Faculteit Bio-ingenieurswetenschappen
Academiejaar 2014 – 2015
No Feast without Famine
Optimization of the high-load contact stabilization process
to maximize chemical energy recovery from sewage
Koen Pauwels
Promotor: Prof. dr. ir. Siegfried E.Vlaeminck
Prof. dr. ir. Nico Boon
Tutor:
MSc. Francis Meerburg
Masterproef voorgedragen tot het behalen van de graad van
Master in de bio-ingenieurswetenschappen: Chemie en Bioprocestechnologie
Faculteit Bio-ingenieurswetenschappen
Academiejaar 2014 – 2015
No Feast without Famine
Optimization of the high-load contact stabilization process
to maximize chemical energy recovery from sewage
Koen Pauwels
Promoter: Prof. dr. ir. Siegfried E. Vlaeminck
Prof. dr. ir. Nico Boon
Tutor:
MSc. Francis Meerburg
Masterproef voorgedragen tot het behalen van de graad van
Master in de bio-ingenieurswetenschappen: Chemie en Bioprocestechnologie
De auteur en promotor geven de toelating deze scriptie 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 deze scriptie.
The author and 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.
Ghent, June 2015
The promoters,
The Tutor,
The author,
Prof. dr. ir. Siegfried E. Vlaeminck
MSc. Francis Meerburg
Koen Pauwels
Prof. dr. ir. Nico Boon
Acknowledgements
No Feast without Famine.
Like the teaser of my thesis says: “before you reach your final goal, a rough path of holes and bumps
has to be overcome”. Luckily, you are not the only one walking that path and many have walked it
before you. There is always someone standing on the sidewalk to point out the right direction, to
cheer you on, to give instructions to dodge as many obstacles as possible and to help you back on
your feet when you didn’t manage to avoid a hindrance. Because of these people, the journey
doesn’t feel like a heavy burden as they help you carry the weight and even make it enjoyable. To all
of you, I would like to say: Thank you.
Special thanks go to Francis, the one and only inventor of the HiCS system. Without your profound
knowledge and gut feeling about the system, I wouldn’t have come far. Even in the dark ages of the
first semester, where technical issues got the upper hand and a lot of time was invested in fixing daily
issues, your unmistakable enthusiasm and positivism kept me going. Thanks for the enjoyable talks,
the humorous remarks, the many insights about wastewater treatment, the time you invested in the
project and learning me how to pipet correctly.
I also would like to thank my predecessor Tim for handing over the HiCS-torch to me and sharing the
knowledge you already managed to acquire. Thank you for taking over a part of the experiments
during the first exam period, together with Francis, to win back some precious time that was lost in
the first semester.
More thanks go to professor Vlaeminck and Dries for sharing your know-how of running a lab-scale
reactor, for your interest in the work I’ve done and for helping me comprehend and process the
results I gathered. I also would like to thank Veerle for keeping an eye on my reactor, for helping me
clean the lab after one of the reactors decided to flood once again and for the many hours we spent
together preparing synthetic influent.
Very special thanks go to my fellow students, who have become dear friends: Wout, Esther,
Delphine, Mathias, Thomas, Matthias, Cornelia, Pieter, Hildebrand and Abbas. Your jokes, chats and
cheerfulness, in and outside LabMET, made the lab-life even more enjoyable. Finally, I would like to
thank my girlfriend, parents, friends and sister for giving me the courage to carry on and finish this
last chapter of my career as a student.
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Page | v
List of Abbreviations
A/B-process
'Adsorption-Belebungsverfahren' or Adsorption bio-oxidation process
AD
Anaerobic digestion
AOB
Ammonia oxidizing bacteria
BOD
Biological oxygen demand
BSA
Bovine serum albumin
CAS
Conventional activated sludge
Canon
Completely autotrophic nitrogen removal over nitrite
C-EPS
Carbohydrates-EPS
CEPT
Chemically enhanced primary sedimentation
CHP
Combined heat and power
COD
Chemical oxygen demand
CS
Contact stabilization
CSTR
Continuous stirred-tank reactor
DO
Dissolved oxygen
EPS
Extracellular polymeric substances
F/M ratio
Food-to-microorganism ratio
GWP
Global-warming potential
HiCS
High-load contact stabilization
HiCAS
High-load conventional activated sludge
HRAS
High-rate activated sludge
HRT
Hydraulic retention time
LB-EPS
Loosely bound EPS
MBR
Membrane bioreactor
N
Nitrogen
Page | vi
NOB
Nitrate oxidizing bacteria
OLAND
Oxygen-limited autotrophic nitrification/denitrification
P
Phosphorus
PAO
Phosphate accumulating organisms
P/C ratio
Proteins over carbohydrates ratio
PE
Population equivalent
P-EPS
Protein-EPS
PHA
Polyhydroxyalkanoates
PHB
Polyhydroxybutyrate
PN/A
Partial nitritation/anammox
rbCOD
Rapidly biodegradable COD
SBR
Sequencing batch reactor
SGP
Specific gas production
SI
Solubility index
SRT
Sludge retention time
SS
Suspended solids
SSV
Settled sludge volume
SVI
Sludge volume index
SYNTHES
Synthetic sewage
TB-EPS
Tightly bound EPS
TS
Total solids
TSS
Total suspended solids
VFA
Volatile fatty acids
VS
Volatile solids
VSS
Volatile suspended solids
WWTP
Wastewater treatment plant
Page | vii
List of Symbols
BX
Sludge-specific organic loading rate
(g bCOD g-1 VSS d-1)
BV
Volumetric organic loading rate
(g bCOD L-1 d-1)
CODcol
Colloidal COD
(mg L-1)
CODdiss
Dissolved COD
(mg L-1)
CODpart
Particulate COD
(mg L-1)
CODtot
Total COD
(mg L-1)
COD%
COD removal efficiency
(%)
EE
Electrical energy
(J)
ET
Synthesis energy
(J)
ES
Thermal energy
(J)
fCOD/VSS
COD/VSS ratio
/
HRT
Hydraulic retention time
(h)
kd
Decay rate
(d-1)
QI
Influent flow rate
(L d-1)
QE
Effluent flow rate
(L d-1)
QW
Waste flow rate
(L d-1)
SI
Influent substrate concentration
(g COD L-1)
SRTact
Actual sludge retention time
(days)
SRTint
Intended sludge retention time
(days)
tC
Contact time
(min)
tS
Stabilization time
(min)
Vcontact
Working volume after contact phase
(L)
VR
Reactor volume
(L)
Vstabilization
Working volume during stabilization phase
(L)
Page | viii
Vwaste
Working volume after waste phase
(L)
XE
Effluent biomass concentration
(g VSS L-1)
XR
Reactor biomass concentration
(g VSS L-1)
XW
Waste biomass concentration
(g VSS L-1)
∆XR,growth
Biomass growth in the reactor
(g VSS d-1)
Yobs
Observed yield
(g VSSproduced g-1 CODremoved)
µmax
Maximum growth rate
(d-1)
Page | ix
Abstract (Eng.)
Municipal wastewaters are typically treated through conventional activated sludge processes, often
with the sole aim of meeting the discharge standards. However, in order to become more
sustainable, a transition has to be made from a ‘wastewater treatment plant’ to a ‘resource recovery
plant’. Wastewater has the potential to be a valuable source of nutrients and chemical energy. It is
theoretically feasible to improve a wastewater treatment plant in such a way that it becomes
energetically self-sufficient. However, the chemical energy in the wastewater in the form of organic
matter is too diluted to achieve a high efficiency in methane production by direct anaerobic
digestion. Therefore, the wastewater organics need to be concentrated. A promising technology to
achieve this is the high-load contact stabilization (HiCS) system. This is a high-rate activated sludge
(HRAS) system designed to serve as the first part of a two-stage activated sludge system. The
characterizing high loading rates (>2 g bCOD g-1 VSS d-1), short sludge retention times (SRT) (<3 days)
and feast-famine regime are ideal conditions for selection of microorganisms which have fast
biosorption and bio-accumulation abilities. Optimization of the HiCS system was performed by
running eight lab-scale reactors at different SRT, contact times (tC) and stabilization times (tS), in
order to achieve maximal organics recovery. Standardized synthetic wastewater was used as influent
for the reactors. The performance of the HiCS reactors was evaluated based on the removal of
organic substrate, the sludge yield and the extent of respiration. Next to that, the extracellular
polymeric substances (EPS) production and composition were measured to make an assessment of
their influence on the HiCS performance. Furthermore, the storage of polyhydroxybutyrate (PHB) in
the sludge was characterized. The highest COD removal efficiency of 65 % was achieved at an SRT of
1.31 days and a tC:tS of 15:40 min. This reactor also showed the largest PHB storage response of
21 mg PHB g-1 VSS. However, the HiCS reactor with an SRT of 0.46 days and the same tC:tS, achieved
the highest sludge yield (0.737 kg VSS kg-1 CODremoved), and the highest net recovery of organics. It
was also shown that the protein-EPS concentration plays a more pronounced role in terms of
biosorption and flocculation of sludge than the carbohydrate-EPS concentration. Although the
performance of the optimized HiCS system still has to be evaluated on real wastewater, it shows
great potential as a wastewater pre-concentration technique to achieve energy-neutral wastewater
treatment.
Page | x
Abstract (Ned.)
Huishoudelijk afvalwater wordt typisch behandeld in conventionele actiefslibsystemen die vaak het
behalen van de lozingsnormen als enige doel hebben. Om de technologie duurzamer te maken, moet
het systeem overgaan van het louter zuiveren van afvalwater naar het herwinnen van kostbare
grondstoffen uit afvalwater. Afvalwater heeft namelijk het potentieel om als bron te dienen van
nutrienten en chemische energie. Theoretisch is het zelfs mogelijk om een waterzuiveringsinstallatie
energieneutraal te maken. Het organisch materiaal in afvalwater is echter te veel verdund om hoge
effiencies te verkrijgen in methaanproductie door het anaeroob vergistingsproces. Daarom dient het
organisch materiaal in het afvalwater eerst geconcentreerd te worden. Een veelbelovende techologie
om dit te verwezenlijken, is het ‘high-load contact stabilization’ (HiCS) systeem. Het is een ‘high-rate
activated sludge’ (HRAS) system dat ontworpen is als het eerste deel van een tweedelig
actiefslibsysteem. Het HiCS systeem wordt gekarakteriseerd door een hoge slibbelasting (>2 g bCOD
g-1 VSS d-1), korte slibretentietijden (SRT) (<3 dagen) en een ‘feast-famine’ regime. Deze
omstandigheden zijn ideaal voor de natuurlijke selectie van micro-organismen die het substraat snel
kunnen sorberen en accumuleren. De optimalisatie van het HiCS systeem werd uitgevoerd door acht
reactoren te laten lopen op laboschaal met verschillende SRT, contacttijden (tC) en stabilisatietijden
(tS), met als doel maximale herwinning van organisch materiaal te bereiken. Gestandaardiseerd
synthetisch afvalwater werd gebruikt als influent voor de reactoren. De prestatie van de HiCS
reactoren werd geëvalueerd op basis van verwijdering van organisch substraat, slibopbrengst en
hoeveelheid respiratie. Daarnaast werden de hoeveelheid en samenstelling van de ‘extracellular
polymeric substances’ (EPS) opgevolgd om een inschatting te maken van hoe dit een invloed heeft op
de prestaties van het systeem. Ook werd de opslag van polyhydroxybutyraat (PHB) in het slib
gemeten en gekarakteriseerd. De hoogste COD verwijderingsefficientie van 65 % werd behaald door
de reactor met een SRT van 1.31 dagen en een tC:tS van 15:40 min. Het slib in deze reactor vertoonde
ook het meeste opslag van PHB met een concentratie van 21 mg PHB g-1 VSS. De HiCS reactor met
een SRT van 0.46 dagen en dezelfde tC:tS behaalde echter de hoogste slibopbrengst (0.737 kg VSS kg-1
CODremoved), en behaalde dus ook de hoogste netto herwinning van organisch materiaal. Er werd ook
aangetoond dat de eiwitconcentratie in het EPS een grotere rol speelt dan de
koolhydraatconcentratie tijdens het sorberen van substraat en het flocculeren van het slib. Hoewel
de prestaties van het HiCS systeem nog bevestigd moeten worden bij het behandelen van echt
afvalwater, toont het een groot potentieel als concentreertechniek van afvalwater om
energieneutrale waterzuivering te bereiken.
Page | xi
Contents
Acknowledgements ..........................................................................................................iv
List of Abbreviations .........................................................................................................vi
List of Symbols ................................................................................................................ viii
Abstract (Eng.) ...................................................................................................................x
Abstract (Ned.) .................................................................................................................xi
Contents ...........................................................................................................................xi
List of Figures................................................................................................................... xv
List of Tables .................................................................................................................. xvii
Introduction ..................................................................................................................... 1
I. Literature Study ............................................................................................................. 3
1. Resource scarcity – A present and future threat ............................................................ 3
2. Wastewater treatment – A fully developing sector ........................................................ 5
2.1 Conventional activated sludge ...................................................................................................... 5
2.2 Sustainability issues and potential ................................................................................................ 6
2.3 From ‘Wastewater Treatment Plant’ to ‘Resource recovery Plant’ .............................................. 8
3. High-rate activated sludge........................................................................................... 11
3.1 Concentrating wastewater .......................................................................................................... 12
3.1.1 Biosorption and -flocculation ............................................................................................... 13
3.1.2 Intracellular storage of compounds ..................................................................................... 15
3.1.3 Influence of the sludge retention time ................................................................................ 15
3.3 The Contact Stabilization process ............................................................................................... 16
4. Recovering energy - Anaerobic digestion ..................................................................... 18
5. Research hypotheses .................................................................................................. 20
II. Materials and Methods ............................................................................................... 21
1. Reactors...................................................................................................................... 21
1.1 HiCS reactor setup ....................................................................................................................... 21
1.1.1 Reactor materials ................................................................................................................. 21
1.1.2 SBR cycle ............................................................................................................................... 23
1.1.3 Inoculum ............................................................................................................................... 25
1.2 Flows............................................................................................................................................ 25
Page | xi
1.2.1 Influent ................................................................................................................................. 25
1.2.2 Waste and effluent ............................................................................................................... 26
1.3 Operational conditions ................................................................................................................ 27
1.3.1 Sludge retention time ........................................................................................................... 27
1.3.2 Sludge loading rate ............................................................................................................... 27
1.3.3 Temperature......................................................................................................................... 28
1.3.4 Dissolved oxygen level.......................................................................................................... 28
1.3.5 pH value ................................................................................................................................ 28
1.4 Daily measurements .................................................................................................................... 28
1.4.1 Reactor performance control ............................................................................................... 28
1.4.2 Sampling ............................................................................................................................... 29
1.5 Intensive measurement campaigns ............................................................................................ 29
2. Abiotic batch tests ...................................................................................................... 30
2.1 Determination optimal coagulant and concentration ................................................................ 30
2.2 COD removal and recovery ......................................................................................................... 30
3. Analyses ..................................................................................................................... 31
3.1 Chemical oxygen demand ........................................................................................................... 31
3.2 Biochemical oxygen demand....................................................................................................... 31
3.3 Total and volatile suspended solids ............................................................................................ 32
3.4 Sludge volume index ................................................................................................................... 32
3.5 Extracellular polymeric substances ............................................................................................. 32
3.5.1 EPS extraction ....................................................................................................................... 33
3.5.2 Protein concentration .......................................................................................................... 33
3.5.3 Carbohydrate concentration ................................................................................................ 34
3.5.4 Total and volatile solids ........................................................................................................ 34
3.6 Polyhydroxybutyrate analysis...................................................................................................... 35
3.7 IC measurements......................................................................................................................... 35
4. Calculations ................................................................................................................ 36
4.1 COD removal efficiency ............................................................................................................... 36
4.2 Observed yield ............................................................................................................................. 36
4.3 COD balance ................................................................................................................................ 36
5. Statistical analyses ...................................................................................................... 38
III. Results ....................................................................................................................... 39
1. Operational parameters .............................................................................................. 39
1.1 Dissolved oxygen - Temperature - pH ......................................................................................... 39
1.2 Sludge retention time - Waste flow rate - Biomass concentration ............................................. 40
Page | xii
1.3 Loading rate - Hydraulic retention time ...................................................................................... 42
2. HiCS performance ....................................................................................................... 42
2.1 COD removal................................................................................................................................ 42
2.2 Observed yield ............................................................................................................................. 44
2.3 COD balance ................................................................................................................................ 45
2.4 Ion chromatography .................................................................................................................... 46
3. Extracellular polymeric substances and settleability .................................................... 46
3.1 Protein and carbohydrate concentration .................................................................................... 47
3.2 Protein-carbohydrate ratio and Sludge volume index ................................................................ 49
4. Substrate storage - Polyhydroxybutyrate..................................................................... 51
5. Intensive measurement campaigns ............................................................................. 52
6. Abiotic batch tests ...................................................................................................... 54
6.1 Determination optimal coagulant and concentration ................................................................ 54
6.2 COD removal and recovery ......................................................................................................... 55
IV. Discussion.................................................................................................................. 57
1. HiCS characteristics ..................................................................................................... 57
2. HiCS performance ....................................................................................................... 58
2.1 COD removal................................................................................................................................ 58
2.2 Sludge yield.................................................................................................................................. 60
2.3 Energy recovery ........................................................................................................................... 60
2.4 COD balance ................................................................................................................................ 61
2.5 Phosphate removal...................................................................................................................... 64
2.6 Summary HiCS performance ....................................................................................................... 64
3. EPS characterization and influence on HiCS performance ............................................. 65
4. Substrate storage - Polyhydroxybutyrate..................................................................... 66
5. Intensive measurement campaigns ............................................................................. 67
General conclusion ......................................................................................................... 69
Outreach ........................................................................................................................ 71
References ...................................................................................................................... 73
Addendum...................................................................................................................... 79
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Page | xiv
List of Figures
Figure 1.1: Major pathways in the cities of the present and in the cities of the future
(Verstraete & Vlaeminck, 2011)................................................................................... 4
Figure 1.2: Example of a fully equipped wastewater treatment plant
(Verstraete & Vlaeminck, 2011)................................................................................... 5
Figure 1.3: Biological nitrogen conversions
(Kampschreur et al., 2009) .......................................................................................... 7
Figure 1.4: Scheme of recovering energy in an energy-efficient WWTP
(Redrafted after Wett et al., 2007) .............................................................................. 8
Figure 1.5:
Scheme of centralized ZeroWasteWater approach
(Redrafted after Verstraete & Vlaeminck, 2011, copyright LabMET) .......................... 9
Figure 1.6: Scheme of partial Nitritation/Annamox
(Lackner et al., 2014) ................................................................................................. 10
Figure 1.7: Schematic representation of the reactor configurations of the conventional
activated sludge, contact stabilization, high-rate conventional activated
sludge and high-rate contact stabilization systems
(Meerburg et al., 2015) .............................................................................................. 11
Figure 1.8: Hypothetical mechanism of BOD removal
(Redrafted after Bunch & Griffin, 1987) .................................................................... 14
Figure 1.9: Process flowchart of the sludge processing steps
(Appels et al., 2008) ................................................................................................... 18
Figure 1.10: Subsequent steps in the anaerobic digesition process
(Appels et al., 2008) ................................................................................................... 19
Figure 2.1: Two parallel lab-scale SBR ran in HiCS mode............................................................. 21
Figure 2.2: Close-up of lab-scale SBR ........................................................................................... 22
Figure 2.3: Scheme of a single SBR .............................................................................................. 22
Figure 2.4: Scheme of a six-phasic HiCS SBR cycle ....................................................................... 24
Figure 2.5: Orthogonal design HiCS reactors ............................................................................... 24
Page | xv
Figure 2.6: Schematic representation of the COD balance ......................................................... 38
Figure 3.1: HiCS reactors in operation (waste phase).................................................................. 39
Figure 3.2: Biomass concentration and VSS/TSS ratio for HiCS reactors ..................................... 41
Figure 3.3: COD removal efficiencies and volumetric removal rates of HiCS reactors................ 43
Figure 3.4: The observed yield for each HiCS reactor .................................................................. 44
Figure 3.5: COD balance of each HiCS reactor ............................................................................. 45
Figure 3.6: Sludge protein and carbohydrate concentrations of LB- and TB-EPS fraction
for each HiCS reacto................................................................................................... 47
Figure 3.7: Proteins over carbohydrates ratio and the SVI for each HiCS reactor ...................... 50
Figure 3.8: Proteins over carbohydrates ratio as a function of the SVI ....................................... 50
Figure 3.9: PHB concentration in sludge of each HiCS reactor .................................................... 51
Figure 3.10: Follow-up of DO level from the onset of the stabilization phase for each HiCS
reactor........................................................................................................................ 53
Figure 3.11: Determination of optimal coagulant and concentration for sedimentation
SYNTHES ..................................................................................................................... 54
Figure 3.12: Setup triplicate abiotic batch test before and after 40 min settling ......................... 55
Figure 3.13: Removal efficiencies of primary settlers with and without coagulant In
comparison with the HiCS reactor with an SRT of 0.46 days and a tC:tS of
15:40 min ................................................................................................................... 56
Figure 3.14: COD balances of primary settlers with and without coagulant In comparison
with the HiCS reactor with an SRT of 0.46 days and a tC:tS of 15:40 min .................. 56
Figure 4.1: Comparison COD balances of SBR and CSTR (De Smedt, 2015) HiCS reactors .......... 63
Page | xvi
List of Tables
Table 1.1: Average removal efficiencies of Flemish WWTP in 2013
(Vlaamse Milieumaatschappij, 2013) ............................................................................. 6
Table 2.1: Working volumes, flow rates and duration of each phase in SBR cycle ...................... 23
Table 2.2: Composition of concentrated SYNTHES
(Aiyuk & Verstraete, 2004) ........................................................................................... 26
Table 2.3: Type and amount of daily samples............................................................................... 29
Table 2.4: COD fractions and particle sizes ................................................................................... 31
Table 3.1: Dissolved oxygen, temperature and pH follow-up....................................................... 40
Table 3.2: Comparison of intended and actual SRT and waste flow rates.................................... 40
Table 3.3: Loading rates (volumetric and specific) and hydraulic retention times of HiCS
reactors......................................................................................................................... 42
Table 3.4: Coagulant concentration and transmission rates ........................................................ 55
Table 4.1: Prediction of energy recovery for each HiCS reactor ................................................... 61
Table 4.2: Summary of most important performance indicators .................................................. 64
Table A1: Matrix of correlation coefficients between parameters .............................................. 79
Page | xvii
Page | xviii
Introduction
Typically, municipal wastewater is treated with conventional activated sludge (CAS) processes. These
conventional wastewater treatment plants aim at meeting the discharge standards by removing
organic carbon by oxidation, removing nitrogenous matter by nitrification/denitrification and
lowering the level of phosphates by means of chemical or enhanced biological phosphorus removal.
However, the CAS process has its downsides, such as a high energy demand, production of
greenhouse gases and wasting of valuable recourses. In recent years sustainable development has
gained an increasing amount of attention and we recognize that resources and energy are becoming
scarcer. In order to become more sustainable, wastewater treatment must reach beyond nutrient
removal and aim for resource recovery. In other words, a transition has to be made from a
‘wastewater treatment plant’ to a ‘resource recovery plant’.
The potential energy available in raw wastewater exceeds the electricity demand to operate a
wastewater treatment plant by at least a factor nine. Therefore, it is theoretically feasible to improve
a wastewater treatment plant in such a way that it becomes energetically self-sufficient. Recovery of
energy from wastewater is most often achieved via anaerobic digestion to produce methane as a
form of useful chemical energy. However, in order to make the anaerobic digestion self-sufficient, at
least a tenfold pre-concentration of the organic matter in the wastewater has to be achieved. To
achieve this, several candidate technologies have been proposed like centrifugation, filtration and
especially the chemically enhanced primary sedimentation (CEPT) system. However, neither the
physical separation methods nor CEPT are optimized for removal of dissolved organic matter, which
limits the maximum amount of energy that can be recovered and leaves a considerable fraction of
organics to be treated in subsequent stages. In contrast to these technologies, high-rate activated
sludge (HRAS) systems have the capability to concentrate the particulate and colloidal fraction as
well as the soluble fraction of wastewater by means of biosorption and bio-accumulation.
In this thesis, the high-load contact stabilization (HiCS) process is evaluated as a potential HRAS
system to maximize the capture of organic matter and thus the recovery of chemical energy. The
HiCS process contains an anoxic contact phase at which the sludge is mixed with the influent and a
stabilization phase at which the sludge is aerated. The characterizing high loading rates, short sludge
retention times (SRT) and feast-famine regime are ideal conditions for natural selection of
microorganisms which have fast biosorption and bio-accumulation abilities. The young sludge age
greatly improves the sludge digestion efficiency.
Characterization and optimization of the HiCS process were performed by operating eight lab-scale
HiCS reactors in SBR mode at different SRT, contact times and stabilization times. The reactors were
fed with a synthetic sewage type (SYNTHES), mimicking high-strength domestic sewage. The
performance of the HiCS system was evaluated by the removal of organics from the wastewater and
the recovery of this chemical energy in the sludge. Furthermore, the correlation between the HiCS
performance and the extracellular polymeric substances (EPS) concentration and composition of the
sludge was examined. The protein and carbohydrate concentrations of the EPS and especially the
ratio between the two are thought to be correlated to the settleability of the sludge. Finally, the
Page | 1
storage of carbonaceous substrates was measured by determining the concentration of
polyhydroxybutyrate (PHB) that is present in the sludge. This storage response is believed to be
triggered by the short SRT, contact times and feast-famine regime of HiCS system. To acquire a
dataset of about twenty data points, near-daily measurements were performed during a period of
about four weeks.
This thesis starts with a literature study in which the past, present and future of wastewater
treatment are described. The mechanism and purpose of conventional activated sludge are
explained, together with the downsides of this current approach of treating wastewater. Next, a
conceptual framework to tackle these issues is proposed and the potential of recovering energy and
nutrients from sewage is described. Subsequently, a description of the advantages of concentrating
wastewater and possible technologies is made. A more in-depth look in the different HRAS systems,
and specifically the HiCS system, is done and the mechanisms of how wastewater organics are
concentrated and energy is recovered in these systems are described.
In the following chapters, the research hypotheses are formulated, together with how the
experiments were designed in order to tackle these hypotheses. The design, operational conditions
and follow-up of the HiCS reactors are described and the performed analyses are explained. Finally,
the calculations and statistical analyses are described.
The third chapter comprises the obtained results of the experiments. Here, the follow-up of the
operational parameters is described and the most important performance indicators like the organics
removal and observed yield are looked upon. Furthermore, the results of the EPS and storage
polymer concentrations are described. Finally, the results of the performed abiotic batch test are
described. These results are discussed in the last chapter, before the general conclusions and future
perspectives.
Page | 2
1. Resource scarcity – A present and future threat
I. Literature Study
1. Resource scarcity – A present and future threat
Throughout the world, water scarcity is recognized as one of the main present and future threats to
human activity. As a consequence, water reuse strategies deserve major attention (Fritzmann et al.,
2007). The United Nations predict that by 2050, between two and seven billion people will face
water shortages. Even today, about 80 countries, comprising 20 % of the world population, are
suffering from serious fresh water shortage (United Nations, 2006). This global issue of water scarcity
is not only relevant to arid zones. Continuous population growth, rising standards of living, climate
changes, industrialization, agriculture and urbanization have resulted in fresh water becoming a
limited resource (Verstraete et al., 2009). Water scarcity is often the limiting factor for economic and
social development. Even in countries with sufficient availability of high-quality water, industry and
agriculture have to compete for this resource with households (Verstraete et al., 2009). In the last
decades, an increasing pressure on the use of groundwater has urged water industries to look for
alternative water resources, which should eventually lead to the implementation of closed-cycle
processes in domestic and industrial water supply. As a result, water treatment is not regarded as an
end-of-pipe solution, but as an integral part of the production process (Singh, 2008; Verstraete et al.,
2009).
It first became possible to treat wastewater by chemically breaking it down through the use of
microorganisms and removing the pollutants in the late 19th century (Ardern & Lockett, 1914;
Wiesmann et al., 2006). Initially, the goal of wastewater treatment was to protect downstream users
from waterborne diseases and other nuisances caused by poor hygiene. In the last decades, the focus
extended to include pollution abatement, environmental protection and public health protection by
removing biodegradable material, nutrients and pathogens. In the European Union, this is enforced
by means of effluent standards such as the Council Directive 91/271/EEC and Directive 98/15/EEC
concerning urban wastewater treatment and adopted by member states into national effluent
standards like Vlarem II for Flanders (Vlarem II, 1995). Wastewater reclamation is one of the tools
available to better manage the water resources diverted from the natural water cycle to the
anthropic cycle. The way water is reused should always be linked to health protection, engineering
feasibility, public acceptance and the perceived value of water in the community. Accordingly, as far
as water quality can be ensured and maintained responsibly, society should no longer need the
inefficiency of using water only once. Cities of today have a linear resource flow by which a
significant amount of energy, heat and water go to waste. However, the increasing demand creates
an incentive towards processes that are more closed-cycle. Although reuse is described as one of the
main solutions for water scarcity, few countries currently fully implement this practice (Meneses et
al., 2010).
Next to water scarcity, Western countries deal with increasing demands on energy and resources.
The current linear resource flow does not allow recovery of a large fraction of depleting resources
such as energy, nutrients and water (Figure 1.1A). The water is harvested from a natural system,
after which it is conditioned in a drinking water facility and transported to the user. Here, the user
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1. Resource scarcity – A present and future threat
loads the water with low levels of pollutants and heat energy. Finally, the water is transported to a
wastewater treatment facility where it is treated in an energy-demanding, dissipative way (total
decomposition of all molecules) and returned to the natural system. In this scheme, the wastewater
is regarded as a waste stream. However, rapidly developing technologies allow us to extract and
reuse these valuable resources (Verstraete et al., 2009; Verstraete & Vlaeminck, 2011) (Figure 1.1B).
In order to become more sustainable, these resources have to be short-cycled. Moreover, the
sewage compounds which should be seen as a rich ore to mine for energy, mineral plant nutrients
(nitrogen and phosphorus), organic fertilizer and particularly water. By short-cycling, reuse of these
valuable compounds and minimization of waste production become feasible. The main challenge for
the wastewater treatment sector therefore lies in tackling issues concerning resource scarcity, while
making water purification more sustainable and possibly economically profitable (Van Winckel,
2014).
Figure 1.1: Major pathways in the cities of the present (A) and in the cities of the future (B)
(Verstraete & Vlaeminck, 2011).
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2. Wastewater treatment – A fully developing sector
2. Wastewater treatment – A fully developing sector
The discovery of activated sludge by chemists Edward Arden and William T. Lockett, in 1914, was the
start of a new era in the treatment of wastewater (Ardern & Lockett, 1914). In a wastewater
treatment plant, a diverse community of heterotrophic and autotrophic microorganisms, known as
activated sludge, is used to remove the organic matter and nutrients present in wastewaters. The
different microorganisms in the sludge compete for the available nutrients for growth and
maintenance. Under (partially) aerated conditions, these biological processes can be used for several
purposes, such as removing organic carbon by oxidation, removing nitrogenous matter by
nitrification/denitrification and lowering the level of phosphates by means of enhanced biological
phosphorus removal. During these processes, biological flocs are generated that settle easily, so that
the effluent is low in dissolved and suspended material (PaDEP, 2014).
2.1 Conventional activated sludge
In the activated sludge reactor, biodegradable organic carbon (generally referred to as biological
oxygen demand or BOD) and nutrients can be utilized by the bacteria as substrate for growth and
maintenance. Here, the BOD present in the wastewater will be oxidized to CO2 (mineralization), while
another part of the nutrients is used for creation of new biomass (reproduction) (Metcalf & Eddy,
2003).
The process described above is a simplification of the features of a fully equipped biological
wastewater treatment plant today. Conventional activated sludge (CAS) plants are subdivided in
different parts which all have their specific function in treating the incoming wastewater. The most
common CAS plant layout is shown in Figure 1.2. Such plants combine removal of organic carbon
with the removal of nutrients through nitrification/denitrification and enhanced biological
phosphorus removal.
Figure 1.2: Example of a fully equipped wastewater treatment plant (Verstraete & Vlaeminck, 2011).
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2. Wastewater treatment – A fully developing sector
First, the wastewater undergoes pretreatment (usually, a bar screen is used that typically consists of
a series of vertical steel bars spaced between 2.5 to 8 cm apart) to remove all materials that can
easily be collected. This way, damage or clogging to the pumps and sewage lines by large objects is
prevented. If a primary sedimentation stage is present, a primary clarifier is used to settle sludge and
solids that were not retained by the coarse screen. When grease or oils are present, they can rise to
the surface to be skimmed off. The effluent of the primary settler flows to the secondary treatment
basin which is usually partly anaerobic, anoxic and aerobic. Here, BOD and nutrients are removed,
while mainly new sludge, CO2 and N2 are produced. When using a continuous stirred-tank reactor
(CSTR), the working volume of the basin is fixed and the influent flow rate creates a constant
washout of the mixed liquor into the settler. Here, gravitational sedimentation is implemented to
separate the flocculated sludge from the treated water. The effluent water is discharged and a part
of the sludge is recycled back to the reactor. To be able to maintain a certain sludge concentration
and sludge retention time (SRT) in the reactor, another part of the sludge needs to be wasted
(Metcalf & Eddy, 2003). The excess sludge of both primary and secondary settler can be incinerated
for heat recovery or subjected to anaerobic digestion to recover some of the chemical energy as
biogas (Metcalf & Eddy, 2003; Verstraete & Vlaeminck, 2011).
2.2 Sustainability issues and potential
Wastewater treatment installations are mainly evaluated based on the removal efficiencies they
achieve. CAS plants are very efficient in removing organic carbon and nutrients. Table 1.1 shows the
average removal efficiencies of Flemish wastewater treatment plants in 2013 (Vlaamse
Milieumaatschappij, 2013).
Table 1.1: Average removal efficiencies of Flemish WWTP in 2013 (± Standard Error).
BOD
COD
SS
N
Removal efficiency (%)
97.15 ± 0.19 %
88.05 ± 0.35 %
94.47 ± 0.23 %
72.66 ± 0.92 %
P
72.62 ± 1.36 %
*BOD, biological oxygen demand; COD, chemical oxygen demand; SS, suspended solids; N, nitrogen; P, phosphorus
However, less attention is given to performance indicators of sustainable operation of the CAS
plants, emission of greenhouse gases and recuperation of valuable nutrients (Muga & Mihelcic, 2008;
Verstraete et al., 2009). During the conventional nitrification/denitrification process, nitrous oxide
(N2O) is often a byproduct that is emitted to the atmosphere. Nitrous oxide has a 300-fold stronger
global-warming potential than CO2 and because of that these emissions have been shown to
dominate total greenhouse gas emissions from biological wastewater treatment. Emission data show
a huge variation in the fraction of nitrogen that is emitted as N2O, both in lab scale (0 - 95 % of the
nitrogen load) and full scale (0 - 14.6 % of the nitrogen load) studies (Wunderlin et al., 2012). Nitrous
oxide can be produced during several nitrogen conversions (Figure 1.3), but the main source of N2O
production is incomplete denitrification. Also, a minor part of N2O is generated by the chemical
reaction between nitrite and hydroxylamine, formed as a reaction intermediate during ammonium
oxidation (Kampschreur et al., 2009).
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2. Wastewater treatment – A fully developing sector
Figure 1.3: Biological nitrogen conversions. (1) Aerobic ammonia oxidation; (2) Aerobic nitrite oxidation; (3)
Nitrate reduction to nitrite; (4) Nitrite reduction to nitric oxide; (5) Nitric oxide reduction to nitrous oxide; (6)
Nitrous oxide reduction to dinitrogen gas; (7) Nitrogen fixation; (8) Ammonium oxidation with nitrite to
dinitrogen gas (Anammox). Complete nitrification comprises steps 1 and 2, complete denitrification steps 3–6.
(Kampschreur et al., 2009).
Next to the production of this potent greenhouse gas (Global-Warming Potential GWP20 = 280)
(United Nations, 2014), the high energy demand of CAS plants also has a major negative effect on the
environment in terms of greenhouse gas production (Muga & Mihelcic, 2008). Intensive aeration and
pumping make the energy-efficiency and therefore the cost-effectiveness of the overall process
relatively low (Tsagarakis et al., 2003). Aeration constitutes over 60 % of the overall energy
consumption in plants with anaerobic digestion and 70 % in plants without anaerobic digestion of the
produced sludge (Zessner et al., 2010). Besides the high environmental footprint of CAS, recovery of
mineral nutrients is generally not common practice. About 60 - 65 % of the nitrogen is returned to
the atmosphere and 15 -20 % ends up as organic nitrogen in the sludge (Zessner et al., 2010).
In Nodrhein-Westfalen (Germany), 343 wastewater treatment plants, covering 30x106 Population
Equivalents (PE)*, showed an overall electricity consumption of 33 kWh PE-1 year-1, while only 20 % of
this energy was recovered by anaerobic sludge digestion (Müller & Kobel, 2004). Some very energyefficient plants only require 20 kWh PE-1 year-1 of which around 50 % is recovered by anaerobic
sludge digestion. Yet, such plants are exceptional (Verstraete & Vlaeminck, 2011). The total electrical
energy consumption for larger WWTPs (PE > 100,000) in Sweden was shown to be 42 kWh PE-1 in
2005, while Austria only had a consumption of 23 kWh PE-1 in 2004 (Jonasson, 2007). For
comparison, the German energy manual provides a benchmark value of 23 kWh PE-1 (MURL, 1999).
Energy content measurements made by Shizas and Bagley (2004) indicate that for the full-scale
treatment facility examined, the potential energy available in the raw wastewater exceeds the
electricity requirements of the treatment process by a factor of 9.3. This shows that there is space for
improving the energy-efficiency of the current CAS process. In theory, it should be even feasible to
improve a wastewater treatment plant (WWTP) in such a way that it becomes energetically selfsufficient. One method to achieve this is by retaining a sufficiently high fraction of the chemical
*
One population equivalent (PE) is the average amount of wastewater one person produces in one day: 150 liters
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2. Wastewater treatment – A fully developing sector
energy in the wastewater in the sludge itself. A significant part of the soluble organic matter should
preferably also be embodied within the microorganisms, together with the colloidal and particulate
fractions should be settled and adsorbed onto the sludge flocs. Subsequently, the sludge can be
digested to convert the embodied chemical energy to methane for subsequent electricity and heat
production (Wett et al., 2007).
In Figure 1.4, a possible scheme of how the wastewater’s chemical energy content may be efficiently
converted and divided in different energy fluxes during three steps of an energy-neutral or even
energy-positive WWTP. The energy acquired from organic material degradation can be subdivided in
three different categories: thermal energy (ET), synthesis energy (ES) and electrical energy (EE). During
the aerobic metabolism, a large amount of ES is produced, which goes with a high excess sludge
production. The biogenic heat as a byproduct of microbial growth will not have a significant impact
on the overall temperature of the reactor due to dilution. In comparison with the aerobic
metabolism, the anaerobic digestion generates much less ES and thus less biomass is produced. The
major part of the energy content will be captured in methane, which is easily accessible for
incineration and can be transformed by a combined heat and power plant (CHP) to both electrical
and usable thermal energy. These energy products can be recycled to drive the aeration system and
heat the digesters (Wett et al., 2007).
Figure 1.4: Scheme of recovering energy in an energy-efficient WWTP (Redrafted after Wett et al., 2007).
2.3 From ‘Wastewater Treatment Plant’ to ‘Resource recovery Plant’
In terms of sustainable development, resources have to be short-cycled in a safe way (Figure 1.1B).
To fulfill this, Verstraete and Vlaeminck (2011) developed the ZeroWasteWater concept (Figure 1.5)
as a sustainable centralized (order of 100,000 PE and higher) technology train to short-cycle water,
energy and nutrients from sewage, while adequately abating pathogens, heavy metals and trace
organics. The ZeroWasteWater concept provides a ‘second life’ for sewage compounds and
minimizes waste production from wastewater treatment. The pathways of the current water cycle
will have to be downscaled significantly and wastewater should be considered a rich ore to mine for
energy, mineral plant nutrients (nitrogen and phosphorus), organic fertilizer and particularly water
(Verstraete & Vlaeminck, 2011).
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2. Wastewater treatment – A fully developing sector
Figure 1.5: Scheme of centralized ZeroWasteWater approach
(Redrafted after Verstraete & Vlaeminck, 2011, copyright LabMET).
First, a less diluted waste steam is a prerequisite for energy and material recovery. Next to the
prevention of dilution and microbial activity in the sewer itself, higher COD levels can be obtained by
using a primary treatment stage at the entry of the WWTP (Verstraete & Vlaeminck, 2011). The
primary treatment can concentrate the organics by chemical precipitation or by using a high-rate
activated sludge (HRAS) process (see section 3). Subsequently, the concentrated sludge can be
digested anaerobically to biogas at mesophilic temperatures (35 °C). Bolzonella et al. (2005) reported
that the amount of biogas produced per kilogram of volatile solids added, was in the range
0.07 - 0.15 m3 kg-1 VS. With an average of 1.5 kg COD kg-1 VS and the fact that biogas consists for
about 75 vol% of methane (Sialve et al., 2009), the methane yield was in the range of 0.08 - 0.17 m3
kg-1 COD. The produced biogas can be converted to electricity and heat with a CHP installation. This
process can recover a net amount of electricity which is four times higher than the electricity
recovery of the current advanced CAS plants equipped with anaerobic digestion (Siegrist et al., 2008).
After the anaerobic digestion of the concentrated sludge, the remaining ammonia-rich digestate can
be stripped for nitrogen recovery (Verstraete & Vlaeminck, 2011). To achieve this, aeration is
required next to the addition of a base to raise the pH and volatilize the ammonia. Subsequently, an
acid such as H2SO4 needs to be added to recapture the ammonia from the gas. In this way, a 40 %
(NH4)2SO4 solution can be obtained at pH < 3.5 (Siegrist, 1996). Subsequently, the remaining solid
fraction of the ammonia-stripped digestate can be pyrolysed to biochar, which is an excellent and
safe product to improve soil fertility, but also one of the best means to capture carbon and decrease
carbon emission to the atmosphere. Concerning heavy metals, careful origin tracing, monitoring and
treatment, if required, should prevent their short-cycling in sewage sludge and hence biochar. In the
future, the bioavailability of phosphorus in the biochar under field conditions should be
demonstrated (Verstraete & Vlaeminck, 2011).
Following the primary treatment, the residual carbon and nitrogen in the water line should be
aerobically polished, while recovering heat and upgrading to potable water. The relatively low COD/N
ratios are perfect conditions to use a partial nitritation/anammox (PN/A) process to oxidize the
residual nitrogen and carbon (Figure 1.6) (Siegrist et al., 2008; Verstraete & Vlaeminck, 2011). There
are various novel biological nitrogen removal processes that make use of PN/A like: short-cut
nitrification and denitrification, completely autotrophic nitrogen removal over nitrite (Canon) process
and oxygen-limited autotrophic nitrification/denitrification (OLAND). The main advantages of PN/A in
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2. Wastewater treatment – A fully developing sector
comparison with the conventional nitrification/denitrification process are: (1) 25 % lower oxygen
consumption in the aerobic stage implies 60 % energy savings; (2) in the anoxic stage the electron
donor requirement is lower (up to 40 %); (3) denitrification rates with nitrite are 1.5 to 2 times higher
than with nitrate; (4) reduced CO2 emission by 20 % and (5) 33 - 35 % lower sludge production in the
nitrification process and 55 % in the denitrification process. To obtain partial nitritation, the
ammonia oxidizing bacteria (AOB) have to be able to outcompete the nitrate oxidizing bacteria
(NOB). Several process parameters, including dissolved oxygen (DO) concentration, temperature,
sludge retention time (SRT), substrate concentration, aeration pattern and inhibitors, have been
found to inhibit or washout NOB selectively (Peng & Zhu, 2006). Despite these promising methods,
mainstream PN/A has not been realized so far. Difficulties exist to suppress NOB at low nitrogen
concentrations and low temperatures. Also, maintaining oxygen concentrations and pH in the right
range has shown to be problematic (De Clippeleir et al., 2013; Gilbert et al., 2014).
x%
~ 50 %
~ 50 %
Figure 1.6: Scheme of partial Nitritation/Anammox. Percentages: mol% nitrogen (Lackner et al., 2014).
In Austria, two municipal WWTPs (treatment plants of Strass and Wolfgangsee-Ischl) have achieved
near-energy neutrality on domestic wastewater (Nowak et al., 2011; Wett et al., 2007). This
demonstrates the potential to reach energy self-sufficiency at other municipal WWTPs, too. Both
WWTPs take advantage of biological sorption of COD at the A-stage of the 'adsorptionbelebungsverfahren' or A/B-process, followed by a nitrogen treatment with a PN/A process at the Bstage. These processes allow the plant to recover enough energy to meet its own needs for
operation. It is the result of a longstanding and on-going optimization process including optimal
aeration control and control of the aerobic section of the aeration tank to optimize denitrification
and prevent degradation of particulate organic matter that should be rerouted to the anaerobic
digester as much as possible. Yet, the amount of energy that is recovered only accounts for 11 % of
the total caloric energy available in the wastewater, so further improvement in terms of generating
energy from wastewater is certainly possible (Nowak et al., 2011; Wett et al., 2007).
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3. High-rate activated sludge
3. High-rate activated sludge
In HRAS, the term “high-rate” refers to the higher sludge-specific organic loading rate (BX) under
which the reactor operates in comparison with the low sludge loading rates of conventional activated
sludge systems. A CAS system usually operates at a loading rate of around 0.25 kg BOD kg-1 VSS d-1,
while loading rates of HRAS systems range from 2 to 10 kg BOD kg-1 VSS d-1 (Boehnke et al., 1998).
Figure 1.7 shows a schematic representation of two HRAS systems and their low sludge loading rate
counterparts.
Figure 1.7: Schematic representation of the reactor configurations of the conventional activated sludge (CAS),
contact stabilization (CS), high-rate conventional activated sludge (HiCAS) and high-rate contact stabilization
(HiCS) systems, together with recommended values of sludge-specific organic loading rate (organic loading rate,
OLR) and sludge retention time (SRT). Differences in flow rates are qualitatively represented by arrow thickness
(Meerburg et al., 2015).
To meet the discharge standards, usually the HRAS system is the first part of a two-stage activated
sludge system. This first stage is an adsorption stage and is characterized by a very high food-tomicroorganism (F/M) ratio (same as BX). The treated effluent flows to the second stage (the biooxidation stage) where further polishing of organics, together with removal of nitrogen, occurs by
biological oxidation. Biomass compositions in both stages are distinctly different, reflecting their
different conditions of operation. At the adsorption stage, BX ranges from 2 to 10 kg BOD kg-1 VSS d-1,
while the bio-oxidation stage takes place at a much lower BX of less than 0.1 kg BOD kg-1 VSS d-1
(Boehnke et al., 1998).
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3. High-rate activated sludge
HRAS systems are characterized by short sludge retention times (SRT) of 0.1 to 2 days, while SRT of
CAS systems vary between 8 and 20 days. These short SRT go together with a young sludge age and
high bacterial activity. An advantage is that a younger sludge age greatly improves the sludge
digestion efficiency (Bolzonella et al., 2005). Another benefit is that high BOD and COD removal
efficiencies can be obtained at small treatment volumes and the generation of easily settling sludge.
The high removal efficiencies of BOD and COD are achieved primarily because biochemical and
physical reaction mechanisms such as adsorption, flocculation and coagulation are targeted. By
removing BOD by processes such as biological adsorption, the objective to mineralize as little of the
organic compounds as possible can be attained (Boehnke et al., 1998).
3.1 Concentrating wastewater
A requirement to optimize the recovery of energy and nutrients is to produce a waste stream with
low volume and high concentration of organic matter. In freshly produced household wastewater, a
COD level of around 750 mg COD L−1 is typically found. However, because of dilution with storm and
infiltration water in the sewer system, the concentration that reaches the WWTP is much lower. In
average German conditions, for instance, the sewage is diluted by a factor of 3.4 (Brombach et al.,
2005), which brings the COD level to about 225 mg COD L−1. However, the anaerobic digestion of upconcentrated sewage can be self-supporting from a COD level of 5 g L-1 onwards. This corresponds to
a COD concentration factor of at least 10 (Verstraete et al., 2009; Verstraete & Vlaeminck, 2011).
Dilution of wastewater at the sewer level can be prevented through a number of measures.
Implementation of a separate sewer system with a sanitary and a storm sewer can increase organics
concentrations by around 85 % (Brombach et al., 2005). Secondly, improving maintenance can
reduce infiltration of the sewer systems. A third measure is increasing the efficiency in water usage.
Water conservation of only 25 % could already lead to an additional concentration increase of
around 190 %. Finally, addition of ground kitchen waste can increase the COD concentration even
more. Overall, the combination of these four improvements could roughly increase the COD level by
a factor 5 (Verstraete & Vlaeminck, 2011), eliminating the need to concentrate the wastewater at the
WWTP level.
Unfortunately, upgrading sewage collection systems is a gradual process that can take several
decades. Therefore, the implementation of a more direct measure to concentrate the wastewater is
recommended. Some methods that could be considered on the arrival of wastewater in the
treatment plant are centrifugation, filtration or coagulation/flocculation. Another possibility that has
been proposed as a candidate technology to achieve energy-neutral wastewater treatment is
chemically enhanced primary sedimentation (CEPT), followed by anaerobic digestion of the produced
sludge (Diamantis et al., 2013). However, neither the physical methods nor CEPT are optimized for
removal of dissolved organic matter, which limits the maximum amount that can be recovered and
leaves a considerable fraction of organics to be treated in subsequent stages (Meerburg et al., 2015).
On the contrary, using an advanced concentrator at a high sludge loading rate, where biosorption
and bio-accumulation become important processes, will concentrate the particulate and colloidal
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3. High-rate activated sludge
fraction as well as the soluble fraction of wastewater. Biosorption is defined as the physiochemical
process that passively concentrates and binds organic matter onto the biomass. Bio-accumulation on
the other hand is the active metabolic process to absorb organic matter onto and within the biomass
driven by the respiration energy of the microorganisms (Majone et al., 1999).
Leal et al. (2010) already proved that it is feasible to concentrate grey water up to 10 times its
original COD value with a high-loaded membrane bioreactor (MBR). When the domestic wastewater
streams would be separated into black water (urine and faeces with flush water) and grey water
(discharges of hand basins, laundry, shower, bath and kitchen basin), black water could be
considered for the recovery of organic matter (i.e., as energy and soil conditioner) and nutrients (i.e.,
as fertilizer), while grey water has been considered an alternative source of fresh water. Though the
COD load of the grey water is present at low concentrations (in the range of 200–1000 mg L-1), it
represents half of the total COD load of household wastewater. However, the conversion of this COD
in usable energy by anaerobic digestion remained a challenge, because of these low COD values and
a rather large fraction of colloidal COD. To overcome this problem, the organic matter was pretreated by means of bioflocculation to concentrate the COD (see section 3.1.1). By using a highloaded MBR, Akanyeti et al. (2010) already showed that sewage can be concentrated up to 10 times
leading to a concentrate with up to 93 % of suspended COD. Afterwards Leal et al. (2010) used the
same technique to confirm its feasibility for up-concentrating grey water to the same concentration
factor (Akanyeti et al., 2010; Leal et al., 2010).
3.1.1 Biosorption and -flocculation
Biosorption is an all-embracing term that is used to indicate a number of metabolism-independent
processes (physical and chemical adsorption, electrostatic interaction, ion exchange, complexation,
chelation and microprecipitation) taking place essentially at the cell wall and is opposed to oxidation
through anaerobic or aerobic metabolism (biodegradation) (Aksu, 2005). Bunch and Griffin (1987)
postulated that the removal of BOD in activated sludge reactors is a result of three distinct
consecutive processes (Figure 1.8). While this conceptual kinetics curve has been reproduced in
several widely used texts (Benefield & Randall, 1980; Schroeder, 1977), no conclusive data have been
produced to prove its validity.
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3. High-rate activated sludge
Figure 1.8: Hypothetical mechanism of BOD removal (Redrafted after Bunch & Griffin, 1987).
Initially, it is thought that organic compounds of the wastewater become attached to the microbial
flocs through physicochemical adhesion (adsorption). This step is typically fast and generally does not
exceed a few minutes, in contrast with the latter two (Guellil et al., 2001). Next, excretion of
extracellular enzymes results in hydrolysis of the adsorbed compounds so that they detach and
become soluble. This leads to a temporary increase in the BOD concentration, because finally the
degraded compounds are absorbed into the biomass and used for growth and maintenance.
However, the peak related to hydrolysis and absorption has proven to be difficult to detect and has
yet to be confirmed in practice (Bunch & Griffin, 1987).
Now, one can see that biosorption becomes a very important feature of HRAS systems since the
contact time between biomass and wastewater is within the time window of this first stage of the
mechanism proposed by Bunch and Griffin. Next to that, the impact of biosorption becomes more
important with increasing sludge-specific organic loading rates (Tan & Chua, 1997).
Biological sorption of organics by microorganisms and flocculation are believed to be mediated by
the production of extracellular polymeric substances (EPS). The main EPS components are
carbohydrates, proteins, humic substances and nucleic acids (Garikipati, 2005). This EPS composition
is related to the basic functions of EPS: Aggregation of bacterial cells, adherence to surfaces,
formation of flocs and biofilms, cell-cell recognition, protective barrier of the cell, water retention,
enzymatic activities and sorption of exogenous organic compounds and inorganic ions (Tian, 2008).
There is some evidence that the composition and properties (hydrophobicity and surface charge) of
the EPS are more related to sludge flocculation and biosorption than the total EPS concentration (Ye
et al., 2011). While activated sludge usually has a negative surface charge, the important factor
determining the magnitude of this charge is the ratio of carbohydrates to proteins. Shin et al. (2001)
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3. High-rate activated sludge
reported that the surface charge becomes less negative with increasing carbohydrates to protein
ratio (Shin et al., 2001). Cells with higher negative surface charge show more affinity to associate
with positively charged inorganic particles such as Ca2+ and Mg2+. These divalent cations may act as
bridging agents between different cells or between microorganisms and organics (More et al., 2014).
Thus, when a sufficient amount of divalent cations are present, a stronger negative surface charge is
correlated with better sludge settling (Shin et al., 2001).
Additionally, Li and Yang (2007) demonstrated that a differentiation between loosely bound (LB) and
tightly bound (TB) EPS has to be made. They reported that the sludge had a nearly consistent TB-EPS
value regardless of the SRT, while the LB-EPS content decreased with the SRT. Moreover, as the SRT
lengthened, the flocculation and separation improved considerably. These results demonstrate that
the LB-EPS may have a more pronounced effect on the performance of sludge-water separation, than
the TB-EPS. Furthermore, the overproduction of LB-EPS was shown to have a negative effect on
bioflocculation and sludge–water separation. A possible explanation for these observations is that
although EPS is essential to sludge floc formation, excessive EPS in the form of LB-EPS could weaken
cell attachment and the floc structure, which would result in poor bioflocculation, greater cell
erosion and retarded sludge–water separation. (Li & Yang, 2007).
3.1.2 Intracellular storage of compounds
High-load activated sludge systems are very dynamic systems due to their characterizing short SRT
and contact times. Microorganisms typically switch from a dominating growth response to a
dominating storage response when subjected to such very dynamic conditions (Daigger & Grady,
1982). This storage response is characterized by the uptake and conversion of rapidly biodegradable
COD (rbCOD) to typical storage polymers like polysaccharides and polyhydroxyalkanoates (PHA).
Čech and Chudoba (1982) showed that when sludge is subjected to an intermittent feeding regime
(feast-famine), it is more likely to show a storage response. Such a feast-famine regime is typically
applied in contact stabilization or SBR-type systems. They reported that activated sludge,
intermittently fed with glucose, exhibited a glucose accumulation capacity of 600 - 750 mg gglucose-1,
while continuously fed sludge could only store an amount of 174 mg gglucose-1 (Čech & Chudoba, 1983).
Furthermore, PHA production is positively influenced by short SRT, because the system naturally
selects a community that consists of microorganisms that are able to rapidly accumulate PHA.
3.1.3 Influence of the sludge retention time
The sludge retention time (SRT) is an important parameter in any activated sludge process. It
determines the microbial diversity, overall sludge concentration and yield (biomass growth) in the
reactor (Mogens et al., 2008). High SRT are mainly used when the effluent quality is of major
importance. A high SRT is correlated with a great microbial diversity due to a low selective pressure
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3. High-rate activated sludge
on the present microbial community. Because of this, the slower growing nitrifying and denitrifying
organisms are able to grow which makes nitrogen removal possible (Ekama, 2010). Next to that, a
high SRT stimulates the biomass to degrade micropollutants.
However, for high-rate systems like the HiCS system, the aim is to produce as much sludge as
possible and to maximize biogas production to recover a maximal amount of chemical energy.
Lowering the sludge age increases the amount of sludge that needs to be disposed. Next to that, at
lower SRT the fraction of total COD that will be present in the excess sludge will be higher, while the
fraction of influent COD that will be oxidized in the overall process will decrease (Van Haandel & Van
Der Lubbe, 2007). The young, fast-growing sludge type that will be selected for in the system has the
additional advantage that the sludge digestion efficiency is greatly improved (Bolzonella et al., 2005;
Gossett & Belser, 1982).
3.3 The Contact Stabilization process
A well know process that makes use of the biosorption and storage response to achieve removal of
organics in wastewater is the Contact Stabilization (CS) process (Ullrich & Smith, 1951). The CS
process was developed in the 1950’s as the so-called “biosorption process” to be able to cope with
the increasing organic loads the treatment plants had to deal with at that time. Since the biosorption
process, later renamed as the CS process, did not achieve adequate nitrogen removal efficiencies to
comply with ever more stringent effluent standards, it was only implemented in a number of
locations, mainly in the United States (Rittmann & McCarty, 2001). The CS process regained interest
in the scope of the upcoming need for sustainable development. The scientific community
recognized the potential in implementing the CS process in a more sustainable WWTP by exploiting
its ability to concentrate the organic fraction of the wastewater in the activated sludge. Later on, the
development of the high-load contact stabilization process (HiCS) was investigated to utilize the
advantages of CS even more. By applying a higher load, an even greater selection pressure toward
fast uptake of organics is imposed on the microbiological community (Meerburg et al., 2015; Van
Winckel, 2014; Vercamer, 2013). Until recently, only a small number of studies have been performed
on activated sludge processes that can tentatively be identified as HiCS processes (Huang & Li, 2000;
Zhao et al., 2000). However, both studies showed promising results. Huang and Li found that during
the contact phase, rapid adsorption of substrates was achieved and Zhao et al. (2000) stated that a
HiCS system may perform better than HiCAS in terms of substrate removal.
When operated in CSTR mode, the Contact Stabilization process comprises two reactors in contrast
to the single aerated basin of the CAS process; the contact reactor (contactor) and the stabilization
reactor (stabilizer), separated by a sedimentation tank (Figure 1.7A). The sludge in the contactor
receives the wastewater in a near-endogenous state. Due to the small volume of the contactor, the
hydraulic retention time (HRT) is short (30 to 90 minutes) which implies a short contact period
between sludge and fresh wastewater. In this way, organic matter is predominantly removed via
biological sorption and storage. The mixed liquor of sludge and treated wastewater leaving the
contactor is separated in the secondary settler. Here, the effluent flows to a secondary treatment
Page | 16
3. High-rate activated sludge
system to remove the residual carbon and nitrogen to meet the effluent criteria. The biomass is
concentrated and a part is sent to the stabilizer tank which has a bigger volume and therefore a
longer HRT (4 to 6 hours). In this aerated tank with, the return sludge will consume most of the
nutrients it has taken up which ensures the starved, near-endogenous state. This feast-famine
regime will lead to a natural selection of microorganisms which are able to rapidly concentrate the
organics in the wastewater. This suggests that the discarded excess sludge is able to recover a higher
fraction of energy by means of methane production during anaerobic digestion (Liu et al., 2009;
Vasquez et al., 2010).
Since 1972, many studies have been conducted on the CS process and reported that this system can
be highly efficient in organic matter removal with efficiencies of around 80 % (Vasquez et al., 2010).
Sarioglu et al. (2003) showed that the removal efficiency increases when the particulate COD fraction
of an influent domestic wastewater increases. Efficiencies observed during the study were around
82 % (Sarioglu et al., 2003). The ratio between soluble COD and total COD present in the influent is
called the solubility index (SI). So when the SI decreases, the CS process will attain increasing COD
removal efficiencies.
Regular CS plants operate at a specific loading rate of 0.2 - 0.6 kg BOD kg-1 VSS d-1, similar to the CAS
process (0.25 kg BOD kg-1 VSS d-1) (PaDEP, 2014). However, to achieve energy efficient sludge
digestion, the loading rates in CAS and CS plants are too low to sufficiently concentrate the COD in
the waste sludge (Verstraete & Vlaeminck, 2011). Until recently, the HiCS process has not been
characterized profoundly. Zhao et al. (2000) designed a laboratory scale CS system operating at a
higher specific loading rate than a conventional CS system (0.5 - 1 kg BOD kg-1 VSS d-1). Under optimal
conditions, the HiCS reactor had a total COD removal efficiency of 70 - 80 % and a yield coefficient of
approximately 0.79 kg VSS kg-1 COD in contrast to a yield of 0.4 kg VSS kg-1 COD observed in CAS
systems (Zhao et al., 2000). Despite the fact that the applied loading rate is barely too low to be
considered truly high-rate, the results are very promising and impel further investigation on this
topic. The development of a real HiCS reactor as a primary wastewater concentrating technique
becomes feasible.
Page | 17
4. Recovering energy - Anaerobic digestion
4. Recovering energy - Anaerobic digestion
The disposal of sludge is a problem of growing importance, since it now represents up to 60 % of the
current operating costs of a conventional WWTP (Pilli et al., 2011). Furthermore, sludge disposal laws
are becoming stricter (European Commission, 12 June 1986). The sludge must undergo some
treatment in order to reduce its associated volumes, to improve its character and to reduce the
associated health problems and hindrance (Appels et al., 2008). The treatment aims at (1) reducing
the water content of the raw sludge, (2) transforming the high putrescible organic matter into a
relatively stable and inert organic and inorganic residue, and (3) meeting the disposal acceptance
regulations. The common sludge disposal techniques such as incineration and landfill, used over the
years, are neither economical nor sustainable as they generate huge amounts of greenhouse gases.
Therefore, researchers concluded that anaerobic digestion (AD) is a cost-effective, efficient and
sustainable alternative sludge treatment technique. Some benefits of the AD technology are mass
reduction, odor removal, pathogen reduction, less energy use, flexibility toward waste composition
and most importantly the energy recovery from biogas (Pilli et al., 2015).
As stated before, by implementing up-concentration techniques such as HiCS, a high-strength stream
is generated. This concentrated stream can be considered as valuable if the waste-to-energy strategy
is applied. In this respect, anaerobic digestion qualifies in terms of recovery and the possibility to
subsequent deal with the residual solids (Verstraete et al., 2009). The most common process
flowchart of the sludge-processing steps is shown in Figure 1.9. The sludge of the primary and
secondary settler is generally combined and thickened to undergo further treatment. The thickening
occurs by gravity, flotation or belt filtration. This process can reduce the amount of sludge to as little
as a third of its initial volume. The separated water usually is recycled to the influent of the WWTP.
After this, the sludge is subjected to the AD process which further transforms the organic matter into
biogas (60 - 70 vol% of methane), thereby also reducing the amount of final sludge solids for disposal
(Appels et al., 2008).
Figure 1.9: Process flowchart of the sludge processing steps (Appels et al., 2008).
Page | 18
4. Recovering energy - Anaerobic digestion
As shown in Figure 1.10, the AD of organic material comprises four stages: hydrolysis, acidogenesis,
acetogenesis and methanogenesis. AD is a slow and complex process which requires strict anaerobic
conditions, a high retention time and a large digester volume to proceed. It depends on the
coordinated activity of a complex microbial association. In particular, the first step in the AD process,
hydrolysis, is considered as rate-limiting (Pilli et al., 2015). During the hydrolysis process, both
insoluble organic materials and high molecular weight compounds such as lipids, polysaccharides,
proteins and nucleic acids, are degraded to soluble, low molecular weight compounds. These
compounds are further split in volatile fatty acids (VFA), ammonia, CO2, H2S and other by-products at
the acidogenesis step. The higher organic acids and alcohols are further digested by acetogenesis to
produce mainly acetic acid as well as CO2 and H2. Finally, methane is produced by two groups of
methanogenic bacteria: the first group splits acetate into methane and carbon dioxide and the
second group uses hydrogen as electron donor and carbon dioxide as acceptor to produce methane
(Appels et al., 2008).
Figure 1.10: Subsequent steps in the anaerobic digestion process (Appels et al., 2008).
The biogas produced from the anaerobic digester is treated to remove H2S before valorizing the
biogas with a CHP unit. The energy transformation from biogas towards electricity obeys to the
second law of thermodynamics and the yield of electricity is lower than 100 %, currently around
40 %. The heat that is produced is used to maintain the digester temperature and for post-treatment
purposes such as drying and/or evaporation (Verstraete et al., 2009). In spite of the major
advantages of the AD technology, this post-treatment is necessary in order to adapt the produced
effluent stream to comply with the usual discharge standards.
Page | 19
5. Research hypotheses
5. Research hypotheses
The high-load contact stabilization (HiCS) process is a type of HRAS system which is designed to serve
as the first part of a two-stage activated sludge system. The purpose of the HiCS process is to
concentrate the organic matter in the form of sludge and thus maximize potential recovery. The
characterizing feast-famine regime of the system aims at selecting microorganisms which have fast
biosorption and bio-accumulation abilities. The aim of this thesis is to characterize and optimize the
HiCS system by running eight lab-scale reactors at different SRT, contact times (tC) and stabilization
times (tS). Next to the experiments with the HiCS reactors, an abiotic batch test was performed to
characterize the behavior of the synthetic influent in the absence of sludge. In other words, the
performance a primary settler was examined, both with and without an optimized concentration of
coagulant. The following research hypotheses are formulated:

A higher SRT in the HiCS system is correlated to higher EPS concentrations and results in a
higher protein/carbohydrate ratio in the EPS. The tC is negatively correlated to EPS
production, while the tS is positively correlated.
o
o
The protein/carbohydrate ratio of the EPS is positively correlated to sludge separation and
COD removal.
The influence of LB-EPS on sludge separation and COD removal is more pronounced than
the influence of TB-EPS.

The SRT and tC correlate positively with the storage of polyhydroxybutyrate (PHB) storage in
the sludge, while a negative correlation exists between the tS and the PHB storage .

The removal efficiencies of the particulate, colloidal and soluble COD are positively
correlated to the SRT, tC and tS of the HiCS reactor.

An optimal SRT, tC and tS as design parameters of the HiCS system can be found in terms of
sludge separation, COD recovery and sludge yield.

The optimal HiCS reactor performs better in terms of COD removal and recovery compared
to a primary settler with and without the coagulant.
Page | 20
1. Reactors
II. Materials and Methods
1. Reactors
1.1 HiCS reactor setup
1.1.1 Reactor materials
The different experiments to optimize the HiCS process were all operated in lab-scale sequencing
batch reactor (SBR) configuration. Each time, two SBR, with a different SRT, contact time (tC) or
stabilization time (tS), were run in parallel. Figure 2.1 and Figure 2.2 show pictures of the reactor
setup before inoculation. In Figure 2.3, a scheme of the SBR and its in- and outputs is presented. Both
reactors had a working volume of 3 L and mixing occured with magnetic stirrers. Depending on the
setup, pressured air or small aquarium air pumps were used to acquire an air flow rate of 5 L air min-1
during the stabilization phase.
Five or six peristaltic pumps were used (Prominent, Masterflex and Watson Marlow), depending on
the operational conditions. These pumps, together with the magnetic stirrers and aeration pumps
were regulated by a homemade digital timer driven by Arduino soft- and hardware (Arduino, 2015).
The timer was programmed to turn the equipment on and off according to the phase of the SBR cycle
(see section 1.3).
Figure 2.1: Two parallel lab-scale SBR ran in HiCS mode.
Page | 21
1. Reactors
Figure 2.2: Close-up of lab-scale SBR.
Figure 2.3: Scheme of a single SBR.
Page | 22
1. Reactors
1.1.2 SBR cycle
Figure 2.4 represents a scheme of the six different phases of the SBR cycle that was used to simulate
the HiCS reactor. After inoculation, a start-up phase of at least three times the SRT of the reactors
was required to reach a steady state. Once in steady state, the reactors were operated and
maintained for a period of three to four weeks to collect at least 20 data points by taking near-daily
samples. By variation of the different working volumes and flow rates during the SBR phases, shown
in Table 2.1, different SRT and contact and stabilization times could be established.
Reactor
#
1
Table 2.1: Working volumes, flow rates and duration of each phase in SBR cycle. tC = tfill + twaste
SRT
Vcontact
Vstabilization
Vwaste
QI
QE
QW
-1
-1
-1
(days)
(L)
(L)
(L)
(L d )
(L d )
(L d )
0.5
3.0
1.42
2.59
21.64
15.36
5.60
2
3
1.0
0.25
3.0
3.0
1.42
1.47
2.82
2.14
21.64
21.00
18.43
9.21
2.52
11.79
4
2.5
3.0
1.47
2.95
21.00
20.27
0.73
5
0.5
3.0
1.53
2.75
22.27
17.74
4.53
6
0.5
3.0
1.53
2.75
22.27
17.74
4.53
7
1.0
3.0
1.62
2.85
20.91
18.50
2.41
8
1.0
3.0
1.62
2.85
20.91
18.50
2.41
Reactor
#
1
tStabilization
(min)
40
tfill
(min)
10
twaste
(min)
5
tsettle
(min)
40
tdecant
(min)
5
tidle
(min)
5
ttotal
(min)
105
2
3
40
40
10
10
5
5
40
40
5
5
5
5
105
105
4
40
10
5
40
5
5
105
5
40
6
2
40
5
2
95
6
15
13
2
40
5
20
95
7
8
40
15
6
13
2
2
40
40
5
5
2
20
95
95
The HiCS reactors were operated in such a fashion that each reactor differed from another by only
one parameter (SRT, tC or tS), so that changes in reactor performance could be attributed to a change
in one specific operational parameter. Figure 2.5 is a representation of the orthogonal design of the
reactors. The first four SBR were operated at the same tC and tS, while the SRT was set at 0.25, 0.5, 1
and 2.5 days. As an SRT of 0.5 days showed the most promising results at a tC of 15 min and a tS of 40
min, these latter two parameters were changed to define the optimal working conditions. The last
pair of reactors was run at the same tC:tS at an SRT of 1 day to verify that the effect of changing the tC
and tS is the same for both SRT. If not, a possible interaction between these three parameters could
be established.
Page | 23
1. Reactors
Figure 2.4: Scheme of a six-phasic HiCS SBR cycle: 1. Contact phase: Anoxic filling with Synthetic influent, while
mixing with stirrer - 2. Waste phase: Part of the enriched sludge is harvested - 3. Settling phase: Stirring stops
and sludge aggregates and sediments gravitationally - 4. Decantation phase: Effluent without sludge is
decanted from the reactor - 5. Idle phase: Transitional phase and compensation for different contact and
stabilization times so that both reactors have same total cycle duration - 6. Stabilization phase: Aerated feastfamine period.
Figure 2.5: Orthogonal design of HiCS reactors one to eight. See Table 2.1 for detailed description of reactors.
Page | 24
1. Reactors
1.1.3 Inoculum
Every reactor was inoculated with sludge from the WWTP of Nieuwveer, Breda (NL), which is
operated as an A/B-process (Boehnke et al., 1998). The sludge was stored at 4°C and used within 48h
of collection. After running the HiCS reactor with SYNTHES for at least one cycle, 500 mL A-sludge
and 500 mL B-sludge were inoculated during the stabilization phase of the SBR-cycle. A period of
three times the SRT of the HiCS reactor was assumed to be sufficient to reach steady state.
1.2 Flows
1.2.1 Influent
The pumping of the influent was controlled by a level controller which was set at the maximum
working volume of 3 L. The reactor was operated with a synthetic sewage type (SYNTHES), mimicking
high-strength domestic sewage, developed by Aiyuk and Verstraete (2003). The composition of the
concentrated SYNTHES is given in Table 2.2. To be used in the SBR, this concentrated SYNTHES has to
be diluted tenfold to obtain an estimated total COD (CODtot) of 800 mg L-1 which corresponds to highstrength wastewater (Metcalf & Eddy, 2003). The COD:N:P ratio of SYNTHES was expected to be
30:3:1, which is comparable to the 33:3:1 for natural sewage. A broad spectrum of other chemical
compounds and trace metals which are important for bacterial growth is also present in the
SYNTHES.
The concentrated SYNTHES was prepared in batches of 15 to 40 L. To prevent sedimentation of the
particulate matter and creaming of the soya oil as much as possible, a top-stirrer in the SYNTHES
vessel continuously homogenized the mixture. To accomplish a tenfold dilution of the concentrated
SYNTHES arriving as influent in the SBR, a separate tap water pump was set at a flow rate that was
nine times higher than the flow rate of the concentrated SYNTHES.
The flow rate of the influent was not monitored due to practical limitations. A constant flow rate as
shown in Table 2.1 was assumed. This assumption is valid because the influent was controlled by a
level controller as can be seen in Figure 2.3. To verify that the concentrated SYNTHES was correctly
diluted ten times, a periodical COD measurement of the concentrated and diluted SYNTHES was
performed.
Page | 25
1. Reactors
Table 2.2: Composition of concentrated SYNTHES (Aiyuk & Verstraete, 2004). *Estimated parameters.
-1
Component
Amount (mg L )
Chemical compounds
Urea
1600
NH4Cl
200
Na-acetate.3H2O
2250
Peptone
300
MgHPO4.3H2O
500
K2HPO4.3H2O
400
FeSO4.7H2O
100
CaCl2
100
Food ingredients
Starch
Milk powder
Dried yeast
Soy oil
Trace metals
Cr(NO3)3.9H2O
CuCl2.2H2O
MnSO4.H2O
NiSO4.6H2O
PbCl2
ZnCl2
Overall parameters*
CODtotal
CODsoluble
CODparticulate
pH
2100
2000
900
500
15
10
2
5
2
5
8000
2500
5500
7.1
1.2.2 Waste and effluent
The fraction of the reactor content that was removed during the waste and decant phase was
controlled by height. The tubing of the pump that removed the fraction was placed in such a way
that no more than the correct amount of suspension could be decanted. As an extra verification, the
wasted fraction was collected in calibrated vessels to check the waste flow rate on a near-daily basis.
To correct for the amount of waste that was sampled directly from the reactor during the waste
phase, the sampled volume was added to the wasted volume in the calculations.
Page | 26
1. Reactors
1.3 Operational conditions
1.3.1 Sludge retention time
By operating the HiCS reactors at different SRT, the aim was to find an optimal SRT at which the
production of sludge is as high as possible, and thus a maximal amount of chemical energy can be
recovered.
Reactors 1 to 4 were operated with the SRT as the main variable as can be seen in Table 2.1. The SRT
was used as a design parameter following Equation 2.1. Here, the SRT is defined as the ratio
between the sludge mass in the reactor system (XRVR) and the sludge mass that leaves the system per
day (XWQW + XEQE). In this equation, the reality that there is no perfect sludge separation during the
settling phase is taken into account by incorporating the fraction of the sludge that is removed during
the decantation phase. Note that in this SBR setup, wasting was performed during the contact phase,
which implies that the reactor sludge concentration is equal to the concentration of wasted sludge
(XR = XW).
( )
(Eq. 2.1)
-1
-1
*X = sludge concentration (g L ); V = volume (L); Q = flow rate (L d ) R = reactor; W = waste; E = effluent
Note: Reactor volume = 3 L
1.3.2 Sludge loading rate
The sludge-specific organic loading rate (BX) is defined as the amount of substrate given each day to
the microbial community. The BX is expressed as g COD g-1 VSS d-1. The initial BX for the design of each
reactor was chosen to be higher than 2 g bCOD g-1 VSS d-1, because the HiCS system was operated as
a high-rate activated sludge (HRAS) system. According to Meerburg et al. (2015), the loading rate of a
HiCS system should range between 2 to 10 kg bCOD kg-1 VSS d-1.
To verify this parameter during operation, Equation 2.2 was used. Here SIQI is the amount of COD
that is added each day to the sludge mass in the reactor (XRVR).
(
)
-1
(Eq. 2.2)
-1
*S = substrate concentration (g COD L ); Q = flow rate (L d ); I = influent
Page | 27
1. Reactors
1.3.3 Temperature
For this laboratory scale setup of the HiCS reactor, the room temperature was controlled at a
constant 15 ± 0.2 °C, which is about the average outdoor temperature in Western Europe. However,
in reality the activated sludge plant is subjected to the daily and seasonal temperature changes. The
reaction rate of every biological process is temperature-dependent. Therefore, the temperature can
alter the maximum growth rate (µmax) and decay rate (kd) of the present microorganisms. The
biomass yield depends on both of these parameters and will decrease with increasing temperature
as especially kd increases significantly. Up until a certain level, a lower temperature is therefore
desirable for the HiCS system, since maximal sludge production is prioritized (Metcalf & Eddy, 2003).
1.3.4 Dissolved oxygen level
During every phase of the SBR cycle, except the stabilization phase, the dissolved oxygen (DO) level
was approximately zero. In these phases the aeration was shut down to achieve anoxic conditions.
When the stabilization phase began, the aeration system was switched on and an average flow rate
of 5 L air min-1 was delivered. The air flow rate should be sufficiently high to keep the DO level above
1 mg O2 L-1 so that the HiCS system is operated under non-oxygen limited conditions during the
aeration phase. However, the air flow rate has to be moderated to prevent that the sludge
experiences stress due to high shear forces. Furthermore, operational costs may be brought down by
limiting air flow rates.
1.3.5 pH value
Originally the HiCS reactors were designed to be controlled between a pH of 7.85 and 8.15 by an
automatic pH-controller and -probe. However, due to technical issues, the pH-controller was not able
to maintain this correct pH range in the reactors. Because of this, we decided to control the pH
manually (C5010, Consort). A near-daily pH control was performed to verify that the pH value of the
HiCS reactor remained between the acceptable boundaries of 7.75 and 8.25. If these boundaries
were exceeded, some HCl-solution (0.2 M) or NaOH-solution (0.2 M) was added to adjust the pH.
1.4 Daily measurements
1.4.1 Reactor performance control
Several times a day, a verification of the timing of the SBR cycle was performed by checking if the
different phases started and ended at their correct point in time. The reactor walls were cleaned on a
Page | 28
1. Reactors
near-daily basis and the pH of the reactors was maintained manually between 7.75 and 8.25. Also,
the pH of the concentrated SYNTHES and the tap water was checked on a near-daily basis. Besides
that, a DO meter (HQ 30d, Hach-Lange) was used to check the DO level during the stabilization phase
and the air flow rate was adjusted back to 5 L air min-1 if a drop or increase was noticed. In addition,
the working volumes of the HiCS reactor after wasting, decanting and adding influent were also
checked periodically. Finally, the wasted volume of reactor content and the consumed amount of
concentrated SYNTHES were supervised.
1.4.2 Sampling
To be able to achieve a high power for the statistical comparison of the different HiCS reactors, the
aim was to acquire approximately twenty data points during steady state. From different phases of
the SBR cycle, daily samples were taken to perform COD, TSS, VSS and ion chromatography (IC)
measurements and also a fraction of the wasted sludge was used to extract LB-EPS, TB-EPS and PHB.
For one reactor, Table 2.3 gives an overview of the type of sample that is taken and the amount that
is needed to be able to perform each analysis.
Table 2.3: Type and amount of daily samples. n.a.: not applicable.
*An excess of sample was taken for storage to repeat measurements if necessary.
Volume needed for analysis (mL)
Sample type
Phase
COD
TSS & VSS
IC
EPS + PHB Total Volume (mL)*
Effluent
Decant
40
40
10
n.a.
100
Influent
Sludge
Contact
Waste
40
10
40
10
10
n.a.
n.a.
10
100
50
1.5 Intensive measurement campaigns
For each of the HiCS reactors, an intensive measurement campaign was performed. During this
campaign a complete SBR cycle was characterized by taking several samples during each of the
phases, with the exception of the settling and idle phase. Respectively, during the contact phase and
stabilization phase, 3 - 5 and 4 - 6 sludge samples were taken, depending on the tC and tS. Also, an
influent sample and an effluent sample were taken. From the sludge samples, the TSS, VSS, COD, EPS
and PHB concentrations were determined, while only the TSS, VSS and COD concentrations of the
influent and effluent samples were determined. Next to these measurements, a 60 min follow-up of
the DO level was performed in which the full length of the stabilization phase was included. The DO
level remained zero during the other phases of the SBR cycle since no aeration was applied there.
Page | 29
2. Abiotic batch tests
2. Abiotic batch tests
The objective of the abiotic batch tests, performed with the synthetic influent (SYNTHES), was to
characterize its behavior in the absence of sludge. In other words, the performance of the SYNTHES
in a primary settler was tested, both with and without a coagulant. Parameters like the COD
(particulate, colloidal and soluble) removal efficiency and settleability were recorded. The aim of this
experiment is to prove that the presence of sludge is recommended to obtain better results in term
of nutrient removal/recovery and settleability.
2.1 Determination optimal coagulant and concentration
Both Al3+ (as Al2(SO4)3) and Fe3+ (as FeCl3) were tested as possible coagulants since they are also used
in chemically enhanced primary sedimentation (CEPT). The dosage of the coagulant usually lies
between 10 and 50 mg L-1 (Systems, 2015). To find the optimal coagulant and concentration, a
flocculation test for both coagulants at different concentrations was carried out.
To start, a given amount of coagulant, Al2(SO4)3 or FeCl3, was put in a glass tube with a diameter of
4 cm and vertical sides. For Fe3+ the concentrations varied between 0 and 4.3 mmol L-1, while for Al3+
the concentrations ranged between 0 and 1.9 mmol L-1. Next, 200 mL of SYNTHES was poured into
the tubes while stirring and dissolving the coagulant.
Subsequently, the stirring was stopped and the SYNTHES was allowed to flocculate and settle for
40 min. Finally, the settleability was observed with the naked eye and a sample of the supernatant
was taken. To quantify the quality of the supernatant depending on the amount and type of
coagulant, the transmission rate was determined at 610 nm with a spectrophotometer (Biochrom,
Lightwave II). Distillated water was used as a blank with a transmission rate of 100 %.
2.2 COD removal and recovery
To examine how much of the COD of the SYNTHES can be removed by a primary settler, with and
without coagulant, a reactor with the same dimensions as those from the HiCS lab-scale reactor was
used. The experiment was conducted in triplicate.
First, 3 L of SYNTHES was transferred into each reactor vessel while stirring. From each of the
reactors a sample of 50 mL was taken immediately to determine the CODpart, CODcol, CODdiss of the
influent. Next, 40 min of settling time was implemented. After this, another sample of the
supernatant was taken to determine the COD fractions of the effluent. Subsequently, this test was
repeated with the addition of the predetermined type and amount of coagulant. To dissolve and mix
the coagulant, the reactor content was mixed for 15 min prior to the start of the settling phase.
Page | 30
3. Analyses
3. Analyses
3.1 Chemical oxygen demand
The chemical oxygen demand (COD) of the influent, effluent and waste was determined on a neardaily basis. The samples were split into different COD fractions (see Table 2.4) using filters with
different pore sizes. Ashless filters from Whatman (type 41, diameter 47 mm) with pores of 20 to 25
µm were used to retain the particulate COD fraction (CODpart) and obtain a supernatant that contains
both the colloidal (CODcol) and dissolved COD (CODdiss) fractions. Subsequently, this supernatant was
filtered with 0.20 µm filters (Chromafil syringe filter PTFE 15 mm) to have a supernatant containing
only CODdiss.
Table 2.4: COD fractions and particle sizes.
COD fraction
Range particle size
CODpart
> 20 µm
CODcol
CODdiss
25 - 0.20 µm
< 0.20 µm
The COD was measured using three types of Nanocolor kits (Marchery-Nagel): COD-160, COD-1500
and COD-15000. These three types of kits have an analysis range of 10 - 160 mg COD L-1, 100 - 1500
mg COD L-1 and 1000 - 15000 mg COD L-1 respectively.
3.2 Biochemical oxygen demand
The biochemical oxygen demand (BOD) represents the amount of organic material oxidized to CO2
and H2O at 20 °C and is considered as the quantity of readily biodegradable organic matter of a
sample. Just like for the COD measurements, the influent and effluent were fractionated into BODpart,
BODcol and BODdiss. The most widely used parameter is the 5-day BOD (BOD5). The measurement was
carried out using the OxiTop BOD Respirometer Systems which is a manometric method. The
respirometer measures the pressure depletion automatically in a closed bottle due to oxygen
consumption by microorganisms.
First, the inoculum has to be prepared one day in advance by adding some soil and sludge to an
erlenmeyer containing 100 mL of the influent or effluent. The erlenmeyer is closed with cotton wool
and put on a shaker at 28 °C for one night. A specific sample volume, dependent on the expected
BOD content, is put into shaded glass bottles. Next to 1 mL of the freshly prepared inoculum, mineral
solutions are are added to the bottle: 0.1 vol% of the predetermined sample volume of phosphate
buffer at pH 7.2, MgSO4.7H2O, CaCl2 and FeCl3. Subsequently limestone is added in the lid to absorb
the produced CO2 and nitrification inhibitor is added to prevent consumption of oxygen by oxidation
of ammonia. Finally, the bottles are closed firmly with an OxiTop manometer and put on a stir plate
Page | 31
3. Analyses
under a temperature of 20 °C. The pressure drop is registered and can be read as a measured value
in mg L-1 BOD.
3.3 Total and volatile suspended solids
The total suspended solids (TSS) fraction is determined by filtration of a specific sample volume over
a 0.45 µm filter from which the mass is known. The sample is washed twice with distilled water and
afterwards it is dried at 105 °C for at least 1 hour. After weighing the dried filter, the volatile
suspended solids (VSS) fraction is obtained by incinerating the remainder in a muffle furnace
(Nabertherm B150, Germany) at 550 °C for 1.5 hours.
The TSS (mg L-1) is quantified by subtracting the mass of the filter from the mass of the filter, dried at
105 °C and dividing by the volume that was filtered originally. The VSS (mg L-1) is the mass of the filter
after drying at 105 °C minus the mass of the filter after incineration in the muffle furnace, divided by
the original sample volume.
3.4 Sludge volume index
The sludge volume index (SVI) is a standard measure of the physical characteristics of activated
sludge solids. The SVI is the volume occupied by one gram of sludge after settling for 30 min.
Although this index is not supported theoretically, experience has shown it to be useful in routine
process control (Finch & Ives, 1950).
To calculate the SVI, first the settled sludge volume (SSV) has to be determined by pouring 200 mL of
waste sludge into an Imhoff settling cone. By reading the volume of the sludge bed after 5 and 30
min, SSV5 and SSV30 (mL L-1) can be determined. When the suspended solids concentration (mg L-1) is
also known, the SVI (mL g-1) can be calculated by dividing these two predetermined values.
3.5 Extracellular polymeric substances
The production of extracellular polymeric substances (EPS) by microorganisms is believed to be a
very important mechanism in correlation with bioflocculation and settleability. During the extraction
of EPS, a fractionation between LB-EPS and TB-EPS is made. Next to the amount of EPS that is
produced, also the ratio of proteins and carbohydrates has to be taken into account as it determines
the overall charge of the sludge flocs.
Page | 32
3. Analyses
3.5.1 EPS extraction
To extract the EPS from the sludge, a heating extraction method (Morgan et al., 1990) was modified
to include a mild extraction step for the LB-EPS and a harsh step for extracting the TB-EPS. First,
10 mL of sample (or other known amount, depending on the amount of EPS that is present in the
sludge) is dewatered by centrifugation for 5 min at 4000 G. After discarding the supernatant, the
pellet is resuspended by vortexing for 1 min in 10 mL of Ringer solution (9 g L-1 NaCl, 0.42 g L-1 KCl,
0.48 g L-1 CaCl2 and 0.20 g L-1 NaHCO3 adjusted to pH 7.0) diluted to 25 % with distilled water. The
diluted Ringer solution was preheated to 60 °C to ensure that the sludge suspension reached an
immediate temperature of 50 °C. Next, the suspension is centrifuged for 10 min at 4000 G.
Afterwards, the supernatant that contains the LB-EPS fraction is removed gently without loosening
the pellet. To extract the TB-EPS, the pellet is resuspended in 10 mL of preheated (60 °C) diluted
Ringer solution. This suspension is heated for 30 min at 60 °C. Finally the sample is centrifuged for 15
min at 4000 G, after which the supernatant containing the TB-EPS fraction is recovered. Both EPS
fractions and the sludge pellet can be stored at -20 °C for further analysis. Note that in order to
calculate the specific EPS concentration, the TSS/VSS concentration has to be known.
3.5.2 Protein concentration
The protein concentration of the EPS fractions was determined using the method of Lowry (1951).
The Lowry method is a colorimetric method and combines the reaction between copper ions and the
N-terminus of protein residues under alkaline conditions with the oxidation of aromatic amino acids.
The Folin Ciocalteu’s phenol reagent that is used, gives a blue color (750 nm) when it is reduced by
reaction with the aromatic compounds. The intensity of the color can be used as a measure of
protein concentration.
For each batch of samples a standard series of bovine serum albumin (BSA) has to be made with a
BSA standard of 1 mg mL-1. This BSA standard can be made in advance and stored at -20 °C. Prepare a
standard series with 0-50-100-150-200-250 µg BSA mL-1. Note that the Lowry analysis is timesensitive wherefore the samples have to be analyzed in series of maximum 10 samples in order to
guarantee an exact timing. Lowry mix has to be prepared freshly from 25 mL Lowry A (20 g L-1
Na2CO3) and 0.5 mL Lowry B (0.1 g L-1 Na3Citrate and 0.5 g L-1 CuSO4.5H2O).
First, 1 mL of EPS extract is diluted with 1 mL of 2 M NaOH. Next, 0.5 mL of standard or sample is
pipetted in a glass tube after which 2.5 mL of Lowry mix is added. This solution is vortexed and
incubated for 15 min in a dark environment. Subsequently, 0.25 mL of Folin Ciocalteu is added. Now,
the solution is vortexed again and put in a dark environment for 40 min. Finally, the color intensity
can be measured with a spectrophotometer (Biochrom, Lightwave II) at 750 nm.
Page | 33
3. Analyses
3.5.3 Carbohydrate concentration
The concentration of carbohydrates in the LB- and TB-EPS fractions was estimated by the anthrone
method as described by Gerhardt (1994), which is a colorimetric method based on the aromatic
compound anthrone. In the first step, the polysaccharides are hydrolyzed and dehydrated to
monomers. After this, the pentoses and hexoses are converted to furfural and
hydroxymethylfurfural, respectively. These compounds react with the anthrone reagent to give a
green-colored compound (Gerhardt, 1994).
A 75 % H2SO4 solution has to be made preferably one day before the experiment, or at least four
hours before starting. The anthrone solution (250 mL flask with 0.5 g of anthrone dissolved in 10 mL
of ethanol, filled up with the 75 % H2SO4 solution) has to be prepared freshly at the day of
measurement. A glucose dilution series for the standard curve with a final concentration of 0-20-4060-80-100 µg mL-1 has to be prepared. During the experiment, it is important to work on ice to cool
down the reaction with the sulfuric acid.
To start the experiment, 1 mL of standard or sample is transferred to a glass tube which is placed on
ice. Next, 2 mL of already chilled 75 % H2SO4 solution is pipetted to the tube. The tube is vortexed
briefly after which 4 mL of already chilled anthrone solution is added. After capping and vortexing,
the tubes are placed on a heating block to react at 100 °C for 15 min. Finally, the tubes are cooled
down to room temperature and measured with a spectrophotometer at a wavelength of 578 nm.
3.5.4 Total and volatile solids
The total and volatile solids (TS and VS) concentrations of the LB-EPS and TB-EPS fractions were also
determined. Note that the EPS fractions are recovered after centrifugation which means that ideally
only suspended material should be present in the sample.
The TS/VS method makes use of crucibles of a known mass. A known volume of the sample is
transferred into the crucible after which it is dried for at least twelve hours at 105 °C. After weighing
the crucible, it is put in the muffle furnace for incineration at 550 °C for 1.5 hours. Finally, the mass of
the crucible and ashes is determined so that the TS and VS concentrations (mg L-1) can be calculated
in the same way as the TSS and VSS concentration is calculated.
Page | 34
3.6 Polyhydroxybutyrate analysis
To measure the concentration of polyhydroxybutyrate (PHB) in the sludge, the sludge pellet obtained
from the EPS extraction (section 2.5.1) was used. The advantage of using the pellet is that the EPS
extraction could be seen as a deactivation method. In a preliminary test, a comparison was made
between the amount of PHB that could be extracted from the sludge pellet and directly from the
untreated sludge. It was shown that the highest PHB concentrations could be obtained from the
sludge pellet (data not shown). This suggests that the sludge pellet is less active after the EPS
extraction than an untreated sample, and thus less PHB is lost due to catabolic processes in the cells.
Before analysis, a standard curve of PHB has to be made. To do this, a dilution series of PHB in
concentrated H2SO4 is made with a range of 0 - 0.120 mg L-1. To convert the crystalline PHB into
amorphous PHB and to dissolve it in the H2SO4 a heating step may be required (2 min at 70°C). Note
that the solution always has to be cooled down before dilution to prevent mistakes due to thermal
expansion of the H2SO4.
To start the PHB analysis, the pellet is washed by suspension in 10 mL of diluted Ringer solution
(25 %) and centrifugation at 2000 G for 30 min. After the centrifugation step, the supernatant is
discarded and the pellet is dissolved in 5 mL of concentrated H2SO4. Next, the glass tubes are put in a
heating block for 20 min at 100 °C. It is important to vortex the samples at least every 5 min to
homogenize the solution. In this step of heating the sulfuric acid, the PHB is converted to crotonic
acid. When the reaction is complete, the samples are cooled down to room temperature. Afterwards
the solution is diluted 15 times and filtered through a 0.20 µm pore size filter (Chromafil syringe filter
PTFE 15 mm) to protect the HPLC tubing. Finally, 1 mL of the sample is transferred in a HPLC vial to
start the analysis. The vials are put in the HPLC and are run for 37 minutes at room temperature on a
Phenomenex Rezex ROA 8 % HPLC column on a Dionex Ultimate 3000 HPLC system. The crotonic acid
is quantified with its absorbance peak at 210 nm using the Dionex Ultimate 3000 Diode Array
Detector. The peak of crotonic acid should typically be detected at a retention time of 30 min.
3.7 IC measurements
The IC measurements were performed on a 761 Compact Ion Chromatograph (Metrohm,
Switzerland) equipped with a conductivity detector to follow-up the concentrations of nitrite, nitrate,
phosphate, sulfate and chloride.
Page | 35
4. Calculations
4. Calculations
4.1 COD removal efficiency
The COD removal efficiency (COD%) is defined as the fraction of the COD concentration of the influent
that is removed by the HiCS system. It is calculated following Equation 2.3.
( )
(Eq. 2.3)
4.2 Observed yield
The yield that was observed (Yobs in g VSSproduced g-1 CODremoved ) during HiCS reactor operation could be
determined on a daily basis. For this, the daily biomass growth in the reactor (∆XR,growth) between two
sample days was calculated by determining the daily sludge balance (Equation 2.4). Note that XR is
equal to XW in this SBR setup.
(
)
(
)
(Eq. 2.4)
The Yobs in g CODproduced g-1 CODremoved can be determined by Equation 2.5 when the COD/VSS ratio
(fCOD/VSS) is known. The volumetric removal of COD is calculated in the denominator of the fraction. All
particulate material residing in the effluent is considered as formed biomass. Therefore, only the
soluble COD fraction of the effluent is considered as a remainder of the original substrate.
(
)
(Eq. 2.5)
4.3 COD balance
In the COD balance (Figure 2.6), the amount of COD that comes into the HiCS reactor should be equal
to the amount of COD that leaves the reactor. The incoming COD is addressed solely to the influent
stream of SYNTHES. The sum of the cumulative load of CODpart,I, CODcol,I and CODdiss,I was set as the
100 % reference for the outgoing COD.
Page | 36
4. Calculations
First, the outgoing COD consists of the cumulative amount of CODpart,E, CODcol,E and CODdiss,E
discarded in the effluent stream. Besides that, the COD build-up or decrease in the reactor (∆CODR)
and the amount of COD that is wasted (∆CODW) are taken into account. The ∆CODR is calculated
following Equation 2.6. Here, the difference in TSS of the waste (∆XW) between two days of sampling
is multiplied by the COD over TSS ratio (fCOD/TSS) and the reactor volume. By dividing this value by the
time between the moments of sampling, the ΔCODR is known.
(
)
(
)
(Eq. 2.6)
Equation 2.7 shows that ∆CODW is calculated by multiplying the XW by the waste flow rate (QW) and
fCOD/TSS. To even out variations between sample days, the mean values of the data point (t) and the
previous data point (t-∆t) were used. The amount of CODcol and CODdiss in the wasted fraction is
subtracted from this value and added to the effluent COD fractions. This is done to compensate for
the fact that in this SBR setup, the sludge is wasted before the settling phase. In a large-scale
continuous HiCS system, the sludge would be wasted from the settled sludge bed and a lower
amount of CODcol and CODdiss would be present. Although this method of calculating the ∆CODW is
not entirely correct, because a minor fraction of the CODcol and CODdiss would still be present in the
aqueous matrix of the wasted sludge, it is a closer approximation of what would happen in a real
WWTP.
(
[
(
)
)
(
(
)
) (
]
(Eq. 2.7)
)
The CODpart, CODcol and CODdiss fractions in the effluent (∆CODE) are calculated according to Equation
2.8. Also here, the mean between two data points is used to compensate for large variations. As
mentioned above, the amount of CODcol and CODdiss in the wasted fraction is added to the respective
COD fractions of the effluent.
(
)
(
) (
)
(Eq. 2.8)
To implement ∆CODR and ∆CODW into the COD balance, their cumulative values are calculated over
time and plotted as a fraction of the total incoming COD. To complete the COD balance, the amount
of COD that was not retrieved in the waste or effluent, was assumed to be mineralized to CO2 during
the aeration phase.
Page | 37
5. Statistical analyses
100 %
Incoming
CODpart,I
CODcol,I
CODdiss,I
=
Outgoing
CODW + CODR
CODpart,E
CODcol,E
CODdiss,E
CO2
Figure 2.6: Schematic representation of the COD balance.
5. Statistical analyses
Statistical analysis of the datasets was performed with the software R version 3.0.2 (R Core Team,
2013). To test the normality of the data residuals, the Shapiro-Wilk normality test was used. The
homogeneity of the variances was tested using the Levene’s test. If the null hypothesis of normality
was rejected, multiple comparisons were performed using the non-parametric Kruskal-Wallis rank
sum test and post-hoc pairwise comparisons using the Wilcoxon rank sum test (also known as MannWhitney U test). In the other case, multiple comparisons were performed using the parametric
analysis of variance (ANOVA) test and post-hoc pairwise comparisons using the student’s t-test. Only
if the null hypothesis of equal means was rejected, pairwise comparisons were performed. The
p-values were adjusted with the Benjamini-Hochberg correction. A difference was considered
significant if the p-value was below 0.05.
Correlations between parameters were investigated by making a table of parameter averages for all
HiCS reactors. A plot matrix in which each parameter is plotted against another was then made. If the
correlation coefficient had an absolute value of 0.6 or more, a more in-depth analysis on the
correlation of the parameters was performed.
Page | 38
1. Operational parameters
III. Results
1. Operational parameters
Except for the first two HiCS reactors, operated for a period of 30 days, every HiCS reactor was run
for 26 days in order to collect an approximate amount of 20 data points by taking near-daily samples.
Also, the reactor conditions were checked on a near-daily basis.
Figure 3.1: HiCS reactors in operation (waste phase).
1.1 Dissolved oxygen - Temperature - pH
The DO level, temperature and pH of the HiCS reactors were measured during the stabilization
phase. The DO level was measured preferably at the start of the stabilization phase to check if the
reactor was running in non-limiting conditions above 1 mg L-1 during stabilization. The average values
for each HiCS reactor are shown in Table 3.1. Minimal variation in temperature and pH during
operation was noticed so that the influence of these parameters on the results of the experiment can
be neglected. The larger variation in DO level can be explained by the fact that this parameter does
not remain constant during the stabilization phase. As the stabilization phase progresses the DO level
Page | 39
1. Operational parameters
increases due to depletion of substances which can be oxidized. Nonetheless, for every HiCS reactor
a sufficient amount of oxygen was available to prevent its limitation.
Table 3.1: Dissolved oxygen, temperature and pH follow-up. Standard error was used to indicate variation.
-1
Reactor #
1
DO (mg O2 L )
6.3 ± 0.7
Temperature (°C)
15.2 ± 0.5
pH
8.1 ± 0.1
2
3
3.2 ± 0.7
4.5 ± 0.8
15.8 ± 0.1
15.6 ± 0.2
8.0 ± 0.1
8.0 ± 0.1
4
5.7 ± 0.9
14.7 ± 0.2
7.8 ± 0.1
5
6
4.5 ± 0.5
3.1 ± 0.5
14.7 ± 0.2
15.1 ± 0.2
7.9 ± 0.1
7.7 ± 0.1
7
8
0.7 ± 0.3
1.8 ± 0.3
14.3 ± 0.1
15.0 ± 0.1
7.9 ± 0.1
7.8 ± 0.1
1.2 Sludge retention time - Waste flow rate - Biomass concentration
In Table 3.2 a comparison between the intended and actual SRT (SRTint and SRTact) and waste flow
rates (QW,int and QW,act) for each reactor is presented. Differences between the intended parameter
values and the actual ones of some of the HiCS reactors can be attributed to deviations of TSS
concentrations from the predicted values and due to temporary problems such as failing of pumps,
wear of tubing or shifts of level controllers due to vibrations. Obviously, these issues were always
solved as soon as possible to reduce the error. Nonetheless, none of the SRTact differ strongly from
the SRTint so that differentiation between HiCS reactors remains possible.
Table 3.2: Comparison of intended and actual SRT and waste flow rates.
Standard error was used to indicate variation.
-1
-1
Reactor #
1
tC (min)
15
tS (min)
40
SRTint (days)
0.50
SRTact (days)
0.46 ± 0.03
QW,int(L d )
5.60
QW,act(L d )
5.39 ± 0.35
2
15
40
1.00
1.31 ± 0.08
2.52
1.83 ± 0.14
3
4
15
15
40
40
0.25
2.50
0.24 ± 0.00
2.82 ± 0.38
11.79
0.73
11.55 ± 0.00
0.62 ± 0.06
5
6
8
15
40
15
0.50
0.50
0.53 ± 0.02
0.50 ± 0.01
4.53
4.53
4.54 ± 0.19
4.41 ± 0.14
7
8
8
15
40
15
1.00
1.00
0.88 ± 0.03
0.85 ± 0.05
2.41
2.41
2.36 ± 0.09
2.48 ± 0.14
The SRT of HiCS reactors 1, 5 and 6 was aimed to be 0.5 days to be able to compare these reactors
and examine the effect of changing the tC and tS. The same goes for reactors 2, 7 and 8, but with an
SRT of 1 day. Between the SRT of reactors 1, 5 and 6, only a minor significant difference between
reactor 1 and 5 was noticed (p-values: R1-R5: 0.031 - R1-R6: 0.194 - R5-R6: 0.224). However, a
significant difference between reactor 2 and the other reactors can be determined (p-values: R2-R7:
3.9x10-6 - R2-R8: 2.4x10-5 - R7-R8: 0.099). This should be taken into account when comparing these
reactors.
Page | 40
1. Operational parameters
The biomass concentration (XR) represented as mg TSS L-1 or mg VSS L-1 is shown in Figure 3.2. At the
top, the biomass concentration is shown for the first four reactors where the SRT is a variable and tc
and ts are kept constant at 15 and 40 min, respectively. As the arrows indicate, the results of the HiCS
reactor with an SRT of 0.46 and 1.31 days are repeated in the bottom graphs to compare them to the
HiCS reactors of about equal SRT and variable tC:tS. The bottom-left graph represents the biomass
concentration for all HiCS reactors run at an SRT of 0.5 days, but with variable tC and tS, while the
bottom-right graph shows the same for the HiCS reactors operated at an SRT of 1 day. Next to that,
the VSS/TSS ratio is represented on the secondary y-axis.
Figure 3.2: Biomass concentration (XR) and VSS/TSS ratio for HiCS reactors with (top) increasing SRT and
constant tC and tS - (bottom-left) constant SRT (0.5 days) and variable tC and tS - (bottom-right) constant SRT
(1 day) and variable tC and tS. Standard errors are indicated in error bars. Significance levels are indicated for
selected pairwise comparisons (0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘ns’ 1).
Page | 41
2. HiCS performance
1.3 Loading rate - Hydraulic retention time
When designing the HiCS reactors, an attempt was made to keep the variation in hydraulic retention
time (HRT) and volumetric organic loading rate (BV) as low as possible. As can be seen in Table 3.3,
the difference in HRT and BV is minor, considering the restricted amount of technical tools available.
The Sludge-specific organic loading rate (BX) was aimed to be higher than 2 g bCOD g-1 VSS d-1 to
reach the lower limit of a high-rate activated sludge system. For three HiCS reactors, this target value
was not achieved.
Table 3.3: Loading rates (volumetric and specific) and hydraulic retention times of HiCS reactors.
Standard error was used to indicate variation.
-1
-1
-1
-1
Reactor #
1
SRTact (days)
0.46 ± 0.03
tC:tS (min)
15:40
BV (g COD L d )
4.72 ± 0.23
BX (g COD g VSS d )
4.70 ± 0.63
HRT (hours)
3.37
2
1.31 ± 0.08
15:40
4.67 ± 0.23
1.69 ± 0.08
3.44
3
4
0.24 ± 0.00
2.82 ± 0.38
15:40
15:40
5.17 ± 0.50
5.90 ± 0.37
8.11 ± 1.49
1.55 ± 0.13
4.50
3.43
5
6
0.53 ± 0.02
0.50 ± 0.01
8:40
15:15
6.19 ± 0.18
6.19 ± 0.15
3.97 ± 0.22
4.81 ± 0.13
3.23
3.23
7
0.88 ± 0.03
8:40
5.88 ± 0.14
2.44 ± 0.10
3.44
8
0.85 ± 0.05
15:15
5.82 ± 0.08
3.24 ± 0.13
3.44
2. HiCS performance
The performance of the HiCS system is evaluated based on the removal of organics from the
wastewater. Thus, important performance indicators are the COD removal efficiency and volumetric
removal rate. The more organic material that is removed from the influent, the more of these
organics will end up in the wasted sludge. This translates itself to an observed yield, which is another
important performance indicator. A higher yield means that more COD can be digested, which
implies a higher net biogas production. Thus, the observed yield is an approximation for the energy
recovery potential of the reactor.
2.1 COD removal
In Figure 3.3 the COD removal efficiencies (%) and volumetric removal rates (g COD L-1 d-1) for all HiCS
reactors are shown. These parameters are shown for both the total COD (CODtot) as the different
COD fractions: particulate, colloidal and soluble COD (CODpart, CODcol and CODdiss). As can be seen at
the top row, an optimal removal efficiency of the CODtot can be found between the reactors with an
SRT of 0.46 days and 1.31 days when the tC (15 min) and tS (40 min) are kept constant. The CODtot
removal efficiencies of these reactors amount 61.8 ± 2.14 % and 64.89 ± 3.02 % respectively, which is
Page | 42
2. HiCS performance
an insignificant difference (p-value: 0.50). However, the CODtot removal efficiency of 59.6 ± 2.8 %
achieved by the reactor with an SRT of 2.82 days does not differ significantly from these two either
(p-values: 0.36 and 0.18, resp.). The CODtot volumetric removal rates of these HiCS reactors are lower
than those of the reactors with SRT of 0.24 and 2.82 days. This can be explained by the higher BV of
the latter reactors. In the HiCS reactor series where the tC:tS is variable (middle and bottom row), the
reactors with a tC:tS of 15:40 min achieve the best results in terms of CODtot removal efficiency.
Figure 3.3: COD removal efficiencies (left column) and volumetric removal rates (right column) of HiCS reactors
with (top row) increasing SRT and constant tC and tS - (middle row) constant SRT (0.5 days) and variable tC and tS
- (bottom row) constant SRT (1 day) and variable tC and tS. Standard errors are indicated in error bars.
Page | 43
2. HiCS performance
In the graphs, no significant differences in the CODpart removal efficiencies between the HiCS reactors
can be observed. Respectively, the lowest and highest CODpart removal efficiencies are 81 % for an
SRT of 0.88 days at a tC:tS of 8:40 min and 93 % for an SRT of 2.82 days at a tC:tS of 15:40 min. Larger,
but insignificant differences can be found in the volumetric removal rates of the CODpart, but these
can be partially related to the variations in BV (Table 3.3).
Lower than the CODdiss removal efficiency, the daily CODcol removal efficiency of each reactor
throughout its runtime was very dynamic, which is evident from the wide range of the standard error
bars. Nonetheless, one can see that the ability to remove the colloidal and soluble organics is the
main aspect in which further optimization of the HiCS system is needed. When increasing the SRT,
while keeping the tC:tS constant, an optimum for the efficiency of removal of both CODdiss and CODcol,
can be found between the HiCS reactors with an SRT of 0.46 days and 1.31 days. This also comes to
expression in the CODtot removal efficiency. When the tC and tS are varied (middle and bottom row),
for an SRT of around 0.5 days, the optimal CODdiss and CODcol removal efficiency can still be found at
a tC:tS of 15:40 min. For an SRT of around 1 day, this optimum is shifted to a tC:tS of 8:40 min, but it is
possible that the rather large difference in SRT has a greater influence on this result than the
decreased contact time.
2.2 Observed yield
The observed yield (Yobs) can be defined as the amount of sludge in grams of COD that is produced for
each gram of COD that is removed by the system. As shown in Figure 3.4, the Yobs decreases with
increasing SRT. When plotting the Yobs in function of the SRT, a strong correlation with a correlation
coefficient of -0.967 can be found (see addendum). On the other hand, only the Yobs of the HiCS
reactor with an SRT of 2.82 days is remarkably lower than the other reactors at a tC:tS of 15:40 min.
For this reactor, a Yobs of 0.70 ± 0.17 g CODSludge g-1 CODremoved was observed, while by lowering the
SRT, the Yobs progressively increased to 0.95 ± 0.08; 1.02 ± 0.07 and 1.06 ± 0.13 g CODSludge g-1
CODremoved, as visualized in the graph.
Figure 3.4: The observed yield for each HiCS reactor. Standard errors are indicated in error bars.
Significance levels are indicated for selected pairwise comparisons (0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘n.s.’ 1).
Page | 44
2. HiCS performance
Furthermore, no significant difference in Yobs can be detected between the HiCS reactors with
variable tC:tS, as can be seen in the middle graph for an SRT of around 0.5 days and at the right graph
for an SRT of around 1 day.
2.3 COD balance
The COD balance of each HiCS reactor is presented in Figure 3.5. Critical parameters for evaluating
the performance of the HiCS reactors are the fractions of the CODIN that end up in the effluent and in
the sludge. The first fraction has to be as small possible, while the fraction that is withheld by the
sludge has to be as great as possible to be able to harvest and digest a maximal amount of organics.
As shown at the top graph of Figure 3.5, the amount of COD that is recovered in the sludge (waste
and reactor) increases when the SRT decreases. A maximal fraction of 63.4 % can be found in the
reactor with an SRT of 0.24 days. The reactors with an SRT of 0.46 and 1.31 days have a comparable
COD recovery in the sludge of 54 % and 52 %, respectively. When increasing the SRT even further to
2.82 days, the amount of COD in the sludge decreases to only 23.1 % Due to the cumulative method
of calculating the COD fractions, the standard error bars are not presented in the graph. The most
favorable effluent COD concentrations can be found at the HiCS reactor with an SRT of 1.31 days.
Figure 3.5: COD balance of each HiCS reactor.
Page | 45
3. Extracellular polymeric substances and settleability
The bottom-left graph of Figure 3.5 shows that the most favorable COD balance for the HiCS reactors
with an approximate SRT of 0.5 days can be found at a tC:tS of 15:40 min. This reactor shows the
highest concentration of COD in the waste and reactor (54 %) as well as the lowest amount
unrecovered COD in the effluent (CODpart: 3.7 % - CODcol: 6.6 % - CODdiss: 25.5 %). On the other hand,
the bottom-right graph shows that for the HiCS reactors with an approximate SRT of 1 day, the
reactor with tC:tS of 15:40 min achieved the best result in terms of COD recovery in the waste and
reactor (52 %). This HiCS reactor also achieves the lowest COD fractions in the effluent (CODpart: 3.4 %
- CODcol: 7.9 % - CODdiss: 20.3 %).
As already mentioned in section 2.1, the removal of CODpart is about the same for each reactor (all
pairwise p-values > 0.05). The reactors mostly differ from one another in terms of CODcol and CODdiss
removal. Nonetheless, another important parameter is the amount of carbon that is oxidized to CO2
during the stabilization phase. The extent of this process determines the amount of COD that is
available for recovery and thus it plays a major role in the amount of COD that remains in the sludge.
2.4 Ion chromatography
With anion chromatography the NO2-, NO3- and PO43- concentrations of the influent and effluent
were measured on a weekly basis. Although there were large fluctuations in the anion
concentrations of both sample types, for each HiCS reactor a general removal of NOX- and PO43- could
be observed (data not shown). Based on the results, a rough estimation could be made for the
removal efficiencies of these anions. For NOX--Nitrogen, the removal efficiency ranged between 57 %
and 92 %, while a range between 20 % and 63 % was determined for PO43- removal.
3. Extracellular polymeric substances and settleability
To represent the amount of extracellular polymeric substances (EPS) produced by the sludge, the
protein and carbohydrate concentrations of both loosely and tightly bound (LB and TB) fractions
were used (section 3.1). The volatile solids (VS) concentrations of these fractions were also
measured, but the variability on these measurements was too great to draw any conclusions. These
variations were possibly caused by temperature differences from the crucibles at the moment they
were weighed and loss of ashes during transport.
Furthermore, the protein and carbohydrate concentrations and especially the ratio between the two
are thought to be correlated to the settleability of the sludge. A comparison between these two
parameters is made in section 3.2.
Page | 46
3. Extracellular polymeric substances and settleability
3.1 Protein and carbohydrate concentration
The protein and carbohydrate concentrations of both LB- and TB-EPS fractions are presented in
Figure 3.6. The concentrations are expressed as equivalent concentration of the calibration standard
(BSA for proteins; glucose for carbohydrates) dived by the sludge VSS concentration. The secondary
axis refers to the LB/TB-EPS ratio of these protein and carbohydrate concentrations.
Figure 3.6: Sludge protein (left column) and carbohydrate (right column) conc. of LB- and TB- EPS for each HiCS
reactor with (top row) increasing SRT and constant tC and tS - (middle row) constant SRT (0.5 days) and variable
tC and tS - (bottom row) constant SRT (1 day) and variable t C and tS. Standard erros indicated in error bars.
Significance levels are indicated for selected pairwise comparisons (0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘ns’ 1).
Page | 47
3. Extracellular polymeric substances and settleability
As seen on the top row in Figure 3.6, the highest protein (P-EPS) concentrations can be found at the
SRT of 0.46 days and 1.31 days with no significant difference between the two (p-values: LB-EPS: 0.88
- TB-EPS: 0.18). For these HiCS reactors, the P-LB-EPS concentrations are 22.2 ± 6.1 mg BSA g-1 VSS
and 18.8 ± 1.9 mg BSA g-1 VSS, respectively. The respective P-TB-EPS concentrations amount
65.5 ± 6.7 mg BSA g-1 VSS and 73.5 ± 4.3 mg BSA g-1 VSS. The highest LB/TB-ratio of 0.34 can be found
at an SRT of 0.46 if the tC:tS is 15:40 min.
No significant differences between the HiCS reactors with variable SRT and a constant tC:tS of 15:40
min could be noted for the carbohydrate (C-EPS) concentrations. The average C-LB-EPS and C-TB-EPS
concentrations of this series of reactors were 5.2 mg glucose g-1 VSS and 17.3 mg glucose g-1 VSS. On
the other hand, a remarkable decreasing trend in the C-LB-EPS concentration and the LB/TB ratio
could be observed with increasing SRT. In order of increasing SRT, the LB/TB ratios amount to 0.50;
0.34; 0.23 and 0.12.
In the middle row, the P-EPS and C-EPS concentrations are shown for the reactors with an SRT of
about 0.5 days and a variable tC:tS. Although no significant difference can be observed in the C-EPS
concentrations, the P-EPS concentrations have a maximum at a tC:tS of 15:40 min for both LB- and TBEPS fractions. Furthermore, for both proteins and carbohydrates, a lower LB/TB-EPS ratio is observed
when the tC is shortened, while a higher LB/TB-EPS ratio is achieved when the tS is shortened.
However, this effect is not present in the HiCS reactor series with an SRT of about 1 day.
The same determination was made for the P-EPS concentrations of the reactors in which the SRT is
kept constant around 1 day and the tC:tS is variable (bottom row Figure 3.6). For the C-EPS
concentrations of this HiCS reactor series, the reactor with a tC:tS of 15:40 min has the lowest
concentration for both fractions (C-LB-EPS: 3.5 ± 0.4 mg glucose g-1 VSS - C-TB-EPS: 14.8 ± 1.3 mg
glucose g-1 VSS). The other reactors in this series have a C-LB-EPS concentration of about
7.5 mg glucose g-1 VSS and a C-TB-EPS concentration of about 20 mg glucose g-1 VSS . Important to
keep in mind is that the SRT of the reactor with a tC:tS of 15:40 min is significantly larger than the SRT
of the other reactors. The consequence of this difference is shown by the LB/TB-EPS ratio of the
carbohydrates. As demonstrated by the results of the top row, the LB/TB-EPS ratio decreases when
the SRT becomes longer. Nonetheless, an increasing trend is observed in the LB/TB-EPS ratio of the
middle carbohydrates graph, while this trend is decreasing for the reactors with an SRT of around 0.9
days in the bottom graph. All of these results suggest that the effect of changing the tC and tS on the
EPS content and composition is dependent on the SRT and, therefore, these operational parameters
possibly interact with one another.
A positive correlation between the P-EPS concentration of the sludge and the CODtot removal
efficiency was found. The P-LB-EPS and P-TB-EPS share a respective correlation coefficient of 0.639
and 0.873 with the CODtot removal efficiency (see addendum). The same observation was made
between the P-EPS concentration and the SVI. The correlation coefficients between the SVI and the
P-TB-EPS and P-LB-EPS concentration amount 0.768 and 0.567. The reverse was determined for the
C-EPS concentrations, especially for the LB-EPS fraction. A negative correlation coefficient of -0.702
was established between the CODpart removal efficiency and the C-LB-EPS concentration. Between
the SVI and the C-LB-EPS concentration, a correlation coefficient of -0.719 was determined.
Surprisingly, a positive correlation coefficient of 0.837 was found between the CODcol removal rate
Page | 48
3. Extracellular polymeric substances and settleability
and the C-LB-EPS. This suggests that, even though the data shows some inconsistencies, the protein
content of EPS seems more strongly associated with a higher substrate removal efficiency.
3.2 Protein-carbohydrate ratio and Sludge volume index
The sludge volume index (SVI) is not a perfect parameter indicator for sludge settleability, because
the determination of the SVI is often subjective. When the SVI is determined for the same sludge adt
different biomass concentrations, different results will be observed since the biomass concentration
is correlated to the settling velocity. To prevent this error, the standard methods recommend diluting
the sludge to a standard value of 2500 mg TSS L-1 before the SVI measurement is performed. Since
this test was performed on a near-daily basis, this preliminary step would have been too timeconsuming. Furthermore, the walls of the Imhoff settling cone are not straight, which may hinder
normal settling behavior. Therefore, the SVI measurements performed in this work are indicative and
should be interpreted accordingly. Nonetheless, the SVI is a widely used parameter in both research
as well as industrial applications and is thought to be correlated to the EPS production of the sludge.
A comparison between the proteins over carbohydrates (P/C) ratio and the SVI for each HiCS reactor
is presented in Figure 3.7. The P/C ratio for the reactors with a tC:tS of 15:40 min is the highest at an
SRT of 1.31 days and amounts 5.43 for the LB-EPS and 4.96 for the TB-EPS. Another observation is
that the P/C ratio from the LB-EPS is lower than the TB-EPS at the lowest SRT of 0.24 days, while this
shifts gradually towards a higher LB-EPS P/C ratio when the SRT increases.
For both HiCS reactor series in which the SRT was kept around 0.5 days and 1 day (middle and
bottom row), the P/C ratio is the highest at a tC:tS of 15:40 min. A significant decrease in P/C ratio is
noticed when lowering the tC or tS to 8 and 15 min, respectively. Furthermore, for both reactor series,
this decrease in P/C ratio is of similar magnitude.
None of the SVI of the HiCS reactors is high enough to be problematic (i.e., sludge is considered to be
‘bulking’ at an SVI above 200 ml g-1). Each of the HiCS reactors achieved an adequate sludge
separation. Nonetheless, an increase in SVI is observed when the SRT is lengthened. A correlation
between the SVI and the SRT is confirmed by the correlation coefficient of 0.806 when plotting these
parameters in function of one another (see addendum). For the reactors with a common tC:tS of
15:40 min and an increasing SRT of 0.24; 0.46; 1.31 and 2.82 days a respective SVI of 16.7 ± 4.1;
34.8 ± 2.8; 51.9 ± 3.1 and 55.5 ± 4.5 ml g-1 was determined. For the reactors with an SRT of around
0.5 days as well as for those with an SRT of around 1 day, the highest SVI is observed at the HiCS
reactors with a tC:tS of 15:40 min.
When plotting the P/C ratios as a function of the SVI results in Figure 3.8, a positive correlation can
be observed. Another observation is that especially the P/C ratio from the LB-EPS fraction, more than
the TB-EPS fraction, has a stronger correlation with the settleability of the sludge. Respectively for
both EPS fractions, an R-squared value of 0.78 and 0.49 can be found.
Page | 49
3. Extracellular polymeric substances and settleability
Figure 3.7: Proteins over carbohydrates ratio (left column) and the SVI (right column) for each HiCS reactor with
(top row) increasing SRT and constant tC and tS - (middle row) constant SRT (0.5 days) and variable tC and tS (bottom row) constant SRT (1 day) and variable t C and tS. Standard errors are indicated in error bars.
Significance levels are indicated for selected pairwise comparisons (0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘ns’ 1).
Figure 3.8: Proteins over carbohydrates ratio as a function of the SVI.
Page | 50
4. Substrate storage - Polyhydroxybutyrate
4. Substrate storage - Polyhydroxybutyrate
The storage of carbonaceous substrates was measured by determining the concentration of
polyhydroxybutyrate (PHB) that is present in the sludge. The PHB concentrations in the sludge for
each HiCS reactor are presented in Figure 3.9. The left graph shows the reactors with increasing SRT
and a constant tC:tS of 15:40 min. In this series, a maximal PHB concentration of 21.0 ± 2.5 mg PHB g-1
VSS is determined for the reactor with an SRT of 1.31 days. A strongly significant difference between
this HiCS reactor and the reactors with SRT of 0.46 and 2.82 days can be found (p-values: 2.8x10-4 and
2.2x10-3, resp.). The sludge of the reactor with an SRT of 0.24 days possesses the lowest amount of
PHB: 2.7 ± 0.5 mg PHB g-1 VSS.
Figure 3.9: PHB concentration in sludge of each HiCS reactor. Standard errors are indicated in error bars.
Significance levels are indicated for selected pairwise comparisons (0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘ns’ 1).
The middle graph of Figure 3.9 shows the PHB concentrations of the sludge in the HiCS reactors with
variable tC:tS and an SRT of about 0.5 days. No significant difference in PHB concentration between
the reactors with a tS of 40 min is observed (p-value: 0.92) , while decreasing the tS to 15 min results
in a significant decrease of the amount of storage polymer in the sludge to 4.15 ± 0.37 mg PHB
g-1 VSS (p-value: 4.5x10-4).
When comparing the HiCS reactors with an SRT of about 1 day and variable tC:tS, the sludge of the
reactor with a tC:tS of 15:40 min has the highest PHB concentration. When lowering the tC to 8 min
for one reactor and lowering the tS to 15 min for the other reactor, the PHB concentrations decrease
to a respective 6.85 ± 1.53 and 2.57 ± 0.44 mg PHB g-1 VSS. Between these two reactors, the
difference in PHB concentration is also significant (p-value: 0.035), which implies that the reduction
of the tS to 15 min has a more pronounced effect on the amount of storage polymer in the sludge
than a reduction of the tC to 8 min. This is also confirmed by the results of the reactor series in the
middle of Figure 3.9.
A remarkable correlation between the PHB concentration in the sludge and the CODtot removal
efficiency can be established. A correlation coefficient of 0.836 was determined (see addendum). It is
possible that when a higher amount of COD is removed by the HiCS reactor, the storage response of
the sludge becomes more pronounced.
Page | 51
5. Intensive measurement campaigns
5. Intensive measurement campaigns
For each of the HiCS reactors, a 60 min follow-up of the DO level was performed, in which the full
length of the stabilization phase was included. During the other phases of the SBR cycle no aeration
is applied, hence the DO level remains zero. The results of these measurements are plotted in
Figure 3.10, together with the CODtot concentrations that were measured at several points of time in
the stabilization phase. The transition between the stabilization phase and the contact phase is
indicated by a vertical line.
For each of the graphs, except the ones of the reactors with a tS of 15 min, the DO level remained
relatively low during the stabilization phase, despite a constant air supply, which implies a high
oxygen consumption. After that, the DO level started to increase (indicated by an arrow), presumably
because the substrate became limited and less oxygen needed to be consumed. Eventually, the DO
level reaches another steady-state value at which it remains until the aeration is shut down at the
beginning of the contact phase. The consumption of oxygen often coincides with a decrease in the
CODtot concentration in the reactor.
The moment at which the DO level starts to increase is different for each reactor and is found after
aerating the reactor for 12 to 25 min. For the HiCS reactor with an SRT of 0.46 days and a tC:tS of
15:40 min, the DO level started to increase at about 15 min. This was the main reason the decision
was made for a next experiment to decrease the tS from 40 to 15 min of one of the HiCS reactors
while keeping the SRT constant. As can be seen in the graphs of the reactors with only 15 min of
stabilization time (bottom-right of Figure 3.10), no second steady-state period of the DO level can be
observed.
Next to the monitoring of the DO and COD levels, the TSS, VSS, EPS and PHB concentrations were
also measured at several points in time during each phase of the SBR cycle. Because of the feastfamine regime, the expectation was to detect variations in the concentrations of these parameters,
especially the PHB concentrations, during one SBR cycle. However, the results of these
measurements are inconclusive and are not presented in this section. A possible explanation is that
during one SBR cycle the variations in these parameters are too limited to cause noticeable changes
in the sludge. The variations are more likely to be originating from experimental errors.
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5. Intensive measurement campaigns
Figure 3.10: Follow-up of DO level from the onset of the stabilization phase for each HiCS reactor. The x-axis
starts at the moment the stabilization phase starts and makes a transition to the contact phase as is indicated
by a vertical line. Arrows indicate the start of DO level increase.
Page | 53
6. Abiotic batch tests
6. Abiotic batch tests
6.1 Determination optimal coagulant and concentration
To perform the flocculation experiment, a preliminary test had to be performed to decide if Al3+ or
Fe3+ is the optimal coagulant and in which concentration it should be added. To determine which
coagulant achieved the best settling properties, several concentrations of Al2(SO4)3 and FeCl3 were
mixed with 200 mL of SYNTHES. The performance of both coagulants was checked by the naked eye
(Figure 3.11) and by determining the transmission rate of the supernatant (Table 3.4).
As indicated in Table 3.4, the supernatant after 40 min of sedimentation has the highest transmission
rate (93.5 %) and thus the clearest effluent when a concentration of 0.74 mmol L-1 of Al3+ is added.
For Fe3+ as the coagulant, the transmission rate reached a maximum of 87.7 % when a concentration
of 0.72 mmol L-1 was added. Since the highest transmission rate was achieved by Al3+, the decision
was made to continue the flocculation experiment with this optimal Al3+ concentration.
Figure 3.11: Determination of optimal coagulant and concentration for sedimentation SYNTHES. The upper
picture was taken after 40 min, while the lower picture was taken after 20 min, explaining the different
3+
transparency between corresponding Al -concentrations.
Page | 54
6. Abiotic batch tests
Table 3.4: Coagulant concentration and transmission rates with indication of the optimal concentration.
n.m.: not measured.
3+
3+
Al - concentration
Transmission
Fe - concentration
Transmission
-1
-1
(mmol L )
(%)
(mmol L )
(%)
0.00
28.4
0.00
28.4
0.08
0.15
n.m.
n.m.
0.18
0.36
57.6
58.7
0.23
n.m.
0.54
60.2
0.31
0.38
n.m.
n.m.
0.72
0.90
87.7
87.5
0.37
0.74
87.3
93.5
0.86
1.73
n.m.
n.m.
1.11
1.48
86.5
80.9
2.59
3.46
n.m.
n.m.
1.85
75.7
4.32
n.m.
6.2 COD removal and recovery
The performance of the primary settler with and without coagulant (Figure 3.12), is compared with
the results of the HiCS reactor with an SRT of 0.46 days and a tC:tS of 15:40 min, because this reactor
achieved the highest sludge yield. The efficiency of COD removal from the influent is presented in
Figure 3.13. As observed, the HiCS reactor with an SRT of 0.46 days achieves the maximal CODtot
removal efficiency (61.8 ± 2.1 %). This is due to the fact that the HiCS reactor is able to remove a
higher fraction of the CODpart and CODdiss from the influent. The primary settler with coagulant and
the one with coagulant achieve a CODtot removal efficiency of 30.1 ± 1.0 % and 49.8 ± 1.4 %,
respectively The CODcol removal efficiency of the primary settler with coagulant is greater than the
one from the HiCS reactor, but as can be seen in Figure 3.14, the fraction of CODcol in the influent
represents 17.1 % of the substrate, while the CODpart and CODdiss fractions comprise 35.4 % and 47.4
% of the influent COD, respectively.
Figure 3.12: Setup triplicate abiotic batch test before (left) and after (right) 40 min settling.
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6. Abiotic batch tests
Figure 3.13: Removal efficiencies of primary settlers with and without coagulant
in comparison with the HiCS reactor with an SRT of 0.46 days and a tC:tS of 15:40 min.
Standard errors are indicated in error bars.
Figure 3.14: COD balances of primary settlers with and without coagulant
in comparison with the HiCS reactor with an SRT of 0.46 days and a tC:tS of 15:40 min.
The distributions of the COD fractions in the influent and in the reactor are shown in the COD
balance of Figure 3.14. The results of the primary settlers are again compared with the results from
the HiCS reactor with an SRT of 0.46 days. The amount of COD that is recovered in the reactor and
thus can be used to recover energy is about equal for the HiCS reactor and the primary settler with
coagulant (54.0 % and 53.6 %, resp.). Without coagulant, the performance of the primary settler
decreases significantly and only 35.3 % of the COD ends up in the sludge fraction. This is due to the
fact that no soluble material and only a small fraction of the CODcol (20.7 ± 5.5 %) are removed.
Page | 56
1. HiCS characteristics
IV. Discussion
1. HiCS characteristics
The variations in pH, temperature and DO level of the HiCS reactors are minimal, so the influence of
these parameters on the outcome of the experiments can be neglected (Table 3.1). The measured
DO levels are more dynamic than the temperature and pH. This can be explained by the fact that the
DO level was measured at one point of time in the stabilization phase, while the oxygen level does
not remain constant but increases in this timeframe. Furthermore, sludge deposits on the air stone,
variations in air pressure and wear of the tubing can also be a reason for a variable DO level.
Nonetheless, the microbial community in each HiCS reactor generally received a sufficient amount of
oxygen to prevent limitation.
The difference between the intended and actual SRT (SRTint and SRTact) of the HiCS reactors (Table
3.2) can be attributed to wear and sludge deposit in the tubing. Next to that, the tubing that controls
the height of the reactor content is also subject to vibrations of the pumps and shifts due to cleaning
of the reactor walls. Nevertheless, the approximation of the SRTint by the SRTact is close enough to be
able to compare and distinguish the HiCS reactors.
Since less sludge is wasted as the SRT increases, naturally the biomass concentration of the HiCS
reactors increases to (Figure 3.2). Furthermore, no major differences in VSS/TSS ratio can be
observed. This result can be expected, because the overall composition of the synthetic influent
should be about the same for each reactor so the concentration of inorganics in the sludge should
also be the about equal. According to Vásquez et al. (2010), in order to achieve an optimal
performance, typical biomass concentrations in a continuous contact stabilization process vary
between 1000 and 3000 mg VSS L-1 for the contact reactor and between 4000 and 10,000 mg VSS L-1
for the stabilization reactor. However, note that in a HiCS system the SRT are shorter which
automatically implies a lower sludge concentration. The results in Figure 3.2 represent the biomass
concentrations in the contact phase. Only the biomass concentrations of the HiCS reactors with a
constant tC:tS of 15:40 min and an SRT of 0.46 and 1.31 days lie between these recommended limits
(1160 ± 106 and 2789 ± 130 mg VSS L-1, resp.). The reactors with variable tC:tS and an SRT of around
0.5 days and 1 day also succeed in having a biomass concentration between these limits.
Meerburg et al. (2015) defined a continuous high-rate system on the basis of a specific loading rate
between 2 and 10 g bCOD g-1 VSS d-1. Although these boundaries are arbitrary, the lower loading rate
was not achieved for each of the reactors as shown in Table 3.3. Important to note is that these
boundaries are defined for a CSTR, while an SBR type of HiCS reactor was used to conduct the
experiments. In an SBR, the biomass is only active during a selected amount of time, namely during
the contact and stabilization phases. This is about 50 % of the time for six of the HiCS reactors and
even only 30 % for the reactors with a tC:tS of 15:15 min. Conversely, in a CSTR system, active and
inactive processes occur simultaneously in parallel compartments. In other words, all other
parameters being equal, loading rates per unit of time are inherently higher in a CSTR system with
continuous parallel phases than in a SBR system with discontinuous phases. To compensate the
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2. HiCS performance
difference between CSTR and SBR loading rates, a ‘time expansion factor’ may be introduced. This
factor can be defined as the ratio of volumetric loading rates of an SBR reactor and an equivalent
CSTR reactor with equal influent flow rates and retention times during the contact, settling and
stabilization phase. For the eight HiCS reactors, the ‘time expansion factor’ ranged between 1.4 and
1.7, depending on the specific length of each reactor phase. This indicates that a sludge-specific
loading rate of 2 g bCOD g-1 VSS d-1 in a CSTR would be roughly equivalent to a loading rate between
1.4 and 1.2 g bCOD g-1 VSS d-1 in the SBR-based HiCS reactor.
However, each of the reactors’ loading rates was far higher than the range of loading rates of 0.2 0.6 g BOD g-1 VSS d-1 at which a conventional contact stabilization process operates (Metcalf & Eddy,
2003). In practice, reaching such high sludge loading rates can often prove to be difficult, especially
when the wastewater is low-strength. Therefore, when implementing the HiCS system, it is desirable
to achieve a specific loading rate that is as high as possible.
2. HiCS performance
As the HiCS process is used in the HRAS-stage of a two-stage activated sludge system, the primary
function is to maximize sludge production, while efficiently removing organic material from the
influent stream. Since a low COD/N ratio is desirable for the removal of nitrogen in the second stage
of the two-stage activated sludge system (Van Hulle et al., 2010), the removal of COD by the HiCS
reactor is one of the top-priority performance indicators. Subsequently, by removing a maximal
amount of COD from the waste stream, the HiCS reactor is able to recover a maximal amount of
chemical energy. Hence, the yield as the amount of COD that can be harvested as sludge is another
important parameter indicating the performance of the HiCS reactor.
2.1 COD removal
The difference between removal rates of CODpart between the reactors is insignificant. The main
distinction between the HiCS reactors can be attributed to the difference in CODcol and CODdiss
removal, and further optimization efforts should focus on increasing removal of these two substrate
fractions. In the reactor series with a constant tC:tS of 15:40 min, the fact that the reactor with an SRT
of 0.24 days achieves such limited CODcol and CODdiss removal efficiencies can be explained by the
fact that the biomass concentration is too low to be able to capture a sufficient amount of CODcol and
too low to absorb a large fraction of the CODdiss. On the other hand, the poor CODcol and CODdiss
removal efficiencies at an SRT of 2.82 days can be attributed to the fact that more hydrolysis of the
CODpart takes place since the sludge concentration is significantly higher. Hydrolysis of particulate
organics produces CODcol and CODdiss and by that it counteracts the removal of these COD fractions.
So in practice, one should opt to implement an SRT between 0.46 and 1.31 days to achieve maximal
removal of the CODcol and CODdiss fractions.
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2. HiCS performance
In Figure 3.13, the COD removal efficiencies of HiCS reactor with an SRT of 0.46 days are compared
with the results of the flocculation test (Figure 3.13). Chemical flocculation achieved a higher
efficiency in capturing and redirecting colloidal substrate into the sludge than the HiCS system tested
here. However, colloidal substrate is only a minor constituent of wastewater and the main effort
should be redirected to optimize capture of dissolved substrate, which comprises a larger fraction of
the CODIN. The HiCS reactor achieved a higher removal efficiency of CODdiss, which results in the fact
that the HiCS reactor performed better in terms of COD removal than the primary settler with an
optimized amount of Al3+ as coagulant.
Parallel to this thesis, a continuous HiCS reactor with an SRT of 1.18 ± 0.18 days, a tC of 16.6 ± 0.7 min
and a tS of 38 min was being operated by De Smedt (2015). At these operational conditions, a CODtot
removal efficiency of 60.0 ± 2.6 % was reported (De Smedt, 2015). The results of this continuous HiCS
reactor can be compared to those of the SBR HiCS reactor with an SRT of 1.31 days and a tC:tS of
15:40 min. This reactor achieved a similar 64.89 ± 3.02 % removal efficiency which confirms both
results. Hence, we can conclude that both in SBR mode as in continuous mode, HiCS systems are able
to attain a similar performance when operated under similar conditions.
When keeping the SRT constant around 0.5 days, the CODtot removal efficiency decreases when
decreasing the tC from 15 min to 8 min. This can especially be attributed to the decrease in CODcol
removal. In Figure 3.6 it is shown that the sludge of this reactor has a lower protein-LB-EPS
concentration in comparison with the reactor with a tC of 15 min. Since the LB-EPS concentration and
especially the protein fraction are correlated with adsorption of colloidal material, a lower CODcol
removal efficiency is a natural result. Assumingly, the LB-EPS is produced during the contact phase
and hydrolyzed during the stabilization phase, so a shorter tC would indeed result in a lower LB-EPS
concentration. Another possible explanation is that because the tC is so short, adsorption of CODcol is
not achieved to a full extent. This implies the selective advantage of producing more EPS is less
pronounced.
Lowering the tS from 40 min to 15 min also results in a significant decrease in COD removal. Here
both, the CODcol and CODdiss removal efficiencies decrease. The sludge protein-LB-EPS concentration
has decreased significantly. A possible explanation is that the tS may be too short for the sludge to
metabolize a sufficient amount of the organics that were absorbed during the contact phase. A
period of 15 min seems to lead to insufficient stabilization of the HiCS sludge, since a large fraction of
the substrate is still present in the cells.
In a previous study by Van Winckel (2014) in which two lab-scale SBR HiCS reactors were run with the
same synthetic influent, comparable removal efficiencies were attained. A first HiCS reactor was run
at an SRT of 1 day and a tC:tS of 20:20 min and achieved a low CODtot removal efficiency of
32.5 ± 5.3 %. Despite the large standard error, a similar removal efficiency of 39.7 ± 1.5 % was
achieved by the HiCS reactor with an SRT of 0.85 and a tC:tS of 15:15 min. The second reactor
operated by Van Winckel had an SRT of 1 day and a tC:tS of 5:35 min and achieved to remove only
29.7 ± 6.0 % of the CODtot (Van Winckel, 2014). Our HiCS reactor operated at an SRT of 0.88 days and
a tC:tS of 8:40 min approximates these operational conditions the closest, but achieved a better
CODtot removal efficiency of 54.5 ± 2.2 %. Most likely, this difference can be attributed to the slightly
longer tC of 8 min.
Page | 59
2. HiCS performance
When comparing the volumetric COD removal rates in Figure 3.3 with the volumetric loading rates in
Table 3.3, a logical correlation can be noticed. When the BV increases, the volumetric removal rate
also increases compared to the other reactors. If the BV would be more equal, the removal rates
would likely show the same trend as the COD removal efficiencies.
2.2 Sludge yield
The amount of sludge that can be yielded from a HiCS reactor is an important performance indicator.
The higher the yield, the more biogas can be produced by fermentation of the sludge during
anaerobic digestion. This results in a maximal production of useful energy. As shown in Figure 3.4,
the Yobs is negatively correlated to the SRT of the HiCS reactor with an correlation coefficient of
-0.967. This can be attributed to the fact that the rate at which the biomass concentration in the
reactors increases is less pronounced than the rate at which the waste flow rate decreases when the
SRT becomes longer.
The observation that the Yobs decreases when the SRT increases matches partially to Equation 4.1
formulated by Metcalf & Eddy (2003), where Yobs is expressed as a function of the maximal growth
yield (Ymax) and the SRT. A Ymax of 0.639 g CODsludge g-1 CODremoved is generally assumed for aerobic
heterotrophic growth of biomass. However, in this thesis, the yield is not only dependent on the
biomass growth, but also on the storage and sorption of organic substrate. Next to that, all effluent
particulate material is considered to be sludge which implies that even when no biomass activity
would be present in the reactor a biomass yield would be observed as an artifact of the calculation
method. These additional effects raise the Yobs to values up to 1 g CODSludge g-1 CODremoved which are
impossible to achieve when only the growth of biomass in the reactor is taken into account.
Therefore, it is reasonable to state that next to the relationship between Yobs and Ymax described in
Equation 4.1, additional parameters describe the Yobs in the HiCS system.
(Eq. 4.1)
2.3 Energy recovery
To predict the amount of useful chemical energy in the form of biogas that would be recovered from
the influent, the empirical relationship between the specific gas production (SGP) and the applied
SRT, established by Bolzonella et al. (2005), will be utilized (Equation 4.2). According to this equation,
a shorter SRT and thus a younger sludge age greatly improve the sludge digestion efficiency.
However, the lowest SRT used to determine this empirical relationship was 8 days, while the SRT
used for the HiCS reactors never exceeds 2.82 days. An estimation of the energy recovery in
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2. HiCS performance
g CODCH4 g-1 CODremoved van be made, when the methane content in biogas is assumed to be 60 vol%
(de Mes et al., 2003) and the theoretical COD value of methane is known to be 4.0 g CODCH4 g-1 CH4.
(
)
(Eq. 4.2)
Table 4.1: Prediction of energy recovery for each HiCS reactor. *Estimated values by implementation of Eq. 4.2.
Reactor
tC
tS
SRTact
SGP
Yobs
Energy recovery
3
-1
-1
-1
#
(min)
(min)
(days)
(m biogas kg VSS*) (kg VSS kg CODremoved) (kg CODCH4 kg CODremoved)
1
15
40
0.46
0.227
0.737
0.402
2
15
40
1.31
0.222
0.609
0.324
3
4
15
15
40
40
0.24
2.82
0.228
0.213
0.663
0.438
0.364
0.224
5
6
8
15
40
15
0.53
0.50
0.227
0.227
0.614
0.607
0.334
0.330
7
8
40
0.88
0.224
0.605
0.326
8
15
15
0.85
0.225
0.561
0.302
A prediction of the energy recovery, defined as the amount of CODCH4 that can be produced by
anaerobic digestion when 1 kg of organic matter from the SYNTHES is removed by the HiCS reactors,
is shown in Table 4.1. According to these results, the HiCS reactor with an SRT of 0.46 days at a tC:tS
of 15:40 min shows the most promising results when the aim is to maximize the recovery of chemical
energy from sewage. However, these results should only be used as an indication, because the SGP
of the different sludge types is only an estimation and should be verified by a biochemical methane
potential (BMP) test. Furthermore, the Yobs was achieved by feeding the HiCS reactors with synthetic
wastewater. To confirm the obtained results, the performance and especially the yield of the HiCS
reactor should be verified when treating real sewage.
2.4 COD balance
As shown in the top graph of Figure 3.5, the fraction of CODIN that ends up in the sludge of the waste
and reactor increases when the SRT shortens. The aim is to maximize this fraction since only this
sludge fraction can be harvested during the waste phase and digested to recover chemical energy. At
a tC:tS of 15:40 min, the main reason that this fraction increases with increasing SRT can be attributed
to the lower extent of oxidation of substrate. When the biomass concentration in the HiCS reactor
increases, the CODIN that has been biosorbed and stored by the biomass has to be divided amongst
more microbial cells. Each cell uses a part of these organics during respiration for its growth and
maintenance metabolism. When fewer cells are present, less substrate is needed for maintenance
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2. HiCS performance
respiration. This results in a larger fraction of the substrate that remains untouched in and on the
biomass. In other words, a larger fraction of the COD that we aim to recover remains available in the
sludge for digestion, while less of this COD is oxidized during the aeration phase.
Based on this graph, the optimal HiCS reactor is the one with an SRT of 0.24 days and a t C:tS of 15:40
min. However, the fraction of CODIN that ends up as recovered sludge from this HiCS reactor does not
differ strongly from the ones with an SRT of 0.46 and 1.31 days. Furthermore, an undesirably low
concentration of biomass (856 ± 97 mg VSS L-1) is present in the HiCS reactor with an SRT of 0.24
days. Vásquez et al. (2010) reported that the biomass concentration in a continuous contact
stabilization process preferably should vary between 1000 and 3000 mg VSS L-1 for the contact
reactor. Because of this and the fact that lower sludge concentrations bring along an increased risk of
a totally washing out the biomass, the assumption was made that this reactor would only perform up
to expectations under intensely controlled conditions like in a laboratory. In more realistic
conditions, real wastewater has to be treated and influent loading rates may fluctuate, so that a
more robust microbial community has to be present. Therefore, we decided to perform the
experiments with variable tC:tS at a longer SRT to achieve higher biomass concentration.
Furthermore, the HiCS reactors with a longer SRT achieved better results for the other performance
indicators: a potentially higher energy recovery was determined at an SRT of 0.46 days (Table 4.1)
and the COD removal efficiencies of the other HiCS reactors with the same tC:tS were significantly
higher (Figure 3.3).
At the bottom graphs of Figure 3.5 it is shown that lowering the tC from 15 to 8 min results in a
decreased fraction of CODIN that ends up as recovered sludge. This is may be the result of the fact
that by almost halving the contact time, the sludge does not have a sufficient amount of time to
adsorb and accumulate the same amount of organic substrate from the influent. The consequence of
this is that a larger COD fraction ends up in the effluent. When the tC is kept at 15 min, but the tS is
lowered from 40 to 15 min, a significant decrease of CODIN that ends up in the sludge that can be
harvested is observed. Especially the major decrease in CODdiss removal in contrast to the other
reactors has a major role in this result. It is likely that the biomass does not have enough time to
achieve sufficient aerobic regeneration during the stabilization phase. This could possibly have the
consequence that the substrate, which at a tC of 40 min would have been used for growth and
maintenance, partially remains in the cells. This could mean that during the next cycle the biomass is
not able to take up an equal amount of the newly fed substrate. The fact that respiration of the
biomass has not come to its end at 15 min of stabilization time is shown in Figure 3.10. Here, only
from the moment that the DO level reaches its second steady state, which is well beyond the 15 min
mark, respiration is assumed to be complete.
Important to note is that because of the calculation method, the COD balances would all have an
even more favorable outcome if the sludge was wasted after the settling phase as is done in a normal
WWTP. Now, because the sludge is wasted during the contact phase, a part of the soluble and
colloidal material that otherwise would end up in the effluent stream, is wasted too. To have a closer
approximation of the conditions in a real WWTP, the amount of CODcol and CODdiss that is determined
in the effluent is subtracted from the COD fraction in the waste and reactor and added to the
effluent COD fractions. However, this results in an overcompensation because a minor fraction of the
subtracted CODcol and CODdiss would still be present in the wasted sludge after settling. As a
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2. HiCS performance
consequence of this method of calculation, a smaller COD fraction that can be harvested from the
sludge and a larger fraction that ends up in the effluent are presented in the COD balances.
In Figure 4.1 a comparison is made between the COD balances of the SBR HiCS reactor and the CSTR
run by De Smedt (2015). The SBR HiCS reactor that is presented was run under operational
conditions that resemble the conditions in the CSTR the closest. As shown, no major differences
between the HiCS reactors are observed. However, the CSTR performed slightly worse than the SBR
in terms of accumulating COD in and on the sludge. Next to that, the effluent stream of the CSTR
contained a larger fraction of CODpart and CODcol than the SBR, but a smaller fraction of CODdiss was
retrieved in the effluent. Furthermore, the degree of mineralization of COD by respiratory processes
was about equal for both types of HiCS reactors. Hence, a similar performance can be found for both
the SBR and CSTR reactor types when operated under similar conditions.
Figure 4.1: Comparison COD balances of SBR and CSTR (De Smedt, 2015) HiCS reactors
When comparing the performance of the HiCS reactor to the results of the abiotic batch test in
Figure 3.14, an equal performance in sludge recovery can be observed between the HiCS reactor and
the primary settler with an optimal concentration of Al3+ as a coagulant. Typically chemically
enhanced primary sedimentation (CEPT) achieves CODpart removal efficiencies of 85 % (Metcalf &
Eddy, 2003). This is confirmed in Figure 3.13 where the primary settler with coagulant achieved a
CODpart removal efficiency of 79 % when treating SYNTHES. However, CEPT is not optimized for
removal of dissolved organic matter, which limits the maximum amount of organic matter that can
be recovered. The HiCS reactor is able to perform better in terms of CODdiss removal since the
biomass is able to accumulate this fraction of the COD within the cells by absorption. Even so,
because the biomass needs respiration, this extra CODdiss removal does not result in a higher COD
recovery in the sludge compared with the primary settler with Al3+.
Page | 63
2.5 Phosphate removal
Although the phosphate measurements were only indicative, a relative high phosphate removal in
each of the HiCS reactors was achieved. Phosphate accumulating organisms (PAO) are usually the
main group of microorganisms to achieve such high phosphate removal rates. The alternating regime
of aerobic and anaerobic phases and a high loading rate are typical features of the HiCS system.
These conditions are ideal for PAO to accumulate phosphorus in their cellular biomass and achieve
excess removal. The presence of PAO was not verified in this thesis and no research has proven their
capability to grow in an activated sludge plant at such low SRT. However, it was already shown that
efficient biological phosphorus removal could be obtained at SRT >2.9 days (Mamais & Jenkins,
1992).
2.6 Summary HiCS performance
In Table 4.2, a summary is presented of the most important performance indicators: CODtot removal
efficiency, degree of mineralization, COD recovery in waste and reactor and an estimation of the
energy recovery. The tC:tS of 15:40 min clearly achieved the best results in comparison with a tC:tS of
8:40 or 15:15 min. At an SRT of 1.31 days, the highest CODtot removal efficiency is achieved, but due
to the fact that a larger fraction of this COD is mineralized to CO2, the sludge yield is lower than the
one from the HiCS reactor with an SRT of 0.46 days. The latter reactor also has the largest potential
in recovering a maximal amount of energy, which is the eventual goal of this thesis.
Table 4.2: Summary of most important performance indicators. Standard error was used to indicate variation.
n.a.: not applicable. P.S.: primary settler. *Estimated values based on Eq. 4.2
Reactor
tC
tS
SRTact CODtot removal Mineralization
Yobs
Energy recovery*
-1
-1
#
(min)
(min) (days)
(%)
(%)
(kg VSS kg CODremoved) (kg CODCH4 kg CODremoved)
1
15
40
0.46
61.8 ± 2.1
8.1
0.737
0.402
2
3
15
15
40
40
1.31
0.24
64.6 ± 3.0
51.6 ± 2.8
16.3
0
0.609
0.663
0.324
0.364
4
15
40
2.82
59.6 ± 2.8
38.4
0.438
0.224
5
8
40
0.53
53.3 ± 3.4
6.7
0.614
0.334
6
15
15
0.50
44.0 ± 2.3
7.3
0.607
0.330
7
8
8
15
40
15
0.88
0.85
54.5 ± 2.2
39.7 ± 1.5
3.6
6.9
0.605
0.561
0.326
0.302
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3. EPS characterization and influence on HiCS performance
3. EPS characterization and influence on HiCS performance
In Figure 3.6, the protein and carbohydrate concentrations of both LB- and TB-EPS fractions are
presented. The EPS concentrations are in the order of 10-100 mg P-EPS or C-EPS g-1 VSS which is
about the same order of magnitude as concentrations found in literature (Brown & Lester, 1980; Li &
Yang, 2007; Shin et al., 2001). As can be seen, the largest variations can be observed in terms of PEPS concentration, while the C-EPS concentrations remain fairly constant in function of the SRT and
tC:tS. This suggests that especially the protein concentration of the EPS has an influence on certain
parameters like sorption of particulate and colloidal organic matter and on biomass flocculation,
sludge settlement and dewaterability. The P/C ratios and SVI are presented in Figure 3.7. An
important note is that the SVI of the HiCS reactors does not exceed a value of 55.5 ± 4.5 ml g-1 sludge.
Even this maximum observed value would still be desirable when achieved in large-scale settlers.
The P-EPS concentrations are the highest at an SRT of 0.46 and 1.31 days when the tC:tS is 15:40 min.
These two HiCS reactors also achieve the highest CODtot removal efficiencies. When the P-EPS
concentration decreases, the CODtot removal efficiency drops accordingly. The correlation between
these two parameters is confirmed by the correlation coefficients of 0.873 for P-TB-EPS and 0.639 for
P-LB-EPS. When comparing the P-EPS concentrations with the SVI, correlation coefficients of 0.768
and 0.567 are found for P-TB-EPS and P-LB-EPS, respectively. It is likely that sorption of organic
substrate and bioflocculation occur by the same type of interactions induced by the properties of the
EPS. Xie et al. (2010) reported that the presence of protein in EPS plays a more important role in
bioflocculation of cells than carbohydrate in EPS. They revealed that flocculation of cells decreased
sharply when they were treated with cellulase and proteinase K to destroy the EPS. When continuing
the treatment with only cellulase, the ability to flocculate recovered quickly. On the other hand,
when cellulase was removed and only Proteinase K continued on being added, the cells showed no
signs of recovery (Xie et al., 2010). Furthermore, Martin-Cereceda et al. (2001) reported that EPS in
biofilm reactors had twice the hydrophobicity of those in activated sludge. Hydrophobicity is a crucial
parameter to flocculation and settling of biomass. They showed that the amount of P-EPS was 3.5
times higher in a biofilm in comparison with activated sludge, while the quantities of humic acids and
carbohydrates were only twice as high (Martin-Cereceda et al., 2001). This confirms that also in this
case the P-EPS plays a more pronounced role than the C-EPS.
Resulting from the relatively constant C-EPS concentrations and variable P-EPS concentration, the
P/C ratios show about the same trend as the P-EPS in function of the SRT and the of the tC:tS of the
HiCS reactors. Another consequence is that the P/C ratio of the EPS, especially the LB-EPS fraction,
shown in Figure 3.7, is also positively correlated with the CODtot removal efficiency and the SVI. In
contrast to Shin et al. (2001) who reported that the settleability of the sludge increases together with
the P/C ratio of the EPS, a reverse correlation between these parameters was observed in these
results. However, many conflicting observations about this topic have been reported in literature:
Some papers suggest that C-EPS plays a more important role in bridging by divalent cations and thus
in bioflocculation (Bruus et al., 1992; Forster, 1985). Other researchers report that P-EPS has a more
positive effect on sludge hydrophobicity and bioflocculation (Dignac et al., 1998; Urbain et al., 1993).
Urbain et al. (1993) also reported a positive correlation between the EPS concentration and the SVI,
while Shin et al. (2001) found a negative correlation.
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4. Substrate storage - Polyhydroxybutyrate
Additionally, the amount of LB-EPS, represented by the fraction of the EPS that is easily extractable,
is thought to be more closely correlated to the sludge-water separation than the amount of TB-EPS
(Li & Yang, 2007). Although it is reported that EPS is essential to bioflocculation, an excessive amount
of EPS in the form of LB-EPS could weaken this floc formation and thus the sludge-water separation.
The EPS concentrations presented in Figure 3.6, show no significant correlation between the LB-EPS
and the SVI. However, in Figure 3.7, the P/C ratio of the LB-EPS seems to be more closely related to
the SVI than the P/C ratio of the TB-EPS. The correlation coefficients amount 0.783 and 0.491,
respectively. The P/C ratios of the LB-EPS and TB-EPS both show a minor positive correlation to the
CODtot removal efficiency. The respective correlation coefficients are 0.501 and 0.508.
To conclude, these results suggest that for HiCS reactors, which by definition operate at low SRT, and
thus low biomass concentrations, the EPS concentration of the sludge has only a limited effect on the
COD removal and the SVI. It is more likely that the amount of P-EPS in comparison with the amount
of C-EPS has a more pronounced influence on these parameters. The P/C ratio of the LB-EPS fraction
has a larger correlation coefficient to the SVI than the P/C ratio of the TB-EPS, which supports the
hypothesis that the LB-EPS is a better indicator for the sludge separation performance than TB-EPS.
4. Substrate storage - Polyhydroxybutyrate
The storage response in activated sludge should be triggered and enhanced when it is exposed to
very dynamic conditions (Daigger & Grady, 1982). Such dynamic conditions can be found in the HiCS
system due to its characterizing short SRT and contact times. Next to that, the typical feast-famine
regime of the HiCS system contributes to the occurrence of this storage response (Čech & Chudoba,
1983). This storage response is demonstrated by measuring the PHB concentration in the sludge.
In the HiCS reactor series where the tC:tS is kept constant at 15:40 min and the SRT increases from
0.24 to 2.82 days (left graph Figure 3.9), a maximum PHB concentration can be found at an SRT of
1.31 days. The fact that increasing the SRT to 2.82 days lowers the storage response can possibly be
explained by the lower selective pressure towards PHB accumulating microorganisms. Lowering the
SRT to 0.46 and 0.24 days also significantly decreases the PHB storage in the sludge. It is possible that
at such low SRT, the microorganisms that accumulate PHB are outcompeted by the remaining
microbial community.
When lowering the tC from 15 to 8 min, a different result is achieved between the reactor series with
an SRT of about 0.5 days and the series with an SRT of about 1 day. At an SRT of 0.5 days, the PHB
concentration in the sludge remains almost equal, while at an SRT of 1 day a great drop in PHB
storage is observed. This suggests that the effect of changing the tC depends on the SRT at which the
HiCS reactor is operated meaning that these parameters interact with one another. Lowering the tS
from 40 to 15 min significantly decreases the PHB storage response in both reactor series. However,
also for the tS, the decrease is less extensive relatively to the reactor with a tC:tS of 15:40 min. This
implies that there is an interaction effect between the SRT and the tS on the PHB storage response. A
small remark is that for the reactor series with an SRT of about 1 day, the difference in PHB
concentration in the sludge is also influenced by the significant difference in SRT between the HiCS
reactors.
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5. Intensive measurement campaigns
Another observation is that lowering the tC from 15 to 8 min has a less pronounced effect on the PHB
storage than lowering the tS from 40 to 15 min. This result is unexpected because it is contradictory
to the mechanism of how PHB is accumulated in the cells. During the anaerobic contact phase, PHB
accumulating microorganisms absorb rapidly biodegradable organics (rbCOD) and converse it to PHB
within the cell. The energy for rbCOD uptake is derived from the hydrolysis of intracellular storage
polymers like polyphosphate and glycogen. During the aerobic stabilization phase, PHB is oxidized,
providing energy for growth and regeneration of the storage polymers in the cells (Saunders et al.,
2003). This mechanism suggests that decreasing the tS should result in a higher PHB concentration,
while decreasing the tC has a negative effect on PHB storage. However, in these HiCS reactors both
variations result in a decreased concentration of PHB in the sludge. A possible explanation is that
although the presence of an aerobic/anaerobic phase, a feast-famine regime and a low SRT in the
HiCS reactors, a certain minimum length of the tC is required to accumulate a sufficient amount of
PHB in the cells, but also the tS has to have a certain length to be able to rebuild the polyphosphate
and glycogen.
5. Intensive measurement campaigns
During the follow-up of the DO level of each HiCS reactor (Figure 3.10), a gradual increase of the DO
level was noticed after 12 to 15 min. At this point of time, the substrate is presumably becoming
limited and thus less oxygen is needed for respiration. When the DO level reaches an upper steadystate value, the rbCOD is believed to be fully exhausted. The graph of the DO level of the HiCS
reactors with a tS of only 15 min does not show the same double steady-state curve as the one of the
other HiCS reactors with a tS of 40 min. Supposedly, a tS of 15 min is too short for the biomass to fully
exploit the substrate is has taken up during the contact phase for growth and maintenance
respiration.
During every intensive measurement campaign, a follow-up was performed of the biomass, EPS and
PHB concentrations through the different phases of the SBR cycle. However, the results of these
measurements were inconclusive and variations are more likely to be originating from experimental
errors than from changes in the sludge properties. A possible explanation is that the SBR cycle is just
too short to detect changes in sludge characteristics, like EPS production. These parameter changes
occur only very gradually over several SBR cycles and are undetectable during one SBR cycle. For PHB
storage, a more pronounced cyclical pattern was expected, as PHB is typically produced during feast
conditions and consumed during famine. However, no such pattern could be observed. Instead, the
PHB concentration remained relatively constant during the different phases. This may be explained
by the fact that the feast-famine alternation occurred too quickly to produce notable changes in the
PHB content of the biomass, or that variations during one cycle were too minimal to be detected
with the used techniques.
Page | 67
Page | 68
General conclusion
The aim of this thesis was to assess the potential of the HiCS system as a pre-concentration
technique for wastewater. The HiCS system was optimized in terms of energy recovery in the sludge
by variation of the SRT, tC and tS. The EPS concentration and composition were determined to
examine the possible correlation between the EPS and other performance indicators like the COD
removal efficiency and the SVI. The storage response of the sludge was evaluated by determination
of the PHB concentration in the sludge. Finally, the HiCS system was compared with a primary settler
in which chemically enhanced flocculation was used to concentrate the synthetic influent. A
summary of the conclusions is given, based on the research hypotheses:

While the C-EPS concentration remains relatively equal between the HiCS reactors, both the
P-EPS concentration and the P/C ratio of the EPS are dependent on the SRT, tC and tS.
Furthermore, the tC and tS possibly interact with the SRT, since the effect of changing the tC
or tS is dependent on the SRT.
o
o
The P-EPS concentration is positively correlated to the SVI as well as to the COD
removal efficiency. Because of the relatively constant C-EPS concentration, the P/C
ratio also shows a positive correlation to these two parameters.
No significant correlation between the LB-EPS concentration and the SVI was
observed. However, the P/C ratio of the LB-EPS is closer related to the SVI than the
P/C ratio of the TB-EPS. The TB-EPS concentration shows a closer correlation to the
CODtot removal efficiency than the LB-EPS concentration.

When keeping the tC:tS constant at 15:40 min, a maximum PHB concentration can be found
at an SRT of 1.31 days. Both the tC as the tS are positively correlated to the PHB storage
response. However, lowering the tC from 15 to 8 min has a less pronounced effect than
lowering the tS from 40 to 15 min.

The HiCS reactor with an SRT of 1.31 days and a tC:tS of 15:40 min achieved the highest CODtot
removal efficiency. Lowering the tC and tS results in a decreased COD removal efficiency. The
main distinction between the HiCS reactors can be attributed to the difference in CODcol and
CODdiss removal, and further optimization efforts should focus on increasing removal of these
two substrate fractions.

The sludge yield, and thus energy recovery, are maximal at an SRT of 0.46 days and a tC:tS of
15:40 min. The tC:tS of 15:40 min clearly achieved the best results in comparison with a tC:tS
of 8:40 or 15:15 min. The SRT was shown to be positively correlated to the SVI. However,
none of the SVI of the HiCS reactors is high enough to be problematic.

The highest efficiency in terms of CODcol removal is achieved by chemical flocculation, while
in terms of CODdiss removal, the HiCS reactor achieves the best result. This results in a better
CODtot removal, since colloidal substrate is only a minor constituent of wastewater. However,
the COD recovery was about equal in both reactors due to respiration of the biomass.
Page | 69
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Outreach
The HiCS process has already shown great potential as a wastewater pre-concentration technology.
For further optimization and implementation in large-scale applications of the HiCS system, some
suggestions for future research are made:

As shown in the results, the HiCS reactors with a tC:tS of 15:40 min and an SRT of 0.46 and
1.31 days achieved the best results in terms of COD removal and recovery. The intended SRT
of these reactors were 0.5 days and 1 day. Based on the results of their reactor performance,
a prediction is made that the true optimum of SRT lies somewhere around 0.8 - 1 day.

It was shown that reducing the tS to 15 min had a significant negative influence on the HiCS
reactor performance. Nonetheless, decreasing the tS from 40 min to at least 30 min should
presumably not have a great effect on the reactor performance. At 30 min of stabilization
time the DO level always reached its second steady-state period, suggesting that respiration
has ended. Reducing the aeration time by a factor 1/4, will also reduce the aeration costs,
which are usually one of the main costs in a WWTP, by 1/4. Conversely, in order to obtain a
stronger selection pressure for PHB-accumulating organisms, a longer ts might be needed to
entirely deplete PHB levels during stabilization.

A better estimation of the COD balance would be possible if the sludge is wasted from the
settled sludge bed after the settling phase instead of after the contact phase. This way, the
colloidal and soluble COD fractions in the effluent and the sludge are estimated correctly and
the COD balance of the HiCS system should be even more favorable.

A next step is to test the HiCS reactor performance at these optimal conditions when it is
treating real wastewater instead of SYNTHES. First, the reactor should be run with a
standardized batch of wastewater. For example, by collecting a large volume of the
wastewater, homogenizing and characterizing it, and keeping it stored in a cool place to
prevent deterioration. After that, the HiCS system should be tested in realistic fluctuating
conditions as they occur in the influent of a WWTP.

When the HiCS process is optimized at lab scale, it should be tested at pilot scale treating real
wastewater. Furthermore, the system should be subjected under realistic environmental
conditions, such as fluctuating outside temperatures.
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Page | 72
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Addendum
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