape has to be used for all measurements c. Constant stirring must be provided d. Constant temperature of mixed liquor during the measurements

The kLa measurement is performed three times and then the average kLa value is used for further calculations. Nitrification was inhibited by adding allylthiourea (ATU) to the reactor in a concentration of 10 mg/L. The ATU solution was prepared by dissolving 2.0 g ATU in 1L of distilled

23

water and stored at 4°C. The solution was prepared every two weeks because it is only stable for two weeks. Finally, a specific volume of substrate was added to the mixed liquor and the dissolved oxygen concentrations were measured. Evaluation of the respirogram Figure 2-‐4 illustrates the typical respiration rate profile, called a respirogram, obtained after addition of wastewater to endogenous sludge during a respirometric batch test. During this procedure a known volume of raw wastewater is added to a known amount of endogenous sludge (Ekama et al., 1986; Spanjers and Vanrolleghem, 1995). The initial peak is brought about by the oxidation of readily biodegradable matter (SS), followed by one shoulder due to the utilisation of slowly degradable COD (XS).

Figure 2-‐4 OUR-‐curve obtained after addition of 0.25 l of wastewater taken before the PST into 1.9 l of mixed liquor of the WWTP of Roeselare

Readily Biodegradable substrate SS The readily biodegradable fraction is composed of small molecules, such as volatile fatty acids, carbohydrates, alcohols, peptones and amino acids that can be directly metabolized (Henze, 1992). The readily biodegradable substrate is degraded rapidly, resulting in a fast respirometric response (Vanrolleghem et al., 1999). Upon addition of wastewater, the microorganisms will start oxidizing the SS, thereby using dissolved oxygen, which results in an increase in the oxygen uptake rate (OUR). Once SS becomes depleted, the oxygen demand for aerobic respiration decreases and reaeration becomes important again. This results in an increase in DO and simultaneously a decrease in OUR until the original endogenous level is reached because all external substrate is degraded (Nopens, 2010; Orhon and Okutman, 2003; Vanrolleghem et al., 1999). As shown in Figure 2-‐4, integrating the surface under the OUR curve and above the first shoulder gives the total amount of oxygen consumed at the expense of all available readily biodegradable substrate. Only a fraction of the SS is oxidized and the remainder (the heterotrophic yield, YH) is reorganized in new cell material. The yield indicates the COD fraction that is converted to cell biomass and the fraction that is used to provide the energy needed for different synthesis reaction. This energy is released by oxidative phosphorylation and is proportional to the mass of oxygen

(1-‐YH)SS

(1-‐YH)XS

OUR

(mg/

l.h)

0

5

10

15

20

25

Time (min)0 10 20 30 40 50

24

utilised, which in turn is proportional to the COD consumed. Therefore, in order to obtain SS from respirometric measurements, knowledge of YH is necessary (Barnett et al., 1998; Petersen, 2000; Vanrolleghem et al., 1999). The yield YH is assumed to be 0.67 gCOD/gCOD (Fall et al., 2011; Kappeler and Gujer, 1992) in the performed respirometric tests. The concentration of SS initially present in the mixture of biomass and wastewater (CSR) can be calculated as follows:

𝐶!" =1

(1 − 𝑌!)𝑂𝑈𝑅 𝑑𝑡

!!"#$%

!=

∆0!1 − 𝑌!

(2-‐5)

where YH is the heterotrophic biomass yield. The endpoint tfinal of the integration interval is the time instant where SS is completely depleted and where the exogenous respiration rate for SS becomes zero. The concentration of SS in the wastewater (CS) can then easily be determined by taking into account a dilution factor:

𝐶! = 𝐶!"𝑉!𝑉!!

(2-‐6)

where VR is the volume of the wastewater and sludge in the batch reactor and VWW is the volume of wastewater added to the batch reactor (Gatti et al., 2010; Orhon and Okutman, 2003; Vanrolleghem et al., 1999). Slowly biodegradable substrate XS This fraction is composed of high-‐molecular compounds made up of soluble, colloidal and particulate COD fractions (Henze, 1992). These compounds need to be hydrolysed to low-‐ molecular compounds (SS) by extracellular enzymes of bacteria prior to utilization because they cannot pass the cell membrane as such (Pasztor et al., 2008). The degradation of these compounds results in a slower respirometric response than for SS because the hydrolysis rate is lower than the oxidation rate of SS (Petersen, 2000). Figure 2-‐4 shows a typical respirogram for raw wastewater. As explained above, the first initial peak is associated with the degradation of readily biodegradable matter. This peak is followed by a decreasing ‘tail’ due to the utilisation of slowly degradable COD. After the depletion of this fraction, the OUR returns to its original endogenous level (Nopens, 2010; Orhon and Okutman, 2003). The concentration of XS in the wastewater can be determined in a similar way as for SS, equation 2-‐6 (Kappeler and Gujer, 1992; Sollfrank and Gujer, 1991). Oxidation processes such as nitrification can occur at the same time as oxidation of organic matter. In that case, it is quite impossible to discriminate between an XS tail and the oxygen consumption related to nitrification. Therefore, a nitrification inhibitor (ATU) is added to facilitate the determination of XS (Spanjers and Vanrolleghem, 1995).

2.2.3.2 Static gas – static liquid

This type of test is performed without aeration. The mixed liquor of the biological tank from the WWTP of Eindhoven (operated by ‘Waterboard de Dommel’) or Roeselare (operated by ‘Aquafin NV’) was aerated overnight until the endogenous respiration phase was reached. 1.9 l of activated sludge in the endogenous phase was transferred to the batch reactor and aerated until a dissolved oxygen concentration of 6 -‐ 8 mg/l was reached. ATU in a concentration of 10 mg/l was added to the batch reactor to inhibit nitrification. After the aeration was stopped, the decline in oxygen

25

concentration with time due to respiration was monitored. During this type of experiment the mass balance of equation 2-‐1 becomes (Drtil et al., 1993; Gernaey et al., 2001):

𝑑𝑆!𝑑𝑡

= − 𝑂𝑈𝑅 (2-‐7)

This is a very simple equation since the aeration terms can be omitted. Figure 2-‐5 shows a typical respirogram obtained with this type of experiment. During phase I, oxygen is utilized at a constant rate (OURI) when the microorganisms in the activated sludge are in endogenous state. At a certain time point, a known volume of substrate is added to the batch reactor resulting in a temporary increase in respiration rate (OURII) due to substrate degradation (phase II). If the substrate is completely degraded and removed, the respiration returns to a value equal (OURIII), or slightly different from the original endogenous respiration rate (phase III). After the measurement of one concentration of substrate, the batch vessel is aerated again and the protocol is repeated with a new dose of substrate.

Figure 2-‐5: DO-‐profile obtained after addition of 13.6 mg of sodium acetate trihydrate to 1.9 l of mixed liquor of the WWTP of Roeselare

Evaluation of the respirogram The differential term in equation 2-‐7 can be approximated with a finite difference term and equation 2-‐7 becomes (Vanrolleghem, 2002):

∆𝑆!∆𝑡

= − 𝑂𝑈𝑅!"! = −𝑂𝑈𝑅! − 𝑂𝑈𝑅!! (2-‐8)

The concentration of biodegradable matter in the substrate (CSR) can be calculated as follows:

𝐶!" = (𝑂𝑈𝑅!! − 𝑂𝑈𝑅!)∆𝑡!

1 − 𝑌!𝑉!𝑉!!

(2-‐9)

Where OURII represents the total respiration rate and is equal to the sum of the endogenous respiration rate (OURI) and the exogenous respiration rate due to substrate degradation. The time needed to degrade the biodegradable matter present in the substrate is represented by ΔtS. VR and VWW represent respectively the total volume in the reactor and the volume of the added wastewater sample. The heterotrophic biomass yield (YH) is assumed to be 0.67 g COD/g COD (Fall et al., 2011; Kappeler and Gujer, 1992) in the performed respirometric tests.

ΔtS

Substrate

ΔS0

I

II

III

DO (m

g/l)

4

6

8

10

Time (s)0 500 1000 1500

DO-profile

26

2.3 Simulation software: WEST

The software program used for the simulation of the performed respirometric experiments is WEST. WEST stands for World-‐wide Engine for Simulation, Training and automation and is developed by the company MOSTforWATER (Kortrijk, Belgium) in collaboration with BIOMATH (Ghent University). For the simulation experiments, the ASM1 model was selected. To fit this model with the experimental data sets, parameter estimation experiments are performed. During parameter estimation the set of model parameters, that fit the experimental data best, is searched for. This is achieved by minimization of an objective function. In WEST, two different algorithms can be used, namely the simplex method (Nelder and Mead, 1965) or the Praxis method (Brent, 1973). These algorithms minimise the distance between a simulated trajectory and a measured trajectory (Meirlaen, 2002). The objective function determines the distance measure between the experimental and simulated values and is typically a sum of squared errors. Considering p dimensions, the simplex minimization method uses a geometrical figure (simplex) consisting of p+1 points interconnected by line segments forming polygonal faces. Each point of the simplex corresponds to a set of optimization variable values and represents one objective function value. The simplex method always starts with an initial arbitrary vertex (i.e. corner point). Then by performing elementary operations (such as reflection, expansion, etc.), it tries to improve the initial solution by finding an adjacent vertex with a better objective function value. If the average value of the whole simplex and the relative difference between the objective function values of the vertices are below a certain threshold, the algorithm stops. The Praxis algorithm stands for PRincipal AXIS and is a derivative-‐free optimization solver. Through repeated combination of one-‐dimensional searches along a set of various directions, the method aims to find the numerical minimum of functions consisting of several variables (Claeys, 2008).

27

3 RESULTS AND DISCUSSION

3.1 Analysis of the respirogram

Direct parameter abstraction from respirograms for wastewater characterisation is proposed as a simple and straightforward evaluation method. This method is ascribed above in chapter 2 ‘Material and methods’ (2.2.3.1. Flowing gas–static liquid). A few problems have arisen during the application of this evaluation method. First of all, there were some difficulties during the determination of the area under the OUR-‐curve. In some respirograms, it was observed that the endogenous respiration rate changes after addition of the sample. Spanjers and Vanrolleghem (1995) and Lagarde et al. (2005) experienced the same phenomenon. Both authors had two different approaches for determining the surface area under the OUR-‐curve. Lagarde et al. (2005) used the endogenous respiration rate after the addition of the sample for their calculations, as shown in Figure 3-‐1(b). Spanjers and Vanrolleghem (1995) determined the endogenous rate by performing a linear interpolation between the rate measured before the addition of the sample and the rate at the end of the respirogram (Figure 3-‐1(a)). Figure 3-‐1 illustrates the differences between the two approaches. The respirogram in Figure 3-‐1 is obtained after addition of 250.0 ml of a wastewater solution with a concentration of 125.3 mg COD/l to 1.9 l diluted activated sludge. Applying the method of Lagarde et al. (2005) results in a biodegradable substrate concentration of 13.2 mg/l while the approach of Spanjers and Vanrolleghem (1995) yields 9.3 mg/l. It is important that there is a standardized way to evaluate the respirograms because the two different approaches give different results. During this work the method of Spanjers and Vanrolleghem (1995) was applied to analyze the results.

Figure 3-‐1: Determination of the surface under the OUR-‐curve according to (a) Spanjers and Vanrolleghem (1995) and Lagarde et al. (2005) obtained after addition of 250.0 ml of a 125.3 mg COD/l wastewater solution to a batch reactor containing 1.9 l diluted activated sludge (with 10 mg/l ATU to block nitrification)

Furthermore, there also exist different approaches for the determination of the SS fraction. Kappeler and Gujer (1992) determine the SS concentration as illustrated in Figure 3-‐2(a), while Vanrolleghem et al. (2003) and Ekama et al. (1986) determine the area under the OUR-‐curve as shown in Figure 3-‐2(b). The respirogram is obtained after dosing 250.0 ml of influent of the PST (276.7 mg COD/l) to 1.9 l activated sludge. Following the approach of Kappeler and Gujer (1992) a SS concentration of

(a) (b)

OUR

(mg/

l.h)

−8

−4

0

4

8

Time (s)0 200 400 600 800

OUR-profile

OUR

(mg/

l.h)

−8

−4

0

4

8

Time (s)0 200 400 600 800

OUR-profile

28

39.2 mg/l is obtained, while the other method yields 47.4 mg/l. Subsequently another XS concentration is obtained for the two different approaches. During this work, the method of Vanrolleghem et al. (2003) and Ekama et al. (1986) was used for the determination of the SS fraction.

Figure 3-‐2: Determination of the SS concentration according to (a) Kappeler and Gujer (1992) and (b) Vanrolleghem et al. (2003) and Ekama et al. (1986) of a OUR-‐profile obtained after addition of 250.0 ml of influent of a PST to a batch reactor containing 1.9 l activated sludge (with 10 mg/l ATU to block nitrification)

Finally, one of the most important limitations is that this method can only be used when the individual components in the sample are dominant. Thus a change in shape of the respirogram has to be visible when the particular components are degraded and almost exhausted (Spanjers et al., 1999). This was not always the case during the analysis of the wastewater samples. Moreover, it was often difficult to determine the inflection point in the curve indicating the depletion of the readily biodegradable substrate and further degradation of the slowly biodegradable fraction in the sample. This was especially the case with noisy respirograms, even after filtering of the raw data.

3.2 Acetate as substrate

Experiments with the readily biodegradable substrate acetate were performed to verify if the two different respirometers in the lab reproduce the same OUR profile and subsequently give the same substrate concentration. Activated sludge of the WWTP of Eindhoven was used. 250.0 ml of a solution of sodium acetate trihydrate with a concentration of 92.0 mg COD/l was dosed to the sludge. The experimental set-‐up of the two respirometers was identical. ‘Flowing gas -‐ static’ liquid respirometric analysis was performed in triplicate for the two respirometers each. After calculating the SS fraction, a concentration of 52.9 mg/l (std = 8.6%) for the first respirometer and 61.2 mg/l (std = 8.3%) for the second respirometer is obtained (Figure 3-‐3).

(a) (b) O

UR (m

g/l.h

)

0

5

10

15

20

Time (s)0 1000 2000 3000 4000 5000 6000

OUR-profile

OUR

(mg/

l.h)

0

5

10

15

20

Time (s)0 1000 2000 3000 4000 5000 6000

OUR-profile

29

Figure 3-‐3: Readily biodegradable substrate concentration (SS) obtained with respirometric measurements after addition of 250.0 ml of acetate solution (92.0 mg COD/l) to 1.9 l of activated sludge of the WWTP of Eindhoven.

There exists a small difference between the obtained results for the two respirometers. The experimental set-‐up of the respirometers was identical, but it was noticed that the DO sensor of one respirometer showed more measurement noise than the other one. Measurement noise has an influence on the OUR-‐values since during the OUR calculations derivatives are taken, which enhances the effect of noise (Sin, 2004). However considering the standard deviations, these data show that the two respirometers give similar results. Both respirometers can be used simultaneously for wastewater characterisation, thus allowing a higher measuring frequency. Secondly the amount of SS seems to be underestimated. Only a value of 52.9 mg COD/l and 61.2 mg COD/l was obtained with the two respirometers, while the added acetate concentration was 92.0 mg COD/l. Apparently, not all the biodegradable COD added to the batch reactor can be recovered from the respirogram. There are different hypothesises possible to explain these results. First of all, the default value of 0.67 g COD/g COD is used for YH during the calculation of the biodegradable substrate concentration. However when this value is used in equation 2-‐5, the amount of SS seems to be underestimated since only a value of 52.9 mg COD/l and 61.2 mg COD/l was obtained while the added acetate concentration was 92.0 mg COD/l. A possible explanation might be that the value of YH differs from the default value. Based on these experimental data, the yield can be calculated as follows (Majone et al., 1999; Strotmann et al., 1999) :

𝑌!"# = 1 −∆0!

𝐶𝑂𝐷!"# (3-‐1)

where Δ02 is the change in oxygen concentration (mg/l) due to substrate degradation and CODdeg the amount of readily biodegradable COD (mg/l) added to the batch reactor. According to equation 3-‐1, a yield of 0.795 g COD/g COD (std = 2.9 %) is obtained. In literature, high yield values have been attributed to the occurrence of a storage phenomenon because less oxygen is consumed while the majority of the substrate is incorporated into the biomass. High yield values have been reported by Dircks et al. (1999) (0.72 g COD/g COD), Guisasola et al. (2005) (0.79 g COD/g COD) and Karahan-‐Gül et al. (2002) (0.78 g COD/g COD). These authors state that high yield values are typical for heterotrophic bacteria with much available substrate and extensive storage. Conventional activated sludge processes are often subjected to highly variable conditions of external substrate availability. The storage of polymers (usually, polysaccharides and lipids) can be caused by a feast and famine regime. At high concentration of substrate (feast phase), microorganisms accumulate storage

Ss (m

g/l)

0

20

40

60

Resp 1 Resp 2

30

polymers that are used for growth when the extracellular substrate is depleted (famine phase). Acetate is known to be stored as poly-‐hydroxybutyrate (PHB) (Karahan-‐Gül et al., 2002). The experiments with acetate as substrate were performed using activated sludge of the WWTP of Eindhoven where nitrification and denitrification take place. Subsequently the biomass is subjected to alternating anoxic and aerobic conditions and variable influent wastewater patterns. Under these dynamic conditions, microorganisms capable of quickly accumulating substrate during the feast phase have a competitive advantage over organisms without storage capacity and can balance their growth rate in dynamic processes (Carucci et al., 2001; Majone et al., 1999; van Loosdrecht et al., 1997). If the storage phenomenon occurs, it is advised to increase the YH to a higher value (e.g. 0.75) than the standard value of 0.67 mg COD/mg COD. The best solution is however to perform a model-‐ based interpretation of the experimental data. The interpretation and evaluation of the OUR-‐profile becomes more complicated if substrate adsorption and accumulation or storage phenomena occur. It makes the estimation of the SS and XS fraction in the wastewater more difficult because it is quite impossible to separate the degradation of the slowly biodegradable substrate from the oxygen consumption related with the degradation of internal storage polymers (Sin, 2004). Figure 3-‐4(a) shows the OUR-‐profile obtained after dosing 250.0 ml of acetate solution (92.0 mg COD/l). Upon addition of the sample, the respiration rate gradually increases to a maximum level. Thereafter the OUR-‐curve gradually decreases back to the endogenous respiration rate. Normally if the storage phenomenon occurs a typical storage tail is observed, as shown in Figure 3-‐4(b)). Apparently in Figure 3-‐4(a) there is no such a storage tail. Moreover, in Figure 3-‐4(b) an instantaneous increase in respiration rate after dosing of the sample is observed followed by a plateau phase. Additionally, the drop in respiration rate is steeper than in Figure 3-‐4(a). Guisasola et al. (2005) observed the same phenomenon, namely no observable storage tail and a high growth yield (0.73 g COD/g COD). This yield is also higher than the default value of 0.67 g COD/g COD. Guisasola et al. (2005) concluded that this observation suggests the presence of storage phenomenon as such and believe that both growth and storage processes occur simultaneously. Thus part of the acetate is consumed for growth and the rest is stored. The data obtained during this work confirm these findings.

Figure 3-‐4: OUR-‐profile obtained after addition of (a) 250.0 ml of acetate solution (92.0 mg COD/l) to a batch reactor containing 1.9 l activated sludge (with 10 mg/l ATU to block nitrification) and (b) OUR-‐curve with a storage tail after addition of 50 mg COD/l acetate to sludge of the WWTP of Granollers (Catalonia, Spain) (Guisasola et al., 2005)

(a) Time (min) (b)

OUR

(mg/

l.h)

0

5

10

15

20

Time (s)0 1000 2000 3000 4000 5000

OUR-profile

31

In addition, the lower substrate concentration could also be caused by the presence of certain compounds in the mixed liquor making the substrate unavailable for the biomass and subsequently inhibiting the uptake of acetate. The acetate ion has a negative charge and could possibly bind to compounds with a positive charge. This makes the substrate unavailable for the microorganisms in the activated sludge (Deweerdt, 2010).

3.3 Glucose as substrate

Additionally, experiments with glucose were performed. Glucose is a readily biodegradable substrate and is tested to verify if similar findings as with acetate are observed. Glucose is known to be stored as glycogen through a metabolic pathway completely different from that of PHB storage. The readily biodegradable substrate present in wastewater is likely to be stored as PHA and glycogen (Karahan-‐Gül et al., 2002). For this experiment, activated sludge of the WWTP of Roeselare was used and 250.0 ml of a solution of glucose with a concentration of 213.5 mg COD/l was added to the activated sludge (WWTP of Roeselare). This was repeated four times. Figure 3−5 illustrates the respirometric profile obtained after addition of glucose.

Figure 3-‐5: OUR-‐profile obtained after addition of (a) 250.0 ml of glucose solution (213.5 mg COD/l) to a batch reactor containing 1.9 l activated sludge (with 10 mg/l ATU to block nitrification)

After calculation of the concentration of biodegradable substrate with the default value 0.67 g COD/ g COD, a concentration of only 59.6 mg COD/l (std = 7.7%) is obtained. This is much lower than the COD concentration added to the batch reactor, namely 213.5 mg COD/l. COD measurements of the glucose solution were performed to verify the COD concentration and a value of 220 mg/l was obtained. To exclude the fact that the error (time lag) introduced by the DO probe dynamics lead to errors in the calculated OUR-‐values, all the measured DO data were corrected for the dynamic response of the DO sensor (Vanrolleghem et al., 1998). The applied respirometric method relies on the rate of change of dissolved oxygen but the DO measuring probe has a certain time lag. The area under the OUR-‐curve was calculated using the DO concentration measured by the DO probe and the actual DO-‐concentration corrected for the response of the sensor. Correction of the DO data did not yield different values for the area under the OUR-‐curve, excluding the possibility that the DO probe dynamics lead to errors in the OUR-‐values.

OUR

(mg/

l.h)

0

5

10

15

20

Time (s)0 1000 2000 3000

OUR-profile

32

Thus, after the addition of glucose, the same findings as with acetate are observed. After recalculating the yield according to equation 3-‐1, a value of 0.91 g COD/g COD (std = 0.8%) is obtained. High yield values for glucose have been reported by Dircks et al. (1999) (0.91 g COD/ g COD), Goel et al. (1999) (0.9 g COD/ g COD) and Karahan-‐Gül et al. (2002) (0.87 g COD/ g COD). According to these authors, high yield values are caused by the occurrence of storage. Comparing the yield values obtained for acetate and glucose, leads to the conclusion that a higher yield is obtained for glucose (0.91 g COD/g COD) than for acetate (0.80 g COD/g COD). However, one should be careful to compare these two experiments since they were not performed with the same activated sludge of the same WWTP. Dircks et al. (1999), Goel et al. (1999) and Karahan-‐Gül et al. (2002) observed the same findings, namely a higher yield for glucose than for acetate. They explained this by the fact that the formation of glycogen from glucose requires less energy as compared to PHB accumulation from acetate. According to Dircks et al. (2001) the storage of glycogen is energetically more efficient than the storage of PHB. Because of this the maximum yield of glycogen from glucose is 46% higher than the yield of PHB from acetate (Karahan-‐Gül et al., 2002). However, as was the case with acetate, despite the high yield value, no typical storage tail is observed. In addition, the lower substrate concentration could be caused by the presence of certain compounds in the activated sludge inhibiting the uptake of the substrate. However this possibility seems unlikely for both acetate and glucose. The experiments with acetate and glucose as substrate were carried out with activated sludge of two different WWTPs (Roeselare and Eindhoven). Thus, inhibiting components should have been present in both types of activated sludge. The experiments with acetate and glucose could be repeated with activated sludge of the same WWTP to see if the same results would be obtained.

3.4 PST influent and effluent as substrate

3.4.1 Evaluation respirogram

3.4.1.1 Direct evaluation method

Figure 3-‐6 illustrates the typical respirogram obtained after addition of 250.0 ml of wastewater. Typically, the DO concentration decreases immediately upon addition of the sample, followed by a large increase. This increase in DO concentration was not expected. Therefore, 250.0 ml of distilled wastewater was added to the reactor, to check if the same profile would be obtained. Upon addition of the sample, the same immediate increase in DO concentration is observed (Figure 3-‐7). This increase in oxygen concentration is probably caused by the addition of the sample. Due to the relatively large sample volume that is added, temporary swirls are created in the reactor, creating air-‐bubbles and a temporary higher oxygen transfer. Because there is no biodegradable substrate present in the distilled water, the DO concentration goes slowly back to the saturated DO concentration, while a faster decrease in DO concentration is observed in Figure 3-‐6 due to the degradation of biodegradable matter present in the wastewater sample.

33

Figure 3-‐6: DO-‐profile (a) and OUR-‐profile (b) obtained after addition of 250.0 ml of PST influent (266.0 mg COD/l) to a batch reactor containing 1.9 l activated sludge (with 10 mg/l ATU to block nitrification)

Figure 3-‐7: DO-‐profile obtained after addition of 250.0 ml of distilled water to a batch reactor containing 1.9 l activated sludge (with 10 mg/l ATU to block nitrification)

Moreover Figure 3-‐6 shows that after the addition of the wastewater sample, the endogenous respiration rate is lower than before addition of the sample. Lagarde et al. (2005) observed the same finding. This is also observed after the addition of distilled water, namely the DO concentration does not go back to the original DO concentration before addition of the sample. The higher DO concentration and subsequently lower endogenous respiration rate after sample addition is possibly caused by the dilution of the activated sludge resulting in a higher endogenous DO concentration and subsequently lower endogenous OUR.

3.4.1.2 WEST

The software programme West was used to simulate the experimental DO-‐profiles obtained after the addition of a wastewater sample. Figure 3−8 illustrates the configuration used for simulating the respirometric experiments in WEST. The configuration consists of a buffer tank, 2 timers and an activated sludge tank. The buffer tank represents the sample that is added to the batch reactor, while the activated sludge tank represents the respirometric batch reactor. The first timer is connected with the buffer tank and regulates at which time point 250.0 ml of sample is dosed to the

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activated sludge tank. The second timer is connected to the activated sludge tank to mimic the possible change in kLa value due to the addition of the sample.

Figure 3-‐8: configuration of the respirometer in WEST

A steady state simulation is performed. In WEST, the respirometer needs to be translated as realistically as possible. The biological parameters in the buffer tank and activated sludge tank are set to the values that occur in respectively wastewater and the respirometric batch reactor. A parameter estimation experiment was not performed due to lack of time. However, a simulation to check if the obtained DO-‐profiles could be mimicked with WEST was performed. Figure 3-‐9 shows the result of the simulation experiment. The immediate increase in DO concentration upon addition of 250.0 ml of wastewater sample can be mimicked in WEST by increasing the DO concentration of the sample added to the batch reactor or by temporarily increasing the kLa value upon addition of the sample. Both approaches are model simplifications to mimic the extra aeration caused by dosing the sample. Moreover, a higher equilibrium DO concentration is obtained after addition of the sample, as was observed in the real respirometric profiles. It can be concluded that simulation of the experimental data is possible.

Figure 3-‐9: Simulated DO-‐profile in WEST

Timer 1 Timer 2

Respirometer Sample container

DO-‐profile

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35

3.4.2 Dry weather conditions

3.4.2.1 One-‐day measurement campaign

A one-‐day measurement campaign was performed on March 12th. One-‐hour time weighted composite samples were taken for the influent and effluent of the PST. ‘Flowing gas -‐ static liquid’ respirometric analysis was performed in triplicate on the influent and effluent of the PST. These samples were taken during dry weather conditions and the detention time of the wastewater in the PST was approximately 1h40min. Despite the large standard deviations, the data in Table 3-‐1 show a trend, namely that the PST effluent contains a lower biodegradable substrate fraction than the influent. This shows that the PST in Roeselare reduces the BOD load for the subsequent biological treatment, as expected. Table 3-‐1: Average percentages of biodegradable COD (CS), SS and XS with respect to total COD of influent and effluent of the PST of the WWTP of Roeselare

Sample time Sample CS/CODTOT

(%) Std* (%)

SS/ CODTOT (%)

Std* (%)

XS/ CODTOT (%)

Std* (%)

10u55-‐11u55 Before PST 26.5 22.2 12.6 38.2 13.9 54.7 12u05-‐13u05 After PST 17.6 28.6 7.5 13.3 10.1 59.9 11u55-‐12u55 Before PST 35.7 28.4 15.6 8.6 20.1 49.4 13u05-‐14u05 After PST 26.4 32.4 11.3 76.9 15.0 88.9 12u55-‐13u55 Before PST 30.2 41.8 14.8 50.5 15.4 33.6 14u05-‐15u05 After PST 22.1 5.7 11.1 31.8 11.0 35.1

* Standard deviation in %

Table 3-‐2 and Figure 3-‐10 give an overview of the removal efficiencies of the total biodegradable substrate concentration (CS), readily biodegradable substrate concentration (SS) and slowly biodegradable substrate concentration (XS) in the wastewater samples. During the sedimentation process, larger more slowly biodegradable suspended solids settle first, while the soluble fractions remain in the primary tank effluent. Therefore it is expected that the overall (CS) removal efficiency follows the same trend as the XS removal efficiency. But apparently, the PST of Roeselare has also a great influence on the removal of soluble readily biodegradable substrate. Because there are not a lot of data points, it is difficult to establish a trend in the removal efficiencies and to draw conclusions. However, these results show that primary treatment has an impact on the different wastewater COD fractions but further investigation is required. Table 3-‐2: Biodegradable COD (CS), SS and XS concentrations and corresponding removal efficiencies

Sample time Number CS

(mg/l) Std* (%)

ECs (%)

SS (mg/l)

Std* (%)

ESs (%)

XS (mg/l)

Std* (%)

EXs (%)

10u55-‐11u55 1

70.4 22.2 44.5

33.5 38.2 50.1

37.0 54.7 39.4

12u05-‐13u05 39.1 28.6 16.7 13.3 22.4 59.9 11u55-‐12u55

2 98.8 28.4

52.9 43.1 8.6

53.6 55.7 49.4

52.3 13u05-‐14u05 46.6 32.4 20.0 76.9 26.6 88.9 12u55-‐13u55

3 83.8 41.8

29.2 41.1 50.5

27.7 42.8 33.6

30.6 14u05-‐15u05 59.4 5.7 29.7 31.8 29.7 35.1


36

Figure 3-‐10: removal efficiencies (%) of CS, SS and XS

3.4.2.2 Weekly measurements

Table 3-‐3 summarizes the results of the PST influent and effluent wastewater samples taken every week on monday morning in the WWTP of Roeselare. All the samples were analysed the next two days in the lab. The wastewater samples of March 24th obtained at the outlet of the PST could not be analysed because the biodegradable substrate concentration was too low, despite the dry weather conditions during sampling. The ratio of readily biodegradable substrate to the total wastewater COD ranges between 5.9 -‐ 8.5% in the PST influent and 10.2% -‐ 12.9% in the PST effluent. For the slowly biodegradable substrate, this ratio ranges between 2.2 -‐ 20.3% in the PST influent and 7.2 -‐ 20.1% in the PST effluent. For the samples of April 7th and 14th the biodegradable substrate concentration in the wastewater is greater at the outlet then at the inlet of the PST, resulting in negative removal efficiencies (Table 3-‐4). COD measurements and a 10-‐day BOD test of these samples, performed within the scope of another thesis, confirm the results obtained with the respirometer (Versluys, 2014). This is contradictory with normal expectations because the purpose of the PST is to remove the suspended solids and to lower the BOD load of the wastewater. Moreover the detention time of the wastewater in the PST on April 14th is the longest. The detention time is calculated by dividing the incoming wastewater flow rate by the volume of the primary sedimentation basin. Longer detention periods normally lead to more removal of suspended solids and BOD load. There are a few possible explanations for the observed phenomenon. First of all an improper sludge withdrawal in the PST may allow the sludge to remain too long in the tank leading to the production of gasses. Due to these gasses, sludge may rise to the water surface in the PST. Therefore less biodegradable matter or suspended solids can settle out and be removed. Another possibility is the occurrence of short-‐circuiting leading to very short detention times. Therefore, setteable material does not have enough time to settle out of the water. Short-‐circuiting can be caused by a variety of factors, such as temperature differences between the influent and the wastewater in the sedimentation basin leading to the formation of density currents or inlet and outlet structure design, unclean weirs and insufficient removal of scum, etc.. All these factors result in carry-‐over and discharge of floating material in the effluent. There is a need to collect and analyse more data in order to establish if the PST of the WWTP in Roeselare is dealing with one or more of the above-‐mentioned operational problems.

37

Table 3-‐3: Average percentages of biodegradable COD, SS and XS with respect to total COD of influent and effluent of the PST of the WWTP of Roeselare obtained with respirometric batch experiments.

* Standard deviation in % Table 3-‐4: Biodegradable COD (CS), SS and XS concentrations and corresponding removal efficiencies


3.4.3 Wet weather conditions Wastewater samples obtained on February 25th and March 3th at the WWTP of Roeselare were taken during wet weather conditions. Overnight, 2.0 l of mixed liquor from the biological tank of the WWTP of Roeselare was well aerated in the reactor in order to remove residual readily biodegradable substrate. ATU was added with a concentration of 10.0 mg/l to ensure that the respirogram is not affected by nitrification. After determination of the kLa, 250.0 ml of wastewater sample was added. Figure 3-‐11 shows the DO-‐profile and OUR-‐profile obtained upon addition of the wastewater sample. This profile is similar to the profile obtained after addition of distilled wastewaster (Figure 3-‐7).

Date Detention time (h)

Sample CS/CODTOT

(%) Std*

(%) SS/ CODTOT

(%) Std*

(%) XS/ CODTOT

(%) Std*

(%)

24/03/14 1.4 Before PST 11.4 21.0 5.9 22.1 5.5 19.8 After PST N.A. N.A. N.A. N.A. N.A. N.A.

07/04/14 1.9 Before PST 9.4 12.0 7.1 13.4 2.2 43.7 After PST 20.1 1.6 12.9 24.3 7.2 46.1

14/04/14 2.0 Before PST 28.9 16.0 8.5 12.7 20.3 17.4 After PST 30.2 27.5 10.2 23.8 20.1 29.3

Date Sample CS

(mg/l) Std* (%)

ECs (%) SS

(mg/l) Std* (%)

ESs (%) XS

(mg/l) Std* (%)

EXs (%)

24/03/14 Before PST 22.4 21.0

N.A. 11.6 22.1

N.A. 10.8 19.8

N.A. After PST N.A. N.A. N.A. N.A. N.A. N.A.

07/04/14 Before PST 19.3 12.0

-‐156.0 14.7 13.4

-‐116.3 4.6 43.7

-‐283.0 After PST 49.3 1.6 31.7 24.3 17.6 46.1

14/04/14 Before PST 63.7 16.0

-‐30.1 18.8 12.7

-‐48.3 44.9 17.4

-‐22.4 After PST 82.9 27.5 27.9 23.8 54.9 29.3

38

Figure 3-‐11: DO-‐profile (a) and OUR-‐profile (b) after addition of 250.0 ml of PST influent to a batch reactor containing 2.0 l activated sludge (with 10 mg/l ATU to block nitrification)

To eliminate the possibility that the organisms in the activated sludge did not have enough essential nutrients, limiting the degradation of the biodegradable substrate, sodium phosphate and ammonia sulphate were added to the activated sludge. However, after adding these nutrients the same respirometric response was observed upon addition of the wastewater samples. Thus, no essential nutrients were limiting for the activated sludge organisms. Since no essential nutrients were lacking, the wastewater samples of the WWTP of Roeselare were probably very dilute because of rainfall conditions before and during sampling. To validate this reasoning, acetate and diluted synthetic wastewater were dosed to the batch reactor. This resulted in a fast respirometric response for both substrates, confirming that the wastewater samples were very dilute. COD measurements of the wastewater samples taken during wet weather conditions yielded a COD concentration ranging between 31.2 mg/l and 179.0 mg/l. In addition five-‐day BOD measurements were performed, resulting in a BOD5 value ranging between 30.3 mg/l and 43.7 mg/l (Versluys, 2014) indicating the presence of biodegradable substrate in these wastewater samples. In comparison, samples obtained during dry weather conditions had a BOD5 value ranging between 58.5 mg/l and 145 mg/l. These samples could all be analysed with the respirometric method. Possibly the dilute wastewater samples contain mainly slowly biodegradable substrate that cannot be degraded during the short-‐term respirometric experiments. On the other hand there could be degradation of the biodegradable substrate by the microorganisms in the activated sludge. But due to the low CS in the dilute wastewater, the rate of oxygen consumption of the microorganisms in the activated sludge during substrate degradation did not exceed the oxygen supply, resulting in DO and OUR-‐profiles as shown in Figure 3-‐11. Therefore, the aeration was lowered to the minimal aeration rate (0.5 l/min) to reduce the oxygen supply. Furthermore, the aeration stone was removed to create larger air bubble sizes for a given aeration power. This results in a lower specific area for mass transfer, thus less efficient oxygen transfer. After the addition of 250.0 ml of wastewater, the same respirometric profile as in Figure 3-‐11 was observed. Decreasing the aeration rate and increasing the air bubble sizes did not decrease the oxygen supply sufficiently.

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3.4.3.1 Batch test with diluted sludge

Since the respirometric protocol did not yield good results for dilute wastewater samples, several attempts were made to improve the respirometric response upon addition of the water samples. First of all, the initial substrate concentration to initial biomass concentration (S0/X0) was adapted. For the same wastewater volume, the magnitude of the area under the OUR-‐curve is not influenced by the S0/X0. This area is only dependent of the mass of biodegradable COD in the wastewater sample. Changing the S0/X0 has only an effect on the shape of the OUR-‐curve. A low S0/X0 results in a tall and narrow curve due the fast utilization of the biodegradable substrate, while a high S0/X0 gives a low and wide OUR-‐curve (Ekama et al., 1986). Therefore a batch test was performed with diluted sludge to create a higher S0/X0 ratio and to slow down the oxygen uptake. 1.0 l of activated sludge was diluted with 1.0 l of distilled water. The wastewater samples obtained during wet weather conditions had a COD concentration ranging between 31.2 mg/l -‐ 179.0 mg/l. To mimic these samples, influent of the PST was diluted with effluent of the WWTP to create samples with a COD concentration in this region. The experimental protocol was followed as mentioned above (2.2.3.1 Flowing gas–static liquid). Figure 3-‐12 illustrates the DO-‐profile and exogenous uptake rate when 250.0 ml wastewater (125.3 mg COD/l) is dosed to the batch reactor containing diluted sludge.

Figure 3-‐12: DO-‐profile (a) and OUR-‐profile (b) obtained after addition of 250.0 ml of a 125.3 mg COD/l wastewater solution to a batch reactor containing 1.9 l diluted activated sludge (with 10 mg/l ATU to block nitrification)

After addition of the sample, the readily biodegradable matter in the sample is degraded after approximately 4 minutes and subsequently the slowly biodegradable substrate is degraded as the OUR-‐curve is decreasing to a lower endogenous OUR. After approximately 9 minutes, all the biodegradable matter in the wastewater sample is degraded. After calculation of the surface area under the OUR-‐curve a total biodegradable substrate concentration of 13.2 mg/l is obtained, consisting of 9.7 mg/l readily biodegradable substrate and 3.5 mg/l slowly biodegradable substrate. After degradation of the first sample when the endogenous respiration rate was reached again and constant for approximately 15 minutes a new sample of 250.0 ml was added to the batch reactor. A respirometric response as shown in Figure 3-‐13 was observed. A much smaller decrease in DO concentration than after the first spike is observed. The total volume in the reactor (VR) amounts 2.4 l, while after the first spike the VR was 2.15 l. A possible explanation for the smaller respirometric response is that due the higher volume in the batch reactor, the air bubbles stay longer in the mixed

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liquor, so increasing the oxygen transfer capacity, leading to a higher dissolved oxygen concentration. Moreover due to the higher volume it is possible that a bigger mixing vortex in the reactor is created, resulting in a better aeration and higher kLa value. Furthermore due to the addition of the sample there is a dilution effect, so less biomass is present per unit of volume resulting in higher dissolved oxygen concentration. It can be concluded that there is no straightforward explanation for the observed phenomenon and that there are a lot of different effects that can be responsible for the observed respirometric profile. After calculation of the surface under the OUR-‐curve a total biodegradable substrate concentration of only 5.3 mg/l is obtained. This is much smaller than the total biodegradable concentration of the first sample. A solution for this observation could be to let the sludge decant to maintain approximately the same activated sludge concentration and to remove 250.0 ml of the supernatant so that the start volume of 1.9l activated sludge is reached again.

Figure 3-‐13: DO-‐profile (a) and OUR-‐profile (b) after addition of 250.0 ml of a 125.3 mg COD/l wastewater solution to a batch reactor containing 2.15 l diluted activated sludge (with 10 mg/l ATU to block nitrification)

A drawback of performing experiments with diluted sludge is the long time necessary for determining the kLa value. Since the kLa value is obtained by a dynamic gassing out method, i.e. the aeration is stopped until a dissolved oxygen concentration of 1.5-‐2 mg/L is reached. Then the kLa value is calculated from the re-‐aeration curve (2.2.3.1 Flowing gas–static liquid). Normally it takes approximately 40 minutes to determine one kLa value, but with diluted sludge it takes 1h40 minutes. Since the kLa-‐value has to be determined 3 times, it takes approximately 5h to determine the kLa. Thus this method does not allow a high-‐measuring frequency.

3.4.3.2 Batch test with concentrated sludge

The same type of experiment was performed with concentrated sludge. The activated sludge was concentrated by decanting 5.0 l mixed liquor and removing 3.0 l of the supernatant liquid. A dilute wastewater sample was made with a COD concentration of 103.7 mg/l. Figure 3-‐14 shows the DO-‐profile and exogenous uptake rate when 250.0 ml wastewater (103.7 mg COD/l) is dosed to the batch reactor containing 1.9 l of concentrated sludge. The total biodegradable matter of the wastewater sample is completely degraded in 6 minutes. According to the respirogram, a total biodegradable substrate concentration of 9.4 mg/l is present in the wastewater sample. The readily biodegradable substrate concentration amounts 5.9 mg/l and the slowly biodegradable substrate

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concentration is 3.5 mg/l. Just as in the experiments with diluted sludge, a lower endogenous respiration rate is reached after addition of the wastewater sample. One kLa value is determined in approximately 20 minutes, so this experiment does not last as long as the experiment with diluted sludge.

Figure 3-‐14: DO-‐profile (a) and OUR-‐profile (b) obtained after addition of 250.0 ml of a 103.7 mg COD/l wastewater solution to a batch reactor containing 1.9 l concentrated activated sludge (with 10 mg/l ATU to block nitrification)

After degradation of the first sample when the endogenous respiration rate was reached again and constant for approximately 15 minutes a new sample of 250.0 ml was added to the batch reactor. A respirometric response as shown in Figure 3-‐15 was observed. As in the experiment with diluted sludge, a much smaller decrease in DO concentration than after the first spike is observed. After calculation of the surface under the OUR-‐curve a total biodegradable substrate concentration of 8.6 mg/l is obtained. This concentration is close to the value obtained after the first spike (9.4 mg/l). Despite the very small decrease in DO-‐concentration, the area under the OUR-‐curve is close to that of the first spike. This is because the endogenous respiration rate after the addition of the sample is used for the calculations of the surface area, resulting in a relatively big area under the curve.

Figure 3-‐15: DO-‐profile (a) and OUR-‐profile (b) obtained after addition of 250.0 ml of a 125.3 mg COD/l wastewater solution to a batch reactor containing 2.15 l concentrated activated sludge (with 10 mg/l ATU to block nitrification)

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3.4.3.3 Comparison between the different respirograms

The test with concentrated sludge resulted in a higher maximum OURex, namely 12.8 mg/l.h in comparison with the maximum OURex (7.8 mg/l.h) of the test with diluted sludge, despite the fact that the COD-‐content of the wastewater sample dosed to the concentrated sludge was a little bit lower (125.3 mg COD/l versus 103.7 mg COD/l). This meets our expectations since the S0/X0 ratio (0.0025 g COD/g VSS) in the test with concentrated sludge is 4.4 times lower than the S0/X0 ratio (0.011 g COD/g VSS) of the test with diluted sludge, resulting in a faster utilization of the biodegradable substrate. Moreover the biodegradable substrate is completely degraded in 6 minutes in the test with concentrated sludge, while the test with diluted sludge lasted 9 minutes to reach complete degradation. An important difference between the experiment with diluted sludge and concentrated sludge is the time needed to determine the kLa. It takes 5 times more time to determine the kLa value with diluted sludge. Finally, for both methods a relatively low biodegradable substrate concentration is obtained in comparison with the dosed COD value.

3.4.3.4 Batch test with larger volume of wastewater

Furthermore a test was performed in a smaller respirometer consisting of a 1L double-‐glass vessel. A higher S0/X0 ratio (0.038 g C0D/g VSS) was created by adding 0.40l of dilute wastewater to the batch reactor containing 0.50 l of activated sludge. The DO-‐profile and OUR-‐profile obtained with this type of experiment is shown in Figure 3-‐16.

Figure 3-‐16: DO-‐profile (a) and OUR-‐profile (b) obtained after addition of 400.0 ml of a 103.7 mg COD/l wastewater solution to a batch reactor containing 500.0 ml concentrated activated sludge (with 10 mg/l ATU to block nitrification)

After addition of the wastewater sample, the exogenous respiration rate reaches a maximum of 40.4 mg/l.h and then decreases to a value lower than the endogenous respiration rate. Thereafter OURex increases again to OURend. This profile does not allow the calculation of CS, since the area under the OUR-‐curve is probably not representative for the oxygen consumed during substrate degradation. Due to the addition of 400.0 ml to 500.0 ml of sludge, the total reactor volume almost doubles upon addition of the sample. The air bubbles can stay longer in the mixed liquor and there is strong dilution of the activated sludge. These factors possibly change the kLa value and oxygen transfer, resulting in an error in the calculated OUR values. A better OUR-‐profile could be obtained, if the change in kLa value and oxygen transfer would be accounted for in the calculation of the OUR value.

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3.4.3.5 Static gas -‐ static liquid respirometry

3.4.3.5.1 Acetate as substrate During this experiment 1.9l of activated sludge was shortly aerated until a DO concentration of 8 -‐ 9 mg/l was reached. Then the aeration was turned off and the decrease in dissolved oxygen concentration due to respiration was followed. To validate this method, a known amount of sodium acetate trihydrate was added to the activated sludge. The results are illustrated in Table 3-‐5. From these results can be concluded that a lower biodegradable substrate concentration is obtained than was originally dosed to the reactor. Additionally, simulation and parameter estimation experiments were performed in WEST. Figure 3-‐17 illustrates the configuration of the respirometric setup in WEST. It consists of a buffer tank representing the acetate sample dosed to the reactor. This buffer tank is connected with an activated sludge tank, representing the respirometric batch reactor. Moreover there is a timer regulating the time point at which acetate from the buffer tank is dosed to the activated sludge tank.

Figure 3-‐17: configuration of the respirometer in WEST

For the determination of the endogenous state of the activated sludge in the batch reactor, an additional experiment was performed, during which the activated sludge was aerated for 3 hours. The initial biomass concentration of the heterotrophs and the kLa were estimated, so that the simulated conditions of endogenous respiration were matching to the real experimental conditions of endogenous respiration. The conditions of the activated sludge tank at the end of this simulation were used as the initial values of the parameters and initial values of the derived state variables of the activated sludge tank in the second simulation without aeration. During this simulation, the SS concentration in the buffer tank is chosen as the parameter to be estimated since acetate is a readily biodegradable substrate. The simplex method is chosen as the optimization algorithm. Figure 3-‐18 shows the simulation results for the experiment in which 13.6 mg sodium acetate trihydrate was added to 1.9 l activated sludge.

Timer

Sample container Respirometer

44

Figure 3-‐18: Simulated and measured DO-‐values after addition of 13.6 mg/l sodium acetate trihydrate (6.4 mg COD/l)

Table 3-‐5 shows the simulation results obtained for CS. These data show that a better estimation of the real COD concentration added to the batch reactor is obtained. Estimating CS with the AMS1 model gives better results than calculating the CS according to equation 2-‐9. However, the estimated results still underestimate the actual dosed COD concentration. This could possibly indicate the occurrence of storage, as was the case with the ‘flowing gas-‐ static liquid’ experiment (3.2 Acetate as substrate). If the storage phenomenon occurs, it is advised to increase the YH to a higher value (Sin, 2004). Table 3-‐5: concentration of biodegradable substrate CS after addition of sodium acetate trihydrate determined with ‘static gas-‐static liquid’ respirometry

Sodiumacetate Trihydrate (mg/l)

COD of sample (mg/l) Calculated Cs (mg/l)

Estimated Cs (mg/l) in WEST

13.6 6.4 4.2 5.0 21.7 10.2 6.6 7.8

3.4.3.5.2 Wastewater as substrate Thereafter, this type of experiment was performed with 250.0 ml of dilute wastewater sample (52.7 mg COD/l). During this method, there is no aeration, so the oxygen decrease due to substrate degradation should be visible upon addition of the sample. However, no increase in respiration rate due to substrate degradation was observed as shown in Figure 3-‐19(a). Moreover an increase in DO concentration was observed after sample addition. The same increase in DO concentration upon addition of 250.0 ml of distilled water is observed, as shown in Figure 3-‐19(b). This increase in DO-‐concentration could be caused due to the dilution of the activated sludge, leading to a higher DO concentration. Moreover due to the sample addition, swirls in the reactor could be created, leading to a higher DO concentration due to transfer of oxygen from the headspace.

Time (d)

DO (m

g/l)

DO-‐profile

Simulated data Experimental data

45

Figure 3-‐19: DO-‐profile obtained after addition of (a) 250.0 ml of PST influent (57.3 mg COD/l) and (b) 250.0 ml of distilled water to 1.9 l activated sludge (arrow indicating the addition of the substrate)

To evaluate the minimum biodegradable substrate concentration leading to an increased respiration rate after sample addition, dilute wastewater samples with different COD concentrations were made. Table 3-‐6 shows the obtained results. For the dilute wastewater sample with a COD concentration of 52.4 mg/l, no increased respiration rate upon addition of the sample was visible. For the other samples, with a higher COD concentration, a visible respirometric response was observed. After calculation of the biodegradable substrate concentration, a very low value is obtained. The calculated concentrations of the biodegradable substrate in the wastewater sample are probably an underestimation of the real biodegradable substrate concentrations, as was the case with acetate. Table 3-‐6: concentration of biodegradable substrate CS in dilute wastewater sample determined with ‘static gas-‐static liquid’ respirometry

COD of sample (mg/l)

Cs (mg/l) Std (%)* Cs/CODtot (%) Std (%)*

52.4 N.A. N.A. N.A. N.A. 80.2 4.1 83.2 5.1 4.2 110.5 9.1 25.9 8.2 2.1 158.9 12.5 28.8 7.9 2.3

* Standard deviation in % Therefore, a parameter estimation experiment was performed in WEST. The same configuration was used as described for acetate. For the determination of the endogenous state of the activated sludge in the batch reactor, an additional experiment was performed, during which the activated sludge was aerated for 3 hours. The initial biomass concentration of the heterotrophs and the kLa were estimated, so that the simulated conditions of endogenous respiration were matching to the real experimental conditions of endogenous respiration. It was noticed that the longer the experiment continued the estimated biomass concentration in the respirometer increased from 0.98 g/l to 4.28 g/l. Indeed, the longer the experiment lasted, the lower (more negative) the slope of the curves were, as shown in Figure 3-‐20. At the beginning of the experiment the endogenous respiration rate is 0.0018 mg/l.s, while at the end of the experiment (approximately 4h later) the

(a) (b)

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endogenous respiration rate is 0.0079 mg/l.s. This increase in respiration rate cannot only be caused by the growth of biomass due to substrate addition. Another possible explanation is the presence of slowly biodegradable substrate present in the wastewater samples, which could not be degraded in the short time frame. This means, that the microorganisms in the batch reactor are not in the endogenous state because they are still degrading slowly biodegradable substrate. However, endogenous conditions of activated sludge in the beginning of the test are crucial for a correct determination of the biodegradable substrate present in a dosed sample. Waiting until the slowly biodegradable substrate is degraded before the aeration is turned on again is not an option because of oxygen limitations. Alternatively, oxygen limitation can be avoided by a regular reaeration of the batch reactor. Moreover it was not possible to estimate the concentration of XS and SS in the wastewater sample with WEST because it was not able to make a distinction between XS and SS.

Figure 3-‐20: DO-‐profile obtained after addition of 250.0 ml of dilute wastewater sample (110.5 mg COD/l) to 1.9 l of activated sludge (a) at the beginning of the experiment and (b) at the end of the experiment

Additionally, the same test was performed with diluted sludge and dilute wastewater. 1.0 l activated sludge was diluted with 1.0 l distilled water. The dilute wastewater sample had a COD concentration of 50.98 mg/l. Upon addition of the wastewater sample, no difference in respiration rate could be observed. Because of the above findings, this type of experiment cannot be used for the determination of the biodegradable substrate concentration of wastewater samples due to the presence of slowly biodegradable matter that cannot be degraded in a short period of time. Moreover for very dilute wastewater samples no increase in respiration rate upon addition of the sample can be observed.

(a) (b)

OURI = -‐0.0079 mg/l.s DO

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4 CONCLUSIONS AND PERSPECTIVES

This work investigates the influence of the primary settling tank in wastewater treatment. Respirometric measurements were carried out to characterize the different COD fractions of the wastewater. The most important findings and conclusions are reported here. First of all, ‘flowing gas-‐ static liquid‘ respirometric measurements of acetate and glucose were carried out. From these results it can be observed that the biodegradable COD concentration of the substrate cannot be totally recovered from the area under the OUR-‐curve. A possible explanation for this phenomenon is that the value of YH differs from the default value (0.67 g COD/g COD). Calculation of the heterotrophic yield from the respirograms for acetate and glucose yields respectively 0.80 g COD/g COD and 0.91 g COD/g COD. Such high yield values have been reported in literature and have been attributed to the storage of polymers caused by a feast and famine regime. However, no typical storage tail was observed in the OUR-‐profile. This observation possibly suggests that growth and storage processes occur simultaneously. A model-‐based interpretation of the experimental data should be performed. Secondly, respirometric measurements were performed with wastewater sampled at the inlet and the outlet of the PST during dry weather conditions. These results illustrate that the primary settler changes the wastewater COD fractions. The results of the one-‐day measurement campaign at the WWTP of Roeselare show that the PST reduces the BOD load for the subsequent biological treatment. This is in contrast with the weekly respirometric measurements. These results show that the biodegradable substrate concentration in the PST effluent is greater than in the PST influent. Improper sludge withdrawal and short-‐circuiting can lead to carry-‐over and discharge of floating material in the effluent. There is a need to collect and analyse more data in order to establish if the PST of the WWTP in Roeselare is dealing with operational problems. A first start for a model-‐based interpretation of the experimental data has been performed. A possible suggestion is to perform model-‐based parameter estimation experiments to determine the SS and XS fractions of the dosed wastewater samples. Additionally, special attention was given to the wastewater characterisation of dilute wastewater sampled during wet weather conditions. Following the same respirometric protocol, as with the dry weather wastewater samples did not yield good results for the dilute, less polluted wastewater samples. Increasing the initial substrate to biomass ratio (S0/X0) by diluting the sludge, does not allow a high measuring frequency because the determination of the kLa value takes a long time. Moreover after the second spike, a much smaller respirometric response is observed. The same finding was observed in experiments with a lower S0/X0 ratio. Letting the sludge decant and subsequently remove a certain volume of the supernatant to maintain the same initial total volume in the batch reactor could solve this issue. However, both methods yielded a relatively low biodegradable substrate concentration in comparison with the actual dosed COD value. Finally a ‘static gas -‐ static liquid’ respirometric approach was applied. Dosing a known amount of readily biodegradable substrate, namely acetate, validated this method. A model-‐based interpretation of the experimental data approximates the actual dosed COD concentration the best. However, the estimated value underestimates the actual concentration. This could possibly suggest the

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occurrence of storage, as was the case with the ‘flowing gas -‐ static liquid’ respirometric measurements. Thereafter, experiments with dilute wastewater samples were performed. It was observed that the endogenous respiration rate of each measurement cycle increased the longer the experiments lasted. This is probably caused by the presence of slowly biodegradable substrate in the wastewater samples. Therefore the microorganisms were not in the endogenous state because they were still degrading slowly biodegradable substrate. However, endogenous conditions of activated sludge in the beginning of each measurement cycle are crucial for a correct determination of the biodegradable substrate present in a dosed sample. This leads to the conclusion that this respirometric approach cannot be used for the characterisation of wastewater samples. Moreover for very dilute wastewater samples no increase in respiration rate upon addition of the sample can be observed. A possible suggestion for further investigation is to apply other respirometric principles, like hybrid respirometry. This type of respirometer consists of an aerated vessel and a closed non-‐aerated respiration chamber. Sludge is continuously pumped between the aeration vessel and the respiration chamber. An advantage of this approach is that it avoids the need to estimate kLa values, thus increasing the measuring frequency. In short, primary settling has a significant influence on the COD fractions and BOD load of wastewater. However, further investigation is required to get more insight on the impact of the primary settler. ‘Flowing gas -‐ static liquid’ batch respirometry, has been useful for the characterisation of polluted wastewater. Nevertheless, this method is less suitable for the determination of the biodegradable substrate concentration in less polluted wastewaters.

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