thesis title - uq espace

1

Mechanistic Understanding of Beneficial Aspects of Iron Salts

and Waterworks Sludge Uses in Urban Wastewater System

Sohan Shrestha

Master of Environmental Engineering (M. Eng.)

Kumoh National Institute of Technology (KIT), Gumi, South Korea

A thesis submitted for the degree of Doctor of Philosophy at

The University of Queensland in December 2019

School of Chemical Engineering

Advanced Water Management Centre (AWMC)

i

Abstract

Iron (Fe)-salts are widely used as the inorganic chemical coagulants for water and wastewater

treatment processes. In retrospect, Fe-salts application in different domains of the urban wastewater

system (UWWS) (e.g. sewers, bioreactor, digester) has been in isolation. The choice and application

of Fe-salts are at present primarily driven by considerations merely at the sub-system level, with their

potential impact on other sub-systems largely being ignored. This necessitates implementing the

integrated use of Fe (either in the form of Fe-salts or waterworks Fe-sludge) across the UWWS for

achieving the multiple benefits. With this integrated Fe strategy, the multiple benefits in the UWWS

could be achieved with the use of the same Fe, substantially reducing the chemical footprint.

However, there is inadequacy in understanding the potential implications of such integrated Fe usage

on other processes and sludge properties during the system-wide operation as the focus so far has

been the phosphorus- and sulfide-related reactions.

The transformation and transport of Fe in the sewer environment during the in-sewer Fe dosing play

a pivotal role in the availability of Fe in the downstream treatment units and hence additional benefits

during system-wide operation. Therefore, this study was carried out with the following overall

objectives: (i) to investigate the different key factors that influence the transformation and transport

of Fe in sewers; (ii) to investigate the impacts of sewer-dosed Fe-salt in relation to the mechanistic

understanding of the unintended potential benefits in downstream treatment units such as sludge

settleability and dewaterability; (iii) to investigate potential for reusing waterworks sludge in sewers

instead of their chemical counterparts (e.g. alum or Fe-salt) for sulfide and phosphate (PO43-) control

in sewer and compare their effectiveness. A number of laboratory, pilot-scale, and field studies were

carried out to fulfil these objectives. Significant contributions of this thesis are outlined below.

Concerning the sewer-dosed Fe-salt, both transformation and transport of Fe are important for the

availability of Fe in the downstream treatment units and the realization of the additional benefits in

downstream WWTP. Here measurements on a full-scale primary settling tank (PST) were undertaken

with two different Fe dosing locations, namely WWTP inlet (minimal retention of Fe prior to PST)

and a branch sewer several kilometres upstream (15 km) of the receiving WWTP. Results showed

that upstream sewer dosing resulted in minimal in-sewer Fe retention, with only 11% of Fe dosed

upstream, reaching the PST (when compared between Fe dosed and Fe reaching the PST). The Fe

retention in the PST (quantified as a difference between the influent and effluent concentration) was

very similar for the two dosing cases. However, total suspended solids (TSS) removal in the PST was

ii

better for upstream sewer dosing than for WWTP inlet dosing trial. To further elucidate the

mechanism, carefully designed laboratory experiments tested the influence of mixing-reaction time

(simulating in-sewer retention) and redox conditions on reactions between sulfide and Fe added as

either ferric chloride salt (Fe-salt) or Fe-rich water treatment sludge (Fe-sludge). With Fe-salt,

dissolved Fe(aq) concentration in the supernatant at the end of each experiment was much lower under

anaerobic conditions (0.40.1 mg.Fe.L-1) than under oxic-to-anaerobic transition conditions (2.20.1

mg.Fe.L-1). Under oxic-to-anaerobic transition conditions with Fe-salt, a short mixing-reaction time

(0.5 hr) showed less settling separation of Fe. In contrast, with Fe-salt under purely anaerobic

conditions, Fe settling separation was not significantly different between a short (0.5 hr) and long

(6.0 hr) mixing-reaction time. Measured particle size distributions (PSDs) were largely dominated by

background suspended solids, but showed particle size increase, possibly due to the coagulating effect

of dissolved Fe2+ and/or growth of FeSx precipitates. With Fe-sludge under oxic-to-anaerobic

transition conditions, particulate Fe(T) settled rapidly, but dissolved Fe(aq) remained low (0.280.04

mg.Fe.L-1), indicating delayed chemical reduction of Fe in the sludge by added sulfide. Overall, the

findings suggested there are important time-based interactions between the dosed Fe and sewage

suspended solids in a sewer, influencing suspended solids settleability in a downstream PST.

Importantly, in-sewer retention time, in-sewer redox conditions, and Fe-source type (Fe-salt/Fe-

sludge being used) are important influencing factors for Fe fractionation and settling separation. All

these factors must be considered when choosing strategies for Fe dosing to sewer to achieve multiple

benefits across integrated UWWS.

In an integrated sewer-WWTP operation, Fe-salts added to sewers control sulfide accumulation

through precipitation. The precipitated Fe, which later undergoes chemical changes under an aerobic

environment in the bioreactor and becomes available for phosphate precipitation, also may interact

with the activated sludge affecting its properties including settling and dewatering performances.

Similarly, the Fe that is carried over to the anaerobic digester (AD) unit from the upstream sewer in

different forms, mainly as precipitates is further likely to interact with the anaerobically digested

sludge and hence affecting the digestate properties. One of the major concerns in this regard is

whether the interactions (associated with Fe) would lead to inferior sludge characteristics (i.e. impact

sludge properties) with implication on sludge settleability and dewaterability other than the

phosphate- and sulfide-related reactions in downstream WWTP. This thesis presented an unintended

beneficial impact of sewer-dosed Fe-salt on activated sludge unit’s performance, i.e. improved

settleability and dewaterability of iron-conditioned activated sludge over the unconditioned activated

sludge. Mean differences in sludge index volume (SVI) and dewatered cake solids content (%) values

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between iron-conditioned and unconditioned activated sludges were 22.5±7.8 mL.g-1 (p<0.05) and

7.8±1.2% (p<0.05), respectively. Similarly, sewer-based Fe dosing resulted in improvement of

dewaterability of iron-conditioned digestate. Iron-conditioned digestate exhibited improved

dewaterability with dewatered cake solids content (%) of 19.20.1% as compared to unconditioned

digestate of 15.50.4%. These beneficial impacts are attributed to the favourable changes exhibited

by Fe-conditioning on key physicochemical, morphological, and rheological properties of activated

sludge and digestate. Overall, these results elucidated the mechanism of synergy among the changes

in key sludge properties for improving settleability and dewaterability. Besides the positive impacts

of in-sewer Fe-salt dosing on sludge settleability and dewaterability, sewer-dosed Fe-salt in

experimental system exhibited a decreased phosphate concentration (mg.P.L-1) in bioreactor effluent

(by 41.2±6.3%) than control system. Importantly, the biological nitrogen removal performance of Fe-

dosed bioreactor also remained unaffected.

Akin to integrated use of inorganic chemical coagulant, if successful reuse of waterworks sludge (as

an alternative to their chemical counterparts) in integrated UWWS operation could be achieved, this

would have a major impact on both sustainable WTP sludge management and the urban wastewater

management. Results affirmed the benefits of direct dosing of waterworks Fe-/Al-sludge to full-scale

sewers as a viable end use for sludge generated from WTP. Reusing waterworks Fe-sludge dosing

was effective for sulfide removal at a ratio of 0.290.06 mg.S.(mg.Fe)-1 but exhibited limited effect

on PO43- removal. Likewise, Al-sludge was effective for phosphate removal at ratio of 0.290.01

mg.P.(mg.Al)-1, but with limited effect on sulfide removal. The mixing of the sludge stream with raw

wastewater, i.e. dilution effect, was primarily responsible for observed reduction in soluble chemical

oxygen demand (sCOD) concentrations, under both Fe-/Al-sludge dosing. The Fe-/Al-sludge dosing

did not cause any increment in dissolved methane (CH4) and nitrous oxide (N2O) formation, nor

release of other heavy metals. Combined spectroscopic, spectrometric, and microscopic analyses

suggest a precipitation reaction between sulfide and ferric ions in Fe-sludge, is likely to be the

dominant mechanism for sulfide removal when dosing Fe-sludge. In terms of phosphate removal with

Al-sludge dosing, ligand-exchange processes between surface hydroxyl (-OH) groups and PO43- ions,

favouring the formation of both inner- and outer-sphere surface Al-phosphate complexes, appears to

be the dominant mechanism. These results demonstrated the potential multiple benefits of dosing

waterworks Fe-/Al-sludge in sewers.

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The findings of this thesis improved our understanding of different key factors influencing Fe-

transformation/fractionation and transport in the sewer when implementing sewer based Fe dosing,

demonstrated additional benefits that could be achieved in downstream treatment units with sewer-

dosed Fe-salts in relation to sludge properties, and also affirmed the benefits of reusing waterworks

Al-/Fe-sludges in full-scale sewers. Such holistic and comprehensive understanding, elucidating the

multiple benefits of Fe-salt and waterworks sludge dosing in sewers, would further enhance the

confidence of applying Fe dosing in sewers for the integrated management for an UWWS in a cost-

effective manner.

v

Declaration by author

This thesis is composed of my original work and contains no material previously published or

written by another person except where due reference has been made in the text. I have clearly stated

the contribution of others to jointly authored works that I have included in my thesis.

I have clearly stated the contribution of others to my thesis as a whole, including statistical

assistance, survey design, data analysis, significant technical procedures, professional editorial

advice, and any other original research work used or reported in my thesis. The content of my thesis

is the result of work I have carried out since the commencement of my research higher degree

candidature and does not include a substantial part of work that has been submitted to qualify for

the award of any other degree or diploma in any university or other tertiary institution. I have clearly

stated which parts of my thesis, if any, have been submitted to qualify for another award.

I acknowledge that an electronic copy of my thesis must be lodged with the University Library and,

subject to the policy and procedures of The University of Queensland, the thesis be made available

for research and study in accordance with the Copyright Act 1968 unless a period of embargo has

been approved by the Dean of the Graduate School.

I acknowledge that the copyright of all material contained in my thesis resides with the copyright

holder(s) of that material. Where appropriate I have obtained copyright permission from the

copyright holder to reproduce material in this thesis and have sought permission from co-authors

for any jointly authored works included in the thesis.

vi

Publications during candidature

Peer-reviewed scientific journal articles

• Sohan Shrestha, Keshab Sharma, Zhongwei Chen, Zhiguo Yuan (2019). Unravelling the

influences of sewer-dosed iron salts on activated sludge properties with implications on

settleability, dewaterability and sludge rheology. Water Research, 167, 115089

(https://doi.org/10.1016/j.watres.2019.115089)

• Sohan Shrestha, Jagadeeshkumar Kulandaivelu, Keshab Sharma, Guangming Jiang, Zhiguo

Yuan* (2020). Effects of dosing iron- and alum-containing waterworks sludge on sulfide and

phosphate removal in a pilot sewer. Chemical Engineering Journal, 387, 124073

(https://doi.org/10.1016/j.cej.2020.124073)

• Sohan Shrestha, Jagadeeshkumar Kulandaivelu, Mario Rebosura, Zhiguo Yuan, Keshab Sharma

(2020). Revealing the variations in physicochemical, morphological, fractal, and rheological

properties of digestate during the mesophilic anaerobic digestion of iron-rich waste activated

sludge. Chemosphere, 254, 126811 (https://doi.org/10.1016/j.chemosphere.2020.126811)

• Sohan Shrestha, Jagadeeshkumar Kulandaivelu, Keshab Sharma*, Zhiguo Yuan, Stephan Tait

(2019). Transformation and transport of sewer-dosed iron in urban wastewater systems (submitted

to ‘Water Research’)

• Sohan Shrestha, Guangming Jiang, Apra Boyle Gotla, Lisha Guo, Madhu Krishna Murali,

Keshab Sharma, Zhiguo Yuan. In-sewer physical, chemical, and biological processes modelling

approaches – a critical review. (‘paper in final preparation - to be submitted’)

• Jagadeeshkumar Kulandaivelu, Jianfa Gao, Yarong Song, Sohan Shrestha, Xuan Li, Jiaying Li,

Katrin Doederer, Jurg Keller, Zhiguo Yuan, Jochen F. Mueller, Guangming Jiang* (2019).

Removal of Pharmaceuticals and Illicit Drugs from Wastewater Due to Ferric Dosing in Sewers.

Environmental Science & Technology, 53, 6245-6254 (https://doi.org/10.1021/acs.est.8b07155 )

• Jagadeeshkumar Kulandaivelu, Sohan Shrestha, Wakib khan, Jason Dwyer, Alan Steward, Leo

Bell, Paul Mcphee, Peter Smith, Shihu Hu, Zhiguo Yuan, Guangming Jiang (2020). Full-scale

trials of ferrous dosing in sewers and wastewater treatment plant for multiple benefits.

Chemosphere, 250, 126221 (10.1016/j.chemosphere.2020.126221)

• Jia Meng, Haoran Duan, Huijuan Li, Shane Watts; Peng Liu, Sohan Shrestha; Min Zheng, Jason

Dwyer, Shihu Hu, Zhiguo Yuan (2020). Free nitrous acid pre-treatment enhances anaerobic

digestion of waste activated sludge and rheological properties of digested sludge: a pilot-scale

https://doi.org/10.1016/j.watres.2019.115089

https://doi.org/10.1016/j.cej.2020.124073

https://doi.org/10.1016/j.chemosphere.2020.126811

https://doi.org/10.1021/acs.est.8b07155


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study. Water Research, 172, 115515 (https://doi.org/10.1016/j.watres.2020.115515)

• Jagadeeshkumar Kulandaivelu, Phil M. Choi, Sohan Shrestha, Xuan Li, Yarong Song, Jiaying

Li, Keshab Sharma, Zhiguo Yuan, Jochen F. Mueller, Guangming Jiang* (2019). Assessing the

removal of organic micropollutants from wastewater by discharging drinking water sludge to

sewers. Water Research, 115945 (https://doi.org/10.1016/j.watres.2020.115945)

Conference presentations

• Sohan Shrestha, Keshab Sharma, Zhiguo Yuan. Understanding the multiple beneficial aspects

of iron-salts uses in integrated urban wastewater system – Lessons learned from lab-scale and

pilot studies (MulFe Concept – saga from novice to ninja). 10th International Water & Health

Seminar. ADSOM Windsor Residence, 16 av. Windsor, Cannes (France), June 25-27, 2018.

• Sohan Shrestha, Christian Kazadi Mbamba, Keshab Sharma, Zhiguo Yuan. Integrated plant-

wide modelling focussing on multiple uses of iron salts: investigation of effect of change in

single sludge-line process configurations. EAIT postgraduate conference, 2017.

• Sohan Shrestha, Christian Kazadi Mbamba, Keshab Sharma, Zhiguo Yuan. In-Sewer Physical,

Chemical and Biological Processes Modelling Approaches – A Review. EAIT postgraduate

conference, 2016

Queensland Water Awards – Finalist

Finalist in the Queensland Water Awards, Australian Water Association (AWA) for the ‘Student

Water Prize – 2019’ “Reusing Iron- and Aluminium-Containing Waterworks Sludge for Sulfide and

Phosphate Removal in Sewers: A Pilot-Scale Investigation”

(http://www.awa.asn.au/AWA_MBRR/About_AWA/Awards/State_Awards/QLD.aspx)

Queensland Water Awards Winner for ‘Research Innovation Award’ – Team Member

Winner of ‘Research Innovation Award – 2019’, Queensland Water Award (QWA), for the research

project, ‘An Integrated Approach to Iron Salt in Urban Water Systems’. Winner of QWA becomes

automatically finalist for the national Australian Water Award (winner will be announced on 11 June

2020 during Ozwater’20) (http://ozwater.org/program/awards)



http://www.awa.asn.au/AWA_MBRR/About_AWA/Awards/State_Awards/QLD.aspx

http://ozwater.org/program/awards

viii

Publications included in this thesis

1. Sohan Shrestha, Jagadeeshkumar Kulandaivelu, Keshab Sharma*, Zhiguo Yuan, Stephan Tait

(2019). Transformation and transport of sewer-dosed iron in urban wastewater systems (submitted

to ‘Water Research’ and under review) – this has been modified and wholly incorporated in the

Chapter 4

Contributor (Authors) Statement of contribution

(relates specifically to the published paper)

Sohan Shrestha

(PhD candidate)

established the research methodology, conducted all

experiments/analyses, and composed the content of

manuscript from initial draft to final submission. (70%)

Jagadeeshkumar

Kulandaivelu

participated in the field full-scale studies ad also

participated in the discussion of experimental results.

(5%)

Keshab Sharma participated in the discussion of experimental results,

and made comments on the manuscript. (5%)

Zhiguo Yuan participated in the discussion of experimental results,


Stephan Tait advised on experimental design, and critically reviewed

the manuscript. (15%)

ix

2. Sohan Shrestha, Keshab Sharma*, Zhongwei Chen, Zhiguo Yuan (2019). Unravelling the

influences of sewer-dosed iron salts on activated sludge properties with implications on

settleability, dewaterability and sludge rheology. Water Research, 167, 115089

(https://doi.org/10.1016/j.watres.2019.115089) – this has been modified and wholly incorporated

in the Chapter 5



Sohan Shrestha

(PhD candidate)




Keshab Sharma advised on experimental design, and critically reviewed


Zhongwei Chen participated in the discussion of experimental results,


Zhiguo Yuan advised on experimental design, and critically reviewed



x

3. Sohan Shrestha, Keshab Sharma*, Jagadeeshkumar Kulandaivelu, Mario Rebosura, Zhiguo

Yuan (2019). Revealing the variations in physicochemical, morphological, fractal, and

rheological properties of digestate during the mesophilic anaerobic digestion of iron-rich waste

activated sludge (accepted for publication in ‘Chemosphere’) – this has been modified and wholly

incorporated in the Chapter 6



Sohan Shrestha

(PhD candidate)




Keshab Sharma advised on experimental design, and critically reviewed


Jagadeeshkumar

Kulandaivelu

helped with the use of analytical equipment and

participated in the discussion of experimental results.

(5%)

Mario Rebosura participated in the discussion of experimental results.

(5%)



xi

4. Sohan Shrestha, Jagadeeshkumar Kulandaivelu, Keshab Sharma, Guangming Jiang, Zhiguo

Yuan* (2019). Effects of dosing iron- and alum-containing waterworks sludge on sulfide and

phosphate removal in a pilot sewer (accepted for publication in ‘Chemical Engineering Journal’)

– this has been modified and wholly incorporated in the Chapter 7



Sohan Shrestha

(PhD candidate)




Jagadeeshkumar

Kulandaivelu

helped with the pilot sewer studies and participated in

the discussion of experimental results. (5%)

Keshab Sharma advised on experimental design, and participated in the

discussion of experimental results (5%)

Guangming Jiang advised on experimental design, and participated in the

discussion of experimental results (5%)



xii

Contributions by others to the thesis

This thesis includes the contributions made by others, especially in the analytical sample analyses.

These contributions are acknowledged as follows:

• Dr. Beatrice Keller-Lehmann, Mrs. Jianguang Li, and Mr. Nathan Clayton from AWMC

analytical lab, operated the Flow Injection Analyser (FIA), Inductively Coupled Plasma Optical

Emission Spectrometry (ICP-OES), Ion Chromatograhy (IC), and Gas Chromatography (GC)

• Mr. Jagadeeshkumar Kulandaivelu from AWMC facilitated with the operation of Fluorescence

Spectrometer

• Mr. Mario Rebosura facilitated in the long-term operation of integrated sewer-WWTP laboratory

set up

• Dr. Ekaterina Strounina from Centre for Advanced Imaging (CAI), UQ helped with the Solid

State Nuclear Magnetic Resonance (NMR) spectroscopy

• A/Prof. Jeff Harmer from Centre for Advanced Imaging (CAI), UQ helped with the Electron

Paramagnetic Resonance (EPR) spectroscopy

• Dr. Javaid Khan from Australian National Fabrication Facility (ANFF) helped with the operation

of Attenuated Total Reflectance-Fourier Transform Infrared Spectrometer (ATR-FTIR)

• Ms Eunice Grinan from Centre for Microscopy and Microanalysis (CMM) helped with the

operation of Scanning Electron Microscopy (SEM)

• Dr. Clement Chen, School of Chemical Engineering helped with the Differential Scanning

Calorimetry (DSC)

• Dr. Will Andersen, Australian Institute for Bioengineering and Nanotechnology, Trau’s Lab

facilitated in using the Malvern Mastersizer 3000

• Chris Carney (AWMC, UQ) facilitated in the thermogravimetric analysis

• Emeritus Prof. Ted (Edward White), School of Chemical Engineering facilitated in using the

Mastersizer/E

xiii

Statement of parts of the thesis submitted to qualify for the award of another degree

None.

Research involving human or animal subjects

No animal or human subjects were involved in this research

xiv

Acknowledgements

I owe my deepest gratitude from the inner core of my heart to my supervisors, Professor Zhiguo Yuan

and Dr. Keshab Sharma, who offered incessant excellent supervision and generous help from the start

to finish of my PhD study. My supervisors provided me guidance in my research with not only their

broad and in-depth knowledge but also with their immaculate passion and enthusiasm. This thesis

would have not been possible without their consistent encouragement, guidance, and support

throughout my PhD candidature. I feel so lucky and blessed to conduct my PhD study under their

supervision.

I would like to extend my sincerest gratitude to Dr. Stephan Tait (Centre for Agricultural Engineering,

University of Southern Queensland), who helped me in a number of ways. Truly speaking, his

supervision and untiring help completely transformed by vision towards the research world. He also

provided valuable advice and discussion with his expertise and insights, which functioned as a

catalyst to me to achieve a higher level.

I am grateful to the generous financial support provided through the University of Queensland (UQI)

International Tuition and Living Allowance Scholarship, which indeed materialized my plan to

pursue my doctoral degree at the Advanced Water Management Centre (AWMC), an internationally

recognized research centre. I would also like to thank the Australian Research Council together with

the national/international research project partners: District of Columbia Water and Sewer

Authority (DC Water), Queensland Urban Utilities (QUU), South East Queensland Water

(SeqWater), PUB Singapore's National Water Agency, and Water Research Australia Ltd for their

support through the Australian Research Council Linkage Project LP 140100386.

I am indebted to Dr. Beatrice Keller-Lehmann, Mr. Nathan Clayton, and Ms. Jianguang Li for their

help in samples analyses throughout my candidature. I would also like to thank few other individuals

for their assistance in my research works, namely, Ms. Eunice Grinan and Mr. Richard (Rick) Webb

from Centre of Microscopy and Microanalysis (CMM), Dr. Ekaterina Strounina and A/Prof. Jeff

Harmer from Centre for Advanced Imaging (CAI), Dr. Javaid Khan from Australian National

Fabrication Facility (ANFF), Dr. Will Andersen and Dr. Rebecca Lane from Australian Institute for

Bioengineering and Nanotechnology, Dr. Clement Chen and Emeritus Prof. Ted from School of

xv

Chemical Engineering. It is an honour for me to work with the people in the sewer research group

especially Mr. Jagadeeshkumar Kulandaivelu, Mr. Mario Rebosura, Mr. Sirajus Salehin, Dr.

Guangming Jiang, Prof. Jurg Kellar, Dr. Ilje Pikaar, and Dr. Eloise Larsen. I am equally grateful to

the AWMC administrative staff, many postgraduate research students, and other academics who gave

so generously their support and kindness. I offer my regards to all of those who supported me in any

respect during my PhD candidature, particularly Dr. Andrew Ward, Dr. Tim Huelsen, Dr. Sergi

Astals, Dr. Huanfei Meng, Dr. Katie Mcintosh, Dr. Andrew Laloo, Dr. Adam Shypanksi, Dr. Madhu

Murali (UWA), Mr. Peter Smith, Ms. Sharon James, Mrs. Vivienne Clayton, Mr. Charles Eddy, and

Ms. Nelly Juillet.

Last but not least, I am whole-heartedly thankful to my parents, my lovely better-half, Deepa Shrestha

including my brother (Anish) and sisters (Sajana, Sabina, Dipika, Dichhya). Their continuous faith,

encouragement, and moral support were indeed a driving force that kept me hustling throughout my

PhD candidature.

xvi

Financial support

This research was supported by the University of Queensland International Scholarship (UQI) (living

allowance + tuition fee).

Keywords

Iron salts; waterworks Fe-/Al-sludge reuse; urban wastewater system; integrated multiple Fe uses;

Fe-transport; Fe-transformation; activated sludge; digestate; settleability; dewaterability

Australian and New Zealand Standard Research Classifications (ANZSRC)

ANZSRC code: 090703, Environmental Technologies, 50%

ANZSRC code: 090409, Wastewater Treatment Process, 50%

Fields of Research (FoR) classification

FoR code: 0907, Environmental Engineering, 50%

FoR code: 0904, Chemical Engineering, 50%

xvii

Table of contents

Abstract .............................................................................................................................................. i

Declaration by author ...................................................................................................................... v

Publications during candidature ................................................................................................... vi

Contributions by others to the thesis ............................................................................................ xii

Statement of parts of the thesis submitted to qualify for the award of another degree ......... xiii

Research involving human or animal subjects ........................................................................... xiii

Acknowledgements ........................................................................................................................ xiv

Financial support .......................................................................................................................... xvi

Keywords ....................................................................................................................................... xvi

Australian and New Zealand Standard Research Classifications (ANZSRC) ........................ xvi

Fields of Research (FoR) classification ....................................................................................... xvi

Table of contents .......................................................................................................................... xvii

List of figures ............................................................................................................................... xxiii

List of tables ................................................................................................................................ xxxii

List of nomenclature ................................................................................................................. xxxvi

Chapter 1........................................................................................................................................... 1

Introduction and literature review ................................................................................................. 1

1.1 Chemical use in urban water system ........................................................................................ 1

1.2 Overview of Fe-salts uses in various components of urban water system and associated

implications .............................................................................................................................. 4

1.2.1 Use of Fe-salt in water treatment plant .............................................................................. 4

1.2.2 Use of Fe-salts in sewers ................................................................................................... 7

1.2.3 Use of Fe-salts in activated sludge system ...................................................................... 10

1.2.4 Use of Fe-salts in anaerobic digester ............................................................................... 12

1.3 Reuse of waterworks Fe- or Al-sludge in urban water system ............................................... 16

1.3.1 Current trend of reusing waterworks sludge .................................................................... 16

xviii

1.3.2 Opportunities for reusing waterworks sludge .................................................................. 17

1.4 Activated sludge and digestate properties .............................................................................. 18

1.4.1 Settleability and dewaterability of sludges ...................................................................... 18

1.4.2 Key sludge properties that affect settleability and dewaterability ................................... 19

1.5 Knowledge gaps and research questions ................................................................................ 25

1.6 Thesis outline .......................................................................................................................... 30

Chapter 2....................................................................................................................................... 31

Research objectives ........................................................................................................................ 31

Chapter 3....................................................................................................................................... 33

Materials and methods ................................................................................................................. 33

3.1 Overview of integrated laboratory set up and operation ........................................................ 33

3.2 Overview of pilot-scale rising main set up and operation ...................................................... 35

3.3 Overview of Luggage Point WWTP and full-scale tests ........................................................ 37

3.4 Dewaterability and settleability tests ...................................................................................... 39

3.5 EPS fraction extraction and analysis ...................................................................................... 40

3.6 Compositional analysis of extracted EPS fractions ................................................................ 41

3.7 Rheological tests ..................................................................................................................... 42

3.7.1 Steady shear rheological tests .......................................................................................... 42

3.7.2 Dynamic shear rheological tests ...................................................................................... 44

3.8 Analytical methods ................................................................................................................. 46

3.8.1 General parameters .......................................................................................................... 46

3.8.2 Bound water and total water contents .............................................................................. 46

3.8.3 Particle size distribution................................................................................................... 48

3.8.4 Fractal dimension ............................................................................................................. 48

3.9 Statistical analysis .................................................................................................................. 50

Chapter 4......................................................................................................................................... 51

Elucidating factors influencing the transformation and transport of sewer-dosed iron in the

xix

urban wastewater systems ............................................................................................................. 51

4.1 Introduction ............................................................................................................................ 52

4.2 Materials and methods ............................................................................................................ 53

4.2.1 Full-scale FeCl2 dosing tests ............................................................................................ 53

4.2.2 Laboratory experiments ................................................................................................... 56

4.2.3 Analytical methods .......................................................................................................... 63

4.3. Results and discussion ........................................................................................................... 64

4.3.1 Full-scale Fe-salt dosing trials ......................................................................................... 64

4.3.2 Laboratory mixing-reaction-settling experiments ........................................................... 73

4.3.3 Implications ..................................................................................................................... 86

4.4. Conclusion ............................................................................................................................. 87

Chapter 5......................................................................................................................................... 89

Unravelling the influences of sewer-dosed iron salts on activated sludge properties with

implications on settleability and dewaterability .......................................................................... 89

5.1. Introduction ........................................................................................................................... 90

5.2. Materials and methods ........................................................................................................... 92

5.2.1 Overview of laboratory apparatus and sludge sources .................................................... 92

5.2.2 Experimental procedures ................................................................................................. 96

5.2.3 Analytical methods .......................................................................................................... 96

5.2.4 EPS extraction and analysis ............................................................................................. 97

5.2.5 Rheological tests .............................................................................................................. 98

5.2.6 Statistical analysis ............................................................................................................ 98

5.3. Results ................................................................................................................................... 98

5.3.1 Variation in sludge settleability and dewaterability ........................................................ 98

5.3.2 Changes in content and composition in EPS fractions .................................................. 101

5.3.3 Changes in cations distribution in EPS .......................................................................... 106

5.3.4 Changes in particle size distribution and bound water content ..................................... 108

xx

5.3.5 Changes in rheological properties .................................................................................. 115

5.4. Discussion ............................................................................................................................ 123

5.5. Conclusion ........................................................................................................................... 127

Chapter 6....................................................................................................................................... 128

Revealing the influence of sewer-dosed iron salts on anaerobically digested sludge properties

with implications on improving dewaterability ......................................................................... 128

6.1 Introduction .......................................................................................................................... 129

6.2 Materials and methods .......................................................................................................... 131

6.2.1 Sources of digestates ...................................................................................................... 131

6.2.2 Experimental framework ............................................................................................... 132

6.2.3 EPS fraction extraction and analysis ............................................................................. 133

6.2.4 Compositional analysis of EPS fractions ....................................................................... 134

6.2.5 Rheological measurements ............................................................................................ 134

6.2.6 Analytical methods ........................................................................................................ 134

6.2.7 Statistical analysis .......................................................................................................... 136

6.3 Results .................................................................................................................................. 136

6.3.1 Variation in digestate dewaterability ............................................................................. 136

6.3.2 Variations in physicochemical properties ...................................................................... 137

6.3.3 Variations in morphological and fractal properties ....................................................... 147

6.3.4 Variations in rheological properties ............................................................................... 151

6.4 Discussion ............................................................................................................................. 161

6.5 Conclusion ............................................................................................................................ 164

Chapter 7....................................................................................................................................... 166

Effects of dosing iron- and aluminium-containing waterworks sludge on sulfide and phosphate

removal in a pilot sewer ............................................................................................................... 166

7.1 Introduction .......................................................................................................................... 167

7.2 Material and methods ........................................................................................................... 169

7.2.1 Pilot rising mains set-up and operation.......................................................................... 169

xxi

7.2.2 Fe- and Al-sludge dosing to pilot sewer ........................................................................ 169

7.2.3 Batch tests to investigate effects of Al:P dosage ratio and suspended solids on phosphate

removal .......................................................................................................................... 173

7.2.4 Analytical methods ........................................................................................................ 174

7.2.5 Statistical analysis .......................................................................................................... 175

7.3 Results and discussion .......................................................................................................... 176

7.3.1 Effects of Fe-sludge dosing on sewage characteristics .................................................. 176

7.3.2 Mechanism of sulfide removal in sewer when dosing Fe-sludge .................................. 182

7.3.3 Effects of Al-sludge dosing on sewage characteristics .................................................. 186

7.3.4 Effects of Al:P dosage ratio and suspended solids on phosphate removal .................... 192

7.3.5 Mechanism of phosphate removal in sewers when dosing Al-sludge ........................... 194

7.3.6 Implications of dosing waterworks Al- or Fe-sludge in sewers .................................... 198

7.4. Conclusion ........................................................................................................................... 200

Chapter 8....................................................................................................................................... 202

Conclusions and future research work ...................................................................................... 202

8.1 Summary of this research work ............................................................................................ 202

8.2 Main conclusions of the thesis ............................................................................................. 207

8.3 Recommendation for future research works ......................................................................... 209

References ..................................................................................................................................... 211

Appendices .................................................................................................................................... 237

Appendix A: Coagulation performance – comparative studies between alum and iron salt towards

finished water qualities ......................................................................................................... 238

Appendix B: Microbial community analysis (MCA) in sludges ................................................ 240

Appendix C: Flow-on downstream effects of in-sewer Fe-salt dosing on bioreactor performance

.............................................................................................................................................. 243

Appendix D: An illustrative example of determination of TTQ and relative sludge network

strength of an iron-conditioned activated sludge (SBR-E) ................................................... 245

Appendix E: Characterization of Fe- and Al-sludge samples using XRD, ATR-FTIR, SEM-EDX,

xxii

and NMR techniques ............................................................................................................ 248

Appendix F: Examination of additional absorbance peaks observed in IR spectra of sample before

and after Fe-sludge dosing .................................................................................................... 250

Appendix G: Characteristics and mechanism of phosphate removal when using waterworks Al-

sludge – overview of hydrolysis-adsorption experiment ...................................................... 252

Appendix H: Comparative overview of previous studies on application of waterworks Al-/Fe-

sludge in treating wastewater with the present study ........................................................... 257

xxiii

List of figures

Figure 1. Schematic representation of a conventional urban water system (UWS)............................ 1

Figure 2. Typical representation of various important in-sewer processes including sewer sediment

strata and possible in-sewer sediment processes (Mouri and Oki, 2010; Nguyen et al., 2015) ........... 8

Figure 3. Adsorption mechanism of phosphate (PO43−) ions on iron (Fe) precipitate ...................... 11

Figure 4. Final disposal routes employed for waterworks sludges (Tahmazi, 2017) ....................... 17

Figure 5. Various options adopted as end uses for waterworks-derived sludge in Australia. .......... 18

Figure 6. Conceptual schematic representation of the changing sludge floc structure owing to cations

distribution in the sludge flocs matrix (primarily Na+, K+, Ca2+, Mg2+, Al3+, Fe3+ concentrations)

resulted due to bridging divalent and trivalent cations exchange phenomena vis-à-vis M+/D++ cations

ratio and sludge settleability (modified from Peeters et al. (2011))................................................... 22

Figure 7. Schematic representation of the integrated laboratory reactor system. Here, only

experimental line is depicted wherein the control line is identical but without the Fe-salt dosing unit.

(b) pictorial representation showcasing the real set-up of integrated laboratory system ................... 35

Figure 8. Rising main pilot system at innovation centre of Luggage Point WWTP ......................... 36

Figure 9. Schematic of the pilot rising main with an internal diameter of 100 mm and a length of 300

m. The experimental line is shown here. The control line was identical but without the sludge dosing

mechanism. Temperature and pH were monitored online by pumping sewage out in a pipe loop at 45

m then returning it at 75 m using Masterflex Peristaltic Pumps (Cole-Parmer, USA) maintaining the

flow rate at 3400 mL.min-1 ................................................................................................................ 37

Figure 10. Simplified diagram showcasing the upstream sewer network and inlet of Luggage Point

WWTP where FeCl2 dosing was trialed. Here, two dosing trials (as highlighted) were conducted

independently, i.e. inlet dosing trial was first trialed followed by the upstream sewer dosing trial .. 38

Figure 11. Simplified process flow diagram of Luggage point WWTP with sampling points (yellow

circled) around the PST pertinent to inlet FeCl2 dosing trial ............................................................. 39

Figure 12. Modified centrifuge stand used for centrifugation for dewaterability analysis: (a) belt filter

fabric; (b) modified stand holding the belt filter fabric ..................................................................... 40

Figure 13. Calibration curves used for determination of (a) protein (PN); (b) polysaccharide (PS)

contents .............................................................................................................................................. 42

xxiv

Figure 14. Schematic diagram of drying test – TG measurement ..................................................... 48

Figure 15. Pictorial representation summarizing the experimental framework for the mixing-reaction-

settling test under simulated in-sewer oxic-to anaerobic transition condition, correspond to 0.5 hr, 4.0

hr, and 6.0 hr mixing times ................................................................................................................ 58


settling tests under simulated in-sewer anaerobic condition, correspond to 0.5 hr, 4.0 hr, and 6.0 hr

mixing times. Here, high purity nitrogen (99% N2) gas was only used for the sparging the sewer

wastewater prior initiation of tests ..................................................................................................... 59

Figure 17. Images showcasing two supernatant samples (one taken at the beginning prior chemicals

addition while other taken following 1.0 hr settling after end of pre-designated mixing-reaction times)

including settled masses sample at bottom of reactors (obtained after end of 6.0 hr mixing-reaction

time under oxic-to-anaerobic transition condition). Here, chemical refer to FeCl3 and Na2S stock

solutions ............................................................................................................................................. 63

Figure 18. Measured mean concentration-time profiles of total - Fe(T), P(T), S(T) in PST underflow

under three different sampling events during WWTP inlet and upstream sewer FeCl2 dosing trials

(separated by solid line). Data presents herein represent mean with 95% CI; number of measurements

(n=5) corresponds to the hourly samples taken for 5.0 hr from PST on different sampling days with a

week interval, adopted in line with FeCl2 dosing duration. Here, samplings 1, 2, and 3 refers to

different sampling days for both full-scale dosing trials.................................................................... 71

Figure 19. Spatio-temporal profiles of PSDs for influent and effluent of a full-scale PST for a WWTP

inlet dosing trial (a, b) and an upstream in-sewer dosing trial (c, d) using FeCl2. PSDs are presented

as volume density (%) of particles. Here, sampling 1 refers to particular pre-designated sampling day,

conducted in line with dosing duration for both dosing trials. Data points correspond to three time

point hourly samples (1 hr, 3 hr, 5 hr) taken from PST. PSDs profiles for other sampling event are

provided in Figure 20 ......................................................................................................................... 72



as volume density (%) of particles. Data points correspond to three time point hourly samples (1 hr,

3 hr, 5 hr) taken from PST. Here, sampling 2 refers to particular pre-designated sampling day,

conducted in line with dosing duration for both dosing trials............................................................ 73

Figure 21. Concentration-time profiles of mixing-reaction-settling laboratory tests with Fe-salt and

different mixing periods (0.5 hr, 4.0 hr, and 6.0 hr), including (a) Fe(T) and (b) Fe(aq) profiles in

supernatant under simulated in-sewer oxic-to-anaerobic transition conditions; and (c) Fe(T) and (d)

xxv

Fe(aq) profiles under simulated in-sewer anaerobic conditions. Error bars indicate calculated standard

deviations (SD) with n=3 in the case of 0.5 hr and 6.0 hr mixing times and n=2 for 4.0 hr mixing time

............................................................................................................................................................ 79

Figure 22. EDX spectra depicting the elemental composition by wt% of the sample subjected to

different mixing time under oxic-to-anaerobic conditions: (a) 0.5 hr; (b) 6.0 hr .............................. 80

Figure 23. BEC images for 0.5 hr (top) and 6.0 hr (bottom) mixing under oxic-to-anaerobic condition:

(a) and (b) corresponding EDX chemical maps acquired for the alloying elements in mapped area -

(c) C; (d) O; (e) Mg; (f) Al; (g) P; (h) S and (i) Fe ............................................................................ 81

Figure 24. Thermo maps (Quant mapping) for samples of both 0.5 hr (top) and 6.0 hr (bottom) mixing

under oxic-to-anaerobic condition, depicting qualitative element distribution maps ........................ 82

Figure 25. Concentration-time profiles of mixing-reaction-settling laboratory tests with Fe-rich water

treatment sludge, including (a) Fe(T) and (b) Fe(aq) profiles in supernatant under simulated oxic-to-

anaerobic transition conditions, respectively. Each data point represents a mean value (n=2) with error

bars being standard deviations ........................................................................................................ 83

Figure 26. Measured particle size distributions for samples collected at different times during the

laboratory mixing-reaction-settling tests using Fe-salt with mixing periods of 0.5 hr or 6.0 hr and

under (a, b, c) oxic-to-anaerobic transition conditions or (d, e, f) purely anaerobic conditions. The

data present volume density (%) of particles ..................................................................................... 84

Figure 27. Measured particle size distributions for sediment collected at the end of mixing-reaction-

settling laboratory tests under oxic-to-anaerobic transition conditions, for 0.5 hr and 6.0 hr mixing

periods using Fe-rich water treatment sludge. The data herein represent the volume density (%) of

particles .............................................................................................................................................. 85

Figure 28. Schematic representation of experimental set up employed for this study, depicting both

control and experimental lines ........................................................................................................... 94

Figure 29. (a) Changes in dewatered cake solids content (%): data represents meanSEM (N=3); (b)

variations in concentrations of S-EPS, LB-EPS and TB-EPS: SBR-E (N=5) and SBR-C (N=5); (c)

variations in concentrations of protein (PN): SBR-E (N=2) and SBR-C (N=2); (d) variations in

concentration of polysaccharides (PS): SBR-E (N=2) and SBR-C (N=2). Here, each data represents

mean values (N=2) ........................................................................................................................... 100

Figure 30. (a)-(b) EEM spectra of different EPS components of two iron-conditioned (SBR-E1, SBR-

E2) (top-half) and unconditioned (SBR-C1, SBR-C2) (bottom-half, separated by dotted line) sludges.

xxvi

Each set of samples (SBR-E1 and SBRC-1, SBR-E2 and SBR-C2) were sampled weekly from

respective experimental and control SBR reactors .......................................................................... 104

Figure 31. (a) Variations in M+/D++ cations ratio values: SBR-E (N=3) and SBR-C (N=3). Here, error

bar represents meanSEM; (b) Changes in size distribution of particles in activated sludges (N=6):

iron-conditioned (SBR-E) and unconditioned sludges (SBR-C). Here, error bar represents the

meanSEM ....................................................................................................................................... 107

Figure 32. SEI images obtained at different magnifications by scanning electron microscopy. (a)-(d)

iron-conditioned activated sludge (SBR-E) (top-half): (a) 300, (b) 500, (c) 1000, (d) 2000; (e)-

(h) unconditioned activated sludge (SBR-C) (bottom-half): (e) 300, (f) 500, (g) 1000, (h) 2000

.......................................................................................................................................................... 111

Figure 33. (a)-(f) Particle fingerprints (or PSD) analyses of iron-conditioned (samples SBR-E1, SBR-

E2, SBR-E3, SBR-E4, SBR-E5, SBR-E6) and unconditioned (samples SBR-C1, SBR-C2, SBR-C3,

SBR-C4, SBR-C5, SBR-C6) activated sludges, depicting the volume density (VD) (%) of particles

in different size class range. Each set of samples (i.e. SBR-E1/SBR-C1, SBR-E2/SBR-C2, SBR-

E3/SBR-C3, SBR-E4/SBR-C4, SBR-E5/SBR-C5, and SBR-E6/SBR-C6) were sampled weekly from

respective SBR reactors ................................................................................................................... 112

Figure 34. DSC thermograms of both activated sludges including pure Milli-Q water. Here, pure

water = S0; iron-conditioned sludges (SBR-E) = S1 and S3; unconditioned sludges (SBR-C) = S4

and S6. Each set of samples (samples S1 and S4, S3 and S6) were sampled weekly from respective

SBR reactors during the 12th month of experimental Phase II (i.e. after initiation of in-sewer FeCl3

dosing in integrated lab system) ....................................................................................................... 113

Figure 35. (a) Observed differences in relative sludge network strength values of both sludges (here,

linear ramp increment was adopted for shear rate from 0-300 s-1 for 76 s); (b)-(d) flow curves

depicting changes in shear viscosities (shear) as function of different shear rates (50, 100, 250 s-1):

changes in shear values of iron-conditioned (SBR-E) and unconditioned (SBR-C) activated sludges.

Here, error bar represents the meanSEM ....................................................................................... 117

Figure 36. (a) changes in TTQ values based on torque rheology; (b)-(c) CSR tests showing flow

curves of iron-conditioned sludges (SBR-E1, SBR-E2); (d)-(e) CSR tests showing flow curves of

unconditioned sludges (SBR-C1, SBR-C2); (f) variations in apparent viscosities A in both activated

sludges. Here, each set of samples (SBR-E1/SBR-C1, SBR-E2/SBR-C2) were sampled weekly from

respective SBR reactors ................................................................................................................... 118

xxvii

Figure 37. Thixotropy analysis based on hysteresis loop tests: (a)-(b) iron-conditioned (samples SBR-

E1, SBR-E2) (top-half) and (c)-(d) unconditioned (samples SBR-C1, SBR-C2) activated sludges

(bottom-half). Here, each set of samples (SBR-E1/SBR-C1, SBR-E2/SBR-C2) were sampled weekly

from respective SBR reactors .......................................................................................................... 119

Figure 38. CSS test results showing the changes in yield stress (y) values: (a)-(b) iron-conditioned

sludges, SBR-E (N=2); (c)-(d) unconditioned sludges, SBR-C (N=2) ............................................ 120

Figure 39. (a)-(c) Evolution of storage (G), loss (G) and complex (G*) moduli in both activated

sludges (SBR-E, SBR-C) during amplitude sweep oscillation tests as a function of applied shear strain

range 0.01-1000%, angular frequency 5 rad.s-1 and at 25±0.01°C; (d)-(e) frequency sweep of both

sludges (SBR-E, SBR-C) with oscillating strains of 10% on G and G over frequency range of 0.1-

100 rad.s-1 at 25±0.01°C; (f) creep-recovery tests for both sludges (SBR-E, SBR-C): response of shear

creep compliance (J) with respect to creep time .............................................................................. 121

Figure 40. (a) Variations in damping (or loss) factor tan() over frequency range of 0.1 – 100 rad.s-1

at 25±0.01°C during frequency sweep of both activated sludges (SBR-E, SBR-C) with oscillating

strains of 10%; (b) creep-recovery tests for both activated sludges (SBR-E, SBR-C): response of shear

strain (%) with respect to creep time ............................................................................................... 122

Figure 41. Possible combined synergistic interplay amongst different underlying interactions behind

improvement in dewaterability and settleability of iron-conditioned activated sludge ................... 123


control and experimental lines ......................................................................................................... 132

Figure 43. Schematic diagram elucidating framework of this study .............................................. 133

Figure 44. Illustration of a drying rate curve obtained for an iron-conditioned digestate via TG

measurement .................................................................................................................................... 136

Figure 45. (a) Cake solids content (%) of iron-conditioned (AD-E) and unconditioned (AD-C)

digestates: error bars represent meanSEM (n=16); (b) effects of centrifugal time (t) on cake solid

content (%), constant mixing intensity = 3750 rpm [t = 5 min (n=6); t =10 min (n=16); t =20 min

(n=6)]; (c) effects of centrifugal speed on cake solid content (%), constant mixing time = 10 min [rpm

= 1000 (n=3); rpm = 2000 (n=3); rpm = 3750 (n=16)]; (d) cake solid content (%) as function of gt

values [gt = 139392.24 (n=3), gt = 557568.96 (n=3), gt = 980101.69 (n=6), gt = 1960203.40 (n=16),

gt = 3920406.80 (n=6)] .................................................................................................................... 137

Figure 46. (a) Quantities of S-EPS, LB-EPS and TB-EPS in terms of TOC content in both digestates.

Error bar represents meanSEM (n=4); (b)-(c) F-EEM spectra of different EPS components of 1st set

xxviii

(AD-E1, AD-C1) (top-half) and 2nd set (AD-E2, AD-C2) (bottom-half) of digestate samples

(separated by solid lines). Each set of samples correspond to different sampling time, sampled in a

week interval from respective experimental AD-E and control AD-C reactors; Quantification of (d)

PN and (e) PS in both digestates (data represents mean values, n=2) ............................................. 138

Figure 47. (a) Variations in monovalent-to-divalent (M+/D++) cations ratio values in iron-conditioned

AD-E (n=2) and unconditioned digestates AD-C (n=2); (b) Changes in size distribution of particles

in both digestates AD-E (n=3) and AD-C (n=3) .............................................................................. 140

Figure 48. DSC thermograms of iron-conditioned (AD-E1, AD-E2, AD-E3) (left-half) and

unconditioned (AD-C1, AD-C2, AD-C3) (right-half, separated by dotted line) digestates. Here,

digestate sample AD-E1 was sampled in conjunction with AD-C1 at same time period from

continuously operated both reactors; similar was the case for AD-E2/AD-C2 and AD-E3/AD-C3.

Each set of samples were sampled in a week interval from respective AD reactors ....................... 146

Figure 49. Drying curves of 1st set of digestate samples with arithmetic abscissa: (a) AD-E1, (b) AD-

C1 (top-half); drying curves of 2nd set of digestate samples with arithmetic abscissa: (c) AD-E2, (d)

AD-C2 (bottom-half). Each set of samples (AD-E1 and AD-C1; AD-E2 and AD-C2) correspond to

different sampling time from respective reactors, i.e., sampled on a weekly basis from respective AD

reactors ............................................................................................................................................. 147

Figure 50. Particle fingerprints (or particle size distribution) analysis of both digestates: (a) samples

AD-E1, AD-C1; (b) samples AD-E2, AD-C2; and (c) samples AD-E3, AD-C3. Here, each set of

samples (as depicted in different sub-plots) were sampled at different sampling time from respective

AD reactors, i.e. sampled on a weekly basis from respective AD reactors ..................................... 150

Figure 51. Changes observed in steady shear rheological measurements between iron-conditioned

(AD-E) and unconditioned digestate (AD-C) samples: (a) relative sludge network strength values and

for this shear rate was increased from 0-300 s-1 in linear ramp manner for 76 s during measurement;

(b)-(d) sludge shear viscosity (shear) as a function of shear rates 50 s-1, 100 s-1, and 250 s-1; (e)-(f)

CSR tests; and (g)-(h) hysteresis loop tests results, showing the ascending and descending flow

curves. Here, iron-conditioned digestate sample AD-E1 was sampled concomitantly with

unconditioned digestate sample AD-C1 from respective experimental and control AD reactors ... 153


(AD-E) and unconditioned digestate (AD-C) samples: (a) totalized torque (TTQ) values, which

adopted an increment of shear rate in linear ramp manner from 0-300 s-1 for 76 s during measurement;

(b)-(c) apparent viscosity, A values as a function of shear rates; (d) infinite shear viscosity, values;

(e)-(f) CSR tests; and (g)-(h) hysteresis loop tests results, showing the ascending and descending flow

xxix

curves. Here, digestate sample AD-E1 was sampled concomitantly with AD-C1 from respective

experimental and control AD reactors and similar was the case for AD-E2 and AD-C2. Each set of

samples were sampled in a week interval from respective AD reactors .......................................... 154

Figure 53. CSS test results of iron-conditioned (AD-E, left half) and unconditioned (AD-C, right

half) digestate samples: (a) AD-E1; (b) AD-C1; (c) AD-E2; (d) AD-C2, (e) AD-E3; and (f) AD-C3.

Here, iron-conditioned digestate sample AD-E1 was sampled concomitantly with unconditioned

digestate sample AD-C1 from respective experimental and control AD reactors and similar was the

case for AD-E2/AD-C2 and AD-E3/AD-C3. Each set of samples were sampled in a week interval

from respective AD reactors ............................................................................................................ 156

Figure 54. (a)-(d) Evolution of storage (G), loss (G), and complex (G*) moduli in iron-conditioned

(AD-E) and unconditioned (AD-C) digestates during amplitude sweep oscillation (i.e. SAS) tests as

a function of applied shear strain range 0.01-1000%, angular frequency 5 rad.s-1, and at 250.01C;

(e)-(f) creep-recovery test: (e) response of creep compliance J(t) with respect to creep time; (f)

response of shear strain (%) with respect to creep time. Here, iron-conditioned digestate sample AD-

E1 was sampled concomitantly with unconditioned digestate sample AD-C1 from respective AD

reactors and similar was the case for other sets of samples AD-E2/AD-C2. Each set of samples were

sampled in a week interval from respective AD reactors................................................................. 158

Figure 55. Possible synergistic interplay amongst different factors behind improving dewaterability

of iron-conditioned digestate ........................................................................................................... 164

Figure 56. (a) Fe-sludge obtained from desalination water treatment plant, (b) Al-sludge obtained

from fresh/surface-water treatment plant, (c)-(d) Visual inspection of color change in sewage

following Fe-sludge dosing: (c) sewage color prior to dosing, (d) sewage color after dosing ........ 171

Figure 57. Laboratory set up for batch tests to investigate effects of Al: PO43- dosage ratio and

suspended solids on phosphate removal. Here, all tests were carried out in borosilicate glass reactors

.......................................................................................................................................................... 174

Figure 58. Changes in sewage characteristics in control [C] and experimental [Exp] sewer pipes after

dosing Fe-sludge. The vertical dashed line represents the time at which Fe-sludge was dosed to the

experimental pipe. Concentration-time profiles are presented for (a) TSS, (b) VSS, (c) total Fe(T), (d)

soluble Fe(sol.), (e) total Al(T), and (f) soluble Al(sol.). Each data point corresponds to the mean value of

three sampling points (15 m, 105 m, 210 m) in sewer pipes. Error bars represent standard error of

mean (SEM). .................................................................................................................................... 179

xxx

Figure 59. Changes observed in sewage characteristics in Control [C] and Experimental [Exp] sewer

pipes on dosing Fe-sludge. Time profiles of: (a) pH, (b) temperature, (c) dissolved N2O concentration

.......................................................................................................................................................... 180


dosing Fe-sludge. The vertical dashed lines represent the sewage characteristics observed at 20 min

and 40 min in both sewer pipes (after dosing of Fe-sludge in experimental line). Concentration-time

profiles are presented for (a) total dissolved sulfide S(-II), (b) sulfite, sulfate, and thiosulfate, (c)

phosphate, PO4-P, (d) tCOD, (e) sCOD, and (f) dissolved methane, CH4. Each data point corresponds

to the mean value of three sampling points (15 m, 105 m, 210 m) in sewer pipes (except for the

dissolved CH4, which correspond to sampling point 15 m). Error bars represent standard error of mean

(SEM). .............................................................................................................................................. 181

Figure 61. (a) X-ray diffraction pattern; (b) infrared (IR) spectra of Fe-sludge samples (before dosing

into pilot sewer) ............................................................................................................................... 182

Figure 62. (a) X-ray diffraction pattern and (b) IR spectra of samples collected at the end of Fe-sludge

dosing into the pilot sewer, i.e. a mixture of raw sewage and Fe-sludge solids .............................. 184

Figure 63. SEM-EDX analysis of elemental composition (Wt%) of Fe-sludge sampled after dosing

into the experimental sewer line (also see Table 31): (a) Secondary Electron Image (SEI), (b)

Spectrum 1, (c) Spectrum 2, (d) Spectrum 3, (e) Spectrum 4, (f) Spectrum 5, and (g) Spectrum 6 185


dosing Al-sludge. The vertical dashed line represents the time at which Al-sludge was dosed to the

experimental pipe. Concentration-time profiles are presented for (a) TSS, (b) VSS, (c) total Al(T), (d)

soluble Al(sol.), (e) total Fe(T), and (f) soluble Fe(sol.). Each data point corresponds to the mean value of

three sampling points (15 m, 105 m 210 m) in sewer pipes. Error bars represent standard error of

mean (SEM). .................................................................................................................................... 189


pipes after dosing Al-sludge. Time profiles of: (a) pH, (b) temperature, and (c) dissolved N2O .... 190


dosing Al-sludge. The vertical dashed lines represent the sewage characteristics observed at 20 min

and 40 min in both sewer pipes (after dosing of Al-sludge in experimental line). Concentration-time

profiles are presented for (a) phosphate, PO4-P, (b) total dissolved sulfide S(-II), (c) sulfite, sulfate,

and thiosulfate contents, (d) tCOD, (e) sCOD, and (f) dissolved methane, CH4. Each data point

corresponds to the mean value of three sampling points (15 m, 105 m, 210 m) in sewer pipes (except

xxxi

for the dissolved CH4, which corresponds to sampling point 15 m). Error bars represent standard error

of mean (SEM). ................................................................................................................................ 191

Figure 67. Effect of various Al:PO43- dosage ratios on phosphate removal in (a) unfiltered and (b)

filtered sewage. Here, each data point corresponds to mean value of duplicate tests (n=2) ............ 193

Figure 68. X-ray diffraction (XRD) pattern of Al-sludge used in this study, showing the dominance

of aluminium (hydr)oxides, as marked by ‘star’ symbols ............................................................... 193

Figure 69. IR spectra of sewage samples taken before and after batch experiment, using an Al-sludge

dosage molar ratio of Al:PO43- = 3:1. Here, star symbols are assigned to respective absorbance bands,

where major changes were observed ............................................................................................... 195

Figure 70. (a)-(d) 27Al spectra and (e)-(h) 31P NMR spectra of sewage samples – before and after Al-

sludge dosing, respectively, with various Al:PO43- molar ratios, reacted for 2 hr with constant mixing

at 25C and pH 7.3 - 7.6: (a) and (e) = raw unfiltered sewage samples before Al-sludge dosing; (b)

and (f) Al:PO43- = 1:1; (c) and (g) Al:PO4

3- = 2:1; (d) and (h) Al:PO43- = 3:1 ................................ 197

Figure 71. A diagrammatic representation elucidating the synthesis of this thesis work ............... 206

xxxii

List of tables

Table 1. Various commonly adopted WTP sludge disposal routes (in percentages) in New Zealand

(122 plants, August 1996, albeit data of 10 treatment plants excluded) (Blakemore et al., 1998;

Ogilvie, 1997), the UK (circa 1999) (Parsons and Jefferson, 2006) and the USA (circa 2000)

(Cornwell, 2006) (major routes in highlighted). .................................................................................. 6

Table 2. Some beneficial aspects associated with WTP-derived iron sludge dosing for wastewater

treatment (adapted from (Sarfert et al., 1994)) .................................................................................... 6

Table 3. Summary of previous research results depicting the influence on digester biogas production

when dosing Fe-laden sludge (Smith and Carliell-Marquet, 2009) ................................................... 14

Table 4. Dispersion conditions employed during the PSD analyses of the sludge sample ............... 50

Table 5. Full-scale tests - WWTP inlet and upstream sewer FeCl2 (30% FeCl2) dosing schedules and

sampling dates .................................................................................................................................... 55

Table 6. Composition of domestic sewage (or wastewater) and freshly prepared Fe-sludge used in

the laboratory experiments. Unless otherwise stated values presented correspond to the mean in

replicates, given with estimates of error (±) at the 95% CI ............................................................... 60

Table 7. Measured Fe(T) and Fe(aq) concentrations in PST influent and effluent for three different

sampling events (days) under separate WWTP inlet and upstream sewer FeCl2 dosing trials. Data

presents calculated mean values ± estimate of error at the 95% confidence interval (CI) and calculated

% reduction in Fe concentrations from PST influent to effluent are also shown .............................. 68

Table 8. Measured P(T) and P(aq) concentrations in PST influent and effluent for three different


presents calculated mean values ± estimate of error at the 95% CI and calculated % reduction in P

concentration from PST influent to effluent are also shown ............................................................. 69

Table 9. Measured S(T) and S(aq) concentrations in PST influent and effluent for three different


presents calculated mean values ± estimate of error at the 95% CI and calculated % reduction in S

concentration from PST influent to effluent are also shown ............................................................. 70

Table 10. Categorizing particles into different size fractions under both tests conditions on using

FeCl3 as iron source. Here, each data corresponds to the mean of 10 replicate measurements (n) = 10

............................................................................................................................................................ 85

xxxiii

Table 11. Categorizing particles into different size fractions under oxic-to-anaerobic tests conditions

on using Fe-sludge as iron source. Here, each data corresponds to the mean of 10 replicate

measurements (n) = 10 ....................................................................................................................... 86

Table 12. Characteristics of domestic sewage (i.e. influent composition of sewer reactors) including

influents of SBR-E and SBR-C reactors. Other than stated values presented correspond to the mean

in replicates, given with estimates of error (±) at the 95% confidence level ..................................... 95

Table 13. Variation in the dewatered cake solid contents (%) in iron-conditioned (SBR-E) and

unconditioned (SBR-C) activated sludges as function of mixing intensity (rpm), centrifugation time

(t) and gt values ................................................................................................................................ 101

Table 14. FRI parameters for operationally defined EEM regions including multiplication factor

specific to each region ...................................................................................................................... 103

Table 15. Influences on intensities of fluorescence spectral parameters of different EPS fractions of

both activated sludges. Here, all samples diluted 20 times. Sludge SBR-E1 was sampled in

conjunction with SBR-C1 at same time period from continuously operated both reactors; similar was

the case for SBR-E2 and SBR-C2, i.e. each set of samples were sampled weekly from respective

experimental and control SBR reactors ........................................................................................... 105

Table 16. Monovalent and divalent cations concentrations in iron-conditioned (SBR-E1, SBR-E2)

and unconditioned (SBR-C1, SBR-C2) sludges .............................................................................. 107

Table 17. Inorganic fractions content analysis ................................................................................ 108

Table 18. Particle size specifications (mean diameter and percentiles) in activated sludges. Here, each

set of samples (i.e. SBR-E1/SBR-C1, SBR-E2/SBR-C2, SBR-E3/SBR-C3, SBR-E4/SBR-C4, SBR-

E5/SBR-C5, and SBR-E6/SBR-C6) were sampled weekly from respective experimental and control

SBR reactors. Also, ‘n’ = no. of measurements, ‘N’ = no. of analyzed samples used, ‘SD’ = standard

deviation ........................................................................................................................................... 110

Table 19. Determination of fractal dimension Df, aggregate structure factor, (S) and ratio between

hydrodynamic radius (RH) to the radius of aggregate (RA) in activated sludges, RH/RA values. Here,

each set of samples (i.e. SBR-E1/SBR-C1, SBR-E2/SBR-C2, SBR-E3/SBR-C3, SBR-E4/SBR-C4,

SBR-E5/SBR-C5, and SBR-E6/SBR-C6) were sampled weekly from respective SBR reactors. Here,

values of Df, RH/RA, and (S) correspond to the mean of 10 replicate measurements (n=10) .......... 113

Table 20. Quantification of TWC, FWC, BWC, dry solids (DS) and wet solids (WS) of the centrifugal

dewatered sludge cake in both activated sludges (TWC = total water content; FWC = free water

content; BWC = bound water content). Here, sample S1 was sampled in conjunction with sample S4

xxxiv

and similar was the case for other set of samples S3 and S6, such that each set of samples were

sampled weekly from respective SBR reactors ................................................................................ 114

Table 21. Changes in intensities of fluorescence spectral parameters of different EPS fractions in

iron-conditioned and unconditioned digestates ................................................................................ 141

Table 22. Monovalent and divalent cations concentrations distribution in both iron-conditioned (AD-

E1, AD-E2) and unconditioned (AD-C1, AD-C2) digestates. Here, each set of samples (AD-E1/AD-

C1; AD-E2/AD-C2) correspond to different sampling time, i.e. sampled in a week interval from

respective AD-E and AD-C reactors, respectively. ......................................................................... 142

Table 23. Changes in bound water content (BWC), total water content (TWC), and free water content

(FWC) of iron-conditioned (AD-E) and unconditioned (AD-C) digestates (conversion factor K =

0.0053 g.J-1). Here, digestate sample AD-E1 was sampled in conjunction with AD-C1 at same time

period from continuously operated both reactors; similar was the case for AD-E2/AD-C2 and AD-

E3/AD-C3. Each set of samples were sampled in a week interval from respective AD reactors .... 144

Table 24. Moisture distribution analysis of iron-conditioned (AD-E) and unconditioned (AD-C)

digestates using drying rate curves, based on thermogravimetric (TG) measurements ................... 145

Table 25. Particle size specifications (mean particle size, Dv50 and percentiles) of iron-conditioned

and unconditioned digestates. Determination of fractal dimension Df, aggregate structure factor (S),

and ratio between hydrodynamic radius (RH) to the radius of aggregate (RA), 𝑅𝐻𝑅𝐴 values. Here, ‘n’

= no. of analyzed samples, ‘SD’ = standard deviation, and values of Dv50 and percentiles including

the values of Df, RH/RA, and (S) correspond to the mean of 10 replicate measurements ................. 149

Table 26. Changes observed in hysteresis loop area (Hla), yield (y), and flow stress (f) values for

iron-conditioned (AD-E) and unconditioned digestate (AD-C) samples ......................................... 155

Table 27. Fitting results of different rheological models of iron-conditioned digestates (temperature

= 25±0.01°C) .................................................................................................................................... 159

Table 28. Fitting results of different rheological models of unconditioned digestates (temperature =

25±0.01°C) ....................................................................................................................................... 160

Table 29. Characteristics of feed wastewater (raw sewage), DAF subnatant (used as diluent), Fe-/Al-

sludge including diluted Fe-/Al-sludge (n = number of measurements as indicated in parentheses; if

n is not stated, a single measurement was taken) ............................................................................. 172

Table 30. Overview of experimental design for batch tests to investigate effects of Al:P dosage ratio

and suspended solids on phosphate removal. Here, test duration = 2 hr, number of replicates, n = 2

.......................................................................................................................................................... 174

xxxv

Table 31. EDX analysis of sample elemental composition following Fe-sludge addition into the pilot

experimental sewer line ................................................................................................................... 185

Table 32. Comparative evaluation of phosphate removal by Al-sludge as a function of Al:PO43- molar

ratio using (a) unfiltered sewage and (b) 0.22 µm filtered sewage. Here, test duration = 2 hr, number

of replicates for each dosing ratio, n = 2 .......................................................................................... 194

Table 33. Chemical shift (iso, Al) (27Al) ppm and integrals obtained from deconvolution of 27Al spectra

.......................................................................................................................................................... 198

Table 34. Chemical shift (iso, P) (31P) ppm and integrals obtained from deconvolution of 31P spectra

.......................................................................................................................................................... 198

xxxvi

List of nomenclature

AD anaerobic digester

AD-E anaerobic digester (experimental); iron-conditioned digestate

AD-C anaerobic digester (control); unconditioned digestate

AIC Akaike information criterion

AICc corrected Akaike information criterion

Al(T) total aluminium

Al(aq), Al(sol.) dissolved aluminium

AS activated sludge

ATR attenuated transform reflectance

BCA bicinchoninic acid

BOD biochemical oxygen demand

BSA bovine serum albumin

BWC bound water content

CEM chemical equilibrium model

CH4 dissolved methane

CI confidence interval

COD chemical oxygen demand

CPR chemical phosphorus removal

CSR controlled shear rate

CSS controlled shear stress

DAF dissolved air flotation

DCBT divalent cation bridging theory

Df fractal dimension

DO dissolved oxygen

DOC dissolved organic carbon

xxxvii

DS dry solids

DSC differential scanning calorimetry

Dv50 volume-weighted mean particle size

e-DNA extracellular deoxyribonucleic acid

EDX energy dispersive X-ray

EEM emission and excitation matrix

EMS environmental management system

EPS extracellular polymeric substances

FA fulvic acid

Fe iron

Fe2+ iron(II), ferrous

Fe3+ iron(III), ferric

Fe(T) total iron

Fe(aq), Fe(sol.) dissolved iron

FeCl3 ferric chloride

FeCl2 ferrous chloride

FeOOH iron (oxy)hydroxides

FeSX iron sulfide precipitates

FeXPO4(OH)x ferric-hydroxy‐phosphate

FeCl3.6H2O iron-chloride hexahydrate

F-EEM fluorescence excitation-emission matrix

FI fluorescence intensity

FIA flow injection analyser

FID flame ionization detector

FRI fluorescence regional integration

FS frequency sweep

FTIR fourier transform infrared spectroscopy

xxxviii

g gravitational acceleration

G elastic (or storage) modulus

G viscous (or loss) modulus

G* complex modulus

HA humic acid

HFO hydrous ferric oxide

Hla hysteresis loop area

HNO3 nitric acid

HRT hydraulic retention time

H2S hydrogen sulfide

IC ion chromatography

ICP-OES inductively coupled plasma optical emission spectrometer

i-DNA intracellular deoxyribonucleic acid

IR infrared

J, (J) shear compliance

K, KH flow consistency coefficient or index

LB-EPS loosely-bound extracellular polymeric substances

LCA life cycle assessment

MCA microbial community analysis

MCI modified centrifugal index

M+/D++ monovalent-to-divalent cation ratio

MOs microorganisms

MulFe multiple re-uses of Fe-salt

n, nH flow behaviour index

NO3- nitrate

NMR nuclear magnetic resonance spectroscopy

NOM natural organic matter

xxxix

N2O dissolved nitrous oxide

OM organic matter

P phosphorus

PN protein

PO43- phosphate (or orthophosphate)

PO43-P phosphate (orthophosphate) as phosphorus

PP polyphosphates

PS polysaccharides

PSD particle size distribution

PST primary settling tank (or primary clarifier)

P(T) total phosphorus

P(aq), P(sol.) dissolved phosphorus

PVC polyvinyl chloride

q scattering angle

Q map quant mapping (or thermo mapping)

R2 coefficient of determination

RCF relative centrifugal force

RM rising main (or pressurized sewer)

RMSE root-mean-square error

RO reverse osmosis

RH/RA ratio between hydrodynamic radius (RH) to the radius of aggregate (RA)

R-NH2 primary amine functional group, where R is alkyl group

S sulfur

(S) aggregate structure factor

SAS strain amplitude sweep

SBR sequencing batch reactor

SBR-C sequencing bacth reactor (control); unconditioned AS

xl

SBR-E sequencing batch reactor (experimental); iron-conditioned AS

sCOD soluble chemical oxygen demand

SCM surface complexation modelling

SD standard deviations

SEI secondary electron images

SEM standard error of mean

SEM-EDX scanning electron microscopy energy dispersive X-day

S-EPS soluble extracellular polymeric substances

SMP soluble microbial product

S0 elemental sulfur

SO42- sulfate

SPS sewer pumping station

SRB sulfate reducing bacteria

SRT sludge retention time

SS absolute sum of squares

SSE sum square error

S(T) total sulfur

S(aq), S(sol.) dissolved sulfur

SUVA254 specific UV absorbance

SVI sludge volume index

SWOL Sydney Water’s Operating License

Sy.x or Se standard error of estimate

tan() loss or damping factor

TB-EPS tightly-bound extracellular polymeric substances

tCOD total chemical oxygen demand

TG thermogravimetric measurement

TOC total organic content

xli

TRUmap EDX layered map

TS total solids

TSS total suspended solid

TTQ totalized torque

TWC total water content

UF ultrafiltration

UVA254 ultraviolet absorbance measurement

UWS urban water system

UWWS urban wastewater system

VD(%) volume density (%)

VS volatile solid

VSS volatile suspended solid

WAS waste activated sludge

WS wet solids

WTP water treatment plant

WWTP wastewater treatment plant

XRD X-ray diffraction

y yield stress

, σ shear stress

γ shear rate

shear shear viscosity

apparent viscosity

infinite shear viscosity

’ Bingham plastic viscosity

f flow stress

(iso, Al) chemical shift in (27Al) ppm

(iso, P) chemical shift in (31P), ppm

1

Chapter 1

Introduction and literature review

1.1 Chemical use in urban water system

Rapidly increasing global population and urbanization could pose a serious threat to the

sustainability of urban water supplies in the urban water system (UWS). This is because the demand

for urban water supplies will grow with rapidly growing cities (i.e. urban sprawl) and the subsequent

need for sustainability. Not only will more urban water supplies be required to fulfill the increasing

demand, more sewage (black-/grey-water) and stormwater will also be generated. In consequence,

this will necessitate more wastewater disposal/treatment facilities and removing more stormwater

(see Figure 1) (Gregory and Hall, 2011). The increased generation of wastewater (effluents) and

biosolids will have further impacts. Such trend will place water utilities under increasing pressure to

meet the growing demands from the standpoint of both water and wastewater treatment. The growing

necessity of water and wastewater treatment indirectly implies more consumption of chemicals,

which in turn would incur higher operational costs. For instance, the global cost of inorganic

coagulants used for water/wastewater treatment in 2018 was $1.37 billion, and this is predicted to

reach $1.84 billion by 2023 (BCC-Research, 2018).

Figure 1. Schematic representation of a conventional urban water system (UWS)

2

Different chemicals are used in different major components of UWS, including water treatment

plant (WTP), sewer networks, and wastewater treatment plant (WWTP) to fulfill different

requirements. These different components in UWS do not operate in isolation and they may have

many linkages to other sub-systems within a city and its surrounding regions. In retrospect, the

‘choice’ and ‘optimal’ application of these chemicals are at present primarily driven by

considerations merely at the sub-system level, with their potential impact on other sub-systems being

largely ignored.

In WTP, drinking water production requires a variety of chemicals, such as coagulants, acids/bases,

and disinfectants. For instance, aluminium (Al)- or iron (Fe)-based coagulants, complemented by

either chloride or sulfate as counter ions, make up the bulk of the inorganic chemical coagulants

used. The typical coagulant consumption is reported to be in the range of 5-20 g Al or Fe/m3 of water

produced (up to 50 – 100 g Al or Fe/m3 in some cases), the consumption depending on the quality

of the source water used for potable water production (Dharmappa et al., 1997). The use of chemical

results in not only large direct costs for chemical input but also the production of large amounts of

sludge, the disposal of which (mostly through landfill) incurs significant costs for water utilities.

In sewers, chemical addition is widely applied to mitigate the costly (in the order of A$100 million

a year in Australia) corrosion and odor problems caused by hydrogen sulfide (H2S). A variety of

chemicals are used for this purpose with the key ones being oxygen, nitrate, magnesium hydroxide,

sodium hydroxide, and iron(Fe)-salt. Among these, Fe-salt is the dominant chemical used in

Australia with Fe-salt treated sewage representing 2/3 of the total amount of sewage receiving

chemical treatment (Ganigue et al., 2011a).

Iron- or aluminium-based salts are often added at WWTPs to improve sludge settleability in both

the primary and secondary settling tanks. These salts are sometimes also added for chemical

phosphate removal, and in some cases to supplement biological phosphorus removal (Yeoman et al.,

1988). The dosing of these coagulants consumes alkalinity, and hence should only be used when the

wastewater has sufficient alkalinity or additional alkalinity may need to be supplied. It is also

practiced that Fe-salts are added to anaerobic digester (AD) for H2S removal in biogas (Ge et al.,

2013).

3

The use of the chemical in one sub-system could have impacts on another system, and use of alum

in WTP is one such example. Alum (i.e. hydrated double sulfate salt of Al) is widely used for water

treatment processes in Australia. This has been found to substantially increase sulfate levels in

drinking water, which eventually ends up in sewage (Pikaar et al., 2014). Such elevated sulfate levels

in sewage will promote the sulfide production in sewers, intensifying sewer concrete corrosion and

odor problems. This suffices that sulfate is not an ideal counter anion in coagulants when the whole

UWS is considered. Hence, the use of chloride-based Fe-salts had been suggested in further

exploiting associated several opportunities with the use of iron-based coagulants. Talking about the

economic implications of changing the inorganic chemical coagulants, overall economic benefits

that can be achieved with the chemical coagulants change-over (iron salts or alum) are expected to

differ depending on the local conditions of the catchments such as the type and size of sewer

network, configuration of the downstream WWTP, effluent nutrients discharge standards, and the

price and availability of alum- and iron-based coagulants, and would require careful consideration

on a case-by-case basis. Within Australia, for example, iron chloride is cheaper in Sydney, while

alum is cheaper in most other regions, judged based on the choice of coagulants for drinking water

treatment. The exact prices are commercially sensitive information due to individual contracts.

However, the costs associated with chemical change-over costs and location of dosing are expected

to be much lower than the potential up-stream and downstream savings that can be achieved for e.g.

expenditure for odour control and rehabilitation of sewer assets alone (Pikaar et al., 2014).

Therefore, economic benefit analysis should be done on a case-by-case basis.

Other than economic benefit analysis when considering the coagulants change-over between alum

and iron salt, we should take to account of the differences between their coagulation performances.

Higher positive charges of hydrolysis species were found for alum compared to FeCl3, which

suggests alum requires lower dosage for charge neutralization. But when residual turbidity was taken

into consideration, it was found that the turbidity removal efficiency of alum is actually lower than

FeCl3 due to the nature of hydrolysis speciation of the latter one. Besides, FeCl3 exhibits higher

𝑂𝐻−: 𝑀+ ratios than alum, which means lower charge density with higher binding capability. The

comparative studies highlighting the differences in coagulation performance between alum and

FeCl3 in terms of finished water qualities are provided in Appendix A.

4

1.2 Overview of Fe-salts uses in various components of urban water system and associated

implications

1.2.1 Use of Fe-salt in water treatment plant

Coagulation process and associated challenges

Coagulation is the most important solid-liquid separation stage in contaminants removal in water

treatment processes for the production of drinking water with acceptable water quality in compliance

with the state’s stringent drinking water rules and regulation and economical WTP operation. Various

types of chemical coagulants, especially hydrolyzing metal salts (aluminum and iron-based) in several

million tons per year are used worldwide for this purpose and the demand for such coagulants is still

growing (Dhiman, 2008). Different mechanisms govern the coagulation process in water and

wastewater treatment. Coagulation using inorganic salts such as iron and alum is primarily based on

the ‘charge neutralization mechanism’ (Oriekhova and Stoll, 2014).

‘Coagulant dosage’ is referred to as one of the most important parameters that influence the

coagulation process in water treatment process. Optimal use of chemical coagulant actually dictates

the effectiveness of chemical coagulation process in producing potable water of desired quality as

failure to apply optimal coagulant dosage could lead to wastage of expensive chemicals, inability to

meet the stringent water quality targets, and less efficient operation of subsequent sedimentation and

filtration processes (Cheng et al., 2008; Gao et al., 2007).

Challenges to handling sludge production during coagulation and potential beneficial re-uses

The addition of metal salts (say Fe-salts) as a coagulant for removal of desired contaminants in source

water during coagulation process results in the production of large amount of sludge. Such production

of sludge during coagulation process in WTP, however, depends on level of organic matter (OM) and

total suspended solids (TSS). Nonetheless, amount and the characteristics of the sludge produced

depend on the type of coagulant used and operational conditions (Aguilar et al., 2002). The cost of

handling and disposal of this produced waterworks sludge accounts for huge operating costs for WTP

(Kyncl, 2008; Snurer, 2005). It is, therefore, crucial to assess and quantify, precisely, the chemical

sludge production resulting from coagulation processes in WTPs in order to design properly the

operating expenditures of the treatment plants.

5

It had been depicted that settled sludge production typically equates to 1 to 3% v/v of the raw water

throughput (Blakemore et al., 1998), whilst another study reported settled coagulant sludge flows

typically vary between 0.1 and 3% volume of WTP throughput (Cornwell, 2006). Due to high WTP

sludge disposal costs, an increased pressure to minimize the amount of sludge sent to waste disposal

facilities is being felt in Australia (Verrelli, 2008a). Accordingly, it is now a mandatory part of Sydney

Water’s Operating License (SWOL) that a water utility needs to monitor and report the production

and beneficial reuse of water treatment ‘residuals’ (including the types of sludge produced), and put

into place a complementary Environmental Management System (EMS) (SWCOL, 2005; Verrelli,

2008a). Hence, more economic alternatives are employed at first to minimize the WTP sludge

generation and at its disposal.

Depending upon the specific local conditions including size of WTP operation, WTP sludge disposal

options had been adopted accordingly, i.e. recycling, mixed waste disposal facility, return-to-source,

segregation and treatment, land spreading, use as construction materials, stockpiling, removal of

hazardous chemicals and dewatering (GHD, 2015; GWC, 2014). Further, WTP waste (sludge + brine)

disposal legislation is also being more stringent these days in different countries (Verrelli, 2008a). In

compliance to this scenario, some of the common disposal routes for WTP sludge (which varies from

country to country) (Table 1) includes – disposal to natural water bodies, discharge to sewer,

discharge to lagoons, waste landfilling, engineering fill and other land application such as agricultural

uses (Russell and Peck, 1998b). However, an adequate amount of research is lacking in a broad range

of beneficial usages of WTP sludge or chemical re-use (Verrelli, 2008a).

It had been reported that annually more than 6000 dry tonnes of WTP sludge are produced only in

Australia (UWI, 2006). Traditionally, this sludge has either been dried and stockpiled on-site for years

or disposed to sewers (UWI, 2006). As shown in Table 1, the disposal of WTP sludge into the sewers

is one of the very popular disposal routes. Doing so, sludge dosed to sewers can be treated together

with the sludges generated from downstream WWTP, delivering large economic benefits. Some other

benefits of WTP sludge dosing directly into sewer or other treatment units of WWTP are depicted in

Table 2 (Sarfert et al., 1994). In retrospect, the feasibility of disposal of WTP sludge to sewer is

largely governed by local geography including the proper coordination between discharging WTP

operators and receiving WWTP operators (Verrelli, 2008a). Importantly, a comprehensive

understanding of implications associated with direct dosing of waterworks-derived sludge into sewers

is still lacking, considering the long history of such sewer-dosing practices (Table 1 and Table 2).

6

Table 1. Various commonly adopted WTP sludge disposal routes in New Zealand, U.K., and U.S.A.

(major routes in highlighted)

S.N. Disposal routes

(in percentages)

Countries New Zealand* United Kingdom

(U.K.)**

U.S.A.***

I Freshwater 45 (50 plants) - -

II Wetland 2 (3 plants) 2 (‘water

environment)

11 (‘streams’)

III Marine 1 (1 plant) - -

IV Sewer, WWTP 23 (26 plants) 25 (direct) 24

4 (trucked)

V Landfill 13 (15 plants) 57 20 (‘landfill)

VI Lagoon 11 (12 plants) 2 13 (‘monofill’)

VII Land application 4 (5 plants) 9 25

VIII Construction

materials

- (0 plants) 1 -

IX Other - (0 plants) - 7

* New Zealand (122 plants, August 1996, albeit data of 10 treatment plants excluded)

(Blakemore et al., 1998; Ogilvie, 1997)

** U.K. (circa 1999) (Parsons and Jefferson, 2006)

*** U.S.A. (circa 2000) (Cornwell, 2006)

Table 2. Some beneficial aspects associated with WTP-derived iron sludge dosing for wastewater

treatment (adapted from (Sarfert et al., 1994))

Application of waterworks Fe-sludge Observed effects

Discharge into sewer system Binding of sulfide and removal of phosphates

by adsorption

Dosing to settling tanks Removal of phosphates by adsorption, also

binding of sulfide

Dosing into activated sludge system Improved phosphate removal and sludge

settleability

Dosing into sludge digestion tanks Binding of sulfide and also stabilization of

digestion process

7

1.2.2 Use of Fe-salts in sewers

Odor and corrosion problems in sewers

Sewer network is one of the crucial components of UWS. The conventional design and management

approach depict ‘sewer pipe’ as a mere ‘wastewater conveyance channel’, overlooking the various

in-sewer transformations that occur in sewer environment prior to it reaches to treatment facilities. In

recent years, sewer networks are not merely taken as infrastructure that solely performs the function

of collecting and transporting wastewater. This is because various in-sewer transformations (aerobic,

anoxic or even anaerobic) occur in sewer environment. Occurrence of these types of transformations

is primarily governed by two major factors, which include - (i) type of electron acceptors (biological

oxidants) present in sewer system (i.e. ‘oxygen’ for aerobic respiration, ‘nitrate’ for denitrification,

‘organic compounds’ for fermentation, ‘sulfate’ for sulfate reduction and ‘carbon-dioxide’ for

methanogenesis) and (ii) characteristics of in-sewer system or type of sewer (Bentzen et al., 1995;

Hvitved-Jacobsen, 2002; Nielsen et al., 1992). In a nutshell, sewer is considered as a ‘bioreactor’

encompassing various in-sewer physical, chemical or biological (microbial) processes occurring in

various in-sewer sub-components such as wastewater (bulk phase), sediment, biofilm, and in gas-

phase (sewer atmosphere and moist sewer surfaces/sewer walls) (see Figure 2) (De Toffol, 2006).

Anaerobic condition prevails when dissolved oxygen (DO) and nitrate (NO3-) ions are absent, mostly

in pressure mains and the surcharged gravity mains. Such prevalence of anaerobic or septic conditions

actually serves as a precursor for sulfide build-up in the sewer system, which is primarily responsible

for corrosion and odor problems (Bentzen et al., 1995; Hvitved-Jacobsen, 2002). Conditions such as

high temperature, low flow velocity, large water depth with insufficient re-aeration, large biofilm area

to bulk water volume ratio, high chemical oxygen demand (COD) concentration, sewer sediment

deposits including stagnant wastewater flow promote the higher sulfide production in sewers (Nielsen

et al., 1992).

8

Figure 2. Typical representation of various important in-sewer processes including sewer sediment

strata and possible in-sewer sediment processes (Mouri and Oki, 2010; Nguyen et al., 2015)

The positive correlation between the H2S level and microbial induced sewer concrete corrosion is the

proven fact, which comes with huge economic cost requisite for sewer pipes repair and maintenance

including replacement (Carrera et al., 2016; Sydney et al., 1996). For instance, replacement and repair

of corroded concrete sewer pipe had been estimated to cost millions of dollars per year alone in the

USA (Koch et al., 2001) and Germany (Hewayde et al., 2006). Similar was the case even in Australia,

the economic loss caused due to sewer corrosion had estimated to be millions of dollars per year

(Rootsey and Yuan, 2011). Hence, there has been growing usage of various biological and chemical

measures lately for controlling sulfides in the sewer system. These measures incorporate addition of

oxidizing chemicals, metal salts as chemical precipitant, biological oxidation of sulfide/biological

inhibition of sulfate reducing bacteria (SRB) activity using biocides including some emerging new

approaches such as use of formaldehyde/para-formaldehyde/glutaraldehyde, microbial fuel cells

(MFCs), slow release solid-phase oxygen and SRB lysis (Zhang et al., 2008; Zhang et al., 2015). Of

the five different widely used chemicals by Australian water utilities for sulfide control in sewer

systems, Fe-salt is relatively the most preferred chemical for sulfide control, i.e. accounts for 66%

of the total sewage receiving chemical dosing. This is because Fe-salt dosing is a simple and cost-

effective method for sulfide control which is appropriate for all kinds of sewer systems (i.e. small,

medium or large) (Ganigue et al., 2011b). Besides, Fe-salt dosing is reported to hinder the SRB’s

activity without interfering the biofilm activities (Zhang et al., 2009b; Zhang et al., 2010).

9

Iron-sulfide interactions in sewer system

As a consequence of sulfide-induced sewer concrete corrosion, there is an annual loss of millions of

dollars globally. The addition of Fe-salts is proven to be effective in controlling sulfide build-up in

sewers. In-sewer dosing of Fe-salts is reported to form ferrous sulfide (FeS) or possibly other iron

sulfide precipitates (FeSX). The sulfide precipitation reactions with Fe are generally simplified as

depicted in Eqs. (1)-(2), which is a two-step reaction (Nielsen et al., 2005a; Padival et al., 1995; Zhang

et al., 2008):

Fe2+ + S2- → FeS (1)

2Fe3+ + 3S2- → 2FeS + S0 (2)

Gutierrez et al. (2010) suggested the fast reduction of Fe3+ to Fe2+ as depicted in Eq. (2) which

corroborated that the reaction to be entirely chemical and it was reported that on average 0.44 mol of

sulfide is oxidized per mol of Fe3+ reduced. This is close to the theoretical value of 0.5 mol S/mol Fe

when elemental sulfur is the oxidation product as outlined in Eq. (2). The oxidation of dissolved

sulfide is relatively fast, and assuming the reaction to be first-order, the average half-life period of

dissolved sulfide is calculated to be 5.6 hr (Nielsen et al., 2005a), it is also demonstrated that dissolved

sulfide oxidizes at a much higher rate than the pool of other metal sulfides. Later, it was depicted that

the dominant product of precipitation is FeS (when dosing ferrous salts) and the dominant or favorable

thermodynamic product of sulfide oxidation (when dosing ferric salts) is sulfate (SO42-). Likewise,

the main sulfide oxidation product is reported to be Sº (elemental sulfur) when using a mixture of

ferric and ferrous salts. Precipitation reactions between ferrous or ferric iron and dissolved sulfide

species as outlined in Eqs. (1)-(2), are not entirely straightforward. Hence, different other possible

reactions between Fe and sulfides species can be found in the literature (Firer et al., 2008). Usually,

several factors affect the sulfide concentration in sewers and hence FeSX precipitation as outlined in

Eqs. (1)-(2). These include – pH, DO, sulfate concentration, wastewater temperature, alkalinity,

biochemical oxygen demand (BOD), flow velocity, and in-sewer retention time. Details can be found

in previous studies (Firer et al., 2008; Wu et al., 2018).

Anaerobic autotrophic bacteria (SRBs) inhabiting the slime layer/biofilms are primarily responsible

for forming sulfides in sewers. The addition of Fe-salts was reported to inhibit the sulfate-reducing

and methanogenic activities of anaerobic sewer biofilms in pressure mains. Zhang et al. (2009b)

revealed Fe3+ dosage significantly inhibited the SRB activity and methanogenic activity of anaerobic

sewer biofilms by 39%–60% and 52%–80%, respectively. These results were in agreement with the

previous studies, which reported Fe3+ inhibited the sulfate reduction and methane production rates in

10

marine and freshwater sediments (Holmer et al., 2005; Lovley and Phillips, 1987b; van Bodegom et

al., 2004; van Bodegom, 1997). Unlike Fe-salt, Fe-rich WTP sludge dosing did not cause the

inhibition of SRB’s activity of the sewer biofilm (Sun et al., 2015).

Dosing of Fe-salt in the sewer for sulfide control demands continuous dosing which incurs high

chemical costs. This necessitates the finding of some other cheaper alternative source of Fe. In this

context, a recent laboratory study showed the effectiveness of Fe-rich WTP sludge in controlling

sulfide in sewer, attributing primarily to the precipitation reaction occurring between sulfide and ferric

in the WTP sludge (Sun et al., 2015). This suggests the direct in-sewer dosing of Fe-rich WTP sludge

could be an effective strategy for sulfide control akin to their chemical counterparts, however with

significant cost savings. Having said that, the comprehensive understanding of the unintended effects

(other than sulfide or phosphate removal) due to WTP sludge dosing in sewers under more realistic

sewer conditions is still lacking.

1.2.3 Use of Fe-salts in activated sludge system

Use of Fe-salts as phosphorus precipitant

Chemical phosphorus removal (CPR) process involves addition of metal salts (such as Fe-salts) in

activated sludge (AS) system, resulting in insoluble phosphate (PO43−) precipitates, which eventually

settle down with the wastewater sludge in the secondary settling tank (Yeoman et al., 1988). Direct

addition of Fe-salts in AS system was found to be effective in PO43− removal (Oikonomidis et al.,

2010). On contrary, recent studies have shown the Fe-salts dosed in the sewer for sulfide control,

could precipitate PO43− in bioreactor and also facilitate in sulfide control in the digester (Ge et al.,

2013; Gutierrez et al., 2010). A laboratory study has demonstrated that by moving dosing Fe-salts

location from the WWTP to a sewer located upstream of the WWTP, both sulfide control in sewer

and phosphate removal in a bioreactor could be achieved with the same Fe dosing (Gutierrez et al.,

2010). This highlights the multiple beneficial uses that could be exploited via the proper selection of

Fe-salt dosing location upon considering the system-wide (integrated sewer-WWTP) operation.

Considering the flowing on effects of Fe with upstream in-sewer Fe-salt dosing during system-wide

operation, FeSX containing sewer effluent when reaches downstream WWTP, FeSX precipitates are

first re-oxidized in the aeration tank regenerating Fe3+ ions, making it available to precipitate PO43−

as depicted in Eq. (3).

1.3FeS + PO43- + 2.9O2 + 0.3H2O + 0.4H+ → Fe1.3PO4(OH)0.9 + 1.3SO4

2- (3)

11

Addition of ferric salts for PO43− removal in activated sludge system is reported to form insoluble

‘ferric hydroxyl-phosphate complexes’ (Nielsen et al., 2005a; Rasmussen and Nielsen, 1996) either

alone or together with Fe(OH)3 which also incorporates an additional mechanism for phosphate

removal through adsorption of PO43- ions on the precipitate as shown in Figure 3 (Luedecke et al.,

1989). The adsorption mechanism could have an important effect on total PO43- removal, especially

at low residual phosphate concentrations (P-limiting conditions). Such chemically mediated P

removal can occur via different pathways and these are as follows (Takacs et al., 2006):

i. adsorption of phosphate onto hydrous ferric oxide (HFO);

ii. co-precipitation of phosphate into the HFO structure;

iii. precipitation of ferric phosphate;

iv. precipitation of mixed cation phosphates (i.e. Ca, Mg, Fe, or Al phosphates, or

hydroxylphosphates).

Accordingly, Takács (2008) proposed two different models for chemically mediated PO43- removal,

i.e. surface complexation modeling (SCM) and chemical equilibrium model (CEM). Regarding the

nomenclature, de Haas et al. (2000) proposed a molecular formula for ferric hydroxyl-phosphate

complex under P-limiting conditions ranging from Fe3(X2+)PO4(OH)8 to Fe2.33(X

2+)2.5PO4(OH)9, with

X2+ being a divalent cation (e.g. Mg2+ or Ca2+).

Figure 3. Adsorption mechanism of phosphate (PO43−) ions on iron (Fe) precipitate

Nonetheless, type of the Fe-salt dosed can also have significant impact on CPR process as different

Fe-salts result in slightly different degrees of PO43− removal, i.e. amount of P removal was found to

be 0.44 and 0.37 mg P.(mg Fe)-1 for Fe3+ and Fe2+ ions, respectively (Gutierrez et al., 2010). This was

corroborated to a different degree of stability of precipitates that forms when using Fe3+ or Fe2+ salts

(Gutierrez et al., 2010). Some studies revealed stable amorphous FeS as the final product when dosing

ferrous salts to precipitate sulfide under anaerobic conditions (Nielsen et al., 2005a; Nielsen et al.,

2005c). However, there are still uncertainties about the detailed mechanism involved in sulfide

oxidation by ferric ion and the subsequent precipitation (Davydov et al., 1998). Compared to ferrous

12

precipitation, more complex reactions and intermediate compounds are involved in ferric

precipitation (Firer et al., 2008). Gutierrez et al. (2010) reported that the use of FeCl3 seemed to create

a pool of Fe-complexes during re-oxidation, resulting in higher PO43− removal under aerobic

condition. However, mechanisms involving FeSX re-oxidation including elaboration of differences in

PO43− removal when using ferrous/ferric salts are not very clear in the literature.

Impacts of using Fe-salts on key activated sludge properties

While the use of Fe-salts for chemical phosphorus precipitation in AS system has received substantial

consideration in the literature, there are limited studies on understanding the influence of Fe-salt

dosing (direct or indirect) on different key activated sludge properties (see Section 1.4). Direct

addition of Fe-salts in AS system was found to be effective in improving settleability (Oikonomidis

et al., 2010) and dewaterability (Wei et al., 2018) of activated sludge. However, none of the studies

to date have reported the unintended beneficial consequences on activated sludge settleability and

dewaterability upon discharging the Fe containing sewer effluents (i.e. resultant of sewer dosed Fe-

salt) into a bioreactor. Developing an understanding of key parameters affecting sludge characteristics

and their interactions with sludge settleability and dewaterability would help to unravel the

mechanism behind the changes in these properties and allow the examination of the impacts of Fe

dosing in a holistic manner.

1.2.4 Use of Fe-salts in anaerobic digester

Hydrogen sulfide (H2S) control

Few studies have shown the efficacy of direct/indirect Fe-salt usage in desulfurizing the digester

biogas (Akgul et al., 2017; Novak and Park, 2010; Rebosura et al., 2018). Direct dosage of Fe-salt to

anaerobic digester (AD) have shown effectiveness in removing H2S in AD biogas (Akgul et al., 2017;

Novak and Park, 2010). Akin, indirect (upstream in-sewer dosing) dosage of Fe-salt to AD have also

shown similar impacts during operation of an integrated laboratory sewer-WWTP system (Rebosura

et al., 2018). In this context, Ge et al. (2013) reported that Fe3+ ions released from ferric phosphate

precipitates under a reductive condition in AD, precipitate with sulfide that formed during anaerobic

sludge digestion, thereby resulting desulfurization of digester biogas. It was also further

recommended that Fe-salt addition to sewers at concentration ranging (5–20 mg.Fe.L-1) would

provide the requisite Fe for sulfide control in AD, without negatively impacting the methane

production and other digestion processes (Ge et al., 2013; Mamais et al., 1994a). Similarly, Fernandez

et al. (2010) also found Fe-precipitates did not exhibit any detrimental effect on AD processes

13

including biogas or methane production. On the contrary, some studies had depicted contrasting

results regarding biogas yield when dosing Fe-laden sludge (Table 3).

Likewise, impacts of Fe-dosed activated sludge (resultant of CPR process using Fe-salts) on the AD

process had been widely discussed over the years, i.e., whether chemical coagulants impaired AD

process or not. Some previous studies reported that there would be no effect of Fe-dosed sludge on

AD process (Ghyoot and Verstraete, 1997; Grigoropoulos et al., 1971), whilst other reported the

adverse impacts of Fe-dosed sludge on AD process (Dentel and Gosset, 1982; Johnson et al., 2003;

Smith and Carliell-Marquet, 2008; Yeoman et al., 1990). A reduction in the biogas production in AD

due to Fe-dosed sludge was the most common adverse effect reported in the latter case. However, this

decline was not related to Fe toxicity but was rather related to the high protein or lipids present in

wastewater (Dentel and Gosset, 1982). In conclusion, we can posit that there exist two views in the

literature regarding the impacts of Fe-dosed activated sludge on AD performance.

Control ammonia toxicity

Methanogens present in AD demand high Fe-availability. Fe is considered one of the essential

micronutrients during anaerobic sludge digestion process as Fe can perform as an enzyme, a terminal

electron acceptor or an oxidation/reduction agent. Fe3+ when reduced to Fe2+ under anaerobic

conditions, reacts with ammonia formed during the anaerobic fermentation resulting in ammonia

reduction (Ivanov et al., 2009). This implies the Fe addition to AD has also beneficial impact in terms

of control of ammonia toxicity.

14

Table 3. Summary of previous research results depicting the influence on digester biogas production

when dosing Fe-laden sludge (Smith and Carliell-Marquet, 2009)

Type of experimental equipment and sludge

used for AD process

Amount of biogas/methane production compare

to biogas production from non-dosed Fe or Al

sludge

Lab-scale batch tests (BT) and semi-

continuous (SC) bench-scale tests, raw sewage

dosed with Fe and Al (Dentel and Gosset,

1982)

21-32% less biogas

Lab-scale SC, primary sludge dosed with Fe

and Al (Yeoman et al., 1990)

20% less biogas

Lab-scale SC, activated sludge dosed at

WWTP with Fe (Johnson et al., 2003)

32% less biogas

Lab-scale BT, AS dosed with Fe (Smith and

Carliell-Marquet, 2008)

12% less biogas; 4-7% less methane

Lab-scale BT, AS dosed with Fe (Smith and

Carliell-Marquet, 2009)

12-20% less biogas; 10-22% less methane

Lab-scale AD, mixture of primary and

activated sludge dosed with Fe (Ofverstrom et

al., 2010)

20-50% less biogas

Control of struvite formation

Anaerobic sludge digestion favors the formation of struvite (MgNH4PO4.6H2O) as ammonia,

phosphate, and magnesium are solubilized during the digestion process (Mamais et al., 1994a). If

high ammonia, phosphate, and magnesium concentrations are present, struvite can form even at a pH

below 7. However, if one of the ions is present at low concentration, a substantially higher pH is

required to induce precipitation of struvite (Takács, 2008). Typically, digested sludge (or digestate)

contains struvite particles that account for 5-15% of the sludge dry weight (Koga, 2019).

Accumulation of struvite in AD and post-AD processes can cause struvite-scaling problems in

15

WWTP (Ohlinger et al., 1998). However, the prevention and treatment of struvite accumulation at

WWTPs is limited and can be a formidable and costly task. WEF (1991) reported the dosing of ferric

salts to remove phosphate as one of the common preventive methods. Mamais et al. (1994a) reported

Fe-salts addition in digester effluents containing struvite crystals could cause the dissolution of

precipitates thereby causing vivianite (Fe(PO4)2.8H2O) formation, a non-soluble ferrous phosphate

precipitate. There has been growing interest in recovering both struvite and vivianite in recent years,

which are considered not only as an ideal P recovery routes but also ideal option to simultaneously

reducing the internal load of P and ammonia in WWTP (Koga, 2019; Wilfert et al., 2016).

Fe-P-S interactions during wastewater treatment in system-wide operation

The niche of interactions existing amongst iron (Fe), phosphorus (P), and sulfur (S) species when

dosing Fe-salts during wastewater treatment holds a significant place in system-wide operation. In

reality, the behavior of S or anaerobic S cycling is closely related with P, and also Fe

oxidation/reduction processes are closely associated with both P and S cycles under anaerobic

condition (Flores-Alsina et al., 2016; Rodriguez-Freire et al., 2014). Both these anaerobic and aerobic

Fe-P-S interactions are complex and affect the whole water cycle in UWS (i.e. sewer system vis-à-

vis downstream WWTP). As outlined by Batstone et al. (2015), sulfate is reduced to sulfides in the

sewer and primary treatment processes, with the sulfide binding with Fe2+ or Fe3+ ions thereby

releasing P. Once FeS reach the AS system, the sulfide is biologically re-oxidized into sulfur and

sulfate, concomitantly iron is re-oxidized into ferric forms. This releases Fe to bind with P as iron

phosphate precipitate, with simultaneous biological assimilation and polyphosphates (PP)

accumulation (Batstone et al., 2015). In AD, sulfate is again reduced to sulfide and precipitated iron

phosphate (formed in AS process), wherein biological assimilated phosphorous (i.e. PP biomass)

might be chemically or biologically released through re-dissolution of thus formed iron phosphate

and hydrolysis of PP under anaerobic condition (Ge et al., 2013). Such re-dissolution of iron

phosphates under anaerobic condition to precipitate sulfide in AD can be attributed to the much lower

solubility of FeS in compared to iron phosphate precipitate (Flores-Alsina et al., 2016; Ge et al.,

2013). Concomitantly, there might be the formation or precipitation of Ca and Mg phosphates due to

the increment of pH in a digester. At the same time, Fe3+ is reduced to Fe2+ using hydrogen or sulfide

as an electron donor. The latter can precipitate as FeS achieving the overall sulfide control in AD

biogas (Zhang et al., 2013) or also produce struvite in the digesters rather than in subsequent sludge

lines (van Rensburg et al., 2003). Recovery of such struvite facilitates to simultaneously recover

phosphate and ammonia from the digested sludge (Koga, 2019). Application of anaerobic-based

WWTPs has reported to result 71-96% P recovery via struvite crystallization (Venkatesan et al.,

16

2014). Further, recent work by Wilfert et al. (2018) reported the formation of vivianite during

anaerobic digestion when iron salts were dosed to the treatment plant. Due to the magnetic properties

of vivianite, this opens up opportunities for its targeted recovery from the sludge via magnetic

separation. This approach has recently gained significant interest and has shown significant economic

and practical potential (Prot et al., 2019).

The occurrence of such chemical interactions/transformations involving Fe, P, and S including the

release of sulfides from volatile solids destruction in AD and its subsequent precipitation could exhibit

some changes on the key properties of anaerobically digested sludge (i.e. digestate) linked directly or

indirectly to its dewaterability, which needs further justification.

1.3 Reuse of waterworks Fe- or Al-sludge in urban water system

1.3.1 Current trend of reusing waterworks sludge

Waterworks sludge (or WTP sludge) are most commonly disposed of in sewers, lagoons, and landfill

sites (Verrelli, 2008b). The disposal options for waterworks sludge, varies depending on the country,

local conditions and size of WTP operation (Russell and Peck, 1998a). The different

management/disposal routes for waterworks sludges in the U.S.A., the U.K., and Japan are presented

in Figure 4. Clearly, landfilling and reusing (i.e. in sewers/WWTP) are two predominant disposal

routes for waterworks sludge. Similar trends were reported by the previous studies (Table 1). In

Australia, end uses of such waterworks sludge vary in each State, however, disposal to landfill or

sewer is the fate of the much waterworks sludge generated from WTP (GHD, 2015). A wide variety

of end uses of sludge (particularly Al-sludge) as reported in the literature is outlined in Figure 5

(GHD, 2015). This is because two-third of Australian water utilities use alum instead of Fe-salts for

the water treatment processes.

17

Figure 4. Final disposal routes employed for waterworks sludges (Tahmazi, 2017)

1.3.2 Opportunities for reusing waterworks sludge

Al or Fe containing waterworks sludge, is an inevitable by-product in WTPs, depending on whether

Al- or Fe-salt is used as a primary coagulant. The daily production of WTP sludge globally is reported

to exceed 10,000 tonnes (Babatunde and Zhao, 2007), and more than 6,000 dry tonnes of WTP sludge

is produced per annum in Australia alone (Verrelli, 2008b). The production of such WTP sludge is

expected to increase over the years, considering the growing demand for potable water by a rapidly

increasing global population. Hence, sustainable management of such enormous volumes WTP

sludge is essential.

Of particular interest are the disposal of WTP sludge to sewers (see Section 1.2.1) (Table 1), which

is more common in Europe, the U.K. and the U.S.A. (Kawamura, 2000; Keeley et al., 2014). Doing

so, WTP sludge could be treated together with sewage sludge in the downstream WWTP, providing

the wide-ranging economic benefits (Verrelli, 2008b). However, there could also be some unintended

consequences when adopting in-sewer dosing of WTP sludge that requires investigations. Several

factors should, therefore, be considered prior adopting sewer disposal for system-wide operation, i.e.

sedimentation in sewers and changes in sewage characteristics, sludge handling capacity of receiving

WWTP, etc. (GHD, 2015; Hsu and Pipes, 1973; Sun et al., 2015). Although there has been growing

interest in the direct reuse of waterworks Al- and Fe-sludge in sewers, the full impacts of such practice

are not well understood, especially in terms of understanding their transformation/transport in sewer,

influence on different sewage characteristics under realistic sewer condition, potential impacts on

18

sludge settling and dewatering performances of receiving WWTP including changes in key activated

sludge and digestate properties. One of the key concerns of such sewer dosing practice is solids

concentration of WTP sludge being discharged into sewers as discharging WTP sludge at too high

solids concentrations may result in sedimentation issues in sewers. Another important factor

associated with this in-sewer WTP sludge dosing strategy is the ‘flow velocity of wastewater in the

receiving sewer’, which should be carefully considered while discharging the WTP sludge (Sun et al.

2015). Similar applies in case of Fe-salt when considering sewer-based Fe-salt dosing and potential

flowing on impacts of Fe at the downstream WWTP (see Sections 1.2.3 and 1.2.4).

Figure 5. Various options adopted as end uses for waterworks-derived sludge in Australia.

1.4 Activated sludge and digestate properties

1.4.1 Settleability and dewaterability of sludges

Large quantities of wastewater sludges are generated during activated sludge treatment and anaerobic

digestion in WWTP. Hence, reducing the volume and water content of activated sludge and digestate

is still a major concern. To dispose of the sludge economically, an effective dewatering process is

19

essential to reduce the sludge volume, which is still a bottleneck for sludge treatment and management

(Jin et al., 2004). This is because dewatering is one of the costly processes in wastewater treatment.

Akin to the effective dewatering, achieving the good settling of activated sludge in WWTP is equally

important. This is because effective separation of the solids from the liquid phase and also subsequent

dewatering of those solids dictates the overall performance of an activated sludge system/bioreactor

(Liu et al., 2013). Notably, the dewatering and settling characteristics of sludges vary depending on

the wastewater sources and treatment processes adopted in WWTP.

Fe-salts are widely used as a coagulant or redox catalyst for water and wastewater treatment processes

(Waite, 2002). Of interest is the uses of Fe3+ or Fe2+-salts in the urban wastewater systems, i.e. sewer

system and other downstream treatment units such as AS system or AD in WWTP. Direct dosing of

Fe-salt in sewers (Ganigue et al., 2011b; Gutierrez et al., 2010; Zhang et al., 2009b; Zhang et al.,

2010) and AD (Akgul et al., 2017; Park and Novak, 2013; Parker et al., 2019) for controlling sulfides

or chemical P precipitation with Fe-salt in AS system (de Haas et al., 2000; de Haas et al., 2001;

Gutierrez et al., 2010), have been established as the proven practices. Such a strategy of direct Fe-salt

dosing has been reported to improve settleability (Oikonomidis et al., 2010) and dewaterability (Wei

et al., 2018) of activated sludge including the dewaterability of digestate (Novak and Park, 2010;

Akgul et al., 2017). Unlike direct dosage of Fe-salt to AS system or AD, the nature of the implications

of precipitated Fe upon reaching downstream AS system or AD on key sludge properties are likely

to be different when indirect (upstream in-sewer) Fe-salt dosing is employed. However, the exact

nature of these impacts is not clear, and this necessitates an investigation of the changes in key

properties of both activated sludge and digestate. This would provide a better understanding of the

system-wide impacts of the Fe dosing much more than sulfide- and phosphate-related reactions in

wastewater treatment and anaerobic sludge digestion. Such understanding would be equally crucial

when considering the recent paradigm shift concerning the Fe-salt usage in integrated sewer-WWTP

operation.

1.4.2 Key sludge properties that affect settleability and dewaterability

Content and composition of extracellular polymeric substances (EPS)

Extracellular polymeric substances (EPS), secreted by a wide range of microorganisms, are primarily

composed of proteins (PN), polysaccharides (PS), and nucleic acids (Chen et al., 2015). EPS accounts

for about 60-80% of total sludge mass (Liu and Fang, 2003) and markedly influences the sludge

settling and dewatering performances (Mikkelsen and Keiding, 2002). Increased loosely-

20

bound/soluble-EPS content is reported to enhance the sludge volume index (SVI) values (Sheng et

al., 2010), whereas the reduced total EPS content is associated with the improved sludge

dewaterability (Chen et al., 2001). This is because increased EPS content increases the amount of

interstitial water in sludge flocs and also catalyzes the steric forces thereby inhibiting the inter-cellular

contacts (Chen et al., 2001; Sheng et al., 2010). Yu et al. (2008) reported the stratified structure of

sludge flocs consisting of soluble EPS (S-EPS = supernatant + slime), loosely-bound EPS (LB-EPS),

tightly-bound EPS (TB-EPS), and pellet fraction, and suggested that the sludge dewatering

performance is mainly dictated by the soluble EPS fractions. In contrast, earlier studies found that the

sludge dewaterability is correlated with LB-EPS rather than TB-EPS fractions (Li and Yang, 2007;

Novak et al., 2003). The dominance of LB-EPS fractions in total EPS has been found to negatively

impact the bio-flocculation, viscosity, effluent suspended solids, settleability, and dewaterability of

sludge (Li and Yang, 2007). This is attributed to the increased amount of bound water and the

formation of highly porous sludge flocs of low density with the increased LB-EPS content (Yang and

Li, 2009). Bio-flocculation in the AS system is a very important phenomenon as it directly affects

sludge settleability and dewaterability (Peeters, 2010).

Besides, EPS composition (PN, PS or PN/PS ratios) is found to significantly affect the sludge

dewaterability (Higgins and Novak, 1997a). Murthy and Novak (1999) reported that a high PN/PS

ratio is detrimental for sludge dewatering performance. Novak et al. (2003) further depicted that the

PN content of the EPS fractions significantly influences the sludge dewaterability in compared to PS

content, owing to the larger molecular size of PN (Murthy et al., 2000). Considering the high water-

holding capacity of PN fractions in sludge (Cetin and Erdincler, 2004; Sponza, 2002), the reduced

PN and PS contents in sludge are reported to positively influence the sludge dewaterability. Notably,

previous studies have only focused on the influence of PN and PS in the sludge EPS matrices in

relation to sludge dewaterability, overlooking the roles of humic acid (HA)-like and fulvic acid (FA)-

like substances. Increased humification index of sludge is also reported to contribute in improving

dewaterability, as previously suggested (Yu et al., 2010). In this context, Niu et al. (2013) have

reported changes in the soluble (S-EPS), loosely-bound (LB-EPS), and tightly-bound (TB-EPS)

concentrations, owing to the strong affinity of Fe3+ ions towards EPS. Albeit it is only for direct Fe-

salt addition, which implies a better understanding in this aspect concerning the influence of indirect

(i.e. sewer based) Fe-salt addition is still lacking.

21

Cations distribution in sludge matrix

Cations are also reported to play a significant role in bio-flocculation in the AS system (Nguyen et

al., 2008; Sobeck and Higgins, 2002). Cations constitute the important structural component of sludge

flocs as cations bind the negatively charged biopolymers (Higgins and Novak, 1997a; b; Murthy and

Novak, 1998) and also neutralize the negative charges on the EPS surface (Wilén et al., 2008). Hence,

the devoid of proper cation composition in the sludge flocs matrix, the strength, and stability of flocs

would be deteriorated causing the reduction in the sludge settleability and dewaterability. Cations,

particularly the role of divalent cations in enhancing the bio-flocculation in activated sludge is widely

accepted (Higgins and Novak, 1997a; b). However, excess monovalent cations can cause

deterioration in sludge floc structure and settling and also enhance the polymer demand for

dewatering (Higgins and Novak, 1997a).

Changes in concentrations of monovalent and divalent cations induce a change in another important

parameter, i.e. monovalent-to-divalent (M+/D++) cation ratio. This M+/D++ cation ratio is considered

as the central component of the divalent cation bridging theory (DCBT), which is widely applied in

evaluating the performance of AS systems. Lesser the M+/D++ cations ratio, better would be the

sludge settling and dewatering performances including effluent quality of AS system (Higgins et al.,

2004). Higgins et al. (2004) showed that lower M+/D++ cations ratio reflects the higher cake solids

content (%) but lower SVI (mL.g-1) values suggesting the enhancement in both the sludge

dewaterability and settleability. Earlier, Higgins and Novak (1997a) showed the positive correlation

of the M+/D++ ratio with the sludge filterability (specific resistance to filtrations, SRF). This is

because a higher M+/D++ ratio means the excess monovalent cations concentrations and these

monovalent cations can displace the divalent cations enmeshed within the sludge floc structure via

ion-exchange and deteriorate the sludge flocs properties. Akin, upon treatment with trivalent cations

such as Fe3+/Al3+ ions, the bridging monovalent or divalent cations present in sludge flocs may

undergo exchange with trivalent cations, further strengthening the flocs stability as explained in the

conceptual ion-exchange mechanism (Figure 6) (Peeters et al., 2011). This is due to higher binding

strength of trivalent cations with activated sludge flocs than that of monovalent or divalent cations

(Li et al., 2012), which is attributed to higher charge valence of trivalent cations (Park et al., 2006).

This suggests the Fe addition (direct or indirect) is likely to influence this M+/D++ cations ratio, which

demands a better understanding.

22

Further, the influence of inorganic content on sludge settleability and dewaterability has also been

reported. The increase in the sludge inorganic fractions contributes to improving the sludge

settleability as sludge with a higher inorganic fraction results in heavier flocs and therefore a better

settling ability (Higgins et al., 2004; Peeters, 2002; Peeters, 2010). Likewise, sludge with higher

inorganic fractions has shown much improved dewaterability (Peeters, 2010).

Figure 6. Conceptual schematic representation of the changing sludge floc structure owing to cations

distribution in the sludge flocs matrix (primarily Na+, K+, Ca2+, Mg2+, Al3+, Fe3+ concentrations)

resulted due to bridging divalent and trivalent cations exchange phenomena vis-à-vis M+/D++ cations

ratio and sludge settleability (modified from Peeters et al. (2011))

Moisture distribution or bound water content

Sludge dewaterability is governed by the total solids (TS) concentration of the sludge cake and the

polymer demand for sludge conditioning. However, TS concentration of the sludge cake is dictated

by the nature of moisture distribution in the sludge cake. This means sludge dewatering performance

is largely influenced by the sludge moisture distribution (Kopp and Dichtl, 2001). The measurement

of different water fractions content (such as free, interstitial, surface, and intracellular water) of sludge

helps in predicting the dewaterability of sludge and also determining the polymer-demand for sludge

conditioning (Kopp and Dichtl, 2000).

23

Amongst the different water fractions, reducing the content of bound water (intracellular + surface

water) is critical for improving sludge dewaterability (Smith and Vesilind, 1995), owing to the close

linkage of bound water with sludge rheological properties, particularly enhancing the sludge viscosity

(Forster, 1983). Viscosity is often used as an indicator of compressibility of sludge, which influences

the sludge dewaterability (Li and Yang, 2007). Also, studies showed the influence of bound water

content (BWC) on the sludge filtration characteristics (sludge filterability) (Forster, 2002; Katsiris

and Kouzeli-Katsiri, 1987). Robinson (1989) showed the positive impact of bound water reduction

on the improvement of sludge dewaterability (i.e. increased cake solids concentration). Likewise, a

number of recent studies have reported the positive influence of decreased BWC on sludge

dewaterability as bound water is intricately associated with the sludge flocs structures including EPS

compositions (He et al., 2017; Kwon et al., 2004; Liang et al., 2015; Tony et al., 2008; Yu et al.,

2016; Yuan et al., 2017; Zhang et al., 2014). These studies employed various chemical treatment

approaches that incorporate the addition of red mud, polymer, acid/alkali, including advanced

oxidization conditioning process. However, the impact of Fe-salt dosing on changing the contents of

the abovementioned different water fractions in the sludge remains to be elucidated.

Sludge morphology

Sludge suspensions are colloidal and supracolloidal system (Prodănescu, 2017), and hence sludge

morphology such as particle/floc size or particle size distribution (PSD) also plays important role in

sludge settleability (Li and Stenstrom, 2018) and dewaterability as the morphological properties also

influence the sludge viscosity (Pham et al., 2010). It has been reported that an increase in sludge

particles/flocs size causes the reduction in surface shear stresses encountered during dewatering

process, thereby reducing the specific cake resistance (Herwijn, 1996). Besides, increased particle

size is reported to reduce the area of exposed sludge particle surface and also the hydrophilicity of

sludge flocs, thereby causing improvement in dewaterability (Zhen et al., 2012). The beneficial

impact of larger sludge flocs on sludge dewatering is also noted by (Dai et al., 2018). In terms of

PSD, the higher supracolloidal particle size fractions (1-100 m) are reported to have a negative

impact on sludge dewaterability (Higgins and Novak, 1997a; Karr and Keinath, 1978). This is

attributed to ability of supracolloidal solids to cause clogging of filter or cake medium and hence

hinders the sludge filterability (i.e. specific resistance to filtration, SRF) (Karr and Keinath, 1978;

Yin et al., 2004). Secondly, the presence of predominant large particles/flocs can consequently ease

bound water release. A higher proportion of small particles enhances the surface area of sludge flocs

and hence, increases bound water quantity as bound water is directly linked with sludge particles

24

surface (Bougrier et al., 2006). Likewise, change in settleable size fractions may influence the

settleability of sludge (Jin et al., 2003; Wilén et al., 2003).

Akin to this, fractal dimension (Df) which reflects the structural properties (degree of compactness)

of sludge aggregates, has also been reported to influence the sludge dewaterability (Zhang et al., 2018;

Zhao et al., 2013). This is because particle size and Df influence sludge porosity, density, and

permeability (Zhao et al., 2013). The higher the Df, the more compact is the sludge (Hermawan et al.,

2004) and the stronger is sludge elasticity (Zhang et al., 2018). Sludge flocs characterized by a more

compact structure (high Df value) may lead to the expansion of particle suspension surfaces, creating

spatial structures. Consequently, this might increase the water content in sludge which in turn may

deteriorate sludge settling properties (Kuśnierz and Wiercik, 2016). Regarding the influence of sludge

floc structure on sludge dewaterability, Turchiuli and Fargues (2004) reported a decrease in sludge

bound water content with a lower Df value, i.e. less compact flocs (lower Df values) contain more

water but less bound water, resulting in better sludge dewaterability (Kopp and Dichtl, 2001).

It is now clear that sludge morphology also plays an important role in sludge settleability and

dewaterability. In retrospect, studies investigating the influence of Fe-salt dosing on sludge

morphological properties are limited. If available, it is only for direct Fe-salt addition to bioreactor or

sludge conditioning with direct Fe-salt addition (Li 2005; Niu et al., 2013; Oikonomidis et al., 2010).

Hence, this entails a better understanding of these aspects and resultant implication on sludge

settleability and dewaterability concerning the influence of sewer-dosed Fe-salt dosing.

Sludge rheology

Sewage sludge is a non-Newtonian fluid, that exhibits rheological characteristics, such as shear-

thinning, thixotropic, yielding, and viscoelastic properties (Eshtiaghi et al., 2013b; Liu et al., 2016c;

Seyssiecq et al., 2003). In this notion, sludge rheology deals with the description of the internal sludge

molecular structure including prediction and quantification of sludge flowability (Dentel et al., 2005).

Hence, sludge rheology influences the hydrodynamic processes involved in sludge handling

(Ratkovich et al., 2013), which in turn may influence the sludge dewaterability. The understanding

of sludge rheology, therefore, facilitates the assessment of sludge stabilization or dewaterability and

the selection of design parameters concerning sludge storage, handling/transportation, including

sludge pumping and mixing (Eshtiaghi et al., 2013a; Eshtiaghi et al., 2013b; Lotito et al., 1997). For

instance, sludge viscosity, one of the key rheological properties, is reported to impact oxygen mass

25

transfer to flocculated biomass in an aeration tank (Hasar et al., 2004) and also influence the sludge

dewaterability (Li and Yang, 2007). Likewise, relative sludge network strength and yield stress (y)

are other important rheological parameters, associated with sludge dewaterability (Örmeci and Abu-

Orf, 2005). This is because effective dewatering relies on the strength of sludge aggregates. Lower is

the value of sludge network strength, smaller would be the deformation resistance against the applied

shear stress and vice-versa. Reduced deformation resistance promotes the release of incorporated

water within the sludge aggregates (Ormeci et al., 2004; Yen et al., 2002). Similarly, the reducedy

value implies a reduction in sludge viscosity as all three bound water, viscosity, and y of activated

sludge are strongly inter-related, as previously documented by Forster (2002). Albeit the sludge

rheology is likely to influence both the sludge settling and dewatering performances, understanding

the impacts of Fe-salt addition on different sludge rheological properties (e.g. time- and load-

dependent properties, sludge viscoelasticity) is also surprisingly rudimentary. If available, it is only

for the influence of direct Fe-salt addition on sludge viscosity (Wei et al., 2018).

1.5 Knowledge gaps and research questions

Some important knowledge gaps are identified based on the literature review and accordingly

associated research questions were formulated, which are outlined below:

(i) What are the factors likely influencing the transformation and transport of sewer-dosed

iron in the urban wastewater systems?

Direct dosing of Fe-salts for sulfide abatement in sewer networks is a common practice, providing

protection against sulfide-induced sewer corrosion and odor problems (Nielsen et al., 2005b).

However, a sewer system and a downstream WWTP are connected entities in the urban wastewater

system (UWWS) and any intervention to sewer will have impacts on the operation and performance

of the WWTP. As a result, the Fe dosed into the sewer networks will be transported into the

downstream WWTP although in different forms, potentially assisting in P removal (Gutierrez et al.,

2010), desulfurization of digester biogas (Ge et al., 2013), and control of struvite/vivianite scale

formation in AD systems (Frossard et al., 1997; Mamais et al., 1994b). Few studies have demonstrated

the feasibility of such multiple re-uses of Fe-salt (Zhang et al., 2011) and waterworks Fe-sludge

(Edwards et al., 1997) within the UWWS and derivation of above-stated benefits. Consequently, new

insights have emerged on the use of Fe to derive multiple benefits across the UWWS by reducing

chemical use, which is a win-win solution from both the economic and environmental standpoints.

One of the key factors that influence the secondary benefit of sewer-dosed Fe to downstream WWTP

26

is the settling of Fe along with the associated solids in sewer and the primary settling tank (PST). The

transformations of Fe between ferrous and ferric form, the formation, dissolution, and reactivity of

Fe mineral precipitates, and settling behavior of Fe-precipitates are expected to influence the carry-

over of Fe and its efficacy in such multiple-uses applications. Earlier, it has been suggested that

adopting different sewer dosing locations of Fe-salts will alter in-sewer retention time, and

accordingly, this may influence Fe particle growth, Fe-fractionation (liquid bulk phase versus settled

particulate phase) and separation efficiency. For this, Gutierrez et al. (2010) used experimental

conditions simulating in-sewer exposure of Fe to anaerobic conditions in the presence of excess

sulfide. The mixing period was varied to simulate different in-sewer retention times for Fe during

transport in sewers. Their study suggested that dosing location (which influences in-sewer retention

time) could have an impact on settling performance in a downstream PST. Further, it was suggested

that an end-of-pipe sewer dosing location may not provide enough time for sufficiently large

precipitates to grow to settle out in a PST (Gutierrez et al., 2010). In-sewer oxic-to-anaerobic

transition conditions as typically found in the segments of sewer (Vollertsen et al., 2008) may impact

the transformation and transport of Fe in sewers, which was not explored by Gutierrez et al. (2010).

In addition, the dosing of Fe-rich sludge and corresponding transformation and transport of Fe in

sewers has not been investigated. This necessitates an examination of the hypotheses of Gutierrez et

al. (2010) concerning the effect of Fe-salt dosing location on downstream settling in a PST via both

carefully designed laboratory mixing-reaction-settling tests and a full-scale monitoring study. This is

because when considering dosing Fe-salts in sewers for integrated sewer-WWTP operation, Fe-

transformation/fractionation occurring in the sewer environment including the extent of Fe-transport

from the sewer to downstream WWTP plays a determinant role. The current understanding of

different key factors potentially affecting such Fe-transformation and Fe-transport to activated sludge

system of WWTP is inadequate. In this context, unraveling the influences of in-sewer

retention/reaction time and oxidative/reductive conditions on the Fe-transformation/transport and

also comparing the thus observed behavior for Fe-rich sludge and Fe-salt would provide valuable

knowledge considering the recent growing interest for Fe-salt/Fe-sludge multiple uses in UWWS.

(ii) What are the likely influences of Fe-salt dosing to sewer on activated sludge properties with

implications on settleability and dewaterability during integrated sewer-WWTP operation?

When considering the Fe-salt multiple uses in integrated sewer-WWTP operation, Fe-salt used in

sewers for sulfide control could have far-reaching benefits in terms of phosphorus removal in

bioreactors and sulfide control in the digester (Edwards et al., 1997; Ge et al., 2013; Gutierrez et al.,

27

2010). In an integrated system-wide operation, Fe-salt added to sewers controls sulfide through

precipitation. The precipitated-iron, which later undergoes chemical changes in the bioreactor and

becomes available for phosphate precipitation, may also interact with the activated sludge affecting

its properties including settleability and dewaterability. Both settleability and dewaterability are the

key parameters for WWTP operation and improvement in these parameters could influence not only

the bioreactor operation but also overall WWTP operation and sludge management. Effluent quality

of WWTP is largely dependent on the good settleability of activated sludge (Wilén et al., 2010).

Likewise, better sludge dewaterability reduces sludge volume and hence eases the heavy economic

burden of sludge management (Li et al., 2016). Dewatering of activated sludge would be particularly

important in a case where activated sludge systems produce surplus sludge which has to be dewatered

before disposal without going through sludge digestion (Brix, 2017; Park et al., 2006). In retrospect,

the impacts of sewer-dosed Fe-salt on key activated sludge properties (physicochemical,

morphological, rheological) affecting the settleability and the associated mechanism leading to such

improvement has not been fully understood. Similarly, possible alteration to dewaterability of

activated sludge is not well understood and factors responsible for the alteration are not clear. When

aiming to achieve multi-stage beneficial uses of Fe-salt dosing in an integrated UWWS, clear

understanding of the flowing on impacts of Fe dosed to the sewer on both settling and dewatering

properties of activated sludge including the associated underlying possible mechanism can be

significant in terms of wastewater treatment and sludge management. However, none of the studies

to date have reported the unintended beneficial consequences in terms of both activated sludge

settleability and dewaterability upon treating the Fe containing sewer effluents in a bioreactor. It is

worth highlighting here that the Fe dosed to sewers undergoes transformation under different

prevalent redox conditions, and its reactivity in an aerobic treatment and interaction with sludge

particles could be different from that of freshly added Fe-salt.

Thus, it entails the investigation of the changes in key activated sludge properties due to sewer-dosed

Fe-salt and subsequent impacts on settleability and dewaterability of activated sludge. Specifically,

this necessitates in understanding (i) impacts of Fe-salt addition to a sewer location upstream of the

activated sludge unit in both dewatering and settling performances of activated sludge and (ii) impacts

on other activated sludge properties and identify the possible mechanisms responsible for the changes

in sludge dewaterability and settleability. Developing an understanding of key parameters affecting

sludge characteristics in relation to in-sewer Fe-salt dosing would help in elucidating the mechanism

of synergy between the changes in these key sludge properties for improving settleability and

dewaterability, including examining the impacts of in-sewer Fe-salt dosing in a holistic manner.

28

(iii) What are the likely influences of sewer-dosed Fe-salt on anaerobically digested sludge (or

digestate) properties with implications on dewaterability during integrated sewer-WWTP

operation?

Recent few studies have shown the efficacy of direct Fe-salt addition to AD in improving the digestate

dewaterability (Akgul et al., 2017; Novak and Park, 2010). However, the possible impact of indirect

(upstream in-sewer dosing) dosage of Fe-salt on altering the dewaterability of digestate during

integrated sewer-WWTP operation is still not well understood and possible mechanisms leading to

such improvement have not been studied. In contrast to direct Fe dosing, the nature of the implications

of Fe that is carried over to the AD from upstream sewer is likely to be different when in-sewer dosing

is employed. When Fe-salt is added in an upstream anaerobic sewer reactor, Fe precipitates with

sulfides as iron sulfide (FeSX) under the septic condition and subsequently again precipitates with

phosphate ions upon reaching aeration tank thereby forming insoluble ferric-hydroxy‐phosphate

FeXPO4(OH)x complexes (Ge et al., 2013). Waste activated sludge (WAS) containing these

precipitates may undergo additional chemical transformations in the AD unit (Ge et al., 2013;

Rebosura et al., 2018). The Fe present in FeXPO4(OH)x complexes will be reduced and will react with

sulfides or phosphate in AD. The occurrence of such chemical interactions/transformations including

the release of sulfides from volatile solids destruction in digester and its subsequent precipitation

could exhibit some impacts on the key digestate properties, which have not been reported yet.

To evaluate the impacts of sewer-based Fe-salt dosing to digestate properties, it becomes necessary

to investigate changes such dosing approach brings to the key physicochemical, morphological,

fractal, and rheological properties of digestate linked directly or indirectly to its dewaterability. Such

information would be equally crucial when considering the recent paradigm shift in terms of chemical

usage (e.g. Fe-salt) in the integrated operation of sewer-WWTP, as this would provide a better

understanding of the system-wide impacts and facilitate the proper evaluation of the option. Such

investigation will allow to reveal combined synergistic roles of the key sludge properties on the

possible enhancement of the digestate dewaterability.

29

(iv) What are the possible impacts of reusing Fe- or Al-rich waterworks sludge in sewers as

compared to their chemical counterparts?

The Fe-salts are commonly used for controlling sulfide in sewers (Ganigue et al., 2011b). However,

effective sulfide control demands continuous Fe-salt dosing, which incurs high operational costs.

Similar is the case with the use of chemicals in wastewater treatment. It has been reported that the

global cost of inorganic coagulants used for water/wastewater treatment in 2018 was $1.37 billion,

and this is predicted to reach $1.84 billion by 2023 (BCC-Research, 2018). Considering such an

enormous cost associated with chemical dosing, seeking low costs alternatives is a major imperative.

In this context, the cost-effective reuse of materials, that are otherwise considered as wastes, such as

waterworks Al- or Fe-rich sludge (denoted as ‘Al- or Fe-sludge’ hereafter) as the alternatives to their

chemical counterparts (Al-, Fe-salts), could be an appealing solution for both sulfide and phosphorus

removal in sewers including sustainable management of WTP sludge. This is because a study has

reported that the average production of WTP sludge globally exceeds 3.65106 dry tonnes per annum

(Babatunde and Zhao, 2007). In Australia, annual production of WTP sludge by a water utility is

reported to vary between 150 to 43,500 dry tonnes per annum (Dassanayake et al., 2015; GHD, 2015).

The production of WTP sludge is expected to increase over the years, considering the growing

demand for potable water by a rapidly increasing global population, thereby significantly increasing

the costs of sludge transportation and disposal.

Of the various disposal options employed for WTP sludge (GHD, 2015; Verrelli, 2008b), the

particular interest herein is reusing the WTP sludge to sewers. This would allow the direct disposal

of WTP sludge to sewers. Considering the high Fe or Al concentration in WTP sludge (depending on

whether Fe-salt or alum is used as a coagulant), it can potentially be reused for sulfide and phosphate

removal in sewers. In retrospect, there have been no comprehensive studies to date on the application

of waterworks Al- and Fe-sludge to sewers at pilot- or full-scale and their respective roles in sulfide

and phosphate removal. In addition, the impacts on other sewage characteristics, such as particulate

pollutants, dissolved methane (CH4), and nitrous oxide (N2O), are not fully understood. It is believed

that successful reuse of Al- and Fe-sludge instead of chemical coagulants would have a major impact

on both sustainable WTP sludge management and urban wastewater management. Undoubtedly,

reuse of waterworks sludge will deliver both economic and environmental benefits for water utilities,

by reducing the burden of WTP sludge treatment/disposal and reducing chemical consumption in the

urban water system.

30

1.6 Thesis outline

This thesis is organized into eight chapters. Chapter 1 incorporates an introduction providing a

background of the study including the thesis outline and presents a detailed and critical literature

review of the topic, based on which the overall research objectives of this thesis were formulated.

Chapter 2 highlights the specific knowledge gaps and identifies the key research objectives. Chapter

3 describes the methods and materials (or experimental procedures) used in this research work.

Chapters 4 to 7 are the major result chapters and accordingly present the research outcomes of the

designated research objectives. Specifically, Chapter 4 presents the mechanistic understanding of the

key factors that influence the transformation and transport of sewer-dosed Fe in an urban wastewater

system (e.g. sewer system, downstream WWTP). Chapter 5 examines the impact of sewer-dosed Fe-

salt on settleability and dewaterability of activated sludge and also sheds light on the mechanistic

overview of different possible causative factors behind the observed changes in settleability and

dewaterability. Chapter 6 presents the positive impact of in-sewer Fe-salt dosing on improving the

dewaterability of digestate and also sheds light on the mechanism of synergy between the changes in

key digestate properties that result in the contrasting dewaterability between unconditioned and iron-

conditioned digestate. Chapter 7 comprehensively evaluates the effects of direct dosing of waterworks

Fe-/Al-sludge on different sewage characteristics in pilot-scale sewer rising mains, particularly

focusing on removal of dissolved sulfides and phosphate including associated possible underlying

mechanisms behind the observed such removal. Likewise, Chapter 8 concludes the main

achievements of this thesis and gives recommendations for future research.

31

Chapter 2

Research objectives

This chapter presents the research objectives of the thesis.

The Fe-salts are widely used for water and wastewater treatment. However, Fe-salt usage has been

in isolation without considering the ‘big picture’ approach which assesses the effects and benefits

as Fe travels through the urban wastewater system (UWWS) (see Section 1.2). Hence, the overall

aim of this PhD thesis is to investigate the potential, but unintended beneficial aspects of sewer-

dosed Fe-salts during integrated sewer-WWTP operation, especially in relation to sludge properties

for both bioreactor and anaerobic digester. These impacts heavily depend upon the transport of Fe

from the sewer to the downstream wastewater treatment units and Fe-transformation/fractionation

(e.g. Fe mineral precipitates formation and their transport, settling, dissolution and reactivity with

sulfide or phosphate) likely occurring in sewer environment. These phenomena are likely affected

by several different factors including prevailing in-sewer redox conditions, in-sewer retention time,

Fe-source type, etc. Concomitantly, this study also extends to the understanding of precipitate

particle size distribution (PSD), settling, and retention of Fe-precipitates in the sewer that is likely

to influence of transport of Fe across the UWWS. Combined, this implies for integrated system-

wide Fe usage in UWWS, the transformation and transport of sewer-dosed Fe are important,

including in sewers and the downstream WWTP. Once the sewer effluent laden with Fe-precipitate

(resultant of sewer-dosed Fe-salt) is carried over into the activated sludge unit and subsequently to

anaerobic sludge digestion unit, the underlying chemical Fe-P-S interactions (see Section 1.2.4)

occurring during wastewater treatment and sludge digestion processes may potentially impact the

key properties of both activated sludge and digestate with implications on settleability and

dewaterability. Hence, this PhD thesis aims to underpin the different key factors that influence the

Fe-transformation/fractionation and Fe transport across the UWWS. Secondly, this PhD thesis aims

to unravel the influences of sewer-dosed Fe-salt on key sludge properties of bioreactor and digester

with implications on their settling and dewatering performances. Besides, this PhD thesis also aims

to investigate the potential for reusing waterworks sludge (Al- or Fe-sludge) instead of chemical

coagulants such as Al- or Fe-salts in pilot sewers to understand the unintended benefits of

transporting WTP sludge in a sewer pipe, which might provide a cost-effective alternative to

32

chemical dosing. In other words, this study also aims to comprehensively investigate the immediate

impacts of in-sewer Al- or Fe-dosing in the forms of Al- or Fe-sludge under a more realistic sewer

condition. Considering a paradigm shift in terms of use of Fe-salts and waterworks sludge in the

sewer to derive multiple benefits across various components of an integrated UWWS system in

recent years, this work should be of significant value to the water industry.

Hence, the following specific objectives are being addressed herein:

• Research objective 1 (RO-1): Elucidating the major factors influencing the transport and

reactivity of sewer-dosed iron in the urban wastewater systems

• Research objective 2 (RO-2): Unravelling the influences of sewer-dosed iron(Fe)-salts on

activated sludge properties with implications on settleability and dewaterability

• Research objective 3 (RO-3): Understanding the influence of sewer-dosed iron(Fe)-salts on

anaerobically digested sludge properties with implications on improving dewaterability

• Research objective 4 (RO-4): Evaluating the effects of dosing iron- and aluminium-

containing waterworks sludge on sulfide and phosphate removal in a pilot sewer

The aforementioned research objectives were achieved by conducting a number of lab-, pilot-, and

full-scale studies. Lab-scale studies culminated the different bench-scale experiments including the

continuous operation of two integrated sewer-WWTP laboratory systems (control and

experimental). Each system comprised of two anaerobic sewer reactors, a sequencing batch reactor

for biological wastewater treatment, a gravity sludge thickener, and an anaerobic sludge digester.

Similarly, the pilot-scale studies were carried out on two rising main sewers (one control and one

experimental) of a size (300m long and 100 mm in diameter) comparable to a small real sewer.

Besides, full-scale studies were conducted in a real life sewer network (catchments of a receiving

WWTP) and a WWTP.

33

Chapter 3

Materials and methods

This chapter incorporates the general research approaches and methodologies used in addressing the

research objectives in this thesis. General materials and methods are described here, while the

research approaches/methods pertinent to a specific research objective are shown in the ‘materials

and methods’ section of the specific results chapter.

3.1 Overview of integrated laboratory set up and operation

Sludge samples were collected from an integrated laboratory system consisting of two separate lines,

one experimental and another a control line. Each system incorporated a rising main reactor, a

sequencing batch reactor (SBR), a gravity thickener, and an AD reactor (see Figure 7) connected in

series mimicking an integrated urban wastewater system. Both experimental and control lines

consist of two continuously stirred anaerobic sewer reactors, connected in series. Each sewer

reactors were made of acrylic polyvinyl chloride (PVC) sheeting (volume = 0.75 L, internal diameter

= 0.08 m) and completely covered with aluminium foil to prevent exposure of sewage and biofilm

to light during operation. Each sewer reactor lid was also equipped with a small external container

filled with the same wastewater as inside the reactor, which would facilitate in preventing air entry

inside reactor during wastewater displacement (following each pumping events). The sewer reactor

was operated with four equally spaced pumping events in a day and was fed 10 L of domestic sewage

per day, i.e. 2.5 L sewage every 6.0 hr. Each pumping event lasted for 5-10 minutes at the beginning

of each 6 hr cycle. The sewer reactors were kept anaerobic and constantly mixed with magnetic

stirrers. Domestic sewage (or wastewater) used herein was collected weekly from a pumping station

serviced via gravity main located in Indoroophilly, Brisbane. Sewage was stored in a cold room at

4C to minimize the likely biological transformation. However, the wastewater was heated to

22±1 °C using a heating coil before feeding to the anaerobic sewer reactors. The characteristics of

the sewer reactor feed are provided in Chapter 5. The sewer reactor of the experimental line was

intermittently fed with 11 mL of FeCl3 stock solution (only during pumping events) to give a

theoretical concentration of 10 mg.Fe.L-1 of wastewater. This dosing rate was chosen on the

assessment in a previous study (Ganigue et al., 2011b). A stock solution was prepared using iron-

34

chloride hexahydrate (FeCl3.6H2O) of 97% assay (Sigma-Aldrich, Merck, Germany). Sewer effluent

was pumped into a buffer tank with the retention time of 5 min, before being fed to an experimental

SBR for treatment. Average dissolved sulfide concentrations in sewer effluent of the experimental

(with Fe dosing) and control (without Fe dosing) lines were 4.30.3 mg.S.L-1 and 8.20.3 mg.S.L-1,

respectively. Likewise, the soluble Fe(aq) concentrations in sewer effluent of the experimental and

the control lines were 1.00.3 mg.Fe.L-1 and 0.10.0 mg.Fe.L-1, respectively. Further information

regarding the influent compositions of both experimental and control SBR reactors is provided in

Chapter 5.

Each SBR reactor was operated with a cycle time of 6.0 hr comprising of 2.0 hr anoxic mixing, 3.0 hr

aerobic mixing, 45 min settling, and 4 min decanting periods. The mixing in the anoxic and aerobic

periods was done using an overhead stirrer (LabCo, 20 L stirrer). The dissolved oxygen (DO) in

each SBR reactors was maintained between 1.5 to 3.5 mg.O2.L-1 with an aid of on-off switch valve

controlled by a programmable logic controller (PLC), and air supplied from air compressors via

stone diffusers (EcoPlus cylinder air stone). The total working volume of each SBR reactor was

8.5 L, which was made from acrylic PVC material (height = 0.7 m, internal diameter = 0.16 m).

During each SBR cycle, 2.5 L of wastewater was pumped to each SBR from the respective buffer

tanks (which accumulated the sewer effluents) during the first 8 min of the anoxic phase. The SBR

was operated with solids retention time (SRT) of 16 days, with 0.125 L of activated sludge removed

during the last 5 min of the aerobic phase during each cycle of operation, and pumped to the gravity

thickener. Likewise, pH was measured online using an INPRO 3250I probe with M400 transmitter,

and dissolved oxygen (DO) was measured with an INPRO 6860I probe connected to an M200

transmitter, with data logged by a program logic controller (PLC). DO concentration in the SBR

reactor was maintained between 1.5 and 3.5 mg.O2.L-1 with an on-off switch valve controlled by the

PLC, and air supplied from compressors through stone diffusers.

The gravity sludge thickener, made of acrylic material with the total volume of 3.0 L, concentrated

the sludge prior it was fed to the AD reactor. The thickener was intermittently stirred using a custom-

made stirrer at 2 rpm to generate the thickened sludge. The volume of 50 mL waste activated sludge

(WAS) was collected and then pumped to the gravity sludge thickener, before being fed to AD

reactor with the feed cycles adopted to continuously operate all these reactors in an integrated

manner. The AD reactor every day received 50 mL of WAS after thickening, with the same volume

of digested sludge discharged from the reactor simultaneously. A water trap was connected between

35

the gas outlet and a gas counter to prevent any negative pressure build-up inside the reactor during

sludge feeding and wasting. Total iron Fe(T) concentrations of mixed liquor in experimental SBR

was 228.8±22.0 mg.Fe.L−1. AD reactors were continuously stirred by magnetic stirrer (MIXdrive 1

eco) and operated with hydraulic retention time (HRT) of 20 days under mesophilic condition (37°C)

using a water bath. The AD reactors were jacketed glass reactor with the total volume of 1.3 L (1.0

L working volume and 0.3 L reactor headspace). A water trap was connected between the gas outlet

and a gas counter to prevent any negative pressure build-up inside AD during sludge feeding and

wasting. Likewise, Fe(T) concentrations in the digested sludges of AD-E and AD-C reactors were

777.3±69.0 mg.Fe.L−1 and 78.4±5.0 mg.Fe.L−1, respectively. Besides, online monitoring of

temperature, pH, and DO in each line was monitored using an optical probe (Metler-Toledo), and

logged by a PLC.

Figure 7. (a) Schematic representation of the integrated laboratory reactor system. Here, only

experimental line is depicted wherein the control line is identical but without the Fe-salt dosing unit.

(b) pictorial representation showcasing the real set-up of integrated laboratory system

3.2 Overview of pilot-scale rising main set up and operation

The pilot sewer study was conducted in rising main (RM) sewers, located at the Luggage Point

WWTP, Pinkenba, Queensland, Australia. Each of the two RM pipes has an internal diameter of 0.1

m (A/V = 4.0/0.1 m = 40 m−1) and a length of 300 m (Figure 8). One of the sewer pipes was operated

as a ‘control’ and the other as an ‘experimental’ line during the waterworks sludge dosing. These

pilot sewers were supplied with wastewater, directed from the inlet of the Luggage Point WWTP to

a storage tank (Tank 1) located adjacent to the pilot sewer systems (Figure 9). Three sampling ports

were installed in both the sewer lines at the locations of 15 m, 105 m, and 210 m for manual sampling.

36

The wastewater was pumped into the RM systems using a SHE50-16075 centrifugal 3-phase pump

(7.5 Kilowatt, Lowara Pumps, Australia). During a pumping event, the flow rate was maintained at

275 L.min−1, which corresponds to an in-pipe liquid velocity of 0.6 m.s−1. The in-pipe velocity was

chosen since it is considered sufficient to achieve self-cleaning of the pipes but was low enough to

avoid biofilm shearing at the bends. The flow rate was controlled using a flow sensor and PID control

algorithm (National Instruments, Texas). The pumping pattern consisted of a 2 min pumping event

every 60 min interval. The pump was equipped with a Hydrovar variable frequency drive for flow

control to maintain the designed flow rate and was fitted with an inline magnetic resonance flow

meter (IFM SM2000). As shown in Figure 8, the pilot RM sewer system incorporates the 10 levels

of pipes, which were placed at the vertical intervals of 300 mm. During the operation, the influent

wastewater first enters the bottom-placed pipes and then travels up gradient reaching the last level of

pipe at the top. Once it reaches the top section of the pipe, wastewater flows through a downspout

connected to an effluent waste tank (not shown here). The downspout was designed to allow

wastewater to drain out of the final rising main pipe at the topmost location. Hence, only 270 m

sections of each pipe line can be considered fully filled in which complete septic condition could be

maintained; wherein the last 30 m of the pipe section remains partly full most of the time. Thus, only

240 m of each RM sewer pipe was utilized for experimental studies to avoid any complications that

may arise from the development of any headspace.

Figure 8. Rising main pilot system at innovation centre of Luggage Point WWTP

37

Figure 9. Schematic of the pilot rising main with an internal diameter of 100 mm and a length of 300

m. The experimental line is shown here. The control line was identical but without the sludge dosing

mechanism. Temperature and pH were monitored online by pumping sewage out in a pipe loop at 45

m then returning it at 75 m using Masterflex Peristaltic Pumps (Cole-Parmer, USA) maintaining the

flow rate at 3400 mL.min-1

3.3 Overview of Luggage Point WWTP and full-scale tests

The full-scale tests were undertaken in the Luggage Point WWTP and the upstream feeder sewers.

During the test, FeCl2 (30% concentration, IXOM, Melbourne, Australia) was dosed to a branch sewer

located at 18 km upstream of the Luggage Point WWTP and also at the inlet works of the LP WWTP

(Figure 10). The typical average dry weather flow for the WWTP is 131.0 ML.day-1. The LP WWTP

has been designed with a treatment capacity of 900,000 population equivalent, treating about 60% of

domestic wastewater originating from Brisbane. The wastewater from different sewer catchments is

collected at the Eagle Farm pumping station and then pumped through a 9.5 km long RM sewer to

the inlet of Luggage Point WWTP (Figure 11). The primary treatment in Luggage Point WWTP

includes a grit chamber followed by a primary settling tank (PST), with an average dry weather

retention time of 5.0 hr. After the primary treatment, the wastewater is mixed with return activated

sludge (RAS) at 1:1 mixing ratio and the mixed flow passes onto the biological treatment process,

38

which is a tank-in-series activated sludge system. The treatment plant has been designed for nitrogen

removal from wastewater (nitrification/denitrification). However, this treatment plant is not designed

for biological phosphorus (bio-P) removal. The mixed liquor from the bioreactor is then pumped to

the secondary settling tank. After settling, a portion of the effluent from the treatment plant is

subjected to advanced treatment such as ultrafiltration (UF)/reverse osmosis (RO) before being

utilized for the non-potable reuse, and the remaining effluent portion is discharged to the Moreton

Bay, Australia. Part of the settled sludge is returned to the bioreactor as the RAS, while the rest goes

to the digestion in AD. The primary sludge and WAS are treated by a thickener and dissolved air

floatation (DAF) process for thickening. The thickened sludge is subjected to digestion in AD for

energy recovery as biogas. The biogas thus generated is fed to a co-gen unit to produce electricity for

internal usage. The digestate is stored in a storage digester and then dewatered using a centrifuge.

The centrate and other plant drains are circulated back to the inlet of the treatment plant.

Figure 10. Simplified diagram showcasing the upstream sewer network and inlet of Luggage Point

WWTP where FeCl2 dosing was trialed. Here, two dosing trials (as highlighted) were conducted

independently, i.e. inlet dosing trial was first trialed followed by the upstream sewer dosing trial

39

Figure 11. Simplified process flow diagram of Luggage point WWTP with sampling points (yellow

circled) around the PST pertinent to inlet FeCl2 dosing trial

3.4 Dewaterability and settleability tests

Sludge dewaterability was measured using a method described in previous studies (Chen et al., 2001;

Devlin et al., 2011), albeit with some modifications. Sludge samples were centrifuged with a constant

mixing intensity and centrifugation time, i.e., 1757 × g for 10 min. The separated liquid was discarded

and settled sewage solids were manually mixed with the cationic polymer (0.005 g polymer/g sludge)

for 2 min. After this, the sludge was drained through a belt filter fabric and the solids cake was

centrifuged in a centrifuge cup with the modified stand containing belt filter fabric for 10 min using

AllegraTM X-12 Beckman Coulter Centrifuge (Figure 12). The supernatant was removed and the

dewatered cake solids content (%) was determined. Besides, the lab-scale modified centrifugal index

method, previously reported by Higgins et al. (2014), was used in evaluating the sludge dewaterability

in terms of sludge cake solids content (%).

Sludge settleability was measured in terms of sludge volume index (SVI) by conducting the

measurements as outlined in standard methods (APHA, 2005) using the following Eq. (4):

30

TSS

SVI=SVX

(4)

where, XTSS is the measured TSS concentration of the sludge samples in g.L-1; SV30 is the volume

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occupied by the sludge in the graduated measuring cylinder (mL.L-1) after 30 min of settling

Figure 12. Modified centrifuge stand used for centrifugation for dewaterability analysis: (a) belt filter

fabric; (b) modified stand holding the belt filter fabric

3.5 EPS fraction extraction and analysis

A modified heating extraction method was adopted for the extraction of different EPS fractions, as

outlined in previous studies (Li and Yang, 2007). The only modification made herein was the use of

different value of gravitational acceleration for the Benchtop Beckman Coulter, Allegra X-12

centrifuge, i.e. relative centrifugal force (RCF) value of 3267 gravitational acceleration (g). The

EPS was characterized into different fractions namely soluble (S-EPS), loosely-bound (LB-EPS), and

tightly-bound (TB-EPS). All the extracted EPS fractions were quantified in terms of total organic

carbon TOC content (mg.g-1.VSS-1), measured using a TOC analyzer (TOC-5000A, Shimadzu,

Japan).

Cations distributions including their relative concentrations in the different extracted EPS fractions

were evaluated in terms of M+/D++ cation ratio. Concentrations of major cations of interest (K+, Na+,

Mg2+, Ca2+, Al3+, and Fe3+) in extracted EPS fractions of the sludges were measured using an

inductively coupled plasma-optical emission spectrometer (ICP-OES) (Perkin Elmer Optima

7300DV, Waltham, MA, USA) after 70% nitric acid digestion. The M+/D++ ratio was calculated as

the sum of the concentrations of monovalent cations (Na+, K+) divided by the sum of the

41

concentrations of divalent cations (Mg2+, Ca2+), with all concentrations expressed as milliequivalents

per liter (mEq.L-1). Further details of M+/D++ estimation can be found in previous studies (Higgins et

al., 2004; Peeters et al., 2011; Rus et al., 2017).

3.6 Compositional analysis of extracted EPS fractions

Fluorescence excitation-emission matrix (F-EEM) spectral analyses were conducted to investigate

changes in the organic composition of extracted EPS fractions of the sludges, primarily focusing on

the changes in the contents of fluorescing substances (e.g. aromatic tyrosine protein-like, aromatic

trypotophan protein-like, humic acid (HA)-like, soluble microbial product (SMP)-like, and fulvic acid

(FA)-like). For this, fluorescence measurements of different EPS fractions were performed using a

PerkinElmer LS-55 luminescence spectrometer (PerkinElmer, Australia), based on

Winlab® software. Fluorescence intensity (FI) was recorded under the excitation wavelengths varying

from 200 nm to 400 nm with 5 nm interval, and the emission wavelengths varying between 280 nm

and 500 nm with 0.5 nm interval, generating an excitation-emission matrix. A 290 nm cut-off was

used to limit the second-order diffraction (Rayleigh scattering) to reduce the noises in excitation- and

emission-spectra. Excitation and emission scan slits were set at 7 nm, while the scan speed was set at

1200 nm/min and the photomultiplier voltage was set in automatic mode. Sludge samples were

equilibrated to ambient lab room temperature prior analysis to minimize the temperature effect.

Sludge samples were diluted 20 times with Milli-Q water to avoid the inner filter effect (absorption

of photons either incident or emitted light by the sample) by maintaining A230 < 0.05 (Larsson et al.,

2007). Fluorescence regional integration (FRI) values, which were used to quantify spectra for

different organic components observed in EPS fractions, were based on Chen et al. (2003b).

The sludge EPS content was also quantified by measuring the concentrations of proteins (PN) and

polysaccharides (PS) in the extractants. Calibration curves employed for the quantitation of both PN

and PS contents are given in Figure 13. The bulk concentration of PS and PS content in sludge EPS

fractions was measured based on the colorimetric anthrone method as outlined in Le and Stuckey

(2016) after some modifications. Anthrone-sulfuric acid reagent (0.2% anthrone in conc. H2SO4) was

prepared prior to analysis. During the analysis, 0.5 mL of samples or glucose standards were added

into 2.0 mL microcentrifuge tubes, followed by 1.0 mL of anthrone reagent with caution. The tubes

were capped immediately and vortexed briefly prior to being incubated into a water bath at 80C for

30 min. After this, the samples were first cooled for 10-12 min at ambient room temperature and then

quickly transferred in a UV quartz cuvette (Thomas Scientific) for absorbance measurement at 625

42

nm (Synergy HT, BioTek, Winooski, VT). The linear range of measurement was 5-250 mg.glucose.L-

1. Similarly, PN contents in EPS were measured using the protocol based on Pierce bicinchoninic acid

(BCA) kit with BSA (bovine serum albumin) as the standard as outlined in Keithley and Kirisits

(2018). Although it would have given additional information, especially in relation to the lysis of

bacterial cells or EPS disruption, we did not attempt to quantify the concentrations of the nucleic

acids in the extracted EPS fractions herein.

Figure 13. Calibration curves used for determination of (a) protein (PN); (b) polysaccharide (PS)

contents

3.7 Rheological tests

Rheological tests were undertaken using a rheometer (Physica MCR102 Modular Compact

Rheometer, Antor Paar, Australia), equipped with a measuring cup and 14 mm diameter four-blade

vane. A 50 mL sludge sample (e.g. activated sludge and digestate) was poured down into the

measuring cup in which the vane was immersed before each measurement. Temperature during

analyses was maintained at 25±0.01°C using a Peltier control.

3.7.1 Steady shear rheological tests

Steady shear tests were employed to assess the sludge flow behavior (both load- and time-dependent

flow behavior), with a focus on sludge viscosity, thixotropy, and the relationship between shear rate

and shear stress (i.e. rheogram). The tests included a controlled shear rate (CSR) test, a hysteresis

loop test, and a controlled shear stress (CSS) test.

43

Torque rheology measurement described elsewhere (Örmeci and Abu-Orf, 2005; Ormeci et al., 2004),

was employed for further rheological characterization. Area under a torque-time rheogram at a given

time in torque rheology, referred to as ‘totalized torque (TTQ)’, was used to estimate the relative

sludge network strength of sludges as previously outlined in Ormeci et al. (2004).

The CSR test was undertaken to investigate the changes in the viscosity of a sludge sample when

sheared. For this, abrupt flowage and stoppage of sludge were presented by developing the increasing

(ascending path) and decreasing (descending path) rheograms. Accordingly, measurements were

carried out in the steady flow mode to obtain apparent viscosity, A and rheogram of sludge: (i)

increasing shear rate from 0.1 to 1000 s−1 in a logarithm manner; (ii) maintaining constant shear rate

at 1000 s−1 in 30 s; (iii) decreasing shear rate in a logarithm manner from 1000 to 0.1 s−1. Rheogram

of shear stress () was recorded as a function of shear rate () and analyzed for the sludge samples.

Further, shear viscosity (shear) was measured at different shear rates to evaluate the effect of shear

rates on sludge viscosity. Viscosity measurements as a function of time were carried out at different

shear rates (50 s-1, 100 s-1, and 250 s-1), which were chosen complying with the typical shear rate

ranges encountered in sludge handling processes (Kotzé et al., 2015).

Hysteresis loop tests were performed for analyzing the thixotropic behavior of the sludge sample and

evaluating the degree of thixotropy. These tests encompass four major steps: (i) stress history was

minimized by pre-shearing sludge at 5 s-1 for 2 min; (ii) shear rate was linearly increased to the

maximum shear rate in 2 min; (iii) sludge sample was sheared at the maximum shear rate for 1 min;

(iv) shear rate was linearly decreased to 0 s-1 in 2 min. The parameter hysteresis loop area (Hla)

obtained by hysteresis loop tests were used for determining the degree of thixotropy in sludge samples

(Mori et al., 2006; Yuan and Wang, 2013).

The controlled shear stress (CSS) test was employed for yield stress (y) determination. In the CSS

test, shear stress was increased in a stepwise manner and the strain (deformation) response was

determined as a function of the imposed shear stress value. The strain-shear stress curve thus obtained

was used to determine y using the tangent crossover method, depicted in a previous study (Wang et

al., 2011b).

44

3.7.2 Dynamic shear rheological tests

Different dynamic mechanical (or oscillatory) tests were undertaken for sludge samples. These tests

were carried out at 25±0.01°C. For the dynamic measurement, strain sweep (or strain amplitude

sweep, SAS) tests were undertaken to investigate the effects of the amplitude of oscillation on

viscoelastic properties. These tests were carried out with an angular frequency of 5 rad.s-1 and shear

strain range of 0.01 – 1000%. Likewise, frequency sweep (FS) test was performed under the

oscillating shear strain of 0.5% with an angular frequency range of 0.1–100 rad.s-1, to investigate the

effect of frequency of oscillation on viscoelastic properties. Further, the creep test was performed by

applying constant shear stress of 1.0 Pa and monitoring the corresponding compliance for 5 min.

Creep test was carried out to probe the time-dependent nature of changes in sludge under the applied

constant stress. Under the creep test, fixed shear stress was applied to sludge and the resultant shear

strain was monitored for the pre-designated period. After the pre-designated period, the applied stress

was removed, and the strain was monitored thereafter.

Rheological properties of sludge samples were further characterized using different rheological

models. For this, double-repeated linear ramp tests were undertaken encompassing two major steps:

(i) conducting a linear increase of shear rate from 0 s-1 to 300 s-1 in 76 s; (ii) conducting a linear

decrease of shear rate from 300 s-1 to 0 s-1 in 76 s, such that each datum was recorded every 1 s.

Different rheological models used herein include - Bingham, Ostwald de Vaele (or Power-law

model), Herschel-Bulkley and Casson models, and these are represented by Eq. (5)–(8), respectively

(Ratkovich et al., 2013; Seyssiecq et al., 2003):

𝜎 − 𝜎0 = ′𝛾 (5)

𝜎 = 𝐾𝛾𝑛 (6)

𝜎 − 𝜎𝑂𝐻 = 𝐾𝐻𝛾𝑛𝐻 (7)

𝜎0.5 = 𝐾0𝑐 + 𝐾𝑐(𝛾)0.5 (8)

where, 𝜎 is shear stress (Pa); 𝛾 is shear rate (s-1); 𝜎0 is Bingham yield stress; ′ is Bingham plastic

viscosity; 𝐾 is consistency coefficient or index with the units (Pa.sn) is shear stress at a shear rate of

1.0 s-1; exponent 𝑛 is flow behaviour index, which is dimensionless parameter reflecting proximity to

Newtonian fluid index; 𝑛𝐻 is flow behaviour index; 𝐾𝐻 is consistency index; 𝜎𝑂𝐻 is yield stress; 𝜎0𝑐

is square of parameter 𝐾0𝑐, known as Casson yield stress; 𝑐𝑎

is square of parameter 𝐾𝑐, known

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Casson plastic viscosity (this can also be used as ‘infinite shear viscosity’, ∞

, i.e. ∞

= 𝑐𝑎

=

(𝐾𝑐)2). It must be noted that in the case of Newtonian fluid (n = 1), the consistency index K is

identically equal to viscosity of a fluid, η. When the magnitude of n < 1 the fluid is shear-thinning

and when n > 1 the fluid is shear-thickening in nature. For the selection of best-fit or the most suitable

rheological model, the Akaike information criterion (AIC) values, has been employed in addition to

coefficient of determination (R2), adjusted- R2, root-mean-square error (RMSE), absolute sum of

squares (SS) and standard error of estimate (Sy.x or Se) values. Notably, AIC is an estimation of the

relative quality of statistical models for a given set of data and also considered as a measure of

information loss or showed the information loss for a model. Hence, it is desirable to have little

information loss in the models thus employed (Chakrabarti and Ghosh, 2011). Accordingly, when

comparing the best-fit models, the model with the least AIC value is preferable. For this, the corrected

Akaike information criterion, i.e. AICc were also calculated using Eq. (9) (Bozdogan, 1987):

𝐴𝐼𝐶𝑐 = 𝑁 𝑙𝑜𝑔 (𝑆𝑆𝐸

𝑁) +

2𝐾𝑁

𝑁−𝐾−1 (9)

where, K is total number of parameters in rheological model; SSE is sum square error; N is number

of samples (data set). The SSE used in Eq. (9) was formulated using Eq. (10):

𝑆𝑆𝐸 = ∑ (𝜎𝑖 − �̂�𝑖)2𝑁

1 (10)

where, 𝜎𝑖 is measured shear stress and �̂�𝑖 is estimated shear stress calculated from the Eqs. (5-8).

The present study further incorporates calculation of RMSE, SS and Sy.x values for each model as

outlined in Rios et al. (2007), using GraphPad Prism 7.03 software. These values were calculated for

each fit. Since all rheological model equations were fitted with the same number of data points,

RMSE, SS and Sy.x values also could serve as a means for comparing the rheological models in terms

of relative ‘goodness-of-fit’.

46

3.8 Analytical methods

3.8.1 General parameters

Total/volatile suspended solids (TSS, VSS) and total/volatile solids (TS, VS) contents were measured

according to standard methods (APHA, 2005). For the measurement of dissolved sulfur species

(SO42−, HS−, SO3

2−, and S2O32−), samples were filtered (0.22 μm, Millipore, Millex GP) immediately

after collection, and preserved with a sulfide anti-oxidant buffer (SAOB) solution and analyzed using

ion chromatography (IC) with a UV and conductivity detector (Dionex ICS-2000), as described

elsewhere (Keller-Lehmann et al., 2006). Samples for analysis PO4-P were first filtered (using

0.22 μm, Millipore, Millex GP) immediately after sampling, and then analyzed using a Lachat

QuickChem 8000 flow injection analyzer (FIA) (Lachat instrument, Milwaukee, Wisconsin), as

previously described (Gutierrez et al., 2010; Rebosura et al., 2018). Total Fe [Fe(T)], P [P(T)] and S

[S(T)] or other metal ions concentrations (dissolved + particulate) in unfiltered samples and total

dissolved Fe [Fe(aq)], P [P(aq)] and S [S(aq)] or other metal ions concentrations in the filtered samples

(using 0.22 μm, Millipore, Millex GP), were analyzed by ICP-OES (Perkin Elmer Optima 7300DV,

Waltham, MA, USA). Before ICP-OES analysis, samples were digested using 70% nitric acid

(HNO3). Dissolved organic carbon (DOC) was measured using a TOC analyzer (Shimadzu Model

TOC-500A) with ASI-5000A auto-sampler, against external standards of potassium hydrogen

phthalate (C8H5O4K) solution. Similarly, UV absorbance measurement (UVA254) was determined

using a double-beam spectrophotometer (Spectrascan UV-VIS 2600, Thermo Fisher Scientific,

USA). Specific UV absorbance (SUVA254) was calculated as UVA254 (cm−1)×100/DOC (mg.L-1)

(Padhi et al., 2019). Total suspended solids (TSS) was measured using Standard Methods (APHA,

2005). Sludge dewaterability and settleability analyses were carried out as outlined in Section 3.4.

3.8.2 Bound water and total water contents

The bound water content (BWC) of the sludge sample was determined using a Q2000 differential

scanning calorimetry (DSC) analyzer, Q2000 (TA, USA). Here, DSC measurements were carried out

using the freezing-heating method (Wang et al., 2012). Prior to the DSC test, sludge sample was

subjected to centrifugation at 3000 rpm for 10 min. The separated bulk phase after centrifugation was

decanted with caution. The decanted portion of water was considered to be part of bulk solution or

supernatant including slime and LB-EPS fractions. The sludge was first frozen to a temperature of -

20C, assuming that all free water was frozen under this condition, and then brought back to 20C at

a rate of 2C min-1. Heat absorption was quantified by integrating the peak area under the endothermic

curve during the DSC tests. It was reported that bound water does not freeze at a temperature below

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the freezing point of free water (Mao et al., 2016). Herein, the amount of water that did not freeze at

-20C was determined as bound water (Vaxelaire and Cézac, 2004).

Total water content (TWC) in sludge sample in terms of wt% was calculated as previously described,

i.e. the difference between the mass of the sludge sample prior oven drying and mass of the sludge

sample that has been oven-dried at 105C (Mao et al., 2016). Analysis protocol employed for the

determination of BWC and free water content (FWC) in the centrifuged sludge cake samples is

described elsewhere (Katsiris and Kouzeli-Katsiri, 1987; Zhang et al., 2014). Here, FWC content (i.e.

amount of freezable water) in the sludge samples was determined by the endothermic curve area

corresponding to the amount of heat required to melt the frozen water. The relationship between the

FWC and DSC endothermic curve area has been reported as depicted in Eq. (11) (Yu et al., 2016;

Zhang et al., 2014):

𝐹𝑊𝐶 = 𝐾 × 𝐴 (11)

where, FWC is mass of free water (g), A is endothermic curve area (J), and K is conversion factor

(g.J-1). The conversion factor (K) (g.J-1) was determined by obtaining a thermogram of pure water of

known mass and measuring endothermic curve area.

Once the FWC content was determined then the BWC content (i.e. amount of unfreezable water) was

determined as the difference between the TWC and FWC.

Likewise, the moisture distribution in the sludge sample was also analyzed using drying rate curve,

obtained by the thermogravimetric (TG) measurements. An experimental set up used for this

measurement is shown in Figure 14. For the TG measurement, sludge sample was dried under the

constant drying conditions (air-flow, temperature). The different water fractions could be identified

by plotting the drying rate (g.h-1) as a function of the moisture content (i.e. mass of water/total solids,

g.g-1) of the sample. The drying procedure was carried out very slowly as depicted in Figure 14. The

moisture evaporation rate of sludge sample was obtained by placing sludge sample on porcelain

crucibles (60 mm in diameter, 26 mm high) and moving them to a thermostatic oven (GZX-9246

MBE, Shanghai Boxun Industry and Commerce Co., Ltd, China) maintained at 25C and leaving the

sample there with an airflow rate of 35.0 mL.min-1 for 4 days. The moisture evaporation rate was

48

determined by measuring the moisture content in sludge as a function of time. All these tests were

performed in duplicates.

Figure 14. Schematic diagram of drying test – TG measurement

3.8.3 Particle size distribution

The volume-weighted particle size distribution (PSD) was determined with a particle size analyzer

(Malvern Mastersizer 3000, Malvern), equipped with a wet sample dispersion unit (Hydro EV). The

instrument had a measurement accuracy of 0.6% based on the measurement of monomodal latex

standards. Here, laser diffraction measurement was based on Mie Scattering Model. During the

particle size analysis, 400 mL of reverse osmosis (RO) water was used as the dispersant medium,

without applying ultrasound and maintaining laser obscuration in the range of 11-14%. Optical

parameters used for the PSD analysis were absorption coefficient = 1.0 and refractive index = 1.52.

Each sample was analyzed with 10 repeated measurements (n=10). Samples collected for PSD

analysis were stored at 4C before the analysis and were analyzed within 24 hr of sampling. Further

details of the dispersion conditions employed during sample analyses are provided in Table 4.

3.8.4 Fractal dimension

Change in sludge aggregate structure (or degree of compactness) of sludge sample was characterized

by the fractal dimension Df values, calculated from the light scattering data as described by Wilén et

al. (2003) and Wu and He (2010). Sewer-dosed Fe-salt can exhibit the influence on both particle

size/structure, which could be reflected by the change in the Df values. The calculation of Df was

49

based on a power law relationship between the total scattering intensity (I) of light by particles being

analyzed and the magnitude of the scattering angle (q) as shown in Eq. (12). By plotting log(I) as a

function of the log(q), Df was estimated from a fit of a negative linear slope (Wu and He, 2010).

𝐼(𝑞) ∞ 𝑞−𝐷𝑓 (12)

If a beam of light is directed on the sample, intensity of the scattered light can be measured as a

function of wave vector q. This wave vector ‘q’ can be calculated using Eq. (13):

𝑞 =4𝜋𝑛 sin(

𝜃

2)

(13)

where n is refractive index, is wavelength of light, and 𝜃 is scattering angle. The scattering intensity

(I) at each detector was derived from Malvern measurement results. Also, aggregate structure factor

(S) and ratio between hydrodynamic radius (RH) to the radius of aggregate (RA) (𝑅𝐻

𝑅𝐴) of the sludge

sample were determined were calculated using Eq. (14) and Eq. (15), respectively (Gmachowski,

1995; Gmachowski, 1996; Mu and Yu, 2006):

𝑅𝐻

𝑅𝐴= √1.56 − (1.728 −

𝐷𝑓

2)

2

− 0.228 (14)

𝑆 = (𝑅𝐻

𝑅𝐴)

2

(15)

where, Df is the fractal dimension of sludge flocs or aggregates

The value of velocity ratio or ‘ratio of constituent cluster radii’ (𝑅𝐻

𝑅𝐴) describes the dynamic behavior

of the sludge, i.e. the velocity ratio between the primary particles and the aggregates (Gmachowski,

1995). Further, it also reflects the kinetics of sedimentation of sludge pertinent to their solid–liquid

separation system having a different degree of aggregation, but the same volume fraction of

equivalent aggregates. Thus, this value was employed to determine the settleability and filterability

(SRF)/dewaterability of the sludge (Gmachowski, 1995; Gmachowski, 1996). Likewise, the (S) value

50

could be used to characterize the space-filling ability of the sludge, including its compactness of

aggregates/flocs (Gmachowski, 1995; Gmachowski, 1996).

Table 4. Dispersion conditions employed during the PSD analyses of the sludge sample

Particle Refractive Index 1.52

Particle Absorption Index 100.00%

Dispersant Name RO water

Dispersant Refractive Index 1.33

Scattering Model Mie

Analysis Model General Purpose

Weighted Residual 0.3-0.5%

Laser Obscuration 11-14%

Concentration 0.12-0.14%

Span 1.6-1.7

Uniformity 0.49-0.53

Specific Surface Area 79.02-97.96 m².kg-1

3.9 Statistical analysis

Mean values and associated standard deviation (SD), standard error of mean (SEM) of different data

sets were calculated to tests the statistical difference between measured analytical parameters.

Student’s t-test with Welch’s correction and a 95% confidence interval (CI) was applied to determine

whether the difference between the observed mean values of iron-conditioned and unconditioned

sludges (e.g. activated sludge and digestate) pertinent to different properties are statistically

significant or not, which was judged based on the calculated probability value, p-values (p<0.05 or

p>0.05). All statistical tests were undertaken using GraphPad Prism software (version 7.03).

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Chapter 4

Elucidating factors influencing the transformation and

transport of sewer-dosed iron in the urban wastewater

systems

The following manuscript submitted to ‘Water Research’ for publication, has been modified and wholly incorporated in

the Chapter 4: ‘Sohan Shrestha, Wakib Khan, Jagadeeshkumar Kulandaivelu, Keshab Sharma*, Zhiguo Yuan, Stephan

Tait (2019). Transformation and transport of sewer-dosed iron in urban wastewater systems’

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4.1 Introduction

Direct dosing of iron (Fe)-salts to sewer networks is commonly used for control of sulfide-induced

sewer corrosion and odour (Nielsen et al., 2005b). Importantly, the benefits of Fe-salt dosing to a

sewer can extend beyond the sewer into a downstream wastewater treatment plant (WWTP)

(Rebosura et al., 2018; Sun et al., 2015). For instance, in recent years, the sewer system and

downstream WWTP have started being viewed as a single entity rather than in isolation within

integrated urban wastewater system (UWWS). Consequently, new insights have emerged on multiple

uses of Fe-salt across the UWWS in maximizing the multiple benefits to reduce chemical use

(Rebosura et al., 2018).

The efficacy of multiple uses of Fe across the UWWS is expected to be influenced by redox

transformations between ferrous [Fe(II)] and ferric [Fe(III)] form and by the formation of Fe mineral

precipitates and their transport, settling, dissolution and reactivity (e.g. with dissolved sulfide or

phosphate). For example, in a sewer system, Fe(II) or Fe(III) salts are dosed, and can form iron sulfide

precipitates (FeSx) in the sewer network (Hvitved-Jacobsen et al., 2002). Stoichiometry and redox

conditions would determine FeSx formation and re-oxidation (Firer et al., 2008; Kiilerich et al., 2017;

Nielsen et al., 2005b). Overall, Fe transformation rate kinetics may be influenced by mineral

precipitation/dissolution kinetics (Nielsen et al., 2005b). There may also be competition between FeSx

formation, iron(III)-hydroxide precipitation, iron-phosphate precipitation and Fe complexation

processes (Araújo et al., 2000; Nielsen et al., 2005b). All these phenomena could influence precipitate

particle size distribution (PSD), settling and retention of Fe in a sewer. Once Fe successfully passes

into a downstream WWTP, the subsequent transformations and resulting characteristics of Fe-

precipitates are similarly influenced by redox state, stoichiometry and solution equilibria (Solon et

al., 2017). In the primary settling tank (PST), Fe settles out and is transported to the sludge line, or

alternatively is carried over into the activated sludge (AS) process via the main water line (Gutierrez

et al., 2010). In the AS system, FeSx can re-oxidize to release Fe (Gutierrez et al., 2010), causing

precipitation of iron phosphate or ferric hydroxide (Schippers, 2002) and simultaneously adsorbing

or co-precipitating phosphorus (P) (Li et al., 2018; Smith et al., 2008). If Fe is carried into the sludge

line and is not already in FeSx form, Fe can precipitate with sulfide and contribute to desulfurizing

of anaerobic digester (AD) biogas (Ge et al., 2013). There has been recent interest to include the

drinking water treatment system within this UWWS by including the reuse of Fe-rich sludge from

water treatment to control sulfide-induced sewer odour and corrosion (Keeley et al., 2014; Sun et al.,

2015). Fe-rich sludge may be formed under predominantly oxidised conditions during drinking water

53

treatment with Fe then in oxidised Fe(III) form, with implications on subsequent transformations and

reactivity in-sewer (Keeley et al., 2014) and in a downstream WWTP.

Different sewer dosing locations of Fe-salts have previously been explored, to try and alter in-sewer

retention, and accordingly control Fe particle growth, separation efficiency and Fe-fractionation

(liquid bulk phase versus settled particulate phase). For this, Gutierrez et al. (2010) used laboratory

experiments exposing dosed Fe for different periods to anaerobic conditions in sewer wastewater, to

simulate different in-sewer retention times and thereby test effects on Fe transformations and

transport in a subsequent PST. Their study suggested that in-sewer dosing location (which influences

in-sewer retention time) could have an impact on settling performance in a downstream PST. Further,

it was suggested that an end-of-pipe sewer dosing location may not provide enough time for

sufficiently large precipitates to grow to settle out in a PST (Gutierrez et al., 2010). However,

Gutierrez et al. (2010) had not explored in-sewer oxic-to-anaerobic transition conditions, which are

typically found in oxic segments of a sewer (Vollertsen et al., 2008), and also had not tested water

treatment sludge as a source of dosed Fe.

The present study extends the work of Gutierrez et al. (2010) and others conducted at lab scale, by

testing at full-scale, the effect of Fe-salt dosing location on downstream settling in a PST. These tests

aimed to examine the hypotheses of Gutierrez et al. (2010) concerning the impact of Fe dosing

location on Fe transformations and transport. In addition, carefully designed laboratory mixing-

reaction-settling tests were conducted to further elucidate the effects of in-sewer retention time and

redox conditions on Fe on Fe transformations and transport, both for Fe-salt as well as pre-formed Fe

water treatment sludge.

4.2 Materials and methods

4.2.1 Full-scale FeCl2 dosing tests

Full-scale Fe-salt dosing trials were conducted on a sewer feeding a local WWTP in South East

Queensland, Australia. Ferrous (Fe2+) salt reagent (i.e. FeCl2) from IXOM (Melbourne, Australia)

(30% FeCl2 solution) was used as Fe source (see Section 3.3). Typical average dry weather flow for

the WWTP was 131 ML.day-1. Details of the WWTP have been previously reported elsewhere

(Kazadi Mbamba et al., 2016). Two distinct dosing locations were trialled: one at the WWTP inlet

and the other (in a separate trial) at an upstream sewer pump station associated with a major gravity

54

sewer line stretching 7.9 km in length. The flow of this gravity sewer line first met a rising main

line stretching 8.0 km in length, prior to reaching the WWTP inlet (see Figure 10). The WWTP inlet

dosing trial lasted for 1.5 months with varying FeCl2 dosing rates applied every week (Table 5). The

ferrous dosing was intermittent, which lasted for about 6-11 hrs each day. Three sampling campaigns

(sampling 1, 2, and 3) were conducted on the 30th, 42nd, and 44th day of dosing, corresponding to the

FeCl2 dosing amounts of 11.4, 17.2, and 14.2 kg.Fe.ML-1 of sewage, respectively. For the upstream

in-sewer dosing trial lasting 2.5 months, two pumps were used to dose the FeCl2. Notably, three

months transient period was provided after completion of inlet dosing trial to avoid the residual effects

from previous dosing trial in the receiving WWTP. One of the dosage pumps dosed FeCl2 into a

gravity sewer line bypassing the sewer pumping station (SPS) at a dosing rate of 66.0 L.hr-1

continuously 24 hrs per day, 7 days per week (albeit with variable hourly dosage rates, Table 5). The

other pump dosed a fixed flow of FeCl2 of 180 L.hr-1 providing an instantaneous dosage only when

the SPS pumps the water from the wet well. Average run time of this second dosage pump was 15

min for an average 12 times per day on average. The calculated total amount of Fe dosed in the

upstream in-sewer dosing trial was 230 kg.Fe.day-1. Hourly manual composite samples from the

PST influent (after coarse solids screening/grit removal), overflow, and underflow of the PST

(sampling points S1, S2, and S6, Figure 11), were collected over a 5.0 hr period on each of the three

sampling days (Sampling 1, 2, and 3), each on a different week during the trial. A similar sampling

strategy was used for the WWTP inlet dosing trial. These collected samples were immediately stored

in the refrigerator at 4 °C and taken to the laboratory for analysis at the end of each sampling day.

The samples were analysed for total and soluble Fe, P and S concentrations and PSDs (see Section

4.2.3).

55

Table 5. Full-scale tests - WWTP inlet and upstream sewer FeCl2 (30% FeCl2) dosing schedules and

sampling dates

WWTP inlet dosing trial Upstream sewer network dosing trial

Dosage amount,

kg.Fe.ML-1 of sewage

Dosing dates

(DD/MM/YY)

Dosing duration at

WWTP inlet (hr)

Time of

day

Maximum hourly dose

rate (L.hr-1) Hour

2.8 30/07/2018 8 12:00

AM 53 0

2.8 31/07/2018 10 1:00

AM 39 1

2.8 1/08/2018 9 2:00

AM 32 2

5.7 13/08/2018 9 3:00

AM 32 3

8.5 14/08/2018 9 4:00

AM 30 4

11.4 20/08/2018 6 5:00

AM 28 5

11.4 23/08/2018 7 6:00

AM 44 6

11.4 24/08/2018 6 7:00

AM 66 7

11.4 28/08/2018 6 8:00

AM 62 8

11.4

(sampling 1) 30/08/2018 11.4

9:00

AM 65 9

11.4 3/09/2018 8 10:00

AM 66 10

11.4 7/09/2018 6 11:00

AM 64 11

17.2 10/09/2018 8 12:00

PM 66 12

17.2

(sampling 2) 11/09/2018 8

1:00

PM 61 13

14.2 12/09/2018 7 2:00

PM 60 14

14.2

(sampling 3) 13/09/2018 8

3:00

PM 57 15

14.2 14/09/2018 6 4:00

PM 56 16

5:00

PM 56 17

6:00

PM 58 18

7:00

PM 64 19

8:00

PM 62 20

9:00

PM 61 21

10:00

PM 60 22

11:00

PM 58 23 sampling dates of sampling 1, 2 and 3 during WWTP inlet dosing trial; FeCl2 dosing strategy adopted during

upstream sewer dosing trial

56

4.2.2 Laboratory experiments

Experimental materials

Stock solutions of ferric chloride hexahydrate (FeCl3.6H2O, Sigma-Aldrich, 98% assay) and sodium

sulfide nanohydrate (Na2S.9H2O, Sigma-Aldrich, 99.99% assay) were prepared in MilliQ® water

that had been deoxygenated by sparging with high purity nitrogen (N2) gas. Similarly, P-stock

solution (10 mg.P.L-1) was prepared using anhydrous potassium dihydrogen phosphate (KH2PO4)

(Sigma-Aldrich, 99.0% assay), but in normal MilliQ® water not sparged with nitrogen gas.

Fe-based water treatment sludge was prepared using a jar tester equipped with six 1.0 L beakers

(Phipps and Bird, Model PB-700) using the method outlined by Bagastyo et al. (2011). In short, raw

water was collected from a local water treatment plant in South East Queensland, Australia, and FeCl3

stock solution was added whilst mixing for 1 minute at a rapid mixing speed of 200 rpm, followed by

a flocculation period of 10 minutes at a slow mixing speed of 40 rpm. Dissolved organic carbon

(DOC), UV absorbance (UV254) and specific UV absorbance (SUVA254) concentrations of the raw

source water were 12.01.4 mg.C.L-1 (n=4), 0.620.1 au (n=4), 5.10.3 m-1.L.mg-1 (n=4),

respectively. The pH and the FeCl3 dosages were optimized for turbidity removal as measured by

UV254 absorbance, and the optimized pH value was found to be 6.1 at a FeCl3 dose of 60 mg.Fe.L-1.

pH was adjusted using 0.1 M sodium hydroxide (NaOH) (Sigma-Aldrich, 97.0% assay). The

composition of the freshly prepared Fe-sludge is presented in Table 6. The Fe-sludge slurry thus

prepared stored at 4C prior to use and used within 24 hrs of its preparation.

Domestic sewage (or wastewater) used in the laboratory experiments was collected from a residential

pumping station serviced via gravity sewers in Indooroopilly, South East Queensland, Australia. The

wastewater was collected between approximately 10:00 am and 12:00 pm. For wastewater, manual

grab samples were used. The compositions of the wastewater are presented in Table 6 together with

that of Fe-sludge.

Experimental set-up

To simulate different in-sewer exposures, two laboratory reactor systems were set-up to conduct sets

of mixing-reaction-settling tests two different redox conditions, i.e. oxic-to-anaerobic transition

conditions (Figure 15) and purely anaerobic conditions (Figure 16). The apparatus used in the

57

experiments consisted of 1.0 L borosilicate glass reactors completely sealed with cover lid with

multiple sealed ports. One port was used to dose Fe(III) salt stock solution or Fe-rich water treatment

sludge (depending on the Fe source being used) and sulfide stock solution, and to add wastewater to

compensate for loss of volume due to sampling from the other port (minimal overall volume, see

further below). These reactor ports were tightly sealed during operation. The reactor under anaerobic

conditions was coupled with a 5 L Cole-Parmer Kynar gas bag filled with pure helium (He2) to

prevent air getting entry into the reactor, whereas the reactor under oxic-to-anaerobic conditions was

open to air.

The reactors used in the mixing-reaction-settling tests were fitted with a dissolved oxygen (DO) probe

(626250-1) with YSI ProODO handheld optical DO meter (John Morris) and a TPS pH probe

(EPSUN5, Plastic, AgCl Ref) with minichem-pH controller (TPS, Version 2.1.1). Both the pH and

DO probes were pre-calibrated prior to each experiment, as per the manufacturer’s protocol. Each

reactor was continuously mixed using a cylindrical magnetic stirrer bar (256 mm, color squid

IKAMAG white) at 250 rpm.

58


settling test under simulated in-sewer oxic-to anaerobic transition condition, correspond to 0.5 hr, 4.0

hr, and 6.0 hr mixing times

59


settling tests under simulated in-sewer anaerobic condition, correspond to 0.5 hr, 4.0 hr, and 6.0 hr

mixing times. Here, high purity nitrogen (99% N2) gas was only used for the sparging the sewer

wastewater prior initiation of tests

60

Table 6. Composition of domestic sewage (or wastewater) and freshly prepared Fe-sludge used in the laboratory experiments. Unless otherwise stated

values presented correspond to the mean in replicates, given with estimates of error (±) at the 95% CI

Samples Analyzed

fractions

Fe

(mg.Fe.L-1)

P

(mg.P.L-1)

S

(mg.S.L-1)

NH4-N

(mg.N.L-1)

PO4-P

(mg.P.L-1)

Sulfide,

HS−

(mg.S.L-1)

Sulfate,

SOx

(Sulfate,

SO42− +

Sulfite,

SO32− )

(mg.S.L-1)

Thiosulfate,

S2O32−

(mg.S.L-1)

TSS

(mg.TSS.L-1)

Sewer

wastewater

Sample-I Total* 0.18 0.03 9.47

0.53

19.50

0.49

55.22

2.7

7.33

0.57

1.14 0.03 14.23

0.57

0.39 0.17 294.0 90.5

Filtered** − 5.60 0.0 18.02

0.20

Sample-

II

Total 0.86 15.94 21.34 48.75 9.82

Filtered 0.01 9.81 19.74

Fe-sludge Total 1151.0 7.92 13.11

Filtered 0.52 0 5.42

*Total concentrations correspond to particulate + dissolved fractions

**Samples filtered via 0.22 m membrane filter, filtered concentrations correspond to dissolved fractions; values presented in section (Sample-II) correspond to mean (n=2) and were for sample used in the mixing-reaction-settling tests using Fe-sludge

61

Experimental procedure

Two sets of mixing-reaction-settling experiments, differing in their measured redox (DO) conditions,

were performed with Fe-salt as Fe source:

1. Simulating in-sewer oxic-to-anaerobic transition conditions (denoted as ‘oxic-to-anaerobic’

hereafter), and

2. Simulating in-sewer pure anaerobic conditions (denoted as ‘anaerobic’ hereafter), with the

wastewater first sparged with high purity nitrogen (99% N2) gas for 2.0 hr using a 1 spherical

Oblong Diffuser Stone, to remove any DO.

An additional set of mixing-reaction-settling experiments was performed instead using the Fe-rich

water treatment sludge as Fe source, but only under simulated in-sewer oxic-to-anaerobic conditions.

Each set of mixing-reaction-settling tests typically involved the following steps in a sequence:

(a) dosing of domestic wastewater in a completely filled reactor (Figure 15, Figure 16) with FeCl3

and Na2S stock solutions at the outset of the test, at initial added concentrations of 15.01.0

mg.Fe.L-1 and 15.01.0 mg.S.L-1 (1:1 mass ratio, Fe:S molar ratio = 0.57). For reference,

under purely anaerobic conditions, 1.5 moles of sulfide would be required to achieve complete

reduction of 1.0 mole of Fe(III) to Fe(II) and stoichiometric precipitation of FeS (Section

4.3.2);

(b) mixing the contents at 250 rpm for a pre-defined reaction period of 0.5 hr, 4.0 hr or 6.0 hr

mixing times (mimicking different in-sewer retention times); and

(c) stopping mixing and allowing any precipitate that formed to subsequently settle together with

background organic matter for 1.0 hr, mimicking settling in a PST (Gutierrez et al., 2010).

All the tests were carried out at ambient room temperature of 23±1 °C. Each test condition was run

in parallel replicates. Both DO and pH of the liquid phase were continuously monitored throughout

the tests.

For Fe concentration determination, 3.0 mL samples were collected from each reactor at pre-

determined time intervals, including initially after chemical addition, immediately after mixing was

stopped, immediately after the 1.0 hr settling period, and periodically for a time after that (total sample

volumes taken during entire test = 3.06 = 18.0 mL). These samples were collected using luer-lock

syringe from approximately 4-5 cm depth from the top of reactor, representing ‘supernatant’ during

62

the unmixed periods. The Fe concentration in the collected samples were analyzed by inductively

coupled plasma optical emission spectroscopy (ICP-OES) (Section 4.2.3).

For PSD analysis for experiments with Fe-salt as Fe source, three sets of PSD samples were collected.

These were: 1st PSD sample (40 mL volume), prior to chemical addition (represents background

matrix, i.e. wastewater); 2nd PSD sample (40 mL volume), from the supernatant immediately after

mixing was stopped; and 3rd PSD sample, from the reactor bottom-settled particulate mass at the

completion of the test. Only the volume of the 1st PSD sample (prior chemical addition) was

compensated for by adding fresh wastewater. With Fe-rich water treatment sludge, a PSD sample was

only collected for the bottom-settled particulate mass at the end of experiment. PSD was measured

in all cases by laser diffraction (Section 4.2.3).

With Fe-salt under oxic-to-anaerobic transition conditions, an additional sample of bottom-settled

particulate mass was collected at the end of the experiment to analyse for elemental composition by

scanning electron microscopy coupled with energy dispersive x-ray (SEM-EDX) (Section 4.2.3).

Digital photographs were taken at various times during the experiment for visual observation,

including of the settled layers at the bottom of each reactor (Figure 17).

63

Figure 17. Images showcasing two supernatant samples (one taken at the beginning prior chemicals

addition while other taken following 1.0 hr settling after end of pre-designated mixing-reaction times)

including settled masses sample at bottom of reactors (obtained after end of 6.0 hr mixing-reaction

time under oxic-to-anaerobic transition condition). Here, chemical refer to FeCl3 and Na2S stock

solutions

4.2.3 Analytical methods

Dissolved sulfur species (SO42−, HS−, SO3

2−, and S2O32−), PO4-P, Total Fe [Fe(T)], P [P(T)] and S [S(T)]

concentrations (dissolved + particulate) in unfiltered samples and total dissolved Fe [Fe(aq)], P [P(aq)]

and S [S(aq)] concentrations in filtered samples, DOC and TOC, UV absorbance measurement

(UVA254), specific UV absorbance (SUVA254), including the TSS measurements were carried out in

this study as outlined in Section 3.8 (Chapter 3). Likewise, the volume-weighted PSD analysis was

carried out using a laser diffraction analyzer (Mastersizer 3000, Malvern) as described in Section

3.8.3 (Chapter 3).

Scanning Electron Microscopy coupled with Energy Dispersive X-Ray (SEM-EDX) analysis was

carried out at the Centre for Microscopy and Microanalysis, The University of Queensland (UQ). The

surface morphology and elemental composition of the samples were examined by SEM (JEOL JSM-

6610, America), equipped with a detector (Oxford 50mm2 X-Max SDD x-ray) that enabled

simultaneous imaging and elemental analysis at high count rates with 125 eV energy resolutions.

https://www.sciencedirect.com/topics/earth-and-planetary-sciences/absorbance

64

Prior to analysis, the samples were dried in a vacuum oven (SEMSA OVEN 718) at 65C for 8 hr

and then carbon-coated twice (Quorum Q150T, UK), using the Three Heavy-Burst mode to obtain

the carbon thickness of 30–40 nm. For EDX analyses, the EDAX software (EDAX, AMETEK Inc.)

was utilized at a frame resolution of 1024×800, with a dwell time of 200 s/frame to collect 16 frames

for each region of interest. The locations for spot analyses were chosen by examining features of the

secondary electron image, and the quantification of each individual EDX spot analysis in Wt% was

done against the standard mineralogical database. Nonetheless, both EDX layered map (TRUmap)

and Quant mapping techniques were employed to investigate the differences in concentration of

elements over the mapped area in the samples.

4.3. Results and discussion

4.3.1 Full-scale Fe-salt dosing trials

Background total Fe mass loads measured in the PST influent prior to full-scale FeCl2 dosing were

192.6±15.7 kg.Fe.day-1 for the WWTP inlet dosing trial and similarly 166.4±19.7 kg.Fe.day-1 for

upstream in-sewer dosing trial. These represent background Fe levels in the PST influent without Fe

dosing. The total Fe mass loads in the PST influent with full-scale FeCl2 dosing were 3916.9±366.8

Kg.Fe.day-1 for the WWTP inlet dosing trial and 370.7±48.5 kg.Fe.day-1 for the upstream in-sewer

dosing trial. Accordingly, the additional total Fe mass load due to FeCl2 dosing (excluding

background) was estimated to be 3717.8±368.8 kg.Fe.day-1 for the WWTP inlet dosing trial and

204.4±52.3 kg.Fe.day-1 for the upstream in-sewer dosing trial. All these daily Fe mass loads were

calculated based on a dry weather flow of 131 ML.day-1 (see Section 4.2.1). Clearly, the Fe dosing

amount was much lower in the upstream in-sewer dosing trial than in the WWTP inlet dosing trial.

Interestingly, the Fe(T) and Fe(aq) concentrations were relatively lower in PST influent with upstream

in-sewer dosing than with WWTP inlet dosing (Table 7). Interestingly, in the upstream in-sewer

dosing trial, the Fe dosed upstream (i.e. 230 kg.Fe.day-1, Section 4.2.1) was somewhat comparable

to Fe reaching the PST influent (i.e. 204.4 kg.Fe.day-1). This suggest only about 11% of the dosed

iron was retained in the sewer system due to the deposition of Fe-precipitates as solids. Continuous

deposition and re-suspension of solids most likely contributed to the low retention of iron in sewers.

As was anticipated, we did not observe a substantial difference between average daily mass loads of

Fe estimated at upstream sewer network dosing location (i.e. 230 kg.Fe.day-1) and amount reaching

the PST influent (i.e. 204.4 kg.Fe.day-1) with in-sewer dosing trial. This implies that upstream in-

sewer FeCl2 dosing did not result in significant Fe retention in sewer as the Fe dosed and Fe reaching

65

the PST influent were comparable. In other words, the Fe retention in-sewer as sediment was minimal,

or that the in-sewer sediment layer had equilibrated after FeCl2 dosing had begun and before the first

sampling day (Gutierrez et al., 2010). However, Fe concentrations in the PST effluent were lower

than in the PST influent under both FeCl2 dosing trials, possibly due to settling of mineral

aggregates/particulates in PST (Table 7). Relatively, retention of Fe by settling in the PST appeared

to be more effective for WWTP inlet dosing (50-65% Fe to sludge) than for upstream in-sewer dosing

(26-57% Fe to sludge), but due to high measurement variability with full-scale, this difference was

not statistically significant. However, TSS removal in the PST was significantly better for upstream

sewer dosing than for WWTP inlet dosing (Table 7). This observation broadly aligned with the

suggestion by Gutierrez et al. (2010) that in-sewer Fe dosing with a longer in-sewer retention time

promotes settling in a downstream PST. TSS in the PST underflow was 24320±3033 mg.L-1 for the

in-sewer Fe dosing trial and 18920±881 mg.L-1 for the WWTP inlet dosing trial, and these values

aligned with expectations from a TSS mass balance. The primary sludge flow rate was approximately

the same in both dosing trials. A mass balance analysis, comparing the up-concentration effect

primary settling on TSS and Fe(T), suggested that Fe(T) was still accumulating in the underflow

throughout the WWTP inlet dosing trial. Specifically, Fe(T) was at a lower than proportional

concentration in the underflow than would be expected from a TSS mass balance. This interpretation

aligned with an observed slow increase in underflow Fe(T) over time in the WWTP inlet dosing trial

(compare Sampling 1, 2 3, Figure 18). In contrast, underflow Fe(T) in the in-sewer dosing trial

remained stable during the trial and aligned with the TSS mass balance.

On the other hand, phosphorus (P(T) and P(aq)) concentrations were similar with WWTP inlet dosing

and upstream sewer dosing (Table 8), indicating minimal impact of Fe-dosing locations on

phosphorus in sewage and on phosphorus removal via the PST. We also found minimal change in

total and dissolved sulfur (S(T) and S(aq)) concentrations from the PST influent to effluent (Table 9),

and no apparent impact of Fe-dosing locations on sulfur loading, possibly due to the dominant sulfur

species expected to be sulfate rather than sulfide, with sulfate being unaffected by Fe. Variations in

the concentrations (per wet basis) of Fe(T), P(T), and S(T) in the PST underflow between the two dosing

trials are shown in Figure 18. Observed differences in Fe(T) and P(T) concentrations between both

dosing trials were minimal, except S(T). The exception was S(T) on one of the sampling days of the

WWTP inlet dosing trial (Sampling 3, Figure 18), whereon a significantly higher S(T) in the underflow

corresponded to a significantly higher Fe(T) in the underflow. This could be due to additional mass-

based FeSx separation by the PST.

66

Figure 19a-d show measured PSDs in PST influent and effluent for both dosing trials and three

consecutive samples collected on a sampling day (Sampling 1). For comparison, PSDs measured of

another sampling day (Sampling 2) are presented in Figure 20a-d. We observed multi-modal PSDs in

both the PST influent and the PST effluent in all cases, which is likely caused by the mixing of

multiple particle or aggregate size groups owing to flocculation/aggregation and

disaggregation/resuspension (Lee et al., 2012). There was a prominent larger sized modal class in the

PST effluent (>1 mm) that was not very prominent in the PST influent, possibly attributable to a small

volume of large debris carried over into the PST effluent. Mineral aggregates were expected to fall

within the smaller modal size classes, which appeared to translate well from the shape of the influent

PSD into the shape of the effluent PSD in both dosing trials, albeit at much lower particle

concentration in the effluent. This is influenced by settling efficiency. With upstream in-sewer dosing,

the <200 m sized particles in the PST effluent more closely resembled the corresponding size class

in the PST influent (Figure 19c-d). In contrast, the size class 20-80 m was lacking in the PST effluent

in the WWTP inlet dosing trial (Figure 19a-b). However, this observation was not consistent with the

repeat sampling event (Sampling 2, Figure 20a-d). There appeared to be a modal size class in the

range 300 m - 1 mm, prominent in the PST influent but lacking in the effluent, likely due to near-

complete removal during primary settling. Overall, there were clear differences in PSDs between PST

influent and effluent in both the dosing trials. However, it was difficult to resolve clearly the distinct

effect of Fe dosing locations on the observed PSDs, likely due to variations in results for the different

sampling days (Figure 19, Figure 20) and due to a general prominence of background suspended

solids (Table 7) in the measured PSDs, which could not be avoided. Besides, significant differences

in Fe dosage rates and resultant Fe concentrations reaching the PST influent that exist between the

two dosing trials, can also be another contributing factor behind such observed PSDs owing to the

coagulant nature of Fe.

Interestingly, suspended solids removal in the PST was better for upstream sewer dosing than for

WWTP inlet dosing (Table 7). However, there was mismatch between the capture of suspended solids

and Fe retention by settling in the PST (or Fe-transferability) during both dosing trials. More research

needs to be conducted to elucidate the reasons behind such observations in PST when dosing Fe-salts

in integrated sewer-WWTP system. When dosing Fe-salts in sewers, the primary particle size of Fe-

precipitates and the PSD would be influenced by the combined effects of Fe-precipitation,

complexation, aggregation, dissolution, and disaggregation processes. Such competing processes

would be influenced by in-sewer redox conditions as elucidated below (Section 4.3.2).

67

In broad agreement with the lab-scale observations of Gutierrez et al. (2010), our results suggested

that in-sewer retention time does play an important role in determining PST settleability (i.e. TSS

retention in PST). However, we could not resolve exact relationship between Fe retention and TSS

removal by a full-scale PST. To further elucidate effects of in-sewer exposure conditions on Fe

transformations and Fe transport, we carried out carefully designed laboratory experiments (Section

4.3.2).

68

Table 7. Measured Fe(T) and Fe(aq) concentrations in PST influent and effluent for three different sampling events (days) under separate WWTP inlet and

upstream sewer FeCl2 dosing trials. Data presents calculated mean values ± estimate of error at the 95% confidence interval (CI) and calculated %

reduction in Fe concentrations from PST influent to effluent are also shown

Upstream sewer

FeCl2 dosing

Different

sampling

events (days)

PST influent PST effluent % Fe(T)

retained

in PST

% Fe(aq)

retained

in PST

TSS

(n=3)

(mg.TSS.L-1)

Fe(T)

(n=5)

(mg.Fe.L-1)

Fe(aq)

(n=5)

(mg.Fe.L-1)

Fe(T)

(n=5)

(mg.Fe.L-1)

Fe(aq)

(n=5)

(mg.Fe.L-1)

PST

influent

PST

effluent

Sampling 1 3.2 0.9 0.6 0.2 1.4 0.2 0.6 0.1 56.9 0 370 40 90 14

Sampling 2 2.1 0.2 0.3 0.1 1.4 0.3 0.6 0.2 32.4 -

Sampling 3 2.6 0.6 0.8 0.1 1.9 0.2 0.7 0.1 25.6 7.9

WWTP inlet FeCl2

dosing

Sampling 1 20.6 4.6 8.4 4.5 10.3 1.3 3.4 0.7 50.3 60.2 316 19 148 11

Sampling 2 26.5 5.1 12.7 4.6 12.1 5.1 5.4 3.2 54.5 57.4

Sampling 3 28.2 5.6 13.2 6.1 9.7 4.3 3.1 2.3 65.7 76.6

69

Table 8. Measured P(T) and P(aq) concentrations in PST influent and effluent for three different sampling events (days) under separate WWTP inlet and

upstream sewer FeCl2 dosing trials. Data presents calculated mean values ± estimate of error at the 95% CI and calculated % reduction in P concentration

from PST influent to effluent are also shown

Upstream sewer

FeCl2 dosing

Different

sampling

events (days)

PST influent PST effluent % P(T)

retained in

PST

% P(aq)

retained in

PST

TSS

(n=3)

(mg.TSS.L-1)

P(T)

(n=5)

(mg.P.L-1)

P(aq)

(n=5)

(mg.P.L-1)

P(T)

(n=5)

(mg.P.L-1)

P(aq)

(n=5)

(mg.P.L-1)

PST

influent

PST

effluent

Sampling 1 8.7 1.2 5.0 0.5 6.6 0.7 4.7 0.6 24.9 7.2 370 40 90 14

Sampling 2 9.6 1.9 6.0 1.0 7.8 0.6 5.9 0.7 18.7 2.3

Sampling 3 10.0 1.8 6.9 1.2 8.4 1.0 6.9 0.8 15.6 0

WWTP inlet

FeCl2 dosing

Sampling 1 10.4 0.6 6.4 0.3 8.7 0.7 7.4 0.5 16.7 - 316 19 148 11

Sampling 2 11.8 2.2 6.3 2.9 8.4 0.7 7.1 0.5 28.9 -

Sampling 3 11.6 0.8 6.6 0.5 9.3 0.8 7.9 0.5 20.1 -

70

Table 9. Measured S(T) and S(aq) concentrations in PST influent and effluent for three different sampling events (days) under separate WWTP inlet and

upstream sewer FeCl2 dosing trials. Data presents calculated mean values ± estimate of error at the 95% CI and calculated % reduction in S concentration

from PST influent to effluent are also shown

Upstream sewer

FeCl2 dosing

Different

sampling

events (days)

PST influent PST effluent % S(T)

retained in

PST

% S(aq)

retained in

PST

TSS

(n=3)

(mg.TSS.L-1)

S(T)

(n=5)

(mg.S.L-1)

S(aq)

(n=5)

(mg.S.L-1)

S(T)

(n=5)

(mg.S.L-1)

S(aq)

(n=5)

(mg.S.L-1)

PST

influent

PST

effluent

Sampling 1 36.1 1.6 35.2 1.7 30.8 4.4 30.2 3.8 14.5 14.1 370 40 90 14

Sampling 2 30.7 9.3 25.6 9.0 32.8 3.4 28.5 2.7 - -

Sampling 3 36.8 7.8 33.0 8.7 33.9 1.8 29.1 1.2 7.9 12.0

WWTP inlet

FeCl2 dosing

Sampling 1 31.6 6.4 26.5 6.2 29.0 4.5 27.4 4.3 8.2 - 316 19 148 11

Sampling 2 38.1 8.1 33.0 7.4 36.0 5.5 33.2 5.7 5.7 -

Sampling 3 30.7 5.9 25.4 5.3 29.9 2.4 26.4 3.4 2.7 -

71

Figure 18. Measured mean concentration-time profiles of total - Fe(T), P(T), S(T) in PST underflow

under three different sampling events during WWTP inlet and upstream sewer FeCl2 dosing trials

(separated by solid line). Data presents herein represent mean with 95% CI; number of measurements

(n=5) corresponds to the hourly samples taken for 5.0 hr from PST on different sampling days with a

week interval, adopted in line with FeCl2 dosing duration. Here, samplings 1, 2, and 3 refers to

different sampling days for both full-scale dosing trials

72



as volume density (%) of particles. Here, sampling 1 refers to particular pre-designated sampling day,

conducted in line with dosing duration for both dosing trials. Data points correspond to three time

point hourly samples (1 hr, 3 hr, 5 hr) taken from PST. PSDs profiles for other sampling event are

provided in Figure 20

73



as volume density (%) of particles. Data points correspond to three time point hourly samples (1 hr,

3 hr, 5 hr) taken from PST. Here, sampling 2 refers to particular pre-designated sampling day,

conducted in line with dosing duration for both dosing trials

4.3.2 Laboratory mixing-reaction-settling experiments

Near-immediately after chemical addition (Section 4.2.2), the contents of every mixing-reaction-

settling reactor rapidly turned an intense black colour, indicating the formation of FeSx. The DO

readings under simulated in-sewer oxic-to-anaerobic transition conditions were typically 0.180.04

mgO2.L-1 until 60-90 minutes after chemical addition, after which DO decreased to 0 mgO2.L

-1 over

time with mixing. DO readings under simulated anaerobic in-sewer conditions were 0 mgO2.L-1.

Initial pH (7.430.27) of the sewer wastewater used for oxic-to-anaerobic transition tests changed to

74

pH 6.270.16 and pH 8.350.05 with chemical addition, for tests using Fe-salt and Fe-sludge,

respectively. These respective pH values remained approximately constant thereafter. Initial pH

(8.00.02) of the sewer wastewater used for simulated anaerobic tests with Fe-salt decreased to pH

6.400.03 with chemical addition and remained approximately constant thereafter. At these observed

pH values and indicative redox conditions based on DO, the bisulfide pathway was expected to be

dominant for the precipitation of FeSx (Kiilerich et al., 2017; Rickard, 1995), proceeding via a two-

step reaction (Eqs. (16)-(17)) with added Fe3+ being chemically reduced to Fe2+ by added sulfide

forming elemental sulfur (S0), and subsequently Fe2+ precipitating with any remaining sulfide to form

stable FeS precipitate (Hvitved-Jacobsen et al., 2002; Hvitved-Jacobsen et al., 2013; Nielsen et al.,

2005b).

2Fe3+ + HS− → 2Fe2+ + S0 + H+ (16)

Fe2+ + HS− → FeS + H+ (17)

Sulfide may also undergo both chemical and biological oxidation with dissolved oxygen, forming the

sulfate (SO42-) in the sewer wastewater and consuming the minimal available DO in the experiments

(Eq. (18) (ASCE, 1989; Nielsen Asbjørn et al., 2007).

HS− + 2O2 → SO42- + H+ (18)

However, reaction shown in Eq. (18) is expected to occur minimally under oxic-to-anaerobic

conditions, due to low DO availability in these experiments, and is not expected to occur under purely

anaerobic conditions, being completely devoid of O2.

The reactions outlined in Eqs. (16)-(18) in general explains the observed pH decrease in experiments

using Fe-salt and DO consumption with either Fe-salt/Fe-sludge. The pH increase with Fe-sludge (see

Section 4.3.2) was likely due to the dissolution of ferric(oxy)hydroxides (FeOOH or Fe(OH)3)

present in the pre-formed Fe-sludge, as a result of reaction with dissolved sulfide (Eq. (19) (Liu et

al., 2017; S⊘ndergaard et al., 2002), consuming three protons.

2FeOOH + 3H+ + 3HS- → 2FeS + S0+ 4H2O (19)

75

FeOOH or Fe(OH)3 have also been suggested to produce alkalinity in the presence of organic matter

with associated biologically mediated dissolution of iron (oxy)hydroxides (FeOOH or Fe(OH)3) and

formation of Fe2+ (Eq. 20) (Stumm and Morgan, 1996).

4FeOOH + CH2O (organic matter) +H2O → 4Fe2+ + CO2 + 8OH- (20)

This latter reaction could cause the dissolution of iron(III) precipitates to produce Fe2+ that may

remain in solution or precipitate with sulfide as FeSx. The reaction steps given in Eqs. (16)-(20) were

used to interpret results presented in the section below.

Figure 21 shows time trends of measured total iron (Fe(T) = particulate + dissolved) and filtered iron

(Fe(aq)) for the mixing-reaction-settling tests using Fe-salt. Figure 21a and Figure 21c show time

trends of measured Fe(T) while Figure 21b and Figure 21d show time trends of Fe(aq), for the mixing-

reaction-settling tests with FeCl3 as Fe source. Only for oxic-to-anaerobic test conditions (Figure

21a), the measured Fe(T) concentration in supernatant was significantly lower after a 6.0 hr mixing

time as compared to after a 0.5 hr mixing time. With a 0.5 hr mixing time, Fe(T) remained largely

unchanged throughout the experiment, whereas with 4.0 hr and 6.0 hr mixing times, Fe(T) continued

to decrease throughout the experiment. The experiment with 4.0 hr mixing time appeared to follow a

similar trend to the experiment with 6.0 hr mixing time under oxic-to-anaerobic test conditions. In

contrast, with anaerobic test conditions (Figure 21c), Fe(T) remained unchanged during the mixing

period, but declined with subsequent settling or post-settling periods, with an apparent delay in the

Fe(T) decline for the experiment with 6.0 hr mixing time. The decline in Fe(T) during the settling

periods is affected by length of the mixing times under oxic-to-anaerobic conditions. This was further

evidenced by the observed higher semi-quantitative average wt(%) values of Fe observed in bottom-

settled particulate masses subjected to 6.0 hr (i.e. 20.6%) than 0.5 hr (i.e. 11.95%) mixing time.

Similar was the case for wt(%) of S, which was higher for 6.0 hr (i.e. 10.05%) than 0.5 hr (i.e. 8.2%)

mixing time, based on the EDX-based elemental composition analysis. EDX results showed the

presence of strong Fe signals, evidenced by energy peaks in the ranges 0.5 - 1.0 keV and 6.0 - 7.0

keV (Figure 22a-b). This was further supported by the EDX layered maps (Figure 23, Figure 24),

which showed that Fe and S were relatively more prominent in settled solids samples from the test

with 6.0 hr mixing time than with 0.5 hr. In contrast, the relationship is not clear under simulated in-

sewer anaerobic conditions, with a more rapid decline in Fe(T) for experiments with 0.5 hr and 4.0 hr

76

mixing times, as compared to a slightly delayed decline in Fe(T) settling separation with 6.0 hr mixing

time, but after 90 minutes settling, there was no significant difference in Fe(T) between short (0.5 hr)

and long (6.0 hr) mixing-reaction times (p>0.05) (Figure 21c).

Likewise, Fe(aq) initially after chemical addition (t=0) was much lower than Fe(T) in all cases (Figure

21), indicating near-immediate chemical reduction of the majority of added Fe3+ into Fe2+ and

precipitation of Fe2+ as FeSx (Eqs. (16)-(17)). However, the starting Fe(aq) was inconsistent between

the different experiments (t=0, Figure 21b and Figure 21d), possibly due to minor differences in

localised mixing when chemicals were initially added, causing differences in initial reaction extents.

During the mixing period, Fe(aq) continued to decrease in all cases (Figure 21b and Figure 21d), likely

due to additional FeSx precipitation. However, whilst Fe(aq) under anaerobic conditions converged to

a common low final value (Figure 21d) insensitive to length of the mixing period (p>0.05), the final

Fe(aq) value under oxic-to-anaerobic transition conditions was inconsistent with no clear correlation

to the length of mixing period. Moreover, Fe(aq) at the end of the test period was significantly lower

under anaerobic conditions (0.40.1 mg.Fe.L-1) than under oxic-to-anaerobic conditions (2.20.1

mg.Fe.L-1) (Figure 21b and Figure 21d). Under anaerobic conditions with Fe-salt, stable FeS would

have precipitated (Eqs. (16)-(17)), explaining the observed low final value of Fe(aq) in all cases (Figure

21d). However, the results under oxic-to-anaerobic conditions with Fe-salt were somewhat

unexpected. DO at the outset of these tests could have directly oxidized added sulfide into sulfate,

causing some Fe2+ to remain in solution (Eq. (18)). However, this effect was expected to be minimal,

because of low DO. In addition, S(aq) measured at the end of the experiments was not significantly

different from background S(aq) in the sewer wastewater (p>0.05, data not shown). This indicated that

minimal additional sulfate had formed under oxic-to-anaerobic transition conditions and instead that

the majority of added sulfide had precipitated as FeSx. It was hypothesized that iron(III)oxides could

have formed under oxic-to-anaerobic conditions, and may have dissolved and remained in solution

by reductive and chelative effects with organic matter (Eq. (20)) and organic ligands/complexing

agents present in the sewer wastewater (Banwart et al., 1989; Schwertmann, 1991). However, this

hypothesis and these effects need to be further explored in future works, especially for different

stoichiometric ratios of added sulfide to ferric salt dosed under oxic-to-anaerobic transition

conditions, and for different sewage organic matter compositions.

Figure 25a and Figure 25b show time trends of measured Fe(T) and Fe(aq) for the mixing-reaction-

settling tests using pre-prepared Fe-sludge. This Fe source was only tested under oxic-to-anaerobic

transition conditions. In these tests, Fe(T) appeared to be insensitive to mixing-reaction time (Figure

77

25a). With Fe-sludge dosing, Fe(T) settled rapidly, with Fe(T) even decreasing within the mixing

period, even though continuous mixing would be expected to keep Fe-sludge suspended. Similarly,

Fe(aq) concentration remained low throughout the experiment (0.280.04 mg.Fe.L-1), indicating a slow

reduction-dissolution of Fe-sludge in the presence of added sulfide (i.e. minimal re-mobilization).

This showed that the source of Fe being used influenced Fe-fractionation. Specifically, final Fe(aq)

concentrations were substantially lower under oxic-to-anaerobic transition conditions when using Fe-

sludge than with the FeCl3 as Fe source. Similar limitations could apply for FeSx if needing to be re-

oxidized and re-mobilized under pure anaerobic conditions. This may elucidate why final Fe(aq)

concentrations at the end of the experiments under anaerobic conditions with FeCl3 salt as Fe source

and at the end of the experiments using Fe-sludge as Fe source, were comparatively low (Figure 21c

and Figure 25b). These results indicated that with the slow reduction-dissolution of Fe-sludge, sulfide

remained in stoichiometric excess relative to Fe, so that any Fe2+ being re-mobilized rapidly

precipitated with dissolved sulfide to form FeSx thereby maintaining a low Fe(aq) throughout the

experiment (Figure 25b). In this case also, no notable increase was observed in the measured S(aq)

across the experiment (data not shown), indicating minimal formation of additional sulfate during the

experiment. The slow reduction-dissolution of Fe-sludge may not necessarily translate into poor

reactivity towards sulfide in a sewer. For example, previous work of Edwards et al. (1997) dosed Fe-

sludge to a full-scale sewer and did not note any reduced efficacy of this Fe-source type for sulfide

control as compared to what would be expected from sewer-dosed Fe-salts.

Figure 26a-f shows measured PSDs from the mixing-reaction-settling tests using Fe-salt. A number

of similarities were observed among the PSDs of the lab experiments and those of full-scale tests

(Section 4.3.1). The PSDs in both the cases were multi-modal (Table 10) and were generally

dominated by the background suspended solids (e.g. Figure 26a and Figure 26d show background

PSDs). Under oxic-to-anaerobic conditions, some movement of particle volume was observed from

a middle size class (1-100 m) to a larger size class (>100 m) during the experiment (Figure 26a

versus Figure 26b), possibly due to FeSx formation and aggregation, or due to adsorptive coagulation

of background suspended solids by residual Fe(aq) in these tests (Figure 21b). Under anaerobic

conditions, the observed changes in PSD dynamics were much less pronounced than under oxic-

anaerobic conditions, with comparatively minimal change in the PSD of the background suspended

solids (Figure 26d versus Figure 26e). This may reflect a lesser influence of coagulation with Fe(aq)

under anaerobic conditions, due to the low-level Fe(aq) under anaerobic conditions (Figure 21d). As

with the full-scale tests, a much larger modal size class (>1 mm) was present at the end of the mixing

period in some of the experiments, but interestingly, the particles in this modal size class appeared to

78

take some time to form under anaerobic conditions (compare 0.5 hrs vs. 6.0 hrs mixing time, Figure

26e) and only settled out under anaerobic conditions (i.e. not visible in the settled solids in Figure

26c). Overall, there were clear effects of redox conditions on particle size dynamics. However, as in

the full-scale tests, it was difficult to resolve correlations between Fe transformation, and settling

separation behaviour (Figure 21) and observed particle size dynamics (Figure 26), due to a general

prominence of background suspended solids in the measured PSDs.

With mixing-reaction-settling tests using Fe-sludge under oxic-to-anaerobic transition conditions,

measured PSDs of settled solids at the end of the experiments (Figure 27) were similar to PSDs of

the background suspended solids in the sewer wastewater (Figure 26a and Figure 26d), but showed

the formation of a small number of large particles (>1 mm) in the experiment with long mixing period

(6.0 hrs). Details of the observed results of PSD dynamics using Fe-sludge are provided in Table 11.

It is possible that these large particles are FeSx floccules and that these floccules are only able to

aggregate to an adequate size to settle out if given enough mixed reaction time. This would align with

the observations of Gutierrez et al. (2010). This also seems to agree with the observed prominence of

this larger size class in the tests using Fe-salt at anaerobic conditions given a longer mixing time (6.0

hrs, Figure 26f). However, the reason why such floccules would not settle out when using Fe-salt

under oxic-to-anaerobic conditions was not immediately apparent (i.e. size class >1 mm not visible

in Figure 26c). When combined with the full-scale test results, these observations indicate that redox

conditions and in-sewer retention time may have influenced the relative prominence of the larger

modal size class (>1 mm) observed in the measured particle size distributions of the PST effluent in

the WWTP inlet dosing trial (Figure 19b, Figure 20b), as compared to measured particle size

distributions of the PST effluent in the in-sewer dosing trial (Figure 19d, Figure 20d).

79

Figure 21. Concentration-time profiles of mixing-reaction-settling laboratory tests with Fe-salt and

different mixing periods (0.5 hr, 4.0 hr, and 6.0 hr), including (a) Fe(T) and (b) Fe(aq) profiles in

supernatant under simulated in-sewer oxic-to-anaerobic transition conditions; and (c) Fe(T) and (d)

Fe(aq) profiles under simulated in-sewer anaerobic conditions. Error bars indicate calculated standard

deviations (SD) with n=3 in the case of 0.5 hr and 6.0 hr mixing times and n=2 for 4.0 hr mixing time

80

Figure 22. EDX spectra depicting the elemental composition by wt% of the sample subjected to

different mixing time under oxic-to-anaerobic conditions: (a) 0.5 hr; (b) 6.0 hr

81

Figure 23. BEC images for 0.5 hr (top) and 6.0 hr (bottom) mixing under oxic-to-anaerobic condition:

(a) and (b) corresponding EDX chemical maps acquired for the alloying elements in mapped area -

(c) C; (d) O; (e) Mg; (f) Al; (g) P; (h) S and (i) Fe

82

Figure 24. Thermo maps (Quant mapping) for samples of both 0.5 hr (top) and 6.0 hr (bottom) mixing

under oxic-to-anaerobic condition, depicting qualitative element distribution maps

83

Figure 25. Concentration-time profiles of mixing-reaction-settling laboratory tests with Fe-rich water

treatment sludge, including (a) Fe(T) and (b) Fe(aq) profiles in supernatant under simulated oxic-to-

anaerobic transition conditions, respectively. Each data point represents a mean value (n=2) with error

bars being standard deviations

84

Figure 26. Measured particle size distributions for samples collected at different times during the

laboratory mixing-reaction-settling tests using Fe-salt with mixing periods of 0.5 hr or 6.0 hr and

under (a, b, c) oxic-to-anaerobic transition conditions or (d, e, f) purely anaerobic conditions. The

data present volume density (%) of particles

85

Figure 27. Measured particle size distributions for sediment collected at the end of mixing-reaction-

settling laboratory tests under oxic-to-anaerobic transition conditions, for 0.5 hr and 6.0 hr mixing

periods using Fe-rich water treatment sludge. The data herein represent the volume density (%) of

particles

Table 10. Categorizing particles into different size fractions under both tests conditions on using

FeCl3 as iron source. Here, each data corresponds to the mean of 10 replicate measurements (n) = 10

Simulated oxic-to-anaerobic

transition condition Simulated anaerobic condition

PSD

samples

particle size

fractions (m)*

VD** (%)

= 0.5 hr

VD (%) =

6.0 hr

PSD

samples

particle size

fractions (m)

VD (%) =

0.5 hr

VD (%)

= 6.0 hr

1st PSD

1 6.2 6.2

1st PSD

1 4.2 4.1

1-100 84.5 84.5 1-100 90.7 89.7

>100 9.3 9.3 >100 4.9 3.6

2nd PSD 1 5.3 3.5

2nd PSD 1 4.2 3.8

1-100 65.0 73.6 1-100 93.0 83.9

>100 29.2 22.8 >100 2.7 12.2

3rd PSD

1 1.9 2.6

3rd PSD

1 2.9 2.1

1-100 93.3 88.5 1-100 85.3 75.1

>100 4.8 8.8 >100 10.7 22.6

*comparative PSD analyses were also undertaken by estimating the volume density (%) of particles

in different size classes

** VD (%) implies volume density (%)

86

Table 11. Categorizing particles into different size fractions under oxic-to-anaerobic tests conditions

on using Fe-sludge as iron source. Here, each data corresponds to the mean of 10 replicate

measurements (n) = 10

Oxic-to-anaerobic transition test condition using Fe-sludge

PSD sample particle size fractions (m)* VD** (%) = 0.5 hr VD (%) = 6.0 hr

3rd PSD*

1 2.4 1.8

1-100 94.8 84.1

>100 2.8 14.1

*settled solids masses at the bottom of reactor, following end of experiments

** VD (%) implies volume density (%)

4.3.3 Implications

This study demonstrated that extent of in-sewer retention/reaction times and predominantly prevailing

in-sewer redox conditions would largely influence Fe-fractionation/transformation and precipitation

including the changes in primary particle size of Fe-precipitates or overall PSD dynamics occurring

in sewer environment with Fe-dosing. Such phenomenon would subsequently affect the Fe-

availability in sewer bulk phase and hence, amount of Fe-transferability or transport from sewer to

downstream WWTP. These foregoing fundamental aspects in relation to in-sewer Fe-dosing have not

been addressed in previous studies. Interestingly, such observations in terms of Fe-

interactions/availability in sewer bulk phase may vary depending on the type of Fe source types being

used. This was realized in our laboratory experiments (Section 4.3.2). We observed the different

extents of Fe-mobilization and re-immobilization for Fe-salt and Fe-sludge upon exposure to similar

simulated in-sewer condition. In other words, degree of dissolved Fe(aq) mobilizing from freshly

prepared Fe-sludge was relatively restrictive compared to Fe-salt. This implies that different response

may incur in relation to Fe-availability in sewer bulk phase, upon using Fe-sludge instead of Fe-salt

for in-sewer sulfide control upon being exposed to similar in-sewer conditions (more or less oxidized

conditions). Such variability demands further investigation under real scenario in future studies using

Fe-sludge, aiming to understand the Fe-transformation or Fe-release in sewer bulk phase. This

fundamental understanding can be significant in context of waterworks-derived Fe-sludge application

in real sewers and subsequent impact on Fe-transferability to downstream WWTP. In recent years,

there has been growing interest in reusing waterworks Fe-sludge in sewers to gain multiple benefits

in receiving WWTP (Sun et al., 2015). This is because if reusing Fe-sludge in sewers towards

phosphate or sulfide removal is comparably effective akin to Fe-salts, then this would generate

substantial economical and environmental benefits for urban water utilities.

87

These foregoing findings are highly relevant, considering a growing concern for integrated sewer-

WWTP operation and management regarding Fe-salts/Fe-sludge usage in recent years (Gutierrez et

al., 2010; Rebosura et al., 2018; Sharma et al., 2012; Sun et al., 2015). In this context, Rebosura et al.

(2018) had presented multiple beneficial impacts in receiving WWTP in relation to sewer-dosed

FeCl3 via integrated full-scale laboratory system, albeit without incorporating the PST role.

Therefore, this necessitates the full-scale studies in future culminating the sewer network connected

to downstream WWTP (incorporating PST), to further evaluate whether in-sewer Fe-salt dosing akin

to WWTP inlet dosing would result similar multiple benefits in different treatment units or not,

particularly phosphate removal in AS system and sulfide removal in anaerobic digester.

4.4. Conclusion

There has been growing interest in recent years to explore multiple uses of Fe-salts and/or the

beneficial reuse of Fe-sludge in integrated urban wastewater systems. For this, the transformation and

transport of Fe in sewers and via a downstream PST and WWTP would be important, because such

would determine Fe availability in the sewer and various parts of the WWTP (e.g. for phosphate

removal in AS system or sulfide removal in an anaerobic digester). Accordingly, we used full-scale

trials (based on FeCl2 dosing) and controlled laboratory experiments to test the effects of in-sewer

retention, in-sewer redox conditions, and Fe source type (FeCl3 versus Fe-sludge) on Fe

transformation and transport in sewage. From the test results, the following conclusions were drawn:

• In-sewer retention of Fe was minimal in the full-scale trials and Fe separation in the full-scale

primary settler was independent of sewer Fe dosing location. The upstream sewer dosing

resulted in minimal in-sewer Fe retention (i.e. 11% of Fe dosed upstream) when compared

between Fe dosed and Fe reaching the PST. The retention of Fe in the primary sludge

(quantified as a difference between the influent and effluent concentration) was very similar

for the two dosing cases.

• Suspended solids removal in the full-scale primary settler was affected by Fe dosing location

in a sewer, but could not be significantly correlated with Fe retention, due to large

measurement variability at full-scale.

• In the laboratory experimental studies, Fe-sludge settled rapidly, but reactive-dissolution and

re-precipitation in the presence of added sulfide appeared to be slow as compared to the near-

immediate reaction and precipitation of Fe-salt with added sulfide.

88

• Particle size distributions (PSDs) were influenced by settling in a full-scale PST, however the

pre-mixing time (or in-sewer retention time) did not exhibit significant effect on the observed

PSDs. Likewise, PSDs were influenced by redox conditions and mixing-reaction time at lab-

scale. However, it was difficult to correlate PSD dynamics with Fe separation behaviour,

because of a general prominence of background suspended solids in the measured PSDs.

• An increase in modal size classes in the PSD was observed in the lab experiments, thought to

be due to a coagulation effect of dissolved Fe on background suspended solids or FeSx, and a

larger modal size class (>1 mm) was observed in the measured PSDs and its prominence and

settleability were influenced by redox conditions.

Overall, in the laboratory experimental studies, Fe-transformations and transport (settleability) were

influenced by mixing-reaction time (simulated in-sewer retention time), redox conditions, and Fe

source type (e.g. Fe-salt/Fe-sludge), and this is important for Fe transformations and transport in an

urban wastewater management system. These factors must be considered when choosing strategies

to achieve multiple benefits of sewer-dosed Fe across integrated urban wastewater systems. There is

a need for future detailed full-scale studies using Fe-sludge and Fe-salts dosed to a sewer and tracking

Fe in the sewer and via the connected downstream WWTP with PST over extended measurement

periods to obtain data with greater statistical certainty. This may help identifying seemingly important

effects of Fe source type and sewer dosing location on Fe retention in the primary settling tank and

its availability in downstream wastewater treatment units.

89

Chapter 5

Unravelling the influences of sewer-dosed iron salts on

activated sludge properties with implications on

settleability and dewaterability

This chapter has been published and modified for incorporation into Chapter 5 of this thesis: Sohan Shrestha, Keshab

Sharma*, Zhongwei Chen, Zhiguo Yuan (2019). Unravelling the influences of sewer-dosed iron salts on activated sludge

properties with implications on settleability, dewaterability and sludge rheology. Water Research, 167, 115089

(https://doi.org/10.1016/j.watres.2019.115089)


90

5.1. Introduction

Iron(Fe)-salts used in sewers for sulfide control could have far-reaching benefits in terms of

phosphorus removal in bioreactors and even sulfide control in digester (Rebosura et al., 2018). In an

integrated operation of collection and treatment systems, Fe-salts added to sewers controls sulfide

through precipitation. The precipitated-iron, which later undergoes chemical changes in the bioreactor

and becomes available for phosphate precipitation, also may interact with sludge affecting the

activated sludge properties including settling and dewatering performances. Both settleability and

dewaterability are the key parameters and improvement in these parameters could influence not only

the bioreactor operation, also overall WWTP operation and sludge management. Effluent quality of

WWTP is largely dependent on good settleability of activated sludge (Wilén et al., 2010). Likewise,

better sludge dewaterability reduces sludge volume and hence eases heavy burden of sludge

management (Li et al., 2016). Dewatering of activated sludge would be particularly important in a

case where activated sludge systems produce surplus sludge which has to be dewatered prior disposal

(Brix, 2017; Park et al., 2006). Thus, it entails the investigation of the changes in key activated sludge

properties due to sewer-dosed Fe-salt and subsequent impacts on settleability and dewaterability of

activated sludge.

Improvement in settleability of activated sludge due to sewer-dosed FeCl3 had been reported

(Rebosura et al., 2018). However, the impacts on other sludge properties affecting the settleability

and the mechanism leading to such an improvement has not been fully understood. Similarly, possible

alteration to dewaterability of activated sludge is not yet clear and factors responsible for the alteration

are also not clear. When aiming to achieve multi-stage beneficial uses of Fe-salt dosing in an

integrated urban wastewater system, clear understanding of the impacts of iron content on both

settling and dewatering properties of activated sludge including the associated underlying possible

mechanism can be significant in terms of wastewater treatment and sludge management. However,

none of the studies till date have reported the unintended beneficial consequences in terms of both

activated sludge settleability and dewaterability upon discharging the iron containing sewer effluents

into a bioreactor. Developing an understanding of key parameters affecting sludge characteristics and

their interactions with sludge settleability and dewaterability would help understanding the

mechanism behind the changes in these properties and allow the examination of the impacts of iron

dosing in a holistic manner.

91

Different activated sludge properties, particularly the content and composition of EPS, cations

distribution pattern, particle size distribution, and rheological properties, have been reported to impact

sludge settleability and dewaterability (Dentel et al., 2005; Higgins and Novak, 1997b; Niu et al.,

2013; Pham et al., 2010; Ratkovich et al., 2013; Sheng et al., 2010). Understanding of the changes in

these properties due to Fe-salt dosing would allow quantitative evaluation of potential changes in

sludge settleability and dewaterability. Based on this understanding, the underlying mechanisms

responsible for the change in sludge settleability and dewaterability could be established.

Significant role of EPS in relation to bioflocculation, settling, and dewatering of activated sludge has

been reported (Niu et al., 2013; Sheng and Yu, 2006). Increased loosely-bound/soluble-EPS content

is reported to enhance the SVI values (Sheng et al., 2010), whereas the reduced total EPS content is

associated with the improved sludge dewaterability (Chen et al., 2001). In this context, Niu et al.

(2013) have reported changes in the S-EPS, LB-EPS, and TB-EPS concentrations, owing to strong

affinity of Fe3+ ions towards EPS. Further, cations distribution in different EPS fractions could also

influence the activated sludge properties due to ability of cations in binding with the negatively

charged biopolymers (Higgins and Novak, 1997a; b). Specifically, monovalent-to-divalent (M+/D++)

cations ratio of sludge flocs is reported to affect the sludge settling and dewatering properties (Higgins

and Novak, 1997a; b). Albeit the correlation between sludge EPS content/composition and M+/D++

cations ratio of EPS fractions with sludge settleability and dewaterability has been understood, the

knowledge and the role of presence of iron, specifically the iron carried over from the sewers in a

precipitated form into the activated sludge unit, on the settleability and dewaterability is very limited.

If available, it is only for direct Fe-salt addition to the bioreactor (Oikonomidis et al., 2010). Hence,

this demands a better understanding in these aspects concerning influence of sewer-dosed FeCl3.

Particle size distribution (PSD) also plays an important role in sludge settleability and dewaterability

owing to its influence on sludge viscosity (Pham et al., 2010). Increased sludge particles/flocs size

will cause the reduction in surface shear stresses encountered during dewatering process.

Consequently, the specific cake resistance will be smaller (Herwijn, 1996). Direct dosing of iron salts

to the activated sludge unit have been reported to influence the morphological characteristics of

activated sludge (Li, 2005; Oikonomidis et al., 2010), however impacts of sewer-dosed FeCl3 on

morphology of activated sludge remains to be investigated.

92

Sludge rheology deals with the description of the internal sludge molecular structure including

prediction and quantification of sludge flowability (Dentel et al., 2005). Hence, sludge rheology

influences the hydrodynamic processes involved in sludge handling (Ratkovich et al., 2013), which

in turn may influence the sludge dewaterability. This implies understanding of sludge rheology

facilitates in assessment of sludge stabilization or dewaterability and also in selection of design

parameters concerning sludge storage, handling/transportation (Lotito et al., 1997). For instance,

sludge viscosity, one of the key rheological properties, is reported to impact oxygen mass transfer to

flocculated biomass in an aeration tank (Hasar et al., 2004). Relative network strength of sludge and

yield stress (y) are other important rheological parameters, associated with sludge dewaterability

(Örmeci and Abu-Orf, 2005). Effective dewatering relies on the strength of sludge aggregates. Lower

the value of sludge network strength, smaller is the deformation resistance against the applied shear

stress and vice-versa. Reduced deformation resistance promotes the release of incorporated water

within the sludge aggregates (Ormeci et al., 2004; Yen et al., 2002). These rheological properties

might be impacted by the long-term exposure of iron due to its interaction with the sludge flocs.

Comprehensive assessment of likely changes in sludge rheological properties under sewer-dosed

FeCl3, is expected to provide an insight into the impacts on sludge dewaterability.

Any alteration in the morphological, physicochemical and rheological properties of activated sludge

due to the presence of iron could therefore significantly influence both the sludge settling and

dewatering properties. However, such alterations and resulting influences due to the iron salt dosing

to sewer are not clearly understood. This study was therefore conducted to: (i) assess the impacts of

FeCl3 addition to a sewer location upstream of the activated sludge unit in both dewatering and

settling performances of activated sludge; and (ii) understand the impacts on other activated sludge

properties and identify the possible mechanisms responsible for the changes in sludge dewaterability

and settleability. In order to achieve this, several related properties of both iron-conditioned and

unconditioned activated sludges were examined, and a comparison was made between the two sludge

types with respect to these properties to develop the understanding of potential impacts on settleability

and dewaterability.

5.2. Materials and methods

5.2.1 Overview of laboratory apparatus and sludge sources

Activated sludges were collected from an integrated laboratory system consisting of two separate

lines, one experimental and another a control line. Each system incorporated a number of reactors

93

connected in series mimicking a rising main sewer, buffer tank and a SBR (Figure 28), as outlined in

Section 3.1 (Chapter 3). The sewer reactor was fed 10 L of domestic sewage per day via adopting

four pumping events, i.e. 2.5 L every 6.0 hr. Characteristics of domestic sewage (i.e. sewer influent

composition) are provided in Table 12. The sewer reactor of the experimental line was intermittently

fed with FeCl3 stock solution (only during pumping events) at a concentration of 10 mg.Fe.L-1. Sewer

effluent was pumped to a buffer tank, prior to being fed to experimental SBR. Wastewater volume of

2.5 L was pumped to the SBR from the respective buffer tanks (which accumulated the sewer

effluents) during the first 8 min of the anoxic phase. Retention time for the buffer tank was 5 min.

Further information regarding the influent compositions of both experimental and control SBR

reactors is provided in Table 12. Activated sludges sourced from both experimental (SBR-E) and

control SBR (SBR-C) reactors, were denoted as ‘iron-conditioned’ and ‘unconditioned’ activated

sludge, respectively. The two integrated sewer-SBR-thickener-AD systems were continuously

operated for slightly more than 12 months, culminating two major phases: Phase I = baseline phase

(130-240 days, 4th month to 8th month) and Phase II = experimental phase (i.e. post-FeCl3 dosing in

sewer reactor, 242-355 days, 8th month to 12th month). Herein, we were particularly focused on

assessing the changes in key sludge properties concerning long-term exposure of Fe for the activated

sludge system. Accordingly, iron-conditioned and unconditioned activated sludge samples were

sampled during the 3 to 4 months period after initiation of FeCl3 dosing to sewer reactor. Requisite

samples were sampled twice per week from respective SBR reactors.

94

Figure 28. Schematic representation of experimental set up employed for this study, depicting both control and experimental lines

95

Table 12. Characteristics of domestic sewage (i.e. influent composition of sewer reactors) including influents of SBR-E and SBR-C reactors. Other than

stated values presented correspond to the mean in replicates, given with estimates of error (±) at the 95% confidence level

Dif

fere

nt

com

ponen

ts

Analyzed

fractions

Fe

(mg. Fe.L-1)

P

(mg. P.L-1)

S

(mg. S.L-1)

NH4-N

(mg. N.L-1)

PO4-P

(mg. P.L-1) Dissolved sulfur species (mg. S.L-1)

Soluble COD

(mg.COD.L-1)

Total

COD

(mg.COD.L-1)

HS−

SO32−

SO42−

S2O32−

Dom

esti

c

sew

age

Total* 0.18 0.03 9.47 0.53 19.50

0.49

55.22 2.7 7.33 0.57 1.14

0.03

0.10

0.02

14.13

0.57

0.39

0.17

290.5 ± 19.5 625.9 ± 20.9

Filtered** N.D. 5.60 0.0 18.02

0.20

SB

R-C

infl

uen

t

7.5 ± 0.3 8.2 ± 0.4 11.1 ± 0.2

Filtered 0.1 ± 0.0 280.0 ± 8.2 595.0 ±10.5

6.3 ± 0.3 4.3 ± 0.4 10.0 ± 0.3

238.4 ± 9.2 600.0 ±10.0

SB

R-E

infl

uen

t

Filtered 1.0 ± 0.3

*Total concentrations correspond to particulate + dissolved fractions = Fe(T)

**Filtered samples with 0.22 m membrane filter, filtered concentrations correspond to dissolved fractions = Fe(aq) N.D. = non-detectable concentration (<0.01), meaning below the limit of quantification (LOQ) of instrument

96

5.2.2 Experimental procedures

Activated sludges collected from both SBRs were used for the comparative analyses herein. Different

physicochemical, morphological, and rheological properties of the activated sludge samples were

investigated. Nonetheless, likely changes in microbial communities in iron-conditioned and

unconditioned activated sludges was also investigated (see Figure B1, Appendix B). However, each

sample used for analyzing the physiochemical properties, was not repeatedly used for analyzing the

changes in sludge morphology nor rheology. Albeit the key activated sludge properties are expected

to vary with the time after the start of in-sewer FeCl3 dosing, especially during the initial days of

dosing, the study focused on the impacts during steady operation and hence the changes in activated

sludge properties with the function of time was not investigated. In other words, changes in sludge

properties as a function of time (e.g. post one month, two months, half year or even a year) were not

assessed once the Fe was introduced to the system. It would be interesting to evaluate the temporal

effect of Fe dosing on the change of sludge settling and dewatering performances. This is because

downstream treatment units were being continuously fed with the Fe-rich sewer effluent and hence

the proportions of Fe content in the sludge are expected to vary with the time after the start of in-

sewer Fe-salt dosing. Other than the influence on sludge properties during wastewater treatment

owing to in-sewer Fe-salt dosing, downstream effects on bioreactor performance incorporating

different parameters were also monitored (see Appendix C).


Different parameters were analyzed for both unconditioned (SBR-C) and iron-conditioned (SBR-E)

activated sludges, which include:

• Total suspended solids (TSS), volatile suspended solids (VSS), total solids (TS), volatile

solids (VS)

• Sludge settleability in terms of SVI values

• Sludge dewaterability in terms of dewatered sludge cake solids content (%) including the lab-

scale MCI values. The MCI values evaluated as a function of mixing intensity (rpm),

centrifugation time (t) and combination of both (gt or g×t). Here, times gravity (or centrifugal

force) ‘g’ is related to centrifuge rotating speed and rotor radius (r) and this value was

computed as: (rpm/1000)2×r×1.118 (To et al. 2015).

• Volume-weighted PSDs

• Fractal dimension Df values, ratio of hydrodynamic radius (RH) to the radius of aggregate (RA),

97

and aggregate structure factor (S)

• Bound water content

Details of the methods employed for the aforementioned parameters are elaborated in Sections 3.4

and 3.8 (Chapter 3). The BWC of activated sludges was determined using a Q2000 DSC analyzer,

Q2000 (TA, USA). Here, DSC measurements were carried out using freezing-heating method (Wang

et al., 2012). The mass of sludge sample used in this analysis varied in the range of 12.8-14.6 mg.

Heat absorption was quantified by integrating the peak area under the endothermic curve obtained

during DSC test, owing to correlation between sludge water content and the enthalpy value measured

by DSC curves (Wang et al., 2012). Besides, secondary electron images (SEI) of both iron-

conditioned and unconditioned activated sludges were also taken using scanning electron microscope

(SEM) to explore the changes in surface morphology. Details of the method employed are provided

in Section 4.2.3 (Chapter 4).

5.2.4 EPS extraction and analysis

EPS fraction extraction and analysis

The heat extraction method, used in previous studies (Li and Yang, 2007; Morgan et al., 1990), was

used to extract different EPS fractions from activated sludges obtained from both SBRs (SBR-E,

SBR-C) after a minor modification. Further details of this method are provided in Section 3.5

(Chapter 3).

Cations concentrations and their relative distributions for each extracted EPS fraction were also

evaluated in terms of M+/D++ cations ratio. Further details of this method are provided in Section 3.5

(Chapter 3).

Compositional analysis of EPS fractions

Details of the method used for compositional analysis of both unconditioned and iron-conditioned

activated sludges are provided in Section 3.5 (Chapter 3). Here, F-EEM spectral analysis focusing on

the changes in fluorescing substances (aromatic tyrosine protein-like, aromatic trypotophan protein-

like, HA-like, SMP-like, and FA-like) was conducted to investigate changes in the organic

composition of extracted EPS fractions. Nonetheless, EPS was also quantified by measuring the PN

98

and PS concentrations in the extractant as described in Section 3.5 (Chapter 3). Although it would

have given additional information, especially in relation to the lysis of bacterial cells or EPS

disruption, we did not attempt to quantify the nucleic acids concentrations in the extracted EPS

fractions herein.

5.2.5 Rheological tests

Rheological tests were carried out using a rheometer (Physica MCR102 Modular Compact


vane. Prior to each measurement, 50 mL sludge sample was transferred to the measuring cup in which

the vane was immersed. Temperature was maintained at 25±0.01°C using a Peltier control during the

rheological tests. Here, both steady shear and dynamic shear rheological tests were undertaken to

assess the changes in rheological properties of both activated sludges. Steady shear rheological tests

encompass the CSR, hysteresis loop, and CSS tests. Also, relative sludge network strength in both

sludges was also estimated based on torque rheology measurement described elsewhere (Örmeci and

Abu-Orf, 2005; Ormeci et al., 2004). Similarly, dynamic shear (or oscillatory) tests incorporate strain

sweep (or strain amplitude sweep, SAS) test, FS test, including creep test. Details of the methods

employed for all these rheological tests are provided in Section 3.7 (Chapter 3).

5.2.6 Statistical analysis

Mean values, associated SD and SEM values were calculated for a number of data sets. Student’s t-

test with Welch’s correction and 95% CI was applied to determine whether the difference between

the observed mean values of both activated sludges (SBR-E and SBR-C) pertinent to different

properties are statistically significant or not, which was judged based on the p-values (with p<0.05

indicating statistically significant differences and opposite for p>0.05). All statistical tests were

undertaken using GraphPad Prism software, version 8.1.0 (GraphPad Software, San Diego, USA).

5.3. Results

5.3.1 Variation in sludge settleability and dewaterability

Settleability of both iron-conditioned and unconditioned activated sludges was evaluated in terms of

SVI. The total iron Fe(T) concentrations in the experimental and control SBRs were

228.8±22.0 mg.Fe.L-1 (50.5±4.9 mg.Fe (g.TSS)-1) and 20.1±5.2 mg.Fe.L-1 (5.4±1.4 mg.Fe (g.TSS)-1),

respectively. We observed the SVI value of iron-conditioned sludge as 47.44.7 mL.g-1 (N=5),

99

whereas that of unconditioned sludge was 69.96.2 mL.g-1 (N=5). Mean difference in SVI values

between both activated sludges was statistically significant (p<0.05). A similar comparison was made

for dewaterability of the two activated sludges measured in terms of cake solids content (%) and the

results are shown in Figure 29a. Clearly, the iron-conditioned activated sludge exhibited much

improved dewaterability by 37.9±7.3%. Mean difference in cake solids content (%) between the two

activated sludges was also statistically significant (7.8±1.2%, p<0.05). To investigate the variability

in cake solids content (%) in both sludges under varying mixing intensity (rpm) and centrifugation

time (t), a new lab-scale modified centrifugal method, MCI (Higgins et al., 2014) was employed. The

MCI values thus obtained were used to evaluate the dewaterability of both sludges as a function of

mixing intensity (rpm), centrifugation time (t) and combination of both (gt). We found that the

maximum solids cake concentration achievable by the centrifugation method under varying mixing

intensity (rpm), centrifugation time (t) or combination of both (gt), was higher for iron-conditioned

activated sludge Table 13.

These results suggest a synergy between indirect FeCl3 dosing and improved sludge settleability and

dewaterability. This could possibly be attributed to the underlying favorable changes in key activated

sludge properties (i.e. physicochemical, morphological and rheological) owing to Fe-conditioning. In

order to develop an understanding of the possible changes in these sludge properties leading to the

improved settleability and dewaterability and identify the associated mechanism, a comparative

assessment in relation to physicochemical, morphological and rheological characteristics was

conducted for both sludges. This is discussed in the following sections.

100

Figure 29. (a) Changes in dewatered cake solids content (%): data represents meanSEM (N=3); (b)

variations in concentrations of S-EPS, LB-EPS and TB-EPS: SBR-E (N=5) and SBR-C (N=5); (c)

variations in concentrations of protein (PN): SBR-E (N=2) and SBR-C (N=2); (d) variations in

concentration of polysaccharides (PS): SBR-E (N=2) and SBR-C (N=2). Here, each data represents

mean values (N=2)

101

Table 13. Variation in the dewatered cake solid contents (%) in iron-conditioned (SBR-E) and

unconditioned (SBR-C) activated sludges as function of mixing intensity (rpm), centrifugation time

(t) and gt values

Mixing time (min) Cake solids content (%)

(SBR-E)

Cake solids content (%)

(SBR-C)

Mean SD* n** Mean SD n

5 5.07 0.07 2 4.07 0.32 2

10 20.5 1.1 3 12.6 1.9 3

20 1.7 0.1 2 1.58 0.05 2

Mixing intensity (rpm) Cake solids content (%)

(SBR-E)


(SBR-C)

Mean SD n Mean SD n

1000 3.77 0.41 3 3.25 1.76 3

2000 4.87 0.85 3 4.22 1.83 3

3750 20.5 1.1 3 12.6 1.9 3

gt values Cake solids content (%)

(SBR-E)


(SBR-C)

Mean SD n Mean SD n

139392.24 3.77 0.41 3 3.25 1.76 3

557568.96 4.87 0.85 3 4.22 1.83 3

980101.69 5.07 0.07 2 4.07 0.32 2

1960203.4 20.5 1.1 3 12.6 1.9 3

3920406.8 1.7 0.1 2 1.58 0.05 2

*SD – standard deviation;

** n – number of measurements

5.3.2 Changes in content and composition in EPS fractions

Figure 29b shows the differences in the concentration of different EPS fractions in both sludges.

Concentrations of all the EPS fractions (S-EPS, LB-EPS, and TB-EPS) were higher in unconditioned

sludges (SBR-C) than the iron-conditioned ones (SBR-E). Measured mean concentrations of S-EPS,

LB-EPS, and TB-EPS in iron-conditioned activated sludge (meanSEM, N=5) were 2.8±0.3, 9.3±4.6

and 17.0±4.8 mg.TOC(g.VSS)-1, respectively. Likewise, measured mean concentrations of S-EPS,

LB-EPS, and TB-EPS in unconditioned activated sludge (meanSEM, N=5) were 16.2±6.1, 23.3±9.2

and 28.3±8.8 mg.TOC(g.VSS)-1, respectively. The mean difference in terms of S-EPS concentrations

between unconditioned and iron-conditioned activated sludge was statistically significant (p<0.05).

Unlike, this was not the case with both LB-EPS (p>0.05) and TB-EPS concentrations (p>0.05).

Measured mean concentrations of total EPS content in iron-conditioned and unconditioned activated

sludge (meanSEM, N=5) were 29.1±1.1 and 67.7±17.3 mg.TOC(g.VSS)-1 respectively, indicating

102

statistically significant mean differences of 38.6±17.3 mg.TOC(g.VSS)-1 (p<0.05) between the sludge

samples.

F-EEM depicts the spectral information in relation to chemical compositions of EPS matrices in

sludge flocs. The FRI parameters employed for the quantification of F-EEM are shown in Table 14.

F-EEM spectra of EPS fractions of iron-conditioned and unconditioned sludge samples are shown in

Figure 30, which illustrated changes in the fluorescence intensities (FI) of EPS fluorophores by sewer-

dosed FeCl3. The FI corresponding to different fluorophores of EPS fractions of iron-conditioned

activated sludge clearly showed marked changes (Table 15). We found that FI values of both aromatic

protein tyrosine- and tyrosine-like substances in different EPS fractions was weak in iron-conditioned

activated sludges than the unconditioned sludges. Likewise, FI values of both FA-like and HA-like

substances was relatively higher in iron-conditioned activated sludges than the unconditioned ones.

These suffices the changes in organic composition of EPS fractions between the activated sludges

further highlighting decreased protein-like substances and increased humics in iron-conditioned

activated sludge. This is significant because the decrease in protein-fraction and the increase in humic

substances in EPS fractions both influence sludge dewaterability (Yu et al., 2010).

Semi-quantitative F-EEM analyses indicate possible reduction in protein (PN) content in iron-

conditioned activated sludges (Table 15). The PN content of EPS is directly proportional to FI values

(Henderson et al., 2009). For further confirmation, both soluble proteins (PN) and polysaccharides

(PS) contents of both activated sludges were quantified using colorimetric techniques (Figure 29c-d).

Clearly, the iron-conditioned activated sludges showed lower soluble PN and PS contents than

unconditioned sludges. Average soluble PN contents (mg BSA/g VS) in S-EPS, LB-EPS, and TB-

EPS fractions of the iron-conditioned sludge were lower by 46.7%, 46.3%, and 41.1%, respectively.

Similarly, average soluble PS contents (mg glucose/g VS) in S-EPS, LB-EPS and TB-EPS fractions

of the iron-conditioned activated sludge were lower by 41.3%, 44.7%, and 29.3%, respectively.

Reduction in PN and PS contents in iron-conditioned sludge can positively influence sludge

dewaterability considering the high water-holding capacity by PN fractions in sludge (Cetin and

Erdincler, 2004; Sponza, 2002).

103

Table 14. FRI parameters for operationally defined EEM regions including multiplication factor

specific to each region

EEM

regions

Excitation

(nm)

Emission

(nm)

N of EEM data

points per region

Projected excitation-

emission area (nm2)

multiplication

factor (MFi)

Region I

[P1] 200-250 280-330 1000 2500 10.52

Region II

[P2] 200-250 330-380 1000 2500 10.52

Region III

[FA] 200-260 380-500 2880 7200 3.6528

Region IV

[SMP] 250-280 310-380 840 2100 12.5238

Region V

[HA] 280-380 380-500 4800 12000 2.1917

Summation 10520 26300

104

Figure 30. (a)-(b) EEM spectra of different EPS components of two iron-conditioned (SBR-E1, SBR-E2) (top-half) and unconditioned (SBR-C1, SBR-

C2) (bottom-half, separated by dotted line) sludges. Each set of samples (SBR-E1 and SBRC-1, SBR-E2 and SBR-C2) were sampled weekly from

respective experimental and control SBR reactors

105

Table 15. Influences on intensities of fluorescence spectral parameters of different EPS fractions of both activated sludges. Here, all samples diluted 20

times. Sludge SBR-E1 was sampled in conjunction with SBR-C1 at same time period from continuously operated both reactors; similar was the case for

SBR-E2 and SBR-C2, i.e. each set of samples were sampled weekly from respective experimental and control SBR reactors

Fluorescence regional integration (FRI) parameters Iron-conditioned (SBR-E1, SBR-E2) Unconditioned (SBR-C1, SBR-C2)

Organic

components

EEM

Regions

Excitation (nm) Emission (nm) Samples** S-EPS LB-EPS TB-EPS Samples** S-EPS LB-EPS TB-EPS

Aromatic

protein

(tyrosine-like)

P1 200-250 280-330 SBR-E1 8.1 16.0 19.0 SBR-C1 9.6 17.7 24.1

SBR-E2 9.9 22.3 25.6 SBR-C2 8.4 22.7 27.5

Average 9.0 19.1 22.3 Average 9.0 20.2 25.8

Aromatic

protein

(tryptophan-

like)

P2 200-250 330-380 SBR-E1 30.0 39.8 46.9 SBR-C1 33.1 37.6 41.7

SBR-E2 27.5 38.6 34.7 SBR-C2 25.9 40.0 42.9

Average 28.7 39.2 40.8 Average 29.5 38.8 42.3

Fulvic acid

(FA)-like

FA 200-260 380-500 SBR-E1 29.5 20.7 12.8 SBR-C1 28.8 19.7 12.0

SBR-E2 34.2 14.5 16.4 SBR-C2 30.7 14.2 10.1

Average 31.9 17.6 14.6 Average 29.8 16.9 11.0

Soluble

microbial

product (SMP)-

like

SMP 250-280 310-380 SBR-E1 15.5 13.7 17.5 SBR-C1 14.2 14.3 18.8

SBR-E2 10.9 19.2 16.2 SBR-C2 15.5 17.0 15.7

Average 13.2 16.5 16.9 Average 14.8 15.7 17.2

Humic acid

(HA)-like

HA 280-380 380-500 SBR-E1 16.9 9.7 3.8 SBR-C1 14.3 10.7 3.4

SBR-E2 17.5 5.4 7.1 SBR-C2 19.5 6.1 3.8

Average 17.2 7.5 5.4 Average 16.9 8.4 3.6

106

5.3.3 Changes in cations distribution in EPS

Figure 31a shows the changes in M+/D++ cations ratio of both iron-conditioned (SBR-E) and

unconditioned (SBR-C) activated sludges. This M+/D++ cations ratio was calculated based on the

concentrations of monovalent (K+, Na+) and divalent (Mg2+, Ca2+) cations. Iron-conditioned sludges

showed decreased M+/D++ ratios in LB-EPS and TB-EPS fractions including mixed liquor.

Figuratively, almost all monovalent K+ concentrations in iron-conditioned (1.4 mEq.L-1, N=2) and

unconditioned (1.5 mEq.L-1, N=2) activated sludges, were only observed in the extracted three EPS

fractions (S-EPS, TB-EPS, LB-EPS) of sludge but not in pellet fraction. For divalent cations (Mg2+,

Ca2+), 1.3 mEq.L-1 of the total Mg2+ concentration (3.4 mEq.L-1, N=2) was concentrated in the pellet

fractions of iron-conditioned sludge while rest were found to be distributed in other extracted EPS

fractions. However, only 0.5 mEq.L-1 of the total Mg2+ concentration (2.4 mEq.L-1, N=2) was

concentrated in the pellet fractions of unconditioned sludge. On average 3.8 mEq.L-1 and 0.9 mEq.L-

1 of the total Ca2+ concentrations in iron-conditioned (5.7 mEq.L-1, N=2) and unconditioned (2.7

mEq.L-1, N=2) sludges, were present in their pellet fraction, respectively. Relatively, we observed the

higher abundance of divalent cations concentrations in pellet fraction of iron-conditioned sludge in

compared to unconditioned sludge, but this was not case in distribution of monovalent cations. On

contrary, concentrations of trivalent cations (Al3+, Fe3+) were primarily concentrated in pellet fraction

but were negligible in other EPS fractions. Figuratively, 87.7% of 0.6 mEq.L-1 (N=2) and 78.0% of

0.4 mEq.L-1 (N=2) of total Al3+ concentrations were concentrated in pellet fractions of iron-

conditioned and unconditioned sludges, respectively. Akin, 99.6% of 10.7 mEq.L-1 (N=2) and 98.6%

of 0.2 mEq.L-1 (N=2) of total Fe3+ concentrations were concentrated in pellet fractions of iron-

conditioned and unconditioned activated sludges, respectively. These analyses suggest divalent and

trivalent cations remained firmly bound within the sludge flocs while monovalent cations were freely

distributed at the outer parts of both activated sludge flocs (Table 16). This is further elucidated by

modified conceptual representation depicting changes in activated sludge matrix due to changing

cations distribution (Figure 6). We found concentrations of divalent cations (considered herein) in all

EPS fractions were relatively higher in iron-conditioned sludges (Table 16). These divalent/trivalent

cations firmly associated within sludge flocs actually promote the sludge flocs strength and stability

(Li et al., 2012). Expectedly, we observed higher inorganic solid fractions in iron-conditioned sludges

than unconditioned ones (Table 17). Such increment in the sludge inorganic fractions can actually

contribute in the enhancement of sludge settleability (Peeters, 2010).

107

Figure 31. (a) Variations in M+/D++ cations ratio values: SBR-E (N=3) and SBR-C (N=3). Here, error

bar represents meanSEM; (b) Changes in size distribution of particles in activated sludges (N=6):

iron-conditioned (SBR-E) and unconditioned sludges (SBR-C). Here, error bar represents the

meanSEM

Table 16. Monovalent and divalent cations concentrations in iron-conditioned (SBR-E1, SBR-E2)

and unconditioned (SBR-C1, SBR-C2) sludges

Samples* Cations

(mEq.L-1)

Activated sludge

(mixed liquor)

EPS fractions

S-EPS LB-EPS TB-EPS

SBR-E1 K+ 1.93 0.95 0.22 0.75

Na+ 7.51 7.07 18.41 17.81

Mg++ 3.46 1.38 0.29 0.32

Ca++ 5.82 1.33 0.34 0.27

SBR-C1 K+ 1.51 0.86 0.12 0.54

Na+ 6.93 6.84 18.63 17.64

Mg++ 2.36 1.34 0.21 0.27

Ca++ 2.75 1.40 0.25 0.20

SBR-E2 K+ 1.85 1.25 0.22 0.30

Na+ 7.33 6.87 16.26 17.08

Mg++ 3.24 1.67 0.31 0.25

Ca++ 5.60 1.23 0.30 0.27

SBR-C2 K+ 1.51 1.12 0.15 0.28

Na+ 7.45 6.96 16.88 17.58

Mg++ 2.36 1.61 0.20 0.16

Ca++ 2.66 1.44 0.20 0.17

*Here, sample SBR-E1 was sampled in conjunction with SBR-C1 from respective SBR reactors

and similar was in case of SBR-E2 and SBR-C2, such that sampling time of each set of samples

was different, i.e. each set of samples were sampled weekly from respective SBR reactors

108

Table 17. Inorganic fractions content analysis

Activated sludge

samples**

Volatile solids

fractions (%)

Volatile solids

fractions (%)

(average)

Inorganic

fractions (%)

Inorganic

fractions

(%)

(average)

SBR-E1* 43.26

42.87

56.73

57.12

42.48

57.51

SBR-C1 48.33

48.28

51.66

51.72

48.22

51.77

SBR-E2 43.05

42.89

56.95

57.11

42.74

57.26

SBR-C2 48.65

48.41

51.35

51.59

48.18

51.82

45.45

54.55

*numeric presented corresponds to the different set of samples;

** Here, sample SBR-E1 was sampled in conjunction with SBR-C1 from respective SBR reactors

and similar was in case of SBR-E2 and SBR-C2; such that sampling time of each pairs was

different, i.e. each set of samples were sampled weekly from respective SBR reactors

5.3.4 Changes in particle size distribution and bound water content

Figure 31b compares the PSD curve for both the iron-conditioned and unconditioned activated

sludges. The presented PSD curve of each sludge, correspond to the average of six different samples

sampled at different time from respective SBRs albeit each set of samples (i.e., sample SBR-E1 and

SBR-C1) were taken in conjunction with each other (Table 18). The PSD curve of both sludges were

‘monomodal’ in nature, however, size distribution in iron-conditioned sludges was relatively more

left-skewed suggesting the formation of larger-sized particles. This is consistent with the mean

particle size Dv50 measurements (Table 18). The Dv50 (meanSEM, N=6) values were 116.06.7 m

and 102.02.1 m for iron-conditioned and unconditioned sludges, respectively. However,

differences between means in Dv50 between the sludges were not statistically significant (p>0.05).

This is further evidenced by the SEI images obtained at different magnifications (Figure 32). Surface

109

morphology of iron-conditioned activated sludge exhibited the aggregated structure unlike in

unconditioned sludge.

The comparative PSD analyses were also undertaken by estimating the volume density (%) of

particles in different size classes (Figure 33). Volume density (%) (N=6) of supracolloidal (0-100

µm) and settleable particles (100-400 µm) were 47.41.3% and 52.61.3% in unconditioned sludge,

respectively. Likewise, these figures were 40.72.9% and 58.92.7% in iron-conditioned sludge,

respectively (Figure 33). Figuratively, mean differences (N=6) in both supracolloidal and settleable

particles size classes between the sludges were not statistically significant (p>0.05). The observed

reduction in supracolloidal particles while increment in settleable particles can be beneficial for

activated sludge dewaterability and settleability (Yin et al., 2004).

Table 19 shows the variation in the degree of compactness of both sludges as reflected by fractal

dimension Df values. The Df values of iron-conditioned activated sludge were relatively smaller than

that of unconditioned sludge. In aggregate, mean Df values of the iron-conditioned and unconditioned

sludges were 1.910.004 (N=6) and 1.930.006 (N=6), respectively and the differences were not

statistically significant (p0.05). However, in majority of the analyzed samples, Df values of iron-

conditioned sludge were smaller than unconditioned sludge. The high Df value means compact/dense

sludge flocs or compact structure (Jin et al., 2004). This is further supported by the reduced values of

aggregate structure factor (S) and the ratio of constituent cluster radii (𝑅𝐻

𝑅𝐴) in iron-conditioned

activated sludge than unconditioned sludge (Table 19). The variation in 𝑅𝐻

𝑅𝐴 values in both sludges

actually correspond with the values of Dv(50) presented in Table 18. Reduction in 𝑅𝐻

𝑅𝐴 value implies

an increment in a radius of aggregates or flocs, which suggests loose sludge flocs in iron-conditioned

sludge, as previously indicated by the Df values.

Figure 34 shows the DSC thermograms of both activated sludges, obtained using freezing-heating

method. This suggests the presence of more bound water in unconditioned activated sludge than iron-

conditioned sludge. In terms of dry solids (DS), we found BWC of iron-conditioned and

unconditioned sludges were 12.29 g.(g.DS)-1 (N=2) and 17.96 g.(g.DS)-1 (N=2), respectively (Table

20).

110

Table 18. Particle size specifications (mean diameter and percentiles) in activated sludges. Here, each

set of samples (i.e. SBR-E1/SBR-C1, SBR-E2/SBR-C2, SBR-E3/SBR-C3, SBR-E4/SBR-C4, SBR-

E5/SBR-C5, and SBR-E6/SBR-C6) were sampled weekly from respective experimental and control

SBR reactors. Also, ‘n’ = no. of measurements, ‘N’ = no. of analyzed samples used, ‘SD’ = standard

deviation

Iron-conditioned (SBR-E) and unconditioned activated sludges (SBR-C) from SBRs

SBR-E

samples

(N=6)

Mean

diameter and

percentiles

Mean

(m)

(n=10)

SD SBR-C

Samples

(N=6)

Mean diameter and

percentiles

Mean

(m)

(n=10)

SD

SBR-E1 Dv10 32.2 0.33 SBR-C1 Dv10 31.76 0.20

Dv50 101.2 0.83 Dv50 100.3 0.95

Dv90 185.4 1.67 Dv90 187.4 3.50

SBR-E2 Dv10 31.32 0.39 SBR-C2 Dv10 29.76 0.08

Dv50 104.2 0.83 Dv50 98.08 0.21

Dv90 202.4 1.51 Dv90 195.8 0.44

SBR-E3 Dv10 30.2 0.12 SBR-C3 Dv10 29.74 0.08

Dv50 102.2 0.44 Dv50 98.26 0.29

Dv90 188 1.0 Dv90 185 1.0

SBR-E4 Dv10 38.94 0.32 SBR-C4 Dv10 35.06 0.15

Dv50 119.6 0.54 Dv50 108.8 0.44

Dv90 214.6 1.67 Dv90 197.2 1.48

SBR-E5 Dv10 39.2 0.8 SBR-C5 Dv10 31.5 0.14

Dv50 140 1.6 Dv50 99.1 1.7

Dv90 288 0.5 Dv90 196 0.5

SBR-E6 Dv10 37.7 0.1 SBR-C6 Dv10 32.8 0.1

Dv50 131 1.6 Dv50 109 1.8

Dv90 269 0.4 Dv90 211 0.5

111

Figure 32. SEI images obtained at different magnifications by scanning electron microscopy. (a)-(d)

iron-conditioned activated sludge (SBR-E) (top-half): (a) 300, (b) 500, (c) 1000, (d) 2000; (e)-

(h) unconditioned activated sludge (SBR-C) (bottom-half): (e) 300, (f) 500, (g) 1000, (h) 2000

112

Figure 33. (a)-(f) Particle fingerprints (or PSD) analyses of iron-conditioned (samples SBR-E1, SBR-

E2, SBR-E3, SBR-E4, SBR-E5, SBR-E6) and unconditioned (samples SBR-C1, SBR-C2, SBR-C3,

SBR-C4, SBR-C5, SBR-C6) activated sludges, depicting the volume density (VD) (%) of particles

in different size class range. Each set of samples (i.e. SBR-E1/SBR-C1, SBR-E2/SBR-C2, SBR-

E3/SBR-C3, SBR-E4/SBR-C4, SBR-E5/SBR-C5, and SBR-E6/SBR-C6) were sampled weekly from

respective SBR reactors

113

Table 19. Determination of fractal dimension Df, aggregate structure factor, (S) and ratio between

hydrodynamic radius (RH) to the radius of aggregate (RA) in activated sludges, RH/RA values. Here,

each set of samples (i.e. SBR-E1/SBR-C1, SBR-E2/SBR-C2, SBR-E3/SBR-C3, SBR-E4/SBR-C4,

SBR-E5/SBR-C5, and SBR-E6/SBR-C6) were sampled weekly from respective SBR reactors. Here,

values of Df, RH/RA, and (S) correspond to the mean of 10 replicate measurements (n=10)

Iron-conditioned activated sludge (SBR-E) Unconditioned activated sludge (SBR-C)

Samples no. (N=6) Df RH/RA (S) Samples no. (N=6) Df RH/RA (S)

SBR-E1 1.91 0.75 0.57

SBR-C1 1.92 0.76 0.57

SBR-E2 1.90 0.75 0.56

SBR-C2 1.91 0.75 0.57

SBR-E3 1.90 0.75 0.56

SBR-C3 1.91 0.75 0.57

SBR-E4 1.93 0.76 0.58

SBR-C4 1.93 0.76 0.58

SBR-E5 1.90 0.75 0.56

SBR-C5 1.95 0.77 0.59

SBR-E6 1.91 0.75 0.57

SBR-C6 1.94 0.77 0.59

Figure 34. DSC thermograms of both activated sludges including pure Milli-Q water. Here, pure

water = S0; iron-conditioned sludges (SBR-E) = S1 and S3; unconditioned sludges (SBR-C) = S4

and S6. Each set of samples (samples S1 and S4, S3 and S6) were sampled weekly from respective

SBR reactors during the 12th month of experimental Phase II (i.e. after initiation of in-sewer FeCl3

dosing in integrated lab system)

114

Table 20. Quantification of TWC, FWC, BWC, dry solids (DS) and wet solids (WS) of the centrifugal dewatered sludge cake in both activated sludges

(TWC = total water content; FWC = free water content; BWC = bound water content). Here, sample S1 was sampled in conjunction with sample S4 and

similar was the case for other set of samples S3 and S6, such that each set of samples were sampled weekly from respective SBR reactors

Activated

sludge types

Samples

ID

(N=2)

Wt. of

crucibles

(dry)

(W1, g)

Wt. of

crucible +

wet samples

(centrifuged

solid mass)

(W2, g)

Wt. of

crucible

+ oven

dried

samples

(W3, g)

Dry

solids

(DS)

amount

(mc-

ma), g

Wet

solids

(WS)

amount

(mb-

ma), g

(mb

-

mc),

g

TWC

(g/g WS)

TWC

(g/g DS)

FWC#

(g)

(K

A)

FWC

(g/g

WS)

FWC

(g/g

DS)

BWC

(g/g

WS)

BWC

(g/g

DS)

Dry

solids

(DS)

Wdm*

(mc-

ma)/(mb-

ma) (mb-

mc)/(mb-

ma)

(mb-

mc)/(mc-

ma)

ma mb mc (g/g)

Iron-

conditioned

(SBR-E)

S1 16.74 17.37 16.79 0.04 0.62 0.58 0.93 13.70 0.02 0.03 0.49 0.90 13.21 0.07

S3 18.93 19.69 18.99 0.06 0.76 0.70 0.92 11.75 0.02 0.03 0.39 0.89 11.36 0.08

Unconditioned

(SBR-C)

S4 22.37 22.84 22.39 0.03 0.47 0.45 0.95 17.65 0.03 0.06 1.03 0.89 16.62 0.05

S6 14.82 15.51 14.86 0.03 0.68 0.65 0.95 20.10 0.03 0.04 0.79 0.92 19.31 0.05

N.B. here, activated sludge sample was subjected to centrifugation at 3000 rpm for 10 min; bulk solution or supernatant part was then decanted and remaining centrifuged sludge

cake was dried at 105C to determine its water content

*wdm = is the dry matter of the sample, in percentages or grams per kilogram; # value of conversion factor (K) (g/J) = ratio of mass of pure water used (= 0.0149 g) and endothermic curve area of pure water, A (= 2.80269 J) (where, A is the product of mass

of pure water used for DSC analysis (= 0.0149 g) and endothermic DSC curve area of pure water (= 188.1 J/g)); value of K (g/J) = 0.0053

115

5.3.5 Changes in rheological properties

Steady shear tests showed some variations in load- and time-dependent rheological properties among

the sludges. Figure 35a shows variation in calculated relative network strength values of both sludges.

The average relative network strength values of iron-conditioned and unconditioned sludge were

851.539.7 J.(kg.DS)-1 and 106162.2 J.(kg.DS)-1, respectively with a mean difference of 209.373.8

Nm.sec (N=3), which was statistically significant (p<0.05). The calculation of relative sludge network

strength was based on the totalized torque (TTQ) values, given in Figure 36a. The iron-conditioned

and unconditioned sludges showed the TTQ values of 23.30.4 Nm.sec (N=3) and 24.50.7 Nm.sec

(N=3), respectively. The illustrative procedure employed herein for the determination of TTQ and

respective relative sludge network strength (for the SBR-E sample as an example), which was based

on torque rheology, can be found in Table B1 (Appendix D).

Figure 35b-d show variations in sludge shear viscosity (shear) as a function of shear rates 50 s-1, 100

s-1, and 250 s-1 for both sludge samples. Clearly, shear value of iron-conditioned sludge (SBR-E) was

lower than that of unconditioned sludge (SBR-C). The average shear values (meanSEM) of iron-

conditioned sludge at shear rates 50 s-1, 100 s-1 and 250 s-1 were 23.60.2, 16.10.3 and 24.30.1

mPa.s, respectively. Likewise, average shear values (meanSEM) for unconditioned sludges at the

same shear rates were 58.00.2, 32.00.1 and 31.60.2 mPa.s, respectively.

Figure 36b-c and Figure 36d-e show the changes in sludge thixotropy (structural

breakdown/regeneration) of iron-conditioned and unconditioned sludges, respectively (based on CSR

test results). For this, comparisons were done between the shear stress () in ascending path (up-flow

curve) and descending path (down-flow curve). We did not observe any hysteretic decline in shear

stress values, however, there was a reduction in apparent viscosity A of iron-conditioned sludges

(Figure 36f), which further supported the observed variations in shear (Figure 35b-d). In particular,

previous shear stress history had little or no influence on the flow behavior of both sludges. Shear

stresses of ascending and descending paths were almost identical in low shear rate range ( 300 s-1)

wherein with the further increment in shear rate, shear stress increased in ascending paths than in

descending paths at the same shear rate. However, both sludges depicted a decline in shear stress

along with release of shear rate in the descending path, indicating thixotropic properties of sludges.

To corroborate this observed change in the degree of thixotropy, hysteresis loop tests were

undertaken. Figure 37 presents the changes in relation to thixotropy analysis and hysteresis loop area

(Hla) values, which reflect the sludge thixotropy. The mean Hla values in iron-conditioned and

116

unconditioned sludges were 38.3 Pa.s-1 and 176.3 Pa.s-1, respectively. Figure 38 presents the CSS test

results, depicting the observed changes in yield stress (y) values. Each strain-stress curve (Figure 38)

exhibits a critical shear stress, also referred as ‘y’ (Wang et al., 2011b). Calculated mean y values of

iron-conditioned and unconditioned activated sludges (N=2) were 0.7 Pa and 1.3 Pa, respectively.

The variations observed in viscoelastic rheological properties between iron-conditioned and

unconditioned activated sludges are shown in Figure 39. Effect of amplitude of oscillation on

rheology of both activated sludges was evaluated by SAS test and is illustrated in Figure 39a-c.

Clearly, SAS test results depict the differences observed in different elastic/viscous/complex moduli

(G/G/G*) among the activated sludges (Figure 39a-c). As observed, two moduli depict G > G in

both iron-conditioned and unconditioned sludges (Figure 39a-b) suggest the existence of ‘solid-like

properties (elastic characteristics)’. Likewise, both G and G values are lower in iron-conditioned

sludges than unconditioned sludges (Figure 39a-c). Also, G* values are comparatively higher for

unconditioned sludges (Figure 39c).

Viscoelastic properties of both sludges depicting the effect of frequency of oscillation were further

analyzed by FS tests (Figure 39d-e). The FS tests were carried out using an oscillating shear strain of

10%. An assessment of variation of both stiffness and damping of activated sludge was made and

these are reported as modulus and tan(), respectively. Both activated sludges also exhibited G>G

under FS tests (Figure 39d-e), suggesting the dominance of elastic properties within the range of

oscillatory frequency studied herein. Likewise, both G and G values are lower in iron-conditioned

sludge than unconditioned sludge (Figure 39d-e). Mean tan() values for iron-conditioned and

unconditioned sludges were 0.21 and 0.25, respectively showing a decreasing trend of damping factor

tan() in iron-conditioned sludge (Figure 40a).

Figure 39f shows the creep response of both activated sludges elucidating the variations observed in

creep compliance (J) (Pa-1) with time. Likewise, Figure 40b depicts a comparatively higher growth

in shear strain (%) within the observed time frame of creep test in iron-conditioned sludges as

compared to unconditioned sludges. Both (J) and shear strain (%) values for iron-conditioned sludges

were found to be higher. Notably, the recovery regime after stoppage of applied stress was not

observed in both the sludges, implying the occurrence of irreversible deformation (Figure 39f).

117

Figure 35. (a) Observed differences in relative sludge network strength values of both sludges (here,

linear ramp increment was adopted for shear rate from 0-300 s-1 for 76 s); (b)-(d) flow curves

depicting changes in shear viscosities (shear) as function of different shear rates (50, 100, 250 s-1):

changes in shear values of iron-conditioned (SBR-E) and unconditioned (SBR-C) activated sludges.

Here, error bar represents the meanSEM

118

Figure 36. (a) changes in TTQ values based on torque rheology; (b)-(c) CSR tests showing flow

curves of iron-conditioned sludges (SBR-E1, SBR-E2); (d)-(e) CSR tests showing flow curves of

unconditioned sludges (SBR-C1, SBR-C2); (f) variations in apparent viscosities A in both activated

sludges. Here, each set of samples (SBR-E1/SBR-C1, SBR-E2/SBR-C2) were sampled weekly from

respective SBR reactors

119

Figure 37. Thixotropy analysis based on hysteresis loop tests: (a)-(b) iron-conditioned (samples SBR-

E1, SBR-E2) (top-half) and (c)-(d) unconditioned (samples SBR-C1, SBR-C2) activated sludges

(bottom-half). Here, each set of samples (SBR-E1/SBR-C1, SBR-E2/SBR-C2) were sampled weekly

from respective SBR reactors

120

Figure 38. CSS test results showing the changes in yield stress (y) values: (a)-(b) iron-conditioned

sludges, SBR-E (N=2); (c)-(d) unconditioned sludges, SBR-C (N=2)

121

Figure 39. (a)-(c) Evolution of storage (G), loss (G) and complex (G*) moduli in both activated

sludges (SBR-E, SBR-C) during amplitude sweep oscillation tests as a function of applied shear strain

range 0.01-1000%, angular frequency 5 rad.s-1 and at 25±0.01°C; (d)-(e) frequency sweep of both

sludges (SBR-E, SBR-C) with oscillating strains of 10% on G and G over frequency range of 0.1-

100 rad.s-1 at 25±0.01°C; (f) creep-recovery tests for both sludges (SBR-E, SBR-C): response of shear

creep compliance (J) with respect to creep time

122

Figure 40. (a) Variations in damping (or loss) factor tan() over frequency range of 0.1 – 100 rad.s-1

at 25±0.01°C during frequency sweep of both activated sludges (SBR-E, SBR-C) with oscillating

strains of 10%; (b) creep-recovery tests for both activated sludges (SBR-E, SBR-C): response of shear

strain (%) with respect to creep time

123

Figure 41. Possible combined synergistic interplay amongst different underlying interactions behind

improvement in dewaterability and settleability of iron-conditioned activated sludge

5.4. Discussion

Sewer-dosed FeCl3 and subsequent iron availability in bioreactor and resulting underlying

interactions with activated sludge has been found to impact several key activated sludge properties.

This viewpoint was evidenced by a schematic representation illustrated in Figure 41, depicting the

underlying contributing factors behind improved settleability and dewaterability of iron-conditioned

activated sludge.

In terms of changes in physicochemical sludge properties, we observed a reduction in S-EPS content

(Figure 29b), reduced PN and PS contents (Figure 29c-d), and increased humification index (as

reflected by increased HA-like and FA-like substances) of iron-conditioned sludge. A greater S-EPS

content increases interstitial (or bound) water content in sludge flocs, which may inhibit the inter-

cellular contacts in sludge biomass (Chen et al., 2001; Sheng et al., 2010) and also increases the

sludge viscosity (Li and Yang, 2007). Opposite to this, reduced S-EPS would positively impact both

the sludge settleability and dewaterability. Considering high water-holding capacity of PN fractions

in sludge (Cetin and Erdincler, 2004; Sponza, 2002), the reduced PN and PS contents in iron-

124

conditioned sludge are likely to positively influence the sludge dewaterability. In addition, increased

humification index of iron-conditioned sludge (Table 15) is also likely to contribute in improved

dewaterability, as previously suggested (Yu et al., 2010). Notably, previous studies have only

focussed on the influence of PN and PS in the sludge EPS matrices in relation to sludge

dewaterability, overlooking the roles of HA-like and FA-like substances unlike here (Figure 41).

Cations distribution in the sludge matrix, particularly decreased M+/D++ cations ratio in iron-

conditioned sludge (Figure 31a) positively influence the settleability and dewaterability (Figure 41).

Higher M+/D++ ratio implies excess monovalent cations concentrations, which can displace the

divalent cations enmeshed within the sludge floc matrix via ion-exchange mechanism, destabilizing

the sludge flocs stability. This in turn would deteriorate the sludge flocs structure, and hence settling

and dewatering properties (Higgins and Novak, 1997b). However, upon treatment with trivalent

cations such as Fe3+ ions, the bridging monovalent or divalent cations present in sludge flocs may

undergo exchange with trivalent cations, further strengthening the flocs stability as explained in the

conceptual ion-exchange mechanism (Figure 6, Section 1.3.2). This is due to higher binding strength

of trivalent cations with activated sludge flocs than that of monovalent or divalent cations (Li et al.,

2012), which is attributed to higher charge valence of trivalent cations (Park et al., 2006). Results

depicting monovalent and divalent cations concentrations (Table 16), also showed trivalent cations

(Fe3+, Al3+) firmly bound within the activated sludge flocs promoting sludge flocs strength and

stability. Relatively, more trivalent cations (Fe3+, Al3+) were concentrated in pellet fractions of iron-

conditioned sludge than the unconditioned sludge. Besides, iron-conditioned sludge also exhibited

higher sludge inorganic fractions (Table 17), which would result in heavier sludge flocs (Peeters,

2010), facilitating the better settleability (Figure 41).

Further, particle size distribution is also considered as another important factor influencing sludge

dewaterability (Pham et al., 2010) and settleability (Li and Stenstrom, 2018). However, differences

observed in Dv50 or PSD among the different particle size classes between the two sludges (Figure

31b, Figure 33, Table 18) were not statistically significant (p>0.05). We observed only a marginal

increase in both Dv50 (i.e. 13.8%) and settleable particles (>100 m), but decrease in supracolloidal

particles (1-100 m) in the iron-conditioned sludges. Notably, PSD curve for iron-conditioned

activated sludges was slightly left-skewed (Figure 31b), suggesting possible aggregation of smaller

flocs into larger ones. Such aggregation phenomenon can be attributed to flocculating ability of Fe3+

ions (resultant of sewer-dosed FeCl3). Similarly, increase in settleable size fractions, albeit marginal,

125

possibly may have contributed to improved settleability of iron-conditioned activated sludge (Figure

41) as evidenced by reduced SVI values (see Section 5.3.1). Besides, decrease in supracolloidal

particles and corresponding increase in settleable particles can also be beneficial for sludge

dewaterability. This can be summed up with two major reasons. Firstly, increased supracolloidal

particle size fractions is reported to hinder the sludge filterability (i.e. specific resistance to filtration)

(Yin et al., 2004). Secondly, presence of predominant large particles/flocs (Figure 31b, Figure 33,

Table 18) can consequently ease bound water release. Higher composition of small particles enhances

the surface area of sludge flocs and hence, increases bound water quantity as bound water is directly

linked with sludge particles surface (Bougrier et al., 2006). This was supported by relatively lower

bound water content in iron-conditioned sludge (Figure 34, Table 20). Additionally, marginal

reduction in Df, (S), and 𝑅𝐻

𝑅𝐴 (Table 19) in iron-conditioned sludge could also have positively impacted

the activated sludge settleability and dewaterability (Figure 41). Sludge flocs characterised by more

compact structure (high Df value) may lead to the expansion of particle suspension surfaces, creating

spatial structures. Consequently, this might increase the water content in sludge which in turn may

deteriorate sludge settling properties (Kuśnierz and Wiercik, 2016). Regarding the influence of sludge

floc structure on sludge dewaterability, Turchiuli and Fargues (2004) reported that bound water

content in sludge decreased with the Df, value, i.e., less compact flocs (lower Df values) contained

more water but less bound water, resulting in better sludge dewaterability (Kopp and Dichtl, 2001).

Such changes in physicochemical and morphological properties, due to long-term iron exposure, are

also reflected by the changes in rheological properties. These encompass weakening of relative sludge

network strength (Figure 35a) and reduced viscosity (Figure 35b-d, Figure 36f), thixotropy (based on

Hla values) (Figure 37) and y (Figure 38). We observed reduction in relative sludge network strength,

which implies lower resistance of sludge against the applied shear stress. Also, iron-conditioned

sludge being less thixotropic, as reflected by reduced Hla values, suggests existence of relatively

weak colloidal forces among the sludge particles. These results are an indicative of the greater ability

of iron-conditioned sludge to release most of its incorporated water while withstanding the applied

shear. Such ease in releasing of water implies improved sludge dewaterability (Figure 41), as

previously suggested (Abu-Orf Mohammad and Örmeci, 2005; Ormeci et al., 2004). Besides,

increased viscosity of sludge is associated with an increased SVI values (Tixier et al. (2003) and

decrease in sludge viscosity results in improved sludge flowability (Liu et al., 2016b; Liu et al.,

2016c). The observed reduction in viscosity, further supported by reduction in y values, therefore

indicates possible improvements in both flowability and settleability (lower SVI) of iron-conditioned

sludge. The reducedy value also implies a reduction in sludge viscosity because all three bound water,

126

viscosity, and y of activated sludge are strongly inter-related, as previously documented by Forster

(2002). The reduced y value of iron-conditioned sludge can be attributed to improved flocculation of

sludge particles by Fe3+ ions. Forster (2002) observed a reduction of y in iron-dosed activated sludge

sourced from full-scale aeration tanks, where direct addition of FeCl2 was adopted. The results of this

study also suggest that the iron entering an aeration tank as a precipitate have got similar properties

akin the iron dosed directly to the aeration tank as far as changes in activated sludge properties are

concerned and subsequent positive influence on sludge settleability and dewaterability (Figure 41).

The changes in time- and load-dependent rheological properties observed in iron-conditioned sludge

are further complemented by the reduction in elastic/viscous/complex moduli (G/G/G*) (Figure

39a-e) and damping factor tan() (Figure 40a), but increased shear compliance (J) (Figure 39f) and

shear strain (%) (Figure 40b) with time. Decrease in G and G values of iron-conditioned sludge

implies possible weakening of sludge structure or reduction in the sludge elasticity (solid-like

behavior), while reduction in G* (Figure 39c) means the weaker deformation resistance of sludge

against the applied external shear (Bobade et al., 2017; Feng et al., 2014a; Feng et al., 2014b).

Likewise, reduction in tan() value suggests that iron-conditioned sludge exhibits the weaker solid-

like (or elastic) properties (Liu et al., 2016c) and in consequence, the proportion of energy dissipation

to energy storage on applying external shear (Mezger, 2006) would be reduced, subsequently

resulting improved sludge flowability (Wang et al., 2017). Such improvement in flowability of iron-

conditioned sludge is also likely due to existence of weak colloidal forces and sludge network strength

(Feng et al., 2014a), as supported by reduced Hla values observed herein. Interestingly, these results

are also in line with the trend of creep compliance (J) values (Figure 39f), which were higher for iron-

conditioned sludge. Increment in creep compliance values attributes to the reduced stiffness or

deformation resistance against the applied shear (as previously depicted by reduced G* modulus).

Such reduced deformation resistance could possibly be the reason behind the relatively higher growth

in shear strain (%) of iron-conditioned sludge in compared to unconditioned sludge (Figure 40b). In

nutshell, these foregoing results implicates weakened sludge elasticity or solid-like properties, lower

sludge network strength, and internal deformation resistance of the iron-conditioned sludge, while

opposite was the case for unconditioned sludge. The foregoing results confirmed the interplay

existing amongst the different key properties of iron-conditioned activated sludge and their changes

due to iron availability. The combined synergistic effect of such phenomenon is likely responsible

for improvement in settleability and dewaterability, as outlined in Figure 41.

127

5.5. Conclusion

This study investigated the impact of sewer-dosed FeCl3 on settleability and dewaterability of iron-

conditioned activated sludge and also shed lights on mechanistic overview of different possible

causative factors behind the observed changes in settleability and dewaterability. The main

conclusions are:

• Sewer-dosed FeCl3 showed improvement in both settleability and dewaterability of activated

sludge. Mean differences in SVI and dewatered cake solids content (%) values between iron-

conditioned and unconditioned activated sludges were 22.5±7.8 mL.g-1 (p<0.05) and 7.8±1.2%

(p<0.05), respectively.

• There have been no negative impacts in physicochemical, morphological, and rheological

properties due to iron dosing. Instead, iron-conditioned sludge (228.8±22.0 mg.Fe.L-1) exhibited

favorable changes in several key sludge properties.

• Iron-conditioned activated sludge showed lower contents of soluble extracellular polymeric

substances S-EPS fractions, PN and PS, and M+/D++ cations ratio, but higher humification index

(e.g. increased HA- and FA-like substances) as compared to the unconditioned sludge.

• Iron-conditioned activated sludge exhibited marginal increment in mean particle size (Dv50) and

settleable particle size classes (100-400 µm) but reduction in supracolloidal particle size classes

(1-100 m).

• In terms of sludge rheology, iron-conditioned sludge exhibited relatively lower relative sludge

network strength, viscosity, yield stress, elastic/viscous/complex moduli (G/G/G*), and

damping factor tan() but increased shear compliance (J) and shear strain (%) with time. Iron-

conditioned sludge therefore exhibited relatively weaker deformation resistance and sludge

elasticity.

• Examination of underlying possible mechanism for improved settleability and dewaterability of

iron conditioned activated sludge was attempted. Based on foregoing results, we can posit that

the combined synergistic effect of favorable changes observed in key sludge properties could be

underlying contributing factor responsible for such improvement.

• The information observed herein could be highly beneficial when considering iron salts dosing

to sewer in full-scale integrated sewer-WWTP operation.

128

Chapter 6

Revealing the influence of sewer-dosed iron salts on

anaerobically digested sludge properties with

implications on improving dewaterability

The chapter has been published and modified to be wholly incorporated in the Chapter 6: ‘Sohan Shrestha, Keshab

Sharma*, Jagadeeshkumar Kulandaivelu, Mario Rebosura, Zhiguo Yuan, Keshab Sharma* (2020). Revealing the

variations in physicochemical, morphological, fractal, and rheological properties of digestate during the mesophilic

anaerobic digestion of iron-rich waste activated sludge. Chemosphere, 254, 126811

(https://doi.org/10.1016/j.chemosphere.2020.126811).


129

6.1 Introduction

Anaerobic digestion of sewage sludge is a key process in the wastewater treatment system. In

retrospect, handling and disposal of anaerobically digested sludge (or as ‘digestate’) are of prime

concern for water utilities, as these involve significant economic costs (Darby et al., 1997).

Considering the high moisture content of digestate (94-98% by weight) (Darby et al., 1997; Mikkelsen

and Keiding, 2002), reduction in sludge water content during the dewatering process is crucial. Any

enhancement in digestate dewaterability is hugely beneficial for sludge volume reduction and this, in

turn, can influence the economics of the entire WWTP operation.

Recent few studies have shown the efficacy of iron(Fe)-salt usage (e.g. direct/indirect) in improving

the digestate dewaterability (Akgul et al., 2017; Novak and Park, 2010; Rebosura et al., 2018). Direct

dosage of Fe-salt to anaerobic digester (AD) have shown effectiveness in improvement of digestate

dewaterability (Akgul et al., 2017; Novak and Park, 2010). Akin, indirect (upstream in-sewer dosing)

dosage of Fe-salt to AD have also shown similar impacts during operation of an integrated laboratory

sewer-WWTP system (Rebosura et al., 2018). In contrast with direct dosage, the nature of the

implications of iron that is carried over to the AD from upstream sewer are likely to be different when

in-sewer dosing is employed. When Fe-salt is added in upstream anaerobic sewer reactor, Fe

precipitates with sulfides as iron sulfide (FeSX) under septic condition and subsequently again

precipitates with phosphate ions upon reaching aeration tank thereby forming insoluble ferric-

hydroxy‐phosphate FeXPO4(OH)x complexes (Ge et al., 2013). Waste activated sludge (WAS)

containing these precipitates may undergo additional chemical transformations in AD unit (Ge et al.,

2013; Rebosura et al., 2018). The Fe present in FeXPO4(OH)x complexes will be reduced and will

react with sulfides in AD. Occurrence of such chemical interactions/transformations including the

release of sulfides from volatile solids destruction in digester and its subsequent precipitation could

exhibit some impacts on the key digestate properties, which have not been reported yet. Despite some

earlier indication of improved digestate dewaterability due to sewer-dosed iron(III)-chloride (FeCl3)

(Rebosura et al., 2018), possible mechanisms leading to such improvement have not been studied.

This necessitates an investigation of the influence of iron dosing on underlying sludge properties and

their role in possible enhancement of the digestate dewaterability.

There are a number of parameters characterizing the physicochemical properties of sludge, which are

reported to have a direct or indirect influence on sludge dewaterability. This includes concentrations

and properties of different extracellular polymeric substance (EPS) fractions (soluble/loosely-

130

bound/tightly-bound) and bound water content (BWC) (Niu et al., 2013; Xing et al., 2017). Li and

Yang (2007) reported deterioration in digestate dewaterability with increment in soluble-EPS wherein

Novak et al. (2003) concluded otherwise. Besides, cations distribution in sludge EPS fractions,

particularly monovalent-to-divalent (M+/D++) cations ratio, is considered an important parameter

concerning settling and dewatering properties of sludge (Higgins and Novak, 1997a; b). Higgins et

al. (2004) showed that lower M+/D++ cations ratio reflects the higher dewatered cake solids content

(%). Similarly, improved dewatering rate can usually be related to ease in sludge moisture reduction

(Wang et al., 2017) and this can be assessed by measuring the bound water content of the sludge. In

addition, sludge morphology (size/structure/compactness), also plays an important role in sludge

dewaterability (Pham et al., 2010). Fractal dimension, Df, a parameter that is associated with sludge

aggregate structure or reflects the degree of compactness, has also been reported to influence the

sludge dewaterability (Zhang et al., 2018; Zhao et al., 2013). Both the particle size distribution (PSD)

and Df influence sludge porosity, density, and permeability (Zhao et al., 2013), which are related to

sludge dewaterability. Sewer dosing of FeCl3 is likely to have impacts on the above-mentioned

physicochemical properties of digestate, and hence on the dewaterability. However, the exact nature

of these impacts is not clear, and this necessitates an investigation of the sludge properties. The

understanding of the changes in key digestate properties (e.g. physicochemical, morphological, and

rheological) due to flowing-on effects of upstream sewer-dosed FeCl3, could provide the mechanistic

insights behind the improved dewaterability.

There have been attempts relating the sludge dewaterability with physicochemical properties.

However, solely analyzing different physicochemical properties cannot fully elucidate the underlying

fundamental mechanism behind resultant variability in sludge dewaterability, as suggested in

previous study (Wang et al., 2017). Achieving better solid-liquid separation in sludge dewatering

process equally demands the understanding of sludge hydrodynamics or rheology. This is because

sludge rheology is closely interlinked to the sludge conditioning process (Örmeci, 2007), and

physiochemical interactions (Eshtiaghi et al., 2013b) including sludge dewaterability in terms of

specific resistance to filtration, SRF (Marinetti et al., 2010). This suggests that a thorough

investigation of the changes in major physicochemical, morphological, and rheological properties of

digestate is required to underpin the underlying sludge dewatering mechanism.

In order to evaluate the impacts of sewer based FeCl3 dosing to anaerobically digested sludge, it

becomes necessary to investigate changes it brings to the key properties of digestate linked directly

or indirectly to its dewaterability. Such information would be equally crucial when considering the

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recent paradigm shift in terms of chemical usage in the system-wide operation of sewer-WWTP, as

this would provide a better understanding of the system-wide impacts and facilitate the proper

evaluation of the option. This study, therefore, aims to explore the impacts of sewer-dosed FeCl3 to

digestate dewaterability and associated digestate properties and provide insight into the underlying

mechanism governing the alteration in dewaterability. Specific objectives of this study are to

investigate: (i) the influence of iron (Fe)-rich WAS (i.e. resultant of sewer-dosed FeCl3 in integrated

sewer-bioreactor-thickener-AD laboratory system) as the AD feed on major physicochemical,

morphological, and rheological properties of digestate; and (ii) the inter-relationship among the

digestate properties and its dewaterability. To achieve this, both iron-conditioned and unconditioned

digestate samples collected at different time-period during the reactor’s steady operation were

analyzed for different sludge properties and a comparison of the results was made to draw

conclusions.

6.2 Materials and methods

6.2.1 Sources of digestates

Digestates were collected from two parallel integrated laboratory system (experimental and control

line), each incorporating rising main (RM) sewer, sequencing batch reactor (SBR), gravity thickener,

and AD reactor (Figure 42)., as outlined in Section 3.1 (Chapter 3). All reactors were made of made

up of acrylic polyvinyl chloride (PVC) material. Both experimental and control sewer reactors were

fed with domestic sewage, collected weekly from a residential pumping station serviced via gravity

sewers in Indooroopilly, South East Queensland, Australia. Characteristics of domestic sewage can

be found in Table 12. Besides, sewer reactor of the experimental line was intermittently (during

pumping events) dosed with FeCl3 solution at a concentration of 10 mg.Fe.L-1 wherein the control

line was not. This chosen Fe dosing rate is within the range typically used by water utilities (Ganigue

et al., 2011). Sewer effluent was then used as the influent to SBR. The WAS from the SBR was then

fed to a thickener, followed by AD in line with the feed cycles adopted to continuously operate all

these reactors in an integrated manner. The 50 mL WAS generated from the SBR after thickening

process was dosed once per day to AD reactors.

For comparative analysis, digestates were obtained from the AD reactors in both experimental (AD-

E) and control (AD-C) lines. AD reactors were continuously stirred by magnetic stirrer (MIXdrive 1

eco) and operated with hydraulic retention time of 20 days under mesophilic condition (37 °C) using

a water bath. Total volume of each AD reactor was 1.3 L (1.0 L working volume and 0.3 L reactor

132

headspace). Total iron concentrations in digestates sourced from experimental and control AD

reactors were 777.3±69.0 mg.Fe.L−1 (50.8±4.5 mg.Fe (g.TSS)-1) and 78.4±5.0 mg.Fe.L−1

(6.4±0.4 mg.Fe (g.TSS)-1), respectively. Notably, integrated laboratory system was continuously

operated for 12 months, culminating both baseline (Phase I = 130-240 days, 4th - 8th month) and

experimental phases (Phase II = 242-355 days, 8th - 12th month). Experimental phase with iron dosing

commenced after 8th months of operation under the baseline conditions and digestates used herein

were sampled during 11th and 12th months of operation during the Phase II (i.e. 3 to 4 months after

the commencement of dosing of Fe in the experimental line), when the operation and performance of

the system was stable. We particularly focused on assessing the changes in key digestate properties

concerning long-term exposure of Fe for AD system and hence we waited for a long time after Fe

dosing started. Requisite samples were sampled from both AD-E and AD-C reactors twice per week.

Digestates obtained from AD-E and AD-C reactors have been denoted as ‘iron-conditioned’ and

‘unconditioned’ digestate, respectively in the following sections.


control and experimental lines

6.2.2 Experimental framework

Different physicochemical, morphological, and rheological properties of both digestates were

investigated and subsequently comparisons were made. The schematic diagram elucidating

framework of this study is shown in Figure 43. Nonetheless, likely changes in microbial communities

in iron-conditioned and unconditioned digestates was also investigated (see Figure B2, Appendix B).

133

However, each sample used for analyzing the physiochemical properties, was not repeatedly used

again for analyzing the changes in sludge morphology nor rheology. Albeit the key digestate

properties are expected to vary with the time after the start of in-sewer FeCl3 dosing, especially during

the initial days of dosing, the study focused on the impacts during steady operation and hence the

changes in digestate properties with the function of time was not investigated. In other words, changes

in digestate properties as a function of time were not assessed, once the Fe was introduced to the

system. It would be interesting to evaluate the temporal effect of Fe dosing on the change of sludge

settling and dewatering performances. This is because the proportions of Fe content in the sludge are

expected to vary with the time after the start of in-sewer Fe-salt dosing.

Figure 43. Schematic diagram elucidating framework of this study

6.2.3 EPS fraction extraction and analysis

The modified heat extraction method as outlined in previous studies (Li and Yang, 2007; Xiao et al.,

2017), was used to extract different EPS fractions from digestates obtained from both ADs (AD-E,

AD-C) after a minor modification. Further details of this method are provided in Section 3.5 (Chapter

3).

Cations concentrations and their relative distributions for each extracted EPS fraction were also

evaluated in terms of M+/D++ cations ratio. Further details of this method are provided in Section 3.5

(Chapter 3).

134

6.2.4 Compositional analysis of EPS fractions

Details of the method used for compositional analysis of both unconditioned and iron-conditioned

digestates are provided in Section 3.5 (Chapter 3). Here, F-EEM spectral analysis focusing on the

changes in fluorescing substances (aromatic tyrosine protein-like, aromatic trypotophan protein-like,

HA-like, SMP-like, and FA-like) was conducted to investigate changes in the organic composition of

extracted EPS fractions. Nonetheless, EPS was also quantified by measuring the PN and PS

concentrations in the extractant as described in Section 3.5 (Chapter 3).

6.2.5 Rheological measurements

Rheological tests were carried out using a rheometer (Physica MCR102 Modular Compact


vane. Prior to each measurement, 50 mL sludge sample was transferred to the measuring cup in which

the vane was immersed. Temperature was maintained at 25±0.01°C using a Peltier control during the

rheological tests. Here, both steady shear and dynamic shear rheological tests were undertaken to

assess the changes in rheological properties of both activated sludges. Steady shear rheological tests

encompass the CSR, hysteresis loop, and CSS tests. Also, relative sludge network strength in both

sludges was also estimated based on torque rheology measurement described elsewhere (Örmeci and

Abu-Orf, 2005; Ormeci et al., 2004). Similarly, dynamic shear (or oscillatory) tests incorporate strain

sweep (or strain amplitude sweep, SAS) test including creep test. Details of the methods employed

for all these rheological tests are provided in Section 3.7 (Chapter 3).

Rheological properties of digestates were further characterized using different rheological models -

Bingham, Power-law, Herschel-Bulkley, and Casson models. Further details of the models employed

herein including approach employed for selection of best-fit model against experimental data are

provided in Section 3.7.2 (Chapter 3).


Different parameters were analyzed for both iron-conditioned (AD-E) and unconditioned (AD-C)

digestates, which include:

• Total suspended solids (TSS), volatile suspended solids (VSS), total solids (TS), volatile

solids (VS)

135

• Total and dissolved metal ions concentrations

• Sludge dewaterability in terms of sludge cake solids content (%) including the lab-scale MCI

values (see Section 5.2.3)

• Volume-weighted PSDs

• Fractal dimension Df values, ratio of hydrodynamic radius (RH) to the radius of aggregate (RA),

and aggregate structure factor (S)

• Bound water content (BWC)

Details of the methods employed for the aforementioned parameters are elaborated in Sections 3.4

and 3.8 (Chapter 3). The BWC of both the digestates was determined using a Q2000 DSC analyzer,

Q2000 (TA, USA). Here, DSC measurements were carried out using freezing-heating method (Wang

et al., 2012). The mass of sludge sample used in this analysis varied in the range of 12.9-15.6 mg.

Heat absorption was quantified by integrating the peak area under the endothermic curve obtained

during DSC test, owing to correlation between sludge water content and the enthalpy value measured

by DSC curves (Wang et al., 2012). Details of the method employed for BWC measurement are

provided in Section 3.8 (Chapter 3). Likewise, the moisture distribution in digestates was also

analyzed using drying rate curve (Figure 44), obtained by the thermogravimetric (TG) measurement

(Section 3.8, Chapter 3). Experimental set up used for this measurement is shown in Figure 14.

As depicted in Figure 44, the drying curve initiates from the top right-hand corner owing to the high

moisture content (mass of water/total solids, g.g-1) and terminates at lower left-hand corner, when all

the moisture content in sample has dried up completely. Three critical points A, B and C can be

identified on drying curves, point C indicates the end of FWC. This is because drying rate will be

linear as long as there is free water in sludge, which is only component removed by mechanical

dewatering processes (Kopp and Dichtl, 2001). This suggests the solid content at point C is therefore

the maximum solid content in sludge cake, which is achievable via mechanical dewatering.

136

Figure 44. Illustration of a drying rate curve obtained for an iron-conditioned digestate via TG

measurement


Mean values and associated SD, SEM of different data sets were calculated. Student’s t-test with

Welch’s correction and a 95% CI was applied to determine whether the difference between the

observed mean values of AD-E and AD-C digestates pertinent to different properties are statistically

significant or not, which was judged based on the p-values (p<0.05). All statistical tests were

undertaken using GraphPad Prism software (version 7.03).

6.3 Results

6.3.1 Variation in digestate dewaterability

Figure 45 shows the dewaterability of iron-conditioned and unconditioned digestates in terms of

dewatered cake solids content (%). Iron-conditioned digestate exhibited improved dewaterability

(Figure 45a) with mean cake solids content (%) (meanSEM, n=16) of 19.20.1% as compared to

unconditioned digestate with the mean cake solids content (%) of 15.50.4%. Mean difference was

statistically significant (p<0.05). Further, Figure 45b-d present the MCI values in terms of cake solids

content (%) as a function of mixing intensity, centrifugation time or combination of both for

digestates. We found that maximum solids cake achievable by the centrifugation method was higher

for iron-conditioned digestate in all cases.

137

Figure 45. (a) Cake solids content (%) of iron-conditioned (AD-E) and unconditioned (AD-C)

digestates: error bars represent meanSEM (n=16); (b) effects of centrifugal time (t) on cake solid

content (%), constant mixing intensity = 3750 rpm [t = 5 min (n=6); t =10 min (n=16); t =20 min

(n=6)]; (c) effects of centrifugal speed on cake solid content (%), constant mixing time = 10 min [rpm

= 1000 (n=3); rpm = 2000 (n=3); rpm = 3750 (n=16)]; (d) cake solid content (%) as function of gt

values [gt = 139392.24 (n=3), gt = 557568.96 (n=3), gt = 980101.69 (n=6), gt = 1960203.40 (n=16),

gt = 3920406.80 (n=6)]

6.3.2 Variations in physicochemical properties

Variation in content of EPS fractions in both digestates is depicted in Figure 46a. Quantities of S-

EPS, LB-EPS and TB-EPS were relatively lower in iron-conditioned digestates. Mean concentrations

of S-EPS, LB-EPS, and TB-EPS in iron-conditioned digestate (meanSEM, n=4) were 6.5±0.5,

8.0±1.8, and 5.8±0.6 mg.TOC.(g.VSS)-1, respectively, while those in unconditioned digestate

(meanSEM, n=4) were 8.5±0.5, 8.3±2.6, and 7.8±1.4 mg.TOC.(g.VSS)-1, respectively. The mean

difference of S-EPS concentrations among the unconditioned and iron-conditioned digestates was

statistically significant (p<0.05), while this was not the case with both LB-EPS (p>0.05) and TB-EPS

concentrations (p>0.05). Such reduction in S-EPS content of iron-conditioned digestate is likely to

contribute in improving its dewaterability.

138

Figure 46. (a) Quantities of S-EPS, LB-EPS and TB-EPS in terms of TOC content in both digestates.

Error bar represents meanSEM (n=4); (b)-(c) F-EEM spectra of different EPS components of 1st set

(AD-E1, AD-C1) (top-half) and 2nd set (AD-E2, AD-C2) (bottom-half) of digestate samples

(separated by solid lines). Each set of samples correspond to different sampling time, sampled in a

week interval from respective experimental AD-E and control AD-C reactors; Quantification of (d)

PN and (e) PS in both digestates (data represents mean values, n=2)

The F-EEM spectra of EPS fractions of both digestates are shown in Figure 46b-c. The FRI

parameters employed for the quantitative analysis of F-EEM spectra are given in Table 14 (Chen et

al., 2003a; Chen et al., 2003b). Each F-EEM depicts the spectral information regarding the chemical

compositions of EPS matrices in digestates. Figure 46b-c showed that sewer-dosed FeCl3 addition

resulted notable changes in both the fluorescence peak positions including the fluorescence intensities

(FI) of EPS fluorophores. We found that FI values of both aromatic protein (PN) tyrosine- and

139

tyrosine-like substances in different EPS fractions were weaker in iron-conditioned digestates (AD-

E) than the unconditioned digestates (AD-C) (Table 21). Considering PN content in EPS fractions is

equivalent to FI values (Henderson et al., 2009), we can posit the decrease in PN content in iron-

conditioned digestates. For further confirmation, both soluble PN and PS contents were

colorimetrically quantified (Figure 46d-e). As the figures show, soluble PN and PS contents were

relatively lower in iron-conditioned digestate than unconditioned digestate, with an exception of PS

content in LB-EPS and TB-EPS fractions. The mean soluble PS contents (mg.glucose.(g.VS)-1) in

mixed-liquor sample, S-EPS, and LB-EPS fractions of iron-conditioned digestate as compared to the

unconditioned digestate were lower by 58.99%, 64.93%, and 2.77%, respectively. Similarly, the mean

soluble PN contents (mg.BSA.(g.VS)-1) in mixed-liquor sample, S-EPS, LB-EPS, and TB-EPS

fractions of iron-conditioned digestate as compared to the unconditioned digestate were lower by

43.91%, 44.55%, 40.97%, and 36.56%, respectively.

Figure 47a shows the changes in M+/D++ cations ratio of both iron-conditioned (AD-E) and

unconditioned (AD-C) digestates. Iron-conditioned digestate showed decreased M+/D++ ratios in S-

EPS, LB-EPS, and TB-EPS fractions including mixed-liquor. Table 22 exhibits the monovalent (K+,

Na+) and divalent (Mg

2+, Ca

2+) cations distribution in both digestates. Difference in divalent cations

concentrations between mixed liquor and combined different extracted EPS fractions exhibited the

higher abundance of divalent cations concentrations in pellet fraction of iron containing digestate than

non-iron containing digestate, but not in case of monovalent cations. On contrary, major share of

trivalent cations (Al3+, Fe3+) concentration was present in pellet fraction of both digestates. It was

observed that 87% of 2.1 mEq.L-1 (n=2) and 95% of 2.5 mEq.L-1 (n=2) of total Al3+ concentrations

were concentrated in pellet fractions of iron-conditioned and unconditioned digestates, respectively.

Akin, 95% of 19.5 mEq.L-1 (n=2) and 95% of 1.5 mEq.L-1 (n=2) of total Fe3+ concentrations were

concentrated in pellet fractions of iron-conditioned and unconditioned sludges, respectively. This

affirms only a negligible fraction of trivalent cations (Al3+, Fe3+) was present in other three extracted

EPS fractions. These analyses suggest divalent and trivalent cations remained firmly bound within

the sludge flocs while monovalent cations were freely distributed at the outer parts of both digestate

flocs (Table 22). We found concentrations of divalent cations (considered herein) in all EPS fractions

were relatively higher in iron-conditioned digestates. The presence of divalent/trivalent cations firmly

associated within sludge flocs promote the sludge flocs strength and stability (Li et al., 2012). Such a

phenomenon, in turn, may affect the M+/D++ cations ratio in sludge flocs, which is reported to

influence sludge dewaterability (Higgins et al., 2004).

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Figure 47. (a) Variations in monovalent-to-divalent (M+/D++) cations ratio values in iron-conditioned

AD-E (n=2) and unconditioned digestates AD-C (n=2); (b) Changes in size distribution of particles

in both digestates AD-E (n=3) and AD-C (n=3)

141

Table 21. Changes in intensities of fluorescence spectral parameters of different EPS fractions in iron-conditioned and unconditioned digestates

FRI* parameters Iron-conditioned (AD-E1, AD-E2) Unconditioned (AD-C1, AD-C2)

Organic

components

EEM

Regions

Excitation

(nm)

Emission

(nm)

Samples**

S-EPS

LB-EPS

TB-EPS

Samples**

S-EPS

LB-EPS TB-EPS

aromatic

protein

(tyrosine-

like)

P1 200-250 280-330 AD-E1 14.2 17.8 17.9 AD-C1 17.0 17.5 18.2

AD-E2 11.7 12.0 13.7 AD-C2 15.4 15.8 15.8

Average 13.0 14.9 15.8 Average 16.2 16.6 17.0

aromatic

protein

(tryptophan-

like)

P2 200-250 330-380 AD-E1 32.7 34.7 39.4 AD-C1 35.1 37.4 41.2

AD-E2 23.2 23.0 29.0 AD-C2 28.8 27.5 29.3

Average 28.0 28.9 34.2 Average 32.0 32.5 35.3

fulvic acid

(FA)-like

FA 200-260 380-500 AD-E1 26.4 20.9 17.5 AD-C1 22.0 20.3 16.2

AD-E2 30.6 24.6 27.7 AD-C2 25.2 25.7 26.0

Average 28.5 22.7 22.6 Average 23.6 23.0 21.1

soluble

microbial

product

(SMP)-like

SMP 250-280 310-380 AD-E1 12.9 13.8 16.0 AD-C1 14.1 14.1 15.9

AD-E2 12.8 16.7 13.2 AD-C2 14.2 13.5 13.7

Average 12.9 15.2 14.6 Average 14.2 13.8 14.8

humic acid

(HA)-like

HA 280-380 380-500 AD-E1 13.7 12.8 9.1 AD-C1 11.8 10.8 8.5

AD-E2 21.7 23.8 16.3 AD-C2 16.3 17.5 15.2

Average 17.7 18.3 12.7 Average 14.0 14.1 11.8

*Fluorescence regional integration (FRI); all samples diluted 20 times;

**Each set of samples (AD-E1 and AD-C1; AD-E2 and AD-C2) correspond to different sampling time from respective reactors. Sludge AD-E1 was sampled in conjunction with

AD-C1 at same time period from continuously operated both reactors; similar was the case for AD-E2 and AD-C2. However, each set of samples were sampled in a week interval

from respective AD reactors

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Table 22. Monovalent and divalent cations concentrations distribution in both iron-conditioned (AD-

E1, AD-E2) and unconditioned (AD-C1, AD-C2) digestates. Here, each set of samples (AD-E1/AD-

C1; AD-E2/AD-C2) correspond to different sampling time, i.e. sampled in a week interval from

respective AD-E and AD-C reactors, respectively.

Digestates

samples

Cations Concentrations in mixed-

liquor digestate sample

(mEq.L-1)

Concentrations in extracted EPS

fractions from digestates

(mEq.L-1)

S-EPS LB-EPS TB-EPS

AD-E1 Monovalent K+ 2.34 2.16 0.62 0.27

Na+ 6.42 6.87 7.65 7.80

Divalent Mg2+

9.65 2.62 0.76 0.42

Ca2+

17.84 3.85 1.22 0.64

AD-C1 Monovalent K+ 2.40 2.11 0.26 0.08

Na+ 8.34 8.20 8.02 8.27

Divalent Mg2+

7.83 1.40 0.18 0.20

Ca2+

10.38 1.41 0.23 0.21

AD-E2 Monovalent K+ 2.32 2.05 0.52 0.22

Na+ 6.72 6.33 7.86 8.01

Divalent Mg2+

9.52 2.61 0.61 0.37

Ca2+

16.16 4.32 1.11 0.66

AD-C2 Monovalent K+ 2.36 2.15 0.59 0.27

Na+ 8.16 7.85 7.92 7.95

Divalent Mg2+

8.35 2.44 0.98 0.55

Ca2+

10.05 2.60 0.69 0.37

143

For the estimation of bound water content (BWC), amount of heat absorption value (J.g-1) reflected

by the endothermic curve area as observed in DSC thermogram (see Figure 48), was used (see Section

3.6). Iron-conditioned digestate exhibited the lower BWC quantity as compared to the unconditioned

digestate. The BWC of iron-conditioned and unconditioned digestates was 91.50.1 wt(%) (n=3) and

93.20.1 wt(%) (n=3), respectively. Mean difference in BWC among the two digestates was

statistically different (p<0.05). The details of the calculations are provided in Table 23. The BWC of

iron containing digestate in terms of dry solids (DS) sludge mass was 15.10.2 g (g DS)-1, whilst it

was 21.90.06 g (g DS)-1 for the non-iron containing digestates. Mean differences in BWC between

the two digestates was statistically significant (p<0.05). Such differences in BWC contents could

result in significant change in digestates dewaterability. For further confirmation of this, the moisture

distribution in both digestates was analyzed using drying rate curves based on the thermogravimetric

(TG) measurements (see Section 2.3) (see Table 24). The results (see Figure 49) are in line with the

BWC determined using DSC thermograms.

144

Table 23. Changes in bound water content (BWC), total water content (TWC), and free water content (FWC) of iron-conditioned (AD-E) and

unconditioned (AD-C) digestates (conversion factor K = 0.0053 g.J-1). Here, digestate sample AD-E1 was sampled in conjunction with AD-C1 at same

time period from continuously operated both reactors; similar was the case for AD-E2/AD-C2 and AD-E3/AD-C3. Each set of samples were sampled in

a week interval from respective AD reactors

Digestates mass of samples

used for analysis

(mg)

endothermic curve

area in DSC

thermogram

(J.g-1)

Minima of

endothermic

peaks (°C)

Endothermic

curve area, A (J)

FW

content

(g)

FW

content

(wt%)

TWC

content

(wt%)

BWC

content

(wt%)

Iron

-condit

ioned

AD-E1 15.6 323.8 0.5 5.1 0.0 2.7 94.0 91.3

AD-E2 12.9 330.2 0.2 4.3 0.0 2.3 93.7 91.5

AD-E3 15.3 281.4 0.9 4.3 0.0 2.3 93.9 91.6

Unco

ndit

ioned

AD-C1 15.2 323.0 0.3 4.9 0.0 2.6 95.7 93.1

AD-C2 15.2 340.1 0.2 5.2 0.0 2.7 95.7 93.0

AD-C3 15.5 277.0 0.9 4.3 0.0 2.3 95.7 93.4

145

Table 24. Moisture distribution analysis of iron-conditioned (AD-E) and unconditioned (AD-C) digestates using drying rate curves, based on

thermogravimetric (TG) measurements

Digestates** Total

water

(g)

Total

solids

(g)

Initial moisture content of

sludge (g.g-1)

Different moisture components*

Free water

content

(%)

Interstitial and surface water

content

(%)

Bound water content

(or Intracellular water)

(%)

AD-E1 27.9 0.5 54.2 84.9 14.8 0.4

AD-E2 5.1 0.1 45.3 81.7 17.7 0.7

Average 16.5 0.3 49.8 83.3 16.3 0.6

AD-C1 6.7 0.1 59.0 78.0 20.4 1.6

AD-C2 6.5 0.2 42.8 84.2 14.0 1.8

Average 6.6 0.2 50.9 81.1 17.2 1.7

*All moisture content expressed in % initial moisture;

**Each set of samples (AD-E1 and AD-C1; AD-E2 and AD-C2) correspond to different sampling time from respective reactors, i.e. sampled on a

weekly basis from respective AD reactors

146

Figure 48. DSC thermograms of iron-conditioned (AD-E1, AD-E2, AD-E3) (left-half) and

unconditioned (AD-C1, AD-C2, AD-C3) (right-half, separated by dotted line) digestates. Here,

digestate sample AD-E1 was sampled in conjunction with AD-C1 at same time period from

continuously operated both reactors; similar was the case for AD-E2/AD-C2 and AD-E3/AD-C3.

Each set of samples were sampled in a week interval from respective AD reactors

147

Figure 49. Drying curves of 1st set of digestate samples with arithmetic abscissa: (a) AD-E1, (b) AD-

C1 (top-half); drying curves of 2nd set of digestate samples with arithmetic abscissa: (c) AD-E2, (d)

AD-C2 (bottom-half). Each set of samples (AD-E1 and AD-C1; AD-E2 and AD-C2) correspond to

different sampling time from respective reactors, i.e., sampled on a weekly basis from respective AD

reactors

6.3.3 Variations in morphological and fractal properties

Figure 47b compares the PSD curve for both iron-conditioned and unconditioned digestates. The

presented PSD curve of both digestates, correspond to the average of three different samples collected

at different dates from respective AD reactors. The PSD curve of both digestates were ‘monomodal’

in nature, however, size distribution in iron-conditioned digestate was relatively more left-skewed

suggesting the formation of larger-sized particles. This is supported by increased mean particle size

Dv50 values for iron-conditioned digestate as compared to the unconditioned digestate (Table 25).

The difference between mean Dv50 values among the two digestates was statistically significant

(p<0.05).

The comparative PSD analyses were also undertaken by estimating the volume density (%) of

particles in different size classes (Figure 50). We found that % share of supra-colloidal particles (1-

148

100 µm) showed marginal reduction wherein settleable particles (>100 µm) showed marginal

increment in all iron-conditioned digestates over the unconditioned digestates. The % share of supra-

colloidal particles (meanSEM, n=3) in volume-weighted PSD of iron-conditioned and

unconditioned digestates were 90.5±0.7% and 91.6±0.4%, respectively, while the % share of

settleable particles (meanSEM, n=3) were 9.5±0.7% and 8.4±0.4%, respectively. Mean differences

in the % share of both supra-colloidal and settleable particles between the digestates were not

statistically significant (p>0.05). However, it was reported that the decrease in supra-colloidal

particles size classes can be beneficial for sludge dewaterability, as previously reported (Yin et al.,

2004).

Table 25 shows the variation observed in the fractal dimension, Df values between both digestates.

The Df values (meanSEM, n=3) of iron-conditioned and unconditioned digestates were 1.620.01

and 1.640.003, respectively. Mean difference in the Df value (0.020.01) between the two digestates

was not statistically significant (p>0.05). The high Df value means compact/dense sludge flocs or

compact structure and vice-versa (Jin et al., 2004). The above results imply that the compactness of

iron-conditioned digestate remained unaffected, i.e. sludge structure was not loosened. This was

further supported by the values of aggregate structure factor (S) and 𝑅𝐻

𝑅𝐴 observed in both the digestates.

149

Table 25. Particle size specifications (mean particle size, Dv50 and percentiles) of iron-conditioned and unconditioned digestates. Determination of

fractal dimension Df, aggregate structure factor (S), and ratio between hydrodynamic radius (RH) to the radius of aggregate (RA), 𝑅𝐻

𝑅𝐴 values. Here, ‘n’ =

no. of analyzed samples, ‘SD’ = standard deviation, and values of Dv50 and percentiles including the values of Df, RH/RA, and (S) correspond to the mean

of 10 replicate measurements

Iron-conditioned digestates (AD-E) Unconditioned digestates (AD-C)

samples mean particle size and

percentiles (m)

Df

Mean

(SD)

(n=3)

RH/RA (S) samples mean particle size and

percentiles (m)

Df

Mean

(SD)

(n=3)

RH/RA (S)

Dv10 Dv50 Dv90 Dv10 Dv50 Dv90

AD-E1 12.6 35.8 91.7 1.60

(0.001)

0.60 0.36 AD-C1 11.3 34.9 97.6 1.64

(0.01)

0.62 0.39

AD-E2 12.4 37.8 99.9 1.63

(0.004)

0.62 0.39 AD-C2 11.5 33.1 95.1 1.65

(0.003)

0.63 0.40

AD-E3 12.4 36.7 91.6 1.63

(0.001)

0.62 0.39 AD-C3 12.0 34.4 90.3 1.64

(0.001)

0.63 0.40

Here, each set of samples (samples AD-E1/AD-C1, AD-E2/AD-C2, and AD-E3/AD-C3) were sampled at different time period from respective AD

reactors, i.e., sampled in a week interval from respective AD reactors

150

Figure 50. Particle fingerprints (or particle size distribution) analysis of both digestates: (a) samples

AD-E1, AD-C1; (b) samples AD-E2, AD-C2; and (c) samples AD-E3, AD-C3. Here, each set of

samples (as depicted in different sub-plots) were sampled at different sampling time from respective

AD reactors, i.e. sampled on a weekly basis from respective AD reactors

151

6.3.4 Variations in rheological properties

Steady shear rheological properties

Figure 51a shows variations in the relative sludge network strength values for both digestates,

calculated based on the totalized torque (TTQ) values (Nm.s) (Figure 52a). Relative sludge network

strength values (meanSEM, n=3) of iron-conditioned digestates were lower than the unconditioned

digestates, i.e., 57816.6 J.(kg.DS)-1 and 72022.6 J.(kg.DS)-1, respectively.

Viscosity is another important rheological parameter that might have some influence on digestate

dewaterability. Figure 51b-d show variations in shear viscosity (shear) as a function of shear rates of

50 s-1, 100 s-1, and 250 s-1 for both digestates. The shear values of iron-conditioned digestates under

different shear rates were lower than those of unconditioned digestates. These results were further

supported by the observed trends of apparent viscosities A (Figure 52b-c). The A values of both

digestates at low shear rate region decreased very sharply and remained fairly constant with the

increasing shear rate for both digestates, depicting their ‘shear-thinning property’. Albeit the

reduction in A of sludge depicted a somewhat similar trend, A values for iron-conditioned digestates

were lower than those for unconditioned digestates. Likewise, difference in infinite shear viscosity

values among the two digestates is depicted in Figure 52d. Iron-conditioned digestates depicted

lower values (meanSEM, n=3) (22.41.3 mPa.s) as compared to the unconditioned digestates

(25.20.4 mPa.s).

The CSR tests were undertaken to investigate the impact of shear time or shear history on flow

behavior of digestates. Figure 51e-f did not exhibit the hysteretic decline in the shear stress values in

rheogram of both digestates. Similar results were observed for other sets of samples (Figure 52e-f).

The results suggest that the previous shear stress history had little or no influence on flow behavior

for both digestates. Ascending and descending shear rate paths were almost identical in low shear rate

range (300 s-1) wherein ascending paths (up-flow curve) showed increasing trend as compared to

the descending path (down-flow curve) with further increment in shear rate. Irrespective of different

solids concentrations, both digestates exhibited a decline in the shear stress along with the release of

shear rate in the descending path. This suggests the thixotropic properties of both digestates. Besides,

the observed trends of up-flow and down-flow curves indicate some changes with ‘degree of

thixotropy’ between the digestates (Figure 51e-f).

152

To further corroborate the likely changes in the degree of sludge thixotropy as reflected by the

hysteresis loop area (Hla) values (Liu et al., 2016c), hysteresis loop tests were undertaken. Figure

51g-h present the results of a set of iron-conditioned and unconditioned digestates. Similar trends

were observed for other sets of samples (Figure 52g-h). Likewise, the Hla values are presented in

Table 26. Iron-conditioned digestate exhibited lower Hla values indicating iron-conditioned digestate

is comparatively less thixotropic than the unconditioned digestate, which could be due to the weaker

colloidal forces existing amongst the iron-conditioned sludge particles. In retrospect, results further

suggest that both digestates exhibit the thixotropic property, without showing a clear hysteresis.

The CSS tests were undertaken for determining the yield stress (y) and flow stress (f) values. The

y values were determined from strain-stress curves (Figure 53) and the results are presented in Table

26. The observed lower y and f values for iron-conditioned digestates as compared to the

unconditioned digestates, suggests that iron-conditioned digestate is likely to impart less shear

resistance against the applied shear, owing to inherent lower viscosity as previously observed (Figure

51b-d).

153


(AD-E) and unconditioned digestate (AD-C) samples: (a) relative sludge network strength values and

for this shear rate was increased from 0-300 s-1 in linear ramp manner for 76 s during measurement;

(b)-(d) sludge shear viscosity (shear) as a function of shear rates 50 s-1, 100 s-1, and 250 s-1; (e)-(f)

CSR tests; and (g)-(h) hysteresis loop tests results, showing the ascending and descending flow

curves. Here, iron-conditioned digestate sample AD-E1 was sampled concomitantly with

unconditioned digestate sample AD-C1 from respective experimental and control AD reactors

154


(AD-E) and unconditioned digestate (AD-C) samples: (a) totalized torque (TTQ) values, which

adopted an increment of shear rate in linear ramp manner from 0-300 s-1 for 76 s during measurement;

(b)-(c) apparent viscosity, A values as a function of shear rates; (d) infinite shear viscosity, values;

(e)-(f) CSR tests; and (g)-(h) hysteresis loop tests results, showing the ascending and descending flow

155

curves. Here, digestate sample AD-E1 was sampled concomitantly with AD-C1 from respective

experimental and control AD reactors and similar was the case for AD-E2 and AD-C2. Each set of

samples were sampled in a week interval from respective AD reactors

Table 26. Changes observed in hysteresis loop area (Hla), yield (y), and flow stress (f) values for

iron-conditioned (AD-E) and unconditioned digestate (AD-C) samples

Analysed

different sets of

samples

Digestate

samples

Hla

(Pa.s-1) TS

(g.L-1)

Yield stress,y

upward

inflection point

yield point (Pa)

flow stress, f,

upward

inflection point

yield point (Pa)

I AD-E1 27.3 15.9 (0.04) 0.61 2.15

AD-C1 83.4 11.9 (0.72) 1.97 2.97

II AD-E2 36.2 14.9 (0.16) 0.98 1.97

AD-C2 62.2 11.6 (0.19) 1.38 2.86

III AD-E3 137.2 15.7 (0.78) 0.80 2.29

AD-C3 156.8 13.3 (2.24) 2.34 3.71 iron-conditioned digestate sample AD-E1 was sampled concomitantly with unconditioned

digestate sample AD-C1 from respective experimental and control AD reactors and similar was

the case for other sets of samples AD-E2/AD-C2 and AD-E3/AD-C3. Here, each set of samples

were sampled in a week interval from respective AD reactors standard deviation (SD) of triplicate analysis

156

Figure 53. CSS test results of iron-conditioned (AD-E, left half) and unconditioned (AD-C, right

half) digestate samples: (a) AD-E1; (b) AD-C1; (c) AD-E2; (d) AD-C2, (e) AD-E3; and (f) AD-C3.

Here, iron-conditioned digestate sample AD-E1 was sampled concomitantly with unconditioned

digestate sample AD-C1 from respective experimental and control AD reactors and similar was the

case for AD-E2/AD-C2 and AD-E3/AD-C3. Each set of samples were sampled in a week interval

from respective AD reactors

Dynamic shear rheological properties

The changes in viscoelastic rheological properties between iron-conditioned and unconditioned

digestates are shown in Figure 54a-f. Effect of amplitude of oscillation on rheology of both digestates

was evaluated by SAS test (Figure 54a-d). Clearly, SAS test results depict the differences observed

157

in different storage/loss/complex moduli (G/G/G*) between the digestates (Figure 54b-d). As

observed, two moduli depict G > G in both iron-conditioned and unconditioned digestate (Figure

54a) suggesting the existence of ‘solid-like properties (elastic characteristics)’. Both G and G values

representing elastic and viscous property of sludge (Baudez et al., 2013), respectively were lower in

iron-conditioned digestate than the unconditioned digestate (Figure 54b-c). Also, G* values are

comparatively higher for unconditioned digestate (Figure 54d). This implies the influence of iron

containing WAS on both the elastic and viscous behavior of digestate.

The creep responses of both digestates elucidating the variation of creep compliance, J(t) (Pa-1) and

shear strain (%) with time are shown in Figure 54e-f. Both creep compliance and shear strain (%) for

iron-conditioned digestates were found to be higher. Increased creep compliance suggests that iron-

conditioned digestate is easily deformed by a given stress, as earlier suggested (Ruiz-Hernando et al.,

2014). Also, lower J(t) values implies the existence of stronger internal structure in sludge and vice-

versa. Notably, the recovery regime after stoppage of applied stress in both digestates was observed,

implying no occurrence of irreversible deformation (Figure 54e). The extent of deformation was

comparatively higher in unconditioned digestates than iron-conditioned digestates during creep

recovery phase. Figure 54f shows the higher growth in shear strain (%) within the observed time

frame of creep test in iron-conditioned digestates than the unconditioned digestates. This increase in

shear strain (%) indicates iron-conditioned digestate is subjected to extra shear, possibly due to

reduced deformation resistance (Figure 54e). Reduced deformation resistance in iron-conditioned

digestate is evidenced by the decreased G* moduli (Figure 54d).

For further characterization of the digestates, rheological models were fitted to the shear stress-shear

rate flow curves at varying TS contents (see Section 6.2.5 and Section 3.7.2). Different rheological

model parameters were calculated for iron-conditioned and unconditioned digestates. The fitting

results based on coefficient of determination (R2) and Akaike’s information criteria (AICc) values

indicate that power law model was the best-fit model to represent the flow behavior (Table 27 and

Table 28). We found that both digestates exhibit shear-thinning or pseudoplastic behavior as revealed

by flow behavior index (n values, i.e. n<1). Variations of power law model parameters (K – flow

consistency coefficient and n) with the TS contents demonstrated quite contrasting trend in between

iron-conditioned and unconditioned digestates. We observed the lower value of K and higher value

of n with the increasing TS contents in iron-conditioned digestates, however this was not case with

the unconditioned digestates. If we compare the overall trends of K and n values between both

158

digestates, iron-conditioned digestate exhibits the high K and low n values with reference to the

Power-law model.

Figure 54. (a)-(d) Evolution of storage (G), loss (G), and complex (G*) moduli in iron-conditioned

(AD-E) and unconditioned (AD-C) digestates during amplitude sweep oscillation (i.e. SAS) tests as

a function of applied shear strain range 0.01-1000%, angular frequency 5 rad.s-1, and at 250.01C;

(e)-(f) creep-recovery test: (e) response of creep compliance J(t) with respect to creep time; (f)

response of shear strain (%) with respect to creep time. Here, iron-conditioned digestate sample AD-

E1 was sampled concomitantly with unconditioned digestate sample AD-C1 from respective AD

reactors and similar was the case for other sets of samples AD-E2/AD-C2. Each set of samples were

sampled in a week interval from respective AD reactors

159

Table 27. Fitting results of different rheological models of iron-conditioned digestates (temperature

= 25±0.01°C)

Model parameters Iron-conditioned digestates (AD-E)

AD-E1

(17.33 g.TS.L-1)

AD-E2

(17.5 g.TS.L-1)

AD-E3

(17.69 g.TS.L-1)

Bingham model

Bingham yield stress (Pa) 2.10 3.00 2.70

Bingham plastic viscosity (Pa.s) 0.035 0.036 0.037

R2 0.90 0.91 0.91

Adjusted-R2 0.90 0.91 0.91

Absolute sum of squares 82.00 75.00 73.00

Sy.x 1.10 1.00 0.99

RMSE 1.00 1.00 0.99

AICc 6.88 3.89 2.98

Power law model

K (Pa.s) 1.15 1.62 1.02

n 0.38 0.33 0.43

R2 0.92 0.93 0.96

Adjusted-R2 0.92 0.93 0.96


Sy.x 0.087 0.072 0.066

RMSE 0.087 0.071 0.065

AICc 37.11 37.09 22.94

Herschel-Bulkley model

H-B yield stress (Pa) 0.98 0.796 0.912

Consistency index, KH -0.29 -0.12 -0.24

Flow behaviour index, nH 0.51 0.47 0.52

R2 0.83 0.89 0.9

Adjusted-R2 0.82 0.88 0.9


Sy.x 0.094 0.067 0.07

RMSE 0.093 0.067 0.069

AICc 163.86 155.00 165.97

Casson model

Casson yield stress (Pa) 1.00 1.44 1.21

Casson plastic viscosity (Pa.s) 0.020 0.0196 0.0225

R2 0.87 0.89 0.9

Adjusted-R2 0.87 0.89 0.9

Absolute sum of squares 4 3.1 3.2

Sy.x 0.23 0.2 0.21

RMSE 0.23 0.2 0.21

AICc 128.37 136.33 134.88 Sy.x – standard error of estimate; RMSE – root mean square error; AICc – Akaike’s information

criteria

160

Table 28. Fitting results of different rheological models of unconditioned digestates (temperature =

25±0.01°C)

Model parameters Unconditioned digestates (AD-C)

AD-C1

(12.0 g.TS.L-1)

AD-C2

(12.66 g.TS.L-1)

AD-C3

(13.33 g.TS.L-1)

Bingham model

Bingham yield stress (Pa) 1.60 1.70 1.50

Bingham plastic viscosity (Pa.s) 0.036 0.036 0.036

R2 0.90 0.91 0.90

Adjusted-R2 0.90 0.91 0.90


Sy.x 1.10 1.00 1.00

RMSE 1.00 1.00 1.00

AICc 6.93 4.20 6.36

Power law model

K (Pa.s) 1.16 1.66 1.16

n 0.39 0.29 0.36

R2 0.91 0.80 0.88

Adjusted-R2 0.91 0.79 0.87


Sy.x 0.099 0.12 0.11

RMSE 0.098 0.12 0.11

AICc 42.49 52.82 46.56

Herschel-Bulkley model

H-B yield stress (Pa) 1.38 1.97 2.34

Consistency index, KH -0.71 -1.10 -2.00

Flow behaviour index, nH 0.67 0.85 1.20

R2 0.87 0.91 0.86

Adjusted-R2 0.87 0.91 0.86


Sy.x 0.10 0.10 0.18

RMSE 0.10 0.10 0.18

AICc 225.04 304.20 463.65

Casson model

Casson yield stress (Pa) 0.7396 0.8464 0.6724

Casson plastic viscosity (Pa.s) 0.0225 0.0225 0.0225

R2 0.88 0.90 0.89

Adjusted-R2 0.88 0.90 0.89


Sy.x 0.23 0.21 0.23

RMSE 0.23 0.21 0.22

AICc 124.36 126.44 124.46 Sy.x – standard error of estimate; RMSE – root mean square error; AICc – Akaike’s information

criteria

161

6.4 Discussion

Sewer-dosed FeCl3 and subsequent Fe-availability in AD during integrated sewer-WWTP operation

have been found to exhibit some significant positive impacts on the different key properties of iron-

conditioned digestate. These include changes in content/composition of different EPS fractions,

bound water content (BWC), cations distribution, particle size distribution (PSD), and rheology, as

outlined in Figure 55. We observed not only a reduction in S-EPS contents (Figure 46a), also found

decreased BWC in iron-conditioned digestate (see Section 6.3.5). Such reduction in S-EPS content is

likely to improve dewaterability of iron-conditioned digestate, as suggested by previous studies (Dai

et al., 2017; Li and Yang, 2007). Increased soluble EPS fractions content implies increased interstitial

(or bound) water content in sludge (Chen et al., 2001; Sheng et al., 2010) and also increased sludge

viscosity (Li and Yang, 2007). Nagaoka et al. (Nagaoka et al., 1996) reported the positive correlation

of sludge viscosity with its soluble EPS content, owing to high hydratability of soluble EPS fractions.

Likewise, Yu et al. (Yu et al., 2008) revealed a degradation of sludge EPS promotes release of bound

water. It has also been reported that the increased bound water negatively influences the sludge

dewaterability (Yuan et al., 2017; Zhang et al., 2014) as bound water is intricately associated with the

sludge floc structures and EPS compositions (Vaxelaire and Cézac, 2004). These foregoing results

indicate that a close interrelation existing among soluble EPS content, bound water, and sludge

viscosity might have positively affected the dewaterability of iron-conditioned digestate (Figure 45).

Besides, favorable changes in organic compositions of EPS, particularly the decreased protein (PN)

contents (Figure 46b-e) of iron-conditioned digestate, can also positively influence sludge

dewaterability. This can be attributed to the high water-holding capacity of PN fractions in sludge

(Cetin and Erdincler, 2004; Sponza, 2002). Akin, the decreased polysaccharides (PS) contents in S-

EPS fractions of iron-conditioned digestate (Figure 46b-e), is also likely to positively influence the

dewaterability (Zhou et al., 2015).

Cations distribution in sludge matrix, particularly M+/D++ cations ratio in sludge flocs is another factor

that influences sludge dewaterability. This is because higher M+/D++ cations ratio means the excess

monovalent cations concentrations, which can cause deterioration in the sludge floc structure

(Higgins and Novak, 1997a). Previous studies have also shown increased M+/D++ cations ratio in

sludge matrix resulting in the increased soluble-phosphorus concentration as the soluble-P is reported

to bind more water to solids (Higgins et al., 2014; Rus et al., 2017). We observed the decreased

M+/D++ ratio in iron-conditioned digestate (Figure 47a), which implies possible lower BWC (see

Section 6.3.5) and hence improved dewaterability (Figure 45).

162

In terms of the changes in morphological properties of digestate, particle size distribution is another

important factor likely to influence the digestate dewaterability as evidenced by Carman-Kozeny

equation (Karr and Keinath, 1978). Increased particle size is reported to reduce exposure of fewer

sludge particles surfaces and also the hydrophilicity of sludge flocs, thereby causing improvement in

dewaterability (Zhen et al., 2012). The beneficial impact of larger sludge particles on sludge

dewatering was also noted by Dai et al. (Dai et al., 2018). We observed relatively marginal increase

in the Dv50 of iron-conditioned digestates (Table 25), which suggests that the improvement of

dewaterability in this case could also be attributed to the change in particle size. This was further

evidenced by the slightly left-skewed PSD curve observed in iron-conditioned digestate, suggesting

the possible aggregation of sludge particles/flocs (Figure 47b).

The changes in physicochemical and morphological properties are also reflected by the changes in

rheological properties of digestates. Iron-conditioned digestate showed a reduction in the relative

sludge network strength (Figure 51a), suggesting its greater ability to release the most of its

incorporated water (Abu-Orf Mohammad and Örmeci, 2005; Ormeci et al., 2004). Such ease in the

release of water implies improved digestate dewaterability. Ormeci et al. (2004) reported that

effective dewatering depends on the strength of aggregates within the sludge matrix. Similarly, the

viscosities (shear, A, and

) of iron-conditioned digestate were lower as compared to unconditioned

digestate (see Section 6.3.7). Reduced viscosity suggests an enhancement in the digestate fluidity and

hence better dewaterability (Li and Yang, 2007). In consequence, iron-conditioned digestate

exhibited the decreased y values (Table 26), which reflects the lesser shear resistance against the

applied shear as y represents the critical resistance that must be exceeded before flow occurs (Møller

et al., 2006). Reduced viscosities and y of iron-conditioned digestate are further complemented by

the decreased Hla values (Table 26), indicating that iron-conditioned digestate is less thixotropic than

unconditioned digestate. This could be corroborated to the existence of weakened colloidal forces

amongst the iron-conditioned sludge particles, as previously reported (Liu et al., 2016a; Liu et al.,

2016c). In addition, iron-conditioned digestate showed decrease in storage/loss/complex moduli

(G/G/G*) values (Figure 54a-d). The decrease in G and G values suggests the weakening sludge

structure or network strength (Bobade et al., 2017; Feng et al., 2014a), while a reduced G* value

implies the weaker deformation resistance (Feng et al., 2014a). These results are in line with the trend

of creep compliance J(t) values (Figure 54e), which were higher in iron-conditioned digestate

implying lesser stiffness and reduced deformation resistance as compared to the unconditioned

digestate, possibly due to the weaker internal structure. Such reduced deformation resistance is likely

responsible for the higher growth of shear strain (%) in iron-conditioned digestate (Figure 54f).

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Consequently, the extent of deformation was relatively higher in unconditioned digestate (Figure

54e). However, no irreversible deformation occurred in both digestates as depicted by the recovery

regime aftermath of stoppage of applied shear (Figure 54e). Notably, the increased deformation

resistance in unconditioned digestate is further favored by the relatively high K and low n values

concerning power-law model parameters (Table 27 and Table 28). This further indicates that

unconditioned digestate may exhibit the relatively greater degrees of shear-thinning (or

pseudoplasticity) and flow consistency (or stiffness). This is because smaller is the value of n, more

shear-thinning is the sludge and vice-versa, wherein K value reflects the average firmness of sludge

(Liu et al., 2016c). Increased flow consistency can result in increased viscosity as both material’s

viscosity and consistency are interrelated. This likely explains why unconditioned digestate exhibited

increased viscosity (Figure 51b-f), negatively impacting its dewaterability. Nonetheless, observation

of G>G (Figure 54a-d) suggest that both digestates exhibit the elastic (solid-like) behavior.

However, decreased viscoelastic parameters (G, G) in iron-conditioned digestate as compared to

the unconditioned digestate (Figure 54b-c), indicates that the weakened viscoelastic behavior of iron-

conditioned digestate.

Based on foregoing experimental results, we can posit that the digestion of the Fe-rich WAS (resultant

of sewer-dosed FeCl3) in AD resulted in the improved dewaterability of iron-conditioned digestate as

compared to unconditioned digestate (Figure 45). Such a phenomenon is due to the combined

synergistic effect of favorable changes observed in physicochemical, morphological, and rheological

properties of iron-conditioned digestate, as demonstrated in Figure 55.

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Figure 55. Possible synergistic interplay amongst different factors behind improving dewaterability

of iron-conditioned digestate

6.5 Conclusion

This study experimentally demonstrated that the Fe-rich WAS generated from a bioreactor treating

wastewater receiving sewer-dosed FeCl3, when treated in AD during integrated sewer-WWTP

operation, exhibited improvement in dewaterability. Iron-conditioned digestate exhibited improved

dewaterability with dewatered cake solids content (%) of 19.20.1% as compared to unconditioned

digestate of 15.50.4%. To explain such contrasting dewaterability behavior between iron-

conditioned and unconditioned digestates, a comparative assessment of changes in different key

digestate properties was undertaken. The following conclusions were drawn from the comparative

assessment:

• Anaerobic digestion of Fe-rich WAS in an AD (operated under mesophilic condition) showed

positive impacts on the physicochemical, morphological, and rheological properties of iron-

conditioned digestate while its fractal property remained unaffected when compared to

unconditioned digestate.

• Iron-conditioned digestate showed relatively reduced contents of bound water, S-EPS

fraction, PN and PS. Likewise, there were decrease in values of particle size (DV50), M+/D++

cations ratio, viscosity, y, f, relative sludge network strength, storage/loss/complex

(G/G/G*) moduli but increase in creep compliance and shear strain (%) than unconditioned

digestate. Iron-conditioned digestate further exhibited relatively decreased deformation

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resistance against applied shear, including weakened viscoelastic behaviour, shear-thinning,

and flow consistency (or stiffness).

• Combined, all these foregoing results elucidating the favorable changes in key sludge

properties correspondingly underpin the factors likely contributing to the improved

dewaterability of iron-conditioned digestate. In retrospect, the results suggest that it was not

possible to pinpoint a single factor predominantly contributing to improving the

dewaterability. Such improvement in the digestate dewaterability translates into the

significant cost savings requisite for sludge handling and disposal.

Hence, the observed positive impacts on several key digestate properties linked directly with the

improved sludge dewaterability in the study further enhance the confidence of implementing sewer-

based Fe-salt dosing strategy for integrated sewer-wastewater treatment plant operation.

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Chapter 7

Effects of dosing iron- and aluminium-containing

waterworks sludge on sulfide and phosphate removal in

a pilot sewer

The chapter has been published and modified to be wholly incorporated in the Chapter 7: Sohan Shrestha, Jagadeeshkumar

Kulandaivelu, Keshab Sharma, Guangming Jiang, Zhiguo Yuan* (2020). Effects of dosing iron- and alum-containing

waterworks sludge on sulfide and phosphate removal in a pilot sewer. Chemical Engineering Journal, 387, 124073

(https://doi.org/10.1016/j.cej.2020.124073).

https://doi.org/10.1016/j.cej.2020.124073

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7.1 Introduction

Excess release of phosphorus (P) to freshwater bodies due to anthropogenic activity can cause

eutrophication (Wang et al., 2011a) or toxic algal blooms (Reichwaldt and Ghadouani, 2012), which

can negatively impact aquatic organisms and human health. Consequently, water utilities have been

subject to stringent P discharge standards in recent years. Achieving targeted P removal has been a

common practice in full-scale WWTPs, but the same approach has not been applied to sewers.

Sewage is also considered one of the main contributing sources of P reaching freshwater bodies, for

example, through sewer overflow (Bowes et al., 2015).

Likewise, sulfide build-up in sewer networks is also a serious issue causing health hazards, nuisance

odour, and in-sewer corrosion (Pikaar et al., 2014). Inorganic salts, particularly iron (Fe)-salts, are

commonly used for controlling sulfide in sewers (Ganigue et al., 2011b). However, effective sulfide

control demands continuous Fe-salt dosing, which incurs high operational costs. The global cost of

inorganic coagulants used for water/wastewater treatment in 2018 was $1.37 billion, and this is

predicted to reach $1.84 billion by 2023 (BCC-Research, 2018). Considering the enormous cost of

chemical dosing, seeking low costs alternatives is a major imperative. In this context, the reuse of

cost-effective materials such as waterworks aluminium-rich or iron-rich sludge (denoted as ‘Al- or

Fe-sludge’ hereafter) as alternatives to chemical coagulants (Al-, Fe-salts), is an appealing solution

for both sulfide and phosphorus removal in sewers.

Waterworks Al- or Fe-sludge, are inevitable by-products in water treatment plants (WTPs), when Al-

or Fe-salt is used as primary coagulant. Babatunde and Zhao (2007) reported that the average

production of WTP sludge globally exceeds 3.65106 dry tonnes per annum. Annual production of

WTP sludge by an Australian water utility varies between 150 to 43,500 dry tonnes per annum

(Dassanayake et al., 2015; GHD, 2015). The production of WTP sludge is expected to increase over

the years, considering the growing demand for potable water by a rapidly increasing global

population. Hence, sustainable management of such enormous volumes WTP sludge is essential.

Traditionally waterworks sludge has been dried and stockpiled on-site for years, however it is

becoming common to dispose of WTP sludge in sewers, lagoons, and landfill sites (GHD, 2015;

Verrelli, 2008b). The disposal options for WTP sludge, vary depending on country, local conditions

and size of WTP operation (Russell and Peck, 1998a). In Australia, end use or disposal of WTP sludge

varies in each State (GHD, 2015). Of particular interest is disposal of WTP sludge to sewers, which

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is more common in Europe, the U.K. and the U.S.A. (Kawamura, 2000; Keeley et al., 2014). In doing

so, WTP sludge could be treated together with sewage sludge in the downstream WWTP, offering

potentially wide-ranging economic benefits (Verrelli, 2008b).

In recent years, there has been growing interest in the direct reuse of waterworks Al- and Fe-sludge

in sewers, but the impacts of such practice are not well understood. Studies on the feasibility of

reusing Al-sludge for phosphate (Babatunde and Zhao, 2010; Ippolito et al., 2003; Makris et al.,

2004b; Zhao et al., 2007) or particulate pollutants removal (Guan et al., 2005a), were based on bench-

scale experiments, often using synthetic wastewater. Studies reusing Fe-sludge for phosphate removal

(Leader et al., 2008; Makris et al., 2004b) and sulfide removal (Sun et al., 2015) also adopted a similar

approach. In terms of full-scale application, Edwards et al. (1997) showed a substantial reduction in

sulfides in digester gas of a receiving WWTP on direct application of WTP Fe-sludge to real sewers,

but the efficacy of Al-sludge on sulfide removal in the digester gas was marginal. The influence of

Fe-sludge dosing on control of sulfide in sewers was not investigated. To our best knowledge, there

have been no comprehensive studies to date on the application of waterworks Al- and Fe-sludge to

sewers at pilot- and full-scale and their respective roles in sulfide and phosphate removal. In addition,

the impacts on other sewage characteristics, such as particulate pollutants, dissolved methane, and

nitrous oxide, are not fully understood. Successful reuse of Al- and Fe-sludge instead of chemical

coagulants would have a major impact on both sustainable WTP sludge management and urban

wastewater management. Undoubtedly, reuse of waterworks sludge will deliver both economic and

environmental benefits for water utilities, by reducing the burden of WTP sludge treatment/disposal,

and reducing chemical consumption in urban water system.

In this study, we aim to investigate the impact of reusing waterworks Al- and Fe-sludge on sulfide,

phosphate, and other major sewage characteristics. Two pilot-scale rising main (RM) sewers are used

in this study, one as an experimental system, and the other as a control. For this, two sets of

experiments were conducted, reusing Fe-sludge and Al-sludge, respectively. These sludges were

sourced from two different WTPs. Batch tests were also undertaken to assess impacts of Al:P dosage

ratio and suspended solids on phosphate removal in sewage.

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7.2 Material and methods

7.2.1 Pilot rising mains set-up and operation

This study was conducted on two pilot rising main (RM) sewers, located at the Luggage Point WWTP

(Queensland, Australia). Each of the two RM pipes has an internal diameter of 0.1 m (A/V = 4.0/0.1

m = 40 m−1) and a length of 300 m. One of the sewer pipes was operated as ‘control’ and the other as

‘experimental’ line. These pilot sewers were supplied with wastewater, directed from the inlet of the

Luggage Point WWTP to a storage tank (Tank 1) located adjacent to the pilot sewer systems (see

Figure 8 and Figure 9). Three sampling ports were installed in both sewer lines at the locations of 15

m, 105 m, and 210 m for manual sampling.

7.2.2 Fe- and Al-sludge dosing to pilot sewer

The Fe-sludge was obtained from the Gold Coast Desalination Plant located at Tugun, Queensland,

Australia. The Al-sludge was obtained from Mount Crosby Westbank Water Treatment Plant

(Queensland, Australia). The Fe- and Al-sludges were obtained in slurry and dewatered sludge cake

forms, respectively (Figure 56).

Prior to feeding into the system, the Fe-sludge was mixed and diluted with subnatant of the Dissolved

Air Floatation (DAF) unit of Luggage Point WWTP. Such mixing was done in advance of feeding

raw wastewater to the sewer lines. Dilution of the sludge was undertaken herein to make the sludge

‘pumpable’ into sewer pipe. The targeted total solids (TS) elevation of 1.0 g.L-1 inside the sewer pipes

was selected based on the local trade waste sewer acceptance guidelines. The characteristics of both

sludges, DAF subnatant used for dilution, and the sewer feed wastewater are given in Table 29.

Both sewer pipes were at pseudo-steady state steady state prior to sludge dosing experiment. At the

beginning of the experiment, both sewer pipes were replenished with fresh raw wastewater by running

the feed pumps continuously for 15 min. For this, flow rate in sewer pipes was maintained at 275

L.min−1, which corresponds to an in-pipe liquid velocity of 0.6 m.s−1. Once the RM feed pumps were

turned off, the re-circulation pumps (Figure 9) were turned on, which re-circulated wastewater, at a

flow rate of 110 L.min-1, i.e. 0.22 m.s-1 flow velocity, from 240 m and back to the start of the pipe (at

4 m) in both sewer lines, with an aim to keep the solids in suspension during the experiment. The

waterworks Fe- (Experiment 1) or Al-sludge (Experiment 2) in Tank 2 was then dosed into the

experimental sewer line at flow rate of 12 L.min-1 for 20 min (total dosage = 240 L). This flow rate

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was maintained by a peristaltic pump (L/S Precision Modular Drive, Cole Parmer, United States).

The submersible pump was used in the sludge feed tank (Tank 2) to achieve proper mixing of diluted

Fe-/Al-sludge during injection of sludge mixed liquor to the experimental line. The dosing amount of

Fe-/Al-sludge was optimized to achieve the targeted TS concentration. The re-circulation mode was

maintained for 6 hr, within the typical range of hydraulic retention time for real sewer pipes.

To assess the impacts of Fe-/Al-sludge dosing on dissolved sulfide, phosphate, and other sewage

characteristics, wastewater quality parameters were monitored through grab sampling. However, the

sediment depth or composition of settled materials in the sewer pipes were not measured during both

Fe-/Al-sludge dosing tests. Grab samples were taken before (pre-dosing samples, t0 = 0 min) and

after sludge dosing at pre-designated time intervals over 6 hr (t20 = 20 min, t40 = 40 min, t60 = 60 min,

t120 = 120 min, t180 = 180 min, t240 = 240 min, t300 = 300 min, t360 = 360 min). The grab samples were

taken simultaneously at three different locations (15 m, 105 m, and 210 m) in both sewer pipes (Figure

9). Considering the equilibrium conditions maintained throughout the pipe, sampling at three

locations was considered triplicate (n=3). Wastewater samples were analyzed, using the methods

outlined in Section 7.2.4, for total and volatile solids, total and soluble Fe/Al, total and soluble

chemical oxygen demand (COD), dissolved sulfur species, and phosphate (PO43-) concentrations. In

addition, pH and temperature were monitored online in both sewer lines (Figure 9).

For the Fe-sludge dosing test, samples were taken from the feed tank (Tank 2) (during the sludge

feeding period) and the experimental line at the end of the test for characterization using X-ray

Diffraction (XRD), Scanning Electron Microscopy coupled with Energy Dispersive X-Ray (SEM-

EDX), and Attenuated Total Reflectance-Fourier Transform Infrared (ATR–FTIR) spectroscopy.

These analyses were carried out to understand the possible mechanisms behind dissolved sulfide and

phosphate removal when reusing Fe-sludge. Details of these analyses are provided in Section 7.2.4.

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Figure 56. (a) Fe-sludge obtained from desalination water treatment plant, (b) Al-sludge obtained

from fresh/surface-water treatment plant, (c)-(d) Visual inspection of color change in sewage

following Fe-sludge dosing: (c) sewage color prior to dosing, (d) sewage color after dosing

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Table 29. Characteristics of feed wastewater (raw sewage), DAF subnatant (used as diluent), Fe-/Al-sludge including diluted Fe-/Al-sludge (n = number

of measurements as indicated in parentheses; if n is not stated, a single measurement was taken)

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7.2.3 Batch tests to investigate effects of Al:P dosage ratio and suspended solids on phosphate

removal

Batch tests were carried out on unfiltered and filtered sewage, at various Al:P molar ratios, to evaluate

the effects of Al:P dosage ratio and suspended solids on phosphate removal. This was required as Al-

sludge was dosed in excess during the pilot study. All tests were carried out in borosilicate glass

reactors, with an unsealed port for Al-sludge dosing and sampling, and two other ports for a dissolved

oxygen (DO) probe (626250-1) with YSI ProODO handheld optical DO meter (John Morris), and a

TPS pH probe (EPSUN5, Plastic, AgCl Ref) with minichem-pH controller (TPS, Version 2.1.1),

respectively. The pH and DO probes were pre-calibrated prior to each test, as per the manufacturer’s

protocol. All the reactors were mixed with magnetic stirrers (256 mm) at 250 rpm (Figure 57). The

filtered sewage was prepared using glass microfiber filters [CAT No. 1822-047, Grade GF/CTM (1.2

m). Al-sludge was dosed into the reactor at various dosing rates, based on the molar ratio (Al:P) of

the total Al concentration versus total dissolved P concentration in the sewage. Both pH and DO were

measured online. Prior to each test, the reactor was filled with fresh sewage (no headspace). Each test

was performed in duplicate (n=2) at pH 7.50.1, with DO 0.70.1 mg.L-1, and at ambient temperature

of 242.0 C. An overview of the experimental design is presented in Table 30.

During each test, total Al (Al(T)), total dissolved Al (Al(sol.)), and phosphate (PO43-) concentrations

were monitored and analyzed using methods described in Section 7.2.4. Samples were taken before-

(t0 = 0 min) and after Al-sludge dosing at pre-designated time intervals (t10 = 10 min, t30 = 30 min, t60

= 60 min, t90 = 90 min, t120 = 120 min). Samples taken at t0 = 0 min (before Al-sludge dosing) and

t120 = 120 min (following end of test) during the batch tests 1, 3, and 4 (using unfiltered sewage),

were further characterized using Attenuated Total Reflectance-Fourier Transform Infrared (ATR–

FTIR) including 27Al and 31P solid state Nuclear Magnetic Resonance spectroscopy (see Section

7.2.4). The samples taken t0 = 0 min were also characterized using X-ray diffraction (XRD) analysis.

These XRD and spectroscopic analyses were undertaken to determine the mechanism behind PO43-

removal, when dosing Al-sludge.

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Figure 57. Laboratory set up for batch tests to investigate effects of Al: PO43- dosage ratio and

suspended solids on phosphate removal. Here, all tests were carried out in borosilicate glass reactors

Table 30. Overview of experimental design for batch tests to investigate effects of Al:P dosage ratio

and suspended solids on phosphate removal. Here, test duration = 2 hr, number of replicates, n = 2

Batch tests Test No. Al:P molar ratio

Tests using unfiltered sewage 1 1:1

2 1.5:1

3 2:1

4 3:1

Tests using filtered sewage 5 2:1

6 3:1


For measurement of dissolved sulfur species (sulfide, sulfate, sulfite, thiosulfate) and chloride (Cl-)

concentrations, 1.5 mL sample was filtered (0.22 μm, Millipore, Millex GP) immediately after

collection, and preserved with a 0.5 mL sulfide anti-oxidant buffer (SAOB) solution. Samples were

then analysed using ion chromatography (IC) with a UV and conductivity detector (Dionex ICS-

2000), as described elsewhere (Keller-Lehmann et al. 2006). Samples for phosphate (PO43-) and

ammonium (NH4+) analysis were filtered (0.22 μm, Millipore, Millex GP) immediately after

sampling, and then analysed using a Lachat QuickChem 8000 flow injection analyser (FIA) (Lachat

instrument, Milwaukee, Wisconsin). Total Fe (Fe(T)), Al (Al(T)), P (P(T)), and S (S(T)) concentrations

(dissolved + particulate) in unfiltered samples, and total dissolved Fe (Fe(sol.)), Al (Al(sol.)), P (P(sol.)),

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and S (S(sol.)) concentrations in filtered samples (0.22 μm, Millipore, Millex GP), were measured using

Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES) (Perkin Elmer Optima

7300DV, Waltham, MA, USA). Before ICP-OES analysis, samples were digested using 70% nitric

acid (HNO3). Total and volatile solids (TS, VS) and their suspended solids fractions (TSS, VSS) were

measured using standard methods (APHA, 2005). Total and soluble chemical oxygen demand (tCOD

and sCOD, respectively) were measured using COD cell test kits (Merck, range 25–1500 mg.COD.L-

1 and 500–10000 mg.COD.L-1). For sCOD determination, samples were filtered (0.22 μm, Millipore,

Millex GP) prior to analysis. Similarly, total organic carbon TOC content was measured using a TOC

analyzer (TOC-5000A, Shimadzu, Japan).

Dissolved methane (CH4) and nitrous oxide (N2O) were measured using the previously described

protocol (Liu et al., 2015; Sturm et al., 2015). Filtered (0.22 μm, Millipore, Millex GP) samples were

injected into a 12 mL vacuumed Exetainer tube. After achieving equilibrium in the tube, CH4 and

N2O in the gas phase were measured using a gas chromatograph (Shimadzu GC-9A) equipped with a

flame ionization detector (FID). The concentrations of CH4 and N2O were calculated using mass

balance and Henry's Law.

In the Fe-sludge dosing study, Fe-sludge samples collected before- and after dosing into the

experimental sewer line were characterised by using X-ray diffraction (XRD), Scanning Electron

Microscopy coupled with Energy Dispersive X-Ray (SEM-EDX) and Attentuated Total Reflectance -

Fourier Transform Infrared (FTIR) spectroscopy. In the Al-sludge dosing study, freshly collected sludge

samples were characterised by XRD. In addition, unfiltered sewage samples obtained before- and after Al-

sludge dosage at various Al:PO43- molar ratios, were analysed using both ATR-FTIR and Solid-State

Nuclear Magnetic Resonance (NMR) spectroscopy. Details of XRD, SEM-EDX, ATR-FTIR and 27Al

and 31P solid-state NMR analysis techniques are provided in Appendix E.


Mean values including associated SD and SEM were calculated for each parameter sampled at three

locations (15 m, 105 m, and 210 m, n=3). Notably, 240 L of Fe- or Al-sludge was added to the 236

m (=240 m - 4 m) sewer pipe (volume = 1850 L), giving a dilution of 11.5%. This dilution effect was

incorporated to all parameters in data analysis for the Fe-/Al-sludge dosing study (see Sections 7.3.1

and 7.3.3). Because of transition phase immediately post-dosing, data collected in the first 40 min

were not considered for the data analysis. Further, student’s t-test with Welch’s correction and a 95%

https://www.sciencedirect.com/topics/earth-and-planetary-sciences/vapor-phase

https://www.sciencedirect.com/topics/earth-and-planetary-sciences/gas-chromatography

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CI was applied to determine whether the differences observed between mean values of respective

parameters in control and experimental sewer lines, were statistically significant, based on the p-

values (p<0.05). All statistical tests were undertaken using GraphPad Prism software (version 7.03).

7.3 Results and discussion

7.3.1 Effects of Fe-sludge dosing on sewage characteristics

Figure 58a-f show the changes in suspended solids, Fe, and Al concentrations with Fe-sludge dosing.

Mean differences in TSS and VSS concentrations between experimental and control sewer lines were

71.8±6.9 mg.TSS.L-1 (Figure 58a) and 25.6±2.9 mg.VSS.L-1, respectively (Figure 58b). A decreasing

trend in TSS and VSS concentration in both sewer lines was observed, which suggests the settling of

solids occurred in sewer pipes during recirculation at 0.22 m.s-1 flow velocity. The Fe(T)

concentrations also decreased over time, displaying a similar trend (Figure 58c). Mean Fe(T)

concentrations in control and experimental sewer lines were 2.0±0.3 mg.Fe.L-1 and 22.0±4.0 mg.Fe.L-

1, respectively. However, mean Fe(sol.) concentrations were relatively low at <0.5 mg.Fe.L-1 in both

control and experimental sewer pipes (Figure 58d). Interestingly, the concentration-time profiles of

Al(T) were similar to the Fe(T) trend (Figure 58e). Mean Al(sol.) concentrations were relatively low at

<0.1 mg.Al.L-1 in both sewer lines (Figure 58f). In addition, respective values for pH (7.0±0.02)

(Figure 59a) and temperature (25.6±0.4 C) (Figure 59b) were similar in both sewer lines during Fe-

sludge dosing.

Figure 60a-b show a decrease in sulfide, sulfite, and thiosulfate concentrations in the experimental

line. Notably, the total dissolved sulfides level initially present in the sewage was unusually high

16.0±0.3 mg.S.L-1 because the raw sewage was sourced from the inlet of the treatment plant (i.e. end

of the sewer network). Sulfide concentration decreased rapidly at the beginning of the test, followed

by a relatively slow increase with time. Dilution could be contributing to the initial decrease in sulfide

concentration as DAF subnatant does not contain sulfide (Table 29). In contrast, sulfide continued to

rise slowly in the control line. The mean difference in sulfide concentration between the control and

experimental sewer lines was 12.8±0.5 mg.S.L-1 (p<0.05), equivalent to 80% of the sulfide

concentration in raw sewage (Table 29). Overall, sulfide concentration decreased by 57.61.3% in

the experimental line (Figure 60a). The total dissolved sulfide removed per total Fe added (as Fe-

sludge) was 0.290.06 mg.S.(mg.Fe)-1 (0.510.1 mol.S.(mol.Fe)-1). This implies that the

physicochemical processes occurring in-sewer between Fe-sludge and sulfide are responsible for

sulfide removal. The visual observation of black-coloured sewage following Fe-sludge dosing (see

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Figure 56) suggests that FeS formed through a precipitation reaction between iron and sulfide. Sun et

al. (2015) observed sulfide removal in a laboratory sewer reactor following addition of Fe-sludge, but

this is the first time that such a process has been demonstrated in a pilot sewer. The observed sulfide

to Fe molar ratio of 0.51 is lower than the theoretical stoichiometry, which is 0.67 for reactions

between ferric ions and sulfide and 1.0 for reactions between ferrous irons and sulfide (Zhang et al.,

2009a). The observed ratio is similar to that reported by Sun et al. (2015) for a laboratory sewer

reactor (0.50±0.02 mol.S.(mol.Fe)-1).

There was a sharp increase in sulfate in the experimental line following addition of Fe-sludge (Figure

60b). This is largely due to a higher sulfate concentration in DAF subnatant as compared with raw

sewage (Table 29). As described in Section 7.2.2, the DAF subnatant was used to dilute the Fe-sludge

prior to its addition. This increase caused significantly higher sulfate concentrations in the

experimental line than in control sewer line (Figure 60b). The mean difference was 17.0±2.4 mg.S.L-

1 (p<0.05). Sulfate was consumed in both the experimental and the control lines, as evidenced by the

sulfide profiles (Figure 60a). However, the sulfate consumption rate and sulfide production rate in

the experimental lines appear to be slightly lower that these rates in the control line. This may be due

to potentially inhibitory effects of Fe-sludge dosing on sulfate-reducing activity of anaerobic sewer

biofilms. Lovley and Phillips (1987a) showed sulfate reduction in sediments was inhibited by 86-

100% when dosing ferric (oxy)hydroxide. Interestingly, ferric (oxy)hydroxide (FeOOH) is one of the

predominant mineral precipitates found in the Fe-sludge used herein, as evidenced by XRD spectra

(Figure 61a). Bratby (2006) also reported that waterworks Fe-sludge typically contains ferric

hydroxides bound with organic or inorganic compounds. The mean difference in the sulfite

concentrations between the control and experimental sewer lines was 0.4±0.05 mg.S.L-1 (p<0.05),

while the mean difference in thiosulfate concentration was 1.0±0.1 mg.S.L-1 (p>0.05) (Figure 60b).

Figure 60c shows there was a sharp decrease in phosphate concentration in the experimental line

following Fe-sludge addition. Again, this is largely due to the much lower phosphate concentration

in the DAF subnatant as compared with raw sewage (Table 29). This caused a mean difference in

phosphate concentrations between the two sewer lines of 0.8±0.1 mg.P.L-1 (p<0.05) (4.9±0.02

mg.P.L-1 in control and 4.0±0.1 mg.P.L-1 in experimental), equivalent to 21.8% of that in raw sewage

(Table 29). This represents a decrease in PO4-P concentration by 17.31.5% in the experimental

sewer line. This marginal mean difference in phosphate concentrations can be attributed to the

combination of dilution and Fe-induced removal, where a dilution effect holds notable contribution

(i.e. 0.7 mg.P.L-1). This implies that the Fe-P reaction contributed little to the decrease in phosphate

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concentrations in experimental line. Here, the observed decrease in sulfide with limited impact on

phosphate removal with Fe-sludge addition corresponds to the prevalent pH (7.0±0.02) (Figure 59a).

In retrospect, effectiveness of sulfide and phosphate precipitation with Fe is likely to be influenced

by the prevalent wastewater pH conditions albeit the detailed underlying chemistry under in-sewer

condition is not investigated in this study.

Figure 60d-e show the variations in the COD concentrations (tCOD, sCOD) between both sewer lines.

The mean difference in tCOD concentration between the experimental and control sewer lines was

32.0±7.0 mg COD/L (p>0.05), which can be primarily attributed to dilution. This is because tCOD

concentrations were similar in the Fe-sludge (after dilution with DAF) and raw wastewater in the

beginning of experiment, following Fe-sludge dosing (Figure 60d). Earlier, Sun et al. (2015) showed

an increase in tCOD concentration by 40.0±4.0 mg.L-1 with Fe-sludge addition. Such observed

differences may be attributed to individual properties and the origin of respective waterworks Fe-

sludge. The Fe-sludge used herein, sourced from the seawater desalination plant, has relatively low

tCOD content (60.1±1.7 mg.(g.DS)-1) as compared with the tCOD content of Fe-sludge (352.0±9.0

mg.(g.DS)-1), which was sourced from freshwater treatment plant (Sun et al., 2015). Without

considering the dilution effect, the mean difference in sCOD concentration between the control and

experimental sewer lines was 35.2±4.1 mg.COD.L-1 (p<0.05) (Figure 60e), which is equivalent to

15.3% of that in raw sewage (Table 29). Dilution of the sludge stream with the raw wastewater could

have caused the decrease in sCOD (30.0 mg.COD.L-1), as Fe-sludge has a lower sCOD

concentration after dilution with DAF as compared with sCOD in raw wastewater.

Similarly, differences in mean concentrations of dissolved CH4 and N2O in experimental and control

sewer lines were 1.2±2.0 mg.COD.L-1 (p>0.05) (Figure 60f) and 0.01±0.1 g.N.L-1 (p>0.05) (Figure

59c), respectively. This implies addition of WTP Fe-sludge did not cause an increase in greenhouse

gas, GHG formation in sewers. In addition, the total concentrations of other metals (As, Cd, Co, Cr,

Ni, Pb, Se, Zn) except Mn (0.2 mg.L-1) in the both sewer lines were comparable, i.e. <0.01 mg.L-1.

This confirms that dosing of Fe-sludge in the sewer did not increase the loading of other metals to the

receiving WWTP.

179


dosing Fe-sludge. The vertical dashed line represents the time at which Fe-sludge was dosed to the

experimental pipe. Concentration-time profiles are presented for (a) TSS, (b) VSS, (c) total Fe(T), (d)

soluble Fe(sol.), (e) total Al(T), and (f) soluble Al(sol.). Each data point corresponds to the mean value of

three sampling points (15 m, 105 m, 210 m) in sewer pipes. Error bars represent standard error of

mean (SEM).

180


pipes on dosing Fe-sludge. Time profiles of: (a) pH, (b) temperature, (c) dissolved N2O concentration

181


dosing Fe-sludge. The vertical dashed lines represent the sewage characteristics observed at 20 min

and 40 min in both sewer pipes (after dosing of Fe-sludge in experimental line). Concentration-time

profiles are presented for (a) total dissolved sulfide S(-II), (b) sulfite, sulfate, and thiosulfate, (c)

phosphate, PO4-P, (d) tCOD, (e) sCOD, and (f) dissolved methane, CH4. Each data point corresponds

to the mean value of three sampling points (15 m, 105 m, 210 m) in sewer pipes (except for the

dissolved CH4, which correspond to sampling point 15 m). Error bars represent standard error of mean

(SEM).

182

Figure 61. (a) X-ray diffraction pattern; (b) infrared (IR) spectra of Fe-sludge samples (before dosing

into pilot sewer)

7.3.2 Mechanism of sulfide removal in sewer when dosing Fe-sludge

Figure 62a shows the chemical composition of a sample collected after Fe-sludge dosing (see Section

7.2.2). XRD analysis revealed that ferric sulfate, i.e. Fe2(SO4)3, and iron oxyhydroxides, i.e. FeOOH,

were the predominant mineral precipitates in the sample. This was similar to the chemical

composition observed in Fe-sludge before dosing (Figure 61a). Ferric activator [Fe2(SO4)3] (Figure

62a, Figure 61a) can form iron-sulfide precipitates (FeSx) in the sample under reductive conditions

(see Section 7.2.1). At the same time, the presence of ferric compounds such as FeOOH can result in

sulfidization reactions between FeOOH and H2S, forming FeSx (FeS, FeS2) as in Eqs. (21)-(22) (Liu

et al., 2017; S⊘ndergaard et al., 2002).

183

2FeOOH + 3H2S → 2FeS + S0+ 4H2O (21)

FeS + H2S → FeS2 + H2 (22)

Such possible interactions are reflected by the appearance of broader and sharper peaks in samples

taken after dosing with Fe-sludge (Figure 62a) as compared with those in Fe-sludge alone (Figure

61a). Notably, a peak corresponding to iron-sulfide (FeSx) precipitates appeared (Figure 62a). This

implies the physicochemical reaction, i.e. precipitation between sulfide and ferric ion in Fe-sludge is

likely to be the dominant mechanism for sulfide removal (Figure 60a), and is expected to proceed as

outlined in Eq. (21). This is further supported by EDX-determined elemental composition of the Fe-

sludge sample after dosing (Figure 63). For this, both atomic percentage and atomic ratio were

calculated for iron and sulfide. The atomic ratio of 0.89 − 0.92 (Table 31) indicates that the

precipitates as FeS. As shown in Figure 60a, the sulfide concentration decreased rapidly at the

beginning, followed by a relative slower decrease. Such a trend may be attributed to a decrease in

reactive sites, i.e. surface FeOOH (Bratby, 2006; Sun et al., 2015), likely caused by continuous

precipitation reactions occurring in-sewer.

Further, in the infrared (IR) spectra of the sample obtained after Fe-sludge dosing (Figure 62b), the

band previously seen at 871 cm-1 disappeared (Figure 61b). This band represents the primary amine

functional group (R-NH2, where R is alkyl group) and carbonate group coordinated with Fe, originally

present in the Fe-sludge sample before dosing (see Figure 61b). This R-NH2 functional group could

be responsible for binding sulfides to form R-NH3-HS or R-NH3S- (Pang et al., 2017). This is

accompanied by the appearance of a sharper peak at 1025 cm-1 (Figure 62b), which corresponds to

S-O covalent bond stretching of inorganic sulfates (Smidt and Meissl, 2007). This suggests the

precipitation of dissolved sulfides with FeOOH (bound with other organic or inorganic compounds)

present on the Fe-sludge surface, is likely the dominant physicochemical process contributing to

sulfide removal (Figure 60a). Additional analysis of other IR spectra absorbance peaks from Fe-

sludge sampled before dosing (Figure 61b) and samples after Fe-sludge dosing (Figure 62b) is

provided in Appendix F.

184

Figure 62. (a) X-ray diffraction pattern and (b) IR spectra of samples collected at the end of Fe-sludge

dosing into the pilot sewer, i.e. a mixture of raw sewage and Fe-sludge solids

185

Figure 63. SEM-EDX analysis of elemental composition (Wt%) of Fe-sludge sampled after dosing

into the experimental sewer line (also see Table 31): (a) Secondary Electron Image (SEI), (b)

Spectrum 1, (c) Spectrum 2, (d) Spectrum 3, (e) Spectrum 4, (f) Spectrum 5, and (g) Spectrum 6

Table 31. EDX analysis of sample elemental composition following Fe-sludge addition into the pilot

experimental sewer line

Elemental composition of Fe-sludge sample after dosing

Major

elements of

interest

Weight (%) Spectrum 1 Spectrum 2 Spectrum 3 Spectrum 4 Spectrum 5 Spectrum 6

Fe 4.80 9.40 22.10 40.70 18.80 32.60

S 5.90 10.20 14.10 32.90 11.90 20.20

Elemental composition of Fe-sludge sample after dosing

Major

elements of

interest

Atomic (%) Spectrum 1 Spectrum 2 Spectrum 3 Spectrum 4 Spectrum 5 Spectrum 6

Fe 0.09 0.17 0.39 0.73 0.34 0.58

S 0.18 0.32 0.44 1.03 0.37 0.63

Atomic ratio

(Fe, S)

0.50 0.53 0.89 0.71 0.92 0.92

Assumed

composition

FeS2 FeS2 FeS FeS2 FeS FeS

186

7.3.3 Effects of Al-sludge dosing on sewage characteristics

Figure 64a-f show the changes in suspended solids and Al, Fe concentrations with Al-sludge dosing.

The mean difference in TSS concentration between experimental and control sewer lines was

509.4±23.1 mg.TSS.L-1 (Figure 64a); while, the mean difference in VSS concentration was 139.0±2.5

mg.VSS.L-1 (Figure 64b). Like Fe-sludge dosing, we observed decreasing TSS concentration in both

sewer lines with time, implying that solids may be settling in the sewer pipes during recirculation.

TSS concentration is likely to influence the Al(T) or Fe(T) concentrations in the sewer bulk phase, as

previously observed in Figure 58c-d. However, this was not the case as shown by the concentration-

time profiles of Al (Al(T), Al(sol.),) and Fe (Fe(T), Fe(sol.)) in Figure 64c-f. Neither Al(T) nor Fe(T)

concentrations showed decreasing trends with time. The mean Al(T) concentrations in control and

experimental sewer lines were 0.5±0.05 mg.Al.L-1 and 46±3.0 mg.Al.L-1, respectively (Figure 64c).

However, mean Al(sol.) concentrations were insignificant (<0.5 mg.Al.L-1) in both the sewer lines

(Figure 64d). Mean Fe(T) concentrations in control and experimental lines were similar at 2.0±0.2

mg.Fe.L-1 and 3.0±0.2 mg.Fe.L-1, respectively (Figure 64e); whereas mean Fe(sol.) concentrations were

0.4±0.06 mg.Fe.L-1 and 0.05±0.03 mg.Fe.L-1, respectively (Figure 64f). In addition, both pH

(7.0±0.0) (Figure 65a) and temperature (25.0±0.1C) (Figure 65b) were comparable in the two sewer

lines during Al-sludge dosing.

Figure 66a shows the changes observed in phosphate (PO4-P) concentrations in both sewer lines.

Considering the dilution effect, the mean difference in PO4-P concentrations between the two sewer

lines was 5.3±0.03 mg.P.L-1 (p<0.05). This represents a relative decrease in PO4-P concentration by

97.50.2% in the experimental line. Here, the dilution would cause a decrease in PO4-P

concentrations by 0.6 mg.P.L-1, which accounts for a small part of the observed difference. Phosphate

removal with Al-sludge can take place via surface-complexation, ligand-exchange or precipitation

processes. Hence, additional analysis was undertaken to investigate the stoichiometry and the

phosphate removal mechanisms (Sections 7.3.4 – 7.3.5). The total PO43- removed per total Al added

(as Al-sludge) was 0.340.02 mg.P.(mg.Al)-1. This measured ratio is below the theoretical Al:PO43-

ratio of 0.87:1. This is likely because Al was added in excess, as evidenced by the almost complete

removal of PO43-. Such PO4

3- removal in sewers upon using waterworks sludge may impact the P

recovery at the receiving WWTP. This requires the understanding of Al and P interactions and

characterization of Al-P mineral precipitates in WWTP, which would facilitate in P recovery using

appropriate separation techniques. In this context, Prot et al. (2019) reported P can be recovered using

187

magnetic separation process from digested sludge, rich in Fe-P mineral precipitates (e.g. vivianite).

However, there has been no report that Al-bound P can be recovered. Many studies showed the

efficacy of waterworks Al-sludge in phosphorus removal in wastewater treatment, as reviewed by

Babatunde and Zhao (2007), also the wide variety of end uses or disposal practices for waterworks

Al-sludge had been reported (GHD, 2015). In Australia, disposal to landfill is the most common

adopted practice for much of the waterworks Al-sludge (GHD, 2015). However, there is little existing

information about the potential secondary benefits of Al-sludge addition to sewers, in particular

phosphate removal.

Figure 66b-c depicts the changes observed in sewage dissolved sulfur species concentrations

following Al-sludge dosing. Considering the dilution effect, the mean difference in sulfide

concentration between the two sewer lines was 1.8±0.4 mg.S.L-1 (p<0.05) (Figure 66b), equivalent to

7.3% of sulfide in raw sewage (Table 29). This equates to a small decrease in sulfide concentration

(6.31.4%) in the experimental line. Here, the dilution would cause a decrease in sulfide

concentrations by 2.8 mg.S.L-1, which implies that dilution was the cause of the observed mean

difference. Sulfide removal by precipitation with Fe or Al is unlikely, as the Al-sludge addition only

increased total Fe concentration by 1.0 mg.Fe.L-1 (Figure 64e), and Al is not known to precipitate

with sulfide. Studies had reported that humic substances or organic matter in sludge could mediate

sulfide removal to some extent via oxidation, owing to high redox potential (Edwards et al., 1997;

Heitmann and Blodau, 2006). Other possible in-sewer processes contributing to sulfide removal

include the formation of organic sulfur compounds and sulfide adsorption onto sludge (Heitmann and

Blodau, 2006; Pang et al., 2017).

Figure 66c shows a relatively higher sulfate concentration in the experimental line. Considering the

dilution effect, the mean difference in sulfate concentrations between the two sewer lines was 4.7±0.8

mg.S.L-1 (p<0.05). This difference can be primarily attributed to a relatively higher sulfate

concentration in DAF subnatant as compared with raw wastewater (Table 29), as evidenced by a

sharp increase in sulfate in experimental line at the beginning of the experiment. Theoretically, the

dilution would cause an increase in sulfate concentration by 4.3 mg.S.L-1. Sulfate was consumed in

both the sewer lines, with concomitant sulfide production (Figure 66b). Likewise, the mean difference

in sulfite concentration between the two sewer lines was comparable (0.10.01 mg.S.L-1) (p>0.05),

while the mean difference in thiosulfate concentration was 0.7±0.1 mg.S.L-1 (p>0.05).

188

Figure 66d-e show the variations in the COD concentrations (tCOD, sCOD) between the two sewer

lines. The mean difference in tCOD between the two sewer lines was statistically significant

(649.0±83.0 mg.COD.L-1, p<0.05). Increased tCOD in the experimental sewer line than control line

is likely due to release of organic matter from Al-sludge dosing. In contrast, Guan et al. (2005a)

showed in sewage jar-tests that the tCOD concentration decreased by 15.0% with Al-sludge dosing

at 18-20 mg.Al.L-1. Without considering the dilution effect, the mean difference in sCOD

concentration between the sewer lines was 33.9±6.9 mg.COD.L-1 (p<0.05) (Figure 66e), equivalent

to 12.7% sCOD in raw sewage (Table 29). This decrease in sCOD concentration is perhaps primarily

caused by dilution as DAF subnatant does not contain much sCOD (Table 29). This is reflected by

the sharp decrease in concentration observed in the first 20 min. Here, only the dilution would cause

a decrease in sCOD concentration by 31.0 mg.COD.L-1, which accounts for most of the observed

mean difference. In general, reduced soluble COD could impact the nitrogen removal process in

receiving WWTP, especially when the WWTP incorporates a primary clarifier where suspended

solids settle. Despite the increased tCOD concentrations in the experimental sewer line, there were

no significant changes in respective dissolved CH4 (Figure 66f) and N2O (Figure 65c) concentrations

compared to the control line. The mean difference in dissolved CH4 between the two sewer lines was

0.35±2.7 mg.COD.L-1, while the mean difference for N2O concentrations was 0.01±0.08 g.N.L-1.

This implies that discharge of WTP Al-sludge to sewers does not cause increased GHGs formation

in sewers. In addition, the respective concentrations of metals (As, Cd, Co, Cr, Ni, Se, Zn) in both

sewer lines were 0.01 mg/L, except for Mn (0.2 mg.Mn.L-1), Cu (0.1 mg.L-1) and Pb (0.1 mg.L-

1). This confirms that dosing of Al-sludge does not increase the loading of other metals to the

receiving WWTP.

189


dosing Al-sludge. The vertical dashed line represents the time at which Al-sludge was dosed to the

experimental pipe. Concentration-time profiles are presented for (a) TSS, (b) VSS, (c) total Al(T), (d)

soluble Al(sol.), (e) total Fe(T), and (f) soluble Fe(sol.). Each data point corresponds to the mean value of

three sampling points (15 m, 105 m 210 m) in sewer pipes. Error bars represent standard error of

mean (SEM).

190


pipes after dosing Al-sludge. Time profiles of: (a) pH, (b) temperature, and (c) dissolved N2O

191


dosing Al-sludge. The vertical dashed lines represent the sewage characteristics observed at 20 min

and 40 min in both sewer pipes (after dosing of Al-sludge in experimental line). Concentration-time

profiles are presented for (a) phosphate, PO4-P, (b) total dissolved sulfide S(-II), (c) sulfite, sulfate,

and thiosulfate contents, (d) tCOD, (e) sCOD, and (f) dissolved methane, CH4. Each data point

corresponds to the mean value of three sampling points (15 m, 105 m, 210 m) in sewer pipes (except

for the dissolved CH4, which corresponds to sampling point 15 m). Error bars represent standard error

of mean (SEM).

192

7.3.4 Effects of Al:P dosage ratio and suspended solids on phosphate removal

Figure 67a and Figure 67b show the influence of various Al:PO43- dose ratios on phosphate removal

in sewage, unfiltered and filtered, respectively. Increasing addition of Al-sludge resulted in increased

phosphate (PO43-) removal in both cases. This is because Al-sludge predominantly consists of

amorphous aluminium (hydr)oxides, (as evidenced by the Al-sludge XRD pattern, Figure 68), which

provide active adsorption sites for available PO43- ions. At a higher Al-sludge dosing rate, more

surface area and adsorption sites are available, resulting in higher PO43- removal (Figure 67a-b). Akin

Babatunde et al. (2008) reported that the concentration of surface –OH groups increases via surface

site density, with the increasing Al-sludge concentration. The possible mechanism governing PO43-

removal is discussed in Section 7.3.5. On average, with unfiltered sewage the total PO43- removed per

Al added (as Al-sludge) for Al:PO43- molar ratios of 1:1, 1.5:1, 2:1 and 3:1 was 0.30, 0.31, 0.26, and

0.28 mg.P.(mg.Al)-1, respectively (Figure 67a, Table 32). For filtered sewage, the average total PO43-

removed per Al added (as Al-sludge) for Al:P molar ratios of 2:1 and 3:1 was 0.34, and 0.28

mg.P.(mg.Al)-1, respectively (Figure 67b, Table 32). Phosphate removal was comparable in unfiltered

and filtered sewage when dosing Al-sludge of Al:PO43- molar ratio 2:1 and 3:1, respectively (Figure

67a-b). This implies that PO43- removal in sewage was primarily due to added Al-sludge and it is

unlikely that PO43- removal was due to interactions of added Al (as Al-sludge) with sewage suspended

solids.

193

Figure 67. Effect of various Al:PO43- dosage ratios on phosphate removal in (a) unfiltered and (b)

filtered sewage. Here, each data point corresponds to mean value of duplicate tests (n=2)

Figure 68. X-ray diffraction (XRD) pattern of Al-sludge used in this study, showing the dominance

of aluminium (hydr)oxides, as marked by ‘star’ symbols

194

Table 32. Comparative evaluation of phosphate removal by Al-sludge as a function of Al:PO43- molar

ratio using (a) unfiltered sewage and (b) 0.22 µm filtered sewage. Here, test duration = 2 hr, number

of replicates for each dosing ratio, n = 2

Al:PO43- molar ratio (using unfiltered sewage)

Al-sludge and molar ratio (Al:PO43-) Al:PO4

3- =

1:1

(n=2)

Al:PO43- =

1.5:1

(n=2)

Al:PO43- =

2:1

(n=2)

Al:PO43-

=

3:1

(n=2)

Total phosphate removed (mM.L-1*) 0.02 0.02 0.03 0.04

Al added (as Al-sludge) (mM.L-1) 0.20 0.26 0.37 0.50

Molar ratio for Al-sludge (Al:total PO43-

removed)

11.6:1 11.4:1 13.7:1 12.8:1

Molar ratio for Al-sludge (total PO43-

removed:Al)

0.09:1 0.09:1 0.07:1 0.08:1

Al:PO43- molar ratio (using 0.22 µm filtered sewage)

Al-sludge and molar ratio (Al: PO43-) Al:PO4

3- =

2:1

(n=2)

Al:PO43-

=

3:1

(n=2)

Total phosphate removed (mM.L-1) 0.03 0.04

Al added (as Al-sludge) (mM.L-1) 0.27 0.46

Molar ratio for Al-sludge (Al:total PO43-

removed)

10.4:1 12.3:1

Molar ratio for Al-sludge (total PO43-

removed: Al)

0.10:1 0.08:1

*mM.L-1 - millimoles per litre

7.3.5 Mechanism of phosphate removal in sewers when dosing Al-sludge

We conducted a separate set of bench-scale experiments (Appendix G) to understand the

characteristics and mechanisms of phosphate (PO43-) removal when dosing Al-sludge as observed in

Figure 66a and Figure 67a. This experiment comprised two phases – first, the hydrolysis of added Al-

sludge, and second, the subsequent adsorption test for PO43- removal. The results showed that the

dominant pathway consisted of ligand-exchange resulting in formation of Al-phosphate complexes

(Figure G1, Appendix G), which suggests that surface-precipitation was contributing to PO43-

removal. This finding prompted the further spectroscopy analyses to identify the Al-coordination

number. For these analyses, bench-scale experiments were undertaken with sewage sampled before-

and after dosing Al-sludge (see Section 7.3.4).

195

Figure 69. IR spectra of sewage samples taken before and after batch experiment, using an Al-sludge

dosage molar ratio of Al:PO43- = 3:1. Here, star symbols are assigned to respective absorbance bands,

where major changes were observed

Figure 69 shows the IR spectra of sewage samples, before and after Al-sludge (as Al:PO43- = 3:1)

dosing. As previously stated, the formation of Al-phosphate complexes with Al-sludge dosing is

reflected by particular absorbance bands in mid-infrared regions from 800-1200 cm-1. The peaks in

this region are assigned to metal-orthophosphate complexes (Scorates, 2001; Tejedor-Tejedor and

Anderson, 1990). Absorbance bands in this region can also be assigned to asymmetric stretching

vibrations of the bridging PO2- (O=P–O−) and P–O–P, or asymmetric and symmetric stretching

vibrations of the PO43- ions (Scorates, 2001). Clearly, the relative peak intensity of Al-phosphate

complexes is stronger in the sample taken after Al-sludge dosing (Figure 69), which implies that PO43-

is chemically adsorbed on the Al-sludge surface.

Further, it is critical to understand how the PO43- is associated with Al-OH on the sludge surface,

whether by forming ‘inner-sphere’ or ‘outer-sphere’ surface complexes, or both. The occurrence of

outer-sphere surface complexation resulting from PO43- ions exchanging with surface -OH groups, is

evidenced by the ligand-exchange mechanism described in Figure G1. Evidence of inner-sphere

complexation can also be gained from IR spectra (Figure 69). At 3200 cm-1 the IR spectra of the

sample taken before Al-sludge dosing demonstrates strong OH- stretching (Al-Tahmazi and

196

Babatunde, 2016). This stretching becomes more pronounced in the IR spectra of the sample taken

after Al-sludge dosing. In addition, an intense peak associated with the deformation vibrations of

multi-centered hydroxyl groups of aluminium oxides (Al-OH) appeared at 1017-1018 cm-1 in the

sample taken after Al-sludge dosing (Persson et al., 1996). This implies the possible formation of

inner-sphere surface complexes between PO43- ions and aluminium oxides (as evidenced by the XRD

pattern of Al-sludge) (Figure 68).

Figure 70a-d show the 27Al NMR spectra and Figure 70e-h show the 31P NMR spectra of sewage

sampled before and after Al-sludge dosing, respectively. These 27Al and 31P NMR spectra further

corroborate the association of PO43- ions and aluminium oxides as outlined previously. The

broad resonance peak observed in two regions of 27Al spectra, i.e. -40 ppm to 30 ppm, and 40

ppm to 60 ppm in samples after Al-sludge dosing (Figure 70b-d), resulting from a chemical shift

δ(27Al) around 0 ppm, -5 ppm, -25 ppm or 50 ppm (Lookman et al., 1997; Lundehøj et al., 2019),

is due to octahedral Al-coordination with a single PO43- or four PO4

3- and two hydroxyl/water ligands.

This is further evidenced by the chemical shift (iso, Al) ppm results from 27Al spectra deconvolution

presented in Table 33. The quantitative results (%) show that most Al was in octahedral co-ordination,

which corroborates the dominance of Al-phosphate complexes, as previously deduced by the

hydrolysis-adsorption experiment (see Appendix G) and IR spectra (Figure 68). Notably, the

resonance peaks’ intensity increased in samples with increasing aluminium loading (Figure 70b-d) as

compared with raw sewage (Figure 70a) at pH 7.3-7.6.

Likewise, 31P spectra shows the broadening of resonance peaks with a negative chemical shift around

0 ppm to -50 ppm in samples after Al-sludge dosing (Figure 70f-h) as compared with raw sewage

(Figure 70e). This likely indicates the chemical adsorption of PO43- ions onto aluminium oxides on

the Al-sludge surface (Figure G1, Appendix G) with the increasing Al:PO43- dosage ratio. Adsorption

of PO3- on aluminium (hydr)oxides usually yields chemical shifts in the region 0 to -20 ppm (Li et

al., 2010; Li et al., 2013; Lookman et al., 1997) whereas aluminium phosphates yield chemical shifts

from -10 to -30 ppm (Li et al., 2013). The 31P spectra observed under different Al:PO43- ratio (Figure

70f-h) further corroborates the existence of outer-sphere complexes (= 10 to 0 ppm) and inner-sphere

complexes (= 0 to -10 ppm), and also suggests the possible formation of surface precipitates (= -10

to -30 ppm) such as AlPO4.2H2O, Al3(OH)3(PO4)2 (Li et al., 2013). The possible formation of surface

precipitates is supported by the deconvolution results of 31P spectra that most P-integral (%)

experienced a chemical shift (iso, P) at -21 ppm and -27 ppm (Table 34). Lookman et al. (1994)

197

attributed the resonance line at -27 ppm to crystalline AlPO4, while resonance lines at -22.2 ppm and

-27.2 ppm were attributed to anhydrous AlPO4 (Johnson et al., 2002). The formation of surface

precipitates in aqueous solution containing PO43- ions, is also likely be governed by the dissolution-

reprecipitation process that can occur on Al-sludge addition.

Hence, we can assume that with Al-sludge dosing (enriched with aluminium (hydr)oxides), the

predominant reaction will be ligand-exchange between the sludge surface -OH active functional

group and H2PO4- or HPO4

- (dominant in pH range 6.64-8.39). This in turn would result in the

formation of both inner- and outer-sphere surface Al-phosphate complexes. This ligand-exchange

substituting the surface -OH groups with PO43- ions could in turn slightly raise the pH of the solution,

and release other anions such as sulfate (SO42-) or humics during the process. In addition, surface-

precipitates can form with a longer contact time.

Figure 70. (a)-(d) 27Al spectra and (e)-(h) 31P NMR spectra of sewage samples – before and after Al-

sludge dosing, respectively, with various Al:PO43- molar ratios, reacted for 2 hr with constant mixing

at 25C and pH 7.3 - 7.6: (a) and (e) = raw unfiltered sewage samples before Al-sludge dosing; (b)

and (f) Al:PO43- = 1:1; (c) and (g) Al:PO4

3- = 2:1; (d) and (h) Al:PO43- = 3:1

198

Table 33. Chemical shift (iso, Al) (27Al) ppm and integrals obtained from deconvolution of 27Al spectra

Chemical

shift (iso, Al)

(27Al) ppm

Sewage

sample

(Before Al-

sludge dosing)

Experiments with various Al:P molar ratios

(Al:PO43-)

Al-coordination

1:1 2:1 3:1

Al-integral

(%)

Al-integral

(%)

Al-integral

(%)

Al-integral

(%)

0 51.0 86.8 95.1 95.2 octahedral or

hexahedral

coordination

50 49.0 13.2 4.9 4.8 tetrahedral

coordination

Table 34. Chemical shift (iso, P) (31P) ppm and integrals obtained from deconvolution of 31P spectra

Chemical shift (iso, P)

(31P), ppm

Sewage sample (Before

Al-sludge dosing)

Experiments with various Al:P molar ratios

(Al:PO43-)

1:1 2:1 3:1

P-integral

(%)

P-integral

(%)

P-integral

(%)

P-integral

(%)

-27 18.3 71.7 73.1 90.5

-21 81.7 28.3 26.9 9.5

7.3.6 Implications of dosing waterworks Al- or Fe-sludge in sewers

This study evaluated the impacts of discharging waterworks Fe- or Al-sludge into pilot sewers.

Neither Fe- nor Al-sludge caused an increase in GHG (dissolved CH4, N2O) production in sewers.

No release of other metals was observed in both cases. Dilution caused by mixing of the Fe- or Al-

sludge sludge stream with raw wastewater was found to be largely responsible for the observed

reduction in sCOD concentrations.

Dosing of 22.1 mg.Fe.L-1 (as Fe-sludge) lead to a decrease in dissolved sulfide, while dosing of 45.7

mg.Al.L-1 (as Al-sludge) decreased phosphate concentrations. Based on waterworks Fe-sludge dosing

to laboratory sewers, Sun et al. (2015) reported that waterworks Fe-sludge was effective in controlling

dissolved sulfide concentration, and also showed that phosphate removal could be an additional

benefit. In contrast, in the current study dosing of Fe-sludge was effective for dissolved sulfide

removal, while Al-sludge dosing was more effective for phosphate removal. Notably, our study was

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conducted in pilot sewers under more realistic sewer conditions. The findings of the current study are

in contrast to Edwards et al. (1997), which reported Fe-sludge to be more effective than Al-sludge in

phosphate removal. However, those results were primarily based on bench-scale experiments under

controlled conditions, rather than Fe- or Al-sludge dosing in pilot sewers as in this study. The

differences in the Fe-/Al-sludges sources and the resultant varying sludge compositions could be

another factor behind such contrasting result. Further details highlighting the novelty of this study as

compared to the previous studies conducted to treat wastewater on applying Fe- or Al-sludge are

provided in Appendix H.

The results from the current study further confirm the benefits of applying Fe-sludge and Al-sludge

to full-scale sewers as a viable end use for sludge generated from WTPs. This could have significant

environmental and economic benefits for water utilities in implementing a circular economy in urban

water management via sustainable WTP sludge management. Instead of waterworks sludge being

considered a waste product, it can be reused as a resource for pollutants or nutrients removal in an

urban wastewater system.

Globally, average daily production of WTP sludge exceeds 10,000 tonnes (Babatunde and Zhao,

2007). The large volume of sludge incurs high disposal and storage costs. For instance, the total cost

of waterworks sludge disposal is worth $33.47−$44.62 million per annum in the Netherlands alone

(Horth et al., 1994). Pikaar et al. (2014) reported that 56% of the surveyed 77 WTPs in Australia use

alum as primary coagulant, and the case is similar in the U.S.A., the U.K., Canada, and China. The

cost of Al-sludge disposal in landfill in Australia is $130−$200 per tonne excluding sludge transport

which costs around $30−$40 per tonne (GHD, 2015). The enormous costs associated with waterworks

sludge disposal and handling demands a rethink of options such as sludge reuse or alternative disposal

routes.

Disposal of waterworks sludge into sewers for management at the receiving WWTP enables system-

wide cooperation, and has been identified as an option for beneficial reuse by utilities (Babatunde and

Zhao, 2007; GHD, 2015). The current study provides firm evidence of the multiple benefits observed

in both sewers and the receiving WWTP (Edwards et al., 1997), on discharge of waterworks Fe- or

Al-sludge into sewers. A few Australian water utilities have adopted sewer disposal practices for Al-

sludge, to reduce the phosphorus loads to receiving WWTPs (GHD, 2015). Similarly, Filho et al.

(2013) also reported that long-term dosing of waterworks Al-sludge in sewers caused no adverse

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effects on removal efficiency of organics or nutrients in the receiving WWTP. Edwards et al. (1997)

estimated that savings of $20,500−$96,500 per annum in a 17 MGD capacity treatment plant

(excluding costs for coagulant storage and dosing facilities) could be made by reusing Fe-sludge in

sewers.

Disposal of waterworks sludge into sewers is practical when a sewer main of the receiving WWTP is

located in close proximity to the WTP (GHD, 2015). However, in most cases the WTP is at a distant

location in relation to the sewer main. In such cases, construction of a new sewer main would be

required incurring additional infrastructure costs. In addition, disposal of waterworks sludge into

sewers increases the solids concentration, potentially causing sludge sedimentation in sewers.

Increased solids loading to the receiving treatment plant will also result from sewer discharge of

waterworks sludge. Therefore, a holistic approach, which considers factors that affect both sewer and

WWTP operation, must be adopted prior to full-scale sewer disposal of waterworks Fe- or Al-sludge.

These factors include assessing: (i) impacts on sewer infrastructure such as sewer corrosion or

blockages due to sludge sedimentation, and changes in sewage characteristics, (ii) current sludge

handling capacity of receiving WWTPs, and (iii) impacts on treatment processes of receiving

WWTPs, and final WWTP effluent quality including quality of WWTP biosolids (GHD, 2015; Hsu

and Pipes, 1973; Sun et al., 2015). Hence, further long-term comprehensive study incorporating such

holistic approach (or coupled with life cycle assessment) is essential for fully evaluating the impacts

of waterworks sludge discharge in real-life full-scale sewer networks and receiving WWTPs for

system-wide operation. In addition, a comprehensive comparative technological, environmental, and

economic analysis is vital in maximizing the multiple benefits from waterworks sludge dosing to

sewers. Besides, dosing of waterworks-sludge directly at WWTP is also an option (e.g. P removal)

which would eliminate the sludge sedimentation issue, but in-sewer sulfide control (as in case of Fe-

sludge dosing) could not be achieved. However, there are also transport costs associated with this

strategy.

7.4. Conclusion

This study, for the first time, comprehensively investigated the effects of dosing waterworks Fe- and

Al-sludge in pilot sewers, particularly focusing on removal of sulfides and phosphate, and associated

mechanisms. Changes in sewage characteristics were examined to understand the unintended

consequences of sludge dosing. The major conclusions are:

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• Waterworks Fe-sludge was effective in removing dissolved sulfides in-sewer. Fe-sludge removes

sulfide at a ratio of 0.290.06 mg.S.(mg.Fe)-1 in sewage. Dosing of Fe- or Al-sludge in sewers

caused no increase in GHG (dissolved CH4, N2O) formation, nor release of metals.

• Waterworks Al-sludge was effective in phosphate (PO43-) removal in-sewer. Al-sludge removes

phosphate at ratio of 0.290.01 mg.P.(mg.Al)-1 in sewage (based on batch test results).

• The physicochemical reaction (precipitation) between sulfide and ferric ions in Fe-sludge is likely

to be the dominant mechanism for sulfide removal when dosing Fe-sludge in-sewer, based on

combined XRD, ATR-FTIR, and SEM-EDX analyses. Adsorption of dissolved sulfides onto

FeOOH (bound with other organic or inorganic compounds) present on the Fe-sludge surface, is

possibly another physicochemical process contributing to sulfide removal.

• Combined ATR-FTIR, NMR, and XRD analyses suggest ligand exchange occurs between sludge

surface -OH groups and PO43- ions, favoring the formation of both inner – and outer-sphere

surface Al-phosphate complexes as the dominating mechanism for phosphate removal when

dosing Al-sludge. The formation of surface-precipitates also likely contributes to phosphate

removal.

• Long-term, system-wide studies are needed to comprehensively analyze the effects of Fe-/Al-

sludge dosing in real and dynamic sewers, and potential for unintended consequences at the

receiving WWTP.

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Chapter 8

Conclusions and future research work

8.1 Summary of this research work

Different chemicals are used in different components of an urban wastewater system (UWWS),

including a sewer system, and WWTP for various reasons. The ‘choice’ and ‘optimal’ application of

these chemicals are at present primarily driven by mere considerations at the sub-system level, with

their potential impact on other sub-systems largely ignored. In retrospect, there can be implications

of any changes occurring in one upstream sub-system to the performance of downstream sub-systems

(Pikaar et al., 2014). This is because the different in-sewer physical, chemical, and biological

phenomena occurring in the sewer environment may change the sewer wastewater

characteristics/composition during conveyance, which in turn could have subsequent impacts on the

downstream WWTP. Accordingly, the sewer system and WWTP are no longer considered as a

separate entity instead perceived as a single entity within the UWWS in recent years (Calabro et al.,

2009). The current growing demand for sustainable urban wastewater management also necessitates

the integration of sewer and WWTP. Such integration will facilitate the system-wide optimal design

and cost-effective operation of both systems and also minimize their impacts on the environment

(Vollertsen et al., 2002). In this context, there has been a paradigm shift from a ‘fragmented approach’

to ‘integrated approach’ in terms of chemical usage (e.g. Fe-salt/Fe-sludge) in UWWS. However, the

application of Fe-salts/Fe-sludge has been in isolation without considering the ‘big picture’ approach

that assesses the immediate and downstream impacts as Fe travels through the UWWS. For instance,

the studies elucidating the beneficial impacts of Fe doing to sewer on the WWTP performance have

been limited primarily to phosphate removal in activated sludge process and sulfide removal in the

sludge digester. However, the possible interactions of available Fe with sludge and potential changes

to the sludge properties, which could have impacts on the settleability and dewaterability of sludge

as applicable, has so far been ignored. In this context, this study aims to look into the potential benefits

of Fe-salts discharge to sewers and extends the work to the investigation of the impacts of sewer

based Fe-dosing on sludge properties of downstream treatment units. This study also aims to

comprehensively investigate the potential impacts of waterworks sludge discharge to sewers.

Inorganic chemical coagulants (e.g. alum or Fe-salt) are widely used in WTP, generating waterworks

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Al- or Fe-sludge as by-products during the treatment process. A significant amount of WTP sludges

are produced globally exceeding on average 3.65106 dry tonnes per annum (Babatunde and Zhao,

2007) and this is expected to increase even more over the years due to rapidly increasing global

population. There has been growing interest in direct reusing waterworks sludge in sewers in recent

years as such a strategy would reduce the sludge disposal costs for WTP and also reduce the chemical

usage. Given consideration to the high Al or Fe content in waterworks sludge, such as waterworks

Al- or Fe-sludge can be a potentially cost-effective solution for controlling both sulfide and

phosphorus in sewers. If anticipated positive outcome is confirmed, it would have a significant impact

on urban water management. However, efficient reuse of the waterworks Al- or Fe-sludge has, until

recently, been overlooked to be a major imperative. In this context, Chapter 7 of this thesis highlighted

the opportunity to reuse ‘waterworks-derived Al- or Fe-sludge’ as an alternative to their chemical

counterparts (Al-, Fe-salts) for both phosphorus and sulfide removal in sewers (see Figure 71). This

thesis comprehensively evaluated the effects of direct dosing of waterworks Fe-/Al-sludge in pilot-

scale sewer under more realistic conditions, particularly focusing on removal of dissolved sulfides

and phosphate and associated underlying possible mechanisms. Besides, changes in other sewage

characteristics were also examined. The outcomes of this study affirm the benefits of reusing

waterworks Fe-sludge and Al-sludge to full-scale sewers as a viable end-use for sludge generated

from WTPs. In-sewer direct dosing of waterworks Al-sludge was found to be effective for phosphate

removal from sewer bulk phase, wherein Fe-sludge was effective for removal of dissolved sulfide.

This study also showed that reusing of waterworks Al-sludge or Fe-sludge in sewers neither cause

any increase in greenhouse gases (dissolved CH4, N2O) formation nor release of other metals into the

wastewater. These foregoing outcomes exhibited the successful reuse of Al- and Fe-sludge for

effective phosphate and sulfide removal in sewers, respectively. Waterworks Fe-sludge dosing was

effective for sulfide removal at a ratio of 0.290.06 mg.S(mg.Fe)-1, while Al-sludge was effective for

phosphate removal at ratio of 0.290.01 mg.P(mg.Al)-1. Hence, it could be corroborated that

transporting waterworks sludge through sewers could have significant benefits in terms of sewer

management, which has been realized and demonstrated in this study.

This PhD thesis also aims to unravel the mechanistic understanding of the potential, but unintended

beneficial aspects of sewer-dosed Fe-salts/Fe-sludge during integrated sewer-WWTP operation,

particularly concerning activated sludge and digestate properties during wastewater treatment and

sludge digestion. For understanding such flowing on impacts of sewer-dosed Fe on sludge properties

of bioreactor and digester other than sulfide and phosphate removal during integrated sewer-WWTP

operation, it is critical to understand the availability of Fe in bioreactor. As the availability depends

upon sewer conditions and particle setting in the primary settling tank (PST), both in-sewer Fe-

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transformation/fractionation and subsequent Fe-transport from sewer to downstream WWTP is

important. This is because the extent of availability of Fe to downstream WWTP as a result of the

changes during Fe-transport in sewer plays a determinant role for achieving multiple benefits of Fe

in system-wide operation. However, current understanding of the key factors potentially affecting

such phenomena is very limited. Previously, a laboratory study has solely highlighted the influence

of in-sewer retention time on Fe transport in sewers and its subsequent availability in a downstream

WWTP (Gutierrez et al., 2010). In this context, based on both carefully designed laboratory mixing-

reaction-settling tests (using both Fe-salt/Fe-sludge) to simulate the in-sewer conditions and full-scale

test (using Fe-salt) around a PST for two Fe-salt dosing locations (one at the WWTP inlet and other

at the upstream sewer), this thesis has demonstrated that not only varying in-sewer retention/reaction

time, in-sewer redox conditions, and also type of Fe-source being used, would impact the Fe-

transformation/fractionation in prevailing sewer environment and subsequent Fe transport to

downstream WWTP (see Chapter 4). Specifically, the key outcomes of Chapter 4 include (Figure 71):

• Not only in-sewer retention times (which is a direct function of Fe-dosing locations, either close

to WWTP or at upstream sewer locations), also prevailing in-sewer oxidative/reductive conditions

upon exposure (with Fe-salt dosing) affects Fe-precipitates transformations and Fe-fractionation

between the solid and dissolved phases. Concurrently, such phenomena would influence primary

particle size of Fe-precipitates or overall PSD dynamics, which eventually would affect in-sewer

Fe retention and transport.

• Fe-availability in sewer bulk phase was observed to be impacted by the type of Fe-source (Fe-

salt/Fe-sludge) used when being exposed to similar in-sewer conditions, attributing to the delayed

reduction-dissolution of Fe-sludge in the presence of added sulfide (i.e. minimal re-mobilization).

In retrospect, there was a minimal influence of the type of Fe sources on PSD dynamics under the

prevailing in-sewer redox conditions, although some differences in Fe-fractionation were

observed upon exposure to similar simulated in-sewer condition.

• The primary settling is another important process found to be influencing Fe retention, regardless

of changes in the Fe dosing locations during integrated sewer-WWTP operation.

Hence, the influence of these factors must be considered when choosing strategies for Fe dosing to

sewer to achieve multiple benefits across integrated UWWS.

Once the Fe carried over from the sewers reaches into activated sludge system and subsequently to

anaerobic sludge digestion unit, the likely chemical Fe-P-S interactions (see Section 1.2.4) occurring

during wastewater treatment and sludge digestion may potentially impact the key physicochemical,

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morphological, and rheological properties of both activated sludge and the digestate, which could

have implications on settleability and dewaterability, two key sludge properties. However,

comprehensive understanding of potential changes in earlier stated key properties of sludge sourced

from bioreactor and digester units due to flowing on impacts of sewer-dosed Fe-salt remains to be

elucidated. In this context, Chapter 5 demonstrated that precipitated Fe (resultant of sewer-dosed Fe-

salt) upon reaching downstream bioreactor provides additional benefits in terms of improving the

settleability and dewaterability of activated sludge (Figure 71). Importantly, the results demonstrated

that Fe dosing in sewer does not have any negative impacts on key activated sludge properties. On

the other hand, potential downstream impacts of sewer-dosed Fe-salt on key digestate properties

including digestate dewaterability during system-wide operation still remain unanswered: how does

dosing iron-rich waste activated sludge (Fe-WAS) as digester feed impact on key digestate properties

and contribute to the overall digestate dewaterability?. Such fundamental understanding of potential

impacts on digestate properties other than dewaterability and desulfurization owing to sewer-dosed

Fe-salt would have important implications for application of Fe-salts for system-wide operation. The

outcomes of Chapter 6 included in this thesis has demonstrated the improvement in digestate

dewaterability upon using Fe-WAS (resultant of sewer-dosed Fe-salt) as digester feed during

integrated sewer-WWTP operation (Figure 71). These are additional benefits of Fe dosed to sewers

other than phosphate and sulfide removal in the downstream WWTP. This study also showed that in-

sewer Fe-salt dosing results in favorable changes to the key digestate properties (e.g.

physicochemical, morphological, fractal, and rheological properties). The combined synergistic

interplay of such favorable changes in key digestate properties is likely to be responsible for

improving digestate dewaterability. The outcomes of these studies (Chapter 5 and Chapter 6) hold the

significant value because the settleability and dewaterability are the two key parameters and any

improvement in these parameters could influence not only the bioreactor or digester operation, but

also impact the overall WWTP operation and sludge management. Effluent quality of WWTP is

largely dependent on good settleability of activated sludge (Wilén et al., 2010). Likewise, better

sludge dewaterability reduces sludge volume and hence eases heavy burden of sludge management

(Li et al., 2016).

In a nutshell, the outcomes of this thesis should be of significant value to the water industry,

particularly considering the growing interest for Fe-salts/Fe-sludge multiple uses in integrated

UWWS in recent years. Specifically, this PhD thesis provided the mechanistic understanding of

unintended beneficial impacts of sewer-dosed Fe-salts during integrated sewer-WWTP operation,

particularly in relation to settleability and dewaterability of activated sludge and the digestate

dewaterability. In addition, this PhD thesis also experimentally demonstrated the potential multiple

206

benefits of reusing waterworks sludge (Al- or Fe-sludge) in pilot sewer under more realistic condition.

Combined, this would have a major impact on both sustainable waterworks sludge management and

urban wastewater management. Undoubtedly, such reuse practice will deliver both economic and

environmental benefits for water utilities, by reducing the burden of WTP sludge treatment/disposal

and reducing chemical consumption in urban water system. This could urge urban water utilities to

adopt an implementation of integrated approach to Fe-salt/Fe-sludge in urban wastewater

management as both environmental and economical benefits can be achieved at a reduced operational

cost when adopting the integrated Fe strategy for system-wide operation.

Figure 71. A diagrammatic representation elucidating the synthesis of this thesis work

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8.2 Main conclusions of the thesis

This thesis investigated the beneficial impacts of using the Fe-salt and waterworks Fe-/Al-sludge in

UWWS and elucidated the underlying mechanistic aspects of the associated processes. By conducting

lab-, pilot- and full-scale studies, this thesis demonstrated that the application of integrated Fe strategy

in UWWS offers benefits not only in the treatment unit (i.e. sewer) receiving the Fe dosing and also

delivers benefits other than sulfide or phosphate removal in downstream treatment units. Specifically,

the results of all the studies incorporated in this thesis have led to the following key conclusions:

• There has been growing interest in recent years to explore multiple uses of Fe-salts and/or the

beneficial reuse of Fe-sludge in integrated UWWS. For this, the transformation and transport of

Fe in sewer would be important, because such would determine Fe availability in a sewer and in

various parts of a downstream WWTP (e.g. for phosphate removal in activated sludge system or

sulfide removal in an anaerobic digester). In the context, the results of this thesis showed that

there are important time-based interactions between dosed Fe and sewage suspended solids in

sewer, influencing suspended solids settleability in a downstream PST.

• The sewer Fe dosing locations (which dictates the in-sewer retention time) was found to influence

the suspended solids removal in full-scale PST, however did not influence Fe settling separation

in PST. In other words, in-sewer retention of Fe was minimal in the full-scale trials and Fe

separation in full-scale PST is independent of in-sewer Fe dosing locations. The upstream sewer

dosing resulted in minimal in-sewer Fe retention (i.e. 11% of Fe dosed upstream) when

compared between Fe dosed and Fe reaching the PST. The retention of Fe in the primary sludge

(quantified as a difference between the influent and effluent concentration) was very similar for

the two dosing cases. However, total suspended solids removal in the PST was relatively better

for upstream sewer dosing than for WWTP inlet dosing.

• The pre-mixing time (or in-sewer retention time) did not exhibit the significant effect on observed

PSDs of Fe-sludge floc.

• The key factors that influence the Fe-transformation/fractionation (dissolved versus particulate)

and subsequently Fe retention/transport in sewer include in-sewer retention time, also prevailing

in-sewer redox conditions, and Fe-source type that being used. Combined, this would impact the

suspended solids settleability and Fe settling separation in downstream PST. These factors must

be considered when choosing system-wide Fe dosage strategies to achieve multiple (immediate

as well as downstream) benefits of sewer-dosed Fe during integrated sewer-WWTP operation.

• Considering the flowing on effect of Fe during integrated sewer-WWTP operation, sewer-dosed

Fe-salt improved the settleability and dewaterability of activated sludge. Relatively, the SVI value

of iron-conditioned sludge as 47.4±4.7 mL.g-1, whereas that of unconditioned activated sludge

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was 69.9±6.2 mL.g-1. Likewise, the iron-conditioned activated sludge exhibited much improved

dewaterability by 37.9±7.3%.

• Iron-conditioned activated sludge (228.8±22.0 mg.Fe.L-1) exhibited favorable changes in several

key sludge properties (physicochemical, morphological, and rheological) as compared to the

unconditioned activated sludge (20.1±5.2 mg.Fe.L-1). The combined synergistic effect of such

number of favorable changes observed in key sludge properties is likely responsible for improving

the settleability and dewaterability of iron-conditioned sludge.

• The anaerobic digestion of the iron-rich waste activated sludge (Fe-WAS), resultant of in-sewer

Fe-salt dosing, exhibited an improvement in the dewaterability of digestate. The mean cake solids

contents (%) of iron-conditioned and unconditioned digestate were 19.2±0.1% and 15.5±0.4%,

respectively. Such improved dewaterability could be attributed to the favorable changes in the

physicochemical, morphological, fractal, and rheological properties. The combined synergistic

interplay of such favorable changes in key digestate properties is likely to be responsible for

improving iron-conditioned digestate dewaterability. However, it was not possible to pin-point a

single factor predominantly contributing in improving dewaterability.

• Continuous dosing of sewer-dosed Fe-salt did not show any negative impacts to the key properties

of both activated sludge and digestate.

• Direct dosing of waterworks Fe-sludge in pilot sewer was effective for sulfide removal from sewer

bulk phase, but with limited effect on phosphate removal. The sulfide removal ratio for Fe-sludge

was 0.290.06 mg.S(mg.Fe)-1.

• The precipitation reaction between sulfide and ferric ions in Fe-sludge, is likely to be the dominant

mechanism for sulfide removal when dosing Fe-sludge.

• Direct dosing of waterworks Al-sludge was effective for phosphate removal, but with limited

effect on sulfide removal. The phosphate removal ratio for Al-sludge was 0.290.01

mg.P(mg.Al)-1.

• In terms of phosphate removal with Al-sludge dosing, ligand-exchange processes between the

surface -OH groups and PO43- ions, favoring the formation of both inner- and outer-sphere surface

Al-phosphate complexes, appears to be the dominant mechanism. These findings demonstrated

the potential multiple benefits of reusing the waterworks Fe-/Al-sludge in sewers akin to their

chemical counterparts.

• The direct dosing of Fe-/Al-sludge did not cause any increment in dissolved CH4 and N2O

formation, nor release of other metals in sewers.

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8.3 Recommendation for future research works

Different research gaps have been identified that entail further investigation in future in addition to

the research objectives thus investigated in this PhD thesis. Some of these research gaps are

summarized below:

• Both full-scale Fe-salt dosing trials and controlled laboratory experiments were used to

investigate the effects of in-sewer retention, in-sewer redox conditions, and Fe source type (Fe-

salt versus Fe-sludge) on Fe transformation and transport in sewer wastewater (Chapter 4). Such

transformation and transport of Fe would determine Fe availability in a sewer and in various parts

of a downstream WWTP (e.g. for phosphate removal in AS system or sulfide removal in AD).

There is a need for further detailed full-scale studies in future doing Fe-sludge to a sewer and

tracking Fe along the sewer and the connected downstream WWTP with a PST as was done in

our study with Fe-salt. This would clarify the seemingly important Fe transformation and

transport effects of Fe source type, albeit that previous work of Edwards et al. (1997) did not note

any reduced efficacy of Fe-sludge dosed to a full-scale sewer as compared to what would be

expected from sewer-dosed Fe-salt.

• It can be anticipated that there could be progressive changes to the physicochemical,

morphological, and rheological properties of activated sludge and digestate with time after the

initiation of the Fe dosing in sewer upstream of bioreactor and digester units. However, in the

studies incorporated in this thesis, we particularly focused on assessing the changes in such key

properties of activated sludge (Chapter 5) including digestate (Chapter 6) with the long-term

Fe addition to sewer under the steady operating conditions after the 3 to 4 months period after the start

of Fe dosing. No attempt was therefore made in this thesis on understanding the temporal changes

to properties of activated sludge and digestate after initiating Fe dosing. Hence, it is worth

investigating the changes in key properties of activated sludge or digestate as a function of time

(e.g. one month/three month/half year/one year/even longer running time) following the Fe

introduction to the integrated system. It is likely that iron proportion of the sludge vary with the

time and similarly the key sludge properties are expected to vary with the time after the start of

in-sewer FeCl3 dosing, especially during the initial days of dosing.

• In addition to assessing the temporal changes in physicochemical, morphological, and rheological

properties of activated sludge or digestate with Fe addition to the system (Chapter 5 and Chapter

6), it is worth investigating the changes in the microbial communities of activated sludge or

digestate as a function of time. In other words, it is recommended to assess the response of the

microbial community of activated sludge in bioreactor and digestate in anaerobic digester unit in

terms of its structure to the sewer dosing of Fe.

210

• When assessing the changes in the contents of different EPS fractions including associated major

organic components/biopolymers in each extracted fraction of activated sludge due to Fe addition,

focus was given in quantifying the changes in the contents of S-EPS, LB-EPS, and TB-EPS

fractions. This was then accompanied by quantification of the protein, polysaccharides, including

humics (FA-like and HA-like substances) contents in the thus extracted EPS fractions (Chapter

5). In retrospect, quantifying the deoxyribonucleic acid (e-DNA) or intracellular-DNA (i-DNA)

concentrations in EPS fractions as the possible mechanistic interconnection amongst the

contents of e-DNA, sludge floc aggregation, and settleability or dewaterability of activated

sludge is worth investigating in future. This would help in elucidating the possible role of Fe

availability in the disruption of EPS or cell lysis. Nonetheless, it is worth investigating the extent

of influence of Fe availability in activated sludge system on EPS disruption and cell lysis.

• Successful reuse of Al- and Fe-sludge as an alternative to chemical coagulants (alum or Fe-salts)

would have a major impact on both sustainable waterworks sludge management and urban

wastewater management. The results incorporated in this thesis (Chapter 7) further confirm the

benefits of applying Fe-sludge and Al-sludge to full-scale sewers as a viable end use for sludge

generated from WTP. However, it is recommended to undertake the further long-term

comprehensive study coupled with life cycle assessment (LCA) for fully evaluating the impacts

of waterworks sludge discharge in real-life full-scale sewer networks and receiving WWTP for

system-wide operation. In addition, a comprehensive comparative technological, environmental,

and economic analyses of waterworks sludge dosing to sewers is recommended in maximizing

the multiple benefits of such strategy.

• The described laboratory-scale studies herein clearly highlight the potential to reduce the overall

chemical footprint of water utilities by adopting a catchment-wide approach coupled with

substantial improvements in terms of overall sulfide control performance and phosphate removal

in downstream treatment units (including the favorable changes in sludge properties with direct

positive implication on their settling and dewatering performances), not only sulfide control in

upstream sewer system. However, it should be emphasized that these studies were conducted

under controlled laboratory conditions (i.e. constant temperature, flow, SRT, and HRT) using

simplified configurations. In real-life situations, the flow (and thus SRT, HRT) is highly dynamic,

whereas sewer networks typically comprise a complex system of large amounts of different sewer

pipes consisting of a mixture of gravity sewers and rising mains with changing anaerobic and

aerobic conditions. Full-scale field trials over a prolonged time period using a real-life full-scale

sewer network and downstream WWTP are therefore essential in days ahead to assess the

practical feasibility of multiple reuses of iron in the form of iron salts or iron-containing

waterworks sludge.

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References

Abu-Orf Mohammad, M. and Örmeci, B. 2005. Measuring Sludge Network Strength Using

Rheology and Relation to Dewaterability, Filtration, and Thickening—Laboratory and Full-

Scale Experiments. Journal of Environmental Engineering 131(8), 1139-1146.

Aguilar, M.I., Saez, J., Llorens, M., Soler, A. and Ortuno, J.F. 2002. Nutrient removal and sludge

production in the coagulation-flocculation process. Water Research 36, 2910-2919.

Akgul, D., Abbott, T. and Eskicioglu, C. 2017. Assessing iron and aluminum-based coagulants for

odour and pathogen reductions in sludge digesters and enhanced digestate dewaterability.

Science of The Total Environment 598, 881-888.

Al-Tahmazi, T. and Babatunde, A.O. 2016. Mechanistic study of P retention by dewatered

waterworks sludges. Environmental Technology & Innovation 6, 38-48.

Almasri, D.A., Saleh, N.B., Atieh, M.A., McKay, G. and Ahzi, S. 2019. Adsorption of phosphate

on iron oxide doped halloysite nanotubes. Scientific Reports 9(1), 3232.

APHA, 2005. Standard Methods for the Examination of Water and Wastewater, American Public

Health Association/American Water Works Association/Water Environment Federation,

Washington DC, USA.

Arai, Y. and Sparks, D.L. 2001. ATR–FTIR Spectroscopic Investigation on Phosphate Adsorption

Mechanisms at the Ferrihydrite–Water Interface. Journal of Colloid and Interface Science

241(2), 317-326.

Araújo, A.L., de Oliveira, R., Mara, D.D., Pearson, H.W. and Silva, S.A. 2000. Sulphur and

phosphorus transformations in wastewater storage and treatment reservoirs in northeast

Brazil. Water Science and Technology 42(10-11), 203-210.

ASCE, 1989. Sulfide in Wastewater Collection and Treatment Systems, New York, USA.

Babatunde, A.O. and Zhao, Y.Q. 2007. Constructive Approaches Toward Water Treatment Works

Sludge Management: An International Review of Beneficial Reuses. Critical Reviews in

Environmental Science and Technology 37(2), 129-164.

Babatunde, A.O. and Zhao, Y.Q. 2010. Equilibrium and kinetic analysis of phosphorus adsorption

from aqueous solution using waste alum sludge. Journal of hazardous materials 184(1), 746-

752.

212

Babatunde, A.O., Zhao, Y.Q., Yang, Y. and Kearney, P. 2008. Reuse of dewatered aluminium-

coagulated water treatment residual to immobilize phosphorus: Batch and column trials using

a condensed phosphate. Chemical Engineering Journal 136(2), 108-115.

Bagastyo, A.Y., Keller, J. and Batstone, D.J. 2011. Size fractionation characterisation of removed

organics in reverse osmosis concentrates by ferric chloride. Water Science and Technology

63(9), 1795-1800.

Baghvand, A., Zand, A.D., Mehradadi, N. and Karbassi, A. 2010. Optimizing Coagulation Process

for Low to High Turbidity Waters Using Aluminum and Iron Salts. American Journal of

Environmental Sciences 6(5), 442-448.

Bai, L., Wang, C., Pei, Y. and Zhao, J. 2014. Reuse of drinking water treatment residuals in a

continuous stirred tank reactor for phosphate removal from urban wastewater. Environmental

Technology 35, 2752-2759.

Banwart, S., Davies, S. and Stumm, W. 1989. The role of oxalate in accelerating the reductive

dissolution of hematite (α-Fe2O3) by ascorbate. Colloids and Surfaces 39(2), 303-309.

Batstone, D.J., Puyol, D., Flores-Alsina, X. and Rodríguez, J. 2015. Mathematical modelling of

anaerobic digestion processes: applications and future needs. Reviews in Environmental

Science and Bio/Technology 14(4), 595-613.

Baudez, J.-C., Gupta, R.K., Eshtiaghi, N. and Slatter, P. 2013. The viscoelastic behaviour of raw

and anaerobic digested sludge: Strong similarities with soft-glassy materials. Water Research

47(1), 173-180.

BCC-Research, 2018. Specialty Water Treatment Chemicals: Technologies and Global Markets.

Rajaram, S. (ed), Wellesley, MA 02481, USA.

Bentzen, G., Smith, A.T., Bennett, D., Webster, N.J., Reinholt, F., Sletholt, E. and Hobson, J. 1995.

Controlled Dosing of Nitrate for Prevention of H2S in a Sewer Network and the Effects on

the Subsequent Treatment Processes. Water Science and Technology 31(7), 293-302.

Biber, M.V., dos Santos Afonso, M. and Stumm, W. 1994. The coordination chemistry of

weathering: IV. Inhibition of the dissolution of oxide minerals. Geochimica et Cosmochimica

Acta 58(9), 1999-2010.

Blakemore, R., Chandler, R., Surrey, T., Ogilvie, D. and Walmsley, N. 1998. Management of Water

Treatment Plant Residuals in New Zealand, First Edition.

Bobade, V., Baudez, J.C., Evans, G. and Eshtiaghi, N. 2017. Impact of gas injection on the apparent

viscosity and viscoelastic property of waste activated sewage sludge. Water Research 114,

213

296-307.

Bougrier, C., Albasi, C., Delgenès, J.P. and Carrère, H. 2006. Effect of ultrasonic, thermal and ozone

pre-treatments on waste activated sludge solubilisation and anaerobic biodegradability.

Chemical Engineering and Processing: Process Intensification 45(8), 711-718.

Bowes, M.J., Jarvie, H.P., Halliday, S.J., Skeffington, R.A., Wade, A.J., Loewenthal, M., Gozzard,

E., Newman, J.R. and Palmer-Felgate, E.J. 2015. Characterising phosphorus and nitrate

inputs to a rural river using high-frequency concentration–flow relationships. Science of The

Total Environment 511, 608-620.

Bozdogan, H. 1987. Model selection and Akaike's Information Criterion (AIC): The general theory

and its analytical extensions. Psychometrika 52(3), 345-370.

Bratby, J. 2006. Coagulation and Flocculation in Water and Wastewater Treatment, IWA publishing,

London, Seattle.

Brix, H. 2017. Sludge Dewatering and Mineralization in Sludge Treatment Reed Beds. Water 9(3),

160.

Calabro, P.S., Mannina, G. and Viviani, G. 2009. In sewer processes: mathematical model

development and sensitivity analysis. Water Science and Technology 60(1), 107-115.

Carrera, L., Springer, F., Lipeme-Kouyi, G. and Buffiere, P. 2016. A review of sulfide emissions in

sewer networks: overall approach and systemic modelling. Water Science and Technology

73(6), 1231-1242.

Cetin, S. and Erdincler, A. 2004. The role of carbohydrate and protein parts of extracellular

polymeric substances on the dewaterability of biological sludges. Water Science and

Technology 50(9), 49-56.

Chakrabarti, A. and Ghosh, J.K. 2011. Philosophy of Statistics. Bandyopadhyay, P.S. and Forster,

M.R. (eds), pp. 583-605, North-Holland, Amsterdam.

Chen, J., LeBoeuf, E.J., Dai, S. and Gu, B. 2003a. Fluorescence spectroscopic studies of natural

organic matter fractions. Chemosphere 50(5), 639-647.

Chen, W., Westerhoff, P., Leenheer, J.A. and Booksh, K. 2003b. Fluorescence Excitation−Emission

Matrix Regional Integration to Quantify Spectra for Dissolved Organic Matter. Environmental

Science & Technology 37(24), 5701-5710.

Chen, Y., Yang, H. and Gu, G. 2001. Effect of acid and surfactant treatment on activated sludge

dewatering and settling. Water Research 35(11), 2615-2620.

214

Chen, Z., Zhang, W., Wang, D., Ma, T. and Bai, R. 2015. Enhancement of activated sludge

dewatering performance by combined composite enzymatic lysis and chemical re-flocculation

with inorganic coagulants: Kinetics of enzymatic reaction and re-flocculation morphology.

Water Research 83, 367-376.

Cheng, W.P., Chi, F.H., Li, C.C. and Yu, R.F. 2008. A study on the removal of organic substances

from low-turbidity and low-alkalinity water with metal-polysilicate coagulants. Colloids and

Surfaces A: Physicochemical and Engineering Aspects 312(2), 238-244.

Choi, Y., Jung, B.-G., Son, H.-J. and Jung, Y.-J. 2010. Determination of Optimum Coagulants (Ferric

Chloride and Alum) for Arsenic and Turbidity Removal by Coagulation. Journal of the

Environmental Sciences 931-940.

Cornwell, D.A. 2006. Water treatment residuals engineering, AWWA Research Foundation and

American Water Works Association, Denver, Colorado; pp. 364.

Dai, Q., Ma, L., Ren, N., Ning, P., Guo, Z., Xie, L. and Gao, H. 2018. Investigation on extracellular

polymeric substances, sludge flocs morphology, bound water release and dewatering

performance of sewage sludge under pretreatment with modified phosphogypsum. Water

Research 142, 337-346.

Dai, Y., Huang, S., Liang, J., Zhang, S., Sun, S., Tang, B. and Xu, Q. 2017. Role of organic

compounds from different EPS fractions and their effect on sludge dewaterability by

combining anaerobically mesophilic digestion pre-treatment and Fenton’s reagent/lime.

Chemical Engineering Journal 321, 123-138.

Daou, T.J., Begin-Colin, S., Grenèche, J.M., Thomas, F., Derory, A., Bernhardt, P., Legaré, P. and

Pourroy, G. 2007. Phosphate Adsorption Properties of Magnetite-Based Nanoparticles.

Chemistry of Materials 19(18), 4494-4505.

Darby, J.L., Poxon, T.L. and Tsuchihashi, R. 1997. Influence of Biocolloids and Biocolloidal

Structure on the Dewaterability of Anaerobically Digested Sludge, University of California -

Davis, USA.

Dassanayake, K.B., Jayasinghe, G.Y., Surapaneni, A. and Hetherington, C. 2015. A review on alum

sludge reuse with special reference to agricultural applications and future challenges. Waste

Management 38, 321-335.

Davydov, A., Chuang, K.T. and Sanger, A.R. 1998. Mechanism of H2S oxidation by ferric oxide

and hydroxide surfaces. The Journal of Physical Chemistry B 102(24), 4745-4752.

de Haas, D., Wentzel, M. and Ekama, G. 2000. The use of simultaneous chemical precipitation in

215

modified activated sludge systems exhibiting biological excess phosphate removal Part 1:

literature review. Water SA 26(4), 439-452.

de Haas, D.W., Wentzel, M.C. and Ekama, G.A. 2001. The use of simultaneous chemical

precipitation in modified activated sludge systems exhibiting biological excess phosphate

removal Part 6: Modelling of simultaneous chemical-biological P removal –review of existing

models. Water SA 27(2), 135-150.

De Toffol, S. 2006. Sewer system performance assessment – an indicators based methodology. ,

eingereicht an der, Leopold Franzens Universität Innsbruck, Fakultät für

Bauingenieurwissenschaften zur Erlangung des Titels, Doktor der technischen

Wissenschaften, Innsbruck.

Dentel, S.K., Ayol, A. and Filibeli, A. 2005. Modern rheometric characterization of sludges. Journal

Residuals Science & Technology 2(4), 233-240.

Dentel, S.K. and Gosset, J.M. 1982. Effect of chemical coagulation on anaerobic digestibility of

organic materials. Water Research 16(707-718).

Devlin, D.C., Esteves, S.R.R., Dinsdale, R.M. and Guwy, A.J. 2011. The effect of acid pretreatment

on the anaerobic digestion and dewatering of waste activated sludge. Bioresource Technology

102(5), 4076-4082.

Dharmappa, H.B., Hasia, A. and Hagare, P. 1997. Water treatment plant residuals management.

Water Science and Technology 35(8), 45-56.

Dhiman, R. Speciality Chemicals for Water Treatment: The Global Market; Report No. CHM050A;

BCC Research: Wellesley, MA, USA, 2008; p. 101.

Duan, Y., Li, H., Ye, L. and Liu, X. 2006. Study on the thermal degradation of polyoxymethylene by

thermogravimetry–Fourier transform infrared spectroscopy (TG–FTIR). Journal of Applied

Polymer Science 99(6), 3085-3092.

Edwards, M., Courtney, B., Heppler, P.S. and Hernandez, M. 1997. Beneficial discharge of iron

coagulation sludge to sewers. Journal of Environmental Engineering 123(10), 1027-1032.

El Samrani, A.G., Lartiges, B.S., Montargès-Pelletier, E., Kazpard, V., Barrès, O. and Ghanbaja, J.

2004. Clarification of municipal sewage with ferric chloride: the nature of coagulant species.

Water Research 38(3), 756-768.

Eshtiaghi, N., Baudez, J. and Slatter, P. 2013a. Rheological behaviour of anaerobic digested sludge:

impact of concentration and temperature. Juan M. Lema, M.C.e. (ed), p. 4, International Water

Association (IWA), United Kingdom.

216

Eshtiaghi, N., Markis, F., Yap, S.D., Baudez, J.-C. and Slatter, P. 2013b. Rheological characterisation

of municipal sludge: A review. Water Research 47(15), 5493-5510.

Feng, G., Liu, L. and Tan, W. 2014a. Effect of Thermal Hydrolysis on Rheological Behavior of

Municipal Sludge. Industrial & Engineering Chemistry Research 53(27), 11185-11192.

Feng, G., Tan, W., Zhong, N. and Liu, L. 2014b. Effects of thermal treatment on physical and

expression dewatering characteristics of municipal sludge. Chemical Engineering Journal

247, 223-230.

Fernandez, J., Perez, M. and Romero, L.I. 2010. Kinetics of mesophilic anaerobic digestion of the

organic fraction of municipal solid waste: influence of initial total solid concentration.

Bioresouce Technology 101, 6322-6328.

Filho, S.S.F., Piveli, R.P., Cutolo, S.A. and de Oliveira, A.A. 2013. Water treatment plant sludge

disposal into stabilization ponds. Water Science and Technology 67(5), 1017-1025.

Firer, D., Friedler, E. and Lahav, O. 2008. Control of sulfide in sewer systems by dosage of iron salts:

Comparison between theoretical and experimental results, and practical implications. Science

of the Total Environment 392(145-156).

Flores-Alsina, X., Solon, K., Kazadi Mbamba, C., Tait, S., Gernaey, K.V., Jeppsson, U. and Batstone,

D.J. 2016. Modelling phosphorus (P), sulfur (S) and iron (Fe) interactions for dynamic

simulations of anaerobic digestion processes. Water Research 95, 370-382.

Forster, C.F. 1983. Bound water in sewage sludges and its relationship to sludge surfaces and sludge

viscosities. Journal of Chemical Technology and Biotechnology. Biotechnology 33(1), 76-84.

Forster, C.F. 2002. The rheological and physico-chemical characteristics of sewage sludges. Enzyme

and Microbial Technology 30(3), 340-345.

Frossard, E., Bauer, J.P. and Lothe, F. 1997. Evidence of vivianite in FeSO4-flocculated sludges.

Water Research 31(10), 2449-2454.

Ganigue, R., Gutierrez, O., Rootsey, R. and Yuan, Z. 2011a. Chemical dosing for sulfide control in

Australia: An industry survey. Water Research 45, 6564-6574.

Ganigue, R., Gutierrez, O., Rootsey, R. and Yuan, Z. 2011b. Chemical dosing for sulfide control in

Australia: An industry survey. Water Research 45(19), 6564-6574.

Gao, B.-Y., Yue, Q.-Y. and Wang, Y. 2007. Coagulation performance of polyaluminum silicate

chloride (PASiC) for water and wastewater treatment. Separation and Purification Technology

56(2), 225-230.

217

Ge, H., Zhang, L., Batstone, D.J., Keller, J. and Yuan, Z. 2013. Impact of iron salt dosage to sewers

on downstream anaerobic sludge digesters: sulfide control and methane production. Journal

of Environmental Engineering 139, 594-601.

Georgantas, D.A. and Grigoropoulou, H.P. 2005. Phosphorus removal from synthetic and municipal

wastewater using spent alum sludge. Water Science and Technology 52, 525-532.

GHD, 2015. Alum sludge reuse investigation - working technical report, pp. 1-150, GHD, Monash

University, ACTEW Water, and Seqwater.

Ghyoot, W. and Verstraete, W. 1997. Anaerobic digestion of primary sludge from chemical pre-

precipitation. Water Science and Technology 36(6-7), 357-365.

Gmachowski, L. 1995. Mechanism of shear aggregation. Water Research 29(8), 1815-1820.

Gmachowski, L. 1996. Hydrodynamics of Aggregated Media. Journal of Colloid and Interface

Science 178(1), 80-86.

Gon Kim, J., Hyun Kim, J., Moon, H.-S., Chon, C.-M. and Sung Ahn, J. 2002. Removal capacity of

water plant alum sludge for phosphorus in aqueous solutions. Chemical Speciation &

Bioavailability 14(1-4), 67-73.

Gregory, A. and Hall, M. 2011. Urban water sustainability Prosser, I. (ed), pp. 75-88, CSIRO

Publishing, Australia.

Grigoropoulos, S., Vederr, R. and Max, D. 1971. Fate of aluminium-precipitated phosphorus in

activated sludge and anaerobic digestion. Journal of the Water Pollution Control Federation

43(12), 2366-2382.

Gu, B., Schmitt, J., Chen, Z., Liang, L. and McCarthy, J.F. 1995. Adsorption and desorption of

different organic matter fractions on iron oxide. Geochimica et Cosmochimica Acta 59(2),

219-229.

Guan, X.-H., Chen, G.-H. and Shang, C. 2005a. Re-use of water treatment works sludge to enhance

particulate pollutant removal from sewage. Water Research 39(15), 3433-3440.

Guan, X.-H., Liu, Q., Chen, G.-H. and Shang, C. 2005b. Surface complexation of condensed

phosphate to aluminum hydroxide: An ATR-FTIR spectroscopic investigation. Journal of

Colloid and Interface Science 289(2), 319-327.

Guan, X.H. 2005. Competitive adsorption between orthophosphate and other phosphates on

aluminum hydroxide. Soil Science 170(5), 340-349.

Gutierrez, O., Park, D., Sharma, K.R. and Yuan, Z. 2010. Iron salts dosage for sulfide control in

218

sewers induces chemical phosphorus removal during wastewater treatment. Water Research

44(11), 3467-3475.

GWC, 2014. Water treatment waste management. WASH Technical Paper, P.b.C.I.a.P.N.f.t.G.W.C.,

pp. 1-8. (ed).

Hasar, H., Kinaci, C., Ünlü, A., Toǧrul, H. and Ipek, U. 2004. Rheological properties of activated

sludge in a sMBR. Biochemical Engineering Journal 20(1), 1-6.

He, D.-Q., Zhang, Y.-J., He, C.-S. and Yu, H.-Q. 2017. Changing profiles of bound water content and

distribution in the activated sludge treatment by NaCl addition and pH modification.

Chemosphere 186, 702-708.

Heitmann, T. and Blodau, C. 2006. Oxidation and incorporation of hydrogen sulfide by dissolved

organic matter. Chemical Geology 235(1), 12-20.

Henderson, R.K., Baker, A., Murphy, K.R., Hambly, A., Stuetz, R.M. and Khan, S.J. 2009.

Fluorescence as a potential monitoring tool for recycled water systems: A review. Water

Research 43(4), 863-881.

Hermawan, M., Bushell, G.C., Craig, V.S.J., Teoh, W.Y. and Amal, R. 2004. Floc Strength

Characterization Technique. An Insight into Silica Aggregation. Langmuir 20(15), 6450-

6457.

Herwijn, A.J.M. 1996. Fundamental aspects of sludge characterization, Technische Universiteit

Eindhoven, Eindhoven, Netherlands.

Hewayde, E., Nehdi, M., Allouche, E. and Nakhla, G. 2006. Effect of geopolymer cement on

microstructure, compressive strength and sulphuric acid resistance of concrete. Magazine of

Concrete Research 58(5), 321-331.

Higgins, M., Bott, C., Schauer, P. and Beightol, S. 2014. Does Bio-P Impact Dewatering after

Anaerobic Digestion? Yes, and not in a good way! Proceedings of the Water Environment

Federation (2), 1-11.

Higgins, M.J. and Novak, J.T. 1997a. Dewatering and Settling of Activated Sludges: The Case for

Using Cation Analysis. Water Environment Research 69(2), 225-232.

Higgins, M.J. and Novak, J.T. 1997b. The Effect of Cations on the Settling and Dewatering of

Activated Sludges: Laboratory Results. Water Environment Research 69(2), 215-224.

Higgins, M.J., Sobeck, D.C., Owens, S.J. and Szabo, L.M. 2004. Case Study II: Application of the

Divalent Cation Bridging Theory to Improve Biofloc Properties and Industrial Activated

219

Sludge System Performance-Using Alternatives to Sodium-Based Chemicals. Water

Environment Research 76(4), 353-359.

Holmer, M., Duarte, C.M. and Marba, N. 2005. Iron additions reduce sulfate reduction rates and

improve seagrass growth on organic enriched carbonate sediments. Ecosystems 8(6), 721-

730.

Horth, H., Gendebien, A., Agg, R. and Cartwright, N. 1994. Treatment and disposal of waterworks

sludge in selected European countries. Foundation for water research technical reports. No.

FR 428.

Hsu, D.Y. and Pipes, W.O. 1973. Aluminum Hydroxide Effects on Wastewater Treatment Processes.

Journal (Water Pollution Control Federation) 45(4), 681-697.

Huang, S.-H. and Chiswell, B. 2000. Phosphate removal from wastewater using spent alum sludge.

Water Science and Technology 42, 295-300.

Hvitved-Jacobsen, T. 2002. Sewer Processes-Microbial and Chemical Process Engineering of Sewer

Networks, first ed. , CRC Press, Boca Raton, FL.

Hvitved-Jacobsen, T., Vollertsen, J. and Matos, J.S. 2002. The sewer as a bioreactor - A dry weather

approach. Water Science and Technology 45(3), 11-24.

Hvitved-Jacobsen, T., Vollertsen, J. and Nielsen, A.H. 2013. Sewer Processes-Microbial and

Chemical Process Engineering of Sewer Networks, CRC press, Boca Raton, FL, USA.

Ippolito, J.A., Barbarick, K.A., Heil, D.M., Chandler, J.P. and Redente, E.F. 2003. Phosphorus

Retention Mechanisms of a Water Treatment Residual. Journal of Environmental Quality

32(5), 1857-1864.

Ivanov, V., Kuang, S.L., Stabnikov, V. and Guo, C.H. 2009. The removal of phosphorus from reject

water in a municipal wastewater treatment plant using iron ore. Journal of Chemical

Technology and Biotechnology 84(78-82).

Jin, B., Wilén, B.-M. and Lant, P. 2003. A comprehensive insight into floc characteristics and their

impact on compressibility and settleability of activated sludge. Chemical Engineering Journal

95(1), 221-234.

Jin, B., Wilén, B.-M. and Lant, P. 2004. Impacts of morphological, physical and chemical properties

of sludge flocs on dewaterability of activated sludge. Chemical Engineering Journal 98(1),

115-126.

Johnson, B.B., Ivanov, A.V., Antzutkin, O.N. and Forsling, W. 2002. 31P Nuclear Magnetic

220

Resonance Study of the Adsorption of Phosphate and Phenyl Phosphates on γ-Al2O3.

Langmuir 18(4), 1104-1111.

Johnson, D.K., Carliell-Marquet, C.M. and Forster, C.F. 2003. An examination of the treatment of

iron-dosed waste activated sludge by anaerobic digestion. Environmental Technology 24(8),

937-945.

Karakashev, D., Batstone, D.J. and Angelidaki, I. 2005. Influence of Environmental Conditions on

Methanogenic Compositions in Anaerobic Biogas Reactors. Applied and Environmental

Microbiology 71(1), 331.

Karr, P.R. and Keinath, T.M. 1978. Influence of Particle Size on Sludge Dewaterability. Journal

(Water Pollution Control Federation) 50(8), 1911-1930.

Katsiris, N. and Kouzeli-Katsiri, A. 1987. Bound water content of biological sludges in relation to

filtration and dewatering. Water Research 21(11), 1319-1327.

Kawamura, S. 2000. Integrated Design and Operation of Water Treatment Facilities, John Wiley &

Sons.

Kazadi Mbamba, C., Flores-Alsina, X., John Batstone, D. and Tait, S. 2016. Validation of a plant-

wide phosphorus modelling approach with minerals precipitation in a full-scale WWTP.


Keeley, J., Jarvis, P. and Judd, S.J. 2014. Coagulant Recovery from Water Treatment Residuals: A

Review of Applicable Technologies. Critical Reviews in Environmental Science and

Technology 44(24), 2675-2719.

Keithley, S.E. and Kirisits, M.J. 2018. An improved protocol for extracting extracellular polymeric

substances from granular filter media. Water Research 129, 419-427.

Keller-Lehmann, B., Corrie, S., Ravn, R., Yuan, Z. and Keller, K. 2006. Preservation and

Simultaneous Analysis of Relevant Soluble Sulfur Species in Sewage Samples, BOKU-SIG,

Vienna, Austria, pp. 339-346.

Kiilerich, B., van de Ven, W., Nielsen, A. and Vollertsen, J. 2017. Sulfide Precipitation in Wastewater

at Short Timescales. Water 9(9), 670.

Kim, J.G., Kim, J.H., Moon, H.-S., Chon, C.-M. and Ahn, J.S. 2002. Removal capacity of water plant

alum sludge for phosphorus in aqueous solutions. Chemical Speciation & Bioavailability 14,

67-73.

Koch, G., Brongers, M., Thompson, N., Virmani, Y. and Payer, J. 2001. Corrosion cost and

221

preventive strategies in the United States Office of Infrastructure Research and Development,

Federal Highway Administration, McLean, VA.

Koga, D. 2019. Phosphorus Recovery and Recycling. Ohtake, H. and Tsuneda, S. (eds), pp. 255-264,

Springer Singapore, Singapore.

Kopp, J. and Dichtl, N. 2000. The Influence of Free Water Content on Sewage Sludge Dewatering.

Hahn, H.H., Hoffmann, E. and Ødegaard, H. (eds), pp. 347-356, Springer Berlin Heidelberg,

Berlin, Heidelberg.

Kopp, J. and Dichtl, N. 2001. Prediction of full-scale dewatering results of sewage sludges by the

physical water distribution. Water Science and Technology 43(11), 135-143.

Kotzé, R., Haldenwang, R., Fester, V. and Rössle, W. 2015. In-line rheological characterisation of

wastewater sludges using non-invasive ultrasound sensor technology. Water SA 41, 683-690.

Kuśnierz, M. and Wiercik, P. 2016. Analysis of particle size and fractal dimensions of suspensions

contained in raw sewage, treated sewage and activated sludge. Archives of Environmental

Protection 42(3), 67-76.

Kwon, J.H., Park, K.Y., Park, J.H., Lee, S.H. and Ahn, K.H. 2004. Acidic and hydrogen peroxide

treatment of polyaluminum chloride (PACL) sludge from water treatment. Water Science and


Kyncl, M. 2008. Opportunities for water treatment sludge re-use. Geoscience Engineering 54(1), 11-

22.

Laiti, E., Persson, P. and Öhman, L.-O. 1996. Surface Complexation and Precipitation at the

H+−Orthophosphate−Aged γ-Al2O3/Water Interface. Langmuir 12(12), 2969-2975.

Larsson, T., Wedborg, M. and Turner, D. 2007. Correction of inner-filter effect in fluorescence

excitation-emission matrix spectrometry using Raman scatter. Analytica Chimica Acta

583(2), 357-363.

Le, C. and Stuckey, D.C. 2016. Colorimetric measurement of carbohydrates in biological wastewater

treatment systems: A critical evaluation. Water Research 94, 280-287.

Leader, J.W., Dunne, E.J. and Reddy, K.R. 2008. Phosphorus Sorbing Materials: Sorption Dynamics

and Physicochemical Characteristics. Journal of Environmental Quality 37(1), 174-181.

Lee, B.J., Fettweis, M., Toorman, E. and Molz, F.J. 2012. Multimodality of a particle size distribution

of cohesive suspended particulate matters in a coastal zone. Journal of Geophysical Research

117(C3), 1-17.

222

Lee, L.Y., Wang, B., Guo, H., Hu, J.Y. and Ong, S.L. 2015. Aluminium-based water treatment residue

reuse for phosphorus removal. Water 7(4), 1480-1496.

Ler, A. and Stanforth, R. 2003. Evidence for surface precipitation of phosphate on goethite.

Environmental Science & Technology 37, 2694.

Li, H., Wen, Y., Cao, A., Huang, J., Zhou, Q. and Somasundaran, P. 2012. The influence of additives

(Ca2+, Al3+, and Fe3+) on the interaction energy and loosely bound extracellular polymeric

substances (EPS) of activated sludge and their flocculation mechanisms. Bioresource


Li, J. 2005. Effects of Fe(III) on floc characteristics of activated sludge. Journal of Chemical

Technology & Biotechnology 80(3), 313-319.

Li, R., Cui, J.-L., Li, X. and Li, X.-Y. 2018. Phosphorus removal and recovery from wastewater using

Fe-dosing bioreactor and co-fermentation: Investigation by X-ray absorption near edge

structure (XANES) spectroscopy. Environmental Science & Technology 52(24), 14119-

14128.

Li, W., Feng, J., Kwon, K.D., Kubicki, J.D. and Phillips, B.L. 2010. Surface Speciation of Phosphate

on Boehmite (γ-AlOOH) Determined from NMR Spectroscopy. Langmuir 26(7), 4753-4761.

Li, W., Feng, X., Yan, Y., Sparks, D.L. and Phillips, B.L. 2013. Solid-State NMR Spectroscopic

Study of Phosphate Sorption Mechanisms on Aluminum (Hydr)oxides. Environmental

Science & Technology 47(15), 8308-8315.

Li, X.Y. and Yang, S.F. 2007. Influence of loosely bound extracellular polymeric substances (EPS)

on the flocculation, sedimentation and dewaterability of activated sludge. Water Research

41(5), 1022-1030.

Li, Y., Yuan, X., Wu, Z., Wang, H., Xiao, Z., Wu, Y., Chen, X. and Zeng, G. 2016. Enhancing the

sludge dewaterability by electrolysis/electrocoagulation combined with zero-valent iron

activated persulfate process. Chemical Engineering Journal 303, 636-645.

Li, Z. and Stenstrom, M.K. 2018. Impacts of SRT on Particle Size Distribution and Reactor

Performance in Activated Sludge Processes. Water Environment Research 90(1), 48-56.

Liang, J., Huang, S., Dai, Y., Li, L. and Sun, S. 2015. Dewaterability of five sewage sludges in

Guangzhou conditioned with Fenton's reagent/lime and pilot-scale experiments using

ultrahigh pressure filtration system. Water Research 84, 243-254.

Liu, C., Lei, Z., Yang, Y., Wang, H. and Zhang, Z. 2013. Improvement in settleability and

dewaterability of waste activated sludge by solar photocatalytic treatment in Ag/TiO2-coated

223

glass tubular reactor. Bioresource Technology 137, 57-62.

Liu, J., Wei, Y., Li, K., Tong, J., Wang, Y. and Jia, R. 2016a. Microwave-acid pretreatment: A

potential process for enhancing sludge dewaterability. Water Research 90, 225-234.

Liu, J., Yang, Q., Wang, D., Li, X., Zhong, Y., Li, X., Deng, Y., Wang, L., Yi, K. and Zeng, G. 2016b.

Enhanced dewaterability of waste activated sludge by Fe(II)-activated peroxymonosulfate

oxidation. Bioresource Technology 206, 134-140.

Liu, J., Yu, D., Zhang, J., Yang, M., Wang, Y., Wei, Y. and Tong, J. 2016c. Rheological properties

of sewage sludge during enhanced anaerobic digestion with microwave-H2O2 pretreatment.


Liu, R., Zhao, Y., Sibille, C. and Ren, B. 2016d. Evaluation of natural organic matter release from

alum sludge reuse in wastewater treatment and its role in P adsorption. Chemical Engineering

Journal 302, 120-127.

Liu, Y. and Fang, H.H.P. 2003. Influences of Extracellular Polymeric Substances (EPS) on

Flocculation, Settling, and Dewatering of Activated Sludge. Critical Reviews in

Environmental Science and Technology 33(3), 237-273.

Liu, Y., Sharma, K.R., Fluggen, M., O'Halloran, K., Murthy, S. and Yuan, Z. 2015. Online dissolved

methane and total dissolved sulfide measurement in sewers. Water Research 68, 109-118.

Liu, Y., Zhang, Z., Bhandari, N., Dai, Z., Yan, F., Ruan, G., Lu, A.Y., Deng, G., Zhang, F., Al-Saiari,

H., Kan, A.T. and Tomson, M.B. 2017. New Approach to Study Iron Sulfide Precipitation

Kinetics, Solubility, and Phase Transformation. Industrial & Engineering Chemistry Research

56(31), 9016-9027.

Lookman, R., Grobet, P., Merckx, R. and Van Riemsdijk, W.H. 1997. Application of 31P and 27Al

MAS NMR for phosphate speciation studies in soil and aluminium hydroxides: promises and

constraints. Geoderma 80(3), 369-388.

Lookman, R., Grobet, P., Merckx, R. and Vlassak, K. 1994. Phosphate sorption by synthetic

amorphous aluminium hydroxides: a 27Al and 31P solid-state MAS NMR spectroscopy study.

European Journal of Soil Science 45(1), 37-44.

Lotito, V., Spinosa, L., Mininni, G. and Antonacci, R. 1997. The rheology of sewage sludge at

different steps of treatment. Water Science and Technology 36(11), 79-85.

Lovley, D.R. and Phillips, E.J. 1987a. Competitive mechanisms for inhibition of sulfate reduction

and methane production in the zone of ferric iron reduction in sediments. Applied and

environmental microbiology 53(11), 2636-2641.

224

Lovley, D.R. and Phillips, E.J.P. 1987b. Competitive mechanisms for inhibition of sulfate reduction

and methane production in the zone of ferric iron reduction. Applied and Environmental

Microbiology 53, 2636-2641.

Luedecke, C., Hermanowicz, S.W. and Jenkins, D. 1989. Precipitation of ferric phosphate in activated

sludge: a chemical model and its verification. Water Science and Technology 21, 325-337.

Lundehøj, L., Jensen, H.C., Wybrandt, L., Nielsen, U.G., Christensen, M.L. and Quist-Jensen, C.A.

2019. Layered double hydroxides for phosphorus recovery from acidified and non-acidified

dewatered sludge. Water Research 153, 208-216.

Ma, J., Lenhart James, H. and Tracy, K. 2011. Orthophosphate Adsorption Equilibrium and

Breakthrough on Filtration Media for Storm-Water Runoff Treatment. Journal of Irrigation

and Drainage Engineering 137(4), 244-250.

Makris, K.C., El-Shall, H., Harris, W.G., O'Connor, G.A. and Obreza, T.A. 2004a. Intraparticle

phosphorus diffusion in a drinking water treatment residual at room temperature. Journal of

Colloid and Interface Science 277, 417.

Makris, K.C., Harris, W.G., O'Conno, G.A. and Obreza, T.A. 2004b. Phosphorus Immobilization in

Micropores of Drinking-Water Treatment Residuals:  Implications for Long-Term Stability.

Environmental Science & Technology 38(24), 6590-6596.

Mamais, D., Pitt, P.A., Cheng, Y.O., Loiacono, J. and Jenking, D. 1994a. Determination of ferric

chloride dose to control struvite precipitation in anaerobic sludge digesters. Water


Mamais, D., Pitt, P.A., Cheng, Y.O., Loiacono, J. and Jenking, D. 1994b. Determination of ferric

chloride dose to control struvite precipitation in anaerobic sludge digesters. Water


Mao, H., Wang, F., Mao, F., Chi, Y., Lu, S. and Cen, K. 2016. Measurement of water content and

moisture distribution in sludge by 1H nuclear magnetic resonance spectroscopy. Drying

Technology 34(3), 267-274.

Marinetti, M., Dentel, S.K., Malpei, F. and Bonomo, L. 2010. Assessment of rheological methods for

a correlation to sludge filterability. Water Research 44(18), 5398-5406.

Mezger, T.G. 2006. The rheology handbook: For users of rotational and oscillatory rheometers,

Vincentz Network, Hannover, Germany.

Mikkelsen, L.H. and Keiding, K. 2002. Physico-chemical characteristics of full scale sewage sludges

with implications to dewatering. Water Research 36(10), 2451-2462.

225

Møller, P.C.F., Mewis, J. and Bonn, D. 2006. Yield stress and thixotropy: on the difficulty of

measuring yield stresses in practice. Soft Matter 2(4), 274-283.

Morgan, J.W., Forster, C.F. and Evison, L. 1990. A comparative study of the nature of biopolymers

extracted from anaerobic and activated sludges. Water Research 24(6), 743-750.

Mori, M., Seyssiecq, I. and Roche, N. 2006. Rheological measurements of sewage sludge for various

solids concentrations and geometry. Process Biochemistry 41(7), 1656-1662.

Mouri, G. and Oki, T. 2010. Modelling sewer sediment deposition, erosion, and transport processes

to predict acute influent and reduce combined sewer overflows and CO2 emissions. Water

Science and Technology 62(10), 2346-2356.

Mu, Y. and Yu, H.-Q. 2006. Rheological and fractal characteristics of granular sludge in an upflow

anaerobic reactor. Water Research 40(19), 3596-3602.

Murthy, S.N. and Novak, J.T. 1998. Effects of potassium ion on sludge settling, dewatering and

effluent properties. Water Science and Technology 37(4), 317-324.

Murthy, S.N. and Novak, J.T. 1999. Factors Affecting Floc Properties During Aerobic Digestion:

Implications for Dewatering. Water Environment Research 71(2), 197-202.

Murthy, S.N., Novak, J.T. and Holbrook, R.D. 2000. Optimizing Dewatering of Biosolids from

Autothermal Thermophilic Aerobic Digesters (ATAD) Using Inorganic Conditioners. Water


Nagaoka, H., Ueda, S. and Miya, A. 1996. Influence of bacterial extracellular polymers on the

membrane separation activated sludge process. Water Science and Technology 34(9), 165-

172.

Nguyen, T., Sharma, K., Jiang, G., Ganigue, R., Cesca, J., Vuong, L. and Yuan, Z. 2015. SeweX

modelling to support corrosion and odour management in sewers. Sewer Management-

Technical Paper. Water, 71-78.

Nguyen, T.P., Hilal, N., Hankins, N.P. and Novak, J.T. 2008. Determination of the effect of cations

and cationic polyelectrolytes on the characteristics and final properties of synthetic and

activated sludge. Desalination 222(1), 307-317.

Nielsen, A.H., Lens, P., Vollertsen, J. and Hvitved-Jacobsen, T. 2005a. Sulfide-iron interactions in

domestic wastewater from a gravity sewer. Water Research 39(12), 2747-2755.

Nielsen, A.H., Piet, L., Vollertsen, J. and Hvitved-Jacobsen, T. 2005b. Sulfide–iron interactions in

domestic wastewater from a gravity sewer. Water Research 39(12), 2747-2755.

226

Nielsen, A.H., Yongsiri, C., Hvitved-Jacobsen, T. and Vollertsen, J. 2005c. Simulation of sulfide

buildup in wastewater and atmosphere of sewer networks. Water Science and Technology

52(3), 201-208.

Nielsen Asbjørn, H., Hvitved-Jacobsen, T. and Vollertsen, J. 2007. Effects of Iron on Chemical

Sulfide Oxidation in Wastewater from Sewer Networks. Journal of Environmental

Engineering 133(6), 655-658.

Nielsen, P.H., Raunkjaer, K., Norsker, N.H., N.A., J. and Hvitved-Jacobsen, T. 1992. Transformation

of Wastewater in Sewer System-A Review. Water Science and Technology 25(16), 17-31.

Niu, M., Zhang, W., Wang, D., Chen, Y. and Chen, R. 2013. Correlation of physicochemical

properties and sludge dewaterability under chemical conditioning using inorganic coagulants.

Bioresource Technology 144, 337-343.

Novak, J.T. and Park, C.-M. 2010. Effect of aluminium and iron on odors, digestion efficiency and

dewatering properties. EPA Report, W.E.R.F.W., IWAP ISBN: 978-1-84339-283-5/1-84339-

283-6 (ed).

Novak, J.T., Sadler, M.E. and Murthy, S.N. 2003. Mechanisms of floc destruction during anaerobic

and aerobic digestion and the effect on conditioning and dewatering of biosolids. Water

Research 37(13), 3136-3144.

Ofverstrom, S., Sapkaite, I. and Dauknys, R. 2010. An investigation of impact of iron and aluminium

addition on the anaerobic digestion process, Kalmar, Sweden.

Ohlinger, K.N., Young, T.M. and Schroeder, E.D. 1998. Predicting struvite formation in digestion.

Water Research 32(12), 3607-3614.

Oikonomidis, I., Burrows, L.J. and Carliell-Marquet, C.M. 2010. Mode of action of ferric and ferrous

iron salts in activated sludge. Journal of Chemical Technology & Biotechnology 85(8), 1067-

1076.

Oriekhova, O. and Stoll, S. 2014. Investigation of FeCl3 induced coagulation processes using

electrophoretic measurement, nanoparticle tracking analysis and dynamic light scattering:

Importance of pH and colloid surface charge. Colloids And Surfaces A-Physicochemical And

Engineering Aspects 461(1), 212-219.

Örmeci, B. 2007. Optimization of a full-scale dewatering operation based on the rheological

characteristics of wastewater sludge. Water Research 41(6), 1243-1252.

Örmeci, B. and Abu-Orf, M.M. 2005. Protocol to Measure Network Strength of Sludges and Its

Implications for Dewatering. Journal of Environmental Engineering 131(1), 80-85.

227

Ormeci, B., Cho, K. and Abu-Orf, M. 2004. Development of a laboratory protocol to measure

network strength of sludges using torque rheometry. Journal of Residuals Science &


Padhi, R.K., Subramanian, S. and Satpathy, K.K. 2019. Formation, distribution, and speciation of

DBPs (THMs, HAAs, ClO2−, and ClO3−) during treatment of different source water with

chlorine and chlorine dioxide. Chemosphere 218, 540-550.

Padival, N.A., Kimbell, W.A. and Redner, J.A. 1995. The use of iron salts to control dissolved sulfide

in districts trunk sewers. Journal of Environmental Engineering 121, 824.

Pang, B.-W., Jiang, C.-H., Yeung, M., Ouyang, Y. and Xi, J. 2017. Removal of dissolved sulfides in

aqueous solution by activated sludge: mechanism and characteristics. Journal of Hazardous

Materials 324, 732-738.

Park, C., Muller, C.D., Abu-Orf, M.M. and Novak, J.T. 2006. The Effect of Wastewater Cations on

Activated Sludge Characteristics: Effects of Aluminum and Iron in Floc. Water Environment

Research 78(1), 31-40.

Park, C.M. and Novak, J.T. 2013. The effect of direct addition of iron(III) on anaerobic digestion

efficiency and odor causing compounds. Water Science and Technology 68(11), 2391-2396.

Parker, W., Celmer-Repin, D., Bicudo, J. and Law, P. 2019. Assessment of the use of mainstream

iron addition for phosphorous control on H2S content of biogas from anaerobic digestion of

sludges. Water Environment Research 0(0), 1-9.

Peeters, B. 2002. Effect of activated sludge composition on its dewaterability and sticky phase,

Katholieke Universiteit Leuven, Belgium.

Peeters, B. 2010. Mechanical Dewatering and Thermal Drying of Sludge in a Single Apparatus.

Drying Technology 28(4), 454-459.

Peeters, B., Dewil, R., Lechat, D. and Smets, I.Y. 2011. Quantification of the exchangeable calcium

in activated sludge flocs and its implication to sludge settleability. Separation and Purification

Technology 83, 1-8.

Persson, P., Nilsson, N. and Sjöberg, S. 1996. Structure and Bonding of Orthophosphate Ions at the

Iron Oxide–Aqueous Interface. Journal of Colloid and Interface Science 177(1), 263-275.

Pham, T.T.H., Brar, S.K., Tyagi, R.D. and Surampalli, R.Y. 2010. Influence of ultrasonication and

Fenton oxidation pre-treatment on rheological characteristics of wastewater sludge.

Ultrasonics Sonochemistry 17(1), 38-45.

228

Piaskowski, K. 2013. Orthophosphate removal from aqueous solutions using drinking-water

treatment sludge. Water Science and Technology 68, 1757-1762.

Pikaar, I., Sharma, K.R., Hu, S.H., Gernjak, W., Keller, J. and Yuan, Z.G. 2014. Reducing sewer

corrosion through integrated urban water management. Science 345(6198), 812-814.

Prodănescu, A. 2017. Dewaterability of thermophilic digestate: Characteristics and underlying

processes. Master Thesis, Delft University of Technology, The Netherlands.

Prot, T., Nguyen, V.H., Wilfert, P., Dugulan, A.I., Goubitz, K., De Ridder, D.J., Korving, L., Rem,

P., Bouderbala, A., Witkamp, G.J. and van Loosdrecht, M.C.M. 2019. Magnetic separation

and characterization of vivianite from digested sewage sludge, Separation and Purification

Technology 224, 564-579

Rajan, S.S.S. 1975. Adsorption of divalent phosphate on hydrous aluminium oxide. Nature

253(5491), 434-436.

Rasmussen, H. and Nielsen, P.H. 1996. Iron reduction in activated sludge measured with different

extraction techniques. Water Research 30(3), 551-558.

Ratkovich, N., Horn, W., Helmus, F.P., Rosenberger, S., Naessens, W., Nopens, I. and Bentzen, T.R.

2013. Activated sludge rheology: A critical review on data collection and modelling. Water

Research 47(2), 463-482.

Razali, M., Zhao, Y.Q. and Bruen, M. 2007. Effectiveness of a drinking-water treatment sludge in

removing different phosphorus species from aqueous solution. Separation and Purification


Rebosura, M., Salehin, S., Pikaar, I., Sun, X., Keller, J., Sharma, K. and Yuan, Z. 2018. A

comprehensive laboratory assessment of the effects of sewer-dosed iron salts on wastewater

treatment processes. Water Research 146, 109-117.

Reichwaldt, E.S. and Ghadouani, A. 2012. Effects of rainfall patterns on toxic cyanobacterial blooms

in a changing climate: Between simplistic scenarios and complex dynamics. Water Research

46(5), 1372-1393.

Ricca, G. and Severini, F. 1993. Structural investigations of humic substances by IR-FT, 13C-NMR

spectroscopy and comparison with a maleic oligomer of known structure. Geoderma 58(3),

233-244.

Rickard, D. 1995. Kinetics of FeS precipitation: Part 1. Competing reaction mechanisms. Geochimica

et Cosmochimica Acta 59(21), 4367-4379.

229

Rios, N., Nopens, I., de Schepper, V., Jiang, T., Verstraete, W. and Vanrolleghem, P. 2007. A

Rheological Model for Activated Sludge in a Side-Stream MBR, Harrogate, UK.

Rizzo, L., Gennaro, A.D., Gallo, M. and Belgiorno, V. 2008. Coagulation/chlorination of surface

water: A comparison between chitosan and metal salts. Separation and Purification


Robinson, J.K. 1989. The role of bound water content in defining sludge dewatering characteristics,

Blacksburg, Virginia.

Rodriguez-Freire, L., Sierra-Alvarez, R., Root, R., Chorover, J. and Field, J.A. 2014.

Biomineralization of arsenate to arsenic sulfides is greatly enhanced at mildly acidic

conditions. Water Research 66, 242-253.

Rootsey, R. and Yuan, Z. 2011. The sewer corrosion and odour research (SCORe) project delivering

outcomes to the water industry. Water 38(1), 69-73.

Ruiz-Hernando, M., Simón, F.-X., Labanda, J. and Llorens, J. 2014. Effect of ultrasound, thermal and

alkali treatments on the rheological profile and water distribution of waste activated sludge.

Chemical Engineering Journal 255, 14-22.

Rus, E., Fountain, P., Mills, N., Achame, S., Obinna, M. and Manocher, A. 2017. The role of soluble

P & EPS on dewatering performance. Proceedings of the Water Environment Federation (1),

1007-1024.

Russell, J.S. and Peck, B.E. 1998a. Process residuals, McGraw‐Hill, New York, USA.

Russell, J.S. and Peck, B.E. 1998b. Process residuals in: American Water Works Association and

American Society of Civil Engineers (Eds.); Water Treatment Plant Design, Third Edition; ,

McGraw‐Hill, New York; 1998; pp. 485–530.

S⊘ndergaard, M., Wolter, K.-D. and Ripl, W. 2002. Handbook of Ecological Restoration: Volume

1: Principles of Restoration. Davy, A.J. and Perrow, M.R. (eds), pp. 184-205, Cambridge

University Press, Cambridge.

Sarfert, F., Jekel, M. and Wichmann, K. 1994. Treatment and utilization of waterwork sludges in

Germany. International Water Supply 12(3), 6-8.

Schippers, A., Jørgensen, B.B. 2002. Biogeochemistry of pyrite and iron sulfide oxidation in marine

sediments. Geochimica et Cosmochimica Acta 66(1), 85-92.

Schwertmann, U. 1991. Solubility and dissolution of iron oxides. Plant and Soil 130(1-2), 1-25.

Scorates, G. 2001. Infrared and raman characteristic group frequencies: tables and charts, John Wiley

230

& Sons Ltd., New York, USA.

Seyssiecq, I., Ferrasse, J.-H. and Roche, N. 2003. State-of-the-art: rheological characterisation of

wastewater treatment sludge. Biochemical Engineering Journal 16(1), 41-56.

Sharma, K.R., Corrie, S. and Yuan, Z. 2012. Integrated modelling of sewer system and wastewater

treatment plant for investigating the impacts of chemical dosing in sewers. Water Science and

Technology 65(8), 1399-1405.

Sheng, G.-P. and Yu, H.-Q. 2006. Characterization of extracellular polymeric substances of aerobic

and anaerobic sludge using three-dimensional excitation and emission matrix fluorescence

spectroscopy. Water Research 40(6), 1233-1239.

Sheng, G.-P., Yu, H.-Q. and Li, X.-Y. 2010. Extracellular polymeric substances (EPS) of microbial

aggregates in biological wastewater treatment systems: A review. Biotechnology Advances

28(6), 882-894.

Singh, B.P., Menchavez, R., Takai, C., Fuji, M. and Takahashi, M. 2005. Stability of dispersions of

colloidal alumina particles in aqueous suspensions. Journal of Colloid and Interface Science

291(1), 181-186.

Smidt, E. and Meissl, K. 2007. The applicability of Fourier transform infrared (FT-IR) spectroscopy

in waste management. Waste Management 27(2), 268-276.

Smith, J.A. and Carliell-Marquet, C.M. 2008. The digestibility of iron-dosed activated sludge.

Bioresource Technology 99(18), 8585-8592.

Smith, J.A. and Carliell-Marquet, C.M. 2009. A novel laboratory method to determine the biogas

potential of iron-dosed activated sludge. Bioresource Technology 100(5), 1767-1774.

Smith, J.K. and Vesilind, P.A. 1995. Dilatometric measurement of bound water in wastewater sludge.

Water Research 29(12), 2621-2626.

Smith, S., Takacs, S., Murthy, S., Daigger, G.T. and Szabo, A. 2008. Phosphate Complexation Model

and Its Implications for Chemical Phosphorus Removal. Water Environment Research 80(5),

428-438.

Snurer, H. 2005. Sludge production from chemical precipitation, Department of Chemical

Engineering, Lund Institute of Technology, Sweden.

Sobeck, D.C. and Higgins, M.J. 2002. Examination of three theories for mechanisms of cation-

induced bioflocculation. Water Research 36(3), 527-538.

Solon, K., Flores-Alsina, X., Kazadi Mbamba, C., Ikumi, D., Volcke, E.I.P., Vaneeckhaute, C.,

231

Ekama, G., Vanrolleghem, P.A., Batstone, D.J., Gernaey, K.V. and Jeppsson, U. 2017. Plant-

wide modelling of phosphorus transformations in wastewater treatment systems: Impacts of

control and operational strategies. Water Research 113, 97-110.

Song, X., Pan, Y., Wu, Q., Cheng, Z. and Ma, W. 2011. Phosphate removal from aqueous solutions

by adsorption using ferric sludge. Desalination 280, 384-390.

Sponza, D.T. 2002. Extracellular polymer substances and physicochemical properties of flocs in

steady and unsteady-state activated sludge systems. Process Biochemistry 37(9), 983-998.

Stevenson, F.J. and Goh, K.M. 1971. Infrared spectra of humic acids and related substances.

Geochimica et Cosmochimica Acta 35(5), 471-483.

Stumm, W. and Morgan, J.J. 1996. Aquatic chemistry: chemical equilibria and rates in natural waters,

Wiley, New York.

Sturm, K., Keller-Lehmann, B., Werner, U., Raj Sharma, K., Grinham, A.R. and Yuan, Z. 2015.

Sampling considerations and assessment of Exetainer usage for measuring dissolved and

gaseous methane and nitrous oxide in aquatic systems. Limnology and Oceanography:

Methods 13(7), 375-390.

Sun, J., Pikaar, I., Sharma, K.R., Keller, J. and Yuan, Z. 2015. Feasibility of sulfide control in sewers

by reuse of iron rich drinking water treatment sludge. Water Research 71, 150-159.

SWCOL, 2005. Sydney Water Corporation Operating Licence 2005–2010 Sydney Water, Sydney;

June 2005; pp. 83.

Sydney, R., Esfandi, E. and Surapaneni, S. 1996. Control concrete sewer corrosion via the crown

spray process. Water Environment Research 68(3), 338-347.

Tahmazi, T.A. 2017. Characteristics and mechanims of phosphorus remvoal by dewatered water

treatment sludges and the recovery, Cardiff University, Cardiff, Wales, U.K.

Takács, I. 2008. Experiments in Activated Sludge Modelling, PhD Thesis, Ghent University,

Belgium.

Takacs, I., Murthy, S., Smith, S. and McGrath, M. 2006. Chemical phosphorous removal to extremely

low levels: experience of two plants in the Washington D.C. area. Water Science and


Tejedor-Tejedor, M.I. and Anderson, M.A. 1990. The protonation of phosphate on the surface of

goethite as studied by CIR-FTIR and electrophoretic mobility. Langmuir 6(3), 602-611.

Tixier, N., Guibaud, G. and Baudu, M. 2003. Towards a rheological parameter for activated sludge

232

bulking characterisation. Enzyme and Microbial Technology 33(2), 292-298.

To, V.H.P. 2015. Improved conditioning for biosolids dewatering in wastewater treatment plants.

Master's Thesis, Faculty of Engineering and IT, University of Technology (UTS), Sydney,

Australia, pp. 1-153.

Tony, M.A., Zhao, Y.Q., Fu, J.F. and Tayeb, A.M. 2008. Conditioning of aluminium-based water

treatment sludge with Fenton’s reagent: Effectiveness and optimising study to improve

dewaterability. Chemosphere 72(4), 673-677.

Turchiuli, C. and Fargues, C. 2004. Influence of structural properties of alum and ferric flocs on

sludge dewaterability. Chemical Engineering Journal 103(1), 123-131.

Uyguner, C.S., Bekbolet, M. and Selcuk, H. 2007. A Comparative Approach to the Application of a

Physico-Chemical and Advanced Oxidation Combined System to Natural Water Samples.

Separation Science and Technology 42(7), 1405-1419.

UWI, 2006. United Water International, Parkside, South Australia.

van Bodegom, P.M., Scholten, J.C.M. and Stams, A.J.M. 2004. Direct inhibition of methanogenesis

by ferric iron. FEMS Microbiology Ecology 49(2), 261-268.

van Bodegom, P.M., Stams, A.J.M. 1997. Effects of alternative electron acceptors and temperature

on methanogenesis in rice paddy soils, pp. 167-182.

van Rensburg, P., Musvoto, E.V., Wentzel, M.C. and Ekama, G.A. 2003. Modelling multiple mineral

precipitation in anaerobic digester liquor. Water Research 37(13), 3087-3097.

Vaxelaire, J. and Cézac, P. 2004. Moisture distribution in activated sludges: a review. Water Research

38(9), 2215-2230.

Venkatesan, A.K., Hamdan, A.-H.M., Chavez, V.M., Brown, J.D. and Halden, R.U. 2014. Mass

Balance Model for Sustainable Phosphorus Recovery in a US Wastewater Treatment Plant.

Journal of Environmental Quality 45, 84.

Verrelli, D.I. 2008a. Drinking water treatment sludge production and dewaterability, The University

of Melbourne, Melbourne, Australia.

Verrelli, D.I. 2008b. Drinking water treatment sludge production and dewaterability The University

of Melbourne.

Vollertsen, J., Hvitved-Jacobsen, T., Ujang, Z. and Talib, S.A. 2002. Integrated design of sewers and

wastewater treatment plants. Water science and technology : a journal of the International

Association on Water Pollution Research 46(9), 11-20.

233

Vollertsen, J., Nielsen, A.H., Jensen, H.S. and Hvitved-Jacobsen, T. 2008. Modeling the Formation

and Fate of Odorous Substances in Collection Systems. Water Environment Research 80(2),

118-126.

Waite, T.D. 2002. Challenges and opportunities in the use of iron in water and wastewater treatment.

Reviews in Environmental Science and Biotechnology 1(1), 9-15.

Wang, C.-H., Gao, S.-J., Wang, T.-X., Tian, B.-H. and Pei, Y.-S. 2011a. Effectiveness of sequential

thermal and acid activation on phosphorus removal by ferric and alum water treatment

residuals. Chemical Engineering Journal 172(2), 885-891.

Wang, H.-F., Ma, Y.-J., Wang, H.-J., Hu, H., Yang, H.-Y. and Zeng, R.J. 2017. Applying rheological

analysis to better understand the mechanism of acid conditioning on activated sludge

dewatering. Water Research 122, 398-406.

Wang, W.Y., Li, A.M. and Zhang, X.M. 2012. DSC and SEM Analysis on Bound Water

Characteristics in Sewage Sludge. Advanced Materials Research 347-353, 2085-2089.

Wang, Y., Dieude-Fauvel, E. and Dentel, S.K. 2011b. Physical characteristics of conditioned

anaerobic digested sludge – A fractal, transient and dynamic rheological viewpoint. Journal

of Environmental Sciences 23(8), 1266-1273.

WEF, 1991. Design of municipal wastewater treatment plants - Vol (II), Water Environment

Federation and American Society of Civil Engineers, Alexandria, Va.

Wei, H., Ren, J., Li, A., Yang, H. 2018. Sludge dewaterability of a starch-based flocculant and its

combined usage with ferric chloride. Chemical Engineering Journal 349, 737-747.

Wilén, B.-M., Jin, B. and Lant, P. 2003. Impacts of structural characteristics on activated sludge floc

stability. Water Research 37(15), 3632-3645.

Wilén, B.-M., Lumley, D., Mattsson, A. and Mino, T. 2008. Relationship between floc composition

and flocculation and settling properties studied at a full scale activated sludge plant. Water

Research 42(16), 4404-4418.

Wilén, B.M., Lumley, D., Mattsson, A. and Mino, T. 2010. Dynamics in flocculation and settling

properties studied at a full-scale activated sludge plant. Water Environment Research 82(2),

155-168.

Wilfert, P., Mandalidis, A., Dugulan, A.I., Goubitz, K., Korving, L., Temmink, H., Witkamp, G.J.

and Van Loosdrecht, M.C.M. 2016. Vivianite as an important iron phosphate precipitate in

sewage treatment plants. Water Research 104, 449-460.

234

Wilfert, P., Dugulan, A.I., Goubitz, K., Korving, L., Witkamp, G.J. and Van Loosdrecht, M.C.M.

2018. Vivianite as the main phosphate mineral in digested sewage sludge and its role for

phosphate recovery. Water Research 144, 312-321.

Wu, J. and He, C. 2010. Experimental and modeling investigation of sewage solids sedimentation

based on particle size distribution and fractal dimension. International Journal of

Environmental Science & Technology 7(1), 37-46.

Wu, L., Hu, C. and Liu, V.W. 2018. The Sustainability of Concrete in Sewer Tunnel—A Narrative

Review of Acid Corrosion in the City of Edmonton, Canada. Sustainability 10(2).

Xiao, K., Chen, Y., Jiang, X., Yang, Q., Seow, W.Y., Zhu, W. and Zhou, Y. 2017. Variations in

physical, chemical and biological properties in relation to sludge dewaterability under Fe (II)

– Oxone conditioning. Water Research 109, 13-23.

Xing, Y., Wang, Z., Hong, C., Yang, Q., Feng, L., Jia, M. and Li, Y. 2017. Mechanism and Parameter

Optimization of Fenton’s Reagent Integrated with Surfactant Pretreatment to Improve Sludge

Dewaterability. PLOS One 12(1), e0169523.

Yang, S.-F. and Li, X.-Y. 2009. Influences of extracellular polymeric substances (EPS) on the

characteristics of activated sludge under non-steady-state conditions. Process Biochemistry

44(1), 91-96.

Yang, Y., Tomlinson, D., Kennedy, S. and Zhao, Y.Q. 2006. Dewatered alum sludge: A potential

adsorbent for phosphorus removal. Water Science and Technology 54, 207-213.

Yang, Y., Zhao, Y.Q., Babatunde, A.O., Wang, L., Ren, Y.X. and Han, Y. 2006. Characteristics and

mechanisms of phosphate adsorption on dewatered alum sludge. Separation and Purification

Technology 51(2), 193-200.

Yen, P.-S., Chen, L.C., Chien, C.Y., Wu, R.-M. and Lee, D.J. 2002. Network strength and

dewaterability of flocculated activated sludge. Water Research 36(3), 539-550.

Yeoman, S., Lester, J.N. and Perry, R. 1990. The effects of chemical phosphorus precipitation on

anaerobic-digestion. Environmental technology 11(8), 709-720.

Yeoman, S., Stephenson, T., Lester, J.N. and Perry, R. 1988. The removal of phosphorus during

wastewater treatment: a review. Environmental Pollution 49(3), 183-233.

Yin, X., Han, P., Lu, X. and Wang, Y. 2004. A review on the dewaterability of bio-sludge and

ultrasound pretreatment. Ultrasonics Sonochemistry 11(6), 337-348.

Yu, B., Zhang, D., Shan, A., Lou, Z., Yuan, H., Huang, X., Yuan, W., Dai, X. and Zhu, N. 2015.

235

Methane-rich biogas production from waste-activated sludge with the addition of ferric

chloride under a thermophilic anaerobic digestion system. RSC Advances 5(48), 38538-

38546.

Yu, G.-H., He, P.-J. and Shao, L.-M. 2010. Novel insights into sludge dewaterability by fluorescence

excitation–emission matrix combined with parallel factor analysis. Water Research 44(3),

797-806.

Yu, G.-H., He, P.-J., Shao, L.-M. and He, P.-P. 2008. Stratification Structure of Sludge Flocs with

Implications to Dewaterability. Environmental Science & Technology 42(21), 7944-7949.

Yu, J., Wang, D., Yan, M., Ye, C., Yang, M. and Ge, X. 2007. Optimized Coagulation of High

Alkalinity, Low Temperature and Particle Water: pH Adjustment and Polyelectrolytes as

Coagulant Aids. Environmental Monitoring and Assessment 131, 377-386.

Yu, W., Yang, J., Shi, Y., Song, J., Shi, Y., Xiao, J., Li, C., Xu, X., He, S., Liang, S., Wu, X. and Hu,

J. 2016. Roles of iron species and pH optimization on sewage sludge conditioning with

Fenton's reagent and lime. Water Research 95, 124-133.

Yuan, D. and Wang, Y. 2013. Influence of extracellular polymeric substances on rheological

properties of activated sludge. Biochemical Engineering Journal 77, 208-213.

Yuan, D., Wang, Y. and Qian, X. 2017. Variations of internal structure and moisture distribution in

activated sludge with stratified extracellular polymeric substances extraction. International

Biodeterioration & Biodegradation 116, 1-9.

Zhang, H., Yang, J., Yu, W., Luo, S., Peng, L., Shen, X., Shi, Y., Zhang, S., Song, J., Ye, N., Li, Y.,

Yang, C. and Liang, S. 2014. Mechanism of red mud combined with Fenton's reagent in

sewage sludge conditioning. Water Research 59, 239-247.

Zhang, J., Li, N., Dai, X., Tao, W., Jenkinson, I.R. and Li, Z. 2018. Enhanced dewaterability of sludge

during anaerobic digestion with thermal hydrolysis pretreatment: New insights through

structure evolution. Water Research 131, 177-185.

Zhang, J., Zhang, Y., Chang, J., Quan, X. and Li, Q. 2013. Biological sulfate reduction in the

acidogenic phase of anaerobic digestion under dissimilatory Fe (III)-reducing conditions.

Water Research 47(6), 2033-2040.

Zhang, L., De Schryver, P., De Gusseme, B., De Muynck, W., Boon, N. and Verstraete, W. 2008.

Chemical and biological technologies for hydrogen sulfide emission control in sewer systems:

a review. Water Research 42(1-2), 1-12.

Zhang, L., Jingxing, M.A., Yinchen, J., Zhang, H., Liu, Y. and Cai, L. 2015. Abatement of sulifde

236

generation in sewage by glutaraldehyde supplementation and the impact on the activated

sludge accordingly. Frontiers of Environmental Science & Engineering 9(2), 365-370.

Zhang, L., Keller, J. and Yuan, Z. 2009a. Inhibition of sulfate-reducing and methanogenic activities

of anaerobic sewer biofilms by ferric iron dosing. Water Research 43(17), 4123-4132.

Zhang, L., Keller, J. and Yuan, Z. 2009b. Inhibition of sulfate-reducing and methanogenic activities

of anaerobic sewer biofilms by ferric iron dosing. Water Research 43, 4123-4132.

Zhang, L., Keller, J. and Yuan, Z. 2010. Ferrous Salt Demand for Sulfide Control in Rising Main

Sewers: Tests on a Laboratory-Scale Sewer System. Journal of Environmental Engineering

136(10), 1180-1187.

Zhang, L.H., De Gusseme, B., Cai, L.K., De Schryver, P., Marzorati, M., Boon, N., Lens, P. and

Verstraete, W. 2011. Addition of an aerated iron-rich waste-activated sludge to control the

soluble sulphide concentration in sewage. Water and Environment Journal 25(1), 106-115.

Zhao, P., Ge, S., Chen, Z. and Li, X. 2013. Study on pore characteristics of flocs and sludge

dewaterability based on fractal methods (pore characteristics of flocs and sludge dewatering).

Applied Thermal Engineering 58(1), 217-223.

Zhao, Y.Q., Razali, M., Babatunde, A.O., Yang, Y. and Bruen, M. 2007. Reuse of Aluminum‐based

Water Treatment Sludge to Immobilize a Wide Range of Phosphorus Contamination:

Equilibrium Study with Different Isotherm Models. Separation Science and Technology

42(12), 2705-2721.

Zhen, G., Lu, X., Wang, B., Zhao, Y., Chai, X., Niu, D., Zhao, A., Li, Y., Song, Y. and Cao, X. 2012.

Synergetic pretreatment of waste activated sludge by Fe(II)–activated persulfate oxidation

under mild temperature for enhanced dewaterability. Bioresource Technology 124, 29-36.

Zhou, J., Xu, W., Wong, J.W.C., Yong, X., Yan, B., Zhang, X. and Jia, H. 2015. Ultrasonic and

Thermal Pretreatments on Anaerobic Digestion of Petrochemical Sludge: Dewaterability and

Degradation of PAHs. PLOS one 10(9), e0136162-e0136162.

237

Appendices

238

Appendix A: Coagulation performance – comparative studies between alum and iron salt

towards finished water qualities

Table A1: Comparative studies between efficacy of alum and FeCl3 (usage as chemical coagulants)

towards finished water qualities

Coagulants

(dose)

Source water Overview of water quality characteristics

(% Removal)

Refs.

Turbidity

(NTU)

Alkalinity

(mg.L-1)

as CaCO3

DOC

(mg.L-1)

pH UV254 (m-1) THMFP

(μg.L-1)

FeCl3 (40

and 80

mg.L-1)

Alum (40

mg.L-1)

FeCl3 >

Alum

Alento

constructed

basin (Italy)

FeCl3: 88%*

Alum: 80%

(FeCl3

dosage 80

mg.L-1,

whereas

Alum dosage

was 40

mg.L-1, both

at pH 6)

n.d. FeCl3:

51.3%

(Dosage

40

mg.L-1

at pH 5)

7.9 FeCl3: 80%

Alum: 77%

n.d. Rizzo et

al. (2008)

FeCl3

Alum

Both

coagulants

were dosed

at 50, 60,

and 80

mg.L-1.

FeCl3 >

Alum

Drinking

water

reservoirs

(Istanbul,

Turkey)

Reservoir 1:

Elmali

5.5 71 FeCl3:

48%

Alum

44%

7.59 FeCl3: 78%

Alum:

76.9%

179 Uyguner

et al.

(2007)

Reservoir 2:

Omerli

2.4 61 FeCl3:

34.1%

Alum:

28%

7.40 Both FeCl3

and Alum:

64.9%

169

Reservoir 3:

Buyukcekmece

2.8 133 FeCl3:

29.1%

Alum:

25.9%

7.69 FeCl3: 50%

Alum: 47%

178

FeCl3 (9.73

mg.L-1)

AlCl3 (8

mg.L-1)

FeCl3 >

AlCl3

Yellow River

(Tianjin,

China)

FeCl3:

78.8%

(FeCl3

dosage was

12.98 mg.L-1

at pH 7.4,

whereas

AlCl3

showed no

removal. The

reason was

mentioned as

the

differences

in their

hydrolysis

and

precipitation

behaviors)

292 n.d. 8.15 Both FeCl3

and AlCl3:

27.4%

(AlCl3 dose

requirement

was 0.35

mg.L-1

higher than

FeCl3

(12.98

mg.L-1 ) at

pH 7.4 to

achieve

similar

efficiency)

n.d. [11]

Yu et al.

(2007)

239

FeCl3 (8

mg.L-1)

Alum (16

mg.L-1)

FeCl3 >

Alum

Deer Creek

Reservoir and

Little

Cottonwood

Creek

Reservoir

(Utah, USA)

FeCl3:

90.6%

Alum:

90.2%

(effective pH

for FeCl3

was 8,

whereas it

was 6.5 for

Alum)

96.46 n.d. 7.86 n.d. n.d. [76]

Choi et

al. (2010)

FeCl3 (5-50

mg.L-1)

Alum (5-50

mg.L-1)

FeCl3 >

Alum

Standard jar

test (Iran)

FeCl3: 99%

Alum:

98.5%

Optimum

conditions:

FeCl3: 10

mg.L-1, pH

5-6

Alum: 20

mg.L-1, pH 7

n.d. n.d. n.d. n.d. n.d. [77]

Baghvand

et al.

(2010)

*(%) value indicates the removal efficiency using alum and FeCl3 coagulants; other values represent the

raw water values of the parameters studied; THMFP denotes Trihalomethane formation potential; n.d.

indicates no data available

240

Appendix B: Microbial community analysis (MCA) in sludges

To investigate the changes in the microbial communities of the activated sludges including

anaerobically digested sludges (unconditioned and iron-conditioned) owing to the likely influence of

in-sewer FeCl3 dosing, MCA was carried out for sludges sourced from both control (SBR-C, AD-C)

and experimental (SBR-E, AD-E) SBR and AD reactors. For this, iron-conditioned and unconditioned

sludge samples from control and experimental SBR/AD reactors were sampled during the 4 months

period after initiation of FeCl3 dosing to sewer reactor.

The DNA of both unconditioned (SBR-C, AD-C) and iron-conditioned (SBR-E, AD-E) sludge

samples were extracted right after collection using the Fast DNATM SPIN Kit for Soil (MP

Biomedicals, CA, USA) according to the manufacture’s protocol. To perform 16S rRNA gene

amplicon sequencing (Illumina), extracted DNA samples were provided to the Australia Center for

Ecogenomics (ACE) at the University of Queensland (Brisbane, Australia). The extracted 16S rRNA

gene was amplified using the universal primer set 926F (5’- AAACTYAAAKGAATTGACGG-3’)

and 1392R (5’-ACGGGCGGTGTGTRC-3’). The resulting PCR amplicons were then purified using

Agencourt AMPure XP beads (Beckman Coulter), which was then indexed using the Illumina

Nextera XT 384 sample Index Kit A-D (Illumina FC-131-1002) in standard PCR conditions with Q5

Hot Start HighFidelity2X Master Mix. The indexed amplicons were pooled together in equimolar

concentrations and sequenced on MiSeq Sequencing System (Illumina) at ACE as per the

manufacturer's protocol. Raw sequencing data were quality-filtered and demultiplexed using

Trimmomatic, with poor-quality sequences trimmed and removed. Subsequently, high-quality

sequences at 97% similarity were clustered into operational taxonomic units (OTUs) using QIIME

(an open source for bioinformatics database) with default parameters, and representative OTU

sequences were taxonomically BLASTed against the genes 16S rRNA database. The results are

presented below:

241

Figure B1. Changes observed in relative abundance of major (a) phyla (%) and (b) classes (%) of

microbial communities in unconditioned and iron-conditioned activated sludges

The results of relative abundance of major phyla (%) and classes (%) of microorganisms in

unconditioned and iron-conditioned activated sludges are shown in Figure B1. Of all the identified

seven major phyla of bacterial communities, relative abundance (%) of Proteobacteria (31.2%),

Bacteroidetes (23.0%), Planctomycetes (7.8%) were dominant in iron-conditioned sludge wherein

these phyla in unconditioned sludge sample were 21.7%, 18.2% and 4.0%, respectively. Similarly,

relative abundance (%) of four other major phyla Chloroflexi (13.3%), Actinobacteria (7.1%),

Firmicutes (0.7%) and TM7 (2.8%) were dominant in unconditioned sludge whilst these phyla in

iron-conditioned sludge sample were 13.0%, 5.2%, 0.6% and 0.4%, respectively. In terms of major

classes of filamentous organisms, Alveolata, Saprospirae, Anaerolineae and Betaproteobacteria were

primarily abundant in both sludge samples from SBR-E and SBR-C. However, relative abundance

(%) of all Alveolata, Saprospirae, Anaerolineae and Betaproteobacteria classes were higher in iron-

conditioned sludge, i.e., 7.9%, 16.3%, 11.4% and 20.7%, respectively. Similarly, relative abundances

(%) of these major four classes in unconditioned sludge sample were observed to account for 2.4%,

13.8%, 11.1% and 12.8%, respectively.

242

Figure B2. Relative abundance of major classes (%) of microbial communities present in both

unconditioned and iron-conditioned digestate samples. Most abundant classes presented above dotted

line. Of all the identified major classes of microbial communities, relative abundance (%) of classes

more abundant in digestate (AD-E) than digestate (AD-C) include Methanomicrobia, Bateroidia,

Anaerolineae and Gammaproteobacteria. Akin, classes Actinobacteria, Betaproteobacteria, Clostridia

and Methanobacteria were relatively more abundant in digestate (AD-C) than digestate (AD-E)

Here, both unconditioned (AD-C) and iron-conditioned (AD-E) digestate samples were dominated

by the strictly acetoclastic Methanosaeta; comparatively relative abundance (%) of Methanosaeta

was higher in AD-E than AD-C (Figure B2). The more dominance of Methanosaeta in both ADs is

likely suggesting the aceticlastic methanogenesis as the dominant methanogenic pathways in both

reactors. This finding is in line with previous studies. Karakashev et al. (2005) concluded that AD

operating with high ammonia-nitrogen and volatile fatty acids (VFAs) was characterised by

dominance of the Methanosarcinace in the methanogens wherein AD operating at low levels of

ammonia and VFA by dominance of the Methanosaetaceae. Later, Yu et al. (2015) reported that

Methanosarcina is the only a methanogens that utilizes all three major methane production pathways

which include (i) acetoclastic methanogenesis, (ii) hydrogenotrophic methanogenesis and (iii) methyl

compound utilizing pathway.

243

Appendix C: Flow-on downstream effects of in-sewer Fe-salt dosing on bioreactor performance

The differences observed in the key SBR effluent quality parameters between the experimental (SBR-

E) and control (SBR-C) systems are presented in Figure C1 and Figure C2. Other than the positive

impacts of in-sewer Fe-salt dosing on the settleability and dewaterability of activated sludge, Fe-

dosed experimental system exhibited a decreased phosphate concentration (mg.P.L-1) (by 41.2±6.3%)

in bioreactor effluent than control system. Importantly, the biological nitrogen removal performance

of Fe-dosed bioreactor remained unaffected as evidenced by the similar ammonium and nitrate

concentrations observed in SBR effluent of both experimental and control systems.

Figure C1. Concentration-time profiles of different parameters in SBR effluent of both experimental

(SBR-E) and control (SBR-C) systems: (a) phosphate; (b) ammonium; (c) nitrate; (d) sulfate; (e) TSS;

(f) tCOD. Phase I represents establishment of stable and comparable baseline conditions between the

two systems. The vertical, dotted line marks the start of in-sewer FeCl3-dosing (i.e. commencement

of experimental Phase II).

244

Figure C2. Differences in the key SBR effluent quality parameters of both experimental (SBR-E)

and control (SBR-C) systems during experimental Phase II (i.e. after initiation of in-sewer FeCl3-

dosing at 10 mg.Fe.L-1): (a) phosphate; (b) ammonium; (c) nitrate; (d) sulfate; (e) pH.

Likewise, average sulfate concentrations in the two SBR effluents were 19.5±1.1 and 20.1±1.2

mg.S.L-1, respectively, for the control and experimental reactors. The difference was statistically

insignificant despite the dissolved sulfide concentration in the wastewater entering the experimental

SBR being lower than that in the control SBR. The average sulfide concentration in sewer effluent in

the experimental system was 4.3± 0.4 mg.S.L-1, as compared to 8.2 ± 0.4 mg.S.L-1 in the control

system. The mean difference was determined to be 3.9 ± 0.4 mg.S.L-1, which is statistically significant

(p < 0.05). This represents a relative decrease of 47.9 ± 4.1%.

245

Appendix D: An illustrative example of determination of TTQ and relative sludge network strength of an iron-conditioned activated sludge

(SBR-E)

Table D1. Determination of TTQ and relative sludge network strength of an iron-conditioned activated sludge (SBR-E)

Time

(s)

Torque

(mN·m)

(SBR-E1)

TTQ

(J.s)

2πN

(where N=3000)

total work energy,

Wt=2πN*(TTQ)

(J)

the unit work energy,

Wu=(2πN*TTQ/V)

(J/cm3), where

V=sample volume used

solid

content

of

sample

(kg/m3)

Area under

the

rheogram

upto certain

shear rate

(kg/ms3 or

Pa/s)

Shear rate

(s-1)

Relative sludge network

strength or total energy

dissipation per unit of dry

solids (DS) (J/kg DS),

Etd=2At/X, where X=solids

content of sample (kg/m3)

0.5 8.23E-06 8.23E-06 18840 1.55E-01 3.10E-03 3.84 2.34E+01 298 922.0

1.5 0.00011156 2.06E-05 18840 3.88E-01 7.75E-03

2.5 0.00041312 0.0002995 18840 5.64E+00 1.13E-01

3.5 0.00047484 1.75E-03 18840 3.29E+01 6.58E-01

4.5 0.00071038 0.0038822 18840 7.31E+01 1.46E+00

5.5 0.00049527 7.79E-03 18840 1.47E+02 2.93E+00

6.5 0.00054867 0.0110085 18840 2.07E+02 4.15E+00

7.5 0.00060848 1.51E-02 18840 2.85E+02 5.70E+00

8.5 0.00020586 0.0202956 18840 3.82E+02 7.65E+00

9.5 0.0011255 2.23E-02 18840 4.19E+02 8.38E+00

10.5 0.0010004 0.034069 18840 6.42E+02 1.28E+01

11.5 0.00030227 4.56E-02 18840 8.59E+02 1.72E+01

12.5 0.0011246 0.049352 18840 9.30E+02 1.86E+01

13.5 0.0017065 6.45E-02 18840 1.22E+03 2.43E+01

14.5 0.0026194 0.0892784 18840 1.68E+03 3.36E+01

15.5 0.0024093 1.30E-01 18840 2.45E+03 4.89E+01

16.5 0.0029015 0.1696325 18840 3.20E+03 6.39E+01

17.5 0.0026058 2.20E-01 18840 4.15E+03 8.31E+01

18.5 0.0017998 0.2686161 18840 5.06E+03 1.01E+02

19.5 0.00012165 3.04E-01 18840 5.72E+03 1.14E+02

20.5 0.0031806 0.306206 18840 5.77E+03 1.15E+02

21.5 0.0031961 3.75E-01 18840 7.06E+03 1.41E+02

246

22.5 0.00066682 0.4465011 18840 8.41E+03 1.68E+02

23.5 0.004463 4.62E-01 18840 8.71E+03 1.74E+02

24.5 0.0014026 0.5715149 18840 1.08E+04 2.15E+02

25.5 0.0024404 6.07E-01 18840 1.14E+04 2.29E+02

26.5 0.0059727 0.6719518 18840 1.27E+04 2.53E+02

27.5 0.0033285 8.36E-01 18840 1.58E+04 3.15E+02

28.5 0.00075011 0.9310633 18840 1.75E+04 3.51E+02

29.5 0.00047604 9.53E-01 18840 1.80E+04 3.59E+02

30.5 0.00066049 0.9677108 18840 1.82E+04 3.65E+02

31.5 0.00051971 9.89E-01 18840 1.86E+04 3.72E+02

32.5 0.0012014 1.0054068 18840 1.89E+04 3.79E+02

33.5 0.0040462 1.05E+00 18840 1.97E+04 3.94E+02

34.5 0.0082532 1.1852476 18840 2.23E+04 4.47E+02

35.5 0.0053113 1.48E+00 18840 2.78E+04 5.57E+02

36.5 0.0019358 1.6720986 18840 3.15E+04 6.30E+02

37.5 0.009563 1.74E+00 18840 3.29E+04 6.57E+02

38.5 0.0017416 2.1128666 18840 3.98E+04 7.96E+02

39.5 0.0092595 2.18E+00 18840 4.11E+04 8.22E+02

40.5 0.0050247 2.5566696 18840 4.82E+04 9.63E+02

41.5 0.0029895 2.77E+00 18840 5.21E+04 1.04E+03

42.5 0.0082863 2.8922484 18840 5.45E+04 1.09E+03

43.5 0.010069 3.25E+00 18840 6.13E+04 1.23E+03

44.5 0.0088803 3.7007729 18840 6.97E+04 1.39E+03

45.5 0.0071498 4.10E+00 18840 7.73E+04 1.55E+03

46.5 0.007818 4.4372923 18840 8.36E+04 1.67E+03

47.5 0.010221 4.81E+00 18840 9.06E+04 1.81E+03

48.5 0.010504 5.3043658 18840 9.99E+04 2.00E+03

49.5 0.0069538 5.82E+00 18840 1.10E+05 2.19E+03

50.5 0.0055849 6.1754807 18840 1.16E+05 2.33E+03

51.5 0.0098848 6.46E+00 18840 1.22E+05 2.44E+03

52.5 0.0066734 6.982055 18840 1.32E+05 2.63E+03

53.5 0.0091945 7.34E+00 18840 1.38E+05 2.77E+03

54.5 0.0072014 7.8401822 18840 1.48E+05 2.95E+03

55.5 0.010219 8.24E+00 18840 1.55E+05 3.10E+03

56.5 0.0085943 8.8172334 18840 1.66E+05 3.32E+03

57.5 0.0082833 9.31E+00 18840 1.75E+05 3.51E+03

58.5 0.0094686 9.7959787 18840 1.85E+05 3.69E+03

59.5 0.01024 1.04E+01 18840 1.95E+05 3.90E+03

60.5 0.0096798 10.97888 18840 2.07E+05 4.14E+03

247

61.5 0.010426 1.16E+01 18840 2.18E+05 4.36E+03

62.5 0.0098394 12.225813 18840 2.30E+05 4.61E+03

63.5 0.011171 1.29E+01 18840 2.42E+05 4.84E+03

64.5 0.011258 13.571144 18840 2.56E+05 5.11E+03

65.5 0.01077 1.43E+01 18840 2.70E+05 5.39E+03

66.5 0.0098214 15.024748 18840 2.83E+05 5.66E+03

67.5 0.013604 1.57E+01 18840 2.96E+05 5.91E+03

68.5 0.0094823 16.619567 18840 3.13E+05 6.26E+03

69.5 0.01498 1.73E+01 18840 3.26E+05 6.51E+03

70.5 0.009983 18.334677 18840 3.45E+05 6.91E+03

71.5 0.0099301 1.90E+01 18840 3.59E+05 7.18E+03

72.5 0.016451 19.768394 18840 3.72E+05 7.45E+03

73.5 0.017304 2.10E+01 18840 3.95E+05 7.90E+03

74.5 0.015633 22.26669 18840 4.20E+05 8.39E+03

75.5 0.012166 2.34E+01 18840 4.42E+05 8.83E+03

248

Appendix E: Characterization of Fe- and Al-sludge samples using XRD, ATR-FTIR, SEM-

EDX, and NMR techniques

X-ray diffraction (XRD) analysis was undertaken to study the changes in mineral composition of

sludge samples before- and after dosing into the experimental systems (pilot rising main, glass

reactor) containing sewage. Samples were analyzed immediately after sampling, and then dried in a

vacuum oven (SEMSA OVEN 718) at 60 °C for 12 hr prior to analysis. The analysis was performed

using an XRD diffractometer (Bruker D8 Advance MKII), which used a Cu Kα radiation X-ray source

(wavelength, λ=1.5406 ) and 18 KW intensity. X-rays were generated at 40 kV and 40 mA, over a

2θ range of 10–90° with scanning rate of 2.0° min-1. X-ray diffraction patterns were processed using

Rigaku PDXL2 data processing software (version 2.3.1.0). The mineral composition was identified

using Gade software (version 5) and the PDF-2 crystal structure database.

Scanning Electron Microscopy coupled with Energy Dispersive X-Ray (SEM-EDX) analysis was

carried out at the Centre for Microscopy and Microanalysis, The University of Queensland (UQ). The

surface morphology and elemental composition of the samples were examined by SEM (JEOL JSM-

6610, America), equipped with a detector (Oxford 50mm2 X-Max SDD x-ray) that enabled

simultaneous imaging and elemental analysis at high count rates with 125 eV energy resolutions.

Prior to analysis, the samples were dried in a vacuum oven (SEMSA OVEN 718) at 60 °C for 8 hr

and then carbon-coated twice (Quorum Q150T, UK), using the Three Heavy-Burst mode to obtain

the carbon thickness of 30–40 nm. For EDX analyses, the EDAX software (EDAX, AMETEK Inc.)

was utilized at a frame resolution of 1024×800, with a dwell time of 200 s/frame to collect 16 frames

for each region of interest. The locations for spot analyses were chosen by examining features of the

secondary electron image, and the quantification of each individual EDX spot analysis in Wt% was

done against the standard mineralogical database.

Attentuated Total Reflectance - Fourier Transform Infrared (FTIR) spectroscopy of the solid phase

samples were recorded from 400 to 3400 cm-1 using an ATR-FTIR spectrometer (Nicolet 5700), with

a diamond internal reflection (DATR) module. Spectra were recorded with a 4 cm-1 resolution by

coadding 128 scans. Prior to the analysis, the samples were centrifuged (Beckman Coulter, USA) at

2000 rpm and 251 C for 2 min without air bubbles to prevent the advent of any structural changes.

The particles were then immediately applied to the diamond ATR crystal and the IR spectra were

recorded.

https://www.sciencedirect.com/topics/earth-and-planetary-sciences/diffraction-pattern

249

Solid-State Nuclear Magnetic Resonance (NMR) analyses were undertaken to investigate the possible

underlying mechanism behind phosphate removal when using Al-sludge. Solid-state NMR

spectroscopy is considered a powerful technique to determine short-range structural information (Li

et al., 2013), and hence used herein to gain insight into the underlying mechanism. Solid State NMR

analyses were performed on a Bruker Avance III spectrometer with a 300 MHz magnet (7.41 T)

equipped with a 4.0 mm double air bearing, magic angle spinning (MAS) probe. Prior to analysis, the

samples were centrifuged (Beckman Coulter, USA) at 1,000 rpm and 251 C for 2 min, and vacuum

dried at 60 C for 4 hr. The samples were then loaded into a zirconia rotor with a Kel-F cap and

rotated at 8 kHz. Both 27Al and 31P spectra were recorded using the single pulse routine. For 27Al,

pulse length was 1 s with repetition delay of 1 s. For 31P, a 2 s 90o pulse was used with the relaxation

delay of 20 s. Deconvolution and integration of spectra were performed with PeakFit software.

250

Appendix F: Examination of additional absorbance peaks observed in IR spectra of sample

before and after Fe-sludge dosing

The IR spectra acquired from 400 to 4000 cm-1 for Fe-sludge samples (Figure 61b) before- and after

dosing (Figure 62b), showed the major changes occurred at 800 to 1800 cm-1. Clear changes were

observed in the phosphate band region 800–1200 cm-1 (Scorates, 2001; Tejedor-Tejedor and

Anderson, 1990). The concurrent loss in absorbance at 871 cm-1, along with the strong band seen at

1025 cm-1 (Figure 62b), suggests a decrease in H2PO4- or HPO4

- concentration. This is because the

band at 871 cm-1 is attributed to P-OH in H2PO4- or H3PO4 (Tejedor-Tejedor and Anderson, 1990).

This supports an observed marginal reduction in phosphate (PO4-P) concentrations by 1.0±0.1 mgP/L

(p<0.05) in the experimental sewer line with Fe-sludge dosing (Figure 59c). Accordingly, particular

absorbance bands were observed from 800 to 1200 cm-1 (Figure 62b), corresponding to metal-

orthophosphate complexes (Scorates, 2001; Tejedor-Tejedor and Anderson, 1990). The absorbance

bands appeared in this region can also be assigned to asymmetric stretching vibrations of the bridging

PO2- (O=P–O−) and P–O–P, or asymmetric and symmetric stretching vibrations of PO3

- ions (Daou

et al., 2007; Scorates, 2001).

The main phosphate species present at the experimental pH of 7.0 – 7.5 were likely H2PO4- or HPO4

-

(Figure 59a), while FeOOH was the dominant mineral (Figure 61a, Figure 62a). Phosphate ions can

possibly hinder the reductive dissolution of FeOOH on the Fe-sludge surface (Figure 61a) in the

presence of sulfide via formation of binuclear inner-sphere complexes (Biber et al., 1994). This is

reflected by a decrease in –OH absorbance bands in the range 3000 – 3600 cm-1 and at 1640 cm-1 in

the sample obtained after dosing (Figure 61b). This indicates phosphate species reacting with surface

-OH groups of the Fe-sludge (Daou et al., 2007). The broad vibration bands existing between 3200 –

3600 cm-1 and 1620 – 1640 cm-1 (Figure 61b, Figure 62b) are associated with the stretching and

bending vibration of O-H in water molecules or FerPO4(OH)3r-3 (Arai and Sparks, 2001; Daou et al.,

2007; Duan et al., 2006).

Absorbance peaks at wavelengths 2921 cm−1 and 2853 cm−1 correspond to asymmetric and symmetric

stretching vibration of C-H in organic matter (-CH2, -CH3 groups), respectively (El Samrani et al.,

2004). The peak at 1537 cm-1 in the Fe-sludge sample after dosing can be assigned to asymmetrical

stretching of -C=O in complexed carboxylate (-COOH) groups (Ricca and Severini, 1993). Likewise,

the peak at 1409 cm-1 (before dosing) and 1422 cm-1 (after dosing) can be tentatively assigned to

symmetrical stretching of -C=O in complexed carboxylate (-COOH) groups (El Samrani et al., 2004).

251

This variation, i.e., the weaker absorbance band in the Fe-sludge sample after dosing, can be explained

by deprotonation of –COOH group under normal sewage pH, and subsequent availability for

association with Fe-hydrolysis products (Gu et al., 1995; Stevenson and Goh, 1971). Following the

addition of Fe-sludge to the pilot sewer, the pH decreased marginally, possibly due to iron hydrolysis

(Figure 59a). Consequently, the carboxylate anion R-COO− converts to carboxylic -COOH functional

groups. Carboxyl groups are then less involved in complexation reactions with Fe(III)-hydrolyzed

species, which leads to an enhanced absorption of -COOH groups and weaker bands for complexed

carboxylates, as previously reported (El Samrani et al., 2004).

252

Appendix G: Characteristics and mechanism of phosphate removal when using waterworks Al-

sludge – overview of hydrolysis-adsorption experiment

Methodology

This set of experiments was conducted to examine the pathways governing phosphate (PO43-) removal

when dosing Al-sludge. We anticipated that there could be physicochemical interaction between

aluminium (Al) and phosphate species, i.e. adsorption of phosphate on Al-sludge surface, and surface-

precipitation occurring. Such removal processes could also be influenced by the competitive effect of

humics present in wastewater. This experiment was conducted in two phases: Phase 1) Hydrolysis of

Al-sludge, and Phase 2) Adsorption tests with phosphate addition. The experiment was carried out as

per Yang et al. (2006), with some modifications.

During Phase 1, 3.0 g.L-1 of Al-sludge (moisture content 82.8%) was hydrolyzed in milli-Q water

(initial pH 5.11 ± 0.01) in a 1.1 L borosilicate glass reactor for 4 days (final pH 8.59 ± 0.20). Milli-Q

water was sparged with pure helium gas for 15 min prior to use, and the reactor was maintained air-

tight throughout the experiment using a 3.0 L Cole-Parmer Kynar gas bag, filled with pure helium

gas. The experiment was conducted in duplicate (n=2). During the hydrolysis phase, the reactor was

mixed at 50 rpm using a magnetic stirrer (color squid IKAMAG white) for the first two days. For

the rest of the experiment, the mixing intensity was maintained at 300 rpm.

Following the hydrolysis phase, the adsorption test (Phase 2) was conducted. Phosphate was added

up to 14 mg.P.L-1 to the hydrolysed suspended solution, and phosphate adsorption by the Al-sludge

was then monitored for 4 h. The phosphate stock solution was prepared using anhydrous potassium

dihydrogen phosphate (KH2PO4) (Sigma-Aldrich, 99.0% assay). During both Phases, changes in pH

and anions/humics (including Cl-, SO42-, total organic carbon) were monitored.

Results

Results of the Al-sludge hydrolysis (Phase 1) and adsorption (Phase 2) experiment are shown in

Figure G1. During the hydrolysis phase (Figure G1, left), an increase in pH from 5.12 to 6.92 was

observed, indicating that OH- ions were released into the solution from Al-sludge. Concomitantly,

the concentrations of Cl-, SO42-, and TOC increased from 0 to 3.5, 0.3 and 3.2 mg.L-1, respectively,

as the hydrolysis phase progressed.

253

During the adsorption phase (Figure G1, right), there was a decrease in phosphate concentration from

13.4 to 9.4 mg.P.L-1. Other parameters such as pH, SO42- and TOC increased from 6.64 to 8.39, 0.3

to 0.7, and 3.24 to 10.24 mg.L-1, respectively. However, Cl- concentration remained relatively

constant, i.e. 3.5 mg.L-1. While during the adsorption phase the phosphate concentration showed a

linear trend, the decrease in total aluminium Al(T) concentration was not linear. The Al(T)

concentration initially increased from 12.5 to 28.0 mg.Al.L-1 following phosphate addition, and

finally decreased to 20.0 mg.Al.L-1. The concentrations of soluble aluminium Al(sol.) concentration

during hydrolysis and adsorption phases were in the range of 0.1 - 0.6 mg.Al.L-1 (data not shown here

in Figure G1). This implies that most Al in the Al-sludge is in a stable and immobilized form at the

test pH range 5.12 – 8.39. This suggests that co-precipitation/surface precipitation alone cannot be

the dominant mechanism in P-removal when using Al-sludge. This is because surface precipitation

occurs via interaction between PO43- ions and Al(sol.) ions released from Al-sludge during dissolution

(Ler and Stanforth, 2003).

254

Figure G1. Concentration-time profiles of pH, Cl-, SO42-, TOC, and total aluminium, Al(T), during

hydrolysis and phosphate adsorption experiments

Discussion

As shown in Figure G1, three major processes were observed: (i) an increase in the pH, (ii) release of

anions (Cl-, SO42-) and TOC, and (iii) a decrease in PO4-P with irregular changes in Al(T)

concentrations during the process. The increase in pH from 5.12 to 6.64 upon Al-sludge addition

during the hydrolysis stage (Figure G1), indicates the release of OH- ions into the solution. This

255

suggests that Al-sludge has a net negative surface charge or hydroxylated surface. The XRD spectra

of Al-sludge also indicated that aluminium (Danish Hydraulic Institute)oxides dominated the sludge

surface (Figure 68). These OH- groups on the Al-sludge surface can participate in complexation

reactions with metals ions and other available ligands (Laiti et al., 1996).The increased pH was

accompanied by an increase in Cl-, SO42-, and TOC concentration in solution (Figure G1, hydrolysis

phase), due to dissolution of Al-sludge during hydrolysis.

The results show that Al-sludge possesses active surface functional groups such as OH-, Cl-, SO42-,

and TOC (humics), which can exchange with the available anions/ligands. However, the increased

OH- concentration in solution, as evidenced by the increased pH during hydrolysis phase, could have

a counter-effect on the electrostatic properties of Al-sludge, decreasing its affinity for other anions,

i.e. PO43- in this case (Yang et al., 2006). There can also be strong competition between PO4

3- and

OH- for occupying active surface sites on sludge, with increased pH in solution (Singh et al., 2005).

This means PO43- removal via adsorption processes is pH dependent (Lee et al., 2015), occurring via

ligand exchange between PO43- ions in solution and OH- present on Al-sludge surface (Gon Kim et

al., 2002; Yang et al., 2006). This supports the observation of a pH increase from 6.64 to 8.39 (Figure

G1, adsorption stage), following addition of phosphate stock solution. The pH increase was

accompanied by a decrease in phosphate concentration (Figure G1, adsorption stage). This suggests

that ligand exchange occurred between PO43- in solution and OH-, Cl- and SO4

2- on Al-sludge surface,

and hence, these ions were released into solution, involving the displacement of surface OH- groups

with PO43- ions. Further, the occurrence of surface precipitation is also likely as evidenced by the

presence of low Al(sol.) concentration (0.6 mg.Al.L-1) and a decrease in Al(T) concentration (albeit

observed only after 3 hrs). This can be explained by the reactions shown in Eqs. (E1)-(E3) (Lee et al.,

2015; Ma et al., 2011; Makris et al., 2004a), noting that the dominant phosphate species are H2PO4-

or HPO4- within the pH range in this study (Almasri et al., 2019).

Al2O3 + 3H2O 2Al(OH)3 (E1)

Al(OH)3 + H2PO4- AlPO4 + 2H2O + OH- (E2)

Al(OH)3 + HPO4- AlPO4 + H2O + 2OH- (E3)

It is likely that the Al-phosphate complexes formed during the P-adsorption process were due to

ligand-exchange rather than precipitation of Al(OH)3 or AlPO4. However, phosphate can adsorb onto

256

Al(OH)3, forming monodentate/bidentate or binuclear complexes (Guan et al., 2005b; Guan, 2005;

Rajan, 1975).

As observed in Figure G1 (adsorption stage), there was release of TOC (organic matter, humics) into

solution. The concentration of TOC averaged 8.71.6 mg.L-1, which is insignificant pertinent to the

effluent quality. This observation further highlights that humics/organic matter can also contribute to

PO43- removal by supplying active sites for PO4

3- adsorption. Humics are a major component of Al-

sludge (62% of organic matter content in Al-sludge used herein), and hence humics can compete with

PO43- ions in achieving the surface active sites for adsorption (Liu et al., 2016d; Yang et al., 2006).

Previous studies showed a positive correlation between humics release from Al-sludge and phosphate

removal from solution (Liu et al., 2016d; Yang et al., 2006).

257

Appendix H: Comparative overview of previous studies on application of waterworks Al-/Fe-

sludge in treating wastewater with the present study

Table H1. Comparison of the previous studies conducted to treat wastewater on applying the

waterworks-derived Fe- or Al-sludge with current study

Waterworks

(or WTP)

sludge

Source of

waterworks

sludge

Application

(e.g. lab-, pilot-,

or full-scale)

Significance References

Fe-sludge Water

treatment

plant (WTP)

Bench-scale lab

experiment

Effective phosphate removal

from aqueous solution

Piaskowski

(2013)

Fe-sludge WTP Batch and column

experiments

Presented ferric sludge as the

effective adsorbent for

phosphate removal from

aqueous solution

Song et al.

(2011)

Aluminium-

laden (or

alum) sludge

WTP Jar tests using real

sewage, sourced

from inlet of

primary clarifier

Enhanced removal of

particulate pollutants (e.g.

suspended solids, COD)

removal

Guan et al.

(2005a)

Alum sludge WTP Batch and

continuous-flow

experiments


from synthetic wastewater

Razali et al.

(2007)

Al- and Fe-

laden

waterworks

sludge

WTP Lab-scale CSTR

experiments


from real wastewater

Bai et al.

(2014)

Fe-sludge WTP Continuously

operated lab-scale

rising main sewer

system, with

intermittent

dosing of

domestic sewage

Relatively more effective in

sulfide removal from real

domestic sewage, but with

limited contribution on

phosphate and soluble COD

removal

Sun et al.

(2015)

Fe-sludge,

Al-sludge

WTP Bench-scale

experiments

Relatively Fe-sludge more

effective than Al-sludge in


aqueous solution

Edwards et al.

(1997)

Fe-sludge WTP Bench-scale

experiments

Effective in phosphate

removal from aqueous

solution

Leader et al.

(2008)

Al-sludge WTP Bench-scale

sorption-

desorption study

Effective in phosphate

removal from aqueous

solution

Ippolito et al.

(2003)

Al-sludge WTP Batch

experiments

Effective phosphorus removal


Babatunde

and Zhao

(2010)

258

Al-sludge WTP Batch adsorption

tests



Zhao et al.

(2007)

Al-sludge WTP Phosphorus

adsorption tests

using lab-based

small-scale

continuous flow

system


from wastewater

Huang and

Chiswell

(2000)

Al-sludge WTP Bench-scale

experiments

Effective phosphorus,

turbidity, and COD removal

from synthetic and municipal

wastewater

Georgantas

and

Grigoropoulou

(2005)

Al-sludge WTP Batch sorption

test



Kim et al.

(2002)

Al-sludge WTP Batch

experiments

Effective adsorbent for


aqueous solution

Yang et al.

(2006)

Fe-sludge Desalination

WTP

Direct reuse of

Fe- and Al-sludge

into pilot rising

main sewers of a

dimension (300m

long and 100 mm

in diameter)

comparable to a

small real sewer

First systematic and

comprehensive study of the

effects of Fe- and Al-sludge in

the treatment unit (i.e. sewer)

receiving the dosing under

more realistic in-sewer

condition;

Relatively Fe-sludge more

effective in removing

dissolved sulfides wherein Al-

sludge more effective for

phosphate removal in sewer;

Underlying mechanisms

associated with removal of

sulfides with Fe-sludge and

phosphate with Al-sludge also

revealed

This study

Al-sludge WTP

thesis title - uq espace

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