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PREVENTION AND MONITORING OF BIOFILM FORMATION IN

DRINKING WATER DISTRIBUTION SYSTEMS

By

FAHIMEH BIMAKR

BSc

This thesis is presented for the degree of

Master of Science - Research

of

The University of Western Australia

School of Pathology and Laboratory Medicine

2015

DECLARATION OF THESIS CONTAINING PUBLISHED WORK AND/OR WORK PREPARED

FOR PUBLICATION

This thesis contains published work and/or work prepared for publication, some of

which has been co-authored. The bibliographical details of the work and where it

appears in the thesis are outlined below.

1. BIMAKR, F., HTWE, T. Z., CHENG, K. Y., GINIGE, M. P., PUZON, G. J.,

SUTTON, D. C., WATKIN, E. L. J., BENNET-CHAMBERS, M. & KAKSONEN,

A. H. 2013. Electrochemical monitoring of biofilm formation on graphite

electrodes in dam water, and detachment following chlorine treatment.

Ozwater 13th International Water Conference. Perth, Australia. (This

work was presented as a poster and is cited in Chapter 3).

2. BIMAKR, F., GINIGE, M. P., HTWE, T. Z., KAKSONEN, A. H., SUTTON, D. C.,

PUZON, G. J., WATKIN, E. L. J. & CHENG, K. Y. The use of electrochemical

methods for biofilm monitoring in drinking water systems.

Bioelectrochemistry, (Submitted). This work largely forms Chapter 3 of

the thesis.

3. BIMAKR, F., GINIGE, M. P., KAKSONEN, A. H., SUTTON, D. C., PUZON, G.

J. & CHENG, K. Y. Assessing graphite and stainless steel electrodes for

biofilm monitoring in chlorinated drinking water systems. Biosensors

and Bioelectronics (Submitted). This work largely forms Chapter 4 of the

thesis.

Statement of Candidate Contribution

This thesis has been submitted in fulfillment of the requirements for Masters in the

Bachelor of Science (Biology) at the University of Western Australia. The work

presented in this study was completed by candidate except for the item below. As the

primary author for the papers mentioned above, the candidate completed all lab work,

data analysis and wrote the manuscript following the suggestions and comments from

the co-authors. With respect to the research presented in chapter 3, Joshua

Ravensdale helped with scanning electron microscopy (SEM) sample preparation,

Elaine Miller from Curtin Electron Microscope Facility provided technical help in

acquiring the SEM images, and Dr Marilyn Bennet-Chambers (Curtin University)

provided valuable comments.

Fahimeh Bimakr and Thet Zaw Htwe, The use of electrochemical methods for

biofilm monitoring in drinking water systems

Student Declaration:

Fahimeh Bimakr

Print Name Signature

19.12.2014

Date

Supervisors Declaration:

Assoc Prof David Sutton Print Name

Signature

19.12.2014 Date

Dr Anna Kaksonen Print Name Signature

19.12.2014 Date

Dr Maneesha Ginige Print Name

Signature

19.12.2014 Date

Dr Geoffrey Puzon Print Name Signature

19.12.2014 Date

Dr Ka Yu Cheng Print Name Signature

19.12.2014 Date

i

Abstract

Biofilm formation in drinking water distribution systems (DWDSs) causes detrimental

impacts on water quality and infrastructure. Biofilms can also act as a reservoir for

pathogens, and are thus of public health concern. To discourage biofilm growth in

DWDSs, antimicrobial agents (disinfectants) including chlorine, chloramines and ozone

are used. However, these chemicals produce harmful disinfection by-products, many

of which are toxic and carcinogenic, and hence their formation should be minimised.

The challenge to maintain appropriate disinfection and to avoid unwanted effects of

biofilm formation in DWDSs requires the development of new technologies for

efficient disinfection and microbial control.

Biofilm formation is affected by the type of pipe wall material, especially its surface

characteristics, including roughness, surface energy and biological affinity. Pipe

materials may also release substances that enhance or inhibit biofilm formation, and

so influence the presence and persistence of microbial pathogens. A number of

nanomaterials having antimicrobial properties have been proposed for use in water

treatment. Moreover, microstructured surfaces and other surface coatings have also

been reported to inhibit biofilm formation. In this study a number of polymers of

different hydrophobicity including high density polyethylene (HDPE),

polytetrafluoroethylene (PTFE) and nylon, with and without embedded copper, as well

as a nanomaterial (carbon nanotubes) and marine paint (Hempel X3) were tested for

their effects on biofilm formation in a laboratory scale pipe rig containing water from a

water supply reservoir (Mundaring Weir, Perth, Western Australia), and compared

with the traditional pipe materials stainless steel and concrete. Microbial growth on

the tested materials was measured by counting DAPI-stained cells using epifluorscence

microscopy, flow cytometry, heterotrophic plate agar, and an ATP assay for measuring

cellular activity. Biofouling on all tested materials was detected using all four methods

(ATP assay, epifluorescence microscopy, flow cytometry and colony counting) as

rapidly as 1 h following installation of the material into the laboratory pipe rig. The

results showed that none of the tested materials or coatings showed superior

performance in preventing biofilm formation relative to stainless steel or concrete.

ii

On-line electrochemical monitoring with electrodes deployed in the water distribution

pipes could potentially provide an early warning of biofilm formation and enable

optimisation of disinfectant dosing in DWDSs. Electrochemical methods have recently

received attention for their potential in monitoring biofilm formation, largely because

they are convenient with respect to installation and operation. In this study, two

electrochemical methods (open circuit potential, OCP; and electrochemical impedance

spectroscopy, EIS) were investigated as a means of real-time monitoring of biofilm

formation in drinking water, and the impacts of chlorination (4.5 mg Cl2 L–1) on both

the biofilm and electrochemical signals were assessed.

Initially, the suitability of using OCP and EIS for biofilm monitoring was evaluated using

graphite electrodes as the surface for both biofilm formation and electrochemical

sensing. The specific objective was to determine if a linear relationship existed

between the biofilm formation and the electrochemical signals. During the period of

biofilm formation (approximately one week), impedance of the electrodes was

measured over a large range of frequencies (100 kHz to 10 mHz), EIS data were

collected, and equivalent circuit analysis was carried out to determine the impedance

and capacitance. The adhesion of the microorganisms caused an increase in

capacitance and a decrease in imaginary impedance at low frequencies (20 mHz).

Capacitance showed the best linearity with change in the density of microorganisms on

the electrode surface (R2 = 0.977). Chlorine was found to be effective in removing

biofilm from the electrodes. EIS parameters returned to baseline levels following

chlorine treatment, concurrent with biofilm removal. The results suggest that EIS is

suitable for real-time monitoring of biofilm formation, and for optimising chlorine

dosing in DWDSs.

The use of a sensitive electrode material is important for biofilm sensing. In the second

part of the biofilm sensing study the electrochemical behaviour of graphite and

stainless steel electrodes was compared and evaluated in terms of sensitivity for

detection of biofilm in a drinking water environment. The electrochemical signals were

exclusively dependent on the extent of biofouling (cell numbers) at the electrode. Both

graphite and stainless steel were found to be suitable materials for the electrochemical

measurements. The EIS measurements showed that capacitance is the most suitable

parameter to indicate biofouling of both electrodes, as capacitance was linearly

iii

correlated to the number of cells attached to the electrode surface (R2 = 0.9).

However, stainless steel was a factor of 10 more sensitive in detecting biofouling than

graphite, based on the capacitance measurements. Chlorination effectively removed

biofilm attached to both the graphite and stainless steel electrodes, but chlorine itself

did not affect the capacitance signal of the electrodes. The results indicate that the

measurement of capacitance based on EIS could be the basis for developing a biofilm

sensor that could be applicable in DWDSs where chlorination of water is commonly

used. Such a biofilm sensor may have worldwide application.

iv

Acknowledgments

First of all, I would like to express my gratitude to my supervisor Assoc/Prof David

Sutton from the University of Western Australia for giving me the opportunity to study

under his supervision. His stimulating suggestions and encouragement have helped me

throughout the research and writing of this thesis.

I am deeply indebted to my supervisor Dr. Anna Kaksonen from CSIRO, for her vast

knowledge and skill in many areas, and her assistance in writing scientific reports and

thesis. Her expertise, understanding, and most importantly patience added

considerably to my research experience. I would like to thank my other supervisors

from CSIRO, Dr Maneesha Ginige, Dr Geoffrey Puzon and Dr Ka Yu Cheng for the

assistance they provided on the research project, and also for their helpful advice in

career and life in general. With their enthusiasm, their inspiration, and their great

efforts to explain things clearly and simply, they helped to make a complicated

research question fun for me. Throughout my thesis-writing period, they provided

encouragement, sound advice, good teaching, good company and lots of good ideas.

This research was supported by funding from the CSIRO Water for a Healthy Country

Flagship. I would like to thank CSIRO for providing the funding for this project and also

for giving me enjoyable environment to conduct my research. I would like also to thank

my friend Penny Wong for taking time out from her busy schedule to serve as my

external reader, for helping me to get through the difficult times, and for all the

emotional support.

I am indebted to my dear parents for their encouragement through the years. Finally, I

wish to thank so much to my dearest husband Dr Mehran Rahmanian and my daughter

Anahita Rahmanian, who are always the biggest joy in my life. They have succeeded to

balance my life so that it has not been overwhelmed by science. I feel most fortunate

to have such a great family. Special thanks for the patience during the last squeeze of

this thesis.

v

Table of Content

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

Acknowledgments ............................................................................................................ iv

Table of Content ................................................................................................................ v

List of Figures .................................................................................................................... x

List of Tables ................................................................................................................... xiv

1. Introduction and scope of research .......................................................................... 1

1.1. Biofilms in drinking water distribution systems ............................................... 1

1.2. What is a biofilm? ............................................................................................. 2

1.3. Biofilm formation .............................................................................................. 3

1.4. Biofilm and health risks ..................................................................................... 4

1.5. Disinfection ....................................................................................................... 4

1.6. Factors affecting biofilm formation .................................................................. 5

1.6.1. Nutrient availability ..................................................................................... 5

1.6.2. Temperature ............................................................................................... 6

1.6.3. Pipe materials .............................................................................................. 6

1.6.4. Ineffective disinfection ................................................................................ 7

1.7. Microtechnology and nanotechnology in biofilm control ................................ 7

1.8. On-line biofilm monitoring.............................................................................. 10

1.8.1. Differential turbidity measurement (DTM) ............................................... 11

1.8.2. Microscopy techniques ............................................................................. 11

1.8.3. Bioluminescence ....................................................................................... 11

1.8.4. Piezoelectric techniques ........................................................................... 12

1.8.5. Electrochemical techniques ...................................................................... 12

1.8.5.1. Open circuit potential (OCP) method ................................................ 13

1.8.5.2. Electrochemical noise (EN) ................................................................ 13

vi

1.8.5.3. Electrochemical Impedance Spectroscopy (EIS) ................................ 14

1.9. Methods for examining adhered bacteria and biofilm ................................... 19

1.9.1. Heterotrophic plate count (HPC) .............................................................. 19

1.9.2. Light microscopy ....................................................................................... 19

1.9.3. Scanning electron microscopy (SEM) ........................................................ 19

1.9.4. Epifluorescence microscopy ..................................................................... 20

1.9.5. Biochemical markers ................................................................................. 20

1.9.6. Flow cytometry (FCM) ............................................................................... 20

1.10. Aim and scope of the thesis ............................................................................ 21

2. The effect of pipe materials on biofilm formation ................................................. 22

2.1. Introduction .................................................................................................... 22

2.2. Materials and methods ................................................................................... 23

2.2.1. Production of nanomaterials and other surfaces for assessing biofilm

formation ................................................................................................................ 23

2.2.2. Coupons .................................................................................................... 25

2.2.3. Construction and operation of the pipe rig .............................................. 27

2.2.4. Detachment of cells from coupons ........................................................... 29

2.2.5. Quantification of microbial activity and cell numbers .............................. 29

2.2.5.1. Adenosine triphosphate (ATP) assay ................................................. 30

2.2.5.2. Viable plate count .............................................................................. 30

2.2.5.3. Epifluorescence microscopy .............................................................. 31

2.2.5.4. Flow cytometry .................................................................................. 32

2.3. Results ............................................................................................................. 34

2.3.1. ATP assay ................................................................................................... 34

2.3.2. Plate count ................................................................................................ 38

2.3.3. Flow cytometry and epifluorescence microscopy .................................... 42

2.4. Discussion ........................................................................................................ 49

vii

2.5. Conclusions ..................................................................................................... 50

3. The use of electrochemical methods for biofilm monitoring in drinking water

systems ............................................................................................................................ 52

3.1. Introduction .................................................................................................... 52

3.2. Materials and Methods ................................................................................... 54

3.2.1. Electrode preparation ............................................................................... 54

3.2.2. Incubation experiments ............................................................................ 54

3.2.2.1. Biofilm formation and its effect on electrochemical properties ....... 54

3.2.2.2. Effect of enrichment medium on electrochemical properties .......... 55

3.2.3. Chlorine treatment.................................................................................... 56

3.2.3.1. Effect of chlorine treatment on biofilm and electrochemical

properties 56

3.2.3.2. Abiotic effect of chlorine on electrochemical properties .................. 56

3.2.4. Analytical methods .................................................................................... 57

3.2.4.1. Electrochemical measurements ........................................................ 57

3.2.4.2. Water analysis .................................................................................... 59

3.2.4.3. Flow cytometer cell counts ................................................................ 60

3.2.4.4. Scanning electron microscopy ........................................................... 60

3.3. Results and discussion..................................................................................... 61

3.3.1. Effects of microbial biofilms on electrochemical signals .......................... 61

3.3.1.1. OCP ..................................................................................................... 61

3.3.1.2. EIS ....................................................................................................... 63

3.3.1.2.1. Impedance measurement ............................................................ 63

3.3.1.2.2. Parameters derived from the equivalent circuit model .............. 63

3.3.1.2.3. EIS spectrum ................................................................................. 66

3.3.1.2.4. Contribution of cells in a biofilm to the electrochemical signals . 67

3.3.2. Chlorine as a disinfectant .......................................................................... 69

viii

3.3.2.1. Impact of chlorine on biofilm and the electrochemical signals......... 69

3.3.2.2. Effect of chlorine on the electrochemical signals .............................. 71

3.3.3. Capacitance was the most suitable electrochemical parameter for

monitoring biofilms ................................................................................................. 74

3.4. Conclusions ..................................................................................................... 74

4. Assessing graphite and stainless steel electrodes for biofilm monitoring in

chlorinated drinking water systems ................................................................................ 75

4.1. Introduction .................................................................................................... 75

4.2. Materials and methods ................................................................................... 77

4.2.1. Preparation of sensor electrodes .............................................................. 77

4.2.2. Biofilm development on electrode surfaces, and analytical procedures . 77

4.2.3. Measurement of electrode electrochemical properties .......................... 78

4.2.4. Microbiological analysis ............................................................................ 80

4.2.4.1. ATP analysis ....................................................................................... 80

4.2.4.2. Flow cytometer cell counts ................................................................ 81

4.2.5. Chlorine treatment.................................................................................... 81

4.2.6. Abiotic incubation to investigate the effect of the medium on

electrochemical parameters ................................................................................... 82

4.3. Results and discussion..................................................................................... 83

4.3.1. Biofilm formation and its effect on electrochemical properties of graphite

and stainless steel electrodes ................................................................................. 83

4.3.2. Changes in OCP ......................................................................................... 84

4.3.3. EIS spectra and changes in capacitance and charge transfer resistance .. 85

4.3.4. Changes in impedance .............................................................................. 88

4.4. Capacitance was the most suitable parameter for detecting biofilm formation

on graphite and stainless steel electrodes ................................................................. 88

4.4.1. Stainless steel was more sensitive in detecting biofilm formation than

graphite. .................................................................................................................. 91

ix

4.5. Changes in electrode capacitance were biofilm-dependant .......................... 92

4.5.1. Effect of sterile incubation medium on capacitance ................................ 92

4.5.2. Impact of a chlorine residual on capacitance ........................................... 93

4.6. Conclusions ..................................................................................................... 95

5. Conclusions and future recommendations ............................................................. 97

References ..................................................................................................................... 100

x

List of Figures

Figure 1.1. The stages of biofilm formation (adapted from Stoodley et al., 2002). ......... 3

Figure 2.1. Carbon nanotube (CNT) with spikes approximately 2 μm apart. The rigidity

of the CNTs and their close spacing enables them to puncture the bacterial cell

wall. .......................................................................................................................... 25

Figure 2.2. Various material surfaces tested in the pipe rig. .......................................... 26

Figure 2.3. Coupons attached to plastic bolts. Materials left to right: N 192, nylon and

concrete. .................................................................................................................. 26

Figure 2.4. Pipe rig used for laboratory experiments on biofilm formation on coupons.

................................................................................................................................. 28

Figure 2.5. Coupons inserted in the pipe rig: copper embedded nylon (left) and

concrete (right). ....................................................................................................... 28

Figure 2.6. Epifluorescence microscopy image of a sample from the pipe rig. Microbial

cells were stained using DAPI. ................................................................................. 32

Figure 2.7. Flow cytometry of a sample from the pipe rig. The sample was stained with

SYTO9 and analysed using flow cytometry. FL1 denotes green fluorescence signals

(520 nm) and FL3 denotes red fluorescence signals (> 670 nm). Electronic gates (- -

-) were used to distinguish microbial cells from background. ............................... 33

Figure 2.8. Adenosine triphosphate (ATP) concentrations in the biofilms that formed

on concrete, stainless steel, nylon and Cu-embedded nylon (N 71: 71 g Cu m–2; N

192: 192 g Cu m–2). .................................................................................................. 34


on concrete, stainless steel, high density polyethylene (HDPE) and Cu-embedded

HDPE (HDPE 85: 85 g Cu m–2; HDPE 238: 238 g Cu m–2). ......................................... 35


on concrete, stainless steel, polytetrafluoroethylene (PTFE) and Cu-embedded

PTFE (PTFE 64: 64 g Cu m–2; PTFE 143: 143 g Cu m–2). ............................................ 36


on concrete, stainless steel, carbon nanotube (CNT) and marine paint. ................ 37

Figure 2.12. Viable aerobic heterotrophic cell counts for biofilms that formed on

concrete, stainless steel, nylon and Cu-embedded (N 71: 71 g Cu m–2; N 192: 192 g

Cu m–2). .................................................................................................................... 38

xi


concrete, stainless steel, high density polyethylene (HDPE), and Cu-embedded

HDPE (HDPE 85: 85 g Cu m–2; HDPE 238: 238 g Cu m–2). ......................................... 39


concrete, stainless steel, polytetrafluoroethylene (PTFE) and Cu-embedded PTFE

(PTFE 64: 64 g Cu m–2; PTFE 143: 143 g Cu m–2). ..................................................... 40


concrete, stainless steel, carbon nanotube (CNT) and marine paint. ..................... 41

Figure 2.16. Total cell numbers in biofilms formed on concrete, stainless steel, nylon

and Cu embedded nylon (N 71: 71 g Cu m–2; N 192: 192 g Cu m–2), determined by

flow cytometry. ........................................................................................................ 43


and Cu-embedded nylon (N 71: 71 g Cu m–2; N 192: 192 g Cu m–2), determined by

epifluorescence microscopy. ................................................................................... 43

Figure 2.18. Total cell numbers in the biofilms that formed on concrete, stainless steel,

high density polyethylene (HDPE) and Cu-embedded HDPE (HDPE 85: 85 g Cu m–2;

HDPE 238: 238 g Cu m–2), determined by flow cytometry. ..................................... 44


and polytetrafluoroethylene (PTFE) and Cu-embedded PTFE (PTFE 64: 64 g Cu m–2;

PTFE 143: 143 g Cu m–2), determined by flow cytometry. ...................................... 45


carbon nanotube (CNT) and marine paint, determined by flow cytometry. .......... 46

Figure 2.21. Total cell numbers in the bulk water, determined by flow cytometry. ...... 48

Figure 2.22. Total cell numbers in the bulk water, determined by epifluorescence

microscopy. .............................................................................................................. 48

Figure 3.1. Schematic diagram of the electrochemical cell used for biofilm monitoring

on graphite electrodes. WE = working electrode (graphite), RE = reference

electrode (Ag/AgCl), CE = counter electrode (platinum wire). ................................ 58

Figure 3.2. Randles equivalent circuit model. Rs represents the solution resistance, Rct

represents the charge-transfer resistance, C refers to capacitance and W is the

Warburg element. .................................................................................................... 59

xii

Figure 3.3. Changes of OCP (A) and EIS parameters (imaginary impedance: B; real

impedance: C; and capacitance: D) during biofilm growth (E) on graphite

electrodes. ............................................................................................................... 62

Figure 3.4. The electrochemical impedance spectra of the graphite electrodes over a

frequency range of 100 kHz to 10 mHz at various time points; the Nyquist plot

shows the relationship between the real impedance (Zre) and the imaginary

impedance (Zim). Day 0 shows no biofilm on electrode; Days 1 to 8 represent

colonisation of biofilm on electrode and the impact after chlorination is shown on

day 9. ........................................................................................................................ 67

Figure 3.5 Changes in OCP (A), EIS parameters (imaginary impedance: B; real

impedance: C; capacitance: D; and charge transfer resistance: E) at 20 mHz, and

cell density (F) on a graphite electrode in the abiotic and biotic systems. ............. 68

Figure 3.6. Effect of chlorination on the OCP (A) and EIS parameters (imaginary

impedance: B; real impedance: C; and capacitance: D) on the graphite electrodes

during the biofilm growth experiment. The dashed vertical lines indicate

application of chlorine (4 mg L–1) for 24 h. The impedance data were obtained at a

frequency of 20 mHz. ............................................................................................... 70

Figure 3.7. Effect of chlorine treatment on biofilm cell numbers. (A) Cell density at day

0, day 8 before chlorination, and day 9 after chlorination. Scanning electron

microscopic images at (B) day 0, (C) day 8, and (D) day 9. ...................................... 71

Figure 3.8. Changes of OCP (A), EIS parameters (imaginary impedance: B; real

impedance: C; and capacitance: D; at 20 mHz) with or without biofilm in abiotic

and biotic systems. Changes of cell density (E) and total chlorine concentration (F)

of graphite electrode with or without biofilm during the chlorination. ................. 73

Figure 4.1. Schematic diagram of the incubation reactor and electrochemical

measurement system (not to scale). WE = working electrode (graphite and

stainless steel), RE = reference electrode (Ag/AgCl), CE = counter electrode

(platinum wire). ....................................................................................................... 78

Figure 4.2. Equivalent circuit for describing microbial attachment to and detachment

from the graphite and stainless steel electrodes. Rs = solution resistance, Rct =

charge-transfer resistance, C = capacitance and W = Warburg impedance. .......... 80

Figure 4.3. Changes in biological (A and B) and electrochemical parameters (C to G) for

the graphite and stainless steel working electrodes during the incubation

xiii

experiment. Vertical dotted lines indicate chlorination events on days 8 and 15

(approximately 4.4 mg Cl2 L–1). The imaginary and real impedances were recorded

at an EIS frequency of 20 mHz. ................................................................................ 84

Figure 4.4. The electrochemical impedance spectra of the graphite and stainless steel

electrodes over a frequency range of 100 kHz to 10 mHz at various time points;

the Nyquist plot shows the relationship between the real impedance (Zre) and the

imaginary impedance (Zim). Day 0 represents no biofilm on the electrode; Days 1

to 8 represent colonisation of biofilm on the electrode, and the impact after

chlorination is shown on day 9. ............................................................................... 86

Figure 4.5. Correlation between various electrochemical parameters and cell density

for the graphite or stainless steel electrodes. The R2 values are correlation

coefficients for the respective linear regression trend lines (the bold lines and

values are for the stainless steel electrodes). ......................................................... 90

Figure 4.6. Relationship between the absolute capacitance (A and B) and change in

capacitance (%) (C and D) with cell density on the graphite and stainless steel

electrodes. ............................................................................................................... 92

Figure 4.7. Abiotic effect of the incubation medium on the capacitance of the graphite

and stainless steel electrodes. The dam water medium was amended with 2 g L–1

yeast extract. ........................................................................................................... 93

Figure 4.8. Abiotic effect of chlorination on the capacitance of the graphite and

stainless steel electrodes. Chlorinated fresh dam water was used as the medium.

No yeast extract was included. ................................................................................ 95

xiv

List of Tables

Table 1.1. A summary of the effects of biofilm formation on EIS parameters in different

EIS experiments. ...................................................................................................... 17

Table 2.1. Summary of nanomaterial, polymers, coating and control materials used in

laboratory-scale pipe rig experiments. .................................................................... 24

Table 3.1. Fitting values of the equivalent circuit model components during biofilm

formation on the graphite electrodes, and following chlorine treatment. ............ 65

Table 3.2. Percentage change in electrochemical parameters at day 8 relative to day 0,

and the relationship between cell density and electrochemical parameters. ........ 65

1

1. Introduction and scope of research

1.1. Biofilms in drinking water distribution systems

Microbial growth in drinking water distribution systems (DWDSs) is a major concern for

consumers as well as for water utilities (AlAbbas et al., 2013). According to the World

Health Organization, potable water should be hygienic and free from any

microorganisms that might be a health risk to the human population (Mittelman et al.,

1992). A major challenge is that the treated water must pass through many kilometres

of pipes before it reaches taps, and the walls of the pipes in the distribution system

provide ideal surfaces for microbial colonization. Studies of DWDSs have shown that

biofilms form the major part of the biomass in pipes, affect the water quality and

increase the cost of maintenance of the distribution networks (Momba et al., 2000). In

DWDSs more than 95% of the biomass is located on the pipe walls because of the large

surface area it provides, and less than 5% is in the water phase (Wingender &

Flemming, 2004). Bacteria can enter distribution systems if the water treatment is

insufficient or poorly operated (e.g. filter breakthrough or ineffective primary

disinfection), and by contamination from cross connections, back flows, and leaking

pipes, joints and valves (Vaerewijck et al., 2005).

Biofilms are more resistant to disinfection than planktonic microorganisms (Yu et al.,

1993), and can act as a reservoir of pathogenic microorganisms able to cause

infectious diseases (Park et al., 2001). The occurrence of such microorganisms in the

water distribution systems can threaten the health of water consumers. Biofilms can

also enhance biocorrosion of metallic pipes through microbially-influenced corrosion

(Lechevallier et al., 1993), and can change the water quality by affecting odour and

flavour (Percival & Walker, 1999). Biofilms are also responsible for reducing dissolved

oxygen and the loss of disinfectant residuals (Momba et al., 2003).

Important factors determining biofilm growth in pipes are the presence and

concentration of nutrients including carbon, nitrogen or phosphorous, and a reduction

in the concentration of disinfectants along the distribution system (Zhou et al., 2009).

Other factors affecting the formation of biofilms include temperature, corrosion

2

products that act as microbial nutrients, and the pipe wall materials (Momba et al.,

2000).

Disinfectants or biocides are chemicals used in drinking water networks to control the

undesirable effects of biofilms (Codony et al., 2005). Commonly used disinfectants in

DWDSs include free chlorine, chloramines and ozone. Such chemicals, when overdosed

to the DWDS, can react with various natural water constituents and produce harmful

disinfection by-products (DBPs) (Ferreira et al., 2013).

The challenge to maintain appropriate disinfection and to avoid unwanted effects of

biofilm growth in water distribution networks calls for new technologies for efficient

disinfection and microbial control. Hence, the overall aim of this thesis was to

investigate new ways to monitor and prevent biofilm formation in DWDSs. The study

was broadly divided into two main themes:

(i) Assessment of novel pipe materials and surfaces for their ability to resist biofilm

formation in DWDSs.

(ii) Development of a novel biofilm sensor to enable real-time monitoring of biofilm

formation in DWDSs that are characterised by a residual chlorine concentration.

1.2. What is a biofilm?

In nature microorganisms often live as sessile communities termed biofilms (Davies et

al., 1998). Biofilms consist of living, reproducing microorganisms that exist as a colony

or community, and can contain a single or multiple species (Mah & O'Toole, 2001).

They have a complex structure, and can be defined as communities of microorganisms

adhering to environmental surfaces (O'Toole et al., 2000). A biofilm community can

form in a range of situations including in water distribution pipelines, on ship hulls and

on teeth; the latter is associated with dental caries (Dunne, 2002). Biofilms are held

together by extracellular polymeric substance (EPS) produced by the microorganisms

(Wimpenny et al., 2000). EPS is comprised of polysaccharides, proteins and

extracellular deoxyribonucleic acid (DNA) (Das et al., 2010). EPS has a role in the

formation of microcolonies and maturation of the biofilm structure, and it enables the

3

biofilm to resist disinfectants, some antibiotics, and environmental stresses (Czaczyk &

Myszka, 2007).

1.3. Biofilm formation

Biofilm formation is divided into five stages (Figure 1.1) (Stoodley et al., 2002) . The

first stage involves initial attachment of microorganisms to the surface. Stage 2

involves irreversible attachment to the surface. In this stage the first microorganisms

to colonise the surface produce the EPS matrix and help the cells to adhere to the

surface. Stage 3 is the first stage of maturation, during which other microorganisms

enter the biofilm where nutrients are absorbed. Stage 4 is the second phase of

maturation, during which the biofilm adopts a complex architecture. The final stage (5)

is the detachment phase, when some microorganisms leave the biofilm. This stage

enables the biofilm-forming microorganisms to spread and form colonies on new

surfaces.

Figure 1.1. The stages of biofilm formation (adapted from Stoodley et al., 2002).

1 2 3 4 5

4

1.4. Biofilm and health risks

The need for safe drinking water, and protection of water resources from

contamination became evident as the relationship of microorganisms to disease and

drinking water was revealed (Szewzyk et al., 2000). Realisation of the connection

between disease and water contamination resulted in the establishment of protected

source areas for drinking water, and also decontamination of treated water to kill or

remove microorganisms.

The requirements for microbiological safety of drinking water specify that the

microbial content should be very low without any pathogenic microorganisms, and the

health risk for acquiring a waterborne infection should be below an accepted limit

(Buthelezi et al., 2009). To achieve these requirements, effective water resource

protection, treatment of raw water and quality control of the treatment process is

required. However, because of the prevalence of biofilms in drinking water systems,

evaluation of factors affecting their formation is also needed.

1.5. Disinfection

Biocides and disinfectants are the principal agents used to control and remove biofilms

in DWDSs (Chen & Stewart, 2000). Disinfectants serve as oxidants in water treatment

(Sadiq & Rodriguez, 2004), and suitable biocides are those that can remove EPS and kill

the cells within the biofilm (Holah et al., 1990; Shakeri et al., 2007). Water suppliers

use disinfectants such as chlorine, chloramines, and ozone to control biofilm formation

(Momba et al., 2000).

Chlorine is an oxidizing agent, and its use aims to leave a sufficient level of chlorine

residual throughout the distribution system to protect it against microbial

recontamination (Sadiq & Rodriguez, 2004). However, chlorine forms undesirable

compounds, including trihalomethanes, which can affect human health (Caravelli et al.,

2006). Monochloramine is a weaker biocide than chlorine, but it penetrates better into

biofilms (Park & Kim, 2008). A disadvantage of using monochloramine is the longer

contact times and higher concentrations necessary to achieve disinfection

effectiveness comparable to chlorine (Park & Kim, 2008). Ozone is another oxidizing

5

biocide that has been used extensively as a disinfectant in drinking water systems and

after a short time it is converted to oxygen (von Gunten, 2003). However, it has a short

half-life and needs to be regenerated (Seol et al., 2003), and because of its chemical

reactivity it is corrosive to materials including copper and some plastics (Yang et al.,

1993).

1.6. Factors affecting biofilm formation

Water distribution systems are complicated environments in which various factors

affect biofilm growth. In the following subsections the effects of a range of parameters

on biofilm growth are discussed.

1.6.1. Nutrient availability

The availability of nutrients is an important factor in the formation of biofilms. Carbon

(C), nitrogen (N) and phosphorus (P) in the approximate proportions 100:10:1 are

required for heterotrophic microbial growth, and simple forms of organic carbon are

more easily used by microorganisms than complex molecules (Momba et al., 2000).

Most sources of carbon compounds in water supplies are natural in origin, and carbon

is usually considered to be a major limiting nutrient for microbial growth (Brunet et al.,

2008). Therefore, the type and concentration of organic carbon influences the

potential for biofilm formation.

To control biofilm formation in water distribution systems, the entry of biodegradable

organic carbon (BOM) into the distribution system should be limited (Volk &

LeChevallier, 1999). Several methods are used for measuring organic carbon in drinking

water, including total organic carbon (TOC), assimilable organic carbon (AOC) and

biodegradable dissolved organic carbon (BDOC) (Stoodley et al., 2002; Wick et al.,

2007).

6

1.6.2. Temperature

Temperature is an important environmental factor affecting biofilm growth in DWDSs

(Gagnon et al., 2000). Lechevallier et al. (1995) found that there was greater species

diversity in the bacterial populations in distribution waters in warmer periods than in

the cold winter months. Rogers et al. (1994) noted that the overall trend of biofilm

formation in a model system at 20, 40 and 50C was related to both temperature and

the piping materials. Bachmann and Edyvean et al. (2005) suggested that at

temperatures > 15C the risk of bacterial growth increased.

1.6.3. Pipe materials

There is a direct relationship between the pipe material and the water quality (Momba

et al., 2000). Biofilm formation will be encouraged if the pipe material is able to

provide the required nutrients for microbial growth (Momba et al., 2000). The

roughness of the pipe material has also been identified as an important factor

affecting the density of bacteria in water distribution systems (Niquette et al., 2000).

Roughness and the porosity of surfaces provide niches and protection for sessile

bacteria from disinfectants, leading to increased bacterial densities on these surfaces

(Bachmann & Edyvean, 2005). Niquette et al. (2000) measured the fixed bacterial

densities on various pipe materials (polyvinylchloride, PVC; polyethylene, PE;

cemented steel; asbestos cement; cemented cast iron; tarred steel and grey iron)

incubated in a drinking water system, using the potential exoproteolytic activity (PEPA)

test. They observed that plastic-based materials including PE and PVC had the lowest

densities of bacterial biomass, while grey iron and cement supported greater biomass.

The greater bacterial density on grey iron was suggested to have been related to

corrosion effects on material porosity and roughness.

Lehtola et al. (2004) compared biofilm formation on copper and plastic pipe material in

a pilot-scale water distribution system using the heterotrophic plate count (HPC) and

the concentration of adenosine triphosphate (ATP) in biofilms. The copper pipes

constrained biofilm formation for 200 days, but after that period microbial density

began to increase. It was concluded that biofilm formation was slower in copper pipes

7

than in plastic pipes. Zhou et al. (2009) reported that fewer bacteria attached to

copper slides than to stainless steel slides in a simulated drinking water system using

HPC without disinfectant, and also that biofilm attachment to the copper slides was

less than that on stainless steel slides in the presence of disinfectant. Copper is toxic

and can prevent the formation of biofilms (Santo et al., 2008; Zhou et al., 2009). Yu et

al. (2010) also compared the biomass production potential (BPP) of various plastic pipe

materials in drinking water with that for copper and stainless steel, and found that the

BPP of copper and stainless steel was less than that for all the plastic materials tested.

1.6.4. Ineffective disinfection

At appropriate concentrations, disinfectants are quite effective in removing

microorganisms (Momba et al., 2000). Gibbs et al. (1990) studied the effect of booster

chlorination (from 0.3 mg L–1 to 0.5 mg L–1 free chlorine residual) on microbial

regrowth in a water distribution supply area using HPC. It was found that there was a

rapid decrease in microbial numbers after booster chlorination, but following a rapid

reduction of residual chlorine in the distribution system, microbial regrowth occurred.

LeChevallier et al. (1995) enumerated the standard plate count (SPC) microorganisms

in chlorinated and untreated water supplies, and found that when no free chlorine

residuals could be detected in the dead-end distribution lines, the number of

microorganisms detected using the SPC was a factor of 23 more than that in

distribution lines containing free chlorine residuals.

1.7. Microtechnology and nanotechnology in biofilm control

Conventional methods of disinfection and decontamination have been effective

against pathogenic microorganisms in water distribution systems (Shannon et al.,

2008). However, disinfectant use has created new problems. Chemicals such as free

chlorine, chloramines and ozone can react with water constituents to form DBPs, many

of which are responsible for cancers and or intoxication (Richardson et al., 2007). To

control waterborne pathogens in water systems, the development of new biofilm

control strategies is crucial. Advances in nanotechnology and engineering provide

8

opportunities for the development of novel water purification processes (Kar et al.,

2011).

Nanotechnology can be described as the engineering of substances at the atomic,

molecular and macromolecular scales (Bostrom & Lofstedt, 2010). Nanomaterials have

dimensions of 1–100 nm, and because of their small structures have unique physical,

chemical and biological properties (Roco, 2003). The large specific surface area of

nanoparticles in combination with their high reactivity makes them excellent

absorbents, catalysts and sensors (Li et al., 2008). Comparison of antimicrobial

nanomaterials with conventional chemical disinfectants showed that antimicrobial

nanomaterials are relatively inert in water, are not strong oxidants, and are not

expected to produce destructive DBPs (Li et al., 2008). Therefore, because of their high

reactivity, small size, large specific surface and ability to carry antimicrobials,

nanomaterials may have application in water systems. Adding antimicrobials to

nanoparticles by physical encapsulation or chemical conjugation may also enhance the

activity of antimicrobials significantly, and release of the antimicrobials may be able to

be controlled (Zhang et al., 2008). Various types of nanomaterials have recently been

assessed for their applicability in water distribution systems to improve water quality.

Some nanomaterials that have been proposed for water purification and their

applicability for water disinfection and preventing microbial growth are described

below.

Titanium dioxide (TiO2)

TiO2 is the most studied nanomaterial and is known to have photocatalytic properties

(Sobczyk-Guzenda et al., 2013). TiO2 is activated by ultraviolet (UV) irradiation and its

antibacterial activity is related to the production of reactive oxygen species (ROS),

peroxide and hydroxyl free radicals (Ziabari & Bahrekazemi, 2014). Photocatalytic

disinfection by TiO2 is activated by visible light (e.g. sunlight) (Li et al., 2008). However,

TiO2 has also caused bacterial death under dark conditions, but the mechanism is

unclear (Adams et al., 2006).

9

Chitosan

Chitosan inhibits replication of bacteriophages in bacteria, and increases resistance to

viral disease in plants (Chirkov, 2002). One of the antimicrobial mechanisms of

chitosan is proposed to involve the interaction of positively charged chitosan particles

with the negatively charged cell membrane, leading to an increase in membrane

permeability and eventual leaking of intracellular components (Qi et al., 2004).

Another proposed mechanism is chitosan-induced chelation of trace metals causing

inhibition of enzyme activities (Rabea et al., 2003).

Nanosilver (nAg)

The antimicrobial mechanism of nAg is unclear. However, several possible mechanisms

have been postulated: 1) nAg adheres to the membrane surface (thus altering

membrane properties), degrading lipopolysaccharides, and causing membrane leakage

(Li et al., 2008); 2) nAg particles damage DNA by entering the bacterial cell and

releasing silver ions (Morones et al., 2005); 3) Ag ions can interact with thiol groups

resulting in protein inactivation (Matsumura et al., 2003), and they also interfere with

DNA replication (Feng et al., 2000). The size of nAg also appears to affect its

antimicrobial properties. Particles < 10 nm in size are more toxic to bacteria such as

Escherichia coli and Pseudomonas aeruginosa, while particles of 1–10 nm can prevent

certain viruses binding to host cells (Sokolowski et al., 2014)

Carbon nanotubes (CNTs)

Carbon nanotubes (CNTs) have antimicrobial activity toward both Gram positive and

Gram negative bacteria (Li et al., 2008) The antimicrobial activity of CNTs is due to

physical interaction with, or oxidative stress of, the cell membrane, which result in loss

of cell integrity (Narayan et al., 2005; Kang et al., 2007).

Microstructured and surface coated materials

Microstructured surfaces have also been used to inhibit the formation of biofilms,

predominantly in the marine environment. Antifouling surfaces with a range of surface

structures (pyramids or riblets) at varying scales (23–69 µm height and 33–97 µm

periodicity) have demonstrated different extents of biofouling (Petronis et al., 2000).

10

Tributyltin (TBT) is an anti-fouling compound that inhibits microorganism growth in the

marine environment, but the use of this compound has been widely banned because

of its harmful effects on marine organisms (Almeida et al., 2007). Natural anti-fouling

compounds isolated from marine plants have been shown to prevent microorganisms

colonization (Qian et al., 2010). Antifouling paints based on silicone, specifically

polydimethylsiloxane, have been used to protect ship hulls from microorganism fouling

(Almeida et al., 2007). However, biofilm prevention using antifouling coatings have

been limited to seawater environments and freshwaters, rather than in drinking water

environments (Callow, 1993).

1.8. On-line biofilm monitoring

Another way to address the problems associated with biofilm growth in DWDSs is to

monitor the dynamics of biofilm formation on a real-time basis. Biofilm monitoring

based on conventional methods relies on biofilm sampling from test surfaces (e.g.

coupons), with subsequent analysis in the laboratory. However, this is time consuming

and there is time-lag between analysis and results (Kadurugamuwa et al., 2003). The

most commonly applied methods are destructive, and disruption or contamination of

the biofilm can occur during passage across the air–water interface during sampling.

Nivens et al. (1995) reported that non-destructive monitoring techniques can

overcome the problems outlined above, and could be used in industrial situations to

monitor processes on-line. Such techniques enable direct measurement of biofilm

parameters in aqueous systems in real-time, are non-invasive, and minimise

interference from microorganisms in the bulk phase (Mauricio et al., 2006). The aim of

on-line biofilm monitoring is to obtain useful signals from the biofilm under

investigation, including energy transfer, acoustic waves, electrical fields, electrical

currents or heat transfer. Most signals are responses to input triggers generated by the

monitoring device and transferred to the surface under investigation, and the signals

are detected by specific sensors. The various on-line biofilm monitoring techniques

have been extensively reviewed by Janknecht et al. (2003), and are summarised in the

following sections.

11

1.8.1. Differential turbidity measurement (DTM)

The DTM method is based on light absorption and scattering by a biofilm. A DTM

device was used for monitoring the turbidity in a wastewater stream from a paper mill

process (Klahre & Flemming, 2000), and consisted of two turbidity probes. One of the

probes was regularly cleaned by a water jet, and the other was left to accumulate

deposits, which increased the turbidity value. Deposit accumulation was indicated by

the difference in readings between the cleaned and the non-cleaned probe. A biofilm

with thickness of < 0.1 mm was not detected by this method, indicating it might not be

useful in some applications.

1.8.2. Microscopy techniques

Visualization of microorganisms on surfaces has been critical to the understanding of

microbial interrelationships. The visual field of a microscope can be converted to a

digital image and analysed using image analysis software, enabling recognition of

individual cells and automatic cell counting. However, with the advances in data

processing equipment there is no potential for on-line biofilm monitoring, except in

laboratory applications (Nivens et al., 1995; Janknecht & Melo, 2003).

Other problems affecting on-site microscopic analysis techniques include: 1) the need

for sensitive microscopes, image acquisition, and analysis hardware and software; 2)

microscope methods involve staining, which is difficult to integrate into an automated

setup; and 3) the application of fixatives or stains affects the biological integrity of

biofilms, rendering continuous monitoring impossible.

1.8.3. Bioluminescence

Bioluminescence is a spectroscopy method based on the detection of light following

enzymatic reactions during metabolism in certain microbes, which produces energy

that excites electrons and produces weak light signals. The presence of organisms can

be detected by utilising this weak light signal (Ivnitski et al., 1999).

12

A problem in the application of this approach is that few organisms are capable of

emitting light naturally, so this method is rarely useful in industrial or field research

applications because of the absence of light-emitting microorganisms in most

situations. Therefore, bulk biofilm monitoring under non-laboratory conditions is

limited by this method (Janknecht & Melo, 2003).

1.8.4. Piezoelectric techniques

The piezoelectric method involves mechanical vibrations to detect biofilm formation. A

piezoelectric sensor consists of a crystal or ceramic body with attached metal

electrodes. When a biofilm forms on the piezoelectrode, the extra mass affects the

vibration properties, changing the frequency of the exciting electric voltage (Bunde et

al., 1998).

A quartz crystal microbalance (QCM) is a piezosensor used in biofilm monitoring

(Nivens et al., 1995). In QCM sensors, when an alternating voltage is applied to the

electrode the entire surface vibrates transversally; these sensors are affected by

changes in temperature, and hydraulic pressure changes. Therefore, this method could

not be employed to detect biofilm formation in DWDSs.

1.8.5. Electrochemical techniques

The bacterial cell surface is composed of a variety of chemical groups including

proteins (Poortinga et al., 2001). Proteins contain electrochemically active groups and

carboxylate functional groups that can facilitate electron transfer from bacteria to a

conductive surface (Bayoudh et al., 2008). Consequently, during bacterial adhesion,

free electrons can be exchanged with a conductive surface and charge can be

transferred to or from the bacterial surface, which could be measured. Electrochemical

measurements are made in an electrochemical cell comprising three electrodes and a

conductive medium in which the three electrodes are submerged; the electrodes are

the working electrode (WE), the counter or auxiliary electrode (CE), and the reference

electrode (RE) (Grieshaber et al., 2008). The reference electrode is usually silver/silver

13

chloride (Ag/AgCl), which maintains a stable potential (Suzuki et al., 1998; Stradiotto et

al., 2003). The WE is used as the transduction element in the biochemical reaction

(Grieshaber et al., 2008). A connection to the CE enables a current to be applied to the

WE if needed (Matsufuji et al., 2006). For electrochemical sensing, each electrode

should be conductive and chemically stable (Pohanka & Skladai, 2008). Electrochemical

methods detect changes in the actively built-up electrical potential, or changes in

passive response to the application of current signals or fixed voltages (Janknecht &

Melo, 2003). In the following subsections the electrochemical methods most

commonly used to monitor biofilms are presented.

1.8.5.1. Open circuit potential (OCP) method

The potential difference between the RE and WE when no electron is allowed to flow

in the external circuit (i.e. zero current) of the electrochemical system can be

measured using the OCP method (Kabir & Mahmud, 2011). Biofilm formation on the

WE surfaces results in a potential difference between the WE and the RE, and this is

referred to as the OCP (Janknecht & Melo, 2003; Zheng et al., 2013). The potential

change is dependent on the electrode material, the presence of microorganisms, and

environmental factors including temperature and salinity (Nivens et al., 1995).

1.8.5.2. Electrochemical noise (EN)

Electrochemical noise (EN) measures potential or current fluctuations, and can be

measured at open circuit conditions (Janknecht & Melo, 2003). It is considered to be a

good method for monitoring and understanding biocorrosion processes because

fluctuations in the electrochemical process produce noise, enabling localised corrosion

to be detected by the occurrence of large fluctuations in potential (Dheilly et al., 2008).

However, the interpretation of signal noise and statistical evaluation are critical

aspects of this method (Janknecht & Melo, 2003).

OCP and EN measurements can indicate microbial activity, and the electrical signals

obtained can be correlated with the presence of biomass under a defined set of

14

conditions, but are not direct or quantitative measures of microbial activity (Nivens et

al., 1995).

1.8.5.3. Electrochemical Impedance Spectroscopy (EIS)

Electrochemical impedance spectroscopy (EIS) can be used to investigate microbial

adhesion to conducting or semiconducting surfaces, because charge transfer is

involved in microbial adhesion (Mansfeld & Little, 1991). The EIS technique is a

powerful and sensitive method for the development of sensors, as it is able to detect

electrical changes on a surface electrode (Suni, 2008; Norouzi et al., 2012). As a result,

any intrinsic electrical property of microbial cells on an electrode surface that could

affect the conductivity in the electrochemical process can be detected by this method

(Mansfeld & Little, 1991).

In EIS experiments a small fixed amplitude sinusoidal voltage signal is applied to an

electrochemical cell using a potentiostat (K'Owino & Sadik, 2005; Randviir & Banks,

2013). The potentiostat is programmed to determine impedance spectra over a range

of frequencies, typically ranging from 100 kHz to 1 mHz (He & Mansfeld, 2009). The

complex impedance of the system can be obtained by applying the sinusoidal voltage

over the range of set frequencies (Grieshaber et al., 2008). Critically, the complex

impedance is calculated as the ratio of the voltage and current generated by a

frequency analyser connected to a potentiostat, according to Equation (1) (K'Owino &

Sadik, 2005; Randviir & Banks, 2013).

(1)

where Z is the impedance, V is the voltage, I is the current, j is the imaginary

component and ω is the frequency.

The complex impedance of a system is the sum of real impedance Zre (ω) and

imaginary impedance Zim (ω) components (Bayoudh et al., 2008). The real impedance

originates from the resistance, and the imaginary impedance originates from the

reactance (Grieshaber et al., 2008).

15

A typical EIS experimental setup consists of an alternating current (AC) power

generator that is connected to an electrochemical cell (K'Owino & Sadik, 2005). As

noted in section 1.8.5, an electrochemical cell consists of a WE, a RE, a CE and a

solution of electrolyte. A sine wave of fixed voltage and frequency is sent to the

potentiostat from the power generator, and interferences to the current by the AC

voltage are presented as capacitive or resistive properties of the WE (K'Owino & Sadik,

2005). Software is used to deduce true values for the impedance, and to obtain

impedance spectra (Randviir & Banks, 2013). Two methods have been commonly used

to present the EIS data, using Nyquist plots (in which the imaginary impedance is

plotted against the real impedance) and Bode plots, in which the impedance and the

phase angle are plotted against the frequency (Park & Yoo, 2003).

The impedance spectrum is typically analysed using an equivalent circuit model that

includes a fitting program to interpret the electrochemical properties associated with

changes in surface characteristics, layers or membranes, as well as exchange and

diffusion processes (Lisdat & Schafer, 2008). The appropriate equivalent circuit model

can be chosen to obtain the impedance parameters of interest, such as resistance or

capacitance. For instance, the Randles equivalent circuit is a model for describing the

impedance behaviour of a system (K'Owino & Sadik, 2005). It consists of solution

resistance Rs, charge transfer resistance Rct, double layer capacitance Cdl and Warburg

impedance W. The term Rs is the resistance between the working electrode and the

reference electrode (Kim et al., 2011) and is independent of the frequency (Randviir &

Banks, 2013). The term Rct is the resistance resulting from electron transfer, and the

term W represents the diffusion of ions in solution. Dielectric and insulating features at

the electrode/electrolyte, resulting from biomolecular interactions, are represented by

the Cdl and Rct components (Lisdat & Schafer, 2008).

A summary of the effects of biofilm formation on EIS parameters reported in various

EIS experiments is shown in Table 1.1. The use of EIS to monitor biofilm formation has

been widely employed on surfaces exposed to various media (e.g. in seawater and in

food industry uses). However, its application in the drinking water industry has not

been widely studied. Unlike other electrochemical methods mentioned in the above

sections, EIS is a non-destructive approach. This makes the use of EIS for on-line

monitoring of biofilm formation in DWDSs highly promising. No study investigating the

16

use of EIS as an on-line monitoring approach for chlorination in DWDSs has been

previously reported.

17

Table 1.1. A summary of the effects of biofilm formation on EIS parameters in different EIS experiments.

Microbial culture Medium EIS configuration Electrodes EIS results References

Frequency

(Hz)

Amplitude

(mV)

WE RE CE

Pseudomonas (P.) putida

DSM 291 and Escherichia coli

ATCC 700078

AB

minimal

medium

(ABMM)

100 kHz to

10 Hz

25 mV Gold or

platinum

disk

Ag/AgCl Platinum Capacitance, a parameter of the electrical

measurement, was sensitive to biofilm

formation and degradation. The capacitance

increased with biofilm growth, and decreased

during biofilm degradation.

(Munoz-

Berbel et

al., 2008)

P. aeruginosa M9

minimal

salts

1 Hz to

100,000 Hz

10 mV Platinum

disk

Ag/AgCl Platinum

wire

Bacterial adhesion and initiation of biofilm

maturation reduced the double layer

capacitance.

(Kim et al.,

2011)

Marine biofilm Seawater 100 kHz–

10 mHz

10 mV Graphite Ag/AgCl Platinum foil Biofilm formation induced a marked increase

in capacitance and a decrease in charge

transfer resistance.

(Xu et al.,

2010)

P. aeruginosa PA01 Lysogeny

broth (LB)

10 Hz to

1 MHz

10 mV Gold Gold n. a. (not

applicable)

The charge transfer resistance increased

during the early stages of biofilm maturation,

and decreased in the later stages of

development.

(Zheng et

al., 2013)

18

P. aeruginosa PAO1 Tryptic soy

broth (TSB)

1 Hz to

100 kHz

10 mV Interdigitat

ed array

(IDA)

electrodes

n. a. n. a. Initial bacterial adhesion induced a decrease

in the double layer capacitance within 1 h,

indicating the double layer capacitance was

the key parameter for the detection of initial

bacterial attachment

(Kim et al.,

2012)

P. stutzeri (PS) and

Staphylococcus epidermidis

(SE)

phosphate

buffer

saline PBS

solution

10 mHz

to

100 kH

10 mV Indium-tin-

oxide (ITO)

coated

glass

plates

Saturated

KCl

calomel

Platinum

wire loop

Bacterial adhesion on the ITO electrode at a

low fixed frequency caused a decrease in

imaginary impedance and a slight increase in

real impedance. There was a decrease in the

charge transfer values, while the double layer

capacitance values were found to increase

after bacterial attachment.

(Bayoudh

et al.,

2008)

Desulfovibrio sp.

Baar’s

medium

(ATCC

medium 12

50)

105 to 10

-

–2 Hz

10 mV Carbon

steel pipe

Saturated

calomel

electrode

Platinum

wire

The biofilm formation decreased the charge

transfer resistance with time, and increased

the corrosion rate.

(AlAbbas

et al.,

2013)

19

1.9. Methods for examining adhered bacteria and biofilm

Microbiological analysis of clinical, food, beverage and water samples is used to

quantify the microbial populations and types of microorganisms attached to surfaces.

The most commonly used methods to quantify microbial populations are briefly

outlined in the following sections.

1.9.1. Heterotrophic plate count (HPC)

This conventional culture method is used to detect microorganisms capable of cell

division on nutritive agar media, which is detected as visible colonies (Hoefel et al.,

2005). Colony development usually takes 24 h but can require several weeks or longer,

and only culturable microorganisms adapted to the growth conditions will form

colonies (Veal et al., 2000). The main advantage of HPC is that it demonstrates that the

cells are culturable, but it is time consuming, labour intensive and tedious (An &

Friedman, 1997).

1.9.2. Light microscopy

This is a basic method for observing and enumerating microorganisms (An & Friedman,

1997). Microorganisms are stained with a dye such as crystal violet or carbol fuchsin. A

microbial flow chamber or a slide culture combined with microscopy can be used to

enumerate microbial cells (Kutalik et al., 2005). Advances in image analysis have made

microbial enumeration much faster and more efficient.

1.9.3. Scanning electron microscopy (SEM)

The morphology of microorganisms adhered to surfaces can be observed using SEM

(An & Friedman, 1997). This method has been used for enumeration of adhered

microorganisms or tissue cells, but is time consuming and only the surface of the

sample can be visualised (Garren & Azam, 2010).

20

1.9.4. Epifluorescence microscopy

This method is used to directly count microorganisms stained with a fluorescent dye

(Lunau et al., 2005). The dye binds with DNA or ribonucleic acid (RNA), and is excited

with light at an appropriate wavelength. Fluorescing cells can be visualised and

distinguished from the other particles below the limit of resolution of light microscopy

(Porter & Feig, 1980). In early studies bacteria were counted using the dye acridine

orange, but this has been replaced by DAPI (4´,6-diamidino-2-phenylindole) (Saby et

al., 1997). The stained samples are counted with high magnification lenses in a large

number of fields, which is time consuming and laborious (Ogawa et al., 2003).

Advances in epifluorescence microscopes have facilitated the enumeration of bacteria

with imaging devices, increasing accuracy and reducing the time involved (Ogawa et

al., 2003).

1.9.5. Biochemical markers

Adenosine triphosphate (ATP) is an important compound in the metabolism in all living

cells. ATP analysis linked to a bioluminescence assay is a useful method for

enumeration and detection of viable cells (Oshita et al., 2011). The reaction between

the luciferase enzyme, the substrate luciferin, and ATP is the basis of the assay. During

the reaction, light is emitted and can be measured quantitatively. The level of light

emission can be correlated with the quantity of ATP extracted from the cells (Lee &

Deininger, 2001).

1.9.6. Flow cytometry (FCM)

Flow cytometry is an cell counting technique capable of enumerating thousands of

cells per second (Davey, 2011). The method is rapid, and it can facilitate analysis of

individual microorganisms (Veal et al., 2000). Flow cytometry is based on the principles

of light scattering, light excitation and emission of fluorochrome molecules. Cells or

particles in a liquid stream are detected by light and fluorescence scattering as the

particles pass through a laser beam (Macey, 2007). Various cellular compounds

21

including DNA and RNA can bind with fluorescent dyes (Brown & Wittwer, 2000). The

stained suspended cells are injected into a flow chamber, which is surrounded by

sheath fluid that forces the cells into a stream (Bernas et al., 2006). The cells are then

passed through the laser, and light and fluorescence is scattered. The scattered

photons of light are converted to electrical impulses by a photomultiplier tube (PMT),

and the signals are processed by an analog-to-digital convertor to produce numerical

signals. The quantity and intensity of the fluorescence is recorded and computer-

sorted as single-parameter, dual-parameter and multi-parameter. Single-parameter

histograms identify the intensity of fluorescence, and the number of cells of a given

fluorescence. From this histogram, weakly fluorescent cells can be distinguished from

strongly fluorescent cells. Dual-parameter histograms reflect forward angle scatter and

90° light scatter (90° LS), and identity various cell types based on size and granularity

(Macey, 2007)

1.10. Aim and scope of the thesis

The overall aim of this study was to generate new knowledge pertaining to the

prevention and control of biofilm formation in drinking water distribution systems

(DWDSs). The specific objectives were to assess various novel pipe materials for the

prevention of biofilm formation in DWDSs, and to develop new methods for

monitoring biofilm formation, to facilitate optimisation of disinfectant application in

DWDSs.

Accordingly, the scope of the thesis was designed as follow:

1. Evaluation of the biofilm formation potential of various materials including

nanomaterials, polymers and coating materials in drinking water systems

(Chapter 2).

2. Development of an electrochemical sensor, based on methods including OCP

and EIS, for the detection of biofilm formation in drinking water systems; and

assessment of the impact of chlorination on biofilm formation and the

electrochemical signals (Chapters 3 and 4).

22

2. The effect of pipe materials on biofilm formation

2.1. Introduction

The characteristics of pipe materials can affect the microbial density in DWDSs. Pipe

material roughness, surface energy , biological affinity, and hydrophobicity have been

identified as important factors that affect biofilm formation in DWDSs (Niquette et al.,

2000; Pasmore et al., 2001). Microbial cells have been suggested to attach more

strongly to hydrophobic surfaces than to hydrophilic surfaces, because of the exclusion

of water from the hydrophobic surfaces (Pasmore et al., 2001; Donlan, 2002). The pipe

surface itself can also influence the biofilm populations, which may lead to the

presence and persistence of microbial pathogens (Kerr et al., 1999). Studies have

shown that bacterial biomass develops more rapidly on iron and cement surfaces than

on plastic-based materials such as polyvinylchloride (PVC) (Niquette et al., 2000).

Copper pipes have antimicrobial activity (Morvay et al., 2011), which may suppress the

growth of environmental pathogens (Lu et al., 2014). Therefore, it is important to

consider the types of materials that come into contact with potable water.

The rapid growth of nanotechnology has received significant attention in

environmental and biological applications. However, the application of nanomaterials

has not been extensively explored in DWDSs. Several natural and engineered

nanomaterials have recently been demonstrated to have strong antimicrobial

properties through diverse mechanisms. Amongst these are photocatalytic production

of reactive oxygen species (ROS) that damage cell components and viruses, and inhibit

enzyme activity and DNA synthesis (Li et al., 2008). Pipes coated with nanomaterials

and polymers could potentially help to control biofilm formation in DWDSs. In marine

environments, hydrophilic polymer surfaces with low values of polymer–water

interface energy are able to resist protein adsorption and reduce cell adhesion

(Krishnan et al., 2008), and ship hulls are typically coated with biocide-containing

paints to prevent colonization by marine organisms (Stafslien et al., 2007). The marine

paints rely on the flow of water past the ship to generate a shear force to dislodge

adhered organisms (Stafslien et al., 2007). As water pipelines carry water at speed,

these coatings may be particularly suitable for preventing biofilm formation. The aim

23

of this study was to evaluate the potential for various novel materials, including

nanomaterials, polymers and coatings, to resist biofilm formation in DWDSs.

2.2. Materials and methods

2.2.1. Production of nanomaterials and other surfaces for assessing biofilm

formation

Various novel materials and surface structures have been produced by members of the

CSIRO Material Science and Engineering section, and were provided to the CSIRO Land

and Water team for testing in a laboratory scale pipe. A summary of the tested

materials and surface structures is presented in Table 2.1. A surface coated with

carbon nanotubes (CNTs) was tested as a nanomaterial surface. A microscope image of

a carbon nanotube surface is shown in Figure 2.1. A series of polymers ranging in

contact angle from hydrophilic to hydrophobic were selected for testing (with and

without embedded copper), including high density polyethylene (HDPE),

polytetrafluoroethylene (PTFE) and nylon. In addition, one of the metal samples

(stainless steel) was coated with fouling-release Hempel X3 marine paint. This coating

belongs to a large group of non-toxic marine paints used for ship hulls. It forms a

hydrogel at the surface, which also acts as a stealth coating because the boundary

layer of water makes the surface “invisible” to settling organisms. Surfaces including

concrete and stainless steel were used as traditional control materials, enabling

comparisons of biofilm formation on the various test and control surfaces.

24

Table 2.1. Summary of nanomaterial, polymers, coating and control materials used in

laboratory-scale pipe rig experiments.

Type of material

Description and type of material Label

Polymers

(with and without embedded copper)

Nylon

Nylon embedded with 71 g Cu m–2

Nylon embedded with 192 g Cu m–2

Nylon

N 71

N 192

High density polyethylene

HDPE embedded with 85 g Cu m–2

HDPE embedded with 238 g Cu m–2

HDPE

HDPE 85

HDPE 238

Polytetrafluoroethylene

PTFE embedded with 64 g Cu m–2

PTFE embedded with 143 g Cu m–2

PTFE

PTFE 64

PTFE 143

Nanomaterial Carbon nanotube CNT

Coating Marine paint Marine paint

Traditional control materials

Concrete

Stainless Steel

Concrete

Stainless Steel

25

Figure 2.1. Carbon nanotube (CNT) with spikes approximately 2 μm apart. The rigidity

of the CNTs and their close spacing enables them to puncture the bacterial cell wall.

2.2.2. Coupons

Various materials and surfaces were cut to produce 'coupons' (approximately 4.1 cm ×

1.5 cm) to test their effects on biofilm formation in the pipe rig (see below). Figure 2.2

shows examples of the coupons, which were attached to plastic bolts using stainless

steel screws for placing in the pipe rig (Figure 2.3).

26

Figure 2.2. Various material surfaces tested in the pipe rig.

Figure 2.3. Coupons attached to plastic bolts. Materials left to right: N 192, nylon and

concrete.

HDPE HDPE 238

238238

HDPE 85

PTFE PTFE 64 PTFE 143

Nylon N 71 N 192

CNT Marine paint

Concrete Stainless steel

27

2.2.3. Construction and operation of the pipe rig

A laboratory-scale pipe rig (2 m length and 0.15 m diameter; Figure 2.4) was designed

and constructed for testing the effects of the various materials and surfaces on biofilm

formation. The pipe rig contained 80 ports for inserting coupons for monitoring biofilm

formation (Figure 2.5). The water for all experiments was collected from the

Mundaring Weir, Mundaring, Western Australia (31.95S, 116.17E). Approximately

800 L of water was recycled through the pipe rig using a Davey XP350P8C pump

(model number 72101/LOP-0) at a flow rate of 120 L h–1, corresponding to a horizontal

water velocity of 6.8 m h–1 through the rig.

Two series of experiments, each of 14 days, were conducted to compare the extent of

biofilm development on the various materials. In both tests, concrete and stainless

steel were included as controls for comparison. In the first series, biofilm formation

was monitored on nylon, nylon embedded with 71 g m¯² Cu (N 71), nylon embedded

with 192 g m¯² Cu (N 192), and the two control materials. In the second series, biofilm

formation was monitored on PTFE, PTFE embedded with 64 g m¯² Cu (PTFE 64), PTFE

embedded with 143 g m¯² Cu (PTFE 143), HDPE, HDPE embedded with 85 g m¯² Cu

(HDPE 85), HDPE embedded with 238 g m¯² Cu (HDPE 238), 0.2% carbon nanotube

(CNT) in polydimethlsiloxane (PDMS), metal coupons coated with antifouling marine

paint, and the two control materials.

28

Figure 2.4. Pipe rig used for laboratory experiments on biofilm formation on coupons.

Figure 2.5. Coupons inserted in the pipe rig: copper embedded nylon (left) and

concrete (right).

ConcreteN71 N192

29

2.2.4. Detachment of cells from coupons

For determining biofilm formation, the first reading on day 0 was taken 1 h after

inserting the coupons into the pipe rig, which commenced the experiment. At each

sampling the coupon was removed from the pipe rig, and material on non-test surfaces

associated with the coupon was removed using a sterilised cotton swab, leaving only

the biofilm that had developed on the test surface of the coupon. The coupon was

then transferred into 30 mL of dechlorinated tap water in a 50 mL centrifuge tube

(Iwaki, Japan). The tube was sonicated (Bransonic 220, USA) for 5 min in an ultrasonic

bath to dislodge the attached biofilm from the coupon. The coupon was removed from

the centrifuge tube and the coupon surface was rubbed with a cotton swab to remove

any remaining biofilm. The swab was transferred to the solution in the centrifuge tube

and sonicated for 5 min, and then removed. The resulting cell suspension was used for

analysis of microbial activity and for microbial cell counts. In addition to analysis of

biofilms attached to the coupons, at each sampling time 30 mL of bulk water sample

was also taken from the pipe rig and was transferred to a 50 mL centrifuge tube (Iwaki,

Japan) for microbial cell counts.

2.2.5. Quantification of microbial activity and cell numbers

Microbial analysis of the biofilm involved:

1. Adenosine triphosphate (ATP) assay for measurement of microbial activity

2. Colony counts (colony forming units; CFU) on plate count agar for total

cultivable aerobic heterotrophic microorganisms

3. Epifluorescence microscopy for total microbial cell counts

4. Flow cytometry (FCM) for total microbial cell counts

The results for the ATP assay, epifluorescence microscopy and FCM were presented as

the average values of duplicate samples; the error bars (standard deviations) were too

small to be evident on the graphical scale being used in the accompanying figures.

Plate count experiments (CFU) were not duplicated.

30

2.2.5.1. Adenosine triphosphate (ATP) assay

Total ATP was measured using the Promicol ®Biomass test kit (Promicol, Netherlands)

and a Lumac ®Biocounter M1500 (3M, USA). A standard curve was prepared using ATP

standards of 10, 100, 500 and 1000 ng mL–1. To measure the ATP concentration in a

cell suspension, a 100 µL aliquot of the suspension was transferred into an Eppendrof

tube and 100 µL of Promex M reagent was added to release ATP from the cells.

Thereafter, 100 µL of Prolux reagent was added to catalyse the conversion of the

chemical energy of ATP into light, through oxidation–reduction activation. The

luminescence in the tube was immediately measured using a Lumac ®Biocounter

M1500 (3M, USA) luminometer. The luminescence value was applied to the standard

curve to calculate the concentration of ATP in the sample using the following Equation

(2):

ATP (ng cm¯²) = ATPv*V/Ac (2)

where ATPv is the ATP concentration in the liquid that contained the dislodged cells

from the coupon surface (ng mL¯¹), V is the volume in which the cells were suspended

(mL), and AC is the surface area of the coupon (cm2).

2.2.5.2. Viable plate count

The number of viable aerobic heterotrophic cells in the samples was determined using

the plate count method (plate count agar; PCA). The main advantage of this method is

that it indicates the number of viable culturable cells, while FCM or DAPI stained cells

indicates both viable and non-viable cells. However, some microbial cells may be viable

but not culturable with the selected growth medium and conditions, and thus may

remain undetected using plate counting. To prepare the PCA plates, 22.5 g of PCA was

suspended in 1 L of Milli-Q water, mixed thoroughly and autoclaved (Tuttnauer, USA)

for 20 min at 121C. The PCA included peptone from casein (5 g L–1), yeast extract (2.5

g L–1), D(+) glucose (1 g L–1), and agar-agar (14 g L–1). A volume of 50 μL of a 1:10

dilution of each sample was uniformly spread onto the PCA plate surface using a sterile

31

spreader. The plates were incubated for 48 h at 37C. The cell count (cells cm¯2) was

based on the number of colony forming units (CFU), using Equation (3):

Cell count (cells cm¯2) = CFU*VT*D/ (Vs*Ac) (3)

where CFU is the number of colonies counted on the plate, VT is total volume into

which the cells were suspended from the coupon (mL), D is the dilution factor, Vs is the

volume of the diluted cell suspension spread on the plate (mL), and Ac is surface area

of the coupon (cm2).

2.2.5.3. Epifluorescence microscopy

The number of microbial cells in the samples was counted using epifluorescence

microscopy, following staining with DAPI. For this analysis 5 mL of water sample was

fixed by adding 1 mL of 5% (w/v) gluteraldehyde. To obtain reliable counts, each

sample was diluted 1:10 (100 μL in 900 μL of decholrinated tap water), and 1 mL of the

diluted sample was then mixed with 9 µL of DAPI reagent (100 µg L–1). After 2 min the

stained sample was filtered through an Isopore® Membrane filter under vacuum. The

filter was then removed using tweezers and placed on a clean microscope slide, and 20

randomly selected fields on the filter were examined using an AXIO microscope (Zeiss,

Australia & New Zealand; 100 oil immersion) to assess whether the distribution of

cells was uniform and to obtain cell counts (Figure 2.6). The total microbial cell count

for each coupon material was determined using Equation (4):

Cell count on coupon (cells cm¯2) = (N*DV1*DV2*(VT/VF)*(AF/AV))/AC (4)

where N is the average number of cells counted per view, DV1 is the dilution factor

from glutaraldehyde fixation (volume of sample + volume of glutaraldehyde/volume of

sample), DV2 is the additional dilution factor for diluting sample before filtering, VT is

the total volume into which cells were suspended from coupon (mL), VF is the volume

of the fixed and diluted sample aliquot filtered through the filter (mL), AF is the area of

filter (cm2), AV is the area of the view from which cells were counted (cm2) and AC is

the area of the material on the coupon (cm2).

32

Figure 2.6. Epifluorescence microscopy image of a sample from the pipe rig. Microbial

cells were stained using DAPI.

2.2.5.4. Flow cytometry

Microbial cell numbers were also estimated using flow cytometry (FCM). For this

analysis an aliquot of the water sample was filtered through a 0.8/0.2 μm Supor®

Membrane as a control/blank, then 0.4 μL of 3.34 mM SYTO9 (Invitrogen, USA) stain

was added to each of 499.6 μL of the control and filtered samples. The stained

solutions were incubated in the dark at room temperature (approximately 22 ± 2 C)

for 15 min prior to FCM measurement. Where necessary, samples were diluted with

sterilised Milli-Q water (Millipore, USA) immediately prior to measurement to ensure

that the cell concentration measured using FCM was always less than 103 cells mL–1. All

experiments were performed using a Cell Lab Quanta TM SC flow cytometer (Beckman

Coulter Quanta, U.S.) equipped with a 22 mV solid state laser emitting light at a fixed

wavelength of 488 nm. Green fluorescence was collected in the FL1 channel (520 ± 20

nm) and red fluorescence was collected in the FL3 channel (> 670 nm). All parameters

were recorded as logarithmic signals. Data were analysed using QUANTA SC software.

Microorganism clusters were detected in a plot of 90 side light scatter versus green

fluorescence (FL1), and electronic gating with the software was used to separate the

microbial clusters from noise. Microbial quantification was performed by counting the

33

number of events included inside the corresponding gate (Figure 2.7). The total cell

density on the coupons was then counted using Equation (5):

Cell count (cells cm¯2) = N*

*D*

(5)

where N is the average cell density in the stained and diluted sample, VSA is the volume

of sample aliquot stained, VD is the volume of stain, D is the dilution factor, VT is the

total volume into which cells were suspended from coupon, and Ac is the surface area

of each coupon (cm2).

Figure 2.7. Flow cytometry of a sample from the pipe rig. The sample was stained with

SYTO9 and analysed using flow cytometry. FL1 denotes green fluorescence signals

(520 nm) and FL3 denotes red fluorescence signals (> 670 nm). Electronic gates (- - -)

were used to distinguish microbial cells from background.

34

2.3. Results

2.3.1. ATP assay

The ATP assay showed that ATP concentrations varied over time on concrete, stainless

steel, nylon and nylon embedded with Cu (Figure 2.8), with less than an order of

magnitude change in the concentrations over the 14 days of the experiment. The ATP

concentrations associated with Cu-embedded nylon were consistently lower than for

concrete and nylon without embedded Cu, whereas the concentrations on stainless

steel fluctuated notably, and had the lowest ATP concentration among all materials on

day 6, but the highest on day 14.


on concrete, stainless steel, nylon and Cu-embedded nylon (N 71: 71 g Cu m–2; N 192:

192 g Cu m–2).

1.0E+01

1.0E+02

1.0E+03

1.0E+04

1.0E+05

0 2 4 6 8 10 12 14

ATP

(n

gcm

-²)

Time (d)

Concrete Stainless Steel NylonN71 N192

35

The ATP concentrations in biofilms that formed on concrete, stainless steel, HDPE and

Cu-embedded HDPE (Figure 2.9) varied substantially during the first week. Following

this the Cu-embedded HDPE showed slightly lower ATP concentrations than the other

materials. The ATP concentration did not notably increase on any of the materials

during the two week experiment.


on concrete, stainless steel, high density polyethylene (HDPE) and Cu-embedded HDPE

(HDPE 85: 85 g Cu m–2; HDPE 238: 238 g Cu m–2).

1.0E+01

1.0E+02

1.0E+03

1.0E+04

1.0E+05

0 2 4 6 8 10 12 14

ATP

(ng

cm-²

)

Time (d)

Concrete Stainless Steel HDPE

HDPE 85 HDPE 238

36

The ATP concentrations in biofilms that formed on concrete, stainless steel, PTFE and

Cu-embedded PTFE (Figure 2.10) fluctuated on all materials over the two weeks of the

experiment, with no clear trends observed for any of the materials. At some time

points the ATP concentration in biofilms on the Cu-embedded PTFE was lower, and at

other times higher, than the concentrations in biofilms on the control materials. The

ATP concentration did not notably increase on any of the materials during the

experiment, and all of the tested materials had similar ATP concentrations compared

with the first day of coupon installation.


on concrete, stainless steel, polytetrafluoroethylene (PTFE) and Cu-embedded PTFE

(PTFE 64: 64 g Cu m–2; PTFE 143: 143 g Cu m–2).

1.0E+01

1.0E+02

1.0E+03

1.0E+04

1.0E+05

0 2 4 6 8 10 12 14

ATP

(ng

cm-²

)

Time (d)

Concrete Stainless Steel PTFE

PTFE 64 PTFE 143

37

For biofilms that formed on concrete, stainless steel, carbon nanotube (CNT) and

marine paint-coated coupons (Figure 2.11), the ATP concentrations were consistently

lower for the CNT (apart from CNT on days 0 and 3) and marine paint-coated coupons

than for coupons of concrete and stainless steel. Although the concentrations

fluctuated to some degree over the 14 days of the experiment, the final concentrations

on all materials were similar to those recorded at the start of the experiment.


on concrete, stainless steel, carbon nanotube (CNT) and marine paint.

In general, none of the novel materials tested produced a noticeable decrease in

microbial activity relative to the traditional control materials (concrete and stainless

steel).

1.0E+01

1.0E+02

1.0E+03

1.0E+04

1.0E+05

0 2 4 6 8 10 12 14

ATP

(ng

cm-²

)

Time (d)

Concrete Stainless SteelCNT Marine Paint

38

2.3.2. Plate count

Trends in the total viable aerobic heterotrophic cell counts (Figure 2.12) based on the

plate count method indicated that there was a marked increase in viable cells in the

biofilms on all materials over the 14 day experimental periods. The greatest increase in

viable cells was associated with biofilm formation on nylon, whereas stainless steel

had the lowest viable cell count after 14 days. The total viable cell count for concrete

was an order of magnitude less than that on the nylon with no embedded Cu. Cell

counts on Cu-embedded nylon were similar to those on nylon after 7 days, but lower

counts were obtained for the N 71 coupons after 14 days. However, the use of a higher

copper content (N 192) did not result in lower cell counts than with the lower copper

content (N 71). As no duplicates were used in this experiment it was not possible to

draw conclusions about the statistical significance of differences in the cell counts.


concrete, stainless steel, nylon and Cu-embedded (N 71: 71 g Cu m–2; N 192: 192 g Cu

m–2).

1.0E+00

1.0E+01

1.0E+02

1.0E+03

1.0E+04

1.0E+05

1.0E+06

1.0E+07

0 2 4 6 8 10 12 14

Ce

ll c

ou

nt

(ce

lls

cm-2 )

Time (d)

Concrete Stainless Steel NylonN71 N192

39

Comparison of viable aerobic heterotrophic cell counts in biofilms that formed on

HDPE, Cu-embedded HDPE, concrete and stainless steel (Figure 2.13) showed that the

viable cell count on stainless steel and HDPE 85 increased to day 1 and decreased or

remained stable thereafter. The cell count increased until day 2 for the HDPE with no

embedded CU and to day 4 for concrete, and decreased towards the end of the 14 day

experimental period. The viable cell count on HDPE 238 increased to day 1, fluctuated

until day 7, then decreased until the end of experiment. At the end of the experiment

all of the tested materials had a similar cell counts, with no clear differences among

the materials. Therefore, HDPE embedded with copper did not decrease cell counts

relative to HDPE, concrete and stainless steel (Figure 2.13).


concrete, stainless steel, high density polyethylene (HDPE), and Cu-embedded HDPE

(HDPE 85: 85 g Cu m–2; HDPE 238: 238 g Cu m–2).

1.0E+00

1.0E+01

1.0E+02

1.0E+03

1.0E+04

1.0E+05

1.0E+06

1.0E+07

0 2 4 6 8 10 12 14

Ce

ll c

ou

nt

(ce

lls

cm-²

)

Time (d)

Concrete Stainless steel HDPE

HDPE 85 HDPE 238

40

Comparison of the biofilms that formed on PTFE, Cu-embedded PTFE, concrete and

stainless steel (Figure 2.14) showed that the viable aerobic heterotrophic cell counts in

the biofilms on concrete, stainless steel and PTFE 64 gradually decreased 1 day

following coupon installation, whereas the cell counts increased until day 4 for PTFE

143 and to day 7 for the PTFE with no embedded Cu. After 14 days the highest cell

counts were associated with PTFE and the lowest (approximately an order of

magnitude lower) were on PTFE 64. The cell counts on PTFE 64 remained lower than

those on PTFE (no embedded Cu) and concrete after day 4. The counts on stainless

steel were similar to those on PTFE 64 throughout the experiment. The data suggest

that the cell counts on PTFE 143 declined abruptly after day 4 but had recovered by

day 14. The experiment would need to be repeated to confirm this observation.


concrete, stainless steel, polytetrafluoroethylene (PTFE) and Cu-embedded PTFE (PTFE

64: 64 g Cu m–2; PTFE 143: 143 g Cu m–2).

1.0E+00

1.0E+01

1.0E+02

1.0E+03

1.0E+04

1.0E+05

1.0E+06

1.0E+07

0 2 4 6 8 10 12 14

Ce

ll c

ou

nt

(ce

lls

cm-²

)

Time (d)

Concrete Stainless steel PTFE

PTFE 64 PTFE 143

41

Comparison of the number of viable aerobic heterotrophic cell in biofilms that formed

on CNT, marine paint-coated, concrete and stainless steel coupons (Figure 2.15)

showed that the viable cell count on stainless steel, CNT and concrete increased to

days 1, 2 and 4, respectively, and decreased or remained stable thereafter. The viable

cell count on marine paint increased during the first 4 days of the experiment,

decreased until day 7, then increased until the end of experiment and had the highest

cell count on day 14. The viable cell counts on marine paint at day 14 were a

magnitude higher than on the traditional materials and CNT (Figure 2.15).


concrete, stainless steel, carbon nanotube (CNT) and marine paint.

In general, Cu-embedded polymers, CNT and marine paint surfaces did not cause a

marked decrease in viable cell counts relative to the counts on traditional pipe

materials (concrete and stainless steel).

1.0E+00

1.0E+01

1.0E+02

1.0E+03

1.0E+04

1.0E+05

1.0E+06

1.0E+07

0 2 4 6 8 10 12 14

Ce

ll c

ou

nt

(ce

lls

cm-²

)

Time (d)

Concrete Sainless Steel

CNT Marine Paint

42

2.3.3. Flow cytometry and epifluorescence microscopy

Flow cytometry was used to determine total microbial cell counts in biofilms on the

test materials, and was compared with total cell counts determined by epifluorescence

microscopy. The total cell count determined by flow cytometry on concrete, stainless

steel, nylon and Cu-embedded nylon (Figure 2.16) increased over time on each

material during the 14-day experiment. The total cell count on concrete was

considerably higher than on the other materials at the end of the experiment. When

determined by epifluorescence microscopy, fluctuations were observed in the total cell

counts on these materials (Figure 2.17), but the numbers increased somewhat on all

materials over the experimental period. However, based on this method higher cell

counts were not found on concrete relative to the other materials tested. This

difference may be because of a nonspecific flow cytometry signal derived from

inorganic particles originating from the concrete coupons. In general, there was less

fluctuation in cell numbers based on flow cytometry relative to epiflouresence

microscopy.

43


and Cu embedded nylon (N 71: 71 g Cu m–2; N 192: 192 g Cu m–2), determined by flow

cytometry.


and Cu-embedded nylon (N 71: 71 g Cu m–2; N 192: 192 g Cu m–2), determined by

epifluorescence microscopy.

1.0E+04

1.0E+05

1.0E+06

1.0E+07

1.0E+08

0 2 4 6 8 10 12 14

Ce

ll c

ou

nt

(ce

lls

cm-²

)

Time (d)

Concrete Stainless steel Nylon

N-71 N-192

1.0E+04

1.0E+05

1.0E+06

1.0E+07

1.0E+08

0 2 4 6 8 10 12 14

Ce

ll c

ou

nt

(ce

lls

cm-²

)

Time (d)

Concrete Stainless Steel Nylon

N71 N192

44

Based on flow cytometry, the total cell counts on concrete, stainless steel HDPE and

Cu-embedded HDPE (Figure 2.18) fluctuated considerably over time on all materials.

The cell counts on concrete were slightly higher than those on the other materials

throughout the experiment. There was a considerable decrease in counts for stainless

steel after 6 days, followed by slight increase to the end of the experiment. The other

three materials had similar cell counts after 14 days, and the counts did not notably

increase relative to the cell counts at the beginning of the experiment.


high density polyethylene (HDPE) and Cu-embedded HDPE (HDPE 85: 85 g Cu m–2;

HDPE 238: 238 g Cu m–2), determined by flow cytometry.

1.0E+04

1.0E+05

1.0E+06

1.0E+07

1.0E+08

0 2 4 6 8 10 12 14

Ce

ll c

ou

nt

(ce

lls

cm-²

)

Time (d)

Concrete Stainless Steel HDPE

HDPE 85 HDPE 238

45

Based on flow cytometry, the total cell counts in biofilms that formed on concrete,

stainless steel, PTFE and Cu-embedded PTFE (Figure 2.19) fluctuated somewhat on all

materials. The cell counts on concrete were slightly higher than those on the other

materials. The biofilms on Cu-embedded PTFE did not have consistently lower counts

than those on PTFE or the stainless steel control. The cell counts did not increase

notably over time on any of the materials.


and polytetrafluoroethylene (PTFE) and Cu-embedded PTFE (PTFE 64: 64 g Cu m–2;

PTFE 143: 143 g Cu m–2), determined by flow cytometry.

1.0E+04

1.0E+05

1.0E+06

1.0E+07

1.0E+08

0 2 4 6 8 10 12 14

Ce

ll c

ou

nt

(ce

lls

cm-²

)

Time (d)

Concrete Stainless Steel PTFE

PTFE 64 PTFE 143

46

Based on flow cytometry, the total cell counts in biofilms that formed on concrete,

stainless steel, CNT and coupons coated with marine paint (Figure 2.20) varied over

time. At the end of the experiment the highest counts were on marine paint and the

lowest on CNT. However, the counts on stainless steel and marine paint were generally

substantially lower than on the other materials until the last sampling occasion.


carbon nanotube (CNT) and marine paint, determined by flow cytometry.

The trends in cell numbers detected using flow cytometry and epifluorescence

microscope did not suggest any consistent decrease in the number of cells on the

novel materials relative to the traditional control materials. In addition, no marked

increase in cell numbers occurred on most of the materials over the two weeks of the

experiment.

1.0E+04

1.0E+05

1.0E+06

1.0E+07

1.0E+08

0 2 4 6 8 10 12 14

Ce

ll c

ou

nt

(ce

lls

cm-²

)

Time (d)

Concrete Stainless Steel

CNT Marine Paint

47

Flow cytometry and epifluorescence microscopy were also used to determine total cell

numbers in the bulk water at each time of sampling of the coupons. Flow cytometry

results indicated that the total cell numbers in the bulk water increased markedly for

two days but decreased greatly thereafter (Figure 2.21). In contrast, the number of

cells detected by epifluorescence microscopy increased slightly over the first 2 days,

and decreased after day 6 (Figure 2.22).

The cell numbers in bulk water, as determined by both flow cytometry and

epifluorescence microscopy, were lower at the end of the two-week experiment than

at the beginning.

48

Figure 2.21. Total cell numbers in the bulk water, determined by flow cytometry.

Figure 2.22. Total cell numbers in the bulk water, determined by epifluorescence

microscopy.

1.0E+06

1.0E+07

1.0E+08

1.0E+09

0 2 4 6 8 10 12 14

Ce

ll c

ou

nt

(ce

lls

mL¯

¹)

Time (d)

1.0E+06

1.0E+07

1.0E+08

1.0E+09

0 2 4 6 8 10 12 14

Ce

ll c

ou

nt

(ce

lls

mL¯

¹)

Time (d)

49

2.4. Discussion

Biofouling on all coupons was detected by all four methods (ATP assay,

epifluorescence microscopy, flow cytometry, colony counts on plate count agar) as

rapidly as 1 h following coupon installation in the laboratory scale pipe rig. The results

showed that under the pipe rig operating conditions none of the novel materials was

effective in preventing biofilm formation, with no marked difference in microbial

density apparent between the traditional and novel materials. In drinking water

distribution systems, because of the large surface to volume ratio, more than 95% of

the entire biomass is located on the walls, and less than 5% occurs in the water phase

(Flemming et al., 1998). In the present study the results showed that the numbers of

cells increased on the coupons and decreased in the bulk water during the

experimental period, suggesting the possible movement of cells from the bulk water to

the coupons.

In this study polymers ranging from hydrophilic to hydrophobic were assessed for their

effect on biofilm formation. The settlement of bacteria in seawater has been reported

to be greater on hydrophilic polymers (epoxy and nylon) than on hydrophobic

polymers (PDMS) (Carl et al., 2012). In the present study biofilm formation on nylon

was greater than that on the traditional materials (concrete and stainless steel)

detected by colony counts and epifluorescence microscopy. In another study (Pasmore

et al., 2001) on the prevention of biofilms on various hydrophilic and hydrophobic

polymers, none of the tested materials was able to completely prevent biofilm fouling.

These results are consistent with those found in the present study. The ability of cells

to attach to polymer surfaces may be also affected by the texture of the surfaces in

addition to the hydrophobicity of the surfaces. In the present study, polymers with

embedded-copper did not decrease the number of cells relative to the traditional

control materials. Copper is one of the most toxic materials for bacteria in biofilms

(Slowey & Jeffrey, 1967), and it has been shown that the cell density in biofilms on

copper is less than in biofilms growing on plastic (Schwartz et al., 1998). For a pilot

scale distribution network it has been reported that the total cell numbers and the ATP

concentration in biofilms in copper pipes increased for 200 days (Lehtola et al., 2004).

50

Lehtola et al. (2004) also reported that the presence of copper in the polymers did not

decrease biofilm formation.

Nanomaterials such as CNTs have been shown to have antimicrobial capabilities in the

treatment of water affected by chemical and biological contaminants (Upadhyayula et

al., 2009). However, in the present study CNTs did not prevent biofilm formation

compared with traditional control materials. The antimicrobial properties of CNTs

depend on bioavailability of the nanotubes and the degree of aggregation (Wick et al.,

2007; Brunet et al., 2008; Li et al., 2008). It is possible that during this study the

conditions required for the expression of CNT antimicrobial properties were not

optimal.

Marine paint may disrupt the early stages of biofilm formation and provide an

effective antifouling coating for protection of the water network. In the present study

the microbial activity in the biofilm on the coupons coated with marine paint

decreased over the first 7 days and increased slightly thereafter. One explanation is

that the paint used in the presented study did not prevent the initial attachment of

bacteria (Mieszkin et al., 2012). Molino et al. (2009) evaluated bacterial formation on

two antifouling paints (Intersmooth 360 and Super Yacht 800) and a fouling release

coating (Intersleek 700) in seawater, and found that all three coatings fouled

significantly by 16 days.

2.5. Conclusions

Pipe materials have a large influence on biofilm formation in water distribution

systems. The surface characteristics of pipe materials, including roughness, surface

energy and biological affinity can affect biofilm formation. Pipe materials can also

release substances that enhance or inhibit biofilm formation, potentially influencing

the presence and persistence of microbial pathogens. Based on the data presented in

this study, the novel materials tested in the laboratory scale pipe rig (carbon

nanotubes, polymers with different hydrophobicities, materials with and without

embedded copper, and marine antifouling paint) did not show superior performance in

preventing biofilm formation when exposed to Mundaring Weir water, relative to the

51

traditional pipe materials, concrete and stainless steel. Future work should focus on

testing the novel materials in the pipe rig for longer time periods to assess their impact

on biofilm formation, and to using tap water containing disinfectant residuals that

reflect the real world use of the materials. Moreover, the flow rates and pressure of

the pipe rig could be adjusted to better represent the conditions in real DWDSs.

52

3. The use of electrochemical methods for biofilm

monitoring in drinking water systems

3.1. Introduction

From a public health standpoint, uncontrolled biofilm formation in water distribution

pipelines is undesirable because biofilms are generally more resistant to disinfection

than planktonic cells (Lechevallier et al., 1988), enabling biofilms to act as reservoirs

for pathogenic microorganisms (Park et al., 2001). Disinfectant dosing is an effective

approach to managing biofilm formation in DWDSs, but it is often based on experience

rather than real-time evidence (Levin et al., 2002). This often results in excessive

disinfectant dosing, leading to the formation of carcinogenic DBPs (Hrudey, 2009).

Hence, new technologies for real-time monitoring of biofilm formation that facilitate

optimised disinfectant dosing in water distribution pipelines are needed.

Several techniques including light scattering (Klahre & Flemming, 2000), cathodic

depolarization (Pavanello et al., 2011) and turbidity (Janknecht & Melo, 2003) have

been developed for real-time biofilm monitoring. However, as biofilms are known to

have complex and uneven structures (Wimpenny et al., 2000), the light scattering

method may be unreliable, cathodic depolarization causes damage to the biofilm

during analysis, and turbidity cannot detect initial biofilm colonization (Pavanello et al.,

2011). Electrochemical methods for biofilm monitoring have recently gained attention,

largely because they are non-destructive to biofilms and the required equipment is

easy to install and operate (Munoz-Berbel et al., 2006; Dheilly et al., 2008; Munoz-

Berbel et al., 2008; Ben-Yoav et al., 2011; Kim et al., 2011).

Open circuit potential (OCP) is an electrochemical technique that has been used to

detect biofilm formation (Liao et al., 2010; Zheng et al., 2013). Biofilm formation on

the electrode surfaces results in a potential difference between the working electrode

and the reference electrode, and this is referred to as the OCP (Janknecht & Melo,

2003; Zheng et al., 2013). The OCP of the electrode is controlled by the oxidation and

reduction reactions arising between the electrode surface and the chemical species

dissolved in the liquid environment (Jeon et al., 2008).

53

Electrochemical impedance spectroscopy (EIS) is also a promising electrochemical

technique for monitoring biofilm formation, and can be used to detect intrinsic

electrical properties of microorganisms adhered to an electrode surface (Bayoudh et

al., 2008). Many microbial cells produce EPS composed of proteins, polysaccharides

and DNA (Flemming et al., 2007). These substances may contain electrochemically

active groups that can facilitate charge transfer. Charge transfer between the microbial

cell and the electrode surface plays an important role during initial microbial adhesion,

with free electrons being exchanged (Bayoudh et al., 2008). An EIS measurement

involves the application of an alternating current (AC), and monitoring of the

impedance and reactance of an electrode with its electrolyte (Marcotte & Tabrizian,

2008). The EIS data are commonly analysed by fitting the data to an equivalent circuit

model in which circuit parameters are used to describe the processes taking place in

the electrochemical system (Boukamp, 1986). For example, the Randles equivalent

circuit model consists of an active electrolyte resistance (RS) connected in series with a

parallel combination of a double-layer capacitance (C) and charge transfer resistance

(Rct) with a specific electrochemical element of diffusion (the Warburg element; W)

(Bonora et al., 1996).

Many studies have reported that biofilm formation can change the double layer

capacitance, charge transfer resistance and conductivity of an electrochemical system.

Kim et al. (2011) monitored biofilm formation on platinum disk electrodes and found

that adhesion of Pseudomonas aeruginosa to the electrode caused a reduction in the

double layer capacitance. Yang et al. (2004) investigated the influence of Salmonella

typhimurium on ITO (indium-tin-oxide)-coated interdigitated microelectrodes exposed

to milk, and reported that bacterial adhesion increased the double-layer capacitance

(at low frequency) of the electrodes and decreased the impedance. Bayoudh et al.

(2008) developed an ITO electrode using an EIS-based flow chamber to detect

Pseudomonas stutzeri and Staphylococcus epidermidis adhesion in a phosphate

buffered saline solution. They demonstrated that bacterial attachment to the

electrode increased the double layer capacitance and decreased the charge transfer

resistance. Although considerable research has been devoted to using EIS for

monitoring biofilm formation in the food industry, in seawater and in cooling water

systems, this method has not yet been applied to the drinking water industry.

54

In this study, the suitability of using OCP and EIS for real-time monitoring of biofilm

formation in drinking water was investigated. Specifically, the relationships between

electrochemical parameters and microbial cell counts (as a surrogate for biofilm

formation) were explored. The impacts of chlorine on both biofilm formation and the

electrochemical signals were also investigated.

3.2. Materials and Methods

3.2.1. Electrode preparation

Graphite rod electrodes (5 mm in diameter and 100 mm in length; Kaiyu Industrial Ltd.,

China) were used as the working electrodes on which biofilm formation occurred. For

each electrode, the length exposed to biofilm formation (50 mm) had a surface area of

800 mm2. Prior to the experiment, the electrodes were soaked in sodium hypochlorite

(20 mg L–1 total chlorine concentration) for 1 h to oxidise any organic material on the

electrode surface. The electrodes were then soaked three times (30 min each) in Milli-

Q water (Millipore, USA), and heated overnight in an oven at 75C to remove any

chlorine residues.

3.2.2. Incubation experiments

3.2.2.1. Biofilm formation and its effect on electrochemical properties

To facilitate biofilm formation, clean graphite electrodes (33) were incubated for 16

days in water collected from the Mundaring Weir drinking water reservoir. The

incubation experiment was performed in two identical incubation reactors (250 mL

glass beakers) in batch mode at 22 ± 2C. To prepare the incubation medium the water

was supplemented with nutrients (500 mg L–1 yeast extract) to expedite biofilm

growth. The incubation medium was continuously stirred (120 rpm) using a magnetic

stirrer (Labstir-1; Whatman) to ensure complete mixing. The beakers were covered

with aluminium foil to restrict phototrophic biological growth. The incubation medium

55

was refreshed daily to ensure continuous availability of nutrients for biofilm growth,

and to remove planktonic cells from the system.

From the 33 electrodes, two replicate electrodes were randomly removed daily over a

period of 8 days for electrochemical measurements and microbiological analysis (flow

cytometer cell counts). This facilitated investigation of the relationship between the

microbial parameters and the electrochemical signals. These electrodes were not

returned to the reactor following analysis. From the remaining electrodes, three

electrodes were removed for scanning electron microscopy examination at day 0, day

8, and day 9.

3.2.2.2. Effect of enrichment medium on electrochemical properties

Sterilised and non-sterilised control experiments were conducted to confirm whether

the changes in the electrochemical signals were due to biofilm attachment to the

electrodes (biofouling). For this experiment, 12 graphite electrodes cleaned as

described above (section 2.1) were sterilised by autoclave (Tuttnauer 5075 EL USA). As

a sterilised (abiotic) control for this experiment, dam water was filtered to remove

microbial cells (0.8/0.2 μm Supor Membrane), amended with yeast extract (500 mg L–

1), and autoclaved to ensure sterility. Six sterile electrodes were transferred

individually to 15 mL sterile Falcon tubes (IWAKI, Japan), to which the sterile dam

water medium with yeast extract was added. The abiotic control tubes were prepared

inside a laminar flow hood (Gelman Sciences HWS, Australia). The non-sterilised

(biotic) experiment was conducted in a similar fashion. Six cleaned (not sterile)

graphite electrodes were incubated in non-sterilised dam water amended with yeast

extract (500 mg L–1). The 12 Falcon tubes were covered and placed in an incubator

shaker (Innova 4330, USA) to mix the medium during the incubation. Subsequently,

two electrodes for biotic and two electrodes for abiotic were sacrificially sampled and

subjected to electrochemical and microbiological analysis at 0, 24 and 48 h.

56

3.2.3. Chlorine treatment

3.2.3.1. Effect of chlorine treatment on biofilm and electrochemical

properties

Chlorine has been successfully used in DWDSs as disinfectant to control the

undesirable effects of biofilms for nearly a century (Bull et al., 1995). To test the effect

of chlorination on biofilm, two electrodes with developed biofilm from the incubation

reactors were transferred on day 8 into a separate reactor containing Mundaring dam

water amended with sodium hypochlorite (in the absence of yeast extract) to give a

total chlorine residual of 4 mg L–1. This concentration was used to emulate a periodic

free chlorine dosing event (i.e. breakpoint chlorination), as customarily used in

chlorinated DWDSs (NHMRC & NRMMC, 2011). Electrochemical measurements (OCP

and EIS) for the electrodes exposed to chlorine residuals were carried out in dam water

medium (in the absence of chlorine and yeast extract) at 0, 1, 2, 3, 4 and 24 h. Total

chlorine concentrations of the incubation medium (Mundaring dam water amended

with sodium hypochlorite) were monitored during the course of the treatments.

Thereafter, the two graphite electrodes were returned to the incubation reactor (dam

water amended with 500 mg L–1 yeast extract) to again facilitate establishment of

biofilm. After an incubation period of seven days (day 15), the two graphite rods were

once again transferred to the chlorinated medium and exposed to chlorine as

described above. As before, OCP and EIS were measured along with total chlorine in

the dam water medium after 0, 1, 2, 3, 4, and 24 h.

3.2.3.2. Abiotic effect of chlorine on electrochemical properties

To test whether electrochemical parameters were influenced by chlorination, two

clean (non-sterile) graphite electrodes (section 3.2.1) were exposed to chlorinated

dam water for 24 h. Electrochemical parameters of the electrodes and the total

chlorine concentrations in the incubation medium were monitored at 0, 1, 2, 3, 4 and

24 h.

57

3.2.4. Analytical methods

3.2.4.1. Electrochemical measurements

Electrochemical measurements were performed in a three-electrode system

(electrochemical cell) using a potentiostat (SP-150 Biologic, France) as shown in Figure

3.1. The graphite rods were used as the working electrodes. A platinum wire (APS

Labware, Australia) and a silver/silver chloride (Ag/AgCl) reference electrode (MF-2079

Bioanalytical Systems) were used as the counter and reference electrodes,

respectively. The platinum wire was coiled around the reference electrode. A fixed

distance (14 mm) was maintained between the working and the reference/counter

electrodes (Figure 3.1). To represent drinking water conditions, Mundaring dam water

without yeast extract (50 mL) was used as the medium in the electrochemical cell

when carrying out the electrochemical measurements. To minimise the influence of

enrichment medium and also to remove any planktonic cells, the graphite rod

electrodes were gently rinsed with Milli-Q water prior to each measurement.

58

Figure 3.1. Schematic diagram of the electrochemical cell used for biofilm monitoring

on graphite electrodes. WE = working electrode (graphite), RE = reference electrode

(Ag/AgCl), CE = counter electrode (platinum wire).

The OCP of the graphite rod electrodes was measured immediately following

immersion into the electrochemical cell, and an OCP value for the graphite working

electrode was recorded after a fixed equilibration period of 30 s. EIS measurements

were conducted immediately following the OCP measurements, using a frequency

range of 100 kHz to 10 mHz and an AC voltage amplitude of 10 mV.

The impedance data were fitted to the Randles equivalent circuit model using the EC-

Lab software (Figure 3.2). The averages of the electrochemical parameters recorded

for the two replicate rods and standard deviations were plotted as a function of time.

59

Double layer capacitance (Cdl) is defined by Equation (6):

Cdl =εε0A/d (6)

where ε is the dielectric constant of the electrolyte, ε0 is the permittivity of free space,

A is the electrode area, and d is the thickness of the double layer capacitance (Kim et

al., 2011; Joung et al., 2012). To remove the influence of the electrolyte (i.e. from ε) on

capacitance, EIS measurements were carried out in fresh dam water during all

measurements. Hence, in this study the electrode area was the major contributor to

the change in capacitance.

Figure 3.2. Randles equivalent circuit model. Rs represents the solution resistance, Rct

represents the charge-transfer resistance, C refers to capacitance and W is the

Warburg element.

3.2.4.2. Water analysis

Total chlorine in water samples was measured following the method described by

Krishna et al. (2013) using a colorimeter (HACH, USA) and DPD (N,N-diethyl-p-

phenylenediamine) total chlorine reagent after calibration of the colorimeter using

sodium hypochlorite.

Rct

Rs

C

W

60

3.2.4.3. Flow cytometer cell counts

For counting microbial cells associated with the electrodes using flow cytometry, the

electrodes were first gently rinsed with Milli-Q water to remove planktonic cells. Each

electrode was then transferred into a 15 mL Falcon tube containing 5 mL of tap water

dechlorinated with 0.2 mg L–1 sodium thiosulphate. The tube was placed in a sonicator

(Bransonic 220, USA) for 5 min to dislodge the attached cells from the electrode. For

use as a control/blank, a dechlorinated tap water sample was filtered using a 0.8/0.2

μm syringe filter. Samples (200 µL) of the control/blank and unfiltered water were

stained using 2 µL of SYBR Green 1 (Invitrogen, USA). The stained samples were

incubated in the dark at room temperature 22 ± 2C for 15 min prior to quantification

of cells using flow cytometry (Cell Lab QuantaTM SC; Beckman Coulter, USA) equipped

with a 488 nm solid state laser. SYBR Green has excitation and emission maxima at 494

and 521 nm, respectively. Green fluorescence was collected in the FL1 channel (525 ±

20 nm) and was also used as the trigger. The data collected were processed using Cell

Lab Quanta Analysis software (Beckman Coulter). Microbial cell clusters were detected

using a plot of 90 red fluorescence (FL3) versus green fluorescence (FL1); electronic

gating was carried out to separate the cell clusters from noise. The quantification of

microbial cells was achieved by counting the number of events included inside the

corresponding gate.

3.2.4.4. Scanning electron microscopy

Three graphite electrodes including a clean electrode at day 0 (no biofilm), an

electrode coated with biofilm (day 8), and an electrode after chlorine treatment (day

9) were examined using a scanning electron microscope (SEM) (Philips XL30 SEM). The

electrodes were fixed in 1% formaldehyde and 3% glutaraldehyde for 3 h at 4C,

dehydrated for 15 min each in 70%, 90% and 100% ethanol, and coated with platinum

(5 nm) prior to SEM examination.

61

3.3. Results and discussion

3.3.1. Effects of microbial biofilms on electrochemical signals

3.3.1.1. OCP

While a positive shift in the OCP as a result of biofilm development has been reported

in most other studies (Xu et al., 2010; Sridharan et al., 2011; AlAbbas et al., 2013), a

negative shift in the OCP associated with biofilm growth was observed in the present

study (Figures 3.3A and 3.3E). On incubating for 8 days in the yeast extract amended

dam water, the electrode potential dramatically shifted from +118 mV to +20 mV

within the first day and gradually decreased to –158 mV at day 8 (Figure 3.3A). This is

consistent with the work of Santo et al. (2006), who also observed a negative shift in

the OCP of brass coupons in artificial and natural seawater, and suggested this was

most likely due to a decrease in the oxygen concentration in the medium. Armon et al.

(2001) also reported a decline in the OCP of titanium, platinum stainless steel,

aluminium alloy and mild steel coupons with Flavobacterium breve and Pseudomonas

fluorescens P17 bacteria present in natural water sources. Santoro et al. (2012) also

observed a dramatic decrease in OCP values over a period of one week following

exposure of an electrode to water, and suggested that the formation of biofilm on the

platinum electrode inhibited the capacity of the platinum (catalytic layer) to reduce

oxygen, resulting in a decrease in the OCP. Mittelman et al. (1992) suggested that the

change in the OCP in a series of laminar-flow adhesions cells could be related to pH,

oxygen concentration or reaction kinetics at the electrode surface. The decrease in

OCP observed in the present study could also be a result of the biofilm reducing

oxygen in the vicinity of the electrode.

62

Figure 3.3. Changes of OCP (A) and EIS parameters (imaginary impedance: B; real

impedance: C; and capacitance: D) during biofilm growth (E) on graphite electrodes.

A

B

C

D

D

E

E

63

3.3.1.2. EIS

3.3.1.2.1. Impedance measurement

In this study an EIS scanning frequency ranging from 100 kHz to 10 mHz was used. To

investigate the impedance of the electrochemical cell, the imaginary and real

impedances recorded at fixed frequencies (80 kHz, 100 Hz, 5 Hz and 20 mHz) were

plotted against time (Figures 3.3B and 3.3C). The results indicate that biofilm adhesion

did not affect the impedance of the graphite electrodes at 80 kHz, 100 Hz and 5 Hz

frequencies, but did affect the impedance of the graphite electrodes at 20 mHz. Yang

et al. (2004) monitored biofilm formation on ITO electrodes at a frequency range of 0.2

Hz to 100 kHz, and concluded that biofilm growth was best represented at low

frequency (< 100 Hz). In the present study the lower scanning frequency (20 mHz) also

clearly indicated changes relating to the formation and removal of biofilm at the

working electrode. As shown in Figure 3.3B, the imaginary impedance at 20 mHz

decreased markedly (42%) after 8 days. In contrast, a marginal increase (22%) was

observed in the real impedance at 20 mHz during biofilm development (Figure 3.3C).

Accordingly, relative to real impedance, imaginary impedance appears to be more

indicative of biofouling (Bayoudh et al., 2008).

3.3.1.2.2. Parameters derived from the equivalent circuit model

The impedance data were also fitted to the equivalent circuit model (Figure 3.2). In this

study, the solution resistance (Rs) did not change during biofilm growth on the graphite

electrodes, as identical aqueous media (fresh dam water) were used in every

measurement (Table 3.1). Chemical transformations occurring at the electrode surface

did not appear to affect the Rs component of the model (Bayoudh et al., 2008). The Rs

parameter was derived from the real impedance (i.e. horizontal axis) value at the high

frequency intercept in the Nyquist plot, and remained constant during the experiment

(Table 3.1). This indicated that the microorganisms attached to the graphite electrodes

had little impact on Rs (Kim et al., 2012).

Warburg impedance is associated with the diffusion of reactants between the bulk

electrolyte and the electrode (Joung et al., 2012). In this experiment, the Warburg

64

impedance increased very slightly from day 0 to day 8, indicating that there was little

diffusion of ions from the bulk electrolyte to the electrode (Table 3.1). Although

Warburg impedance is generally observed in the low frequency region (Randviir &

Banks, 2013), no specific trend with cell attachment to the graphite electrodes was

observed.

The change in capacitance was more pronounced, and consistent with biofilm growth

on the graphite electrodes. The capacitance of the electrodes increased from 17.1 mF

on day 0 to 30.5 mF on day 8 (Figure 3.3D). Relative to day 0, capacitance had

increased by 18% after one day, and by 79% after 8 days. Similarly, an increase in

capacitance was observed with biofilm development on graphite electrodes exposed

to seawater (Xu et al., 2010). Kim et al. (2011) reported that capacitance can be

correlated with the number of microorganisms attached to the electrode surface. It

has been reported that obstruction of the electrode surface (in this instance with

microorganisms) would increase the capacitance (Kim et al., 2011; Joung et al., 2012).

The charge transfer resistance (Rct) also varied during biofilm formation on the

graphite rod electrodes (Table 3.1). The Rct decreased from 9,144 ohm to 1,004 ohm

during the first 8 days of the experiment, indicating a decrease in electron transfer

resistance at the electrode, probably as a result of the presence of biofilm (Xu et al.,

2010). Bayoudh et al. (2008) also observed a decrease in Rct on ITO electrodes, and

concluded that bacterial cells can assist the transfer of electrons to the electrode,

increasing electron transfer and thereby decreasing the charge transfer resistance.

To investigate if there was a correlation between the cell numbers attached to the

graphite electrode and the various electrochemical parameters (OCP, capacitance, Rct,

imaginary and real impedance), a correlation analysis was carried out (Table 3.2). The

highest positive correlation (R2 = 0.977) was obtained with capacitance.

65

Table 3.1. Fitting values of the equivalent circuit model components during biofilm

formation on the graphite electrodes, and following chlorine treatment.

Table 3.2. Percentage change in electrochemical parameters at day 8 relative to day 0,

and the relationship between cell density and electrochemical parameters.

Time (day) Solution

resistance( Rs)

(ohm)

Charge transfer

resistance (Rct )(ohm)

Warburg

impedance (W

)(ohm)

0 (without biofilm) 176 ± 7 9021 ± 173 110 ± 62

8 (with biofilm) 175 ± 8 926 ± 58 135 ± 73

9 (after chlorination) 179 ± 5 7168 ± 266 112 ± 36

15 (with biofilm) 168 ± 5 3762 ± 59 215 ± 36

16 (after chlorination) 171 ± 2 7989 ± 105 195 ± 45

Electrochemical parameters

Percentage change (%) of

electrochemical parameters by

day 8 on a graphite electrode

R² values for the regression

line between biofilm cell

densities and

electrochemical parameters

Open circuit potential –234 0.713

Capacitance 89.1 0.977

Charge transfer resistance –78.1 0.589

Imaginary impedance –41.7 0.882

Real impedance 14.1 0.454

66

3.3.1.2.3. EIS spectrum

The electrochemical impedance spectra of the graphite rods at various time points are

presented in Figure 3.4 in the form of a Nyquist plot. The Nyquist plot shows the

relationship between the real impedance of the graphite rods plotted on the

horizontal axis and the imaginary impedance plotted on the vertical axis. The curves on

the Nyquist plot shifted to the right during the first 8 days of the experiment due to

the attachment of cells on the electrodes. The lower regions of the curves represent

the impedance measured at higher frequencies and the upper regions represent the

impedance measured at lower frequencies. In response to biofilm growth, a greater

shift was observed in the lower frequency region (from 800 mHz to 10 mHz) of the

curves, confirming that this frequency range better reflects microbial adhesion onto

electrode surfaces.

67

Figure 3.4. The electrochemical impedance spectra of the graphite electrodes over a

frequency range of 100 kHz to 10 mHz at various time points; the Nyquist plot shows

the relationship between the real impedance (Zre) and the imaginary impedance (Zim).

Day 0 shows no biofilm on electrode; Days 1 to 8 represent colonisation of biofilm on

electrode and the impact after chlorination is shown on day 9.

3.3.1.2.4. Contribution of cells in a biofilm to the electrochemical signals

As a marked change in some electrochemical parameters was observed after two days

of incubation (Figure 3.3), a control experiment was conducted to confirm whether the

changes observed were caused by biofilm formation. The OCP decreased in the non-

sterile system within the two day period, whereas the OCP remained steady in the

sterile control (Figure 3.5A). A similar observation was made for the imaginary

impedance, real impedance, capacitance, and charge transfer resistance (Figures 3.5B,

3.5C, 3.5D and 3.5E). However, an increase in cell density was observed in the non-

sterile system over two days of exposure (Figure 3.5F). Hence, the observed

electrochemical changes were caused by the presence of biofilm on the electrode.

0

300

600

900

1200

150 250 350 450 550

-Zim

(oh

m)

Zre(ohm)

Day 0 (without biofilm)

Day 1 (with biofilm)



Day 9 (after chlorination)

68

Figure 3.5 Changes in OCP (A), EIS parameters (imaginary impedance: B; real

impedance: C; capacitance: D; and charge transfer resistance: E) at 20 mHz, and cell

density (F) on a graphite electrode in the abiotic and biotic systems.

-200

-100

0

100

200

OC

P (

mV

Ag

/Ag

Cl)

Abiotic system Biotic system

0

200

400

600Im

agin

ary

imp

ed

ance

(o

hm

)

0

10

20

Cap

acit

ance

(m

F) 0

100

200

300

Re

al im

pe

dan

ce

(oh

m)

0.0E+00

6.0E+06

1.2E+07

1.8E+07

2.4E+07

0 1 2

Ce

ll d

en

sity

(ce

llscm

¯²)

Time (d)

0

4000

8000

12000

Ch

arge

tra

nsf

er

resi

stan

ce (

oh

m)

F

E

A

B

C

D

69

3.3.2. Chlorine as a disinfectant

3.3.2.1. Impact of chlorine on biofilm and the electrochemical signals

Following biofilm formation for 8 days on the graphite electrodes, the biofilm was

exposed to chlorine. The impact of this chlorination event on electrochemical

parameters is shown in Figure 3.6.

Following chlorination of the electrodes on day 8, all electrochemical parameters

returned to approximately baseline values measured on day 0 except the real

impedance (Figure 3.6). Specifically, the OCP and imaginary impedance values

increased (Figures 3.6A and 3.6B) while the capacitance decreased (Figure 3.6D).

Additionally, the curves in the Nyquist plot shifted to the left (Figure 3.4), approaching

the position recorded on day 0 (without biofilm). Other parameters of the equivalent

circuit model also responded to chlorination (Table 3.1). Following chlorination on day

8, the graphite electrodes were returned to the incubation medium for another 8 days

to facilitate redevelopment of biofilm on the electrode surface. During days 8 to 15 the

electrochemical parameters showed similar trends to those observed during the initial

period of biofilm development (days 0–8; Figure 3.6).

Both the flow cytometer cell counting and SEM imaging confirmed that chlorination

effectively removed the biofilm from the graphite electrodes (Figure 3.7). On day 8,

the microbial cell density on the graphite was approximately 3.5 × 107 cells cm–2,

indicating extensive biofilm growth (Figure 3.7A). However, following the chlorine

treatment the cell density decreased to 1.5 × 106 cells cm–2 within one day (Figure

3.7A). No biofilm was observed on the graphite electrode when examined using SEM at

day 0 (Figure 3.7B), but clear colonisation was observed on day 8 (Figure 3.7C). The

SEM imaging on day 9 (following chlorination for 24 h) indicated a near complete

removal of biofilm from the graphite surface (Figure 3.7D). The residual cell counts

recorded following chlorination can be attributed to the non-uniformity or porosity of

the graphite (La Mantia et al., 2008), as evident in the SEM images (Figure 3.7). The

finding suggests that the chlorine concentration (4 mg L–1) typically used for

breakpoint chlorination may not completely remove microbial cells from the inner wall

of a water distribution pipeline if it has a high degree of surface porosity.

70

Figure 3.6. Effect of chlorination on the OCP (A) and EIS parameters (imaginary

impedance: B; real impedance: C; and capacitance: D) on the graphite electrodes

during the biofilm growth experiment. The dashed vertical lines indicate application of

chlorine (4 mg L–1) for 24 h. The impedance data were obtained at a frequency of 20

mHz.

71

Figure 3.7. Effect of chlorine treatment on biofilm cell numbers. (A) Cell density at day

0, day 8 before chlorination, and day 9 after chlorination. Scanning electron

microscopic images at (B) day 0, (C) day 8, and (D) day 9.

3.3.2.2. Effect of chlorine on the electrochemical signals

To investigate whether chlorine had an influence on electrochemical signals, an

experiment comparing two electrodes with developed biofilm (biotic system) with two

clean graphite electrodes (abiotic system) was carried out using the chlorinated dam

water (Figure 3.8). The results showed that the presence of chlorine only had an effect

on some electrochemical parameters measured. Specifically, the increase in OCP in the

abiotic system indicated that chlorine had a direct influence on OCP (Figure 3.8A). Real

impedance was also impacted by chlorine, with a negative trend being observed in the

abiotic system. However, both capacitance (14 ± 2 mF) and imaginary impedance

(1407 ± 81 ohm) were independent of chlorine under abiotic conditions.

During the 24 h experiment, cell densities in the biotic system decreased from 3.5 ×

107 cells cm–2 to 1.5 × 106 cells cm–2, with chlorine consumption of approximately 3.94

mg L–1 (Figures 3.8E and 3.8F). Both capacitance and imaginary impedance responded

72

to the removal of cells from the electrode surface; capacitance decreased from 23.2

mF to 15.8 mF, and imaginary impedance increase from 308 ohm to 517 ohm. The

decrease of the chlorine residual in the biotic system was largely a result of oxidation

of the biofilm and autodecomposition of chlorine. On the other hand, the chlorine

decay in the abiotic system was a result of autodecomposition only (Hallam et al.,

2002). This explains the higher chlorine residual in the abiotic system at the end of the

24 h period.

Overall, the results suggest that capacitance is a suitable electrochemical parameter

for measuring cell densities on graphite electrode surfaces, and most importantly it is

not affected by the presence of chlorine residual in the bulk water medium.

73

Figure 3.8. Changes of OCP (A), EIS parameters (imaginary impedance: B; real

impedance: C; and capacitance: D; at 20 mHz) with or without biofilm in abiotic and

biotic systems. Changes of cell density (E) and total chlorine concentration (F) of

graphite electrode with or without biofilm during the chlorination.

74

3.3.3. Capacitance was the most suitable electrochemical parameter for

monitoring biofilms

An electrochemical signal useful for monitoring biofilm formation should show

linearity with cell density and undergo a large change in signal for a small change in cell

density. Based on Table 3.2, the electrochemical parameters suitable for detecting

small changes in cell density were OCP, charge transfer resistance and capacitance,

with capacitance being the most promising as it showed the greatest linearity with cell

density (R2 = 0.977). Although the percentage change in OCP was almost a factor of

two higher than that of capacitance, the linearity between cell density and OCP was

less than that for capacitance. Imaginary impedance showed good linearity with

change in cell density, but was not responsive to small changes in cell density.

3.4. Conclusions

This study demonstrated the use of graphite electrodes and EIS for monitoring biofilm

formation and removal. The study showed that graphite is a suitable substrate for

biofilm monitoring in DWDSs. Electrode capacitance derived from an EIS equivalent

circuit model was a suitable indicator of biofilm formation and detachment on the

graphite electrodes. The adhesion and detachment of microbes to the electrode

surface also impacted the imaginary impedance of the system, when assessed using a

low frequency (20 mHz). Chlorine treatment was effective in removing biofilm from

the electrodes, and neither capacitance nor imaginary impedance was affected by

residual chlorine in the bulk medium.

The method could be used to optimise disinfectant dosing and thereby potentially

reduce the formation of undesirable DBPs in DWDSs. Further studies should focus on

optimising the sensitivity of the method and evaluation of other electrode materials.

75

4. Assessing graphite and stainless steel electrodes for

biofilm monitoring in chlorinated drinking water systems

4.1. Introduction

According to the drinking water guidelines released by the World Health Organization

(2004), it is a regulatory requirement for water utilities to monitor the microbial

quality of water in DWDSs. However, water utilities usually only do this based on bulk

water samples, because collecting biofilm samples in DWDSs is difficult. Given that in

excess of 95% of all biomass in water distribution systems is in pipe wall biofilms

(Flemming et al., 1998), an effective strategy to monitor biofilm development on the

pipe inner surfaces in a DWDSs is highly desirable.

On-line monitoring of biofilm formation on pipe inner surfaces can be assessed using

electrochemical, optical or piezoelectric sensors (Delille et al., 2007). Munoz-Berbel et

al (2006) used impedance measurement to monitor biofilm formation in a bioreactor

containing a medium to which P. aeruginosa had been added, and evaluated the

capacity of several disinfectants (strong acids and bases, ethanol and peroxide

solutions) to remove the biofilm structure from gold chips. However no studies have

assessed the change in the electrochemical parameters that model biofilm formation

after chlorine treatment in DWDSs, and no electrochemical on-line biofilm monitoring

devices are commercially available for deployment in chlorinated or chloraminated

DWDSs. However, electrochemical sensors have been developed to monitor biofilm

development in other systems, including cooling water systems in power plants (Bruijs

et al., 2001). Commercial electrochemical biofilm monitoring devices including

BioGEORGETM have been developed to manage microbially-induced corrosion in pipes.

However, the application of electrochemical sensors for biofilm monitoring has not yet

been embraced by the drinking water industry.

Over the last 20 years, a number of electrochemical techniques have been used to

analyse aquatic samples (Taillefert et al., 2000). However, for biofilm monitoring two

electrochemical methods (open circuit potential; OCP and electrochemical impedance

spectroscopy; EIS) have shown promise (Kim et al., 2012). The non-destructive nature

76

of these two techniques makes them highly advantageous for real-time monitoring of

biofilm development (AlAbbas et al., 2013).

Microbial attachment and biofilm development have been extensively investigated

using EIS (Yang et al., 2004; Munoz-Berbel et al., 2008; Ward et al., 2014). An EIS

measurement for an electrode with its electrolyte involves the application of AC

frequencies and the monitoring of resistance and reactance. The electrode material

and the composition of the media determine the ability of the electrode to exchange

electrons with the electrolyte. Past studies have assessed various materials, including

noble metals (e.g. platinum, gold and silver), mercury, carbon and semiconductor

materials including ITO and Ti (Schmidt et al., 2006; Bayoudh et al., 2008; Li & Miao,

2013) for their suitability as electrode materials for monitoring biofilm development.

However, none of these studies were carried out in aqueous environment exposed to

disinfectants including chlorine and chloramines. The abiotic impact of disinfectants on

the response of a sensor is an important factor governing its applicability in DWDSs.

Graphite and stainless steel are chemically inert and inexpensive materials. Both have

been used as electrodes, and graphite in particular has been widely used in

electrochemical studies that involve bacterial growth (Logan, 2008). Stainless steel has

been largely used in food, pharmaceutical and chemical industries, particularly

because of its corrosion resistance and mechanical robustness (Dumas et al., 2008a;

Dadafarin et al., 2013) and graphite electrodes have commonly been used in fuel cells,

batteries and in other electrochemical applications (Chakrabarti et al., 2013). However,

biofilm studies using graphite and stainless steel electrodes have been limited to

seawater and wastewater environments, rather than in drinking water environments

(Xu et al., 2010; Yu et al., 2011), and no comparative study has been conducted to

investigate the electrochemical properties of biofilm formed on different electrode

materials in drinking water.

The aim of this study was to investigate the use of graphite and stainless steel

electrodes for detection of biofilms in drinking water environments. Using these

electrodes, EIS and OCP measurements were carried out and correlated with

parameters related to biofilm growth (cell counts based on flow cytometry, and

measurements of ATP concentrations). The electrochemical parameters and the

77

biofilm growth indicators were compared in relation to the two electrode materials. A

specific focus was to assess which electrochemical parameter best reflected biofilm

growth on the two electrode materials. The impact of chlorine on the electrochemical

measurement was determined to assess the applicability of the method in chlorinated

DWDSs. The sensitivity of the electrode materials in detecting various bacterial cell

densities was also investigated.

4.2. Materials and methods

4.2.1. Preparation of sensor electrodes

Graphite (KAIYU Industrial LTD) and stainless steel (grade 316) rods with identical

geometric dimensions (length 100 mm, diameter 5 mm) were used as electrodes in

this study. Approximately half of the surface area of each electrode was insulated with

electrically non-conductive material, leaving an area of 800 mm2 exposed to the bulk

medium. All electrodes were initially immersed in sodium hypochlorite solution (20 mg

L–1 total chlorine concentration) for 1 h to oxidise any organic matter present,

including biomass. Subsequently, the electrodes were immersed three times

consecutively for 30 min in fresh Milli-Q water. Prior to use in experiments, the

electrodes were placed in an oven at 75 C for 48 h to remove any residual chlorine.

4.2.2. Biofilm development on electrode surfaces, and analytical procedures

The electrodes were incubated in Mundaring reservoir dam water. The indigenous

microorganisms in the dam water were used as the microbial inoculum to initiate

biofilm formation on the electrode surfaces. The experiment was carried out at 22 ± 2

C in batch mode in an incubation reactor comprising two beakers, each containing 24

electrodes (12 of graphite and 12 of stainless steel). The electrodes in each beaker

were mounted in a plastic holder placed on top of a 250 mL glass beaker (the reactor)

containing 240 mL of medium, such that the test surface of each electrode was

immersed in the medium (Figure 4.1). The medium in each beaker was continuously

stirred at a fixed stirring speed (120 rpm) using a magnetic stirrer to facilitate oxygen

78

transfer and ensure homogeneity of the medium. Each beaker was covered with

aluminium foil to minimise the growth of phototrophic microorganisms. The

incubation was continued for 16 days. The medium was replaced daily to minimise the

accumulation of suspended microorganisms.

The dam water used in the experiments has the following general properties: dissolved

organic carbon: 2.7 to 3.2 mg L–1, analysed using a TOC analyser (Sievers 5310C,

Boulder, Colo.); pH: 7.6–8.4, analysed using a HACH 40d pH meter and probe

(PHC101); ammonia: below detection limit; nitrite: 0.0 to 0.004 mg-N L–1; and nitrate:

0.02 to 0.06 mg-N L–1. The three inorganic nitrogen species were analysed using an

Aquakem 200 photometric analyzer (Thermo Scientific, USA). The incubation water

was supplemented with 2 g L–1 yeast extract to expedite biofilm formation.

Figure 4.1. Schematic diagram of the incubation reactor and electrochemical

measurement system (not to scale). WE = working electrode (graphite and stainless

steel), RE = reference electrode (Ag/AgCl), CE = counter electrode (platinum wire).

4.2.3. Measurement of electrode electrochemical properties

Each day up to day 8 during the experiment, two electrodes were chosen at random

and removed from the reactor for electrochemical and microbiological analyses; these

electrodes were not returned to the reactor following analysis. Prior to carrying out

any measurement, the electrodes were gently rinsed with Milli-Q water to remove

Graphite rodStainless steel rod

MediumPC

Potentiostat

WECERE

Biofilm

Stirrer

Biofilm

MediumStirrer

Measurement systemReactor

79

unattached cells and incubation medium. Subsequently, the electrochemical

properties of the rinsed electrodes were measured using a three-electrode

electrochemical cell (working volume 50 mL) connected to a potentiostat (SP-150

Biologic, France) (Figure 4.1). The cell comprised a silver/silver chloride (Ag/AgCl)

reference electrode (RE) (MF-2079; Bioanalytical Systems), a platinum wire (0.1 mm

diameter; APS Labware, Australia) counter electrode (CE), and the graphite or stainless

steel electrode as the working electrode (WE). The CE was coiled around the RE, and a

fixed distance (14 mm) was maintained between the WE and both the combined RE/CE

during all electrochemical measurements. Dam water (50 mL) was used as the

electrolyte, which was constantly stirred at a fixed speed (80 rpm) using a magnetic

stirrer.

The OCP and EIS measurements of the WE were carried out using the potentiostat. The

OCP was recorded when a stable reading was achieved. The impedance measurements

between 100 KHz and 10 mHz were carried out at an AC voltage of 10 mV. Impedance

data were analysed using EC-Lab software (Biologic, France). The Randles equivalent

circuit model was used to fit the EIS data (AlKharafi & Badawy, 1997). The components

in the equivalent circuit model are active electrolyte resistance (RS), double-layer

capacitance (C), charge transfer resistance (Rct), and the specific electrochemical

element of diffusion (termed the Warburg element; W) (Figure 4.2). Each

measurement was performed in duplicate, and the averages and standard deviations

reported for each time were determined from the measurements made for the two

replicate electrodes.

80

Figure 4.2. Equivalent circuit for describing microbial attachment to and detachment

from the graphite and stainless steel electrodes. Rs = solution resistance, Rct = charge-

transfer resistance, C = capacitance and W = Warburg impedance.

4.2.4. Microbiological analysis

On completion of electrochemical measurements, each biofilm electrode was placed in

a 15 mL Falcon tube containing 5 mL of dechlorinated tap water. The Falcon tube was

placed in an ultrasonic water bath (Bransonic 220, USA) for 5 min to dislodge the

biofilm from the electrode surface. The resulting 5 mL cell suspension was analysed for

microbial activity using ATP analysis, and microbial cell numbers were determined

using flow cytometry. All microbiological analysis were carried out in duplicate, and the

averages and standard deviations reported for each time were determined from the

measurements made for the two replicate electrodes

4.2.4.1. ATP analysis

ATP measurements were conducted following the method described by Ginige et al.

(2011). Total ATP was measured using the Promicol Biomass Detection Kit (Cat. # 360-

0208) and a Celsis Biocounter M 1500 luminometer (Lumac, Netherlands). For each

analysis, freshly prepared ATP standards (10, 100, 500 and 1000 ng mL–1) were used to

derive a calibration curve for estimating the ATP concentration in the samples. To

measure the ATP concentration in each cell suspension, a 100 µL aliquot of suspension

was transferred into an Eppendorf tube, and 100 µL of Promex M reagent was added

to release ATP from the cells. Thereafter, 100 µL of Prolux reagent was added to

Rct

Rs

C

W

81

catalyse the conversion of ATP into light energy via oxidation–reduction activation. The

luminescence in the tube was immediately measured using the luminometer, and the

value obtained was applied to the standard curve to determine the ATP concentration

in the sample.

4.2.4.2. Flow cytometer cell counts

For flow cytometry measurements, an aliquot of dam water filtered through a 0.8/0.2

μm syringe filter (Millipore, Australia) was used as a control/blank. Where necessary,

samples were diluted just prior to measurement using filter sterilised dam water to

achieve a cell density suitable for flow cytometer counting. The detection limit of the

flow cytometer (FC; Cell Lab QuantaTM, Beckman Coulter, USA) was 103 cells mL–1. For

each sample, an aliquot of the cell suspension (200 μL) was mixed with 2 µL of SYBR

Green 1 (10 concentrated; Invitrogen, USA) and incubated in the dark at room

temperature (22 ± 2 C) for 15 min to stain the cells. The cell density in the sample was

measured in the FC fitted with a 22 mV solid state laser emitting light at a wavelength

of 488 nm. SYBR Green 1 has excitation and emission maxima at 494 and 521 nm,

respectively. Green fluorescence was collected at 525 nm. The FC data were processed

using Cell Lab Quanta Analysis software (Beckman Coulter, USA).

4.2.5. Chlorine treatment

To investigate the impact of disinfection on the electrochemical parameters of the

electrode and the biofilm growth indicators, two graphite and two stainless steel

electrodes with developed biofilm were withdrawn from the incubation reactor on day

8 and transferred into a separate reactor containing Mundaring dam water amended

with sodium hypochlorite (in the absence of yeast extract) to give a total chlorine

residual of 4.4 mg L–1. This chlorine residual concentration was used to emulate a

periodic free chlorine dosing event (i.e. breakpoint chlorination), as customarily used

in chlorinated DWDS. Electrochemical parameters for the electrodes exposed to the

chlorine residual, and the total chlorine concentration in the electrolyte, were

measured at 0, 1, 2, 3, 4 and 24 h (the electrodes were removed to make the

82

electrochemical measurements and returned to the reactor), and at 24 h

microbiological analysis (ATP concentration and flow cytometer cell counts) were

carried out. After the microbiological analysis, the two electrodes were returned to the

incubation reactor to again facilitate biofilm growth for a further 8 days, during which

daily electrochemical measurements were carried out (electrodes were removed for

measurement, then returned to the reactor). On day 15, these electrodes were again

exposed to dam water amended with a chlorine residual of 4.4 mg L–1. Electrochemical

measurements on these electrodes, and measurements of the total chlorine

concentration in the electrolyte, were again conducted at 0, 1, 2, 3, 4 and 24 h.

As a control, pre-cleaned (non-biofouled) graphite and stainless steel electrodes were

exposed in duplicate to dam water containing a chlorine residual of 4.4 mg L–1 for 24 h.

Electrochemical measurements on these control electrodes, and measurements of the

total chlorine concentration in the electrolyte, were conducted at 0, 1, 2, 3, 4 and 24 h.

4.2.6. Abiotic incubation to investigate the effect of the medium on

electrochemical parameters

A separate experiment was conducted to assess the abiotic effect of the incubation

medium on the electrochemical parameters. Six pre-cleaned (using sodium

hypochlorite) graphite and stainless steel electrodes were autoclaved at 121 C for 20

min (Tuttnauer 5075 EL, USA). Each electrode was then aseptically transferred into a

15 mL sterile Falcon tube, which contained a filter-sterilised dam water (0.8/0.2 μm

syringe filter, Millipore, Australia). As in the biotic incubation experiment (Section 4.2),

the dam water was amended with 2 g L–1 sterile yeast extract. As a biotic control for

this experiment, six graphite and stainless steel electrodes were treated and incubated

in a similar fashion as the abiotic treatment, except that non-sterilised dam water was

used as the medium. The falcon tubes were covered and placed in an incubator shaker

(Innova 4330, USA) to homogenise the medium during the incubation. The experiment

was carried out inside a laminar flow hood (Gelman Sciences HWS, Australia). At 0, 24

and 48 h, two electrodes of each type were sacrificially sampled and subjected to

electrochemical and microbiological analysis.

83

4.3. Results and discussion

4.3.1. Biofilm formation and its effect on electrochemical properties of

graphite and stainless steel electrodes

Over the first four days of the incubation experiment, the cell densities and ATP

concentrations for both the graphite and stainless steel electrodes increased rapidly,

then gradually increased to a maximum level of approximately 3 × 107 cells/cm2 and 8

× 103 μg/cm2, respectively, by day 8 (Figure 4.3A and 4.3B). Within 24 h following the

chlorination treatment on day 8, the cell densities and ATP concentrations decreased

notably (1 × 106 cells/cm2 and 8 × 102 μg/cm2, respectively) (Figure 4.3A and 4.3B). This

rapid reduction in microbial activity confirmed that the chlorination treatment

effectively interfered with microbial survival and activity in the biofilm on each of the

electrode types. Following removal of the electrodes from the chlorine-containing

medium and replacement with fresh medium on day 9, both the graphite and stainless

steel electrodes were again colonised by microbes between day 9 and day 15. A

second chlorination treatment on day 15 produced a similar rapid decrease in cell

densities and ATP concentrations (Figure 4.3A and 4.3B). The changes in various

electrochemical parameters of the two electrode materials were recorded over the

same period, and the results are discussed below.

84

Figure 4.3. Changes in biological (A and B) and electrochemical parameters (C to G) for

the graphite and stainless steel working electrodes during the incubation experiment.

Vertical dotted lines indicate chlorination events on days 8 and 15 (approximately 4.4

mg Cl2 L–1). The imaginary and real impedances were recorded at an EIS frequency of

20 mHz.

4.3.2. Changes in OCP

In general, the OCP of both the graphite and stainless steel electrodes decreased with

an increase in microbial surface fouling (Figure 4.3C). During the initial 8 days, the OCP

of the graphite and stainless steel electrodes decreased from +63.5 mV to –149 mV

and from +3.5 mV to –241 mV, respectively (Figure 4.3C). Typically, biofouling leads to

an increase in OCP (i.e. electrode ennoblement) in aerobic aqueous environments

(Nguyen et al., 2007). Here, the decrease in OCP indicates a shift towards more

reduced conditions, which was probably a consequence of microbial-driven oxygen

depletion in the vicinity of the electrode (Pocaznoi et al., 2012). Chlorine treatment on

day 8 caused a rapid increase in the OCP for each electrode type to +108 mV and +5

mV for the graphite and stainless steel electrodes, respectively (Figure 4.3C). With re-

A

B

C

D

E

F

G

chlorination chlorination chlorination chlorinationGraphite Stainless steel

0.0E+00

1.0E+07

2.0E+07

3.0E+07

4.0E+07

Ce

ll d

en

sity

(ce

lls/

cm²)

Graphite Stainless Steel

0.0E+00

4.0E+03

8.0E+03

AT

P(n

g/c

m²)

-300

-150

0

150

0 2 4 6 8 10 12 14 16

OC

P(m

V A

g/A

gC

l)

Time (d)

0.0

0.5

1.0

1.5

2.0

0

15

30

45

Ca

pa

cita

nce

(mF

)

Ca

pa

cita

nce

(mF

)

0

20000

40000

60000

80000

0

3000

6000

9000

Ch

arg

e t

ran

sfe

r re

sist

an

ce (o

hm

)

Ch

arg

e t

ran

sfe

r re

sist

an

ce (o

hm

)

0

7000

14000

21000

0

200

400

Ima

gin

ary

im

pe

da

nce

(o

hm

)

Ima

gin

ary

im

pe

da

nce

(o

hm

)0

4000

8000

12000

0

150

300

450

0 2 4 6 8 10 12 14 16

Re

al

imp

ed

an

ce (o

hm

)

Re

al

imp

ed

an

ce (

oh

m)

Time (d)

85

development of surface fouling following this initial exposure to chlorine, there was a

reduction in the OCP for both electrode types. Similar observations were made

following the second chlorination event, on day 15 (Figure 4.3C).

4.3.3. EIS spectra and changes in capacitance and charge transfer resistance

The Nyquist plots obtained from the EIS measurement with the graphite and stainless

steel electrodes during biofilm formation and after chlorine treatment are illustrated in

Figure 4.4. The curves in the Nyquist plot for both graphite and stainless steel

electrodes shifted to the right over 8 days indicating biofilm formation on the

electrodes (Figure 4.4A and 4.4B). Following the chlorine treatment on day 9, the

curves in the Nyquist plot shifted to the left (Figure 4.4A and 4.4B), approaching the

position recorded on day 0 (without biofilm). To quantify the effect of biofilm

formation on the electrochemical properties of the two electrode materials, the

Nyquist plots were further analysed using equivalent circuit model fitting to derive

additional parameters such as capacitance and charge transfer resistance.

86

Figure 4.4. The electrochemical impedance spectra of the graphite and stainless steel

electrodes over a frequency range of 100 kHz to 10 mHz at various time points; the

Nyquist plot shows the relationship between the real impedance (Zre) and the

imaginary impedance (Zim). Day 0 represents no biofilm on the electrode; Days 1 to 8

represent colonisation of biofilm on the electrode, and the impact after chlorination is

shown on day 9.

Biofilm formation usually involves excretion of EPS (Flemming et al., 2007). These

substances may contain electrochemically active groups that can facilitate charge

transfer between microbial cells and the electrode surface (Bayoudh et al., 2008).

Further, microbial cells may possess intrinsic conducting and dielectric properties that

may affect charge transfer resistance and capacitance of an electrode (Bayoudh et al.,

2008).

Prior to surface fouling the background capacitances of the graphite and stainless steel

electrodes were significantly different (a factor of 120), with averages of 3.0 and 0.025

mF/cm2, respectively. It was expected that the electrodes would have different

electrochemical properties, including capacitance. For instance, Zeng et al. (2003)

compared the capacitance of graphite and platinum, and found that the capacitance of

the former (3–60 mF/cm2) was almost a factor of 1000 higher than that of platinum

(0.02–0.04 mF/cm2). Nevertheless, the suitability of an electrode material for biofilm

0

300

600

900

0 100 200 300 400 500

-Zim

(oh

m)

Zre (ohm)

Day 0 (without biofilm) Day 3 (with biofilm)

Day 8 (with biofilm) Day 9 (after chlorination)

0

9000

18000

27000

36000

45000

0 5000 10000 15000 20000

BA

Graphite Stainless steel

87

detection will depend on whether it can generate a measurable electrochemical signal

that is indicative of biofilm growth.

In the present study, the capacitance of the electrodes increased over the first 4 days

of the experiment and remained stable until the first chlorination event on day 8

(Figure 4.3D). Over this period, the capacitance increased from 25 mF to 40 mF and

from 0.2 mF to 1.9 mF for the graphite and stainless steel electrodes, respectively.

These trends were similar to those for the cell density and ATP concentration (Figure

4.3A and B), suggesting that the increase in capacitance was related to microbial

attachment to the electrodes. This result is consistent with a number of previous

studies. For example, using gold electrodes, Malavankar et al. (2012) observed an

increase of two orders of magnitude in capacitance during biofilm formation. Yang et

al. (2006) monitored microbial growth on an interdigitated microelectrode (IME), and

showed a 33% increase in capacitance (from 397.2 nF to 528.2 nF) resulting from

microbial adhesion. Bayoudh et al. (2008) found that as the density of cells of P.

stutzeri increased on ITO electrodes to approximately 3 × 106 cells/cm2, there was an

increase of capacitance from 62.86 μF to 67.65 μF; for S. epidermidis the capacitance

increased from 62.86 μF to 66.80 μF. In our study, following chlorine treatment on day

8, the capacitance of both electrode types decreased within 24 h towards their

respective baseline levels (Figure 4.3D). Following removal from the chlorine

treatment and return to non-chlorinated medium, the capacitance of both electrode

types increased again, most likely related to the surface fouling, as previously

observed. The second chlorine treatment (on day 15) resulted in a similar rapid

decrease of capacitance (Figure 4.3D).

Microbial fouling of the graphite and stainless steel electrodes resulted in a marked

decrease in the charge transfer resistance (Rct) (Figure 4.3E). Following chlorination on

day 8, the Rct values for the graphite and stainless steel electrodes increased and

approached the day 0 values. The re-occurrence of surface fouling from day 9 to day

15 again resulted in a decrease in Rct, and the chlorination on day 15 resulted in an

increase of Rct, as occurred on day 8. Numerous other studies have reported similar

phenomena. For example, Cheng et al. (2009) and Moradi et al. (2014) observed a

decrease in Rct on stainless steel electrodes, and Xu et al. (2010) observed a decrease in

Rct on graphite electrodes triggered by the growth of marine biofilms.

88

4.3.4. Changes in impedance

In the use of EIS, low frequencies (< 100 Hz) has been reported to be the most suitable

for analysing the attachment of biofilms (Paredes et al., 2012). At frequencies < 100 Hz

the electrode impedance is mostly influenced by microbial growth, while at high

frequencies (100–10,000 Hz) impedance is largely influenced by the effect of the

medium (Hause et al., 1981; Yang & Bashir, 2008). Yang et al. (2006) were able to

monitor microbial growth on ITO electrodes using low frequencies (1–10 Hz), but were

unable to monitor changes with frequencies higher than 100 Hz. Bayoudh et al. (2008)

observed a decrease in imaginary impedance and an increase in real impedance at a

fixed low frequency of 150 mHz on indium tin oxide (ITO) electrodes during biofilm

formation. In the present study, the imaginary and real impedances of each of the

electrode materials were recorded at 20 mHz (low frequency), and were used to

construct the time profile over the period of biofilm formation (Figure 4.3F and 4.3G).

As the biofilm grew over time, the imaginary impedance of both graphite and stainless

steel electrodes decreased (Figure 4.3F), but the decrease was more pronounced on

stainless steel than on graphite. Similar trends were recorded for real impedance with

each electrode type (Figure 4.3G). Removal of biofilm following chlorination (day 8)

resulted in an increase in both the imaginary and real impedance for both electrode

types (Figure 4.3F and 4.3G). The regrowth of biofilm thereafter resulted in a decrease

in real and imaginary impedance, indicating that the observed responses were

reproducible.

4.4. Capacitance was the most suitable parameter for detecting biofilm

formation on graphite and stainless steel electrodes

Overall, the results suggest that the formation and removal of biofilm led to

measurable changes in all the electrochemical parameters (OCP, capacitance, charge

transfer resistance, imaginary and real impedance) associated with both the graphite

and stainless steel electrodes. To determine which parameters were suitable for

quantitative detection of biofilm formation, the correlation coefficients of linear

regression trend lines plotted against the cell densities on each electrode material

89

were determined (Figure 4.5). Capacitance was the most suitable indicator, as it was

linearly correlated to attached cell numbers for both the graphite and stainless steel

electrodes (R2 > 0.94); comparatively weak correlations (R2 < 0.83) with cell density on

the electrode surface were found for the other electrochemical parameters measured

(Figure 4.5). The fact that electrode capacitance was sensitive to biofilm formation and

degradation has also been noted by Muñoz-Berbel et al. (2008). Hence, capacitance

was selected to further evaluate which electrode material would give the best

electrochemical response to biofilm formation.

90

Figure 4.5. Correlation between various electrochemical parameters and cell density

for the graphite or stainless steel electrodes. The R2 values are correlation coefficients

for the respective linear regression trend lines (the bold lines and values are for the

stainless steel electrodes).

R² = 0.9707

R² = 0.9499

0

0.5

1

1.5

2

2.5

20

25

30

35

40

45

R² = 0.7217

R² = 0.4834

-350

-250

-150

-50

50

R² = 0.7189

R² = 0.5579

0

20000

40000

60000

02000400060008000

R² = 0.8393

R² = 0.5209

0

10000

20000

0

200

400

R² = 0.3188

R² = 0.614

0

10000

20000

0

50

100

150

200

0.0E+00 1.0E+07 2.0E+07 3.0E+07 4.0E+07

Cell density (cells/cm2)

Stainless steelGraphite

Real impedance

mV

Ag/

AgC

l

Gra

ph

ite

/ St

ain

less

ste

el

mF

oh

m

oh

mo

hm

oh

mo

hm

OCP

Capacitance

Charge transfer resistance

Imaginary impedance

mF

Gra

ph

ite

Stai

nle

ss s

tee

l

A

B

C

D

E

91

4.4.1. Stainless steel was more sensitive in detecting biofilm formation than

graphite

To evaluate which electrode material was more responsive to changes in cell number

on the electrode surface, the capacitance values obtained for each electrode material

were plotted against the cell density (Figure 4.6A and 4.6B). Good linear relationships

were observed for both electrode materials (R2 = 0.97 and 0.96 for the graphite and

stainless steel electrodes, respectively). As the actual capacitance values were much

lower for stainless steel than for graphite, the capacitance values for each electrode

material were normalised to the respective background value to obtain percentage

change values, which were plotted against the cell density (Figure 4.6C and 4.6D).

Again, good linear relationships with correlation coefficients (R2) of 0.96 were recorded

for both electrode materials. However, the sensitivity (i.e. the slope of the linear

regression trend line) for stainless steel was 10 times higher than that for graphite (2 x

10–5 %/cell cm–2 and 2 x 10–6 %/cell cm–2, respectively) (Figure 4.6C and 4.6D). This

result is interesting as it suggests that stainless steel could be a more sensitive

electrode material for detecting small changes in cell density during biofilm growth. As

the cell densities recorded for both stainless steel and graphite electrodes were similar

(Figure 4.3A), such a remarkable difference in sensitivity can only be attributed to the

different intrinsic properties of these materials (Dumas et al., 2008b). However,

further study is required to elucidate the underlying reasons for this observation.

92

Figure 4.6. Relationship between the absolute capacitance (A and B) and change in

capacitance (%) (C and D) with cell density on the graphite and stainless steel

electrodes.

4.5. Changes in electrode capacitance were biofilm-dependant

4.5.1. Effect of sterile incubation medium on capacitance

To verify that the increase in capacitance observed for the two electrode materials was

a result of biofilm growth, a separate incubation experiment was carried out under

sterile conditions to exclude any biological influence (Figure 4.7). When sterile

conditions were imposed (the ATP concentrations and cell densities remained

negligible), the electrode capacitance remained unchanged throughout the incubation

period (Figure 4.7A). When sterile conditions were not maintained, an increase in

capacitance occurred, coinciding with an increase in both ATP concentration and cell

density (Figure 4.7B and 4.7C). This confirmed that the capacitance changes observed

for the electrode materials were biofilm-dependent.

y = 6E-09x R² = 0.9636

0

0.05

0.1

0.15

0.2

0.25

0.3

0.0E+00 1.0E+07 2.0E+07 3.0E+07 4.0E+07

Cap

acit

ance

(mF/

cm2 )

Cell density ( cells/cm2)

y = 5E-08x

R² = 0.9707

0

1

2

3

4

5

6

y = 2E-06x R² = 0.9699

0

20

40

60

80

% in

cap

acit

ance

y = 2E-05xR² = 0.9636

0

200

400

600

800

1000

0.0E+00 1.0E+07 2.0E+07 3.0E+07 4.0E+07

A

B

C

D

Stainless steelGraphite

93

Figure 4.7. Abiotic effect of the incubation medium on the capacitance of the graphite

and stainless steel electrodes. The dam water medium was amended with 2 g L–1 yeast

extract.

4.5.2. Impact of a chlorine residual on capacitance

To ensure that the decrease in capacitance observed following chlorination on days 8

and 15 was not simply an abiotic response to chlorination (Figure 4.3D), an experiment

was conducted in which fouled and non-fouled graphite and stainless steel electrodes

were exposed to chlorine, and the capacitance was measured (Figure 4.8). As

expected, chlorine decay occurred in both treatments. Over a period of 1 h following

chlorination the chlorine residual decreased from 4.4 mg L–1 to 2.1 and to 3.8 mg L–1

for the fouled and non-fouled electrodes, respectively. A further reduction in chlorine

residual concentrations, to 0.3 and 1.1 mg L–1, respectively, occurred over the

0200400600800

0.0

0.5

1.0

1.5

2.0

14

18

22

26

Abiotic - Graphite Biotic - GraphiteAbiotic - Stainless steel Biotic - Stainless steel

0.0E+00

1.0E+06

2.0E+06

3.0E+06

0 12 24 36 48

Cap

acit

ance

of

grap

hit

e (m

F)

Cap

acit

ance

of

stai

nle

ss s

teel

(m

F)

ATP

(ng

/cm

2 )

Cel

l den

sity

(cel

ls/c

m2 )

A

B

C

Time (h)

94

following 24 h (Figure 4.8). An accelerated decay of chlorine was expected in the

presence of biofilm, and the lower chlorine decay rate observed with the non-fouled

electrodes was mainly attributed to auto-decomposition of chlorine (Adhikari et al.,

2012). In the absence of biofilm, the electrode capacitance remained unchanged

throughout the experiment, indicating that the capacitance change was predominately

a result of biofouling (Figure 4.8). These results indicate that real-time detection of

biofilm development is feasible, even with a fluctuating background of chlorine

residuals, and suggests that there is the potential to develop an online electrochemical

sensor to monitor biofilm formation in chlorinated DWDSs.

95

Figure 4.8. Abiotic effect of chlorination on the capacitance of the graphite and

stainless steel electrodes. Chlorinated fresh dam water was used as the medium. No

yeast extract was included.

4.6. Conclusions

In this study, two low cost materials (graphite and stainless steel) were compared for

their suitability for biofilm sensing in chlorinated DWDSs. The major findings were:

1. Among a range of electrochemical parameters examined, the double-layer

capacitance derived from the Randles equivalent circuit model of EIS showed the

best positive linear correlation with cell densities on both graphite and stainless

steel electrodes (R2 > 0.9).

Time (h)

Tota

l Ch

lori

ne

(mg

/L)

Cap

acit

ance

of

grap

hit

e(m

F)

Cap

acit

ance

of

Stai

nle

ss s

teel

(mF)

0

2

4

6With biofouled rodsWith fresh, non-biofouled rods

0.0

0.5

1.0

1.5

2.0

10

15

20

25

30

35

0 5 10 15 20 25

Biofouled rod - GraphiteFresh rod - GraphiteBiofouled rod - Stainless steelFresh rod - Stainless steel

96

2. The capacitance measured for graphite electrodes was approximately an order of

magnitude higher than that for stainless steel, but stainless steel was a factor of

10 more sensitive than graphite for detecting changes in biofilm formation in the

drinking water environment.

3. Varying the background chlorine residual (0–4.4 mg Cl2 L–1) did not affect the

capacitance signal for either graphite or stainless steel electrodes. The observable

changes in capacitance were exclusively a result of biofilm formation.

These findings indicate the potential to develop practical biofilm sensors for the

drinking water industry, based on electrochemical principles. In particular, the absence

of interference in the sensor signal (capacitance) by disinfectant (chlorine residual)

offers an enormous advantage for in situ applications of the sensors in DWDSs.

However, further research is required to optimise the sensitivity and long-term

robustness of the sensor in lower cell density conditions. A more sensitive sensor

would enable a water utility to execute early, effective and benign disinfection control

measures (i.e. dosing of minimal but effective levels of chlorine, and avoiding the

formation of DBPs). Such sensors would assist the water industry in meeting its prime

objective of safe delivery of water to consumers.

97

5. Conclusions and future recommendations

This study investigated ways to improve the current strategies for preventing and

controlling biofilm formation in drinking water distribution systems (DWDSs). This

involved assessing the effect of various types of materials on biofilm formation. In

addition, the development of a novel technology for monitoring of biofilms in DWDSs,

using bioelectrochemical signals, was explored in this study. The following summarises

the important findings of the study, identifies limitations of the study, and provides

recommendation for future research.

The effects of a number of materials on biofilm formation were tested in a laboratory

scale pipe rig simulating a DWDS. The materials tested included polymers having

different hydrophobicities (high density polyethylene, polytetrafluoroethylene and

nylon) with and without embedded copper, nanomaterial (carbon nanotubes), and

marine paint. The extent of biofilm development on the tested materials was

compared with traditional pipe materials including stainless steel and concrete. No

marked difference in microbial density was found between the traditional and novel

materials under the pipe rig operating conditions. This suggests none of the tested

materials showed potential for preventing or decreasing biofilm formation.

Temperature is an important environmental parameter in DWDSs and is known to

affect the formation of biofilms in drinking water. Further study is recommended to

evaluate the effect of seasonal change on biofilm formation. The water used for all the

experiments undertaken was sourced from an environmental water source

(Mundaring Weir, located in Perth, WA) with an unknown mixture of organisms. Tap

water or water from the distribution network (possibly supplemented with nutrients to

stimulate growth) should be used as the water source, to standardise future

experiments testing alternative piping materials. In both cases, these water sources

might better reflect the water in DWDSs. It would also be advisable to test the

mentioned materials and also other pipe materials in the presence of various

disinfectants, to assess the efficiency of disinfectants in killing and dislodging biofilms

formed on the material surfaces. It would be also worthwhile to understand why the

biofilm formation was identical despite the surface properties being so different.

98

The second part of the study involved an investigation of the use of electrochemical

signals for real-time detection of biofilm formation in DWDSs. Biofilm formation on

graphite rod electrodes immersed in a drinking water medium was characterised, and

electrochemical parameters including open circuit potential (OCP) and electrochemical

impedance (EIS) were monitored. The results suggested that graphite was a suitable

substrate for monitoring biofilm formation in DWDSs using electrochemical signals. EIS

provided a reproducible approach to real-time monitoring of biofilm formation and its

removal from graphite electrodes. Biofilm adhesion to the graphite electrodes resulted

in an increase in capacitance, derived from an EIS equivalent circuit model, and a

decrease in the impedance of the system (particularly the imaginary impedance) at a

fixed low frequency (20 mHz). However, among the evaluated parameters, capacitance

showed the most linear relationship with the change in cell density. Chlorination was

effective in removing the biofilm from the graphite electrode, which in turn resulted in

a decrease in capacitance towards the background level. These results suggest that

capacitance is independent of chlorination but responsive to biofilm formation, and

therefore appears to be a suitable parameter for monitoring the formation and

removal of biofilms in DWDSs. Overall, this study showed that electrochemical biofilm

sensors have the potential for use in on-line monitoring of biofilm formation, which

will enable rationalisation of the application of antifouling procedures and optimising

biocide dosing in DWDSs.

To optimise the sensitivity of the electrochemical methods, the electrochemical

parameters associated with two test electrode materials (graphite and stainless steel)

were compared. The formation and removal of biofilm was associated with changes in

all of electrochemical parameters measured (OCP, capacitance, Rct, imaginary and real

impedance) for both materials. Both graphite and stainless steel were suitable

materials for the construction of an electrochemical biosensor. However, stainless

steel was a factor of 10 more sensitive to biofouling, based on the capacitance

measurement. Among the selected electrochemical parameters, capacitance was also

found to be the most suitable indicator for the stainless steel, as it was linearly

correlated with cells density. The findings of this study demonstrate that on-line

monitoring of biofilms in drinking water systems is feasible using electrochemical

sensors based on capacitance measurement. However, more studies are required to

99

further elucidate the electrochemical behaviour of biofilms, to optimise the electrode

materials and sensor construction, and to develop a software platform that could be

used for real-time monitoring of biofilm formation in the field.

Future work should focus on designing and constructing a sensor that can be tested in

a pipe rig system, to enable validation of the performance of the sensor. Use of this

system would facilitate testing of the electrochemical method for biofilm detection on

different materials (e.g. carbon, copper, stainless steel) to reflect different types of

distribution pipe. Subsequently, the sensor could be tested in the presence of different

disinfectants to assess how the sensor output is affected by residual disinfectant

concentrations. In addition, to assess the practicality of the biofilm sensor for long-

term real-time monitoring in DWDSs, a longer term trial should be conducted.

100

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