re-evaluating secondary disinfectants as sentinels … · 2015. 11. 29. · table 5-1: estimation...

RE-EVALUATING SECONDARY DISINFECTANTS AS SENTINELS OF CONTAMINATION AND USING A SYSTEMS

VULNERABILITY MODEL

by

Chris Keung

A thesis submitted in conformity with the requirements for the degree of Masters of Applied Science Graduate Department of Civil Engineering

University of Toronto

© Copyright by Chris Keung 2015

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Re-evaluating Secondary Disinfectants as Sentinels of Contamination and Using a Systems Vulnerability Model

Chris Keung Department of Civil Engineering, University of Toronto

Degree of Masters of Applied Science Convocation 2015

ABSTRACT

To build a framework in which secondary disinfectants can be quantitatively evaluated,

three tasks were performed: (1) A sampling campaign was conducted at a community

using an alternative secondary disinfectant (HuwaSan peroxide) to evaluate various water

quality parameters; (2) bench-scale experiments examined the efficacy of different

disinfectants as sentinels of contamination; and (3) a systems vulnerability assessment was

performed (EPANET-MSX). The results show that: (1) HuwaSan, can limit DBP

formation while maintaining acceptable water quality in terms of the parameters measured;

(2) chlorine was observed to be the most appropriate sentinel of intrusion under the tested

conditions; and (3) under modeled conditions, E. coli propagation was controlled by all

tested disinfectants. For Giardia intrusions, Cl2, ClO2, and HSP achieved 3-log inactivation

between 30-150 minutes, although an assumed inactivation rate for HSP was used. The

same inactivation required chloramines and H2O2 between 330-1180 and 170-910 minutes,

respectively.

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ACKNOWLEDGMENTS

This work was funded by the Natural Sciences and Engineering Research Council of Canada

(NSERC) Industrial Research Chair at the University of Toronto.

Firstly, I would like to thank my thesis supervisor, Professor Ron Hofmann, for his guidance and

encouragement over the last two years. The knowledge and advice you provided me, whether it

was something substantial or a small, subtle comment was truly invaluable. Your management

style really allowed me to make the most out my Masters and I’d like to thank you again for all

the opportunities you provided me.

Thanks to everyone in the Drinking Water Research Group for simply being a wonderful,

eclectic mix of people who are passionate about all things water. In particular, I’d like to thank

Jim Wang for being my go-to-person for anything related to the lab. There are far too many

things to thank you for but I’m positive that I wouldn’t be here finishing my thesis without all

your help. Thanks to Liz and Isabelle for the Genotox work; Ken and Frank for all your help

during the summer; Vivek for being my chauffeur in collecting sewage samples; and to the

numerous people who helped me over the last two years.

I must thank Eugene from OCWA and the management staff from the Township of Killaloe,

Hagarty and Richards for allowing me to tag along in Killaloe. I’m truly grateful for having the

opportunity to spend some time in the community and getting to know a little bit about a place

that I might have never explored. Thanks Eugene for being a great guide and for all your fun tid-

bits of information. I now know that the Beavertail pastry originated in Killaloe and that blue

frogs do in fact exist in Ontario.

Finally, I’d like to thank my dear family and friends (human and canine) for your enduring

support. The last two years have been truly exceptional and is an experience that I’ll always hold

dear to my heart.

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TABLE OF CONTENTS

ABSTRACT……………………………………………………………………………………...ii

ACKNOWLEDGEMENTS………………………………………………………………….....iii TABLE OF CONTENTS…………………………………………………………………….....iv LIST OF TABLES……….……………………………………………………………….…....viii LIST OF FIGURES…………………………………………………………………..................xi 1 INTRODUCTION AND RESEARCH OBJECTIVES ..................................................... 1

1.1 Introduction ...................................................................................................................... 1

1.2 Research Objectives ......................................................................................................... 2

1.2.1 Case Study: Killaloe, Ontario HSP Monitoring Campaign (Chapter 3) ..................... 2

1.2.2 The Ability of Secondary Disinfectants to Serve as Sentinels of ssssssssssssssss ssssss Contamination (Chapter 4) ......................................................................................... 2

1.2.3 EPANET-MSX Modeling (Chapter 5) ....................................................................... 3

1.3 Description of Chapters .................................................................................................... 3

1.4 References ........................................................................................................................ 4

2 LITERATURE REVIEW .................................................................................................... 5

2.1 Hydrogen Peroxide Based Disinfectants .......................................................................... 5

2.1.1 Key Papers and Findings (Hydrogen Peroxide/Silver Disinfectant) .......................... 5

2.1.2 Key Papers and Findings (HuwaSan Peroxide) .......................................................... 7

2.1.3 HuwaSan Peroxide Case Studies (Killaloe and Southwest Middlesex) ..................... 8

2.2 References ........................................................................................................................ 9

3 CASE STUDY: KILLALOE, ONTARIO HSP MONITORING CAMPAIGN ............ 11

3.1 Introduction .................................................................................................................... 11

3.1.1 Research Objectives .................................................................................................. 12

3.2 Materials and Method..................................................................................................... 13

3.2.1 Analytical Methods ................................................................................................... 13

3.2.1.1 Trihalomethanes (THMs), Haloacetonitriles (HANs), Haloketones (HK), sssssss Chloropicrin (CP), and Haloacetic Acids (HAAs)........................................... 13

3.2.1.2 Adsorbable Organic Halogens (AOX) ............................................................ 14

3.2.1.3 Dissolved Organic Carbon (DOC) .................................................................. 14

3.2.1.4 Ultraviolet Absorbance at 254nm (UV254) ...................................................... 14

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3.2.1.5 Adenosine Triphosphate (ATP) Measurement ................................................ 14

3.2.1.6 Heterotrophic Plate Count (HPC) .................................................................... 15

3.2.1.7 Metal Analysis ................................................................................................. 15

3.2.1.8 Genotoxicity – SOS Chromotest Bioassay ...................................................... 15

3.2.2 Study to Identify the HSP Quenching Agent for DBP Analysis .............................. 16

3.2.3 Killaloe Sampling Campaign .................................................................................... 16

3.2.4 Historical Data .......................................................................................................... 17

3.3 Results and Discussion ................................................................................................... 17

3.3.1 Study to Identify the HSP Quenching Agent for DBP Analysis .............................. 17

3.3.2 Killaloe Sampling Campaign .................................................................................... 19

3.4 Summary and Conclusions ............................................................................................. 26

3.5 References ...................................................................................................................... 27

4 THE ABILITY OF SECONDARY DISINFECTANTS TO SERVE AS sssssssssssssssss ssss AS SENTINELS OF CONTAMINATION ...................................................................... 29

4.1 Introduction .................................................................................................................... 29

4.2 Materials and Methods ................................................................................................... 33

4.2.1 Analytical Methods ................................................................................................... 33

4.2.1.1 pH and Temperature Measurement ................................................................. 33

4.2.1.2 Dissolved Organic Carbon (DOC) .................................................................. 33

4.2.1.3 Free Ammonia Measurement .......................................................................... 33

4.2.1.4 Free Chlorine Residual .................................................................................... 34

4.2.1.5 Total Chlorine (Free Chlorine, Monochloramine, Dichloramine) sssssss ssssssss Residual Amperometric Titration ................................................................... 34

4.2.1.6 Chlorine Dioxide Residual .............................................................................. 34

4.2.1.7 Hydrogen Peroxide Residual ........................................................................... 34

4.2.2 Wastewater Evaluation ............................................................................................. 35

4.2.3 Water Source Sampling and Disinfectant Residual Preparation ............................... 36

4.2.4 Simulated Contamination Event – Raw Sewage Intrusion ....................................... 37



4.3 References ...................................................................................................................... 54

5 EVALUATING PATHOGEN PROPAGATION IN A DISTRIBUTION SYSTEM ssss ssss USING A SYSTEMS VULNERABILITY MODEL ....................................................... 57

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5.1 Introduction .................................................................................................................... 57

5.1.1 Problem Statement .................................................................................................... 59

5.2 Materials and Method..................................................................................................... 61

5.2.1 Network Hydraulic Model ........................................................................................ 61

5.2.2 Selection of Nodes to Receive Contamination ......................................................... 62

5.2.3 Volume and Duration of Contamination ................................................................... 62

5.2.4 Selection of Disinfectant Demand (Initial/Decay) .................................................... 64

5.2.5 Concentration of Pathogens ...................................................................................... 65

5.2.6 Pathogen Inactivation Constants ............................................................................... 66

5.2.7 Residual Maintenance Strategy ................................................................................. 67


5.3.1 E. Coli Intrusion ........................................................................................................ 68

5.3.2 Giardia Intrusion ...................................................................................................... 70


5.5 References ...................................................................................................................... 75

6 SUMMARY, CONCLUSIONS AND RECOMMENDATIONS .................................... 79

6.1 Summary and Conclusions ........................................................................................... 79

6.2 Recommendations for Future Work ............................................................................. 80

APPENDICES .................................................................................................................................

A.1 HSP Quenching Agent DBP Analysis……………………………………………...A-2 B.1 THM/HAN/HK/CP Protocol .................................................................................... B-2

B.2 HAA Protocol ........................................................................................................... B-4

B.3 AOX Protocol ........................................................................................................... B-6

B.4 DOC Protocol ........................................................................................................... B-7

B.5 ATP Protocol ............................................................................................................ B-8

B.6 HPC Protocol ............................................................................................................ B-9

B.7 Metals Protocol ....................................................................................................... B-11

B.8 Genotoxicity – SOS Choromotest Assay ................................................................ B-12

B.9 THM Calibration Curves and QA/QC Charts ........................................................ B-15

B.10 HAA Calibration Curves and QA/QC Charts......................................................... B-19

B.11 HAN/HK/CP Calibration Curves and QA/QC Charts ............................................ B-26

B.12 DOC Calibration Curves and QA/QC Charts ......................................................... B-32

D.1 Dissolved Organic Carbon (DOC) ........................................................................... D-2

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D.2 Free Ammonia Measurement ................................................................................... D-3

D.3 Free Chlorine Measurement ..................................................................................... D-3

D.4 Total Chlorine Amperometric Titration ................................................................... D-4

D.5 Chlorine Dioxide Measurement ................................................................................ D-5

D.6 Hydrogen Peroxide Measurement ............................................................................ D-7

D.7 DOC Calibration Curves and QA/QC Charts ........................................................... D-8

D.8 Wastewater Evaluation – Reactivity QA/QC Data ................................................... D-9

E.1 Chlorine Decay Charts ............................................................................................... E-2

E.2 Chloramines Decay Charts ...................................................................................... E-15

E.3 Chlorine Dioxide Decay Chart ................................................................................ E-23

E.4 Hydrogen Peroxide Decay Charts ........................................................................... E-39

E.5 HuwaSan Peroxide Decay Charts ............................................................................ E-55

F.1 EPANET Hydraulic Model Code (.INP File) ............................................................ F-2

F.2 MSX Code Short Duration, High Concentration....................................................... F-9

F.3 MSX Code Short Duration, Low Concentration ..................................................... F-14

F.4 MSX Code Long Duration, High Concentration ..................................................... F-19

F.5 MSX Code Long Duration, Low Concentration ..................................................... F-24

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LIST OF TABLES

Table 3-1: Killaloe sampling sites ................................................................................................ 16 Table 3-2: Paired student t-test comparing DBP degradation for quenching agents ssssssssssssss ssssss at day 0 and day 5 ........................................................................................................ 18 Table 3-3: Microbial equivalents (ME/mL) assessed via ATP luminescence assay ssssssssssssss ssssss in raw and treated drinking water collected from Killaloe .......................................... 20 Table 3-4: Copper, iron, manganese, lead and silver concentrations between ssssssssssssss ssssss ssssss September 2014 and May 2015 in the Killaloe drinking water system...................... 22 Table 3-5: Genotoxic response (IF) of Killaloe distribution samples at 16.5 eq. mL/well .......... 26 Table 4-1: Typical secondary disinfectant residuals ..................................................................... 36 Table 4-2: Concentrations of secondary disinfectants used in sentinel experiments .................... 37 Table 4-3: Chlorine decay regression summary ........................................................................... 44 Table 4-4: Chloramine decay regression summary ...................................................................... 46 Table 4-5: Chlorine dioxide decay regression summary .............................................................. 48 Table 4-6: Hydrogen peroxide decay regression summary .......................................................... 50 Table 4-7: Huwa-San peroxide decay regression summary ......................................................... 52 Table 5-1: Estimation of intrusion flow rate (L/min) using hydraulic modeling ssssssssssssss ssssss (adapted from Kirmeyer et al., 2001) .......................................................................... 63 Table 5-2: Secondary disinfectants initial demands and decay constants used in ssssssssssssss ssssss EPANET-MSX model ................................................................................................. 65 Table 5-3: Summary of predicted concentrations (#/L) of pathogens in raw sewage ssssssssssssss ssssss (adapted from Yang et al. 2015) .................................................................................. 65 Table 5-4: E coli. inactivation constants (Kp) used in EPANET-MSX model ............................. 66 Table 5-5: Giardia inactivation constants (Kp) used in EPANET-MSX model ........................... 67 Table 5-6: Disinfectant residual concentrations added at pumping station (node 1) ssssssssssssss ssssss and tank booster station (node 26) ............................................................................... 67 Table 5-7: Inactivation time to achieve 3-log inactivation for E. coli using ssssssssssssssssssss ssssss CT calculation and EPANET-MSX model (long and short duration)......................... 68 Table 5-8: Inactivation time to achieve 3-log inactivation for Giardia using ssssssssssssssssssss ssssss CT calculation and EPANET-MSX model (long and short duration)......................... 71

Table B- 1: THM/HAN/HK/CP instrument conditions .............................................................. B-2 Table B- 2: THM/HAN/HK/CP reagents ................................................................................... B-2 Table B- 3: THM/HAN/HK/CP method outline ......................................................................... B-2 Table B- 4: THM method detection limits .................................................................................. B-3 Table B- 5: HAN/HK/CP method detection limits ..................................................................... B-4 Table B- 6: HAA instrument conditions ..................................................................................... B-4 Table B- 7: HAA reagents .......................................................................................................... B-4 Table B- 8: HAA method outline................................................................................................ B-5

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Table B- 9: HAA method detection limits .................................................................................. B-6 Table B- 10: AOX instrument conditions ................................................................................... B-6 Table B- 11: AOX reagents ........................................................................................................ B-6 Table B- 12: AOX method outline.............................................................................................. B-6 Table B- 13: DOC instrument conditions ................................................................................... B-7 Table B- 14: DOC reagents......................................................................................................... B-7 Table B- 15: DOC method outline .............................................................................................. B-8 Table B- 16: ATP method outline ............................................................................................... B-8 Table B- 17: HPC method outline .............................................................................................. B-9 Table B- 18: Metals method outline ......................................................................................... B-11 Table B- 19: Genotoxicity SOS Chromotest methods .............................................................. B-12 Table B- 20: Solid phase extraction (SPE) method .................................................................. B-14

Table C- 1: Killalloe sampling campaign summary ................................................................... C-2 Table C- 2: THM/HAN/CP raw data from Killaloe (September 9, 2014).................................. C-4 Table C- 3: THM/HAN/CP raw data from Killaloe (October 28, 2014) .................................... C-5 Table C- 4: THM/HAN/CP raw data from Killaloe (February 3, 2015) .................................... C-6 Table C- 5: THM/HAN/CP raw data from Killaloe (May 28, 2015) ......................................... C-7 Table C- 6: HAA raw data from Killaloe (September 9, 2014) .................................................. C-8 Table C- 7: HAA raw data from Killaloe (October 28, 2014) .................................................... C-9 Table C- 8: HAA raw data from Killaloe (February 3, 2015) .................................................. C-10 Table C- 9: HAA raw data from Killaloe (May 28, 2015) ....................................................... C-11 Table C- 10: Water quality measurements from Killaloe (September 9, 2015) ....................... C-12 Table C- 11: Water quality measurements from Killaloe (October 28, 2015) ......................... C-13 Table C- 12: Water quality measurements from Killaloe (February 3, 2015) .......................... C-14 Table C- 13: Water quality measurements from Killaloe (May 28, 2015) ............................... C-15

Table D- 1: DOC instrument conditions ..................................................................................... D-2 Table D- 2: DOC reagents .......................................................................................................... D-2 Table D- 3: DOC method outline................................................................................................ D-2 Table D- 4: Free ammonia reagents ............................................................................................ D-3 Table D- 5: Free ammonia method outline ................................................................................. D-3 Table D- 6: Free chlorine reagents .............................................................................................. D-3 Table D- 7: Free chlorine method outline ................................................................................... D-3 Table D- 8: Total chlorine reagents ............................................................................................ D-4 Table D- 9: Total chlorine method outline ................................................................................. D-4 Table D- 10: Chlorine dioxide reagents ...................................................................................... D-5 Table D- 11: Chlorine dioxide method outline ........................................................................... D-6 Table D- 12: Hydrogen peroxide reagents .................................................................................. D-7 Table D- 13: Hydrogen peroxide method outline ....................................................................... D-7

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Table D- 14: Free chlorine high concentration wastewater reactivity QAQC data .................... D-9 Table D- 15: Free chlorine med/high concentration wastewater reactivity QAQC data .......... D-10

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LIST OF FIGURES

Figure 3-1: THM concentrations for treated (prechlorinated) water and distribution water sssssssssss in Killaloe system between January 2008 and May 2015, using chlorine ssssssssss ssssssssss as a secondary disinfectant (prior to Nov 2012) and HSP (after Nov 2012)............. 23 Figure 3-2: AOX formation between Sept 2015 to May 2015 ..................................................... 25 Figure 4-1: 30 minute residual remaining (percentage) versus % sewage ................................... 39 Figure 4-2: 24 hour residual remaining (percentage) versus % sewage ....................................... 40 Figure 5-1: Example network distribution system ........................................................................ 62 Figure 5-2: E. coli inactivation for long and short intrusion events ............................................. 69 Figure 5-3: Maximum E. coli concentration observed at each node with intrusion ssssssssssss ssssssssss occurring at node 12 ................................................................................................... 70 Figure 5-4: Giardia inactivation for long intrusion events assuming high disinfectant ssssssssss ssssssssss concentrations ............................................................................................................. 72 Figure 5-5: Giardia inactivation for long intrusion events assuming low disinfectant ssssssssss ssssssssss concentrations ............................................................................................................. 72 Figure 5-6: Maximum Giardia concentration observed at each node with long sssssssssssssss ssssssssss duration intrusion occurring at node 12 for high disinfectant concentrations ............ 73 Figure 5-7: Maximum Giardia concentration observed at each node with long sssssssssssssss ssssssssss duration intrusion occurring at node 12 for low disinfectant concentrations ............. 74 Figure A- 1: TCM concentration at day 0 and day 5 after the addition of various ssssssssss ssssssss quenching agents ................................................................................................... A-2 Figure A- 2: BDCM concentration at day 0 and day 5 after the addition of various ssssssssss ssssssss quenching agents ................................................................................................... A-2 Figure A- 3: DBCM concentration at day 0 and day 5 after the addition of various ssssssssss ssssssss quenching agents ................................................................................................... A-3 Figure A- 4: TBM concentration at day 0 and day 5 after the addition of various ssssssssss ssssssss quenching agents ................................................................................................... A-3 Figure A- 5: TCAN concentration at day 0 and day 5 after the addition of various ssssssssss ssssssss quenching agents ................................................................................................... A-4 Figure A- 6: DCAN concentration at day 0 and day 5 after the addition of various ssssssssss ssssssss quenching agents ................................................................................................... A-4 Figure A- 7: DCP concentration at day 0 and day 5 after the addition of various ssssssssss ssssssss quenching agents ................................................................................................... A-5 Figure A- 8: CP concentration at day 0 and day 5 after the addition of various ssssssssssss ssssssss quenching agents ................................................................................................... A-5 Figure A- 9: BCAN concentration at day 0 and day 5 after the addition of various ssssssssss ssssssss quenching agents ................................................................................................... A-6

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Figure A- 10: TCP concentration at day 0 and day 5 after the addition of various ssssssssss ssssssss quenching agents ................................................................................................. A-6 Figure A- 11: DBAN concentration at day 0 and day 5 after the addition of various ssssssssss ssssssss quenching agents ................................................................................................. A-7 Figure A- 12: MCAA concentration at day 0 and day 5 after the addition of various ssssssssss ssssssss quenching agents ................................................................................................. A-7 Figure A- 13: MBAA concentration at day 0 and day 5 after the addition of various ssssssssss ssssssss quenching agents ................................................................................................. A-8 Figure A- 14: DCAA concentration at day 0 and day 5 after the addition of various ssssssssss ssssssss quenching agents ................................................................................................. A-8 Figure A- 15: TCAA concentration at day 0 and day 5 after the addition of various ssssssssss ssssssss quenching agents ................................................................................................. A-9 Figure A- 16: BCAA concentration at day 0 and day 5 after the addition of various ssssssssss ssssssss quenching agents ................................................................................................. A-9 Figure A- 17: DBAA concentration at day 0 and day 5 after the addition of various ssssssssss ssssssss quenching agents ............................................................................................... A-10 Figure A- 18: BDCAA concentration at day 0 and day 5 after the addition of various ssssssssss ssssssss quenching agents ............................................................................................... A-10 Figure A- 19: CDBAA concentration at day 0 and day 5 after the addition of various ssssssssss ssssssss quenching agents ............................................................................................... A-11 Figure A- 20: TBAA concentration at day 0 and day 5 after the addition of various ssssssssss ssssssss quenching agents ............................................................................................... A-11

Figure B- 1: TCM calibration curve ......................................................................................... B-15 Figure B- 2: Quality control chart for TCM analysis ............................................................... B-15 Figure B- 3: TCM calibration curve ......................................................................................... B-16 Figure B- 4: Quality control chart for BDCM analysis ............................................................ B-16 Figure B- 5: DBCM calibration curve ...................................................................................... B-17 Figure B- 6: Quality control chart for DBCM analysis ............................................................ B-17 Figure B- 7: TBM calibration curve ......................................................................................... B-18 Figure B- 8: Quality control chart for TBM analysis ............................................................... B-18 Figure B- 9: MCAA calibration curve ...................................................................................... B-19 Figure B- 10: Quality control chart for MCAA analysis .......................................................... B-19 Figure B- 11: DCAA calibration curve ..................................................................................... B-20 Figure B- 12: Quality control chart for DCAA analysis ........................................................... B-20 Figure B- 13: TCAA calibration curve ..................................................................................... B-21 Figure B- 14: Quality control chart for TCAA analysis ........................................................... B-21 Figure B- 15: BCAA calibration curve ..................................................................................... B-22 Figure B- 16: Quality control chart for BCAA analysis ........................................................... B-22 Figure B- 17: DBAA calibration curve ..................................................................................... B-23

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Figure B- 18: Quality control chart for DBAA analysis ........................................................... B-23 Figure B- 19: BDCAA calibration curve .................................................................................. B-24 Figure B- 20: Quality control chart for BDCAA analysis ........................................................ B-24 Figure B- 21: CDBAA calibration curve .................................................................................. B-25 Figure B- 22: Quality control chart for CDBAA analysis ........................................................ B-25 Figure B- 23: TCAN calibration curve ..................................................................................... B-26 Figure B- 24: Quality control chart for TCAN analysis ........................................................... B-26 Figure B- 25: DCAN calibration curve ..................................................................................... B-27 Figure B- 26: Quality control chart for DCAN analysis ........................................................... B-27 Figure B- 27: DCP calibration curve ........................................................................................ B-28 Figure B- 28: Quality control chart for DCP analysis .............................................................. B-28 Figure B- 29: CP calibration curve ........................................................................................... B-29 Figure B- 30: Quality control chart for CP analysis ................................................................. B-29 Figure B- 31: BCAN calibration curve ..................................................................................... B-30 Figure B- 32: Quality control chart for BCAN analysis ........................................................... B-30 Figure B- 33: DBAN calibration curve ..................................................................................... B-31 Figure B- 34: Quality control chart for DBAN analysis ........................................................... B-31 Figure B- 35: DOC calibration curve ........................................................................................ B-32 Figure B- 36: Quality control chart for DOC analysis .............................................................. B-32 Figure D- 1: DOC calibration curve ........................................................................................... D-8 Figure D- 2: Quality control chart for DOC analysis ................................................................. D-8 Figure E- 1: Chlorine decay plot - 0.05 mg/L, 4°C, pH 6 ........................................................... E-2 Figure E- 2: Chlorine decay plot - 0.05 mg/L, 23°C, pH 6 ......................................................... E-2 Figure E- 3: Chlorine decay plot - 0.05 mg/L, 4°C, pH 8 ........................................................... E-3 Figure E- 4: Chlorine decay plot - 0.05 mg/L, 23°C, pH 8 ......................................................... E-3 Figure E- 5: Chlorine decay plot - 0.8 mg/L, 4°C, pH 6 ............................................................. E-4 Figure E- 6: Chlorine decay plot - 0.8 mg/L, 4°C, pH 6 ............................................................. E-4 Figure E- 7: Chlorine decay plot - 0.8 mg/L, 23°C, pH 6 ........................................................... E-5 Figure E- 8: Chlorine decay plot - 0.8 mg/L, 4°C, pH 8 ............................................................. E-5 Figure E- 9: Chlorine decay plot - 0.8 mg/L, 4°C, pH 8 ............................................................. E-6 Figure E- 10: Chlorine decay plot - 0.8 mg/L, 23°C, pH 8 ......................................................... E-6 Figure E- 11: Chlorine decay plot - 2 mg/L, 4°C, pH 6 .............................................................. E-7 Figure E- 12: Chlorine decay plot - 2 mg/L, 4°C, pH 6 .............................................................. E-7 Figure E- 13: Chlorine decay plot - 2 mg/L, 23°C, pH 6 ............................................................ E-8 Figure E- 14: Chlorine decay plot - 2 mg/L, 23°C, pH 6 ............................................................ E-8 Figure E- 15: Chlorine decay plot - 2 mg/L, 4°C, pH 8 .............................................................. E-9 Figure E- 16: Chlorine decay plot - 2 mg/L, 4°C, pH 8 .............................................................. E-9 Figure E- 17: Chlorine decay plot - 2 mg/L, 23°C, pH 8 .......................................................... E-10

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Figure E- 18: Chlorine decay plot - 2 mg/L, 23°C, pH 8 .......................................................... E-10 Figure E- 19: Chlorine decay plot - 4 mg/L, 4°C, pH 6 ............................................................ E-11 Figure E- 20: Chlorine decay plot - 4 mg/L, 4°C, pH 6 ............................................................ E-11 Figure E- 21: Chlorine decay plot - 4 mg/L, 23°C, pH 6 .......................................................... E-12 Figure E- 22: Chlorine decay plot - 4 mg/L, 23°C, pH 6 .......................................................... E-12 Figure E- 23: Chlorine decay plot - 4 mg/L, 4°C, pH 8 ............................................................ E-13 Figure E- 24: Chlorine decay plot - 4 mg/L, 4°C, pH 8 ............................................................ E-13 Figure E- 25: Chlorine decay plot - 4 mg/L, 23°C, pH 8 .......................................................... E-14 Figure E- 26: Chlorine decay plot - 4 mg/L, 23°C, pH 8 .......................................................... E-14 Figure E- 27: Chloramines decay plot – 0.5 mg/L, 4°C, pH 6 .................................................. E-15 Figure E- 28: Chloramines decay plot – 0.5 mg/L, 23°C, pH 6 ................................................ E-15 Figure E- 29: Chloramines decay plot – 0.5 mg/L, 4°C, pH 8 .................................................. E-16 Figure E- 30: Chloramines decay plot – 0.5 mg/L, 23°C, pH 8 ................................................ E-16 Figure E- 31: Chloramines decay plot – 1 mg/L, 4°C, pH 6 ..................................................... E-17 Figure E- 32: Chloramines decay plot – 1 mg/L, 23°C, pH 6 ................................................... E-17 Figure E- 33: Chloramines decay plot – 1 mg/L, 4°C, pH 8 ..................................................... E-18 Figure E- 34: Chloramines decay plot – 1 mg/L, 23°C, pH 8 ................................................... E-18 Figure E- 35: Chloramines decay plot – 1.75 mg/L, 4°C, pH 6 ................................................ E-19 Figure E- 36: Chloramines decay plot – 1.75 mg/L, 23°C, pH 6 .............................................. E-19 Figure E- 37: Chloramines decay plot – 1.75 mg/L, 23°C, pH 8 .............................................. E-20 Figure E- 38: Chloramines decay plot – 3 mg/L, 4°C, pH 6 ..................................................... E-21 Figure E- 39: Chloramines decay plot – 3 mg/L, 23°C, pH 6 ................................................... E-21 Figure E- 40: Chloramines decay plot – 3 mg/L, 4°C, pH 8 ..................................................... E-22 Figure E- 41: Chloramines decay plot – 3 mg/L, 23°C, pH 8 ................................................... E-22 Figure E- 42: Chlorine dioxide decay plot – 0.05 mg/L, 4°C, pH 6 .......................................... E-23 Figure E- 43: Chlorine dioxide decay plot – 0.05 mg/L, 4°C, pH 6 .......................................... E-23 Figure E- 44: Chlorine dioxide decay plot – 0.05 mg/L, 23°C, pH 6 ........................................ E-24 Figure E- 45: Chlorine dioxide decay plot – 0.05 mg/L, 23°C, pH 6 ........................................ E-24 Figure E- 46: Chlorine dioxide decay plot – 0.05 mg/L, 4°C, pH 8 .......................................... E-25 Figure E- 47: Chlorine dioxide decay plot – 0.05 mg/L, 4°C, pH 8 .......................................... E-25 Figure E- 48: Chlorine dioxide decay plot – 0.05 mg/L, 23°C, pH 8 ........................................ E-26 Figure E- 49: Chlorine dioxide decay plot – 0.05 mg/L, 23°C, pH 8 ........................................ E-26 Figure E- 50: Chlorine dioxide decay plot – 0.2 mg/L, 4°C, pH 6 ............................................ E-27 Figure E- 51: Chlorine dioxide decay plot – 0.2 mg/L, 4°C, pH 6 ............................................ E-27 Figure E- 52: Chlorine dioxide decay plot – 0.2 mg/L, 23°C, pH 6 .......................................... E-28 Figure E- 53: Chlorine dioxide decay plot – 0.2 mg/L, 23°C, pH 6 .......................................... E-28 Figure E- 54: Chlorine dioxide decay plot – 0.2 mg/L, 4°C, pH 8 ............................................ E-29 Figure E- 55: Chlorine dioxide decay plot – 0.2 mg/L, 4°C, pH 8 ............................................ E-29 Figure E- 56: Chlorine dioxide decay plot – 0.2 mg/L, 23°C, pH 8 .......................................... E-30 Figure E- 57: Chlorine dioxide decay plot – 0.2 mg/L, 23°C, pH 8 .......................................... E-30

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Figure E- 58: Chlorine dioxide decay plot – 0.4 mg/L, 4°C, pH 6 ............................................ E-31 Figure E- 59: Chlorine dioxide decay plot – 0.4 mg/L, 4°C, pH 6 ............................................ E-31 Figure E- 60: Chlorine dioxide decay plot – 0.4 mg/L, 23°C, pH 6 .......................................... E-32 Figure E- 61: Chlorine dioxide decay plot – 0.4 mg/L, 23°C, pH 6 .......................................... E-32 Figure E- 62: Chlorine dioxide decay plot – 0.4 mg/L, 4°C, pH 8 ............................................ E-33 Figure E- 63: Chlorine dioxide decay plot – 0.4 mg/L, 4°C, pH 8 ............................................ E-33 Figure E- 64: Chlorine dioxide decay plot – 0.4 mg/L, 23°C, pH 8 .......................................... E-34 Figure E- 65: Chlorine dioxide decay plot – 0.4 mg/L, 23°C, pH 8 .......................................... E-34 Figure E- 66: Chlorine dioxide decay plot – 0.8 mg/L, 4°C, pH 6 ............................................ E-35 Figure E- 67: Chlorine dioxide decay plot – 0.8 mg/L, 4°C, pH 6 ........................................... E-35 Figure E- 68: Chlorine dioxide decay plot – 0.8 mg/L, 23°C, pH 6 .......................................... E-36 Figure E- 69: Chlorine dioxide decay plot – 0.8 mg/L, 23°C, pH 6 .......................................... E-36 Figure E- 70: Chlorine dioxide decay plot – 0.8 mg/L, 4°C, pH 8 ............................................ E-37 Figure E- 71: Chlorine dioxide decay plot – 0.8 mg/L, 4°C, pH 8 ............................................ E-37 Figure E- 72: Chlorine dioxide decay plot – 0.8 mg/L, 23°C, pH 8 .......................................... E-38 Figure E- 73: Chlorine dioxide decay plot – 0.8 mg/L, 23°C, pH 8 .......................................... E-38 Figure E- 74: Hydrogen peroxide decay plot – 1 mg/L, 4°C, pH 6 ........................................... E-39 Figure E- 75: Hydrogen peroxide decay plot – 1 mg/L, 4°C, pH 6 ........................................... E-39 Figure E- 76: Hydrogen peroxide decay plot – 1 mg/L, 23°C, pH 6 ......................................... E-40 Figure E- 77: Hydrogen peroxide decay plot – 1 mg/L, 23°C, pH 6 ......................................... E-40 Figure E- 78: Hydrogen peroxide decay plot – 1 mg/L, 4°C, pH 8 ........................................... E-41 Figure E- 79: Hydrogen peroxide decay plot – 1 mg/L, 4°C, pH 8 ........................................... E-41 Figure E- 80: Hydrogen peroxide decay plot – 1 mg/L, 23°C, pH 8 ......................................... E-42 Figure E- 81: Hydrogen peroxide decay plot – 1 mg/L, 23°C, pH 8 ......................................... E-42 Figure E- 82: Hydrogen peroxide decay plot – 6 mg/L, 4°C, pH 6 ........................................... E-43 Figure E- 83: Hydrogen peroxide decay plot – 6 mg/L, 4°C, pH 6 ........................................... E-43 Figure E- 84: Hydrogen peroxide decay plot – 6 mg/L, 23°C, pH 6 ......................................... E-44 Figure E- 85: Hydrogen peroxide decay plot – 6 mg/L, 23°C, pH 6 ......................................... E-44 Figure E- 86: Hydrogen peroxide decay plot – 6 mg/L, 4°C, pH 8 ........................................... E-45 Figure E- 87: Hydrogen peroxide decay plot – 6 mg/L, 4°C, pH 8 ........................................... E-45 Figure E- 88: Hydrogen peroxide decay plot – 6 mg/L, 23°C, pH 8 ......................................... E-46 Figure E- 89: Hydrogen peroxide decay plot – 6 mg/L, 23°C, pH 8 ......................................... E-46 Figure E- 90: Hydrogen peroxide decay plot –15 mg/L, 4°C, pH 6 .......................................... E-47 Figure E- 91: Hydrogen peroxide decay plot –15 mg/L, 4°C, pH 6 .......................................... E-47 Figure E- 92: Hydrogen peroxide decay plot –15 mg/L, 23°C, pH 6 ........................................ E-48 Figure E- 93: Hydrogen peroxide decay plot –15 mg/L, 23°C, pH 6 ........................................ E-48 Figure E- 94: Hydrogen peroxide decay plot –15 mg/L, 4°C, pH 8 .......................................... E-49 Figure E- 95: Hydrogen peroxide decay plot –15 mg/L, 4°C, pH 9 .......................................... E-49 Figure E- 96: Hydrogen peroxide decay plot –15 mg/L, 23°C, pH 8 ........................................ E-50 Figure E- 97: Hydrogen peroxide decay plot –15 mg/L, 23°C, pH 8 ........................................ E-50

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Figure E- 98: Hydrogen peroxide decay plot –30 mg/L, 4°C, pH 6 .......................................... E-51 Figure E- 99: Hydrogen peroxide decay plot –30 mg/L, 23°C, pH 6 ........................................ E-51 Figure E- 100: Hydrogen peroxide decay plot –30 mg/L, 4°C, pH 6 ........................................ E-52 Figure E- 101: Hydrogen peroxide decay plot –30 mg/L, 4°C, pH 6 ........................................ E-52 Figure E- 102: Hydrogen peroxide decay plot –30 mg/L, 23°C, pH 8 ...................................... E-53 Figure E- 103: Hydrogen peroxide decay plot –30 mg/L, 23°C, pH 8 ...................................... E-53 Figure E- 104: Hydrogen peroxide decay plot –30 mg/L, 4°C, pH 8 ........................................ E-54 Figure E- 105: Hydrogen peroxide decay plot –30 mg/L, 4°C, pH 8 ........................................ E-54 Figure E- 106: HuwaSan peroxide decay plot –1 mg/L, 23°C, pH 6 ........................................ E-55 Figure E- 107: HuwaSan peroxide decay plot –1 mg/L, 4°C, pH 6 .......................................... E-55 Figure E- 108: HuwaSan peroxide decay plot –1 mg/L, 23°C, pH 6 ........................................ E-56 Figure E- 109: HuwaSan peroxide decay plot –1 mg/L, 23°C, pH 6 ........................................ E-56 Figure E- 110: HuwaSan peroxide decay plot –1 mg/L, 4°C, pH 8 .......................................... E-57 Figure E- 111: HuwaSan peroxide decay plot –1 mg/L, 4°C, pH 8 .......................................... E-57 Figure E- 112: HuwaSan peroxide decay plot –1 mg/L, 23°C, pH 8 ........................................ E-58 Figure E- 113: HuwaSan peroxide decay plot –1 mg/L, 23°C, pH 8 ........................................ E-58 Figure E- 114: HuwaSan peroxide decay plot –6 mg/L, 4°C, pH 6 .......................................... E-59 Figure E- 115: HuwaSan peroxide decay plot –6 mg/L, 4°C, pH 6 .......................................... E-59 Figure E- 116: HuwaSan peroxide decay plot –6 mg/L, 23°C, pH 6 ........................................ E-60 Figure E- 117: HuwaSan peroxide decay plot –6 mg/L, 23°C, pH 6 ........................................ E-60 Figure E- 118: HuwaSan peroxide decay plot –6 mg/L, 4°C, pH 8 .......................................... E-61 Figure E- 119: HuwaSan peroxide decay plot –6 mg/L, 4°C, pH 8 .......................................... E-61 Figure E- 120: HuwaSan peroxide decay plot –6 mg/L, 23°C, pH 8 ........................................ E-62 Figure E- 121: HuwaSan peroxide decay plot –6 mg/L, 23°C, pH 8 ........................................ E-62 Figure E- 122: HuwaSan peroxide decay plot –15 mg/L, 4°C, pH 6 ........................................ E-63 Figure E- 123: HuwaSan peroxide decay plot –15 mg/L, 4°C, pH 6 ........................................ E-63 Figure E- 124: HuwaSan peroxide decay plot –15 mg/L, 23°C, pH 6 ...................................... E-64 Figure E- 125: HuwaSan peroxide decay plot –15 mg/L, 23°C, pH 6 ...................................... E-64 Figure E- 126: HuwaSan peroxide decay plot –15 mg/L, 4°C, pH 8 ........................................ E-65 Figure E- 127: HuwaSan peroxide decay plot –15 mg/L, 4°C, pH 8 ........................................ E-65 Figure E- 128: HuwaSan peroxide decay plot –15 mg/L, 23°C, pH 8 ...................................... E-66 Figure E- 129: HuwaSan peroxide decay plot –15 mg/L, 23°C, pH 8 ...................................... E-66 Figure E- 130: HuwaSan peroxide decay plot –30 mg/L, 4°C, pH 6 ........................................ E-67 Figure E- 131: HuwaSan peroxide decay plot –30 mg/L, 4°C, pH 6 ........................................ E-67 Figure E- 132: HuwaSan peroxide decay plot –30 mg/L, 23°C, pH 6 ...................................... E-68 Figure E- 133: HuwaSan peroxide decay plot –30 mg/L, 23°C, pH 6 ...................................... E-68 Figure E- 134: HuwaSan peroxide decay plot –30 mg/L, 4°C, pH 8 ........................................ E-69 Figure E- 135: HuwaSan peroxide decay plot –30 mg/L, 4°C, pH 8 ........................................ E-69 Figure E- 136: HuwaSan peroxide decay plot –30 mg/L, 23°C, pH 8 ...................................... E-70 Figure E- 137: HuwaSan peroxide decay plot –30 mg/L, 23°C, pH 8 ...................................... E-70

Chris Keung 1

Department of Civil Engineering, University of Toronto 2015

1 INTRODUCTION AND RESEARCH OBJECTIVES

1.1 INTRODUCTION

Although there is growing evidence that a large portion of drinking-water illnesses are linked

with distribution system failure (CDC, 2013), there currently seems to be a lack of rational and

quantitative goals for drinking water disinfection in the distribution system. Recently there have

been significant technical advances and improvements that set clear, scientifically-derived

standards within the treatment plant itself such as CT values for primary disinfection.

Unfortunately, secondary disinfection has not followed this trend as seen by the differing

regulations seen across North America and Europe. Most North American utilities are required to

merely maintain some type of “detectable” residual (USEPA, 2006) while some European

countries like the Netherlands do not maintain any disinfectant residuals at all (van der Kooij et

al., 1999). New concerns surrounding disinfection by-products and opportunistic premise

plumbing pathogens (Prevots et al., 2010; Yoder et al., 2010) suggest that a more quantitative,

evidence-based approach is needed in setting secondary disinfection requirements. Even with

new innovative solutions being developed, it is difficult to evaluate alternative treatment

techniques to traditional treatments due to a lack of clear, quantitative performance objectives.

In beginning to create a more rational, quantitative secondary disinfection framework, three main

objectives for maintaining a disinfectant residual have been proposed: (i) to protect against

pathogens that may intrude or grow in the distribution system; (ii) to inhibit biofilm growth

contamination; and (iii) to act as a sentinel of contamination (LeChevallier, 1999; van der Kooij

et al., 1999). In addition to these objectives two other important considerations in choosing a

suitable disinfectant are the direct toxicity of the disinfectant’s components, and disinfection by-

product (DBP) formation (Trussell, 1999).

The main goal of this research was to perform a rational quantitative re-evaluation of the needs

for secondary disinfection and to begin to build a framework in which alternative disinfectants

and treatments can be evaluated for regulatory approval. This research included: a field

sampling campaign at Killaloe, Ontario, where a new, hydrogen-peroxide based secondary

disinfectant (HuwaSan peroxide) is been used to limit DBP formation in the distribution system

(OCWA, 2012; AVIVE, 2015); laboratory bench-scale experiments examining the efficacy of

Chris Keung 2


using different disinfectants as sentinels of contamination; and a systems vulnerability

assessment using a distribution system water quality model (EPANET-MSX).

1.2 RESEARCH OBJECTIVES

1.2.1 Case Study: Killaloe, Ontario HSP Monitoring Campaign (Chapter 3)

The main goal of this study was to conduct a field sampling campaign at Killaloe, Ontario, over

a 9 month period to examine if Huwa-San peroxide (HSP), when used as a secondary

disinfectant, can continue to limit DBP formation, maintain acceptable water quality, and

minimize the formation of other possibily genotoxic byproducts. The following water quality

parameters were monitored at Killaloe to evaluate the performance of HSP:

• Disinfection by-products including trihalomethanes (THMs), haloacetic acids (HAAs),

haloaceticnitriles (HANs), haloketones (HKs), chloropicrin (CP), and total organic

halogens (AOX);

• Genotoxic response using SOS-Chromotest by EBPI;

• HSP residuals;

• Standard water quality parameters including pH, temperature, dissolved organic carbon

(DOC), and UV254;

• Microbial presence in the Killaloe distribution system by measuring adenosine

triphosphate (ATP) and heterotrophic plate counts (HPC) at various locations; and

• Metals including silver, copper, iron, manganese, lead, magnesium, and calcium.

1.2.2 The Ability of Secondary Disinfectants to Serve as Sentinels of

Contamination (Chapter 4)

The main purpose of this study was to conduct laboratory tests on the stability and reactivity of

traditional (chlorine, chloramines) and alternative (chlorine dioxide, hydrogen peroxide,

HuwaSan peroxide) secondary disinfectants with simulated sewage intrusion (used as a worst-

case scenario) to evaluate their ability to serve as sentinels of contamination and to maintain a

residual to protect against contamination. The experiments address two key issues surrounding

the sentinel evaluation: (1) what percent of sewage causes a “noticeable” change in the

disinfectant residual (an arbitrary limit of 30% change in residual was used in this study); and (2)

determination of decay rates (rate constant k-values) as a function of % intrusion for different

Chris Keung 3


disinfectants (Cl2, chloramines, chlorine dioxide, hydrogen peroxide, HuwaSan peroxide),

residual concentrations, pH, and temperatures. Initial disinfectant demands and decay

coefficients (k-values) for different levels of disinfectant type, disinfectant dose, % of intruded

raw sewage pH, and temperature were calculated and are used for subsequent risk-modeling

using EPANET-MSX (Chapter 5) to evaluate different secondary disinfectants with respect to

disinfectant decay and pathogen exposure throughout an example distribution system.

1.2.3 EPANET-MSX Modeling (Chapter 5)

The purpose of this study was to develop a distribution system water quality model using

disinfectant decay and disinfectant kinetics to quantitatively evaluate different disinfectants

(chlorine, chloramines, chlorine dioxide, hydrogen peroxide, Huwa-San peroxide) in their ability

to control downstream propagation of an intruded pathogen and to subsequently compare their

ability to alleviate potential illness rates. The hydraulic and water quality software, EPANET-

MSX was used to estimate population exposure for a microbial intrusion event of raw sewage

and although this model does not include a full QMRA analysis and includes many simplified

assumptions, the main purpose of this microbial risk model was not to determine the exact risk of

contamination but to compare different disinfectants on an order of magnitude scale. Using this

approach may help in the development of a framework in which plausible scenarios for

distribution system risk mitigation can be evaluated. Subsequent work can then superimpose

more accurate models on top of this framework.

1.3 DESCRIPTION OF CHAPTERS

• Chapter 2 provides a review of literature discussing the following items: hydrogen

peroxide based disinfectants; key papers and findings (hydrogen peroxide/silver

disinfectant); key papers and findings (HuwaSan peroxide); and HuwaSan peroxide case

studies (Killaloe and Southwest Middlesex).

• Chapter 3 presents results from the Killaloe, Ontario, sampling campaign in evaluating

the use of HuwaSan peroxide (HSP) as a secondary disinfectant.

• Chapter 4 presents results from the laboratory bench-scale tests evaluating the stability

and reactivity of different secondary disinfectants in serving as sentinels of

contamination.

Chris Keung 4


• Chapter 5 presents a systems vulnerability assessment using the distribution system water

quality model, EPANET-MSX, to model pathogen dispersion throughout a distribution

system to quantitatively evaluate different disinfectant scenarios.

• Chapter 6 summarizes significant findings of this research and provides

recommendations for distribution system operations and future work.

1.4 REFERENCES

AVIVE (2015) The AVIVE Solution. Retrieved September 20, 2014, from http://www.avivewater.com/the-science/the-avive-solution/

CDC (2013) Surveillance for Waterborne Disease Outbreaks Associated with Drinking Water and Other Nonrecreational Water - United States, 2009-2010. Morbidity and Mortality 62(35), 714-720.

LeChevallier, M.W. (1999) The Case for Maintaining a Disinfectant Residual. Journal of the American Water Works Association 91(1), 86-94.

OCWA (2012) Design Brief Killaloe Drinking Water System: Supporting Information Application for Regulatory Relief, Ontario Clean Water Agency, Mississauga, ON.

Prevots, D.R., Shaw, P.A., Strickland, D., Jackson, L.A., Raebel, M.A., Blosky, M.A., Montes de Oca, R., Shea, Y.R., Seitz, A.E. and Holland, S.M. (2010) Nontuberculous Mycobacterial Lung Disease Prevalence at Four Integrated Health Care Delivery Systems. American Journal of Respiratory and Critical Care Medicine 182(7), 970-976.

USEPA (2006). National Primary Drinking Water Regulation; Stage 2 Disinfectants and Disinfection Byproducts Rule; Final Rule. Federal Register 71(388), January 4, 2006.

van der Kooij, D., Hein, J., van Lieverloo, M., Schellart, J. and Hiemstra, P. (1999) Maintaining Quality Without a Disinfectant Residual. Journal of the American Water Works Association 91(1), 86-94.

Yoder, J., Eddy, B., Visvesvara, G., Capewell, L. and Beach, M. (2010) The Epidemiology of Primary Amoebic Meningoencephalitis in the USA, 1962–2008. Epidemiology and Infection 138(07), 968-975.

Chris Keung 5


2 LITERATURE REVIEW

2.1 HYDROGEN PEROXIDE BASED DISINFECTANTS

Hydrogen peroxide (H2O2) has frequently been used in the food and pharmacological industry as

well in some drinking water applications (primary disinfection) based on its known bactericidal

and bacteriostatic action (Gardiner et al., 1983) but its use as a drinking water secondary

disinfectant is still limited. H2O2 is considered a strong oxidizer with an oxidation potential of

1.8V, which is just below ozone at 2.1V, but stronger than chlorine and chlorine dioxide with

oxidation potentials of 1.5V and 1.4V respectively (Lenntech, 2015). AVIVE™ has begun to

market a proprietary form of H2O2 called Huwa-San Peroxide (HSP) that combines food-grade

H2O2 with a small amount of soluble silver ions (approximately 4-5 ppb) that reportedly

increases the stability of the H2O2 solution (AVIVE, 2015). The manufacturer also claims that

the product is a stronger disinfectant than traditional H2O2 due to silver ions emitting electrostatic

forces that de-stabilize catalase enzymes secreted by bacteria, thus allowing the H2O2 to react

directly with the bacteria (HuwaSan, 2015). Using a similar a generic combination of H2O2 and

silver ions, Pedahzur et al. (1995) proposed that the main advantages of the combination of

H2O2/silver disinfectant are the low toxicity of its components, the ability to have a long lasting

residual and minimal DBP formation (Pedahzur et al,. 1995). HSP is certified under Drinking

Water Standard 60 by NSF and the manufacturer claims that is does not create any other by-

products besides water, oxygen, and low concentrations of silver oxides (AVIVE, 2015).Other

reported advantages of HSP are that it: is stable at elevated temperatures (Kraemer et al., 2014);

has the ability to treat biofilm bacteria including Legionella pneumphila and Pseudomonas

aeruginosa (Kraemer et al., 2014); is easy to use for operators (similar to chlorine); and does not

produce any adverse tastes or odors (Valikis and Shubat, 2013).

2.1.1 Key Papers and Findings (Hydrogen Peroxide/Silver Disinfectant)

At representative concentrations found in distribution system disinfection, H2O2 and silver ions

do not constitute a potential health risk (USEPA, 2011). Food-grade hydrogen peroxide is often

used as a food additive in products such as toothpaste and mouthwash (Gardiner et al., 1983).

Furthermore, ionic silver is not on the USEPA primary drinking water contamination list. It is,

however, on the secondary drinking water contaminant list because long-term exposure at

concentrations greater than 100 ppb may cause skin discoloration (Armon et al., 2000).

Chris Keung 6


A study conducted by Armon et al. (2000) concluded that for biofilm suppression, the

combination of 30 ppm H2O2 and 30 ppb of silver nitrate (AgNO3) was just as effective as H2O2

alone (30 ppm), significantly reducing bulk water bacteria (diverse, indigenous bacteria rather

than specific strain) by 4-logs and attached biofilm bacteria by 1-log magnitude. Silver ions

alone (30 ppb) did not inactivate either the bulk water or biofilm bacteria. The inactivation

activity was seen to be higher at the first stages of biofilm formation and less effective at later

stages (Armon et al., 2000).

Pathogen inactivation kinetics for H2O2 and silver ions individually and in combination were

determined for target microorganisms in synthetic high quality water and high TOC water (6

mg/L). The combination of H2O2 and silver was more effective in the inactivation of E. coli. B

and E. coli. K12 compared to each one acting separately (Liberti et al., 2000). Pedahzur et al.

(2000) also found that the combined disinfectant had a synergistic effect for bacterial

inactivation, sometimes up to 1000-fold higher than each separate component but showed no

increase for synergistic viral inactivity. However, bacterial and viral inactivation for the

formulation of 30-ppm H2O2/30-ppb silver complex was slow compared to the chlorine

disinfectant. 3-log reductions at pH 7 and 24 °C required the H2O2/silver combination (30 ppm-

H2O2 and 30-ppb silver ions) for 77 minutes for E.coli. B and 802 minutes for MS-2 while 1 ppm

chlorine required 15 minutes for E.coli. B and 2 minutes for MS-2 (Liberti et al., 2000).

Shuval et al. (2009) undertook a 24 month study using a stabilized H2O2/silver complex to

control Legionaella pneumophila in hot water systems. Hot water systems usually operate at 40-

50°C making them favorable for biofilm development. Previous treatment using shock

treatments of chlorine (up to 2000 ppm) or raising temperatures above 70°C were unsuccessful

for long-term Legionella control. Using the H2O2/silver complex at a concentration of 20 ppm

(following an initial shock dose of 500 ppm of the H2O2/silver complex successfully controlled

Legionella in the hot water systems (i.e. no positive samples over the 24-month period). With

chlorine, its stability was significantly reduced at elevated temperatures. The H2O2/silver

formulation was found to be stable at high temperatures along with increased disinfection ability

at higher temperatures (Shuval et al., 2009). Another study conducted by Toté et al. (2009)

found that low water temperature had a negative effect on both bactericidal and fungicidal

properties of both the H2O2/silver complex and H2O2 alone. At 0°C, the activity of the

Chris Keung 7


H2O2/silver complex compared to activity at room temperature was reduced by over 90% and the

H2O2 alone was totally ineffective. Conversely, at high temperatures, the performance of both

H2O2 and its silver complex was enhanced. The H2O2/silver formulation (50% - 500 mg/L)

achieved total inactivation of bacteria and fungi within 30 minutes at 40°C compared to 1 hour at

room temperature. H2O2 alone (50%) required 1 and 2 hours for 40°C and room temperature

respectively. At similar conditions (30 minutes, 40°C), the bactericidal activity of the H2O2/silver

complex increased by more than 4-log compared to only a 2-log increase using H2O2 alone (Toté

et al., 2009). One hypothesis for the increased activity at elevated temperatures is that through

catalysis, H2O2 can be converted to highly reactive hydroxyl radicals (OH●) which are more

readily produced as temperatures increase (Toté et al., 2009).

Batterman et al. (2000) compared trihalomethane (THMs) and haloacetic acid (HAAs) formation

between chlorine and a H2O2/silver disinfectant following a 10 minute chlorination period.

THMs and HAAs after 24 hours for the silver/hydrogen peroxide combination were lower than

chlorine at an average of 72 ± 9% for THMs and 67 ± 11% for HAAs. The proposed mechanism

is based on the idea that H2O2 acts as a chlorine quenching agent and instantaneously reduces

chlorine to chloride thereby stopping the DBP forming reaction between chlorine and DBP

precursors (Batterman et al., 2000).

2.1.2 Key Papers and Findings (HuwaSan Peroxide)

In a study conducted by Martin et al. (2015), in comparing antimicrobial efficacy as determined

by the reduction of E. coli K12, at pH 8.5, HSP (2-log inactivation after 30 mins) was more

effective than sodium hypochlorite (0.6-log inactivation after 30 mins). At pH 7, HSP and

sodium hypochlorite were equally effective (Martin et al., 2015). Martin et al. (2015) also

suggested that the increased bacterial inactivation seen in HSP compared to H2O2 is caused by

the addition of cations (Ag+ in HSP) which inhibits the electrostatic interactions between HSP

and the negatively charged bacterial cell surfaces, thus allowing the HSP to interact directly with

the bacterial cell surface (i.e. less susceptible to inactivation by catalase). The silver ions acting

alone at relevant concentrations (0-375 ppb) found in HSP were observed to have a negligible

bactericidal effect, thus, providing reason that the silver ions serve as a mechanism of action that

promote electrostatic interactions at the cell surface allowing the peroxide component in the HSP

to serve as the primary biocidal inactivation agent (Martin et al., 2015).

Chris Keung 8


2.1.3 HuwaSan Peroxide Case Studies (Killaloe and Southwest Middlesex)

Killaloe is a small town in Ontario with a distribution system of approximately 90 service

connections serving approximately 207 residents with 3.5 km of PVC pipe. To reduce DBP

formation, Killaloe has implemented an initial project using Huwa-San Peroxide (HSP) instead

of chlorine as their secondary disinfectant. Killaloe’s source water is considered a GUDI well

(groundwater under the direct influence of surface water), and has been awarded in-situ filtration

credit. The treatment process consists of sodium hypochlorite and potassium permanganate

addition prior to a greensand filter to remove iron and manganese, with chlorine providing 4-log

virus reduction across the greensand filter. The water then flows through a UV reactor for

Giardia and Cryptosporidium inactivation credit. Huwa-San Peroxide (HSP) is then added to

quench the residual chlorine and to provide a disinfectant residual throughout the distribution

system. A dose of approximately 8-12 mg/L of HSP is required to maintain an optimum residual

of 3-8 mg/L. The target minimum residual in the distribution system is 5 mg/L, and the Ministry

of Environment has determined that a concentration of less than 1 mg/L will be considered an

adverse condition (OCWA, 2012).

An earlier pilot study at Killaloe, Ontario, evaluated the ability of HSP in limiting formation of

chlorinated DBPs and to control water quality by monitoring bacteriological indicators (Kraemer

et al., 2014). The results of the study showed that lower THMs and HAAs were observed in the

distribution system when using HSP compared to chlorine as a secondary disinfectant. Using

chlorine prior to implementation of the HSP, total THMs in the Killaloe system ranged from 20-

200 μg/L with approximately 45% of all of the THM samples exceeding the 100 μg/L total THM

regulatory limit (Health Canada, 2014). After the switch to HSP as a secondary disinfectant,

THM levels in the Killaloe system were measured at concentrations between 20-27 μg/L

(OCWA, 2012; Kraemer et al., 2014). HAA concentrations were measured in the treatment plant

clearwells and were observed to have decreased from an average of 61 to 8 μg/L after the switch

to HSP (OCWA, 2012; Kraemer et al., 2014). Lower concentrations of measured THMs and

HAAs after the switch to HSP was likely due to the ability of H2O2 in the HSP in quenching the

chlorine residual – in turn halting further DBP formation reaction between the chlorine residual

and organic matter (Batterman et al., 2000).

Chris Keung 9


In another study conducted in the municipality of Southwest Middlesex, Ontario, the stability of

HSP was evaluated for different pipe materials (PVC, asbestos cement, ductile iron, cast iron,

galvanized and copper). HSP maintained a significant residual and good water quality results

with all materials with the exception of cast iron tuberculated pipe where an initial 10 mg/L dose

of HSP was lost in less than 15 minutes and accompanied by an immediate rusty orange color

change (Valikis and Shubat, 2013).

2.2 REFERENCES

Armon, R., Laot, N., Lev, O., Shuval, H. and Fattal, B. (2000) Controlling Biofilm Formation by Hydrogen Peroxide and Silver Combined Disinfectant. Water Science & Technology 42(1), 187-192.

AVIVE (2015) The AVIVE Solution. Retrieved September 20, 2014, from http://www.avivewater.com/the-science/the-avive-solution/

Batterman, S., Zhang, L. and Wang, S. (2000) Quenching of Chlorination Disinfection by-Product Formation in Drinking Water by Hydrogen Peroxide. Water Research 34(5), 1652-1658.

Gardiner, R.E., Hobbs, N.J. and Jeffery, J. (1983) Hydrogen Peroxide a Real Alternative to Chlorine in Water Treatment?, Ann Arbor Science Pub., Ann Arbor.

Health Canada (2014) Guidelines for Canadian Drinking Water Quality. Retrieved April 23, 2015, from http://www.hc-sc.gc.ca/ewh-semt/pubs/water-eau/sum_guide-res_recom/index-eng.php

HuwaSan (2015) HuwaSan. Retrieved November 20, 2014, from http://www.huwasan.com/faq

Kraemer, L.D., Balch, G., Broadbent, H., Iutzi, M. and Wootton, B.C. (2014) Validation of the AVIVE Water Treatment Solution - Using Huwa-San Hydrogen Peroxide as an Alternative to Chlorine-Based Disinfection Technology, Fleming College, Lindsay, ON.

Lennetch (2015) Water Treatment Solutions - Disinfectants Hydrogen Peroxide. Retrieved July 10, 2015, from http://www.lenntech.com/processes/disinfection/chemical/disinfectants-hydrogen-peroxide.htm

Liberti, L., Lopez, A., Notarnicola, M., Barnea, N., Pedahzur, R. and Fattal, B. (2000) Comparison of Advanced Disinfecting Methods for Municipal Wastewater Reuse in Agriculture. Water Science & Technology 42(1-2), 215-220.

Martin, N., Bass, P., Liss, S.N. (2015) Antibacterial Properties and Mechanism of Activity of a Novel Silver-Stabilized Hydrogen Peroxide. PLOS One 10(7), 1-20.

Chris Keung 10



Pedahzur, R., Katzenelson, D., Barnea, N., Lev, O., Shuval, H., Fattal, B. and Ulitzur, S. (2000) The Efficacy of Long-Lasting Residual Drinking Water Disinfectants Based on Hydrogen Peroxide and Silver. Water Science & Technology 42(1-2), 293-298.

Pedahzur, R., Lev, O., Fattal, B. and Shuval, H.I. (1995) The Interaction of Silver Ions and Hydrogen Peroxide in the Inactivation of E. Coli: A Preliminary Evaluation of a New Long Acting Residual Drinking Water Disinfection. Water Science & Technology 31(5), 123-129.

Shuval, H., Yarom, R. and Shenman, R. (2009) An Innovative Method for the Control of Legionella Infections in the Hospital Hot Water Systems with a Stabilized Hydrogen Peroxide-Silver Formulation. International Journal of Infection Control 5(1), 1-5.

Toté, K., Vanden Berghe, D., Levecque, S., Bénéré, E., Maes, L. and Cos, P. (2009) Evaluation of Hydrogen Peroxide‐Based Disinfectants in a New Resazurin Microplate Method for Rapid Efficacy Testing of Biocides. Journal of Applied Microbiology 107(2), 606-615.

USEPA (2011). 2011 Edition Drinking Water Standards and Health Advisories. Office of Water, U.S Environmental Protection Agency EPA 820-R-11-002, January, 2011.

Valikis, A.K. and Shubat, J. (2013) Killaloe Water System, AVIVE Water Treatment and Huwa-San Peroxide, London, ON.

Chris Keung 11


3 CASE STUDY: KILLALOE, ONTARIO HSP MONITORING CAMPAIGN

ABSTRACT

Between September 2014 and May 2015, a sampling campaign was completed at

Killaloe, Ontario to evaluate if a new hydrogen peroxide-based disinfectant

(HuwaSan peroxide), when used as a secondary disinfectant, could limit

disinfection by-product (DBP) formation. Results from the study show that

HuwaSan peroxide (HSP), when used as a secondary disinfectant, can limit DBP

formation in the distribution system while maintaining acceptable water quality.

When using chlorine as a secondary disinfectant, trihalomethanes (THMs) and

haloacetic acids (HAAs) in the distribution system averaged between 92-114 and

55-67μg/L respectively. Using HSP, over the nine-month period, THMs and

HAAs ranged between 23-45 and 14-26 μg/L respectively. Prechlorination was

found to be the major source of DBP formation based on THM, HAA, total

organic halogens (AOX), and genotoxicity results. The likely mechanism is that

DBP formation is slowed after the quenching of the chlorine residual due to HSP

addition. Based on ATP measurements, HSP was not completely effective in

suppressing microbial growth within the distribution system as measured ATP

increased from the plant effluent to points throughout the distribution system.

3.1 INTRODUCTION Some drinking water utilities control disinfection (chlorination) by-products (DBPs) by using

alternatives to chlorine for secondary disinfection. The most common alternative in North

America is monochloramine, but chlorine dioxide (ClO2) has also been used as a secondary

disinfectant in a number of small systems (Baribeau et al., 2005). AVIVE™ has developed a

proprietary stabilized hydrogen peroxide with low concentrations of silver, called HuwaSan

Peroxide (HSP), that the manufacturer claims is a strong, stable, and safe disinfectant that can

significantly reduce DBPs during drinking water distribution. Other commercial formulations of

hydrogen peroxide and silver have been approved as drinking water disinfectants in a number of

countries in Europe such as Switzerland, Germany and France (Pedahzur et al., 1995).

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In 2012, HSP was approved by the Ontario Ministry of Environment for use as a secondary

disinfectant in the town of Killaloe, Ontario, to replace chlorine with the aim of reducing DBPs

in their distribution system. Prior to the change, THMs ranged from 20-200 μg/L with

approximately 45% of the total THM samples in the treated water (at the treatment plant or the

distribution system) over the 100 μg/L total THM Ontario Drinking Water regulatory limit

(Health Canada, 2014). The treatment process at Killaloe consists of the addition of sodium

hypochlorite (NaOCl) and potassium permanganate (KMnO4) prior to a greensand filter to

remove iron and manganese, with chlorine providing 4-log virus reduction across the greensand

filter. The water then flows through a UV reactor for Giardia and Cryptosporidium inactivation

credit. HSP is then added to quench the residual chlorine and to provide a disinfectant residual

throughout the distribution system. A dose of approximately 8-12 mg/L of HSP is required to

maintain an optimum residual of 3-8 mg/L throughout the system. Initial testing after the switch

to HSP showed reductions in THM concentrations to below 25 μg/L with the majority of DBP

formation occurring during the pre-chlorination and primary disinfection phases, after which the

chlorine residual is quenched with the addition of HSP. HAA concentrations in the system were

also reduced from an average of 61 to 8 μg/L after the switch to HSP (OCWA, 2012a; Kraemer

et al., 2014). Initial results using HSP to reduce DBPs at Killaloe looks promising, but HSP is

still a new, proprietary chemical and further research is still required to evaluate its use as a

viable secondary disinfectant in terms of maintaining acceptable water quality (measured by

common water quality parameters) while minimizing the formation of other byproducts.

3.1.1 Research Objectives

The main goal of this study was to conduct a field sampling campaign at Killaloe, Ontario, over

a 9 month period to examine if HSP, when used as a secondary disinfectant, can continue to limit

DBP formation, maintain acceptable water quality, and minimize the formation of other

genotoxic byproducts. The following water quality parameters were monitored at Killaloe to

evaluate the performance of HSP:

• Disinfection by-products including trihalomethanes (THMs), haloacetic acids (HAAs),

haloacetonitriles (HANs), haloketones (HKs), chloropicrin (CP), total organic halogens

(AOX);

• Genotoxic response using SOS-Chromotest by EBPI;

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• HSP residuals;

• Standard water quality parameters including pH, temperature, dissolved organic carbon

(DOC), and UV254;

• Microbial presence in the Killaloe distribution system by measuring adenosine

triphosphate (ATP) and heterotrophic plate counts (HPC) at various locations; and

• Metals including silver, copper, iron, manganese, lead, magnesium, and calcium to

observe if HSP affects corrosion and the release of metals.

3.2 MATERIALS AND METHOD

3.2.1 Analytical Methods

3.2.1.1 Trihalomethanes (THMs), Haloacetonitriles (HANs), Haloketones (HK), Chloropicrin (CP), and Haloacetic Acids (HAAs)

Trihalomethane (THM) (chloroform (trichloromethane, TCM), bromodichloromethane (BDCM),

dibromochloromethane (DBCM), and bromoform (tribromomethane, TBM)) and

haloacetonitriles (HAN) (trichloroacetonitrile (TCAN), dichloroacetonitrile (DCAN),

bromochloroacetonitrile (BCAN), dibromoacetonitrile (DBAN)), haloketones (HK)

(dichloropropanone (DCP)), and chloropicrin (CP) analyses were conducted using a liquid-liquid

extraction gas chromatographic method based on Standard Method 6232 B (APHA, 2012).

Haloacetic acids (HAAs) (monochloroacetic acid (MCAA), monobromoacetic acid (MBAA),

dichloroacetic acid (DCAA), trichloroacetic acid (TCAA), bromochloroacetic acid (BCAA),

dibromoacetic acid (DBAA), bromodichloroacetic acid (BDCAA), dibromochloroacetic acid

(DBCAA), and tribromoacetic acid (TBAA)) analysis were conducted using a liquid-liquid

extraction gas chromatographic method based on Standard Method 6251 B (Rice et al., 2012).

All analyses were conducted at the University of Toronto laboratory (Toronto, ON) using a

Hewlett Packard 5890 Series II Plus Gas Chromatograph (Mississauga, ON) equipped with an

electron capture detector (GC-ECD) and a DB 5.625 capillary column (Agilent Technologies

Canada Inc., Mississauga, ON). THM instrument conditions, required reagents and method

outline are described in Tables B-1, B-2, and B-3 respectively (Appendix B). The minimum

detection limit (MDL) for THM species is shown in Table B-4 and B-5 (Appendix B). HAA

instrument conditions, required reagents method outlines and method MDLs are described in

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Tables B-6, B-7, B-8, and B-9 respectively (Appendix B). MDLs were determined by

multiplying the standard deviation of 8 replicates, prepared in the same order of magnitude as the

expected MDL, by the Student-t value (3.0).

3.2.1.2 Adsorbable Organic Halogens (AOX)

Adsorbable organic halogens (AOX) include a large group of substances that may be of health

and environmental concern including simple volatile substances and complex organic substances

with a variety of potentially toxic properties. AOX analysis was conducted using a titration

method based on Standard Method 5320 (Rice et al., 2012). All analyses were conducted at the

University of Toronto laboratory (Toronto, ON) using a Trace Element Instruments Xplorer

organic halogens analyzer (Delft, Netherlands). Instrument conditions, reagents and method are

shown in Tables B-10, B-11, and B-12 (Appendix B). Samples were run in duplicates, and a

check standard (100 μg/L) was injected into the test cell before each sample series.

3.2.1.3 Dissolved Organic Carbon (DOC)

Dissolved organic carbon (DOC) was measured using the wet oxidation method based on

Standard Method 5310 D (Rice et al., 2012). The analysis was carried out using an O-I

Corporation Model 1010 Analytical TOC Analyzer with a Model 1051 Vial Multi-Sampler. The

instrument conditions are shown in Table B-13 (Appendix B). Water samples were filtered using

a 0.45 μm fiber glass filter, transferred to 40 mL amber vials, and capped with Teflon®-lined

septum screw caps. Samples were stored at 4ºC and tested within 7 days of collection. DOC

concentrations in water samples were quantified using anhydrous potassium hydrogen phthalate

(KHP) in Milli-Q® water calibration solution. The reagent list and the method outline are listed

in Tables B-14 and B-15 respectively (Appendix B).

3.2.1.4 Ultraviolet Absorbance at 254nm (UV254)

The ultraviolet absorbance at 254 nm (UV254) was determined using a CE 3055 Single Beam

Cecil UV/Visible Spectrophotometer (Cambridge, England) using a 1 cm quartz cell (Hewlett

Packard, Mississauga). The spectrophotometer was zeroed with Milli-Q® water. Quartz cells

were rinsed with Milli-Q® water and the sample between measurements.

3.2.1.5 Adenosine Triphosphate (ATP) Measurement

A Luminultra adenosine triphosphate (ATP) analysis kit (DSA-100C, Fredericton, NB) was used

Chris Keung 15


to carry out the ATP analysis following manufacturer instructions as shown in Table B-16

(Appendix B). Aqueous samples were obtained from the distribution system in 500 mL amber

glass bottles.

3.2.1.6 Heterotrophic Plate Count (HPC)

Heterotrophic plate counts (HPC) were analyzed by SGS Environmental Services (Lakefield,

Ontario). Heterotrophic bacteria were determined by membrane filtration based on Standard

Methods, Section 9215A (Rice et al., 2012). The full HPC method summary can be found in

Table B-17 (Appendix B).

3.2.1.7 Metal Analysis

Dissolved metals in the water samples were analyzed using inductively coupled plasma mass

spectrometry (ICP-MS) by SGS Environmental Services (Lakefield, Ontario). The method is

derived from EPA Method 200.7 (Martin et al., 1994), Standard Method 3030 B and Standard

method 3030 D (Rice et al., 2012). The full method summary can be found in Table B-18

(Appendix B).

3.2.1.8 Genotoxicity – SOS Chromotest Bioassay

Genotoxicity was quantified with the SOS Chromotest™ bioassay (EBPI, Canada), where 100

µL of diluted bacterial suspension (prepared overnight and diluted to 0.05 optical density at 600

nm) was added to each well and incubated with serially diluted samples at 37˚C for 2h.

Following incubation, 100 µL of chromogen for beta-galactosidase (beta-gal) and alkaline

phosphatase (AP) was added to each well and incubated at 37˚C for an additional hour. A

positive control (4-NQO) was tested on every plate, alongside the samples. A microplate reader

(Infinite 200, Tecan, Morrisville, NC) was used to read the activity of beta-gal (OD605) and AP

(OD420) to calculate the SOS induction factor (IF). Solid phase extraction (SPE) is performed to

concentrate the samples in order to achieve a response threshold. The concentration is expressed

as the equivalent mL in each well. To provide context, 16.5 equivalent mL is representative of a

sample that was concentrated 158 fold. Full method summaries for the SOS Chromotest™ and

SPE can be found in Tables B-19 and B-20 respectively (Appendix B).

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3.2.2 Study to Identify the HSP Quenching Agent for DBP Analysis

Preliminary experiments were conducted to determine an appropriate compound to quench

Huwa-San Peroxide (HSP) while ensuring the stability of the DBPs monitored. All tests were

conducted in Milli-Q® water spiked with the DBP stock solutions followed by the addition of 15

mg/L HSP. The absolute concentration of the specific DBPs spiked into solution differed due to

variations in the stock solutions. A control without the addition of HSP or quenching agent was

used to correct for the variation between different DBP species. Solutions were allowed to react

for 10 minutes before the addition of various quenching agents.

Quenching agents tested included catalase (0.2 mg/L), sodium sulfite (150 mg or 600 mg/L),

sodium thiosulfate (120 mg or 480 mg/L), ascorbic acid (100 mg or 400 mg/L), and ammonium

chloride (100 mg or 400 mg/L). DBPs were analyzed on the same day of the quenching agent

addition (Day 0) and 5 days later (Day 5). DBP analysis and protocols were followed according

to Section 3.2.1.1

3.2.3 Killaloe Sampling Campaign

Table 3-1: Killaloe sampling sites

Site # Description 1 Raw water (GUDI well) 2 Post greensand filter (contains Cl2) 3 Post HSP Addition (Cl2 residual quenched and HSP residual maintained) 4 Plant Effluent 5 Tourist Kiosk (first point in distribution system) 6 Summer’s Motors (intermediate point in distribution system) 7 Afelski’s Shoes (end point in distribution system) 8 McCarthy’s Propane (end point in distribution system)

Water samples were collected from Killaloe on September 9, 2014, October 28, 2014, February

3, 2015, and May 20, 2015. Raw water is supplied by a groundwater source under the direct

influence of surface water (GUDI well). GUDI refers to situations where groundwater sources

are vulnerable to pathogen contamination from nearby surface waters (Nnadi and Fulkerson,

2002). Eight locations were sampled: raw water; post greensand (contains Cl2); post HSP

application (downstream of UV); plant effluent; and at four locations in the distribution system.

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Table 3-1 provides a description of the Kilalloe sampling sites. Water age in the distribution

system ranged between 24 and 72 hours. Samples were analyzed for HPC, dissolved metals,

disinfectant residual, pH, temperature, DOC, UV254, DBPs (THM, HAA, HAN, HK, CP, AOX),

adenosine triphosphate (ATP), and genotoxicity.

3.2.4 Historical Data

Samples collected as part of the current campaign were compared to a previous study conducted

by the Centre for Alternative Wastewater Treatment at Fleming College that monitored water

quality parameters at Killaloe immediately following the HSP switch (Kraemer et al., 2014), as

well as previous annual water reports issued for the town of Killaloe. For the Fleming College

study, samples were collected between December 13, 2012 and April 2, 2013 at seven locations:

raw water; treated water leaving the plant; and at 5 locations in the distribution system. DBPs,

residual testing, and ATP analysis followed the same methodology as the current sampling

campaign.

3.3 RESULTS AND DISCUSSION

3.3.1 Study to Identify the HSP Quenching Agent for DBP Analysis

It was necessary to quench the residual HSP in DBP samples to prevent potential changes in

DBP concentrations during sample shipment from Killaloe to the University of Toronto. Work

was undertaken to identify a quenching agent that quickly eliminated HSP from the sample,

without affecting the measured concentration of DBPs.

Figures A-1 to A-20 in Appendix A show initial DBP concentrations in spiked Milli-Q water

(Day 0) and DBP concentrations after Day 5 following the addition of the various quenching

agents (catalase, sodium sulfite, sodium thiosulfate, ascorbic acid, and ammonium chloride).

Two sets of paired Student t-tests were conducted in order to determine if the differences in DBP

concentrations between the quenched samples and the control DBP samples were significant at a

95% confidence interval. The tests were used to identify whether the quenching agent would halt

DBP formation without degrading the already present compounds at Day 0 and Day 5 compared

to a control sample. The first test compared the change in DBP concentrations of the quenched

samples (Milli-Q water with DBPs, HSP and quenching agent) at Day 0 to the control samples

Chris Keung 18


(only Milli Q water with DBPs) at Day 0 to determine the initial stability of the DBPs in the

presence of the quenching agent and HSP. In the second comparison, the quenched (Milli-Q

water with DBPs, HSP and quenching agent) and control samples (only Milli-Q with DBPs)

were compared at Day 5 in order to determine the stability of the DBPs five days after

quenching.

Table 3-2: Paired student t-test comparing DBP degradation for quenching agents at day 0 and day 5

Quenching Agent DBP + HSP

Ammonium Chloride + DBP + HSP

Sodium Sulfite +

DBP + HSP

Sodium Thiosulfate

+ DBP + HSP

Ascorbic Acid + DBP

+ HSP

Catalase + DBP + HSP

Test Day 0

Day 5

Day 0

Day 5

Day 0

Day 5

Day 0

Day 5

Day 0

Day 5

Day 0

Day 5

TCM No No No No No No Yes Yes No No Yes Yes BDCM No No No No Yes Yes No No No No No No CDBM No No No No Yes Yes No No No No N/A N/A TBM No No No No No No No No No No No No

TCAN N/A N/A N/A N/A N/A N/A No N/A No No No No DCAN No No Yes Yes Yes Yes Yes Yes No No No No DCP No No No No N/A N/A N/A N/A No No No No CP No No Yes Yes N/A N/A N/A N/A No No No No

BCAN No No No No N/A N/A N/A N/A No No No No TCP No No Yes Yes N/A N/A N/A N/A No No Yes Yes

DBAN No No No No Yes Yes Yes Yes Yes Yes No No MCAA Yes No Yes No N/A Yes N/A Yes Yes Yes Yes No MBAA Yes Yes No Yes Yes Yes Yes Yes No Yes No No DCAA No No No No Yes Yes Yes Yes Yes Yes No No TCAA Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes BCAA No Yes No Yes Yes Yes Yes Yes Yes Yes Yes Yes DBAA Yes Yes No Yes Yes Yes No Yes Yes No Yes No

BDCAA Yes No No No Yes Yes Yes Yes No Yes No No CDBAA Yes Yes No No Yes Yes No Yes Yes Yes No No TBAA Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

Shaded “Yes” cells represent a statistically significant difference between quenching agent sample and control sample

Table 3-2 is a summary of the two sets of paired Student t-tests comparing DBP degradation for

each quenching agent to a control sample at Day 0 and at Day 5. Shaded cells in the tables

indicate a statistically significant difference between the quenching agent and the controls (i.e.

the quenching agent impairs the result). A suitable quenching agent should ideally remove the

Chris Keung 19


HSP immediately and any remaining quenching agent in the solution should not cause a

significant change in DBP concentrations compared to the control DBP samples. TCAN and

TBAA were always unstable regardless of the quenching agent used. TBAA is not expected to be

present in the Killaloe water (it is usually found only in high-bromide waters). The cause of the

TCAN instability is unknown, and it was subsequently excluded from this study. MCAA and

TCAA showed some instability for all quenching agents analyzed, but the decay in the presence

of catalase was relatively minor (<20%) compared to between 9% and 88% with the other

quenching agents, although still statistically significant. Sodium sulfite (NaSO3) and sodium

thiosulfate (Na2S2O3) greatly decreased the DCAN, DCP, CP, BCAN, TCP, DBAN, MBAA, and

DCAA concentrations. The DBP concentrations of the catalase samples appeared to remain quite

stable for the majority of the analyzed DBPs. Thus, catalase was chosen as the quenching agent.

Catalase is also reported to be non-toxic to most micro-organisms (Toté et al., 2009), and

therefore could also be used to quench the HSP prior to HPC analysis.

3.3.2 Killaloe Sampling Campaign

The Killaloe sampling campaign took place over nine months between September 2014 and May

2015 in which samples were analyzed for common water quality parameters (pH, temperature,

residual concentration, DOC, UV254, ATP, HPC), metals, DBPs (THMs, HANs, HKs, CP,

HAAs, and AOX), and genotoxicity. Table C-1 in Appendix C shows a complete summary for

the Killaloe sampling campaign.

The measured HSP residual leaving the treatment plant (Site 4) ranged from 7.1 to 8.1 mg/L and

in the distribution system ranged from 3.0 to 6.3 mg/L with the lowest concentrations usually

occurring at McCarthy’s Propane (Site 8), one of the end points of the distribution system with

the longest residence time. The estimated water age in the distribution system is between 24 and

72 hours. The target minimum residual in the distribution system is 5 mg/L, and the Ministry of

Environment has determined that a concentration of less than 1 mg/L would be considered an

adverse condition (OCWA, 2012a).. Historical data from the 2012 Annual Water Report when

using chlorine as a secondary disinfectant reported chlorine residuals between 0.72 to 1.91 mg/L

in water leaving the plant and in the distribution system between 0.11 to 1.37 mg/L (OCWA,

2012b). Using the lowest observed distribution system residual concentration, it appears that

HSP residuals decreased between 4.1 to 5.1 mg/L during distribution while chlorine only

Chris Keung 20


decreased between 0.61 to 1.8 mg/L, suggesting that HSP is less stable than chlorine under these

conditions.

ATP is a metabolic compound found in all living organisms which makes it a useful indicator for

measuring the microbial biomass in water. ATP will degrade outside of living cells and therefore

can be used to differentiate between living and dead organic matter. This makes it useful in

evaluating the microbiological activity in both the bulk phase and biofilms (van der Kooij et al.,

1999; van der Wielen and van der Kooij, 2010; Vang, 2013). Measurement of ATP is simple and

rapid making it a useful parameter to help evaluate whether secondary disinfectants are effective

in suppressing microbial growth. ATP is measured using a bioluminescent method in which the

amount of ATP is directly proportional to the amount of fluorescence. Relative light units

(RLU), the unit of measure on most ATP instruments, are not standardized units of measurement

since ATP monitoring systems have different sensitivities and detection (3M, 2014). Thus, RLUs

are converted to ATP values such as cellular ATP (cATP) which represent the amount of ATP

contained within living cells or microbial equivalents (ME/mL) if reporting the results on the

same basis as traditional culture tests (it assumes that 1 E. coli-sized bacteria contains 0.001 pg

of ATP) (LuminUltra, 2013). A summary of the ATP analysis showing ATP as microbial

equivalents (ME/mL) for the Killaloe system pre and post HSP addition is shown in Tables 3-3.

Table 3-3: Microbial equivalents (ME/mL) assessed via ATP luminescence assay in raw and treated drinking water collected from Killaloe

Disinfectant Chlorine HSP

Site-Description Oct-Nov 2012

Dec-Mar 2013

Sept 2014 Oct 2014 Feb 2015 May 2015

1 – Raw Water 5511 10378 3407 2555 2328 2611 2 – Post Greensand N/A N/A 26 99 85 157 3 – Post HSP N/A N/A 13 51 88 209 4 – Plant Effluent 1607 3620 85 293 714 313 5 – Distribution 1582 4110 2508 1891 1368 2246 6 - Distribution N/A N/A 2334 1605 1156 1619 7 - Distribution 2204 5129 2582 1884 2216 1932 8 - Distribution N/A N/A 1288 2330 1768 2037 Distribution System Average (ME/mL)

2185 4112 2178 1928 1627 1959

Chris Keung 21


ATP was always highest at Site 1 (raw water) and decreased substantially for Sites 2 to 4

(through the plant to the effluent), likely indicating that treatment was responsible for the

physical removal of cells by the filter. For the sampling campaign between September 2014 and

May 2015, ATP in the raw water averaged 2475 ME/mL and after treatment (Site 4) averaged

approximately 351 ME/mL. Historical data taken from the Fleming College study also showed

significant decreases in ATP before and after treatment but to a lesser extent, ranging from 5511

to 10378 ME/mL in raw water and 1607 and 3620 MR/mL in treated water. Although the same

bioluminescence assay was used for ATP analysis (Luminultra) in the previous studies, sample

collection and treatment was somewhat different: in the Fleming College study the ATP was

measured immediately on-site while ATP analysis for the recent campaign was completed

approximately 24-28 hours after sample collection.

ATP levels slightly increased between the plant effluent (Site 4) to sites throughout the

distribution system (Sites 5-8) regardless of whether chlorine or HSP was being used. It also

appears that using HSP compared to chlorine led to larger increases in ATP levels between the

plant effluent and distribution system water and might indicate that HSP is not as effective as

chlorine in suppressing microbial growth in the pipes. Although initial results show that HSP

may not be as effective as chlorine in suppressing microbial growth further sampling and

research is needed in evaluating the microbial suppressive capabilities of HSP since the sample

size is limited and sample collection differed between both campaigns.

One of the concerns from switching from chlorine to HSP is that the change in water chemistry

might affect corrosion and the release of metals. Previously in Killaloe there was an incident

where the initial switch to HSP led to elevated copper levels in the water from plumbing fixtures

(265 to 1020 μg/L) (OCWA, 2013). The Canadian Water Quality Guideline aesthetic objective

for copper is set at 1000 μg/L based on taste and staining of plumbing fixtures (Health Canada,

2014). The report at the time noted that the increase in copper concentration was likely due to a

change in the chemical make-up of the bulk water when transitioning to a new disinfectant

(OCWA, 2013). Therefore, to ensure acceptable levels of metals in the distribution system,

copper, iron, manganese, and lead were measured in the distribution system during the current

sampling campaign and determined to be at levels well below the 1000, 300, 50, and 10 μg/L

Canadian Water Quality Guidelines set for copper, iron, manganese, and lead respectively

Chris Keung 22


(Health Canada, 2014). Silver concentrations were also monitored in the distribution system

since it is one of the components of HSP. Silver concentrations averaged 3.6 μg/L which is well

below the 100 μg/L USEPA Secondary Drinking Water regulation (USEPA, 2006). A summary

of the metal analysis is shown in Table 3-4. Historical metal data when chlorine was used as a

secondary disinfectant was not available. Aside from the initial transition period in switching

from chlorine to HSP, it appears that the HSP has acclimatized to the distribution system

environment as concentrations of the monitored metals were within acceptable limits.

Table 3-4: Copper, iron, manganese, lead and silver concentrations between September 2014 and May 2015 in the Killaloe drinking water system

Metal (μg/L) Copper Iron Manganese Lead Silver 1 – Raw Water 1 117 171 0 0 2 – Post Greensand 1 7 1 0 0 3 – Post HSP 4 4 1 0 5 4 – Plant Effluent 147 8 2 0 5 5 – Distribution 105 15 2 0 4 6 - Distribution 323 12 2 0 3 7 - Distribution 102 12 2 0 4 8 - Distribution 343 15 3 0 3

Objective (μg /L) < 1000* < 300* < 50* < 10** <100 * Aesthetic objective ** Maximum allowable concentration DBPs were analyzed for the Killaloe system over the period of September 2014 to May 2015.

THM and HAA concentrations remained fairly consistent and the same overall trend was

observed for each individual sampling date. Measureable concentrations of THMs and HAAs

were still observed after the switch to HSP due to the use of prechlorination for iron and

manganese removal (along with greensand filtration) to ensure primary disinfection credit for

viruses. Figure 3-3 shows the THM formation when using chlorine as a secondary disinfectant

(prior to November 2012) and after the switch to HSP for treated water leaving the plant and in

the distribution system (average of 4 sites within the distribution system) between January 2008

and May 2015. Since the switch to HSP as a secondary disinfectant, THM concentrations in both

the treated and distributed water have significantly decreased. Using HSP, THM concentrations

have yet to exceed 45 μg/L which is well below the 100 μg/L Ontario Drinking Water limit.

Chris Keung 23


Total THMs in treated water (plant effluent) and in the distribution system averaged 92 and 114

μg/L respectively when using chlorine. After the switch to HSP, concentrations have averaged 27

and 28 μg/L (average of Sept 2014 – May 2015 campaign) – a decrease in analyzed THMs of 70

± 1.4% and 76 ± 1.5%. This is consistent with work by Batterman et al. (2000), who compared

DBP formation (following a 10 minute prechlorination period) between chlorine and a

H2O2/silver disinfectant and observed that the combined H2O2/silver disinfectant had lower THM

concentrations compared with chlorine by 72 ± 9%.

Figure 3-1: THM concentrations for treated (prechlorinated) water and distribution water in Killaloe system between January 2008 and May 2015, using chlorine as a secondary disinfectant (prior to Nov 2012) and HSP (after Nov 2012)

Historically, HAAs were not analyzed as frequently as THMs. Using chlorine, post clearwell

HAAs ranged between 55-67 µg/L (OCWA, 2012a). Using HSP, HAAs in the treated water

leaving the plant and at a point in distribution system were 8 and 8.4 µg/L respectively (OCWA,

2012a). In the Killaloe sampling campaign between September 2014 and May 2015, HAAs in

the treated water and distribution system ranged between 14 - 26 µg/L, which were 68 ± 6%

lower compared to when chlorine was used. In the same Batterman et al. (2000) study reported

earlier, the HAA concentrations using the combined H2O2/silver disinfectant were 67 ± 11%

lower than when using chlorine.

0

50

100

150

200

250

Aug-07 Dec-08 May-10 Sep-11 Jan-13 Jun-14 Oct-15

THM

Con

cent

ratio

n (µ

g/L)

Date

Treatment

Distribution

Chris Keung 24


A majority of the halogenated DBPs were formed during the prechlorination stage (average of

Sept 2014 – May 2015 campaign post greensand THMs = 27 μg/L and HAA9 = 22 μg/L). The

chlorine residual (approximately 1 mg/L) was quenched with HSP following filtration at Site 3.

Thus, as expected, DBP formation is slowed after the quenching of the chlorine residual due to

the application of HSP. The concentrations of total THMs and HAA9 in the distribution system

stayed fairly consistent throughout the entire system at concentrations of approximately 34 and

21 μg/L (average between Sept 2014 – May 2015) respectively. Other individual DBPs,

including four haloacetonitriles (HANs), two haloketones (HKs) and chloropicrin (CP) were also

analyzed but were not found to be present in any of the samples.

Adsorbable organic halides (AOX) were also analyzed. Prechlorination was the major source of

AOX formation, with AOX increasing from an average of 25 μg/L in raw water to an average of

177 μg/L (average of Sept 2014 – May 2015 campaign) immediately after HSP addition

following greensand filtration to quench the chlorine. Figure 3-2 shows the AOX throughout the

Killaloe system between September 2014 and May 2015. Interestingly, an average decrease in

AOX of between 14-36% was observed from the point of HSP addition to the plant effluent, with

AOX stabilizing within the distribution system with a slight average decrease of between 3-9%

from the plant effluent. This same trend occurred for all four sampling dates between September

2014 and May 2015. The reason for this trend is unknown.

Chris Keung 25


Figure 3-2: AOX formation between Sept 2015 to May 2015

The SOS-Chromotest™ is a cell-based assay that can quantify the genotoxic potential of a

sample; in other words, assess the level of genetic damage and repair caused by constituents in

the sampled water. Genotoxicity is expressed as an induction factor (IF) of the DNA repair genes

for several concentrations (or concentration factor expressed as equivalent mL). The sample is

considered to have genotoxic potential when the induction factor exceeds 2, which translates as a

doubling in DNA repair gene expression. An IF of 1.0 indicates that no increase in gene repair

expression was observed at any concentration and therefore is not genotoxic. Table 3-5 shows

the genotoxic response (IF) of the Killaloe samples at 16.5 equivalent mL/well. Trends from the

genotoxicity data indicate that chlorination can cause genotoxicity (i.e. Site 2); however, in

general, the addition of HSP, which presumably quenches all residual chlorine, leaving only

HSP, did not have an additive effect on the toxic response. In the distribution system, the

genotoxicity of the water decreased as a function of time and distance in the presence of HSP.

Samples collected from the two furthest points of the distribution system (Site 7 and 8) appear to

be non-toxic, since the IF is less than 2. Although these results are preliminary, it is intriguing

that the presence of HSP appears to be correlated to a decrease over time in the genotoxicity that

is formed by upstream chlorination.

0

50

100

150

200

250

1 2 3 4 5 6 7 8

AOX

(μg/

L)

Site

Sep-14

Oct-14

Feb-15

May-15

Chris Keung 26


Table 3-5: Genotoxic response (IF) of Killaloe distribution samples at 16.5 eq. mL/well

Location Sept 9, 2014 Oct 28, 2014 Feb 3, 2015 July 21, 2015 2 – Post Greensand 2.21 2.28 1.21 2.19 3 – Post HSP Not Sampled 1.97 2.24 1.99 4 – Plant Effluent 1.20 1.57 1.79 1.67 7 - Distribution 1.08 1.37 1.22 1.36 8 - Distribution 1.27 1.22 1.05 1.29

3.4 SUMMARY AND CONCLUSIONS

The Killaloe sampling campaign which took place over nine months between September 2014

and May 2015 continued to show that HSP, when used as a secondary disinfectant, can be used

to limit DBP formation while maintaining acceptable water quality. When using chlorine as a

secondary disinfectant, THMs and HAAs in the distribution system averaged between 92-114

and 55-67 μg/L respectively. Using HSP, over the nine-month period, THMs and HAAs

averaged 28 and 21 μg/L respectively. Prechlorination was found to be the major source of DBP

formation as the highest observed values occurred at Site 2 for THM, HAA and AOX.

Genotoxicity analysis showed that the chlorinated water had the highest genotoxic response and

that HSP did not have an additive effect on the toxic response. Genotoxicity of the water

decreased as a function of time and distance in the presence of HSP. Based on ATP

measurements, HSP was not completely effective in suppressing microbial growth within the

distribution system as measured ATP increased from the plant effluent to points within the

distribution system, but this was similar to observations made in an earlier study when chlorine

was being used. One of the concerns with switching from chlorine to HSP is that the change in

water chemistry might affect corrosion and the release of metals. Copper, iron, manganese, and

lead in the distribution system over the 9-month period were determined to be at levels well

below the 1000, 300, 50, and 10 μg/L Canadian Water Quality Guidelines set for copper, iron,

manganese, and lead respectively.

Chris Keung 27


3.5 REFERENCES

3M (2014) 3M Clean-Trace Hygiene Management System. Retrieved July 25, 2015, from http://multimedia.3m.com/mws/media/686753O/clean-trace-atp-rlus-and-cfus.pdf

Baribeau, H.l., Boulos, L., Pozos, N.L. and Crozes, G.F. (2005) Impact of Distribution System Water Quality on Disinfection Efficacy, American Water Works Association, Denver.

Batterman, S., Zhang, L. and Wang, S. (2000) Quenching of Chlorination Disinfection By-Product Formation in Drinking Water by Hydrogen Peroxide. Water Research 34(5), 1652-1658.


Kraemer, L.D., Balch, G., Broadbent, H., Iutzi, M. and Wootton, B.C. (2014) Validation of the AVIVE Water Treatment Solution - using Huwa-San Hydrogen Peroxide as an Alternative to Chlorine-Based Disinfection Technology, Fleming College, Lindsay, ON.

LuminUltra (2013) Quench Gone Aqueous Test Kit Instructions, Fredericton, NB.

Martin, T.D., Brockhoff, J.T.C. and Group, E.M.W. (1994) Method 200.7 Determination of Metals and Trace Metals in Water and Wastes by Inductively Coupled Plasma-Atomic Emission Spectrometry, U.S Environmental Protection Agency, Cincinnati, OH.

Nnadi, F.N. and Fulkerson, M. (2002) Assessment of Groundwater Under Direct Influence of Surface Water. Journal of Environmental Science and Health, Part A 37(7), 1209-1222.

OCWA (2012a) Design Brief Killaloe Drinking Water System: Supporting Information Application for Regulatory Relief, Ontario Clean Water Agency, Mississauga, ON.

OCWA (2012b) Killaloe Drinking Water System: 2012 Annual Water Report, Ontario Clean Water Agency.

OCWA (2013) Killaloe Drinking Water System - THM Reduction - OSWAP3 - OSWAP Project #3213 - Report on the Status of our Investigation of Water Related Complaint, Ontario Clean Water Agency, Mississauga, ON.

Pedahzur, R., Lev, O., Fattal, B. and Shuval, H.I. (1995) The Interaction of Silver Ions and Hydrogen Peroxide in the Inactivation of E. Coli: a Preliminary Evaluation of a New Long Acting Residual Drinking Water Disinfectant. Water Science and Technology 31(5), 123-129.

Rice, E.W., Bridgewater, L. and A.P.H. Assoication (2012) Standard Methods for the Examination of Water and Wastewater, American Public Health Association Washington, DC.

Chris Keung 28


Toté, K., Vanden Berghe, D., Levecque, S., Bénéré, E., Maes, L. and Cos, P. (2009) Evaluation of Hydrogen Peroxide‐Based Disinfectants in a New Resazurin Microplate Method for Rapid Efficacy Testing of Biocides. Journal of Applied Microbiology 107(2), 606-615.

USEPA (2006). National Primary Drinking Water Regulation; Stage 2 Disinfectants and Disinfection Byproducts Rule; Final Rule. Federal Register 71(388), January 4, 2006.

van der Kooij, D., Hein, J., van Lieverloo, M., Schellart, J. and Hiemstra, P. (1999) Maintaining Quality Without a Disinfectant Residual. Journal of the American Water Works Association 91(1), 86-94.

van der Wielen, P.W.J.J. and van der Kooij, D. (2010) Effect of Water Composition, Distance and Season on the Adenosine Triphosphate Concentration in Unchlorinated Drinking Water in the Netherlands. Water Research 44, 4860-4867.

Vang, O.K. (2013) ATP Measurements for Monitoring Microbial Drinking Water Quality, Technical University of Denmark, Kongens Lyngby.

Chris Keung 29


4 THE ABILITY OF SECONDARY DISINFECTANTS TO SERVE AS SENTINELS OF CONTAMINATION

ABSTRACT

To evaluate the efficacy of using secondary disinfectant residuals as sentinels of

contamination, laboratory bench-scale tests were performed by measuring

disinfection residual concentrations after the intrusion of varying dilutions of raw

sewage (0-1%). Disinfectants were considered to be suitable sentinels of

contamination if they could consistently exhibit a “noticeable” change in

disinfectant residual 30 minutes and/or 24 hours after raw sewage intrusion. As an

arbitrary test level, a change of 30% in disinfectant residual was used as the

“noticeable” change limit. Out of the studied disinfectants (chlorine, chloramines,

chlorine dioxide, hydrogen peroxide, HuwaSan peroxide), chlorine was observed

to be the most appropriate sentinel under the tested laboratory conditions for raw

sewage dilutions of greater than 0.4% and 0.2% for 30 minutes and 24 hours

respectively. The other disinfectants did not appear to consistently exhibit a

noticeable change with intruded raw sewage. Additionally, the laboratory decay

experiments were used to determine decay parameters for subsequent risk

modeling using a distribution system water quality model (EPANET-MSX) to

evaluate disinfectant decay and pathogen exposure throughout a distribution

system.

4.1 INTRODUCTION

One of the potential advantages of maintaining a disinfectant residual throughout a distribution

system is its ability to serve as a sentinel of contamination (Trussell, 1999). Intrusion can happen

in a number of different ways such as treatment breakthrough, leaks, cross connections,

backflows, transient pressure events, reservoir contamination, and repairs (LeChevallier et al.,

2003; van Lieverloo et al., 2006). The intrusion of raw sewage into a drinking water system has

been responsible for many outbreaks of disease (CDC, 2013). Raw sewage can contain a variety

of pathogens with the density and variety related to the population served by the sewage system,

seasonal patterns, and the extent of infections in the community (Geldreich, 1996). Outbreaks are

Chris Keung 30


often reported in which a large number of the public are affected, but such outbreaks are likely

only a small portion of contamination events, with many smaller events occurring unnoticed (van

Lieverloo et al., 2006). The amount of contaminated water that enters the distribution system

during an intrusion event is very difficult to assess and thus this information is rarely reported

(LeChevallier et al., 2003). However, laboratory studies conducted by the USEPA (2003)

reported that for negative pressure events, the volume of intrusion is only a fraction of the water

within the pipe network (much less than 1%). Kirmeyer et al. (2001) also reported that the

volume of intrusion could range from milliliters to thousands of liters depending on the nature

and duration of the event.

An effective, reliable sentinel must be sensitive to a wide range of contaminants and must signal

detection in a consistent and timely manner (Grayman, 2010). Ideally, detection of the

contamination event would be an instantaneous, real-time response and available at all points

within a system which could be made possible with the installation of specialized sensors

throughout the system. However, the vastness of distribution systems along with the limits of our

current technology and resources makes this an unreasonable target (Deininger et al., 2011,

Eliades et al., 2014, Eliades and Polycarpou, 2010). A more feasible target is the “detect to

warn” objective as described by the USEPA in which the incident would be detected before

significant exposure to the public and prior to the emergence of public health indicators such as

consumer complaints or medical incidents (DHS, 2004). A reasonable response time would

allow water utilities to take appropriate remediate actions (Roberston and Morley, 2005; DHS,

2004).

Many utilities are unable to fund extensive online monitoring tools and as an alternative

sometimes monitor for changes in generic water quality parameters including secondary

disinfectant residuals (Hall et al., 2007). The main drawback is that sampling is often infrequent

or not representative of the entire distribution system and contamination events are only detected

after the incidence of public health indicators such as gastroenteritis or as a result of other

consumer complaints (Fogarty et al., 1995; Hrudey and Hrudey, 2004).

The main assumption using indicator water quality parameters as sentinels of contamination is

that the intruded contaminants will affect and cause a noticeable change in the monitored

indicators (Hall et al., 2007). Some studies have shown that free chlorine is effective as a

Chris Keung 31


sentinel of contamination since it reacts readily with nitrogen-containing and organic material

causing a significant decrease in the residual (Clark and Deininger, 2000; Olivieri et al., 1986;

Snead et al., 1980). Conversely, it has been reported that chloramine residuals are less effective

as a sentinel of contamination since they do not change significantly even after a large intrusion

of contaminated water (Snead et al., 1980).

Determining what is deemed a “noticeable change” in disinfectant residual is a complex task that

is site specific and varies greatly depending on many factors such as the monitoring tools,

resources, and operational capabilities of the water utility. Some studies have proposed using

methods such as control charts or Kalman filters (linear quadratic estimations) to establish what

limits would be considered a noticeable change (Eliades et al., 2014). In determining if a water

quality measurement deviated from its baseline and could be considered an anomaly, Byer and

Carlson (2005) collected data using on-line monitoring sensors for common water quality

parameters such as pH, turbidity, chlorine, total organic carbon (TOC), and conductivity to

establish a baseline for the system and to estimate the standard deviation (σ) of the measured

parameters. For normally distributed data, 99.73% of data points will fall within ±3σ. Although

the data collected in Byer and Carlson’s study was not normally distributed, for pH, turbidity,

chlorine, TOC, and conductivity, 100, 98, 99, 97, and 98% of the data fell within ±3σ of the

mean respectively (Byer and Carlson, 2005). Using data collected from the Byer and Carlson

study, the average chlorine concentration in the distribution system was 0.52 mg/L (as Cl2) and

3σ was determined as 0.20 mg/L or approximately 40% of the mean (i.e. a 40% change in free

chlorine residual would be considered an anomaly) (Byer and Carlson, 2005). In another study,

Skadsen et al. (2008) reported total chlorine residuals in the distribution system as 2.14 ± 0.29

mg/L (as Cl2) for one instrument and 1.70 ± 0.35 mg/L for another instrument. Thus, an anomaly

according to the ±3σ criterion would be approximately 40 to 60% depending on which online-

monitoring instrument was used (Skadsen et al., 2008). For the lesser-used disinfectants, chlorine

dioxide (ClO2), hydrogen peroxide (H2O2) and Huwa-San Peroxide (HSP), there is little

information in the literature pertaining to mean and standard deviation values found within

distribution systems.

The main purpose of this study was to conduct laboratory bench-scale tests on the stability and

reactivity of traditional secondary disinfectants (free chlorine, chloramines) and alternatives

Chris Keung 32


(ClO2, H2O2, HSP) to evaluate their ability to serve as sentinels of contamination or to maintain a

residual to protect against contamination. In the case of a large contamination event, it is

probable that the intruded sewage will overwhelm the disinfectant residual quite rapidly. The

range of raw sewage intrusion that is considered in this study should therefore include, at one

end of spectrum, a major contamination event where the risk of infection or illness is very high

(0.5 and 1% sewage intrusions), and at the other end of the spectrum, the study should include a

range of sewage dilutions that represent smaller and more frequent contamination events (0.01

and 0.1% sewage intrusions) where an appropriate secondary disinfectant would either show a

noticeable change in the residual concentration or maintain a residual to provide an opportunity

to disinfect intruded pathogens.

The experiments address two key issues surrounding the sentinel evaluation:

(1) What percent of sewage causes a “noticeable” change in the disinfectant residual?

For this study, an arbitrary test level of greater than a 30% change in residual was considered a

“noticeable” change based on the ± 3σ limits established for chlorine by Byer and Carlson

(2005). This limit is slightly more conservative than the 40% change observed in the Byer and

Carlson study. The purpose of this study was to not to establish absolute, defined limits in

characterizing a “noticeable” change but more about re-assessing the role of secondary

disinfectants in order to compare different disinfectants in a more quantifiable manner. Therefore

this noticeable change limit was solely used as a test level for this study but can change

according to a number of site-dependent factors.

(2) Determination of decay rates (k-values) as a function of % intrusion for different

disinfectants (Cl2, chloramines, ClO2, H2O2, and HSP), residual concentrations, pH, and

temperatures.

Initial disinfectant demands and decay coefficients (k-values) for different levels of disinfectant

type, disinfectant dose, % of intruded raw sewage pH, and temperature were calculated and are

used for subsequent risk-modeling using EPANET-MSX (Chapter 5) to evaluate different

secondary disinfectants with respect to disinfectant decay and pathogen exposure throughout a

distribution system.

Chris Keung 33


4.2 MATERIALS AND METHODS

Bench scale experiments were conducted to study the impact of the type of secondary

disinfectant, initial residual concentration, contact time, pH, and temperature on disinfectant

residual concentrations when subject to a simulated intrusion event. 1 L aliquots of Lake Ontario

water (pH and temperature adjusted) were dosed with the different disinfectants (Cl2,

chloramines, ClO2, H2O2, HSP) and spiked with varying dilutions of raw sewage. Disinfectant

residuals were measured at 0, 30, 480, and 1440 minutes.

4.2.1 Analytical Methods

4.2.1.1 pH and Temperature Measurement

pH and temperature were measured using a pH meter Model 8015 (VWR International). The

instrument was calibrated prior to each use with buffered calibration solutions at pH 4, 7, and 10

(VWR International).

4.2.1.2 Dissolved Organic Carbon (DOC)

Dissolved organic carbon (DOC) was measured using a wet oxidation method based on Standard

Method 5310 D (Rice et al., 2012). The analysis was carried out using O-I Corporation Model

1010 Analytical TOC Analyzer with a Model 1051 Vial Multi-Sampler. The instrument

conditions are shown in Table D-1 (Appendix D). Water samples were filtered using a 0.45 μm

fiber glass filter, transferred to 40 mL amber vials, and capped with Teflon®-lined septum screw

caps). A new calibration curve was prepared before each set of samples. A sample calibration

curve and QAQC are shown in Figures D-1 and D-2 respectively (Appendix D). The reagent list

and the method outline are listed in Tables D-2 and D-3 respectively (Appendix D).

4.2.1.3 Free Ammonia Measurement

Free ammonia in the raw sewage was measured using the indophenol method according to Hach

Method 10200. Free ammonia reagents and the method outline are listed in Tables D-4 and D-5

respectively (Appendix D).

Chris Keung 34


4.2.1.4 Free Chlorine Residual

Free chlorine residual was measured using a DPD colormetric method according to Hach

Method 8021. This procedure is equivalent to Standard Method 4500 G (Rice et al., 2012). Free

chlorine reagents and the method outline are listed in Tables D-6 and D-7 respectively.

4.2.1.5 Total Chlorine (Free Chlorine, Monochloramine, Dichloramine) Residual – Amperometric Titration

Total chlorine, which includes free chlorine and combined chlorine (monochloramine,

dichloramine), was measured using an amperometric titration technique based on Standard

Method 4500 D (Rice et al., 2012). The analysis was carried out using US Filter/Wallace &

Tiernan (USF/W&T) Products Amperometric Titrator Series A-790. The reagent list and method

outline are given in Tables D-8 and D-9 (Appendix D).

4.2.1.6 Chlorine Dioxide Residual

Chlorine dioxide residual was measured using a DPD colourmetric method according to HACH

Method 10126. This procedure is equivalent to Standard Method 4500 ClO2 D (Rice et al.,

2012). Chlorine dioxide reagents and the method outline are listed in Tables D-10 and D-11

respectively. The DPD colourmetric method is an easy way to measure the chlorine dioxide

concentrations in a sample but cannot differentiate between the other chlorine species (free

chlorine, chlorite). For this reason, to ensure accurate dosing of ClO2 concentrations, an

amperometric titration technique according to Standard method 4500 ClO2 C (Rice et al., 2012)

was used to measure free chlorine, chlorine dioxide and chlorite contamination for the ClO2

stock solution.

4.2.1.7 Hydrogen Peroxide Residual

The analysis of hydrogen peroxide (H2O2) was done by determining the yield of I3- formed when

H2O2 reacts with KI in a buffered solution containing ammonium molybdate as a catalyst

(Kolthoff et al., 1973). The H2O2 concentration in the resultant solution was determined by

measuring the ultraviolet absorbance at 351 nm (UV351) using a CE 3055 Single Beam Cecil

UV/Visible Spectrophotometer (Cambridge, England) using 1 cm quartz cells (Hewlett Packard,

Mississauga). The spectrophotometer was zeroed with Milli-Q® water. The reagent list and

method outline are given in Tables D-12 and D-13 (Appendix D).

Chris Keung 35


4.2.2 Wastewater Evaluation

Raw wastewater was collected from the G.E. Booth (Lakeview) Wastewater Treatment Facility

located in Mississauga, Ontario on November 11, 2014. Untreated sewage samples were

collected following grit removal at the head of the primary tank before any biological or

chemical treatment processes.

Raw wastewater comes from many sources and can vary greatly according to the source or at

different periods of time from the same source. Also, the age of wastewater from a single source

can vary for different intrusion events, such as intrusion from a leaking pipe adjacent to a sewer

line compared to intrusion from sewage that has travelled some distance in the subsurface

environment. The scope of this study was to compare the reactivity of different secondary

disinfectants under similar conditions, and although it would be ideal to run the experiments

using identical wastewaters, in reality the experiments took many months and it was not possible

to obtain a single constant wastewater sample that would remain unchanged for this amount of

time. Instead, a single wastewater sample was used and stored for the entire duration of the

experiments. Free ammonia and dissolved organic carbon (DOC), two compounds that react

readily with chlorine (Vasconcelos et al., 1997) were tested periodically throughout the

experiments. The free ammonia remained within 32 to 46 mg/L over the experiment, and DOC

remained within 35 to 48 mg/L.

To sterilize the wastewater samples and make them safer to handle, the samples were autoclaved

at 220°F and 15 kg/cm2 for 25 minutes. Snead et al. (1980) compared autoclaved and

unautoclaved sewage samples for a period of 23 days and reported that autoclaving the

wastewater led to no observable changes in ammonia, total nitrogen, total carbon, turbidity, total

solids, total volatile solids, suspended solids, pH, BOD, and chlorine breakpoint. Wastewater

samples in this study were stored for up to 6 months, and although some of the properties (free

ammonia and DOC) showed slight decreases over the storage period, the reactivity of chlorine

with wastewater (QC decay experiments) remained fairly consistent (Tables D-14 and D-15 in

Appendix D). Wastewater samples were filtered with 0.45 μm filters to ensure consistent

particulate size for the disinfectant decay experiments.

Chris Keung 36


4.2.3 Water Source Sampling and Disinfectant Residual Preparation

Experiments used weekly batches of raw water collected from Lake Ontario (R.C Harris Water

Treatment Plant, Toronto, ON) in 20L polypropylene containers between November 2014 and

May 2015. Collected raw water was filtered using 0.45 μm filters. The filtered raw water

remained very consistent over the course of the experiment, with DOC remaining within 2.3 ±

0.1 mg/L, ammonia within 0.02 ± 0.005 mg/L, and pH within 7.5 ± 0.1. Batches of the raw water

collected over the 6-month period had a consistent 24-hour chlorine demand ranging between 0.1

and 0.2 mg/L. The water samples were adjusted to pH 6 ± 0.2 or 8 ± 0.2 using sulfuric acid (1%

w/w) or saturated sodium hydroxide (1% w/w) and buffered by adding 0.001 M phosphate

buffer. Experiments were conducted at 4 ± 3 °C and 23 ± 4°C to represent winter and summer

temperatures respectively.

Table 4-1: Typical secondary disinfectant residuals

Secondary Disinfectant Low

Concentration (mg/L)

High Concentration

(mg/L) Source

Chlorine (as Cl2) 0.21 4.0 Drinking Water Guidelines (Health Canada, 2014)

Chloramines (as Cl2) 0.52 3.0 Drinking Water Guidelines (Health Canada, 2014)

Chlorine Dioxide (as ClO2) 0.05 0.8 (USEPA, 2002)

Hydrogen Peroxide (as H2O2) N/A 173 (Shuval, 1998)

Silver Peroxide (as H2O2) 104 304 (Shuval, 1998)

HuwaSan Peroxide (as H2O2) 15 N/A (OCWA, 2012)

1. World Health Organization (WHO) Optimum target free chlorine residual is 0.2-0.5 mg/L (Health Canada, 2014).

2. Optimum combined chlorine residual is 1.0 mg/L (Health Canada, 2014). 3. Hydrogen peroxide has been approved as a drinking water disinfectant in Australia and

France at a concentration of up to 17 mg/L (Shuval et al., 1998). 4. Concentrations ranging between 10-30 ppm of hydrogen peroxide and 10 to 30 ppb of silver

have been approved for use as a drinking water disinfectant in a number of countries including Australia and Switzerland (Shuval et al., 1998).

5. Optimum HSP residual is 3-8 mg/L (OCWA, 2012).

Chris Keung 37


Table 4-1 shows the typical range of disinfectant residual concentrations in distribution systems

for six secondary disinfectants. Low and high residual concentrations as well as two intermediate

concentrations were tested in the experiments using chlorine, chloramines, ClO2, H2O2 and HSP

disinfectants as shown in Table 4-2. The initial dose of the disinfectant needed to maintain the

target residuals were calculated using 24-hour demand tests.

Table 4-2: Concentrations of secondary disinfectants used in sentinel experiments

Secondary Disinfectant Low (mg/L)

Med-Low (mg/L)

Med-High (mg/L)

High (mg/L)

Chlorine (as Cl2) 0.2 0.8 2.0 4.0

Chloramines (as Cl2) 0.5 1 1.75 3.0

Chlorine Dioxide (as ClO2) 0.05 0.2 0.4 0.8

Hydrogen Peroxide (as H2O2)

1 6 15 30

HuwaSan Peroxide (as H2O2)

1 6 15 30

4.2.4 Simulated Contamination Event – Raw Sewage Intrusion

1 L aliquots of Lake Ontario water dosed with appropriate disinfectant residual concentrations

(Table 4-2) were spiked with raw sewage at dilutions of 0% (control), 0.01%, 0.1%, 0.5%, and

1% of the total water volume. For a secondary disinfectant to serve as a sentinel or a flag of

distribution system failure, a noticeable change (± 30%) in the residual concentration should be

observed in a relatively short time period. Thus, after the initial measurement, the disinfectant

residual was measured at 30 minutes after the raw sewage spike. Residuals were also measured

at longer contact times of 8 and 24 hours to represent typical water age in small distribution

systems and for use in determining disinfectant decay coefficients.

Chris Keung 38



(1) What percent of sewage causes a “noticeable” change in the disinfectant residual?

One of the objectives of this work was to determine whether monitoring disinfectant residuals

was effective in detecting some intrusion event, and if so, what size of intrusion would trigger a

noticeable change in residual. Raw sewage was used as a worst-case example for intrusion based

of its historical precedence and high level of risk due to the potential presence of pathogens. For

a secondary disinfectant to be used effectively as a sentinel, the residual should exhibit a

“noticeable” change following an intrusion event. Ideally, an alarm would be triggered almost

immediately after an intrusion and therefore the residual at 30 minutes was measured. It may also

still be useful for a sentinel to trigger an alarm at a later duration such as 24 hours if the water

age in the system is old and if the pathogen has the ability to persist. What is deemed a

“noticeable change” is very complex question that requires an analysis of historical practices, an

evaluation of possible computer algorithms to detect “non-trivial” changes as a monitoring tool,

etc. and is a limit that is defined by various site-specific factors. Answering this question was

outside the scope of this project and therefore an arbitrary test level of a change of greater than

30% in residual was deemed as “noticeable”.

Figures 4-1 and 4-2 show the % disinfectant residual remaining (Figure 4-1 at 30 minutes, Figure

4-2 at 24 hours) versus the % sewage added for pH 6 and 8, 4°C and 23°C, and for low, med-

low, med-high, high chlorine, chloramines, ClO2, H2O2, and HSP concentrations.

Chris Keung 39


Figure 4-1: 30 minute residual remaining (percentage) versus % sewage

Chris Keung 40


Figure 4-2: 24 hour residual remaining (percentage) versus % sewage

Chris Keung 41


For the 30 minute experiments, only free chlorine exhibited a “noticeable” change (i.e. residual

remaining dropped below 70%) for sewage intrusions up to 1% by volume (the highest

contamination level examined) with the exception of the low concentration of ClO2 at pH 8 and

23°C. It is well known that chlorine reacts readily with ammonia and other organics in

wastewater (Clark and Deininger, 2000; Olivieri et al., 1986; Snead et al., 1980; Deborde and

Von Gunten, 2008), which cause an instantaneous chlorine demand and allow for a noticeable

change to be seen. pH and temperature did not appear to have a significant impact on the

remaining residual after 30 minutes. Chlorine at its low concentration showed a noticeable

change at very low concentrations of sewage added (less than 0.01%). For increasing chlorine

concentration, the % sewage needed to exhibit a noticeable change also increased (Med/low:

0.07 -0.13%, Med/high: 0.20 -0.27%, High: 0.35 – 0.4%). ClO2 at its lowest concentration of 0.2

mg/L at pH 8 and 23°C showed a noticeable change at approximately 0.5% sewage added.

Although this fits our criteria for a noticeable change, the absolute concentrations of ClO2

residual at the low concentration at pH 8 and 23°C decreased by only 0.08 mg/L after 30 minutes

(0.5% sewage added), similar to changes of 0.07, 0.07 and 0.10 mg/L for the med-low, med-

high, and high ClO2 concentrations respectively at the same pH and temperature. Detecting

changes in ClO2 concentrations on the magnitude of 0.08 mg/L may prove to be very difficult

from an operational standpoint. Since different disinfectants appear at various concentrations

within the distribution system, a % remaining criteria was used to normalize the data between

different disinfectants, but the % remaining residual value might be a bit misleading since for the

same absolute changes in residual concentration (mg/L), lower initial residual concentrations will

have a larger % change. In summary, these results for a 30 minute reaction time demonstrated

that only chlorine showed a consistent noticeable change in residual (>30%) for raw sewage

intrusions of greater than approximately 0.4%, 0.25% and 0.1% for the high, med/high and

med/low chlorine concentrations respectively. At the low chlorine concentration any intrusion of

raw sewage entirely consumed the chlorine residual. For chloramines, H2O2 and HSP, the 30-

minute change in residual for all scenarios was less than 18, 14 and 13% respectively. Therefore,

chlorine appears to be the most appropriate sentinel of intrusion under these conditions.

Chris Keung 42


Even if the contamination event is not recognized immediately, it might be useful to monitor for

longer changes (24 hours) in cases where residence times in the distribution system are longer

and utilities may have time to react before contaminated water reaches the consumer’s tap.

Figure 4-2 shows the 24-hour % disinfectant residual remaining for the various conditions. For

chloramines, H2O2 and HSP it appeared that the residual remained quite stable with only the

lowest initial residual concentrations showing noticeable changes 24 hours after intrusion. Using

chloramine, the only noticeable change in residual (37%) was seen in a situation using the lowest

concentration of 0.5 mg/L (pH 6, 23°C) and the highest intrusion of sewage (1%). For H2O2, the

1% intrusion only caused a noticeable change of between 35-61% for the lowest H2O2

concentration (1 mg/L). Both a 0.5 and 1% sewage dilution caused the low HSP residual (1

mg/L) to change more than 30% (30-83%). A 1% intrusion also caused a noticeable change of 48

and 41% in the 6 mg/L HSP concentration (pH 8) for 4°C and 23 °C respectively. Chlorine is

the most reactive disinfectant and shows a noticeable change at its high concentration at sewage

intrusions greater than 0.2-0.3%. Chlorine dioxide also exhibits a noticeable change for some

scenarios but requires larger % sewage (greater than 0.6% for high concentration at 23°C). The

highest ClO2 concentration that was tested was 0.8 mg/L as compared to 4 mg/L for chlorine so

any small change or error in ClO2 residual will have a greater effect in the % residual remaining

number. Based on the experimental data collected this study for the 30 minute and 24 hour

residual tests, it appears that the only sentinel that exhibits a noticeable change is chlorine at raw

sewage dilutions of greater than 0.4% and 0.2% for 30 minutes and 24 hours respectively.

(2) Determination of decay rates (k-values) as a function of % intrusion for different

disinfectants, residual concentrations, pH, and temperature.

The second objective of this study was to derive decay rate coefficients (k values) for different

disinfectant type, dose, % sewage dilution, pH, and temperature. These k-values would then be

used in subsequent risk-modeling using EPANET-MSX to model disinfectant decay and

pathogen exposure throughout a distribution system (Chapter 5). Disinfectant decay was

modeled after equation (1), which incorporates an instantaneous demand at the time of intrusion

followed by subsequent first order decay.

𝐶𝑡 = (𝐶0 − 𝐼𝐼)−𝑘𝑡 (1)

Chris Keung 43


Where: Ct = disinfectant concentration at time, t after intrusion; C0 = initial disinfectant

concentration at time, t=0; ID = instantaneous demand as calculated as the difference between

the 30-minute (t=30) and initial residual (t=0); and k = decay rate coefficient as determined by

plotting the natural logarithm of residual concentration over initial residual concentration versus

contact time (slope of the plot equals the k-value). Decay plots are shown in Figures E-1 to E-

100 (Appendix E). To predict decay coefficients (k-values) as a function of percent raw sewage,

a linear regression was fitted between the k-values determined in the experiments versus %

sewage added. These equations can be used to predict the disinfectant decay in bulk water for

various contamination events. A complete summary of the initial demands and regression

parameters (slope, intercept, R2) for the linear models for the chlorine, chloramine, ClO2, H2O2,

and HSP disinfectants is shown in Tables 4-3 to 4-7.

Chris Keung 44


Table 4-3: Chlorine decay regression summary

Chlorine

Target Residual pH Temp %

Sewage k value (day-1) Slope Intercept R2 30 min

Demand 24 hr

Demand

Low

6 4

0 0.151

6.65 0.17 1.00

0.02 0.06 0.01 0.254 0.04 0.06 0.1 0.831 0.14 0.16 0.5 0.16 0.16 1 0.19 0.19

6 23

0 0.354

2.81 0.00 1.00

0.01 0.07 0.01 1.007 0.06 0.09 0.1 0.18 0.20 0.5 0.19 0.19 1 0.22 0.22

8 4

0 0.123

3.06 0.14 0.99

0.00 0.00 0.01 0.191 0.04 0.07 0.1 0.445 0.16 0.17 0.5 0.22 0.25 1 0.24 0.24

8 23

0 1.152

1.03 0.01 1.00

0.01 0.07 0.01 1.195 0.08 0.13 0.1 0.14 0.14 0.5 0.11 0.11 1 0.14 0.14

Med-Low

6 4

0 0.053

0.80 0.04 1.00

0.03 0.10 0.01 0.036 0.02 0.07 0.1 0.120 0.30 0.38

0.78 0.84 1 0.843 0.84 0.87

6 23

0 0.167

0.37 0.17 1.00

0.00 0.08 0.01 0.173 0.05 0.10 0.1 0.205 0.42 0.44 0.5 0.72 0.70 1 0.77 0.80

8 4

0 0.079

0.43 0.08 1.00

0.01 0.07 0.01 0.085 0.06 0.13 0.1 0.128 0.29 0.37 0.5 0.298 0.77 0.78 1 0.88 0.88

8 23

0 0.138

3.59 0.16 0.98

0.01 0.11 0.01 0.224 0.05 0.17 0.1 0.518 0.26 0.42 0.5 0.66 0.66 1 0.69 0.69

Chris Keung 45


Table 4- 3 cont.: Chlorine decay regression summary

Chlorine



Demand 24 hr

Demand

Med-High

6 4

0 0.023

0.47 0.03 1.00

0.02 0.02 0.01 0.025 0.09 0.16 0.1 0.086 0.29 0.48

1.39 1.41 1 0.493 1.96 1.98

6 23

0 0.026

0.25 0.03 1.00

0.01 0.04 0.01 0.041 0.04 0.05 0.1 0.069 0.37 0.36 0.5 0.157 1.41 1.40 1 0.291 1.87 1.86

8 4

0 0.054

0.29 0.05 0.97

0.01 0.12 0.01 0.085 0.07 0.26 0.1 0.053 0.37 0.44 0.5 0.179 1.32 1.40 1 0.355 1.91 1.94

8 23

0 0.068

0.68 0.07 1.00

0.02 0.17 0.01 0.071 0.10 0.25 0.1 0.133 0.37 0.52

1.37 1.74 1 0.747 1.84 1.87

High

6 4

0 0.003

0.12 0.00 0.97

0.03 0.03 0.01 0.001 0.09 0.10 0.1 0.022 0.55 0.69 0.5 0.060 1.77 1.88

2.87 2.78

6 23

0 0.012

0.19 0.01 0.96

0.00 0.00 0.01 0.014 0.12 0.16 0.1 0.031 0.59 0.70 0.5 0.073 1.53 1.68 1 0.206 2.71 2.86

8 4

0 0.029

0.13 0.03 0.98

0.05 0.19 0.01 0.036 0.09 0.21 0.1 0.034 0.41 0.51 0.5 0.081 1.63 1.85 1 0.166 2.76 2.93

8 23

0 0.065

0.44 0.04 0.96

0.11 0.36 0.01 0.057 0.10 0.48 0.1 0.077 0.37 0.85 0.5 0.195 1.42 1.80 1 0.511 2.52 2.91

Chris Keung 46


Table 4-4: Chloramine decay regression summary

Chloramine



Demand 24 hr

Demand

Low

6 4

0 0.050

0.24 0.04 0.99

0.00 0.03 0.01 0.052 0.00 0.00 0.1 0.055 0.00 0.03 0.5 0.157 0.02 0.07 1 0.292 0.03 0.15

6 23

0

0.32 0.02 0.95

0.03 0.03 0.01 0.026 0.02 0.02 0.1 0.073 0.00 0.00 0.5 0.131 0.05 0.13 1 0.359 0.10 0.20

8 4

0

0.28 0.05 0.91

0.00 0.03 0.01 0.062 0.00 0.00 0.1 0.099 0.05 0.07 0.5 0.131 0.05 0.08 1 0.359 0.05 0.12

8 23

0

0.08 0.05 0.97

0.00 0.05 0.01 0.043 0.03 0.05 0.1 0.00 0.00 0.5 0.097 0.03 0.08 1 0.126 0.05 0.10

Med-Low

6 4

0

0.09 0.06 0.89

0.02 0.00 0.01 0.053 0.00 0.05 0.1 0.081 0.05 0.10

0.083 0.05 0.10 1 0.157 0.08 0.20

6 23

0 0.064

0.08 0.07 0.98

0.00 0.05 0.01 0.00 0.02 0.1 0.078 0.00 0.07 0.5 0.099 0.05 0.07 1 0.147 0.13 0.23

8 4

0

0.10 0.04 0.86

0.00 0.02 0.01 0.027 0.02 0.05 0.1 0.076 0.05 0.07 0.5 0.078 0.07 0.07 1 0.147 0.02 0.07

8 23

0 0.042

0.03 0.06 0.33

0.02 0.10 0.01 0.077 0.00 0.08 0.1 0.070 0.00 0.05 0.5 0.048 0.03 0.05 1 0.100 0.05 0.15

Chris Keung 47


Table 4-4 cont.: Chloramine decay regression summary

Chloramine



Demand 24 hr

Demand

Med-High

6 4

0 0.030

0.05 0.02 0.96

0.02 0.05 0.01 0.022 0.00 0.05 0.1 0.023 0.07 0.07 0.5 0.08 0.08 1 0.079 0.02 0.15

6 23

0

0.03 0.05 0.80

0.00 0.00 0.01 0.00 0.00 0.1 0.054 0.07 0.15 0.5 0.054 0.03 0.13 1 0.079 0.07 0.15

8 4

0

0.06 0.01 0.91

0.00 0.02 0.01 0.000 0.05 0.03 0.1 0.00 0.00 0.5 0.014 0.05 0.05 1 0.061 0.02 0.12

8 23

0

0.04 0.02 1.00

0.03 0.00 0.01 0.08 0.00 0.1 0.027 0.02 0.07 0.5 0.13 0.10 1 0.062 0.07 0.17

High

6 4

0

0.05 0.02 0.89

0.03 0.03 0.01 0.013 0.00 0.02 0.1 0.034 0.03 0.13

0.037 0.15 0.30 1 0.073 0.10 0.17

6 23

0

0.07 0.01 0.98

0.00 0.00 0.01 0.00 0.10 0.1 0.017 0.00 0.03 0.5 0.054 0.00 0.15 1 0.083 0.08 0.28

8 4

0 0.020

N/A N/A0 N/A

0.05 0.08 0.01 0.012 0.02 0.02 0.1 0.004 0.03 0.08 0.5 0.016 0.05 0.08 1 0.012 0.05 0.10

8 23

0

N/A N/A N/A

0.05 0.00 0.01 0.05 0.03 0.1 0.08 0.00 0.5 0.068 0.07 0.27 1 0.061 0.10 0.28

Chris Keung 48


Table 4-5: Chlorine dioxide decay regression summary

Chlorine Dioxide



Demand 24 hr

Demand

Low

6 4

0 0.043

0.62 0.05 0.98

0.01 0.02 0.01 0.115 0.00 0.03 0.1 0.058 0.02 0.04 0.5 0.384 0.01 0.05 1 0.665 0.05 0.09

6 23

0 0.144

1.91 0.13 0.97

0.01 0.04 0.01 0.288 0.02 0.07 0.1 0.288 0.02 0.06 0.5 0.864 0.01 0.11 1 2.160 0.05 0.20

8 4

0 0.043

0.63 0.05 0.96

0.02 0.03 0.01 0.115 0.02 0.05 0.1 0.101 0.00 0.04 0.5 0.288 0.02 0.09 1 0.720 0.04 0.16

8 23

0 0.130

1.37 0.16 0.93

0.04 0.07 0.01 0.288 0.05 0.10 0.1 0.210 0.04 0.10 0.5 0.864 0.08 0.18 1 0.13 0.24

Med-Low

6 4

0 0.000

0.28 0.00 0.98

0.02 0.02 0.01 -0.003 0.00 0.01 0.1 0.043 0.01 0.03

0.115 0.04 0.09 1 0.288 0.08 0.15

6 23

0 0.144

0.67 0.16 0.97

0.00 0.05 0.01 0.167 0.01 0.07 0.1 0.288 0.02 0.10 0.5 0.432 0.07 0.15 1 0.864 0.07 0.21

8 4

0 0.072

0.65 0.03 0.98

0.01 0.04 0.01 0.043 0.00 0.02 0.1 0.086 0.01 0.06 0.5 0.288 0.03 0.14 1 0.720 0.07 0.22

8 23

0 0.072

1.55 0.06 0.95

0.01 0.03 0.01 0.115 0.02 0.05 0.1 0.288 0.03 0.12 0.5 0.576 0.07 0.18 1 1.728 0.08 0.28

Chris Keung 49


Table 4-5 cont.: Chlorine dioxide decay regression summary

Chlorine Dioxide



Demand 24 hr

Demand

Med-High

6 4

0 -0.010

0.16 0.00 0.95

0.03 0.02 0.01 0.007 0.02 0.02 0.1 0.007 0.05 0.06 0.5 0.101 0.10 0.13 1 0.144 0.12 0.21

6 23

0 0.144

0.63 0.14 0.93

0.01 0.09 0.01 0.144 0.01 0.08 0.1 0.144 0.03 0.10 0.5 0.576 0.04 0.23 1 0.720 0.09 0.32

8 4

0 0.072

0.19 0.10 0.94

0.02 0.07 0.01 0.115 0.02 0.09 0.1 0.144 0.04 0.14 0.5 0.193 0.07 0.20 1 0.288 0.09 0.27

8 23

0 0.130

1.04 0.15 0.99

0.03 0.10 0.01 0.115 0.07 0.13 0.1 0.288 0.09 0.24 0.5 0.752 0.07 0.21 1 1.152 0.11 0.43

High

6 4

0 0.043

0.04 0.05 0.81

0.02 0.05 0.01 0.043 0.03 0.07 0.1 0.067 0.03 0.10

0.072 0.06 0.13 1 0.086 0.11 0.20

6 23

0 0.058

0.36 0.08 0.98

0.03 0.07 0.01 0.101 0.04 0.12 0.1 0.115 0.06 0.15 0.5 0.288 0.08 0.24 1 0.432 0.12 0.38

8 4

0 0.010

0.15 0.03 0.95

0.01 0.02 0.01 0.029 0.01 0.04 0.1 0.058 0.02 0.06 0.5 0.115 0.04 0.14 1 0.168 0.08 0.21

8 23

0 0.086

0.48 0.08 0.96

0.01 0.09 0.01 0.130 0.05 0.15 0.1 0.072 0.11 0.16 0.5 0.288 0.09 0.25 1 0.576 0.11 0.45

Chris Keung 50


Table 4-6: Hydrogen peroxide decay regression summary

Hydrogen Peroxide



Demand 24 hr

Demand

Low

6 4

0 0.029

0.41 0.00 0.96

0.02 0.02 0.01 0.000 0.01 0.01 0.1 0.029 0.01 0.03 0.5 0.144 0.12 0.28 1 0.432 0.16 0.49

6 23

0 0.029

1.02 0.01 0.99

0.02 0.05 0.01 0.014 0.01 0.03 0.1 0.072 0.02 0.09 0.5 0.576 0.01 0.43 1 1.008 0.01 0.70

8 4

0 0.014

0.28 0.00 0.99

0.01 0.03 0.01 0.013 0.00 0.01 0.1 0.014 0.00 0.01 0.5 0.144 0.02 0.21 1 0.288 0.02 0.36

8 23

0 -0.003

0.99 0.01 0.99

0.05 0.05 0.01 0.014 0.05 0.07 0.1 0.086 0.05 0.14 0.5 0.432 0.07 0.49 1 1.008 0.08 0.76

Med-Low

6 4

0 0.010

0.14 0.01 0.99

0.03 0.06 0.01 0.003 0.03 0.05 0.1 0.014 0.01 0.08

0.086 0.00 0.43 1 0.144 0.00 0.82

6 23

0 0.000

0.14 0.00 1.00

0.03 0.02 0.01 0.003 0.13 0.14 0.1 0.014 0.06 0.18 0.5 0.072 0.29 0.74 1 0.144 0.06 1.03

8 4

0 0.009

0.12 0.01 1.00

0.07 0.12 0.01 0.014 0.08 0.16 0.1 0.029 0.08 0.17 0.5 0.072 0.16 0.58 1 0.130 0.15 0.90

8 23

0 -0.001

0.29 0.00 1.00

0.04 0.04 0.01 -0.004 0.06 0.04 0.1 0.029 0.03 0.20 0.5 0.130 0.13 0.91 1 0.288 0.12 1.72

Chris Keung 51


Table 4-6 cont.: Hydrogen peroxide decay regression summary

Hydrogen Peroxide



Demand 24 hr

Demand

Med-High

6 4

0 -0.007

0.12 0.01 0.99

0.05 0.00 0.01 -0.001 0.10 0.06 0.1 0.009 0.14 0.23 0.5 0.043 0.05 0.76 1 0.115 0.14 1.84

6 23

0 0.006

0.05 0.00 0.99

0.00 0.05 0.01 0.000 0.10 0.10 0.1 0.010 0.12 0.14 0.5 0.029 0.30 0.62 1 0.058 0.00 0.84

8 4

0 0.006

0.08 0.01 0.98

0.04 0.11 0.01 0.014 0.19 0.40 0.1 0.59 0.65 0.5 0.058 0.16 0.96 1 0.086 0.50 1.81

8 23

0 0.001

0.08 0.01 0.97

0.13 0.14 0.01 0.009 0.02 0.12 0.1 0.025 0.11 0.47 0.5 0.043 0.26 0.95 1 0.086 0.23 1.59

High

6 4

0

0.03 0.01 0.99

0.04 0.00 0.01 0.33 0.20 0.1 0.013 0.14 0.50

0.029 0.23 0.95 1 0.043 0.73 1.86

6 23

0 0.001

0.04 0.00 0.97

0.09 0.16 0.01 0.28 0.09 0.1 0.003 0.09 0.20 0.5 0.029 0.38 0.99 1 0.043 0.30 1.51

8 4

0 0.006

0.05 0.01 1.00

0.01 0.17 0.01 0.009 0.02 0.25 0.1 0.012 0.02 0.73 0.5 0.032 0.26 1.83 1 0.058 0.47 2.14

8 23

0 -0.001

0.06 0.00 1.00

0.25 0.18 0.01 0.003 0.15 0.25 0.1 0.004 0.15 0.33 0.5 0.029 0.21 1.07 1 0.058 0.60 2.60

Chris Keung 52


Table 4-7: Huwa-San peroxide decay regression summary

Huwa-San Peroxide



Demand 24 hr

Demand

Low

6 4

0 0.086

0.44 0.10 1.00

0.00 0.03 0.01 0.102 0.00 0.00 0.1 0.156 0.00 0.03 0.5 0.318 0.02 0.07 1 0.540 0.03 0.15

6 23

0 0.051

0.68 0.01 0.98

0.03 0.03 0.01 0.013 0.02 0.02 0.1 0.057 0.00 0.00 0.5 0.294 0.50 0.13 1 0.720 0.10 0.20

8 4

0 0.050

0.88 0.00 0.99

0.00 0.03 0.01 0.006 0.00 0.00 0.1 0.040 0.05 0.07 0.5 0.418 0.05 0.08 1 0.887 0.05 0.12

8 23

0 0.012

1.74 0.01 1.00

0.00 0.05 0.01 0.037 0.03 0.05 0.1 0.144 0.00 0.00 0.5 0.772 0.03 0.08 1 1.771 0.05 0.10

Med-Low

6 4

0 0.023

0.19 0.02 1.00

0.02 0.00 0.01 0.021 0.00 0.05 0.1 0.031 0.05 0.10

0.115 0.05 0.10 1 0.203 0.08 0.20

6 23

0 0.012

0.13 0.01 0.99

0.00 0.05 0.01 0.00 0.02 0.1 0.029 0.00 0.07 0.5 0.066 0.05 0.07 1 0.144 0.13 0.23

8 4

0 0.028

0.50 0.02 1.00

0.00 0.02 0.01 0.022 0.02 0.05 0.1 0.049 0.05 0.07 0.5 0.279 0.07 0.07 1 0.517 0.02 0.07

8 23

0 0.041

0.43 0.05 0.99

0.02 0.10 0.01 0.050 0.00 0.08 0.1 0.110 0.00 0.05 0.5 0.292 0.03 0.05 1 0.474 0.05 0.15

Chris Keung 53


Table 4-7 cont.: Huwa-San peroxide decay regression summary

Huwa-San Peroxide



Demand 24 hr

Demand

Med-High

6 4

0 0.007

0.14 0.01 0.98

0.02 0.05 0.01 0.018 0.00 0.05 0.1 0.038 0.07 0.07 0.5 0.072 0.08 0.08 1 0.156 0.02 0.15

6 23

0 0.013

0.16 0.02 0.95

0.00 0.00 0.01 0.017 0.00 0.00 0.1 0.019 0.07 0.15 0.5 0.120 0.03 0.13 1 0.158 0.07 0.15

8 4

0 0.032

0.10 0.04 0.95

0.00 0.02 0.01 0.046 0.05 0.03 0.1 0.049 0.00 0.00 0.5 0.103 0.05 0.05 1 0.129 0.02 0.12

8 23

0 0.039

0.25 0.04 1.00

0.03 0.00 0.01 0.031 0.08 0.00 0.1 0.061 0.02 0.05 0.5 0.163 0.13 0.10 1 0.282 0.07 0.17

High

6 4

0 0.009

0.07 0.00 0.97

0.03 0.03 0.01 0.009 0.00 0.02 0.1 0.006 0.03 0.13

0.033 0.15 0.30 1 0.082 0.10 0.17

6 23

0 0.022

0.12 0.01 0.96

0.00 0.00 0.01 0.009 0.00 0.10 0.1 0.026 0.00 0.03 0.5 0.055 0.00 0.15 1 0.144 0.08 0.28

8 4

0 0.013

0.06 0.02 0.87

0.05 0.08 0.01 0.032 0.02 0.02 0.1 0.033 0.03 0.08 0.5 0.039 0.05 0.08 1 0.088 0.05 0.10

8 23

0 0.007

0.15 0.03 0.96

0.05 0.00 0.01 0.029 0.05 0.03 0.1 0.059 0.15 0.00 0.5 0.104 0.07 0.27 1 0.176 0.10 0.28

Chris Keung 54


One of the limitations with this study is that the initial demands and decay coefficients that were

determined are specific to the wastewater and source water samples used. Initial demands and

decay vary depending on the composition of the wastewater and distributed water and need to be

analyzed on a site-by-site basis. Additionally, experiments were completed in bulk water and

completed without incorporating the complexities of the distribution system such as system

hydraulics, biofilm, and pipe wall interactions.


Chlorine was observed to be the most appropriate sentinel of intrusion under the tested

laboratory conditions at raw sewage dilutions of greater than 0.4% and 0.2% for 30 minutes and

24 hours respectively. The other disinfectants (chloramines, ClO2, H2O2, and HSP) did not

appear to consistently cause a noticeable change in the disinfectant residuals when contaminated

with raw sewage at dilutions of as high as 0.5%. At the largest sewage intrusion of 1%,

chloramines, ClO2, H2O2 and HSP observed 30-minute changes in residuals of less than 18%

with the exception of ClO2 at its low (0.05 mg/L) and med-low (0.2 mg/L) concentrations which

observed differences of between 14-35% and 18-26% respectively. At 24 hours, only the lowest

concentrations of chloramines, H2O2, and HSP showed noticeable changes in residuals of greater

than 30%. For 1% sewage intrusion, ClO2 showed a noticeable 24-hour change for all

concentrations but since the maximum ClO2 residual is only 0.8 mg/L, any small change in

residual will have a greater effect on the % residual remaining value and thus may not be

appropriate as a sentinel of intrusion.

4.3 REFERENCES Byer, D. and Carlson, K.H. (2005) Real-Time Detection of Intentional Chemical Contamination in the Distribution System. Journal of the American Water Works Association 97(7), 130-133.

CDC (2013) Surveillance for Waterborne Disease Outbreaks Associated with Drinking Water and Other Nonrecreational Water - United States, 2009-2010. Morbidity and Mortality 62(35), 714-720.

Clark, R.M. and Deininger, R.A. (2000) Protecting the Nation's Critical Infrastructure: The Vulnerability of US Water Supply Systems. Journal of Contingencies and Crisis Management 8(2), 73-80.

Chris Keung 55


Deborde, M. and Von Gunten, U. (2008) Reactions of Chlorine with Inorganic and Organic Compounds During Water Treatment—Kinetics and Mechanisms: a Critical Review. Water Research 42(1), 13-51.

Deininger, R.A., Lee, J. and Clark, R.M. (2011) Rapid Detection of Bacteria in Drinking Water and Water Contamination Case Studies. Frontiers of Earth Science 5(4), 378-389.

DHS (2004) Department of Homeland Security: Homeland Security Presidential Directive/HSPD-6. Retrieved August 2, 2015 from http://fas.org/irp/offdocs/nspd/hspd-9.html

Eliades, D., Lambrou, T., Panayiotou, C. and Polycarpou, M. (2014) Contamination Event Detection in Water Distribution Systems Using a Model-based Approach. Procedia Engineering 89, 1089-1096.

Eliades, D.G. and Polycarpou, M.M. (2010) A Fault Diagnosis and Security Framework for Water Systems. Control Systems Technology, IEEE Transactions18(6), 1254-1265.

Fogarty, J., Thornton, L., Hayes, C., Laffoy, M., O'Flannagan, D., Devlin, J. and Corocoran, R. (1995) Illness in a Community Associated with an Episode of Water Contamination with Sewage. Epidemiol. Infect. 114, 289-295.

Geldreich, E.E. (1996) Microbial Quality of Water Supply in Distribution Systems, CRC Press, Boca Raton, FL.

Grayman W.M. (2010) Contamination of Water Distribution Systems. Retrieved July 8, 2014 from http://www.federationofscientists.org/PlanetaryEmergencies/Seminars/45th/Grayman%20publication.doc

Hall, J., Zaffiro, A.D., Marx, R.B., Kefauver, P.C., Krishnan, E.R., Haught, R.C. and Herrmann, J.G. (2007) On-line Water Quality Parameters as Indicators of Distribution System Contamination. Journal American Water Works Association, 66-77.


Hrudey, S.E. and Hrudey, E.J. (2004) Safe Drinking-Water. Lessons from Recent Outbreaks in Affluent Nations, IWA Publishing, London.

Kirmeyer, G.J., Martel, K., Howie, K. and LeChevallier, M. (2001) Pathogen Intrusion Into the Distribution System, American Water Works Association, Denver.

Kolthoff, I.M., Sandell, E.B., Meehan, E.L. and Bruckenstein, S. (1973) Quantitative Chemical Analysis, Macmillan Company, London.

http://fas.org/irp/offdocs/nspd/hspd-9.html

http://www.federationofscientists.org/PlanetaryEmergencies/Seminars/45th/Grayman%20publication.doc

http://www.federationofscientists.org/PlanetaryEmergencies/Seminars/45th/Grayman%20publication.doc

Chris Keung 56


LeChevallier, M., Gullick, R., Karim, M., Friedman, M. and Funk, J. (2003) The Potential for Health Risks from Intrusion of Contaminants Into the Distribution System from Pressure Transients. J Water Health 1, 3-14.


Olivieri, V.P., Snead, M.C., Krusé, C.W. and Kawata, K. (1986) Stability and Effectiveness of Chlorine Disinfectants in Water Distribution Systems. Environmental Health Perspectives 69, 15-29.

Rice, E.W., Bridgewater, L. and A.P.H. Association (2012) Standard Methods for the Examination of Water and Wastewater, American Public Health Association Washington, DC.

Roberston, J.A. and Morley, K.M. (2005) Contamination Warning Systems for Water: An Approach for Providing Actionable Information to Decision-Makers, American Water Works Association, Denver.

Shuval, H., Yarom, R. and Shenman, R. (2009) An Innovative Method for the Control of Legionella Infections in the Hospital Hot Water Systems with a Stabilized Hydrogen Peroxide-Silver Formulation. International Journal of Infection Control 5(1), 1-5.

Skadsen, J., Janke, R., Grayman, W., Samuels, W., Tenbroek, M., Steglitz, B. and Bahl, S. (2008) Distribution system On-Line Monitoring for Detecting Contamination and Water Quality Changes. Journal of the American Water Works Association 100(7), 81-94.

Snead, M.C., Olivieri, V.P., Kruse, C.W. and Kawata, K. (1980) Benefits of Maintaining a Chlorine Residual in Water Supply Systems, USEPA, Cincinnati, OH.

Trussell, R.R. (1999) Safeguarding Distribution System Integrity. Journal of the American Water Works Association 91(1), 46-54.

USEPA (2002) Total Coliform Rule Issue Paper: The Effectiveness of Disinfectant Residuals in the Distribution System. Retrieved January 18, 2015 from http://www.epa.gov/safewater/disinfection/tcr/pdfs/issuepaper_effectiveness.pdf

van Lieverloo, J. M., Blokker, M. E., Medema, G., Hambsch, B., Pitchers, R., Stanfield, G., et al. (2006) Microbiological Risk Assessment: A Scientific Basis for Managing Drinking Water Safety from Source to Tap. Retrieved June 19, 2015, from http://www.microrisk.com/uploads/microrisk_distribution_assessment.pdf

Vasconcelos, J.J., Rossman, L.A., Grayman, W.M., Boulos, P.F. and Clark, R.M. (1997) Kinetics of Chlorine Decay. Journal of the American Water Works Association 89, 54-6

Chris Keung 57


5 EVALUATING PATHOGEN PROPAGATION IN A DISTRIBUTION SYSTEM USING A SYSTEMS

VULNERABILITY MODEL

ABSTRACT

A hydraulic distribution system water quality model, EPANET-MSX, was used to

evaluate the ability of various secondary disinfectants (chlorine (Cl2),

chloramines, chlorine dioxide (ClO2), hydrogen peroxide (H2O2), HuwaSan

peroxide (HSP)) to prevent downstream pathogen propagation after a simulated

intrusion event in an example distribution system. Under the modeled conditions,

Cl2, ClO2, H2O2 and HSP achieved 3-log inactivation of E. coli intrusion

scenarios within 15 minutes, thus preventing significant downstream propagation.

Chloramines required between 90-230 minutes to achieve 3-log inactivation of E.

coli under the modeled conditions. Maintaining a chloramine residual still helped

reduce downstream pathogen propagation as the presence of E. coli was limited to

a single section of the network. Cl2, ClO2, and HSP performed similarly in

Giardia intrusion scenarios where 3-log inactivation was achieved between 30-

150 minutes, although an assumed inactivation rate for HSP based on an untested

extrapolation was used. Using chloramines and H2O2 required between 330-1180

and 170-910 minutes respectively to achieve 3-log inactivation of Giardia.

Additionally, chloramines and H2O2 were much less effective than the other

disinfectants at limiting downstream propagation especially at lower

concentrations where Giardia (>10 organisms/L) was observed at 20 of the 24

downstream nodes.

5.1 INTRODUCTION

In recent years, the regulation of drinking water treatment has seen improvements by setting

rational, quantitative goals such as the introduction of CT values to guide primary disinfection.

Unfortunately, the control of water quality within the distribution system hasn’t followed the

same trend. For example in the United States, the Surface Water Treatment Rule (USEPA, 1989)

requires filtration and disinfection that achieves a specific pathogen reduction of 3-log for

Chris Keung 58


Giardia lamblia and 4-log for viruses whereas for the distribution system, the SWTR just

requires a detectable disinfectant residual (either free or combined chlorine) in 95% of the

samples each month (USEPA, 1989). Although there is still a debate about the public health

benefits with maintaining a disinfectant residual, one of the arguments is that a residual may

inactivate pathogens that enter into a distribution system after primary disinfection and perhaps

help to alleviate potential illness. There have been many documented outbreaks leading to

widespread illness such as the contamination of E. coli O157:H7 in Cabool, MO or the outbreak

of Salmonella typhimurium in Gideon, MO in which both systems did not maintain a disinfectant

residual (Haas, 1999). Both of these outbreaks involved vegetative bacterial pathogens (sensitive

to chlorine) and researchers have argued that the severe public health consequences could have

been minimized if a disinfectant residual had been maintained (Haas, 1999; Propato and Uber,

2004).

Pathogen intrusion or contamination can be caused by a number of different mechanisms such as

treatment breakthrough, leaking pipes, valves, or seals, cross connections and backflow,

reservoir contamination, main repairs, negative or transient pressure events, and intentional

intrusions (Besner et al., 2011; van Lieverloo et al., 2006; USEPA, 2002). Geldreich (1996)

examined the source of contamination for several previous outbreaks and reported that

inadequate pressure and back-siphoning were “by far” the most common mechanisms of

contamination. In a study using transient pressure modeling, Kirmeyer et al. (2001) determined

that for a specific distribution system, 90% of the nodes were drawing negative pressures during

modeled power outages. Changes in pressure can be caused by main breaks, sudden changes in

demand, pump stoppage, opening or closing of fire hydrants, fire hydrants, power failures, fire

flows, and many other conditions (LeChevallier et al., 2003). Pipes located below the water table

are subject to pressure caused by the exterior water and thus provides an opportunity for

contaminants to enter under low pressure situations. Kirmeyer et al. (2001) showed that at least

20% of the surveyed systems had pipes below the water table and that all the systems had some

pipe below the water table at least one time during the year. According to the 10 States Standards

(Great Lakes Upper Mississippi River Board of State and Provincial Public Health and

Environmental Managers, 2012), the main cause of some intrusion is the inability to maintain

adequate pressure within the distribution system and therefore should be operated at pressures

greater than 20 psi under all flow conditions (Ten State Standards, 2012; NRC, 2006)

Chris Keung 59


Although some studies have provided insight into the potential health risks associated with

contamination events such as the National Academies’ Water Science and Technology Board

Committee (National Research Council, 2006) linking low disinfectant residuals and pressure

transients in the distribution system to increased cases of gastrointestinal illnesses in the

population consuming tap water (Payment et al. 1991, 1997), the public health impact of

intrusion from pressure transients is still greatly unknown. The public health impact of intrusion

from pressure transients depends on a number of factors including the number and size of the

leak, the concentration of the contaminant entering the system, the frequency, duration and

magnitude of the pressure transient, and the population exposed. Intrusion events can vary

greatly between sites. For example, the volume of intrusion can range from milliliters to

hundreds of liters depending on the effective size of the orifice, the magnitude of the pressure

difference and the nature of the transient event (Kirmeyer et al., 2001) although for most

negative pressure events, the volume of intruded water is very small (less than 1% of the water

within the network) (Payment, 1999).

In summary, low and negative pressure events occur in the distribution system which means that

there exists a potential pathway for contaminants to intrude into the distribution system and

although these events do occur, there is very little information in determining to what extent

these events contribute to public health risk. Although there is still some debate on the

effectiveness of a disinfectant to inactivate pathogens during intrusion events, for most negative

pressure events, the volume of intruded water is very small so there exists an opportunity for

residuals to inactivate intruded pathogens (Snead et al., 1980; Payment, 1999). With the

development of new, innovative treatment solutions, regulators and policy makers may start to

look at the disinfection in distribution system in the same detail as disinfection within the

treatment plant. Quantitative public health evaluations along with studies examining risk-risk

tradeoffs evaluating the role of secondary disinfection (e.g. pathogen disinfection versus biofilm

suppression versus disinfection by-product formation) will be needed (LeChevallier et al., 2003)

in facilitating informed decisions from these regulatory parties.

5.1.1 Problem Statement

The ability of disinfectant residuals to inactivate pathogens between the time they enter the

distribution system and the time they reach the consumer’s taps is still poorly understood. To

Chris Keung 60


comply with disinfection by-product (DBP) regulations, more utilities are switching from

chlorine to chloramines or other alternative disinfectants. Although chloramines may reduce the

formation of regulated DBPs (Krasner, 2009) and may also be effective at suppressing biofilm

formation, they may be less aggressive disinfectants (Baribeau et al., 2005; LeChevallier et al.,

1988), and in the case of intrusion events, there is some question about whether these

disinfectant residuals can limit intruded pathogens from propagating downstream. The efficacy

of disinfection and propagation depends on a number of site-specific parameters including the

distribution system design and operation, the time and size of intrusion, disinfectant decay, and

disinfection kinetics.

The hydraulic and water quality software, EPANET-MSX (Rossman, 2000), was used to

estimate pathogen distribution for a microbial intrusion event. EPANET on its own can model

hydraulic and water quality in distribution systems but can only model single-species models for

water quality. For this reason, the multi specie extension (MSX) was used to simulate the fate

and transport of multiple disinfectant residuals (chlorine, chloramines, chlorine dioxide,

hydrogen peroxide, HuwaSan peroxide) and microbial contaminants (E. coli and Giardia

intrusion) allowing the study of downstream propagation of some contaminant in the presence of

a residual disinfectant (Shang et al., 2008).

The purpose of this paper was to develop a simple, quantitative model to evaluate different

disinfectants (chlorine, chloramines, chlorine dioxide, hydrogen peroxide, Huwa-San peroxide)

in their ability to control downstream propagation of an intruded pathogen (E. coli and Giardia)

and subsequently using this information as a tool for comparing their ability to alleviate potential

illness rates. Although this model will not include a Quantitative Microbial Risk Assessment

(QMRA) analysis and will include many simplified assumptions, the main purpose of this

microbial risk model is not to determine the exact risk of contamination but to compare different

disinfectants on an order of magnitude scale. Using this approach may help in the development

of a framework in which plausible scenarios for distribution system risk mitigation can be

evaluated. Subsequent work can then superimpose a QMRA analysis along with more accurate

models on top of this framework.

Chris Keung 61


5.2 MATERIALS AND METHOD

The assumptions and models used in this study as well as their associated limitations are

described in the sections below. This approach uses hydraulic and water quality models to

simulate the inactivation of pathogens that intrude into the distribution system under the

following assumptions: all reactions occur in bulk solutions (biofilm reactions are ignored),

disinfectant decay is first order, pathogen inactivation follows first order kinetics, disinfection

kinetic models developed under ideal laboratory conditions are assumed to predict inactivation of

pathogens (no particulate shielding) (Propato, 2004), and the hydraulic model assumes plug

flow.

5.2.1 Network Hydraulic Model

EPANET’s Example Network 2 (Figure 5-1) was used as the sample distribution network which

is comprised of 36 nodes, one reservoir tank and one pumping station. The relatively small

distribution system covers a distance of approximately 36,000 ft and it made up of 8 and 12 inch

diameter pipe. A storage tank (node 26) provides water to other nodes when network demands

exceed the average water demand and refills during low demand times or if the tank level drops

below a minimum level. A 24 hour demand adapted from Bentanzo et al. (2008) and Propato and

Uber (2004) was applied to the network which led to large fluctuations in the water age at some

nodes over the simulation. A model run time of 192 hours was selected to ensure a consistent

water age pattern was reached and to ensure a detectable disinfectant residual throughout the

distribution system. The complete set of EPANET-MSX codes can be found in Appendix F.

Chris Keung 62


.

Figure 5-1: Example network distribution system

5.2.2 Selection of Nodes to Receive Contamination

Low pressure events can result in contamination (Kirmeyer et al., 2001) and therefore utilities

should maintain pressures of greater than 20 psi in the distribution system (Ten State Standards,

2012; National Research Council, 2006). Using the EPANET hydraulic model, nodes susceptible

to low pressures were identified as potential locations of intrusion. Node 12 was identified as a

location susceptible to low pressures and was selected as the location of intrusion to observe

downstream propagation of the intruded pathogens. Additionally, an intrusion at node 12 affects

a large area and a large portion of the network.

5.2.3 Volume and Duration of Contamination

One of the difficulties and gaps in characterizing intrusion events has been determining the

duration of an intrusion and the volume of contaminated water that actually enters into the

system. Low/negative pressure events are usually caused by abrupt changes in the velocity of the

Chris Keung 63


water and these events can range from a few milliseconds to a few minutes (Besner et al., 2011).

In determining the magnitude/duration of a negative pressure event, Gullick et al. (2004)

concluded that all negative events for the studied distribution system lasted less than 165 seconds

(approximately 3 minutes). The EPANET-MSX model was run for intrusion durations of 10

minutes (short) and 1 hour (long) and although these durations are typically longer than most

intrusion events, in order to clearly observe the impact of disinfection inactivation on

downstream pathogen inactivation, a longer intrusion time and pathogen load was required.

Table 5-1: Estimation of intrusion flow rate (L/min) using hydraulic modeling (adapted from Kirmeyer et al., 2001)

Orifice Diameter

(mm)

Power Loss Main Break Fire Flow

0.31 m Head

Difference

3.05m Head

Difference

0.31 m Head

Difference

3.05m Head

Difference

0.31 m Head

Difference

3.05m Head

Difference 0.8 0.1 0.6 0.3 0.9 0.3 0.9 3.2 1.5 9.1 4.5 13.6 4.5 13.6 12.7 22.7 136.3 60.6 204.4 60.6 196.8 25.4 60.6 439.1 174.1 726.8 181.7 658.7 50.8 98.4 1400.6 416.4 2536.2 348.3 1847.3

Based on 7 utilities surveys, Kirmeyer et al. (2001) reported circular leak diameters from 3 mm

to 100 mm, circumferential leak width (along perimeter) of 3 mm to 100mm and longitudinal

leaks (along length) widths of 3 to 150 mm by 0.6 -6m long. Leaking water mains located below

the water table are certainly more vulnerable to intrusion as the height of groundwater provides

an external head that may become greater than the internal system pressure when a low pressure

event occurs. Using hydraulic modeling, Kirmeyer et al. (2001) determined the intrusion volume

for a 30 second intrusion event taking into account the size of the orifice, external pressure

difference, and nature of the transient event (Table 5-1). In another study conducted by Betanzo

et al. (2008), an intrusion flow rate of 1 L/min was assumed. In the case of a large intrusion

event (i.e. large intrusion flow rate), the intrusion may overwhelm the disinfectant residual.

Therefore to model a smaller, more frequent intrusion event as well as for overall model

simplicity, an intrusion flow rate of 1.5 L/min was used in the EPANET-MSX model as

Chris Keung 64


estimated by Table 5-1 corresponding to an event caused by a power loss, orifice diameter = 3.2

mm and difference in head of 0.31m.

5.2.4 Selection of Disinfectant Demand (Initial/Decay)

A contamination event was simulated by applying a constant rate, steady-state pathogen inflow

into the system for a specific duration as explained in the previous section (Section 5.2.3). It was

assumed that the intrusion would be raw wastewater, representing a worst case scenario and that

the intrusion would cause decay in the disinfectant residual. Disinfectant decay was modeled

after equation (1), which incorporates an instantaneous demand at the time of intrusion followed

by subsequent first order decay.

𝐶𝑡 = (𝐶0 − 𝐼𝐼)−𝑘𝑡 (1)

Where: Ct = disinfectant concentration at time, t after intrusion; C0 = initial disinfectant

concentration at time, t = 0; ID = instantaneous demand as calculated as the difference between

the 30-minute (t = 30) and initial residual (t = 0); k = decay rate coefficient as determined by

plotting the natural logarithm of residual concentration over initial residual concentration versus

contact time (slope of the plot equals the k-value). Reaction kinetics between raw wastewater

and secondary disinfectants (Cl2, chloramines, ClO2, H2O2, HSP) were determined in laboratory

bench scale decay tests as described in Chapter 4. A full set of decay tests were conducted in

Chapter 4 for different raw sewage dilutions, concentration and type of disinfectant, pH and

temperature but for simplicity, a single parameter for the initial demands and subsequent first-

order decay coefficients was used in the EPANET-MSX model as listed in Table 5-2 below.

Other simplifying assumptions include: only bulk water decay modeled (biofilm and wall

interactions are not taken into account); and EPANET assumes plug flow (no dispersion) (Shang

et al., 2008).

Chris Keung 65


Table 5-2: Secondary disinfectants initial demands and decay constants used in EPANET-MSX model

Disinfectant Initial Demand After Intrusion (mg/L)

First Order Decay Coefficient (1/day)

Cl2 0.26 0.518 Chloramines 0 0.070

ClO2 0.03 0.288 H2O2 0.03 0.029 HSP 0 0.110

5.2.5 Concentration of Pathogens

The use of raw sewage as an outside source of contamination is likely to represent a worst case

situation (Besner et al., 2011), whereas in fact, the level of pathogens found in intrusion

pathways may be more typical of untreated river water than wastewater based on indicator

microorganism concentrations measured next to water mains and in flooded vaults (Besner et al.,

2011). The public health risk associated with such events is not well understood.

In work reported by Yang et al. (2015), 22 studies on the concentrations of norovirus, E. coli

O157:H7, and Cryptosporidium in raw wastewater were summarized by using a two-level meta-

analysis model. This allows for a predictive distribution of pathogen concentrations in raw

sewage (Teunis et al., 2010). Table 5-3 shows the predicted concentrations of pathogens in raw

sewage. Bukhari et al. (1997) reported Giardia concentrations in raw sewage of up to

approximately 50,000 cysts/L. For simplicity, a single pathogen dose was selected for all

EPANET-MSX simulations. The median E. coli O157 concentration of 5.21 x 103 organisms/L

as predicted by Yang et al. (2015) was assumed for all EPANET-MSX pathogen concentrations

(undiluted) to ensure that inactivation trends and pathogen propagation could be clearly

observed.

Table 5-3: Summary of predicted concentrations (#/L) of pathogens in raw sewage (adapted from Yang et al. 2015)

Pathogen Geometric Mean Q0.025 Median Q0.975

Norovirus (virus) 1.59 x 104 1.98 x 10-4 2.38 x 104 1.39 x 1010

E. coli O157:H7 (bacteria) 3.19 x 103 1.57 x 10-7 5.21 x 103 2.47 x 1011

Cryptosporidium (protozoa) 2.58 x 101 2.03 x 10-3 2.84 x 101 2.41 x 105

Chris Keung 66


5.2.6 Pathogen Inactivation Constants

E coli. O157:H7 and Giardia were modeled in the EPANET-MSX software to evaluate pathogen

propagation associated with pathogens with either low or high disinfectant resistance. Pathogen

inactivation kinetics assumed classical Chick-Watson first-order inactivation kinetics (Gyürék

and Finch, 1998). The disinfection kinetic constant Kp, is defined as:

𝐾𝑝 = −ln (𝑃𝑡𝑃0

)

𝐶𝐶 (2)

where Kp = kinetic inactivation constant, Pt = number of pathogens at time t, P0 = number of

pathogens at time zero, and CT = product of disinfectant concentration, C (mg/L) and contact

time, T (min).

To our knowledge there is only one study providing CT values for E. coli using H2O2 and HSP

(Martin et al., 2015) and no CT values for Giardia using H2O2 and HSP. Therefore, to estimate

inactivation rates for E coli. and Giardia using H2O2 and HSP, the inactivation data for E coli.

K12 using chlorine, H2O2 and HSP provided by Martin et al. (2014) was used to determine a

scaling factor. This scaling factor would then be applied to known chlorine inactivation values to

estimate inactivation values for H2O2 and HSP. In the Martin et al. (2015) study, the Kp for

chlorine (E.coli K12) was 18.55 times the value for H2O2 and 1.023 times that of HSP. Thus, Kp

for E. coli using H2O2 and HSP was estimated as Kp for chlorine (11.0) divided by the scaling

factor (i.e. 11/18.55 = 0.593 and 11/1.023 = 10.75 for HSP and H2O2 respectively). Similarly for

Giardia, Kp was determined to be 0.0072 (0.1337/18.55) and 0.1306 (0.1337/1.023) for H2O2

and HSP respectively. A summary of the inactivation kinetics used in the EPANET-MSX model

for E. coli and Giardia are shown in Tables 5-4 and 5-5 respectively.

Table 5-4: E coli. inactivation constants (Kp) used in EPANET-MSX model

Disinfectant Pathogen pH Temp (°C) Kp (L/mg min) Cl2 E. coli O157:H7 7-8 25 11.01

Chloramines E. coli O157:H7 8 25 0.0441

ClO2 E. coli 6.5-7 25 16.4772

H2O2 E. coli K12 7 N/A 0.5933

HSP E. coli K12 7 N/A 10.753

1. Betanzo et al. (2008) 2. LeChevallier et al. (1988) 3. Martin et al. (2015) – estimated according to scaling factor

Chris Keung 67


Table 5-5: Giardia inactivation constants (Kp) used in EPANET-MSX model

Disinfectant Pathogen pH Temp (°C) Kp (L/mg min) Cl2 Giardia 7-9 20 0.13371

Chloramines Giardia 6-9 20 0.00631

ClO2 Giardia 6-9 20 0.45761

H2O2 Giardia N/A N/A 0.00722

HSP Giardia N/A N/A 0.13062

1. USEPA (1989) 2. Martin et al. (2015) – estimated according to scaling factor

5.2.7 Residual Maintenance Strategy

Disinfectant was added into the distribution system at the pumping station (node 1) at

concentrations according to Table 5-6. The presence of the storage tank influences the

distribution of residual concentration through the system. When the storage tank is supplying

water to the network with zero or low disinfectant residual, the dilution can cause large

variations in disinfectant residual. Additionally, based on the limitations of the model, if a

disinfectant concentration is near zero and an instantaneous demand from the intrusion event is

applied, the resulting disinfectant concentration will result in a negative residual which

unrealistically leads to pathogen growth. Therefore, a disinfectant booster was added at the

storage tank at concentrations according to Table 5-6 in order to maintain a consistent positive

residual throughout the distribution system.

Table 5-6: Disinfectant residual concentrations added at pumping station (node 1) and tank booster station (node 26)

Disinfectant Low Concentration (mg/L) High Concentration (mg/L)

Pumping Sta. Node 1

Tank Booster Node 26

Pumping Sta. Node 1

Tank Booster Node 26

Cl2 1 0.5 4 2 Chloramines 1 0.3 3 0.6

ClO2 0.2 0.13 0.8 0.15 H2O2 1 0.3 6 1.1 HSP 1 0.2 6 1.8

Chris Keung 68



5.3.1 E. Coli Intrusion

The first scenario based on E. coli intrusion was modeled in order to represent an event that may

involve a typical organism with “average” disinfection resistance. For simplicity and to clearly

observe the impact of inactivation, an E. coli concentration of 5210 organisms/L was intruded for

either 10 minutes (short duration) or 1 hour (long duration) at node 12. Based on a simple CT

calculation using classical Chick-Watson first-order inactivation kinetics (Equation 2) and the

assumed disinfectant residuals, the estimated time to achieve 3-log inactivation was calculated

and compared to the EPANET-MSX model as seen in Table 5-7.

Table 5-7: Inactivation time to achieve 3-log inactivation for E. coli using CT calculation and EPANET-MSX model (long and short duration)

Disinfectant Inactivation Constant, Kp (L/mg min)

Low/High Conc. (mg/L)

Low/High Conc. Inactivation Time (min) CT

Calculation EPANET

(Long) EPANET (Short)

Chlorine 11.000 1/4 0.6/0.2 < 3 < 3

Chloramines 0.044 1/3 157/52 230/130 190/90

Chlorine Dioxide

16.477 0.2/0.8 2.1/0.5 < 3 < 3

Hydrogen Peroxide

0.593* 1/6 11.7/1.9 < 15 < 15

HuwaSan Peroxide

10.750* 1/6 0.6/0.1 < 3 < 3

*based on an estimated inactivation constant using scaling factor, Kp

Using the CT calculation estimates that 3-log inactivation for E. coli will occur rapidly (less than

12 minutes) for all the disinfectants except chloramine. The EPANET-MSX model under all E.

coli intrusion scenarios followed a similar trend. For all scenarios modeled, using Cl2, ClO2 or

HSP, initial E. coli concentrations of 5210 organisms/L were reduced to below 5 organism/L (3-

log inactivation) within 3 minutes of intrusion with H2O2 requiring less than 15 minutes for the

same reduction. Essentially, complete inactivation was achieved in a short period when using

these disinfectants (Cl2, ClO2, H2O2, and HSP), thus preventing downstream propagation of the

intruded contaminant. To achieve the same inactivation (<5 organism/L) using chloramines took

Chris Keung 69


130 (long duration/high concentration), 230 (long/low), 90 (short/high) and 190 minutes

(short/low) as shown in Figure 5-2.

Figure 5-2: E. coli inactivation for long and short intrusion events

Figure 5-3 shows the maximum E. coli concentrations observed at each node over the simulation

period using chloramines as a secondary disinfectant compared to when using no disinfectant

residual (long duration). Upstream nodes are not shown in the figure as no upstream pathogen

propagation was observed. Maximum E. coli concentrations for high and low chloramine

concentration scenarios were observed downstream at Node 25 at 1129-1159 and 74-75

organisms/L respectively. This indicates that under the modeled conditions, downstream

pathogen propagation occurred although there was still a benefit of maintaining a chloramine

residual compared to the scenario using no disinfectant residual where high E. coli

concentrations (>3556 organisms/L) were present at all downstream nodes. Although

downstream pathogen propagation occurred when using chloramines, the effect was essentially

limited to one segment of the distribution system (Nodes 12-13-14-15-24-23-25, refer to Figure

5-2) as E. coli did not appear in any of the branched sections of the distribution network.

0

1000

2000

3000

4000

5000

0 0.5 1 1.5 2 2.5 3

E. C

oli C

once

ntra

tion

(org

s/L)

Time (hours)

Long Duration - High ChloramineLong Duration - Low ChloramineShort Duration - High ChloramineShort Duration - Low Chloramine

Chris Keung 70


Figure 5-3: Maximum E. coli concentration observed at each node with intrusion occurring at

node 12

5.3.2 Giardia Intrusion

The second modeling scenario modeled Giardia to represent an intrusion containing a pathogen

with high disinfection resistance. Again, similar to the E. coli intrusion scenario, a pathogen

concentration of 5210 Giardia organisms/L was intruded for either 10 minutes (short duration)

or 1 hour (long duration) at node 12. The estimated time to achieve 3-log Giardia activation

using the CT method as described in Equation (2) and the results for the EPANET-MSX model

are shown in Table 5-8.

Figures 5-4 and 5-5 show the impact of high and low disinfectant residual concentrations on

Giardia concentration following a long (1 hour) duration intrusion event as simulated by the

EPANET-MSX model. For the 1 hour intrusion event, Giardia concentrations were reduced to

less than 5 organism/L in 1.3, 6.8, 1.5, 4 and 1.4 hours for high concentrations of Cl2,

chloramines, ClO2, H2O2 and HSP respectively (Figure 5-4). Subsequently, for the same event

but using low disinfectant concentrations, the same level of inactivation required 2.2, 19.6, 2.5,

15 and 2.3 hours for Cl2, chloramines, ClO2, H2O2 and HSP respectively (Figure 5-5). It is worth

noting that although occasional spikes in Giardia concentrations as seen in Figures 5-4 and 5-5

(t= 2.8, 3.4, 4.3 hours) may suggest that Giardia concentrations are increasing with increasing

0

1000

2000

3000

4000

5000

10 12 14 16 18 20 22 24 26 28 30 32 34 36

Max

E. C

oli C

once

ntra

tion

(org

s/L)

Node

Long/High ChloramineLong/Low ChloramineShort/High ChloramineShort/Low ChloramineLong/No Disinf.

Chris Keung 71


water age, these fluctuations are likely caused by spatial differences calculated from the

hydraulic model (Propato and Uber, 2004). Large differences in the average flow rates and

mixing of different waters can cause disinfectant concentrations to vary during a simulation thus

leading to fluctuations in the calculated number of surviving pathogens. Additionally, the

hydraulic model assumes plug flow meaning that dispersion of pathogens is limited and

undistorted during transport (Rossman, 2000; Teunis et al., 2010). Thus, any mixing with a

section of a “plug” containing the undistorted pathogens may cause a peak in pathogens.

Table 5-8: Inactivation time to achieve 3-log inactivation for Giardia using CT calculation and EPANET-MSX model (long and short duration)

Disinfectant Inactivation Constant, Kp (L/mg min)

Low/High Conc. (mg/L)

Low/High Conc. Inactivation Time (min) CT

Calculation EPANET

(Long) EPANET (Short)

Chlorine 0.1337 1/4 52/13 140/80 100/30

Chloramines 0.0063 1/3 1102/367 1180/410 730/330

Chlorine Dioxide

0.4576 0.2/0.8 75/19 150/90 110/50

Hydrogen Peroxide

0.0072* 1/6 959/160 910/240 600/170

HuwaSan Peroxide

0.1306* 1/6 53/9 140/90 90/40

*based on an estimated inactivation constant using scaling factor, Kp

Chris Keung 72


Figure 5-4: Giardia inactivation for long intrusion events assuming high disinfectant

concentrations

Figure 5-5: Giardia inactivation for long intrusion events assuming low disinfectant

concentrations

0

1000

2000

3000

4000

5000

0 2 4 6 8 10

Gia

rdia

Con

cent

ratio

n (o

rgs/

L)

Time (hour)

High Cl2 Conc.High Chloramine Conc.High ClO2 Conc.High H202 Conc.*High HSP Conc.*

0

1000

2000

3000

4000

5000

0 2 4 6 8 10

Gia

rdia

Con

cent

ratio

n (o

rgs/

L)

Time (hour)

Low Cl2 Conc.Low Chloramine Conc.Low ClO2 Conc.Low H202 Conc.*Low HSP Conc.*

Chris Keung 73


To evaluate downstream propagation of Giardia, the maximum Giardia concentrations were

observed at each node for the long (1 hour) intrusion event using high or low disinfectant

concentrations as shown in Figures 5-6 and 5-7 respectively. The short duration intrusion event

showed a similar trend to the long event and will not be presented.

As indicated in Figure 5-6, when using the high concentration of Cl2, ClO2 and HSP, pathogen

propagation was limited to a confined section of the network as Giardia was detected at only

three locations (nodes 13, 14 and 15) located directly downstream of the intrusion site (node 12).

Additionally, chloramines were the least effective at preventing downstream propagation after

the 1 hour intrusion event as 18 out of the 24 downstream nodes observed Giardia

concentrations of greater than 10 organisms/L. H2O2 was slightly more effective than

chloramines with 11 of the 24 downstream nodes receiving greater than 10 organisms/L.

Figure 5-6: Maximum Giardia concentration observed at each node with long duration intrusion

occurring at node 12 for high disinfectant concentrations

As expected, lower disinfectant concentrations led to greater Giardia propagation compared to

when using high concentrations of disinfectants (Figure 5-7). For a 1 hour intrusion and low Cl2,

ClO2 and HSP concentrations, although Giardia concentrations (>10 organisms/L) were

observed further downstream (7 out of 24 nodes), the propagation was still relatively contained

as contamination did not reach any of the branched sections of the network. Conversely,

0

1000

2000

3000

4000

5000

12 14 16 18 20 22 24 26 28 30 32 34 36

Max

Gia

rdia

Con

cent

ratio

n (o

rgs/

L)

Node

High Cl2 Conc.High Chloramine Conc.High ClO2 Conc.High H202 Conc.*High HSP Conc.*

Chris Keung 74


chloramines and H2O2 were not effective at controlling downstream pathogen propagation as

Giardia concentrations (>10 organisms/L) were observed at 20 of the 24 nodes. The only nodes

not receiving contamination (nodes 28, 30, 34 and 36) were locations at the furthest extents of

the distribution system where travel time from the source can take anywhere between 100 – 150

hours.

Figure 5-7: Maximum Giardia concentration observed at each node with long duration intrusion

occurring at node 12 for low disinfectant concentrations


Under the modeled conditions, Cl2, ClO2, H2O2 and HSP were essentially equally effective in

controlling E. coli intrusion scenarios. Intruded E. coli organisms were quickly inactivated by

Cl2, ClO2, H2O2 and HSP (3-log inactivation within 15 minutes) and thus may be beneficial in

preventing downstream propagation. Although E. coli inactivation using chloramines was much

slower than the other disinfectants (between 90-230 minutes), providing a chloramine residual

still helped reduce downstream pathogen propagation as the presence of E. coli was limited to a

single section of the network (no dispersion to branched sections). Cl2, ClO2, and HSP performed

similarly in Giardia intrusion scenarios where 3-log inactivation was achieved between 30-150

minutes and although Giardia inactivation required more time than E. coli inactivation, Cl2,

0

1000

2000

3000

4000

5000

12 14 16 18 20 22 24 26 28 30 32 34 36Max

Gia

rdia

Con

cent

ratio

n (o

rgs/

L)

Node

Low Cl2 Conc.Low Chloramine Conc.Low ClO2 Conc.Low H202 Conc.*Low HSP Conc.*

Chris Keung 75


ClO2, and HSP were still effective in controlling widespread pathogen dispersion throughout the

network—assuming that the extrapolated inactivation kinetics for HSP are correct. Conversely,

to achieve 3-log inactivation of Giardia when using chloramines and H2O2 required between

330-1180 and 170-910 minutes respectively. Chloramines and H2O2 were much less effective

than the other disinfectants at limiting downstream propagation especially at lower

concentrations where Giardia (>10 organisms/L) was observed at 20 of the 24 downstream

nodes.

It should be noted that inactivation kinetics for E. coli and Giardia used in this model were taken

from previous literature values conducted at 25°C which may represent more favorable

conditions for disinfection and thus do not necessarily represent a “worst-case” scenario.

Additionally, the inactivation kinetics for H2O2 and HSP were extrapolated from a single study

conducted by Martin et al. (2015) and therefore estimated values may not be representative of

inactivation kinetics occurring in real distribution systems.

The purpose of this paper was to develop a simple, quantitative approach to evaluate different

disinfectants in their ability to control downstream propagation of an intruded pathogen and

subsequently using this information as a tool for comparing their ability to alleviate potential

illness rates. Although this model did not include a QMRA analysis and included many

simplified assumptions, subsequent work can superimpose a QMRA analysis along with more

accurate models on top of this framework. Using this approach may help in the development of a

framework in which plausible scenarios for distribution system risk mitigation can be evaluated.

5.5 REFERENCES

Baribeau, H., Boulos, L., Pozos, N.L. and Crozes, G.F. (2005) Impact of Distribution System

Water Quality on Disinfection Efficacy, American Water Works Association, Denver, CO.

Besner, M.C., Prévost, M. and Regli, S. (2011) Assessing the Public Health Risk of Microbial

Intrusion Events in Distribution Systems: Conceptual Model, Available Data, and Challenges.

Water Research 45(3), 961-979.

Chris Keung 76


Betanzo, E.W., Hofmann, R., Hu, Z., Baribeau, H. and Alam, Z. (2008) Modeling the Impact of

Microbial Intrusion on Secondary Disinfection in a Drinking Water Distribution System. Journal

of Environmental Engineering 134(4), 231-237.

Bukhari, Z., Smith, H.V., Sykes, N., Humphreys, S.W., Paton, C.A., Girdwood, R.W.A and

Fricker, C.R. (1997) Occurrence of Cryptosporidium Spp Oocysts and Giardia Spp Cysts in

Sewage Effluents From Treatment Plants in England. Water Sci Technol 35(12), 385-390.

Geldreich, E.E. (1996) Microbial Quality of Water Supply in Distribution Systems, CRC Press,

Boca Raton, FL.

Great Lakes Upper Mississippi River Board of State and Provincial Public Health and

Environmental Managers (2012) Recommended Standards for Water Works – Ten State

Standards. Retrieved September 2, 2015 from http://10statesstandards.com/waterrev2012.pdf

Gullick, R.W., LeChevallier, M.W., Svindland, R.C. and Friedman, M.J. (2004) Occurrence of

Transient Low and Negative Pressures in Distribution Systems. Journal of the American Water

Works Association 96(11), 56-66.

Gyürék, L. and Finch, G. (1998) Modeling Water Treatment Chemical Disinfection Kinetics. J Environ Eng 124(9), 783–793.

Haas, C.N. (1999) Benefits of Using a Disinfectant Residual. Journal of the American Water

Works Association 91(1), 65-69.

Kirmeyer, G.J., Martel, K., Howie, K. and LeChevallier, M. (2001) Pathogen Intrusion Into the

Distribution System, American Water Works Association, Denver.

Krasner, S.W. (2009) The Formation and Control of Emerging Disinfection By-Products of

Health Concern. Philosophical Transactions of the Royal Society of London A: Mathematical,

Physical and Engineering Sciences 367(1904), 4077-4095.

LeChevallier, M.W., Cawthon, C.D. and Lee, R.G. (1988) Inactivation of Biofilm Bacteria. Appl

Environ Microbiol 54(10), 2492-2499.

Chris Keung 77


LeChevallier, M.W., Gullick, R., Karim, M., Friedman, M. and Funk, J. (2003) The Potential for

Health Risks from Intrusion of Contaminants into the Distribution System from Pressure

Transients. J Water Health 1, 3-14.

Martin, N., Bass, P., Liss, S.N. (2015) Antibacterial Properties and Mechanism of Activity of a

Novel Silver-Stabilized Hydrogen Peroxide. PLOS One 10(7), 1-20.

National Research Council (2006) Drinking Water Distribution Systems: Assessing and

Reducing Risks, The National Academies Press, Washington, DC.

Payment, P., Richardson, L., Siemiatycki, J., Dewar, R., Edwardes, M. and Franco, E. (1991) A

Randomized Trial to Evaluate the Risk of Gastrointestinal Disease Due to Consumption of

Drinking Water Meeting Current Microbiological Standards. American Journal of Public Health

81(6), 703-708.

Payment, P., Siemiatycki, J., Richardson, L., Renaud, G., Franco, E. and Prevost, M. (1997) A

Prospective Epidemiological Study of Gastrointestinal Health Effects Due to the Consumption of

Drinking Water. International Journal of Environmental Health Research 7(1), 5-31.

Payment, P. (1999) Poor Efficacy of Residual Chlorine Disinfectant in Drinking Water to

Inactivate Waterborne Pathogens in Distribution Systems. Canadian Journal of Microbiology

45(8), 709-715.

Propato, M. and Uber, J.G. (2004) Vulnerability of Water Distribution Systems to Pathogen

Intrusion: How Effective is a Disinfectant Residual? Environmental Science & Technology

38(13), 3713-3722.

Rossman, L.A. (2000) EPANET Version 2 User’s Manual, EPA Drinking Water Research

Division, Cincinnati, OH. Retrieved June 21, 2015 from

http://nepis.epa.gov/Adobe/PDF/P1007WWU.pdf

Shang, F., Uber, J.G. and Rossman, L.A. (2007) Modeling Reaction and Transport of Multiple

Species in Water Distribution Systems. Environmental Science & Technology 42(3), 808-814.

Snead, M.C., Olivieri, V.P., Kruse, C.W. and Kawata, K. (1980) Benefits of Maintaining a

Chlorine Residual in Water Supply Systems, USEPA, Cincinnati, OH.

Chris Keung 78


Teunis, P., Xu, M., Fleming, K., Yang, J., Moe, C. and LeChevallier, M. (2010) Enteric Virus

Infection Risk from Intrusion of Sewage Into a Drinking Water Distribution Network.

Environmental Science & Technology 44(22), 8561-8566.

USEPA (1989) Surface Water Treatment Rule. 40 CFR Parts 141 and 142 Drinking Water;

National Primary Drinking Water Regulation; Filtration, Disinfection; Turbidity, Giardia

lamblia, Viruses, Legionella, and Heterotrophic Bacteria; Final Rule. Federal Register 54(124),

June 29, 1989.

USEPA (2001) Total Coliform Rule Issue Paper: Potential Contamination Due to Cross-

Connections and Backflow and the Associated Health Risks. Retrieved August 23, 2015 from

http://www.epa.gov/safewater/disinfection/tcr/pdfs/issuepaper_tcr_crossconnection-

backflow.pdf

USEPA (2002) Total Coliform Rule Issue Paper: The Effectiveness of Disinfectant Residuals in

the Distribution System. Retrieved January 18, 2015 from

http://www.epa.gov/safewater/disinfection/tcr/pdfs/issuepaper_effectiveness.pdf

USEPA (2006) National Primary Drinking Water Regulation; Stage 2 Disinfectants and

Disinfection Byproducts Rule; Final Rule. Federal Register 71(388), January 4, 2006.

van Lieverloo, J. M., Blokker, M. E., Medema, G., Hambsch, B., Pitchers, R., Stanfield, G., et al.

(2006) Microbiological Risk Assessment: A Scientific Basis for Managing Drinking Water

Safety From Source to Tap. Retrieved June 19, 2015, from

http://www.microrisk.com/uploads/microrisk_distribution_assessment.pdf

Yang, J., LeChevallier, M., Teunis, P. and Xu, M. (2011) Managing Risks From Virus Intrusion

Into Water Distribution Systems Due to Pressure Transients. Journal of Water and Health 9(2),

291-305.

Yang, J., Schneider, O.D., Jjemba, P.K. and LeChevallier, M.W. (2015) Microbial Risk

Modeling for Main Breaks. Journal of the American Water Works Association 107(2), 97-108.

http://www.epa.gov/safewater/disinfection/tcr/pdfs/issuepaper_effectiveness.pdf

Chris Keung 79


6 SUMMARY, CONCLUSIONS AND RECOMMENDATIONS


This research included a field sampling campaign at Killaloe, Ontario testing HSP, laboratory

bench-scale experiments examining the efficacy of using different disinfectants as sentinels of

contamination, and a systems vulnerability assessment using the distribution system water

quality model (EPANET-MSX).

Results from the Killaloe sampling campaign continued to show that HSP, when used as a

secondary disinfectant, can be used to limit DBP formation while maintaining acceptable water

quality. Using HSP, THMs and HAAs averaged 28 and 21 μg/L respectively compared to

previous values (using chlorine) of 92-114 and 55-67 μg/L for THMs and HAAs respectively.

Prechlorination was found to be the major source of DBP formation as the highest observed

values occurred at Site 2 for THM, HAA and AOX. Genotoxicity analysis showed that the

chlorinated water had the highest genotoxic response and that HSP did not have an additive

effect on the toxic response.

Under tested laboratory conditions, chlorine was observed to be the most appropriate sentinel of

intrusion at raw sewage dilutions of greater than 0.4% and 0.2% for 30 minutes and 24 hours

respectively. The other disinfectants (chloramines, ClO2, H2O2, and HSP) did not appear to

consistently cause a noticeable change in the disinfectant residuals when contaminated with raw

sewage at dilutions of as high as 0.5%. At the largest sewage intrusion of 1%, chloramines,

ClO2, H2O2 and HSP observed 30-minute changes in residuals of less than 18% with the

exception of ClO2 at its low (0.05 mg/L) and med-low (0.2 mg/L) concentrations which observed

differences of between 14-35% and 18-26% respectively. At 24 hours, only the lowest

concentrations of chloramines, H2O2, and HSP showed noticeable changes in residuals of greater

than 30%. For 1% sewage intrusion, ClO2 showed a noticeable 24-hour change for all

concentrations but since the maximum ClO2 residual is only 0.8 mg/L, any small change in

residual will have a greater effect on the % residual remaining value and thus may not be

appropriate as a sentinel of intrusion.

Under the modeled EPANET-MSX conditions, Cl2, ClO2, H2O2 and HSP were essentially

equally effective in controlling E. coli intrusion scenarios. Intruded E. coli organisms were

Chris Keung 80


quickly inactivated by Cl2, ClO2, H2O2 and HSP (3-log inactivation within 15 minutes) and thus

may be beneficial in preventing downstream propagation. Although E. coli inactivation using

chloramines was much slower than the other disinfectants (between 90-230 minutes), providing a

chloramine residual still helped reduce downstream pathogen propagation as the presence of E.

coli was limited to a single section of the network (no dispersion to branched sections). Cl2,

ClO2, and HSP performed similarly in Giardia intrusion scenarios where 3-log inactivation was

achieved between 30-150 minutes and although Giardia inactivation required more time than E.

coli inactivation, Cl2, ClO2, and HSP were still effective in controlling widespread pathogen

dispersion throughout the network—assuming that the extrapolated inactivation kinetics for HSP

are correct. Conversely, to achieve 3-log inactivation of Giardia when using chloramines and

H2O2 required between 330-1180 and 170-910 minutes respectively. Chloramines and H2O2 were

much less effective than the other disinfectants at limiting downstream propagation especially at

lower concentrations where Giardia (>10 organisms/L) was observed at 20 of the 24

downstream nodes.

6.2 RECOMMENDATIONS FOR FUTURE WORK

The main goal of this research was to perform a rational quantitative re-evaluation of the needs

for secondary disinfection and to begin to build a framework in which secondary disinfection can

be evaluated. Building on the information provided in this thesis, several recommendations for

future studies in working towards this objective are provided.

Although HSP, has been effective at Killaloe in limiting DBP formation while maintaining

acceptable water quality, other distribution systems have not been rigorously tested. The effect of

site-specific parameters such as source water composition, pipe material, biofilm effects,

network size, etc. on the efficacy of using HSP as a secondary disinfectant are not well defined.

Interestingly, in the Kilalloe system, a decrease was observed for AOX and genotoxicity from

the point of HSP addition to the plant effluent. Although these results are preliminary, it is

intriguing that the presence of HSP appears to be correlated to a decrease over time in AOX and

genotoxicity that is formed by upstream chlorination. The reason for this trend was not studied in

this thesis but further investigation into this topic is warranted.

Chris Keung 81


The accuracy of the systems vulnerability/EPANET-MSX model can be greatly improved with

the integration of more accurate inactivation, decay, and QMRA models. In this study,

inactivation kinetics for H2O2 and HSP were extrapolated from a single study and therefore

estimated values may not be representative of inactivation kinetics occurring in real distribution

systems. More accurate inactivation kinetics models for alternative disinfectants are needed in

order to properly compare different disinfectants using this systems vulnerability approach. Also,

the decay constants were derived from a single wastewater sample. More accurate models may

include testing a variety of different intrusion sources and their effect on disinfectant decay.

Additionally, the results from modeling study were only limited to pathogen concentrations.

Subsequent work can use this current water quality model in combination with a full QMRA

analysis in order to directly compare different disinfectants from a public health risk perspective.

Chris Keung


APPENDICES

Chris Keung A-1


A. HSP QUENCHING AGENT DBP ANALYSIS

Chris Keung A-2


Figure A- 1: TCM concentration at day 0 and day 5 after the addition of various quenching agents

Figure A- 2: BDCM concentration at day 0 and day 5 after the addition of various quenching agents

0

20

40

60

80

100

120

DBP+15mg/L HSP DBP+15mg/L HSP+100mg NH4Cl

DBP+15mg/L HSP+150mg NaSO3

DBP+15mg/L HSP+120mg Na2S2O3

DBP+15mg/L HSP+100mg ascorbic

acid

DBP+15mg/L HSP+0.2mg/L catalase

DBP

TCM

(μg/L)

Figure A-1. TCM

Day 0 Day 5

0

20

40

60

80

100

120





acid


DBP

BDCM

(μg/L)

Figure A-2. BDCM

Day 0 Day 5

Chris Keung A-3


Figure A- 3: DBCM concentration at day 0 and day 5 after the addition of various quenching agents

Figure A- 4: TBM concentration at day 0 and day 5 after the addition of various quenching agents

0

20

40

60

80

100

120





acid


DBP

DBCM

(μg/L)

Figure A-3. DBCM

Day 0 Day 5

0

20

40

60

80

100

120





acid


DBP

TBM

(μg/L)

Figure A-4. TBM

Day 0 Day 5

Chris Keung A-4


Figure A- 5: TCAN concentration at day 0 and day 5 after the addition of various quenching agents

Figure A- 6: DCAN concentration at day 0 and day 5 after the addition of various quenching agents

-10

10

30

50

70

90

110

130





acid


DBP

TCAN

(μg/L)

Figure A-5. TCAN

Day 0 Day 5

0

20

40

60

80

100

120





acid


DBP

DCAN

(μg/L)

Figure A-6. DCAN

Day 0 Day 5

Chris Keung A-5


Figure A- 7: DCP concentration at day 0 and day 5 after the addition of various quenching agents

Figure A- 8: CP concentration at day 0 and day 5 after the addition of various quenching agents

0

20

40

60

80

100

120





acid


DBP

DCP (μg/L)

Figure A-7. DCP

Day 0 Day 5

0

20

40

60

80

100

120





acid


DBP

CP (μ

g/L)

Figure A-8. CP

Day 0 Day 5

Chris Keung A-6


Figure A- 9: BCAN concentration at day 0 and day 5 after the addition of various quenching agents

Figure A- 10: TCP concentration at day 0 and day 5 after the addition of various quenching agents

0

20

40

60

80

100

120





acid


DBP

BCAN

(μg/L)

Figure A-9. BCAN

Day 0 Day 5

0

20

40

60

80

100

120





acid


DBP

TCP (μg/L)

Figure A-10. TCP

Day 0 Day 5

Chris Keung A-7


Figure A- 11: DBAN concentration at day 0 and day 5 after the addition of various quenching agents

Figure A- 12: MCAA concentration at day 0 and day 5 after the addition of various quenching agents

0

20

40

60

80

100

120





acid


DBP

DBAN

(μg/L)

Figure A-11. DBAN

Day 0 Day 5

0

20

40

60

80

100

120

140

160





acid


DBP

MCA

A (μg/L)

Figure A-12. MCAA

Day 0 Day 5

Chris Keung A-8


Figure A- 13: MBAA concentration at day 0 and day 5 after the addition of various quenching agents

Figure A- 14: DCAA concentration at day 0 and day 5 after the addition of various quenching agents

0

20

40

60

80

100

120

140

160





acid


DBP

MBA

A (μg/L)

Figure A-13. MBAA

Day 0

Day 5

0

20

40

60

80

100

120

140

160





acid


DBP

DCAA

(μg/L)

Figure A-14. DCAA Day 0

Day 5

Chris Keung A-9


Figure A- 15: TCAA concentration at day 0 and day 5 after the addition of various quenching agents

Figure A- 16: BCAA concentration at day 0 and day 5 after the addition of various quenching agents

0

20

40

60

80

100

120





acid


DBP

TCAA

(μg/L)

Figure A-15. TCAA

Day 0 Day 5

0

20

40

60

80

100

120





acid


DBP

BCAA

(μg/L)

Figure A-16. BCAA

Day 0 Day 5

Chris Keung A-10


Figure A- 17: DBAA concentration at day 0 and day 5 after the addition of various quenching agents

Figure A- 18: BDCAA concentration at day 0 and day 5 after the addition of various quenching agents

0

20

40

60

80

100

120





acid


DBP

DBAA

(μg/L)

Figure A-17. DBAA

Day 0 Day 5

0

20

40

60

80

100

120





acid


DBP

BDCA

A (μg/L)

Figure A-18. BDCAA

Day 0 Day 5

Chris Keung A-11


Figure A- 19: CDBAA concentration at day 0 and day 5 after the addition of various quenching agents

Figure A- 20: TBAA concentration at day 0 and day 5 after the addition of various quenching agents

0

20

40

60

80

100

120





acid


DBP

CDBA

A (μg/L)

Figure A-19. CDBAA

Day 0 Day 5

0

20

40

60

80

100

120





acid


DBP

TBAA

(μg/L)

Figure A-20. TBAA

Day 0 Day 5

Chris Keung B-1


B. EXPERIMENTAL PROTOCOLS. CALIBRATION AND QA/QC

Chris Keung B-2


B.1 THM/HAN/HK/CP PROTOCOL

Table B- 1: THM/HAN/HK/CP instrument conditions

Parameter Description Injector Temperature 200°C Detector Temperature 300°C

Temperature Program 40°C for 4.0 min 4°C/min temperature ramp to 95°C 60°C/min temperature ramp to 200°C

Carrier Gas Helium Make-up Gas P5 Argon (5% Methane) Flow Rate 1.2 mL/min at 35°C

Table B- 2: THM/HAN/HK/CP reagents

Reagent Source Milli-Q® water Prepared in the laboratory Trihalomethane (THM) concentrated stock for calibration

Supleco, 2000 μg/mL in methanol (48140-U)

Haloacetonitriles (HAN) concentrated stock for calibration Supleco, 2000 μg/mL in methanol (48140-U)

1,2- dibromopropane concentrated stock Supleco, 100 mg/L in Methyl-tert-butyl-ether Sodium sulphate [Na2SO4] Sigma Aldrich, ACS Grade Methyl-tert -butyl-ether (MTBE) Sigma Aldrich, >99.8%

Table B- 3: THM/HAN/HK/CP method outline

Sample Collection: Collect samples in 250 mL amber bottles quenched with either 0.01g sodium thiosulfate when analyzing water with a chlorine residual or 0.5 mL of catalase (1000mg/L) when analyzing water with a hydrogen peroxide residual. Store samples in the dark at 4°C for up to 7 days. To begin preparing samples, remove from refrigerator and bring to room temperature. Blanks: Transfer 25 mL of Milli-Q® water into 40 mL vials and process alongside samples. Standard Solution (THMs): Prepare calibration standards by adding the appropriate amount of 2000 μg/mL THM stock to get standard concentrations of (0, 5, 8, 10, 20, 40, 60 and 80 μg/L) ** Wipe the syringe tip with a Kimwipe before measuring out the THM stock and before adding

Chris Keung B-3


stock to solution. Check Standards (THMs - 40 μg/L): Add 50 μL of calibration solution to 25 mL of Milli-Q® water in a 40 mL vial and process alongside samples. Include blanks and check standards every 10 samples. Standard Solution (HAN/HK/CP): Prepare calibration standards by adding the appropriate amount of 2000 μg/mL HAN stock to get standard concentrations of (0, 2, 4, 8, 12, 16, 32, and 64 μg/L) ** Wipe the syringe tip with a Kimwipe before measuring out the THM stock and before adding stock to solution. Check Standards (HAN/HK/CP - 10 μg/L): Add 12.5 μL of calibration solution to 25 mL of Milli-Q® water in a 40 mL vial and process alongside samples. Include blanks and check standards every 10 samples. Extraction: Transfer 25 ml of each sample vial into a clean 40 mL vial. Add 20 μL of the 1,2-dibromopropane solution. Add 2 scoops of sodium sulphate (Na2SO4) in order to increase extraction efficiency. Add 4 mL of MTBE extraction solvent and cap with Teflon®-lined silicon septum and screw cap. Shake sample vial vigorously for approx. 30 seconds and place on counter on its side. Repeat and complete for all samples, blanks and standards before proceeding. Shake the samples by hand for 2 minutes. Let samples stand for 45-60 minutes for phase separation. Extract 2 mL from the organic layer using a Pasteur pipette and place in a 1.8 mL GC vial filled with 2 small scoops of Na2SO4 (there should not be any water in the vial). Use a clean pipette for each sample. Fill the vial to the top and cap immediately, ensuring that there is no headspace. To ensure only the MTBE layer was taken, freeze the samples and examine the vials after more than two hours to see if there is only one phase visible. If not analyzing immediately, store the samples in the freezer (-11°C) for up to 21 days. Analyze using a GC-ECD.

Table B- 4: THM method detection limits

Analyte Standard Deviation (μg/L) MDL (μg/L) TCM 0.27 0.81

BDCM 0.22 0.66 DBCM 0.27 0.81 TBM 0.33 0.99

Chris Keung B-4


Table B- 5: HAN/HK/CP method detection limits

Analyte Standard Deviation (μg/L) MDL (μg/L) TCAN 0.44 1.32 DCAN 0.29 0.87 DCP 0.25 0.75 CP 0.20 0.60

BCAN 0.23 0.69 DBAN 0.24 0.72

B.2 HAA PROTOCOL

Table B- 6: HAA instrument conditions

Parameter Description Injector Temperature 200°C Detector Temperature 300°C

Temperature Program

35°C for 10.0 min 2.5°C/min temperature ramp to 65°C 10°C/min temperature ramp to 85°C 20°C/min temperature ramp to 205°C, hold for 7 min

Carrier Gas Helium Make-up Gas P5 Argon (5% Methane) Flow Rate 1.2 mL/min at 35°C

Table B- 7: HAA reagents

Reagent Source N-methyl-N-nitroso-p-toluene sulfonamide (Diazald) [CH3C6H4SO2N(CH3)NO]

Sigma Aldrich, 99+%

Sodium hydroxide [NaOH] BDH, 85.0+%, ACS Grade Sulphuric acid [H2SO4] Anachemia, 98+%

Haloacetic acids concentrated stock EPA 552.2 Acids Calibration Mix in MTBE

2,3,5,6 tetrafluorobenzoic acid (TFBA) concentrated stock Supleco, 2000 mg/L in MTBE Sodium sulphate [Na2SO4] Sigma Aldrich, ACS Grade Methyl-tert -butyl-ether (MTBE Sigma Aldrich, >99.8%

Chris Keung B-5


Table B- 8: HAA method outline

Sample Collection: Collect samples in 250 mL amber bottles quenched with either 0.01g sodium thiosulfate when analyzing water with a chlorine residual or 0.5 mL of catalase (1000mg/L) when analyzing water with a hydrogen peroxide residual. Store samples in the dark at 4°C for up to 7 days. To begin preparing samples, remove from refrigerator and bring to room temperature. Blanks: Transfer 25 mL of Milli-Q® water into 40 mL vials and process alongside samples. Standard Solution: Prepare calibration standards by adding the appropriate amount of 2000 μg/mL HAA stock to get standard concentrations of (0, 2, 4, 6, 10, 20, 30, and 40 μg/L) ** Wipe the syringe tip with a Kimwipe before measuring out the THM stock and before adding stock to solution. Check Standards (10 μg/L): Add 12.5 μL of calibration solution to 25 mL of Milli-Q® water in a 40 mL vial and process alongside samples. Include blanks and check standards every 10 samples. Diazomethane Generation: Set up the generation apparatus as shown in Figure 6521:2 in Standard Methods (APHA, 2012). Extraction: Transfer 25 mL of each sample into a clean 40 mL vials. Using a 25 μL syringe, add 20 μL of the 2,3,5,6-TFBA solution. Add 2.8 mL of sulphuric acid (H2SO4) to reduce the pH of the sample. Add 2 two scoop of sodium sulphate (Na2SO4) in order to increase extraction efficiency. Add 5 mL of MTBE extraction solvent and cap with Teflon®-lined silicon septa and screw cap. Shake sample vial vigorously for approx. 30 seconds and place on counter on its side. Complete this procedure for all samples, blanks and standards before proceeding. Shake the samples by hand for 5 minutes. Let samples stand for 45-60 minutes for phase separation. Transfer exactly 1.5 mL of the MTBE layer to GC vials filled with 1 small scoop of Na2SO4 to ensure that there is no water in the vial. Use a clean pipette for each sample. To ensure only the MTBE layer was taken, freeze the samples and examine the vials after more than two hours to see if there is only one phase visible. Add 150 μL of diazomethane to the GC vial (submerge tip before injection) and cap immediately. If not analyzing immediately, store the samples in the freezer (-11°C) for up to 21 days. Analyze using a GC-ECD.

Chris Keung B-6


Table B- 9: HAA method detection limits

Analyte Standard Deviation (μg/L) MDL (μg/L) MCAA 0.28 0.84 MBAA 0.30 0.90 DCAA 0.37 1.11 TCAA 0.30 0.90 BCAA 0.26 0.78 DBAA 0.33 0.99

BDCAA 0.58 1.74 DBCAA 0.33 0.99 TBAA 0.34 1.02

B.3 AOX PROTOCOL

Table B- 10: AOX instrument conditions

Parameter Description Combustion cell temperature 1000°C Combustion gas Oxygen Carrier gas combustion cell Argon Carrier gas to titration cell Oxygen Cell scrubber Concentrated sulfuric acid 98%

Table B- 11: AOX reagents

Reagent Source

Nitrate stock solution, 1% 14 mL of nitrite stock 67% in 1 L of MQ mixed with 14 g of Sodium Nitrate

Nitrate wash solution 50 mL of Nitrate stock solution in 1 L of MQ Acetic Acid Sigma Aldrich, 75% Sulphuric acid [H2SO4] Anachemia, 98+% Standard Solution (4-Chlorophenol) Trace Elements, 200 mg/L Cl Sodium Chloride Trace Elements, 2 mmol/L

Table B- 12: AOX method outline

Sample Collection: Collect samples in 250 mL amber bottles quenched with either 0.01g sodium thiosulfate when analyzing water with a chlorine residual or 0.5 mL of catalase (1000mg/L) when analyzing water with a hydrogen peroxide residual. Store samples in the dark

Chris Keung B-7


at 4°C for up to 7 days. To begin preparing samples, remove from refrigerator and bring to room temperature. Sample Extraction: Prepare the extraction column set by connecting two activated carbon columns with the connector. Make sure to puncture the column cap to allow sample pass through. Assemble the column set onto the Xprep sample filtration unit. Shake and homogenize samples, pour 100 mL into the extraction syringes. Check the wash solution of sodium nitrate/nitric acid. Start the extraction. It takes about 50 minutes for the whole extraction depending on the flow rate (1-2 mL/min). Transferring of activated carbon to the test cups: At the end of sample extraction, take off the column sets from the Xprep. Using the ejecting tool to transfer the activated carbon to clean test cups and place on the sample auto sequencer and run them immediately

B.4 DOC PROTOCOL

Table B- 13: DOC instrument conditions

Parameter Description Acid Volume 500 µL of 5% phosphoric acid Oxidant Volume 1000 µL of 10% sodium persulphate Sample Volume 2 mL Rinses per sample 1 Volume per rinse 15 mL Replicates per sample 3 Reaction time (min:sec) TIC 01:30; TOC 02:00 Detection time (min:sec) TIC 00:00; TOC 03:00 Purge gas Nitrogen Loop Size 10 mL

Table B- 14: DOC reagents

Parameter Description Milli-Q® water Prepared in the laboratory Sulphuric acid, H2SO4 VWR International, 98+% Sodium persulphate, Na2(SO4) Sigma Aldrich, 98+%, anhydrous Potassium hydrogen phthalate (KHP), C8H5KO4 Sigma Aldrich, 98+% Phosphoric acid, H3PO4 Caledon, >85% Nitrogen gas, N2 Praxair, Ultra high purity (UHP)

Chris Keung B-8


Table B- 15: DOC method outline

Blanks: Use 40 mL of Milli-Q® water. Stock Solution: Mix 2.13g potassium hydrogen phthalate in 1 L of Milli-Q® water and acidify at pH<2 with H2SO4. Store in fridge at 4°C. Check Standards (2.5 mg/L): Add 250 µL of stock solution to 100 mL of Milli-Q® water. Analysis: Follow SOP for TOC analyzer

B.5 ATP PROTOCOL

Table B- 16: ATP method outline

Calibration: To calibrate the Luminometer, add two drops (100 μL) of enzyme reagent (Luminase) and two drops (100 μL) of ATP standard (Ultracheck 1) in a 12×55 mm test tube. Measure the relative light units (RLU) using a Luminometer (RLUstandard). Ensure that RLUATP1 > 5000. If not, rehydrate a new bottle of Luminase for maximum sensitivity.

Sample Filtration: Slowly push entire sample volume (100mL) through Luminultra filter and into waste beaker at a rate of approximately 3-5 mL per second.

Sample Extraction: Reattach filter and add 1 mL of UltraLyse7 to the barrel and slowly push the UltraLyse7 through the filter to dryness, collecting in a new 9mL UltraLute tube. Cap the tube and shake gently.

Assay: Using a micropipette, transfer 100 μL from the dilution tube to a new 12×55 mm test tube and add 100 μL of Luminase. Mix gently and immediately place in the Luminometer to measure the RLU (RLUsample). The ATP concentration is determined as follows:

• Cellular ATP (cATP) (pg ATP/mL) : 𝑐𝑐𝑐𝑐 = 𝑅𝑅𝑅𝑐𝑐𝑐𝑃𝑅𝑅𝑅𝑐𝑐𝑃1

𝑥 10,000 (𝑝𝑝 𝐴𝐶𝐴)𝑉𝑠𝑠𝑠𝑠𝑠𝑠 (𝑚𝑅)

• Microbial Equivalents (ME/mL) : 𝑐𝑐𝑐𝑐 �𝑝𝑝 𝐴𝐶𝐴𝑚𝑅�𝑥 1𝑀𝑀

0.001 𝑝𝑝 𝐴𝐶𝐴

Chris Keung B-9


B.6 HPC PROTOCOL

Table B- 17: HPC method outline

Method: Heterotrophic bacteria are determined by the membrane filtration technique and reported as CFU/1mL (colony forming units per 1mL). The sample is filtered by vacuum through a 47mm diameter, 0.45um pore size cellulose-ester gridded membrane filter. The bacterial cells trapped on the surface of the filter form colonies when placed on mHPC medium or Standard Plate Count Agar (SPCA) and are incubated inverted at 35.0± 0.5°C for 48±3 h. The filters are examined by eye and/or a microscope. The heterotrophic bacteria count includes all colonies that form on the medium. Solution sample types include aqueous samples such as drinking water, ground water, surface water, raw sewage, final effluents. The target colonies are enumerated and the final result is reported as CFU/1mL. The CFU/1mL count is calculated using the formula:

CFU/1mL = Target Colonies per Filter * 1 Sample Volume Filtered (mL)

Solid sample types include soil, sludge or biosolid, sediment from lakes, rivers, bays and sewer build-up. A 1.0g (wet weight) sample is transferred to a 99mL phosphate buffer dilution blank bottle. The bottle is shaken to separate (elute) the bacterial cells from the soil or sediment. The target colonies are enumerated and the final result is reported as CFU/1g. CFU/1g wet weight = Target Colonies per Filter * 100

Sample Volume Filtered (mL) Where 100 = 1.0g sample in 99mL phosphate buffer dilution blank bottle is equal to a 100 times dilution

Report samples as CFU/1g in LIMS (laboratory information management system). If CFU/1g dried weight is required, calculate as follows: CFU/1 gm dried weight = Colonies counted

(dilution) x (% dry solids)

Where % dry solids is calculated as follows: % dry solids = TS ÷10000 Specific gravity of the sample

Chris Keung B-10


Notes: Bacteria are viable organisms. Therefore, their environment affects their survival.

1. A short time lapse between collection and analysis is critical for the detection and enumeration of heterotrophic bacteria.

2. Temperature during sample transport can affect the population of the target bacteria. To minimize interference, samples are transported on ice (but not frozen) and analyzed as soon as possible.

3. Temperature during incubation can affect the growth of heterotrophic bacteria. Temperatures other than those specified in this method can bias the count.

4. Some sample matrices can kill the target bacteria. High levels of chlorine, if not preserved with sodium thiosulphate, will decrease the population of heterotrophic bacteria. Sample bottles are received from the manufacturer pre-treated with sodium thiosulphate at a concentration sufficient to neutralize 5mg/L of residual chlorine.

5. Particulate matter, when filtered, can form a physical barrier between the bacteria on the filter and the nutrients in the medium. The subsequent decrease in nutrient uptake will lower the bacterial count.

6. Samples that contain colloidal matter or large numbers of algae can cause decreases in bacterial populations.

Method taken from SGS Environmental Services Method (SGS, 2015)

Chris Keung B-11


B.7 METALS PROTOCOL

Table B- 18: Metals method outline

Method: Multi-element determination of metals and trace elements in aqueous samples and filters by ICP-MS. Dissolved metals are determined on aqueous samples, by passing the sample through a 0.45 um pore size filter. The sample is then immediately acidified using concentrated HNO3. Total recoverable elements are determined on aqueous samples, which have been preserved with HNO3, by digesting the sample with HNO3. This sample is not filtered. The digestion process reduces interferences by organic matter and converts metals associated with particulates to the free metal form. Samples prepared by these methods are analyzed by ICP-MS. The samples are analyzed as prepared and/or are diluted within the linear range of the instrument calibration. The samples are analyzed against 2% HNO3 standardization materials. The samples and quality control materials are aspirated into the plasma via nebulization, where they are desolvated, vaporized, dissociated and ionized. The ions are then transported through the interface of the instrument (sampler and skimmer cones), where the ions are focused and mass filtered by the quadruple. The mass-separated ions are then detected. The measurement of the intensity signal is converted to concentration units via a host computer.

Notes:

Highly alkaline samples will require more acid to lower the pH to <2.

In the case of dissolved samples, samples containing high amounts of solids may be difficult to filter through a 0.45um filter paper. Such samples may be centrifuged to reduce loading on the filter paper.

An aqua regia or strong acid digest may be considered for more complex samples such as industrial effluents, which may resist digestion in the case of the total recoverable metals preparation procedure. Method taken from SGS Environmental Services Method (SGS, 2014)

Chris Keung B-12


B.8 GENOTOXICITY – SOS CHOROMOTEST ASSAY

Table B- 19: Genotoxicity SOS Chromotest methods

Principle: The SOS ChromoTest™ is a test developed for the detection of chemicals or mixtures that can damage cellular DNA. The colorimetric endpoint allows for the quantification of the genotoxic response to the chemical or mixture can be used to calculate the relative strength of genotoxic compounds. The test employs a non-pathogenic strain of E. coli in (PQ37) with a plasmid containing the SOS repair promoter gene linked to -galactosidase gene. The production of β-galactosidase is then measured by the enzyme’s reaction with a blue chromogen, giving off a blue colour. Once the assay is complete, proceed to SOP for Microplate Instruction for SOS Chromotest™ for reading the OD of the samples by a plate reader. Reagents: LB Growth Media for Bacteria (vial A) Lyophilized E.coli PQ37 bacteria (vial B) Saline Solution with 10% DMSO (vial C) Positive control standard – 4-NQO (vial D) Re-hydration of bacteria (evening prior to test): As late in the day as possible, transfer aseptically one full bottle of growth media (vial A) into one bottle of dried bacteria (vial B). Invert and mix well. Transfer 100 uL of mixture into a new vial of growth media (vial A) and incubate overnight at 37°C Bacteria dilution (morning of test): Remove bacteria from incubator and read absorbance at OD 595, using aseptic techniques. Dilute overnight bacterial culture with growth media (vial A) to obtain a 0.05 reading. Keep mixture on bench until ready for use. 10mL is needed per plate. Keep 200uL of sterile growth media for blanks. Serial dilutions of sample: Setup serial dilutions for each sample. This is performed in microtubes. For each sample label the tubes 1-6, which refers to the column number on the plate. Set column aside from 2-6. If performing triplicates, add 28uL of 10% DMSO saline (vial C) and 7uL of sample to tubes with column 1. Mix sample by pipetting up and down, vortex and spin down. In columns 2-6, add 17.5uL of 10% DMSO saline (vial C). Pipet 17.5uL from column 1 to column 2, vortex and spin. Then add 17.5 uL from tube labeled 2 to 3, vortex and spin. Repeat with 3 to 6 sequentially. Microplate Assay: Split the microplate in half in order to have 6 rows for each sample (columns A-H*1-6 and A-H*

Chris Keung B-13


7-12. In total, can run 16 separate rows. Save one row for the positive control and one row for the negative control per plate, and triplicate rows for each sample. Add 5 uL of the sample diluent (saline with 10% DMSO) to rows 2-6 and 8-12. Only the positive control will have 10 uL. For samples, add 5uL of each sample to first row (ex. B1), then 5 uL of sample to B2 (which contains 5uL of sample diluent). Mix well. Remove 5uL from B2 and place in B3. Mix well. Repeat serial dilution to Row 6. Discard 5 uL to ensure all rows have the same volume. In the negative control row, add 5uL of 10% DMSO saline into columns H1-4, and for blanks in H5-6, only add the growth media. In the positive control row, repeat the serial dilution in plate. Add 10uL of 10% DMSO saline (vial C) into columns 2-6. Add 10uL of 4-NQO (vial D) into column 1 and column 2. Pipet up and down to mix in column 2, then transfer 10mL of column 2 into column 3. Repeat the process and discard 10mL from column 6. Using multipipettor, add 100uL of bacteria into all wells except blanks. Incubate plates at 37°C for 2 hours. Read the OD using a plate reader. Detailed protocol is presented in SOP for Microplate Instruction for SOS Chromotest™

Chris Keung B-14


Table B- 20: Solid phase extraction (SPE) method

Reagents: - HLB Oasis 12 cc cartridges. (CAT186000116) - Sulfuric Acid - Methanol - Acetone - Mili-Q water Extraction and sample preparation in the fume hood: 2L water samples in amber bottles, acidified to pH 2 with 40 drops of concentrated H2SO4 and kept in fridge at 4°C until time of extraction. Solid phase extraction (SPE) is performed on the Visiprep vacuum manifold. Condition the SPE columns under gravity (collect acetone and methanol in spare falcon tubes for proper disposal) in the following order: 10mL acetone – preconditioning; 10mL methanol – conditioning; 10mL Milli-Q® water – aqueous buffer. Ensure that the cartridges are not exposed to air after the acetone step (Important! Maintain ~1mm of solvent/aqueous layer on top of SPE media at all times). Connect SPE sampling tube from the sample bottle to HLB column, located on the Visiprep vacuum manifold. Loading of 2L samples, under light vacuum at ~ 10 mL/min (to maintain a linear velocity of 0.17 cm/s). Once samples are loaded, carefully wipe in interior of the HLB cartridge with a Kimwipe, being sure not to disturb the beads. The HLB cartridges are then dried under vacuum for 1 hour or until colour change is noticed. Elution by gravity with two aliquots of 4.5 mL of acetone, collected in falcon tubes. Evaporate acetone under light flow of nitrogen, until ~ 1 mL remaining. Transfer the 1 mL acetone samples into respective GC vials, then rinse the walls of falcon tubes with 0.2 mL fresh acetone and add to GC vial. Evaporate GC vial samples to near completion under nitrogen, when ~100uL of sample remain in vial. Add 50uL of DMSO and mix sample thoroughly. Continue evaporating the acetone under nitrogen until 20uL DMSO are left. Add 10uL of DMSO and mix samples thoroughly. Transfer the 30uL of sample to glass inserts using designated syringe, place insert into GC vial. Store samples in freezer at -20°C.

Chris Keung B-15


B.9 THM CALIBRATION CURVES AND QA/QC CHARTS

Figure B- 1: TCM calibration curve

Figure B- 2: Quality control chart for TCM analysis

y = 185.37x - 30.945 R² = 0.9821

0102030405060708090

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

Con

cent

ratio

n (µ

g/L

)

TCM peak area / 1,2 DBP peak area

TCM (calibration)

30

32

34

36

38

40

42

44

03-Sep 23-Oct 12-Dec 31-Jan 22-Mar 11-May 30-Jun

TC

M (µ

géL

)

Chris Keung B-16


Figure B- 3: TCM calibration curve

Figure B- 4: Quality control chart for BDCM analysis

y = 21.063x - 1.493 R² = 0.9959

0102030405060708090

0 1 2 3 4

Con

cent

ratio

n (µ

g/L

)

BDCM peak area / 1,2 DBP peak area

BDCM (calibration)

34

36

38

40

42

44

46

48


BD

CM

(µgé

L)

Chris Keung B-17


Figure B- 5: DBCM calibration curve

Figure B- 6: Quality control chart for DBCM analysis

y = 24.134x + 0.3255 R² = 0.9971

0102030405060708090

0 0.5 1 1.5 2 2.5 3 3.5

Con

cent

ratio

n (µ

g/L

)

DBCM peak area / 1,2 DBP peak area

DBCM (calibration)

34

36

38

40

42

44

46


DB

CM

(µgé

L)

Chris Keung B-18


Figure B- 7: TBM calibration curve

Figure B- 8: Quality control chart for TBM analysis

y = 57.732x - 1.9486 R² = 0.995

0102030405060708090

0 0.5 1 1.5

Con

cent

ratio

n (µ

g/L

)

TBM peak area / 1,2 DBP peak area

TBM (calibration)

32

34

36

38

40

42

44


TB

M (µ

géL

)

Chris Keung B-19


B.10 HAA CALIBRATION CURVES AND QA/QC CHARTS

Figure B- 9: MCAA calibration curve

Figure B- 10: Quality control chart for MCAA analysis

y = 1075.3x + 2.0596 R² = 0.9379

05

1015202530354045

0 0.01 0.02 0.03 0.04

Con

cent

ratio

n (µ

g/L

)

MCAA peak area / TFBA peak area

MCAA (calibration)

10.0

10.5

11.0

11.5

12.0

12.5

13.0


MC

AA

(µgé

L)

Chris Keung B-20


Figure B- 11: DCAA calibration curve

Figure B- 12: Quality control chart for DCAA analysis

y = 96.876x + 0.0462 R² = 0.9916

05

1015202530354045

0 0.1 0.2 0.3 0.4 0.5

Con

cent

ratio

n (µ

g/L

)

DCAA peak area / TFBA peak area

DCAA (calibration)

9.09.5

10.010.511.011.512.012.513.013.5


DC

AA

(µgé

L)

Chris Keung B-21


Figure B- 13: TCAA calibration curve

Figure B- 14: Quality control chart for TCAA analysis

y = 42.797x + 0.1506 R² = 0.9921

05

1015202530354045

0 0.2 0.4 0.6 0.8 1 1.2

Con

cent

ratio

n (µ

g/L

)

TCAA peak area / TFBA peak area

TCAA (calibration)

9.0

10.0

11.0

12.0

13.0

14.0

15.0


TC

AA

(µgé

L)

Chris Keung B-22


Figure B- 15: BCAA calibration curve

Figure B- 16: Quality control chart for BCAA analysis

y = 44.529x - 0.0633 R² = 0.9909

05

1015202530354045

0 0.2 0.4 0.6 0.8 1

Con

cent

ratio

n (µ

g/L

)

BCAA peak area / TFBA peak area

BCAA (calibration)

9.09.5

10.010.511.011.512.012.513.013.5


BC

AA

(µgé

L)

Chris Keung B-23


Figure B- 17: DBAA calibration curve

Figure B- 18: Quality control chart for DBAA analysis

y = 44.587x + 0.115 R² = 0.9925

05

1015202530354045

0 0.2 0.4 0.6 0.8 1

Con

cent

ratio

n (µ

g/L

)

DBAA peak area / TFBA peak area

DBAA (calibration)

9.0

9.5

10.0

10.5

11.0

11.5

12.0


DB

AA

(µgé

L)

Chris Keung B-24


Figure B- 19: BDCAA calibration curve

Figure B- 20: Quality control chart for BDCAA analysis

y = 41.41x + 0.8365 R² = 0.9851

05

1015202530354045

0 0.2 0.4 0.6 0.8 1 1.2

Con

cent

ratio

n (µ

g/L

)

BDCAA peak area / TFBA peak area

BDCAA (calibration)

6.0

8.0

10.0

12.0

14.0

16.0

18.0


BD

CA

A (µ

géL

)

Chris Keung B-25


Figure B- 21: CDBAA calibration curve

Figure B- 22: Quality control chart for CDBAA analysis

y = 140.15x - 0.3497 R² = 0.9797

05

1015202530354045

0 0.05 0.1 0.15 0.2 0.25 0.3

Con

cent

ratio

n (µ

g/L

)

CDBAA peak area / TFBA peak area

CDBAA (calibration)

8.0

8.5

9.0

9.5

10.0

10.5

11.0


CD

BA

A (µ

géL

)

Chris Keung B-26


B.11 HAN/HK/CP CALIBRATION CURVES AND QA/QC CHARTS

Figure B- 23: TCAN calibration curve

Figure B- 24: Quality control chart for TCAN analysis

y = 11.233x + 1.8539 R² = 0.9676

0

5

10

15

20

25

30

35

0 0.5 1 1.5 2 2.5 3

Con

cent

ratio

n (µ

g/L

)

TCAN peak area / 1,2 DBP peak area

TCAN (calibration)

6789

1011121314


TC

AN

(µgé

L)

Chris Keung B-27


Figure B- 25: DCAN calibration curve

Figure B- 26: Quality control chart for DCAN analysis

y = 7.6309x - 1.2417 R² = 0.9912

0

5

10

15

20

25

30

35

0 1 2 3 4 5

Con

cent

ratio

n (µ

g/L

)

DCAN peak area / 1,2 DBP peak area

DCAN (calibration)

6789

1011121314


DC

AN

(µgé

L)

Chris Keung B-28


Figure B- 27: DCP calibration curve

Figure B- 28: Quality control chart for DCP analysis

y = 25.482x + 1.4023 R² = 0.9867

0

5

10

15

20

25

30

35

0 0.2 0.4 0.6 0.8 1 1.2 1.4

Con

cent

ratio

n (µ

g/L

)

DCP peak area / 1,2 DBP peak area

DCP (calibration)

6789

101112131415


DC

P (µ

géL

)

Chris Keung B-29


Figure B- 29: CP calibration curve

Figure B- 30: Quality control chart for CP analysis

y = 16.608x - 0.8358 R² = 0.9944

0

5

10

15

20

25

30

35

0 0.5 1 1.5 2 2.5

Con

cent

ratio

n (µ

g/L

)

CP peak area / 1,2 DBP peak area

CP (calibration)

6789

10111213141516


CP

(µgé

L)

Chris Keung B-30


Figure B- 31: BCAN calibration curve

Figure B- 32: Quality control chart for BCAN analysis

y = 13.808x - 1.2249 R² = 0.9916

0

5

10

15

20

25

30

35

0 0.5 1 1.5 2 2.5

Con

cent

ratio

n (µ

g/L

)

BCAN peak area / 1,2 DBP peak area

BCAN (calibration)

6789

101112131415


BC

AN

(µgé

L)

Chris Keung B-31


Figure B- 33: DBAN calibration curve

Figure B- 34: Quality control chart for DBAN analysis

y = 19.141x - 1.0444 R² = 0.992

0

5

10

15

20

25

30

35

0 0.5 1 1.5 2

Con

cent

ratio

n (µ

g/L

)

DBAN peak area / 1,2 DBP peak area

DBAN (calibration)

6

8

10

12

14

16

18


DB

AN

(µgé

L)

Chris Keung B-32


B.12 DOC CALIBRATION CURVES AND QA/QC CHARTS

Figure B- 35: DOC calibration curve

Figure B- 36: Quality control chart for DOC analysis

y = 0.0003x - 1.6516 R² = 1

0

2

4

6

8

10

12

0 10000 20000 30000 40000 50000

Con

cent

ratio

n (m

g/L

)

Area Counts

DOC Calibration Curve

2.02.12.22.32.42.52.62.72.8


DO

C (m

g/L

)

Chris Keung C-1


C. RAW DATA

Chris Keung C-2


Table C- 1: Killalloe sampling campaign summary

Parameter Unit

Site 1: Raw Water Site 2: Post Greensand Site 3: Post HSP Addition Site 4: Plant Effluent

14-0

9-09

14-1

0-28

15-0

2-03

15-0

5-28

14-0

9-09

14-1

0-28

15-0

2-03

15-0

5-28

14-0

9-09

14-1

0-28

15-0

2-03

15-0

5-28

14-0

9-09

14-1

0-28

15-0

2-03

15-0

5-28

pH 8.1 7.9 7.8 8.1 8 7.8 8.2 8 7.8 8.1 8.1 7.8 Temperature °C 8.2 8.3 8.6 13 8.2 8.2 8.4 12 8.2 8 8.3 12 8.1 8 8.3 13

Free Chlorine Residual mg/L 0.77 0.89 1.05 1.24 Peroxide Residual mg/L 6.9 7.5 8 8.2 7.4 7.1 7.6 8.1

DOC mg/L 4.6 4.1 4.1 4.1 4.4 3.8 4.0 4.0 4.4 4.0 4.1 4.0 4.0 3.7 3.8 3.9 UV254 Abs @ 254nm 0.10 0.10 0.10 0.10 0.07 0.07 0.09 0.08 0.08 0.08 0.08 0.08 0.07 0.08 0.08 0.08

ATP cATP (pg/mL) 3.4 2.6 2.3 2.6 0.0 0.1 0.1 0.2 0.0 0.1 0.1 0.2 0.1 0.3 0.7 0.3 ME/mL 3407 2555 2328 2611 26 99 85 157 13 51 88 209 85 293 714 313

Heterotrophic Plate Count (HPC) cfu/1mL 1 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0

Metals

Silver µg/L 0.003 0.011 <0.002 0.02 0.021 0.051 0.023 0.034 5.12 5.22 5.32 5.6 4.22 4.51 4.71 4.85 Copper µg/L 2 1 1 1 2 2 1 1 2 7 5 2 185 158 137 107

Iron µg/L 120 124 114 111 6 8 <7 <7 4 <7 <7 <7 8 8 7 <7 Manganese µg/L 172 176 174 161 1 1 1 0 1 1 1 0 2 2 3 1

Lead µg/L 0.03 0.03 <0.01 <0.01 0.1 0.22 <0.01 <0.01 0.09 0.19 0.09 0.04 0.31 0.32 0.21 0.16 Magnesium mg/L 27 29 26 26 27 28 26 27 28 28 27 26 28 28 27 26

Calcium mg/L 81 77 81 90 82 76 79 92 82 80 80 88 83 78 81 91 Hardness mg/L as CaCO3 314 312 308 331 316 305 303 339 319 316 308 325 319 310 314 336

THMs

TCM - trichloromethane (chloroform) µg/L 5 8 2 5 21 10 22 10 15 7 16 16 21 11 26 BDCM - bromodichloromethane µg/L 8 4 4 6 7 5 5 9 10 9 9 DBCM - dibromochloromethane µg/L 1 3 3 3 3 3 2 3 4 4 4 4

TBM - tribromomethane (bromoform) µg/L 4 1 3 1 5 TTHM Total THMs µg/L 5 9 2 5 NA 36 17 28 20 28 14 24 30 40 24 38

HANs

TCAN - trichloroacetonitrile µg/L 2 2 2 2 DCAN - dichloroacetonitrile µg/L 1 1

BCAN - bromochloroacetonitrile µg/L 1 1 DBAN - dibromoacetonitrile µg/L

HKs DCP - 1, 1-dichloro-2-propanone µg/L TCP - 1, 1, 1-trichloropropanone µg/L

CP CP - chloropicrin µg/L

HAAs

MCAA - monochloroacetic acid µg/L 3 3 2 2 2 6 4 3 6 5 3 MBAA - monobromoacetic acid µg/L 2 4 2 1

DCAA - dichloroacetic acid µg/L 5 11 5 1 4 5 8 3 4 7 9 TCAA - trichloroacetic acid µg/L 9 7 4 1 6 5 5 1 4 5 6 DBAA - dibromoacetic acid µg/L 2 2 1 1 1 1 1

BCAA - bromochloroacetic acid µg/L 1 1 2 3 3 3 1 4 3 3 BDCAA - bromodichloroacetic acid µg/L 2 3 3 2 3 3 3 2 3 3 4 CDBAA - chlorodibromoacetic acid µg/L 1 2 3 2 2 3 1 4 2 2 2 2

TBAA - tribromoacetic acid µg/L 1 6 4 1 7 2 5

HAA5 HAA5 (MCAA,DCAA,TCAA,MBAA,DBAA) µg/L 3 0 3 2 NA 15 20 11 10 16 15 17 12 10 18 18

HAA9 Total HAAs µg/L 4 7 3 4 NA 23 24 18 17 32 22 26 19 24 26 27 AOX AOX - adsorbable organic halogens µg/L 21 23 16 39 N/A N/A 149 116 137 204 204 165 114 130 136 140

Genotoxicity Genotoxicity - SOS Assay IF at 16.5 eq. mL 2.21 2.28 1.21 2.19 N/A 1.97 2.24 1.99 1.2 1.57 1.79 1.67

Chris Keung C-3


Table C-1 Cont.: Killalloe sampling campaign summary

Parameter Unit

Site 5: Tourist Kiosk Site 6: Summer's Motors Site 7: Afelski's Shoes Site 8: McCarthy's Propane

14-0

9-09

14-1

0-28

15-0

2-03

15-0

5-28

14-0

9-09

14-1

0-28

15-0

2-03

15-0

5-28

14-0

9-09

14-1

0-28

15-0

2-03

15-0

5-28

14-0

9-09

14-1

0-28

15-0

2-03

15-0

5-28

pH 8.2 8.2 7.9 8.1 8 7.8 8.1 8 7.8 8.2 8.2 7.7 Temperature °C 14 15 8 14 16 14 9 16 15 15 7 14 17 15 8 16

Free Chlorine Residual mg/L Peroxide Residual mg/L 6.1 5.7 6.3 5.6 3.6 4.5 4.2 4.7 5 5.1 5.7 4.8 3.7 3 3.9 3.6

DOC mg/L 4.1 3.8 3.9 3.9 4.2 3.7 3.8 3.8 4.1 3.7 3.8 3.9 4.1 3.7 3.8 3.8 UV254 Abs @ 254nm 0.07 0.08 0.08 0.08 0.07 0.08 0.09 0.09 0.07 0.08 0.08 0.08 0.07 0.08 0.08 0.09

ATP cATP (pg/mL) 2.5 2.7 1.4 2.3 2.3 1.6 1.2 1.6 2.6 1.9 2.2 4.1 1.3 2.3 1.8 2.9

Cell Count (ME/mL) 2508 2749 1368 2246 2334 1605 1156 1619 2582 1884 2216 1932 1288 2330 1768 2037

Heterotrophic Plate Count (HPC) cfu/1mL 0 0 1 0 0 1 13 0 0 0 0 0 1 1 0 0

Metals

Silver µg/L 3.92 4.7 4.61 4.59 3.51 3.31 3.16 3.67 3.52 3.67 4.21 4.42 3.35 2.77 3.44 3.85 Copper µg/L 144 143 55 76 247 320 377 346 146 85 126 73 313 522 261 274

Iron µg/L 17 17 11 16 13 11 9 9 15 12 10 11 13 11 9 28 Manganese µg/L 3 2 3 1 3 2 3 1 3 2 3 1 3 3 3 3

Lead µg/L 0.54 0.52 0.31 0.4 0.44 0.45 0.29 0.38 0.65 0.39 0.31 0.42 0.48 0.51 0.2 0.43 Magnesium mg/L 27 27 27 27 27 27 26 27 27 28 27 26 27 28 26 26

Calcium mg/L 81 80 83 93 82 77 79 92 82 81 80 90 81 80 83 93 Hardness mg/L as CaCO3 313 311 317 341 316 303 305 340 316 317 308 333 315 314 313 341

THMs

TCM - trichloromethane (chloroform) µg/L 20 24 15 27 17 24 22 21 19 22 14 17 19 18 10 19 BDCM - bromodichloromethane µg/L 11 11 10 9 9 11 12 8 10 10 11 7 9 8 9 7 DBCM - dibromochloromethane µg/L 4 4 5 4 4 4 5 3 4 4 5 3 4 3 4 3

TBM - tribromomethane (bromoform) µg/L 1 6 1 5 1 5 1 4 TTHM Total THMs µg/L 36 45 30 40 31 44 39 33 34 41 30 28 33 33 23 29

HANs

TCAN - trichloroacetonitrile µg/L 2 2 2 2 DCAN - dichloroacetonitrile µg/L

BCAN - bromochloroacetonitrile µg/L DBAN - dibromoacetonitrile µg/L

HKs DCP - 1, 1-dichloro-2-propanone µg/L TCP - 1, 1, 1-trichloropropanone µg/L

CP CP - chloropicrin µg/L

HAAs

MCAA - monochloroacetic acid µg/L 7 4 2 7 2 3 7 5 3 5 5 2 MBAA - monobromoacetic acid µg/L 1 1 1 1 1 1 1 1

DCAA - dichloroacetic acid µg/L 3 5 7 8 1 3 6 7 2 3 6 7 1 2 5 7 TCAA - trichloroacetic acid µg/L 1 5 5 5 1 4 5 5 1 4 5 5 1 5 5 5 DBAA - dibromoacetic acid µg/L 1 1 1 1 1 1 1 1 1 1 1 1

BCAA - bromochloroacetic acid µg/L 1 3 3 3 2 3 3 1 2 3 2 3 3 3 BDCAA - bromodichloroacetic acid µg/L 2 3 3 4 2 2 3 3 2 2 3 3 2 2 3 3 CDBAA - chlorodibromoacetic acid µg/L 2 2 1 1 1 2 1 2 2 2 1 2 2 2

TBAA - tribromoacetic acid µg/L 2 6 2 5 2 5 2 5

HAA5 HAA5 (MCAA,DCAA,TCAA,MBAA,DBAA) µg/L 12 12 17 16 10 9 14 16 11 9 17 16 8 9 16 16

HAA9 Total HAAs µg/L 19 26 24 23 15 20 21 21 18 20 25 22 14 21 22 23 AOX AOX - adsorbable organic halogens µg/L 112 124 132 131 107 123 136 136 111 124 136 132 102 112 131 131

Genotoxicity Genotoxicity - SOS Assay IF at 16.5 eq. mL 1.08 1.37 1.22 1.05 1.27 1.22 1.36 1.29

Chris Keung C-4


Table C- 2: THM/HAN/CP raw data from Killaloe (September 9, 2014)

Date Site THMs/HANs/CP (μg/L)

TCM BDCM DBCM TBM TCAN DCAN BCAN DBAN DCP TCP CP TTHMs

9-Se

p-14

1a 7.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.2 1b 3.6 0.5 0.0 0.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 4.6

1 (mean) 5.4 0.3 0.0 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 5.9 2a 14.1 12.4 4.0 0.9 0.4 1.7 4.3 0.0 0.0 0.0 0.3 31.4 2b 16.4 13.4 4.4 2.1 0.4 1.8 4.8 0.0 0.0 0.0 0.4 36.3

2 (mean) 15.2 12.9 4.2 1.5 0.4 1.8 4.6 0.0 0.0 0.0 0.3 33.8 3a 10.4 6.1 3.0 0.5 0.0 0.7 0.2 0.0 0.0 0.0 0.0 20.0 3b 9.5 5.6 2.8 0.8 0.0 0.5 0.2 0.0 0.0 0.0 0.0 18.7

3 (mean) 10.0 5.8 2.9 0.6 0.0 0.6 0.2 0.0 0.0 0.0 0.0 19.3 4a 15.3 9.0 3.8 0.6 0.0 0.2 0.0 0.0 0.0 0.0 0.0 28.6 4b 17.3 8.1 4.1 1.3 0.0 0.2 0.0 0.0 0.0 0.0 0.0 30.9

4 (mean) 16.3 8.6 3.9 0.9 0.0 0.2 0.0 0.0 0.0 0.0 0.0 29.7 5a 19.3 10.5 4.1 0.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 34.5 5b 20.2 10.8 4.2 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 36.2

5 (mean) 19.7 10.6 4.1 0.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 35.4 6a 16.7 9.3 3.6 0.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 30.2 6b 17.2 8.1 3.7 1.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 30.1

6 (mean) 17.0 8.7 3.6 0.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 30.2 7a 17.7 9.9 3.8 0.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 32.1 7b 20.0 10.8 4.1 0.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 35.7

7 (mean) 18.9 10.3 3.9 0.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 33.9 8a 20.8 10.9 3.9 0.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 36.5 8b 17.7 8.1 3.7 0.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 30.5

8 (mean) 19.3 9.5 3.8 0.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 33.5

Chris Keung C-5


Table C- 3: THM/HAN/CP raw data from Killaloe (October 28, 2014)



28-O

ct-1

5

1a 7.3 0.5 0.7 0.0 0.4 0.0 0.0 0.0 0.0 0.0 0.0 8.6 1b 8.2 0.5 0.3 0.0 0.4 0.0 0.0 0.0 0.0 0.0 0.0 9.0

1 (mean) 7.8 0.5 0.5 0.0 0.4 0.0 0.0 0.0 0.0 0.0 0.0 8.8 2a 19.9 15.2 4.2 8.5 0.4 3.3 3.4 0.0 0.0 0.0 0.2 47.8 2b 18.4 14.3 3.9 8.1 0.4 3.0 3.1 0.0 0.0 0.0 0.2 44.7

2 (mean) 19.2 14.7 4.0 8.3 0.4 3.2 3.3 0.0 0.0 0.0 0.2 46.3 3a 13.9 7.0 3.1 3.4 0.4 1.3 0.6 0.0 0.0 0.0 0.1 27.3 3b 16.3 7.5 3.3 3.5 0.4 1.4 0.7 0.0 0.0 0.0 0.2 30.7

3 (mean) 15.1 7.3 3.2 3.4 0.4 1.3 0.6 0.0 0.0 0.0 0.2 29.0 4a 22.9 10.6 4.2 5.1 0.4 0.3 0.1 0.0 0.0 0.0 0.0 42.7 4b 19.4 9.3 3.7 4.5 0.4 0.2 0.1 0.0 0.0 0.0 0.0 37.0

4 (mean) 21.2 9.9 4.0 4.8 0.4 0.2 0.1 0.0 0.0 0.0 0.0 39.9 5a 25.3 11.9 4.8 6.8 0.4 0.0 0.5 0.0 0.0 0.0 0.0 48.7 5b 22.2 10.7 4.2 5.5 0.4 0.0 0.2 0.0 0.0 0.0 0.0 42.6

5 (mean) 23.7 11.3 4.5 6.2 0.4 0.0 0.4 0.0 0.0 0.0 0.0 45.6 6a 26.1 11.9 4.7 5.9 0.4 0.1 0.3 0.0 0.0 0.0 0.0 48.6 6b 21.7 9.9 4.0 4.8 0.4 0.0 0.1 0.0 0.0 0.0 0.0 40.3

6 (mean) 23.9 10.9 4.3 5.3 0.4 0.0 0.2 0.0 0.0 0.0 0.0 44.5 7a 20.3 9.2 3.6 4.5 0.4 0.0 0.1 0.0 0.0 0.0 0.0 37.7 7b 24.1 10.7 4.1 4.9 0.4 0.0 0.1 0.0 0.0 0.0 0.0 43.7

7 (mean) 22.2 10.0 3.8 4.7 0.4 0.0 0.1 0.0 0.0 0.0 0.0 40.7 8a 15.4 7.0 2.8 3.4 0.4 0.0 0.0 0.0 0.0 0.0 0.0 28.7 8b 20.4 8.9 3.5 5.4 0.4 0.0 0.3 0.0 0.0 0.0 0.0 38.3

8 (mean) 17.9 8.0 3.2 4.4 0.4 0.0 0.1 0.0 0.0 0.0 0.0 33.5

Chris Keung C-6


Table C- 4: THM/HAN/CP raw data from Killaloe (February 3, 2015)



3-Fe

b-15

1a 4.2 0.0 0.3 0.0 1.9 0.0 0.0 0.0 1.4 0.0 0.0 4.5 1b 0.0 0.0 0.3 0.0 1.9 0.0 0.0 0.0 1.4 0.0 0.0 0.3

1 (mean) 2.0 0.0 0.0 0.0 2.0 0.0 0.0 0.0 1.0 0.0 0.0 2.0 2a 8.8 4.7 3.1 0.0 1.9 0.1 0.0 0.0 1.4 0.0 0.0 16.6 2b 11.9 4.3 2.3 0.0 1.9 0.0 0.0 0.0 1.4 0.0 0.0 18.5

2 (mean) 10.0 4.0 3.0 0.0 2.0 0.0 0.0 0.0 1.0 0.0 0.0 17.0 3a 10.1 5.0 2.3 0.0 1.9 0.0 0.0 0.0 1.4 0.0 0.0 17.4 3b 4.7 4.8 2.1 0.0 1.9 0.0 0.0 0.0 1.4 0.0 0.0 11.6

3 (mean) 7.0 5.0 2.0 0.0 2.0 0.0 0.0 0.0 1.0 0.0 0.0 14.0 4a 13.5 10.3 4.3 0.0 1.9 0.0 0.0 0.0 1.4 0.0 0.0 28.1 4b 7.7 7.7 3.6 0.0 1.9 0.0 0.0 0.0 1.4 0.0 0.0 19.0

4 (mean) 11.0 9.0 4.0 0.0 2.0 0.0 0.0 0.0 1.0 0.0 0.0 24.0 5a 16.5 10.8 5.6 0.0 1.9 0.0 0.0 0.0 2.0 0.0 0.0 32.9 5b 13.6 8.5 3.8 0.0 1.9 0.0 0.0 0.0 1.4 0.0 0.0 25.9

5 (mean) 15.0 10.0 5.0 0.0 2.0 0.0 0.0 0.0 2.0 0.0 0.0 30.0 6a 22.5 13.0 5.3 0.0 1.9 0.0 0.0 0.0 1.4 0.0 0.0 40.8 6b 21.3 11.7 4.7 0.0 1.9 0.0 0.0 0.0 1.4 0.0 0.0 37.7

6 (mean) 22.0 12.0 5.0 0.0 2.0 0.0 0.0 0.0 1.0 0.0 0.0 39.0 7a 14.4 11.4 5.1 0.0 1.9 0.0 0.0 0.0 1.4 0.0 0.0 30.9 7b 13.5 10.4 4.5 0.0 1.9 0.0 0.0 0.0 1.4 0.0 0.0 28.4

7 (mean) 14.0 11.0 5.0 0.0 2.0 0.0 0.0 0.0 1.0 0.0 0.0 30.0 8a 14.3 10.2 4.0 0.0 1.9 0.0 0.0 0.0 1.4 0.0 0.0 28.5 8b 6.3 7.3 3.3 0.0 1.9 0.0 0.0 0.0 1.5 0.0 0.0 16.9

8 (mean) 10.0 9.0 4.0 0.0 2.0 0.0 0.0 0.0 1.0 0.0 0.0 23.0

Chris Keung C-7


Table C- 5: THM/HAN/CP raw data from Killaloe (May 28, 2015)



28-M

ay-1

5

1a 5.9 0.0 0.3 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 6.2 1b 4.1 0.0 0.3 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 4.5

1 (mean) 5.0 0.0 0.3 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 5.3 2a 20.6 4.2 2.5 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 27.3 2b 23.2 4.0 2.5 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 29.7

2 (mean) 21.9 4.1 2.5 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 28.5 3a 19.7 5.5 3.0 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 28.2 3b 13.0 4.7 2.7 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 20.3

3 (mean) 16.4 5.1 2.8 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 24.3 4a 37.3 10.4 4.3 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 51.9 4b 14.6 6.8 2.9 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 24.3

4 (mean) 25.9 8.6 3.6 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 38.1 5a 33.9 10.7 4.1 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 48.6 5b 19.5 7.9 3.3 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 30.7

5 (mean) 26.7 9.3 3.7 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 39.7 6a 18.9 7.8 3.2 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 29.9 6b 24.0 8.1 3.5 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 35.6

6 (mean) 21.4 8.0 3.4 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 32.8 7a 15.6 6.7 3.0 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 25.3 7b 19.2 7.8 3.3 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 30.3

7 (mean) 17.4 7.3 3.2 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 27.8 8a 20.3 7.4 3.3 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 31.0 8b 17.5 7.4 3.1 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 28.0

8 (mean) 18.9 7.4 3.2 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 29.5

Chris Keung C-8


Table C- 6: HAA raw data from Killaloe (September 9, 2014)

Date Site HAAs (μg/L)

MCAA MBAA DCAA TCAA BCAA DBAA BDCAA CDBAA TBAA HAA5 HAA9

9-Se

p-14

1A 0.0 0.0 0.0 0.0 0.0 0.0 0.3 0.0 0.8 0.0 1.1 1B 7.0 0.6 0.0 0.0 0.0 0.0 0.0 0.0 0.9 7.5 8.5

1 (mean) 3.5 0.3 0.0 0.0 0.0 0.0 0.2 0.0 0.9 3.8 4.8 2A 0.0 1.8 11.9 13.4 1.1 0.0 5.8 2.2 4.3 27.2 40.7 2B 6.3 3.3 10.0 15.1 1.8 1.6 6.3 3.0 3.6 36.3 51.1

2 (mean) 3.1 2.5 11.0 14.3 1.5 0.8 6.1 2.6 4.0 31.7 45.9 3A 5.5 2.3 1.3 1.2 1.4 0.4 1.9 1.6 1.4 10.6 17.0 3B 6.0 2.3 1.6 1.5 1.6 0.5 2.1 1.9 1.2 11.8 18.7

3 (mean) 5.7 2.3 1.4 1.3 1.5 0.4 2.0 1.7 1.3 11.2 17.8 4A 5.6 1.5 2.3 0.6 1.3 0.3 1.8 1.5 1.5 10.3 16.4 4B 7.0 1.7 2.7 0.9 1.5 0.4 2.0 1.6 1.6 12.6 19.3

4 (mean) 6.3 1.6 2.5 0.8 1.4 0.3 1.9 1.5 1.5 11.5 17.9 5A 6.7 1.0 2.7 1.2 1.4 0.1 1.9 1.5 1.8 11.7 18.3 5B 6.9 1.3 2.6 1.5 1.4 0.1 2.1 1.6 2.2 12.4 19.7

5 (mean) 6.8 1.1 2.6 1.4 1.4 0.1 2.0 1.6 2.0 12.0 19.0 6A 6.4 0.8 1.2 0.6 0.2 0.0 1.7 1.4 1.9 9.0 14.2 6B 6.8 1.0 1.5 0.8 0.4 0.0 1.9 1.6 1.9 10.2 15.9

6 (mean) 6.6 0.9 1.3 0.7 0.3 0.0 1.8 1.5 1.9 9.6 15.1 7A 6.8 0.9 1.7 0.9 0.6 0.0 1.8 1.5 1.9 10.3 16.0 7B 7.0 1.1 2.0 1.1 0.7 0.0 1.9 1.6 1.9 11.1 17.2

7 (mean) 6.9 1.0 1.8 1.0 0.6 0.0 1.8 1.5 1.9 10.7 16.6 8A 3.9 0.2 1.4 0.7 0.4 0.0 2.2 1.6 2.1 6.2 12.5 8B 6.8 1.0 1.4 0.6 0.4 0.0 1.8 1.5 1.6 9.7 15.0

8 (mean) 5.3 0.6 1.4 0.6 0.4 0.0 2.0 1.6 1.8 7.9 13.7

Chris Keung C-9


Table C- 7: HAA raw data from Killaloe (October 28, 2014)



28-O

ct-1

4

1A 0.0 0.0 0.0 0.0 0.0 0.0 0.2 1.4 6.9 0.0 8.6 1B 0.0 0.0 0.0 0.0 0.0 0.0 0.1 1.4 6.0 0.0 7.5

1 (mean) 0.0 0.0 0.0 0.0 0.0 0.0 0.2 1.4 6.5 0.0 8.0 2A 0.0 3.4 17.5 10.3 4.6 1.7 5.4 3.2 5.6 32.8 51.6 2B 0.2 3.5 17.8 10.7 4.8 1.8 6.1 3.4 4.7 33.9 53.1

2 (mean) 0.1 3.4 17.6 10.5 4.7 1.7 5.8 3.3 5.2 33.4 52.3 3A 0.0 3.7 4.7 6.1 2.8 2.3 2.6 3.9 8.5 16.9 34.6 3B 0.0 3.4 3.7 6.1 3.0 1.2 3.6 2.6 5.5 14.3 29.0

3 (mean) 0.0 3.6 4.2 6.1 2.9 1.7 3.1 3.2 7.0 15.6 31.8 4A 0.1 1.5 4.4 4.1 3.8 1.2 2.6 2.3 4.8 11.3 24.8 4B 0.0 1.5 4.5 4.2 3.3 1.4 2.8 2.3 5.3 11.6 25.3

4 (mean) 0.1 1.5 4.4 4.2 3.6 1.3 2.7 2.3 5.1 11.4 25.1 5A 0.0 0.9 4.8 4.9 3.3 1.2 2.9 2.3 5.6 11.7 25.8 5B 0.0 0.8 4.4 4.4 2.9 1.3 2.8 2.3 5.4 10.9 24.3

5 (mean) 0.0 0.8 4.6 4.6 3.1 1.2 2.8 2.3 5.5 11.3 25.1 6A 0.0 0.7 3.0 3.4 1.7 0.9 2.3 2.1 5.3 8.0 19.5 6B 0.0 0.8 3.6 4.1 2.2 1.0 2.6 2.4 5.6 9.5 22.2

6 (mean) 0.0 0.7 3.3 3.7 2.0 1.0 2.5 2.3 5.5 8.7 20.9 7A 0.0 0.8 3.2 4.3 2.3 1.0 2.5 2.3 6.4 9.2 22.8 7B 0.0 0.7 3.3 4.3 2.3 1.0 2.3 2.3 4.6 9.2 20.7

7 (mean) 0.0 0.7 3.3 4.3 2.3 1.0 2.4 2.3 5.5 9.2 21.8 8A 0.0 0.6 2.1 3.0 1.2 0.6 2.0 2.1 5.5 6.3 17.2 8B 0.0 0.7 2.6 6.2 4.0 0.7 2.4 2.3 5.1 10.1 24.0

8 (mean) 0.0 0.6 2.4 4.6 2.6 0.6 2.2 2.2 5.3 8.2 20.6

Chris Keung C-10


Table C- 8: HAA raw data from Killaloe (February 3, 2015)



3-Fe

b-15

1A 3.7 0.0 0.0 0.2 0.0 0.2 1.1 0.0 0.0 4.1 5.2 1B 2.1 0.0 0.0 0.2 0.0 0.3 1.1 0.0 0.0 2.5 3.7

1 (mean) 2.9 0.0 0.0 0.2 0.0 0.3 1.1 0.0 0.0 3.3 4.4 2A 2.1 0.0 11.7 7.0 1.5 0.4 2.7 0.5 0.0 21.2 25.9 2B 2.1 0.0 11.1 6.4 1.2 0.4 2.7 0.4 0.0 19.9 24.1

2 (mean) 2.1 0.0 11.4 6.7 1.4 0.4 2.7 0.4 0.0 20.6 25.0 3A 3.4 0.0 5.2 4.5 2.5 1.2 3.0 0.4 0.0 14.4 20.3 3B 3.6 0.0 5.3 4.7 2.6 1.2 3.2 0.7 0.0 14.9 21.4

3 (mean) 3.5 0.0 5.3 4.6 2.5 1.2 3.1 0.6 0.0 14.6 20.8 4A 3.9 0.0 6.7 5.0 3.2 1.3 3.4 1.3 0.0 16.9 24.8 4B 5.3 0.0 6.7 5.1 3.1 1.6 3.3 2.0 0.0 18.7 27.0

4 (mean) 4.6 0.0 6.7 5.0 3.1 1.5 3.3 1.6 0.0 17.8 25.9 5A 3.7 0.0 6.6 5.0 3.1 1.5 3.3 0.6 0.0 16.8 23.7 5B 3.6 0.0 6.7 5.2 3.1 1.5 3.5 1.2 0.0 17.0 24.8

5 (mean) 3.7 0.0 6.7 5.1 3.1 1.5 3.4 0.9 0.0 16.9 24.2 6A 2.1 0.0 5.8 4.9 2.8 1.4 3.2 0.0 0.0 14.1 20.1 6B 2.1 0.0 6.9 5.2 2.8 1.3 3.6 1.7 0.0 15.5 23.5

6 (mean) 2.1 0.0 6.4 5.0 2.8 1.3 3.4 0.8 0.0 14.8 21.8 7A 5.0 0.0 6.2 5.2 2.9 1.6 3.4 2.5 0.0 18.0 26.7 7B 4.2 0.0 6.2 5.1 3.0 1.4 3.2 0.6 0.0 16.9 23.7

7 (mean) 4.6 0.0 6.2 5.1 2.9 1.5 3.3 1.5 0.0 17.4 25.2 8A 4.5 0.0 5.5 4.8 2.6 1.2 3.1 0.0 0.0 16.0 21.7 8B 5.0 0.0 5.4 4.8 2.6 1.2 3.1 0.6 0.0 16.4 22.6

8 (mean) 4.7 0.0 5.4 4.8 2.6 1.2 3.1 0.3 0.0 16.2 22.1

Chris Keung C-11


Table C- 9: HAA raw data from Killaloe (May 28, 2015)



28-M

ay-1

5

1A 2.1 0.0 0.0 0.2 0.0 0.1 1.9 0.7 0.0 2.4 4.9 1B 2.1 0.0 0.0 0.2 0.0 0.2 1.7 0.0 0.0 2.5 4.2

1 (mean) 2.1 0.0 0.0 0.2 0.0 0.2 1.8 0.3 0.0 2.4 4.6 2A 2.1 0.0 4.8 4.2 1.4 0.4 3.5 3.9 0.0 11.5 20.3 2B 2.1 0.0 4.6 4.2 1.5 0.4 3.2 1.0 0.0 11.3 17.0

2 (mean) 2.1 0.0 4.7 4.2 1.5 0.4 3.3 2.4 0.0 11.4 18.6 3A 2.7 0.0 7.2 4.7 2.6 1.0 2.7 0.1 0.0 15.6 21.1 3B 2.8 0.0 8.6 5.5 3.0 0.9 2.9 7.4 0.0 17.8 31.0

3 (mean) 2.7 0.0 7.9 5.1 2.8 0.9 2.8 3.7 0.0 16.7 26.1 4A 3.0 0.0 9.9 6.6 3.5 0.5 5.8 3.1 0.0 20.0 32.5 4B 2.8 0.0 7.6 5.2 2.8 1.0 2.8 0.0 0.0 16.6 22.3

4 (mean) 2.9 0.0 8.8 5.9 3.2 0.7 4.3 1.6 0.0 18.3 27.4 5A 2.1 0.0 7.5 5.4 2.7 0.9 3.5 0.7 0.0 15.9 22.9 5B 2.1 0.0 7.5 5.4 2.8 0.9 3.5 0.9 0.0 15.8 23.0

5 (mean) 2.1 0.0 7.5 5.4 2.8 0.9 3.5 0.8 0.0 15.8 22.9 6A 2.8 0.0 6.6 5.1 2.4 1.0 2.7 0.4 0.0 15.4 21.0 6B 2.7 0.0 6.9 5.3 2.6 1.1 2.7 0.4 0.0 16.0 21.7

6 (mean) 2.8 0.0 6.7 5.2 2.5 1.0 2.7 0.4 0.0 15.7 21.3 7A 2.1 0.0 6.5 5.2 2.3 1.2 3.1 1.1 0.0 15.0 21.6 7B 3.6 0.0 6.7 5.3 2.5 1.0 3.0 0.0 0.0 16.5 22.0

7 (mean) 2.8 0.0 6.6 5.3 2.4 1.1 3.0 0.6 0.0 15.8 21.8 8A 2.1 0.0 7.0 5.3 2.6 1.3 3.3 1.8 0.0 15.7 23.5 8B 2.1 0.0 6.9 5.3 2.6 1.4 3.2 1.6 0.0 15.7 23.1

8 (mean) 2.1 0.0 7.0 5.3 2.6 1.4 3.2 1.7 0.0 15.7 23.3

Chris Keung C-12


Table C- 10: Water quality measurements from Killaloe (September 9, 2015)

Date Site Chlorine Residual (mg/L)

HSP Residual (mg/L)

Temp (°C) pH AOX

(μg/L) DOC

(mg/L) UV254 ATP

(pg/mL) ATP

(ME/mL)

Genotox (IF @

16.5 eq. mL)

09-S

ep-1

5

1A - - - - 22.9 4.6 0.102 3.19 3189 1B - - - - 19.5 4.7 0.101 3.62 3624

1 (mean) - - 8.2 8.1 21.2 4.6 0.101 3.41 3407 2A - - - - N/A 4.4 0.068 0.04 43 2B - - - - N/A 4.5 0.068 0.01 9

2 (mean) 0.77 - 8.2 8.1 N/A 4.4 0.068 0.03 26 2.21 3A - - - - 129.5 4.2 0.078 0.02 17 3B - - - - 143.8 4.5 0.077 0.01 9

3 (mean) - 6.9 8.2 8.2 136.7 4.4 0.077 0.01 13 N/A 4A - - - - 113.3 3.9 0.074 0.09 94 4B - - - - 115.3 4.1 0.075 0.08 77

4 (mean) - 7.4 8.1 8.1 114.3 4.0 0.075 0.09 85 1.20 5A - - - - 112.8 4.1 0.073 2.66 2661 5B - - - - 112.2 4.1 0.073 2.35 2354

5 (mean) - 6.1 14 8.2 112.5 4.1 0.073 2.51 2508 6A - - - - 109.5 4.1 0.071 2.45 2448 6B - - - - 104.7 4.3 0.071 2.22 2219

6 (mean) - 3.6 16 8.1 107.1 4.2 0.071 2.33 2334 7A - - - - 112.6 4.1 0.072 2.81 2805 7B - - - - 109.6 4.2 0.071 2.36 2358

7 (mean) - 5 15 8.1 111.1 4.1 0.072 2.58 2582 1.08 8A - - - - 101.2 4.0 0.070 1.00 1004 8B - - - - 102.5 4.3 0.071 1.57 1572

8 (mean) - 3.7 17 8.2 101.8 4.1 0.071 1.29 1288 1.27

Chris Keung C-13


Table C- 11: Water quality measurements from Killaloe (October 28, 2015)


HSP Residual (mg/L)

Temp (°C) pH AOX

(μg/L) DOC

(mg/L) UV254 ATP (pg/mL)

ATP (ME/mL)

Genotox (IF @

16.5 eq. mL)

28-O

ct-1

5

1A - - - - 25.5 4.1 0.098 2.43 2432 1B - - - - 21.3 4.1 0.100 2.68 2677

1 (mean) - - 8.3 - 23.4 4.1 0.099 2.55 2555 2A - - - - N/A 3.8 0.073 0.13 129 2B - - - - N/A 3.9 0.072 0.07 68

2 (mean) 0.89 - 8.2 - N/A 3.8 0.072 0.10 99 2.28 3A - - - - 202.2 4.0 0.082 0.03 27 3B - - - - 206.4 3.9 0.082 0.07 75

3 (mean) - 7.5 8 - 204.3 3.9 0.082 0.05 51 1.97 4A - - - - 130.4 3.7 0.083 0.22 225 4B - - - - 129.8 3.7 0.083 0.36 361

4 (mean) - 7.1 8 - 130.1 3.7 0.083 0.29 293 1.57 5A - - - - 121.8 3.8 0.082 2.05 2051 5B - - - - 125.8 3.8 0.081 1.73 1730

5 (mean) - 5.7 15 - 123.8 3.8 0.081 1.89 1891 6A - - - - 122.2 3.6 0.086 1.68 1676 6B - - - - 124.5 3.7 0.081 1.53 1533

6 (mean) - 4.5 14 - 123.4 3.7 0.083 1.60 1605 1.37 7A - - - - 124.2 3.7 0.077 1.97 1969 7B - - - - 123.2 3.7 0.077 1.80 1799

7 (mean) - 5.1 15 - 123.7 3.7 0.077 1.88 1884 1.22 8A - - - - 112.2 3.7 0.084 2.55 2548 8B - - - - 111.8 3.7 0.082 2.11 2112

8 (mean) - 3 15 - 112.0 3.7 0.083 2.33 2330

Chris Keung C-14


Table C- 12: Water quality measurements from Killaloe (February 3, 2015)


HSP Residual (mg/L)

Temp (°C) pH AOX

(μg/L) DOC


ATP (ME/mL)

Genotox (IF @

16.5 eq. mL)

03-F

eb-1

5

1A - - - - 18.0 4.2 0.098 1.90 1899 1B - - - - 14.4 4.1 0.101 2.76 2756

1 (mean) - - 8.6 7.9 16.2 4.1 0.099 2.33 2328 2A - - - - 143.7 4.1 0.077 0.03 26 2B - - - - 153.6 4.0 0.095 0.14 144

2 (mean) 1.05 - 8.4 8 148.7 4.0 0.086 0.09 85 1.21 3A - - - - 203.5 4.0 0.082 0.09 92 3B - - - - 204.2 4.0 0.082 0.09 85

3 (mean) - 8 8.3 8 203.8 4.0 0.082 0.09 88 2.24 4A - - - - 135.3 3.9 0.081 0.80 799 4B - - - - 136.2 3.8 0.082 0.63 629

4 (mean) - 7.6 8.3 8.1 135.7 3.8 0.081 0.71 714 1.79 5A - - - - 131.1 3.9 0.078 1.84 1840 5B - - - - 132.1 3.9 0.079 0.90 897

5 (mean) - 6.3 8 8.2 131.6 3.9 0.079 1.37 1368 6A - - - - 136.6 3.8 0.086 0.75 746 6B - - - - 134.6 3.8 0.086 1.57 1565

6 (mean) - 4.2 9 8 135.6 3.8 0.086 1.16 1156 7A - - - - 137.4 3.8 0.080 2.36 2357 7B - - - - 134.0 3.8 0.079 2.08 2075

7 (mean) - 5.7 7 8 135.7 3.8 0.080 2.22 2216 1.22 8A - - - - 131.3 3.8 0.084 2.38 2377 8B - - - - 130.5 3.8 0.084 1.16 1159

8 (mean) - 3.9 8 8.2 130.9 3.8 0.084 1.77 1768 1.05

Chris Keung C-15


Table C- 13: Water quality measurements from Killaloe (May 28, 2015)


HSP Residual (mg/L)

Temp (°C) pH AOX

(μg/L) DOC


ATP (ME/mL)

Genotox (IF @

16.5 eq. mL)

28-M

ay-1

5

1A - - - - 41.7 4.2 0.096 3.13 3133 1B - - - - 36.8 4.0 0.096 2.09 2089

1 (mean) - - 13 7.8 39.3 4.1 0.096 2.61 2611 2A - - - - 118.5 4.0 0.077 0.21 209 2B - - - - 114.3 3.9 0.076 0.10 104

2 (mean) 1.24 - 12 7.8 116.4 4.0 0.076 0.16 157 2.19 3A - - - - 167.7 4.0 0.081 0.21 209 3B - - - - 162.8 4.0 0.080 0.21 209

3 (mean) - 8.2 12 7.8 165.2 4.0 0.080 0.21 209 1.99 4A - - - - 137.0 4.0 0.083 0.31 313 4B - - - - 143.1 3.9 0.086 0.31 313

4 (mean) - 8.1 13 7.8 140.1 3.9 0.085 0.31 313 1.67 5A - - - - 126.7 3.9 0.081 2.40 2402 5B - - - - 134.6 4.0 0.083 2.09 2089

5 (mean) - 5.6 14 7.9 130.7 3.9 0.082 2.25 2246 6A - - - - 138.3 3.7 0.089 1.57 1567 6B - - - - 133.5 3.9 0.089 1.67 1671

6 (mean) - 4.7 16 7.8 135.9 3.8 0.089 1.62 1619 7A - - - - 128.7 3.9 0.079 1.88 1880 7B - - - - 135.2 3.8 0.080 1.98 1984

7 (mean) - 4.8 14 7.8 131.9 3.9 0.079 1.93 1932 1.36 8A - - - - 128.3 3.8 0.087 2.09 2089 8B - - - - 133.3 3.8 0.087 1.98 1984

8 (mean) - 3.6 16 7.7 130.8 3.8 0.087 2.04 2037 1.29

Chris Keung D-1


D. SENTINEL EXPERIMENTAL PROTOCOLS. CALIBRATION AND QA/QC

Chris Keung D-2


D.1 DISSOLVED ORGANIC CARBON (DOC)

Table D- 1: DOC instrument conditions

Parameter Description Acid Volume 500 µL of 5% phosphoric acid Oxidant Volume 1000 µL of 10% sodium persulphate Sample Volume 2 mL Rinses per sample 1 Volume per rinse 15 mL Replicates per sample 3 Reaction time (min:sec) TIC 01:30; TOC 02:00 Detection time (min:sec) TIC 00:00; TOC 03:00 Purge gas Nitrogen Loop Size 10 mL

Table D- 2: DOC reagents

Parameter Description Milli-Q® water Prepared in the laboratory Sulphuric acid, H2SO4 VWR International, 98+% Sodium persulphate, Na2(SO4) Sigma Aldrich, 98+%, anhydrous Potassium hydrogen phthalate (KHP), C8H5KO4 Sigma Aldrich, 98+% Phosphoric acid, H3PO4 Caledon, >85% Nitrogen gas, N2 Praxair, Ultra high purity (UHP)

Table D- 3: DOC method outline

Blanks: Use 40 mL of Milli-Q® water. Stock Solution: Mix 2.13g potassium hydrogen phthalate in 1 L of Milli-Q® water and acidify at pH<2 with H2SO4. Store in fridge at 4°C. Check Standards (2.5 mg/L): Add 250 µL of stock solution to 100 mL of Milli-Q® water. Analysis: Follow SOP for TOC analyzer

Chris Keung D-3


D.2 FREE AMMONIA MEASUREMENT

Table D- 4: Free ammonia reagents

Parameter Description Monochloramine F Reagent pillows Hach (Item # 28022-99) Free ammonia reagent solution Hach (Item # 28773-36)

Table D- 5: Free ammonia method outline

Free Ammonia Measurement: Start program “66” for Free Ammonia measurement on Hach Spectrophotometer. Fill two cells with 10 mL of sample and label one “free ammonia” and one cell “monochloramine”. To the free ammonia cell add one drop of free ammonia reagent solution and shake. Add the contents of one pillow of Monochloramine F to both cells. Shake for 30 seconds and wait for 5 minutes. Blank machine with the monochloramine cell. Place the free ammonia cell in the Hach machine and press read. The result will be in mg/L of free ammonia as nitrogen (NH3-N)

D.3 FREE CHLORINE MEASUREMENT

Table D- 6: Free chlorine reagents

Parameter Description Milli-Q® water Prepared in the laboratory DPD free chlorine reagent powder pillow Hach (Item # 2105569) Sodium hypochlorite, NaClO Sigma Aldrich, available chlorine 10-15%

Table D- 7: Free chlorine method outline

Blanks: Fill sample cell with 10 mL of sample. Start program “80 Chlorine F&T PP” on Hach DR 2500 Spectrophotometer. Insert blank cell into holder and press “ZERO” on the Hach DR 2500. The display shows 0.00 mg/L Cl2

Samples: Fill sample cell with 10 mL of sample and add one powder pillow to the sample cell. Shake cell for 20 seconds – a pink color will develop if chlorine is present. Clean sample cell and measure free chlorine residual by pressing “READ” on Hach machine. Results shown in mg/L Cl2. Stock Solution: Add approximately 10 mL of sodium hypochlorite solution (10-15%) to 500 mL

Chris Keung D-4


Milli-Q® water. The concentration of the stock solution will be approximately 2000 mg/L as Cl2. Stock concentration needs to be verified prior to each use. Store in amber vial and store in fridge at 4°C.

D.4 TOTAL CHLORINE AMPEROMETRIC TITRATION

Table D- 8: Total chlorine reagents

Parameter Description Milli-Q® water Prepared in the laboratory Sodium hypochlorite, NaClO Sigma Aldrich, available chlorine 10-15% Ammonium chloride, NH4Cl Sigma Aldrich, > 99.5% Sodium carbonate, Na2CO3 Sigma Aldrich, ACS grade Sodium bicarbonate, NaHCO3 Sigma Aldrich, ACS grade Phenylarsine oxide (PAO), C6H5AsO BDH, 0.0056N

Phosphate buffer pH 7 Sigma Aldrich, potassium dihydrogen phosphate/di-sodium hydrogen phosphate

Sodium acetate buffer pH 4 Anachemia Electrolyte crystals Siemens Potassium iodide, KI Amresco, ACS grade

Table D- 9: Total chlorine method outline

Monochloramine stock solution: Make pH 9.4 buffer by adding 1.96 g of Na2CO3 and 6.86 g of NaHCO3 in 1000 mL of Milli-Q® Water. Repeat. Make ammonium chloride solution (2500 mg/L) by dissolving 2.5 g of NH4Cl in 1000 mL of pH 9.4 buffer solution. Make chlorine solution (2819 mg/L) by adding 28.19 mL of sodium hypochlorite solution in 1000 mL of pH 9.4 buffer. Validate concentration of chlorine solution using free chlorine DPD colorimetric method as described in Section 4.2.1.4. This concentration of chlorine solution ensures that monochloramine is the dominant species by maintaining ammonia to chlorine ratio of 1:0.85. To prepare monochloramine, combine equal volumes of stock 1 and stock 2 to achieve desired concentration. Verify monochloramine stock solution using amperometric titration described below. Amperometric titration: Free chlorine and combined chlorine (monochloramine, dichloramine) residual are measured using a consecutive three-step amperometric titration. Preparation of 0.00564N potassium iodine solution (KI): Dissolve 50 g of KI in 1 L of Milli-Q® water.

Chris Keung D-5


Determination of free chlorine: On the amperometric titrator turn knob to STBY position and turn switch to the mg/L sensitivity position. Fill the pipette to the top (zero) calibration mark with PAO solution. Measure a 200 mL sample of water to be tested. Place the cup on the titrator and submerge the metal tip of the pump unit in the sample while the sample is being mixed. Add 1 mL of buffer pH 7 to the water sample. Rotate the turns-counting dial clockwise to make the meter pointer read maximum on the scale (far left). Add the PAO solution, the meter pointer will deflect to the left if free chlorine is present in the sample. As long as the pointer is on scale, each addition of PAO will produce a definite pointer deflection to the left if free chlorine is present. The endpoint of the titration is when the addition of PAO no longer produces a noticeable (or not as much as previous increment) deflection. The amount of PAO added represents the free chlorine in mg/L Determination of monochloramine: To the same sample used for the free chlorine determination add 0.2 mL of the KI solution. If monochloramine is present the needle will deflect to the right and it will be possible to continue the titration to a second endpoint. The difference in the pipette reading and the reading obtained from the free chlorine measurement represents monochloramine in mg/L. Determination of dichloramine: To the same sample add one mL of pH 4 buffer and 1 mL of KI solution. If dichloramine is present the pointer will deflect to the right. Continue titration to a third endpoint and the difference between this reading and the second endpoint (monochloramine) represents the concentration of dichloramine in mg/L.

D.5 CHLORINE DIOXIDE MEASUREMENT

Table D- 10: Chlorine dioxide reagents

Parameter Description Milli-Q® water Prepared in the laboratory DPD free chlorine reagent powder pillow Hach (Item # 2105569) Glycine Reagent Hach (Item # 2762133) Sulphuric acid, H2SO4 VWR International, 98+% Sodium chlorite, NaClO2 J.T. Baker, 80%, anhydrous Potassium iodide, KI Amresco, ACS grade Sodium hydroxide, NaOH Sigma Aldrich, 97+%

Chris Keung D-6


Table D- 11: Chlorine dioxide method outline

Blanks: Fill sample cell with 10 mL of sample. Start program “76 Chlor Diox DPD” on Hach DR 2500 spectrophotometer. Insert blank cell into holder and press “ZERO” on the Hach DR 2500. The display shows 0.00 mg/L ClO2

Samples: Fill sample cell with 10 mL of sample and add 4 drops of Glycine Reagent. Swirl cell and then add one powder pillow to the sample cell. Shake cell for 20 seconds and then wait for 30 seconds for powder to settle. Clean sample cell and measure free chlorine residual by pressing “READ” on Hach machine. Results shown in mg/L ClO2. ClO2 Generation: Apparatus setup

Fill bottle #3 with approximately 400 mL of Milli-Q® water and place in an ice bath to cool the water. Fill bottle #1 with 250 mL of 18N (50%) H2SO4. Fill bottle #2 with 250 mL of 15% (by weight) NaClO2. Fill bottle #4 with 30 mL of 15% KI. Fill the NaClO2 reservoir with 100 mL of 25% (by weight) NaClO2. Assemble the system from right to left. Start adding NaClO2 to the H2SO4 (bottle #1). The feed rate should be about 2-3 mL/min or 4-5 drops/min. Continue the process until either the NaClO2 solution is about used up, or the ClO2 trap (bottle #3) is very yellow – approximately 1 hour. Replace the NaClO2 reservoir bottle with Milli-Q® water to flush out the system. Disassemble the system from left to right. Store the ClO2 stock solution from bottle #3 in an opaque plastic bottle, headspace free. Store at 4°C. Verify concentrations of chlorine dioxide, free chlorine, and chlorite in stock solution using the amperometric titration technique according to Standard method 4500 ClO2 C (APHA, 2012)

Chris Keung D-7


D.6 HYDROGEN PEROXIDE MEASUREMENT

Table D- 12: Hydrogen peroxide reagents

Parameter Description Milli-Q® water Prepared in the laboratory Potassium hydrogen phthalate (KHP), C8H5KO4

BDH, 98+%

Sodium hydroxide, NaOH Sigma Aldrich, 97+% Potassium iodide, KI Amresco, ACS grade Ammonium molybdate tetrahydrate EMD, ACS grade Hydrogen peroxide, H2O2 Sigma Aldrich, 30% wt in H2O Sodium hydroxide, NaOH Sigma Aldrich, 97+%

Table D- 13: Hydrogen peroxide method outline

Solution Preparation: Prepare solution A by dissolving 66.0 g of KI, 2.0 g of NaOH, and 0.2 g of ammonium molybdate tetrahydrate in 1000 mL of Milli-Q® water. Prepare solution B by dissolving 20 g of KHP in 1000 mL of Milli-Q® water. Analysis: Add 2.5 mL solution A and 2.5 mL solution B to a 25 mL glass vial. Add varying amounts of sample to obtain an absorbance at 351 nm of about 0.9. The sample volumes used to measure the different concentrations of H2O2 are shown in the table below.

Concentration Sample Volume (mL) Total Volume (mL) 1 mg/L 2.5 mL 7.5 6 mg/L 1.0 mL 6.0 15 mg/L 0.5 mL of sample + 2.00 mL

Milli-Q® water 7.5

30 mg/L 0.25 mL of sample + 2.25 mL Milli-Q® water

7.5

Create blank readings by adding the varying amounts of Milli-Q® water to reagents. Fill a 1-cm quartz curvette with sample and using the spectrometer, measure the absorbance at 351 nm. Repeat with samples. Calculate the resulting H2O2 concentrations using the following formula: Mg/L H2O2 = [A351 x (total vol./sample vol.) x 34 g/mol x 1000 mg/g] / 26450 M-1m-1.

Chris Keung D-8


D.7 DOC CALIBRATION CURVES AND QA/QC CHARTS

Figure D- 1: DOC calibration curve

Figure D- 2: Quality control chart for DOC analysis

y = 0.0003x - 1.6516 R² = 1

0

2

4

6

8

10

12

0 10000 20000 30000 40000 50000

Con

cent

ratio

n (m

g/L

)

Area Counts

DOC Calibration Curve

2.02.12.22.32.42.52.62.72.8


DO

C (m

g/L

)

Chris Keung D-9


D.8 WASTEWATER EVALUATION – REACTIVITY QA/QC DATA

Table D- 14: Free chlorine high concentration wastewater reactivity QAQC data

Date 23-Nov-15 13-Jan-15 18-Feb-15 Time (min) 0 10 30 1440 0 10 30 1440 0 10 30 1440

Chlorine 8 23 0 3.52 3.48 3.44 3.1 3.56 3.54 3.54 3.3 3.38 3.38 3.34 3 3.3 3.24 3.16 3 3.62 3.62 3.58 3.28 3.36 3.3 3.26 3.02

Average (mg/L) 3.41 3.36 3.3 3.05 3.59 3.58 3.56 3.29 3.37 3.34 3.3 3.01

Change in Residual (mg/L) 0.05 0.11 0.36 0.01 0.03 0.3 0.03 0.07 0.36

Chlorine 8 23 0.01 3.44 3.2 3.3 2.86 3.54 3.46 3.42 3.18 3.4 3.3 3.26 2.92 3.48 3.14 3.41 3.1 3.44 3.38 3.28 3.1 3.38 3.28 3.28 2.84

Average (mg/L) 3.46 3.17 3.355 2.98 3.49 3.42 3.35 3.14 3.39 3.29 3.27 2.88


Chlorine 8 23 0.1 3.42 2.8 3.06 2.6 3.48 3.08 2.98 2.6 3.42 3.04 3.06 2.62 3.46 2.98 3.08 2.58 3.58 3.28 3.2 2.74 3.4 3.16 2.88 2.74

Average (mg/L) 3.44 2.89 3.07 2.59 3.53 3.18 3.09 2.67 3.41 3.1 2.97 2.68


Chlorine 8 23 0.5 3.2 1.9 1.8 1.36 3.65 2.14 1.88 1.64 3.5 2.08 2.02 1.62 3.2 1.92 1.76 1.43 3.63 2.2 1.96 1.6 3.38 2.04 1.92 1.62

Average (mg/L) 3.2 1.91 1.78 1.395 3.64 2.17 1.92 1.62 3.44 3.18 1.97 1.62


Chlorine 8 23 1 3.1 0.78 0.61 0.22 3.49 0.82 0.62 0.38 3.4 1.8 0.9 0.42 3.18 0.85 0.63 0.23 3.55 0.98 0.7 0.28 3.5 1.4 0.9 0.45

Average (mg/L) 3.14 0.815 0.62 0.225 3.52 0.9 0.66 0.33 3.45 1.6 0.9 0.435


Chris Keung D-10


Table D- 15: Free chlorine med/high concentration wastewater reactivity QAQC data

Date 23-Nov-15 28-May-15 10-Jun-15 Time (min) 0 10 30 1440 0 10 30 1440 0 10 30 1440

Chlorine 8 23 0 1.75 1.73 1.7 1.58 1.51 0.88 0.89 0.89 1.92 1.92 1.96 1.95 1.77 1.76 1.78 1.6 1.7 0.92 0.87 0.91 1.93 1.9 1.9 2.02

Average (mg/L) 1.76 1.745 1.74 1.59 1.605 0.9 0.88 0.9 1.925 1.91 1.93 1.985

Change in Residual (mg/L) 0.015 0.02 0.17 0.705 0.725 0.705 0.015 -0.005 -0.06

Chlorine 8 23 0.01 1.81 1.68 1.68 1.55 1.48 0.84 0.84 0.85 1.92 1.95 1.93 1.9 1.74 1.7 1.68 1.51 1.58 0.88 0.86 0.85 2.02 1.95 2.02 1.96

Average (mg/L) 1.775 1.69 1.68 1.53 1.53 0.86 0.85 0.85 1.97 1.95 1.975 1.93

Change in Residual (mg/L) 0.085 0.095 0.245 0.67 0.68 0.68 0.02 -0.005 0.04

Chlorine 8 23 0.1 1.86 1.55 1.46 1.3 1.42 0.76 0.65 0.6 1.93 1.76 1.63 1.6 1.76 1.44 1.41 1.27 1.46 0.96 0.69 0.66 1.94 1.73 1.69 1.63

Average (mg/L) 1.81 1.495 1.435 1.285 1.44 0.86 0.67 0.63 1.935 1.745 1.66 1.615


Chlorine 8 23 0.5 1.92 0.74 0.52 0.15 1.4 0.08 0.09 0.06 1.95 0.92 0.61 0.46 1.92 0.8 0.57 0.21 1.36 0.06 0.06 0.05 1.9 0.88 0.54 0.42

Average (mg/L) 1.92 0.77 0.545 0.18 1.38 0.07 0.075 0.055 1.925 0.9 0.575 0.44


Chlorine 8 23 1 1.92 0.11 0.06 0.06 1.29 0.06 0.05 0.08 1.94 0.23 0.23 0.09 1.91 0.16 0.1 0.04 1.42 0.1 0.11 0.1 1.93 0.15 0.13 0.03

Average (mg/L) 1.915 0.135 0.08 0.05 1.355 0.08 0.08 0.09 1.935 0.19 0.18 0.06


Chris Keung E-1

Department of Civil Engineering, University of Toronto

E. DECAY PLOTS

Chris Keung E-2


E.1 CHLORINE DECAY CHARTS

Figure E- 1: Chlorine decay plot - 0.05 mg/L, 4°C, pH 6


y = -1.05E-04x - 1.15E-01

y = -1.76E-04x - 2.00E-01

y = -5.77E-04x - 7.03E-01 -2.50

-2.00

-1.50

-1.00

-0.50

0.000 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

0.05 mg/L - 4°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -2.46E-04x - 3.40E-02

y = -7.00E-04x - 2.29E-01 -3.00

-2.50

-2.00

-1.50

-1.00

-0.50

0.000 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

0.05 mg/L - 23°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01%

Chris Keung E-3




y = -8.53E-05x - 7.42E-03

y = -1.33E-04x - 1.86E-01

y = -3.09E-04x - 1.01E+00

-2.50

-2.00

-1.50

-1.00

-0.50

0.00

0.50

0 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

0.05 mg/L - 4°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -8.00E-04x - 1.55E-02

y = -8.30E-04x - 8.20E-01

-3.00

-2.50

-2.00

-1.50

-1.00

-0.50

0.00

0.50

0 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

0.05 mg/L - 23°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01%

Chris Keung E-4




y = -1.14E-03x - 2.41E+00

y = -5.85E-04x - 2.74E+00 -4.50-4.00-3.50-3.00-2.50-2.00-1.50-1.00-0.500.00

0 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

0.8 mg/L - 4°C, pH 6 - 0.5%, 1%

0.50% 1%

y = -3.68E-05x - 3.22E-02

y = -2.52E-05x - 3.83E-02

y = -8.32E-05x - 3.93E-01 -0.70

-0.60

-0.50

-0.40

-0.30

-0.20

-0.10

0.000 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

0.8 mg/L - 4°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

Chris Keung E-5




y = -1.16E-04x + 1.32E-02

y = -1.20E-04x - 4.13E-02

y = -1.42E-04x - 6.03E-01 -1.20

-1.00

-0.80

-0.60

-0.40

-0.20

0.00

0.20

0 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

0.8 mg/L - 23°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -5.52E-05x + 1.04E-03

y = -5.93E-05x - 5.69E-02

y = -8.91E-05x - 3.44E-01 -0.70

-0.60

-0.50

-0.40

-0.30

-0.20

-0.10

0.00

0.10

0 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

0.8 mg/L - 4°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

Chris Keung E-6




y = -2.07E-04x - 1.68E+00

y = 3.19E-05x - 2.34E+00 -3.00

-2.50

-2.00

-1.50

-1.00

-0.50

0.000 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

0.8 mg/L - 4°C, pH 8 - 0.5%, 1%

0.50% 1%

y = -9.61E-05x - 1.83E-02

y = -1.56E-04x - 8.52E-02

y = -3.60E-04x - 4.42E-01 -1.60

-1.40

-1.20

-1.00

-0.80

-0.60

-0.40

-0.20

0.00

0.20

0 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

0.8 mg/L - 23°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

Chris Keung E-7


Figure E- 11: Chlorine decay plot - 2 mg/L, 4°C, pH 6


y = -1.57E-05x - 1.15E-03

y = -1.77E-05x - 4.32E-02

y = -5.98E-05x - 1.44E-01 -0.35

-0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.000 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

2 mg/L - 4°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -3.01E-05x - 1.20E+00

y = -3.42E-04x - 2.72E+00 -4.00

-3.50

-3.00

-2.50

-2.00

-1.50

-1.00

-0.50

0.000 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

2 mg/L - 4°C, pH 6 - 0.5%, 1%

0.50% 1%

Chris Keung E-8




y = -1.81E-05x - 5.37E-03

y = -2.83E-05x - 4.70E-03

y = -4.79E-05x - 9.21E-02 -0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.00

0.05

0 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

2mg/L - 23°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -1.09E-04x - 1.22E+00

y = -2.02E-04x - 3.44E+00 -4.50-4.00-3.50-3.00-2.50-2.00-1.50-1.00-0.500.00

0 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

2 mg/L - 23°C, pH 6 - 0.5%, 1%

0.50% 1%

Chris Keung E-9




y = -3.75E-05x - 2.75E-03

y = -5.88E-05x - 2.79E-02

y = -4.14E-05x - 1.65E-01 -0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.00

0.05

0 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

2 mg/L - 4°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -1.24E-04x - 9.12E-01

y = -2.47E-04x - 2.05E+00 -3.00

-2.50

-2.00

-1.50

-1.00

-0.50

0.000 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

2 mg/L - 4°C, pH 8 - 0.5%, 1%

0.50% 1%

Chris Keung E-10




y = -4.72E-05x - 1.40E-02

y = -4.95E-05x - 5.63E-02

y = -9.23E-05x - 2.10E-01 -0.60

-0.50

-0.40

-0.30

-0.20

-0.10

0.00

0.10

0 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

2 mg/L - 23°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -7.68E-04x - 1.11E+00

y = -5.19E-04x - 2.90E+00 -4.50-4.00-3.50-3.00-2.50-2.00-1.50-1.00-0.500.00

0 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

2 mg/L - 23°C, pH 8 - 0.5%, 1%

0.50% 1%

Chris Keung E-11




y = -1.78E-06x - 5.00E-03

y = -5.07E-07x - 2.53E-02

y = -1.51E-05x - 1.52E-01 -0.25

-0.20

-0.15

-0.10

-0.05

0.000 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

4 mg/L - 4°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -4.20E-05x - 5.77E-01

y = 2.80E-05x - 1.53E+00 -1.80-1.60-1.40-1.20-1.00-0.80-0.60-0.40-0.200.00

0 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

4 mg/L - 4°C, pH 6 - 0.5%, 1%

0.50% 1%

Chris Keung E-12




y = -8.22E-06x + 3.09E-03

y = -9.93E-06x - 3.02E-02

y = -2.14E-05x - 1.64E-01 -0.25

-0.20

-0.15

-0.10

-0.05

0.00

0.05

0 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

4 mg/L - 23°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -5.06E-05x - 5.70E-01

y = -1.43E-04x - 1.45E+00 -2.00-1.80-1.60-1.40-1.20-1.00-0.80-0.60-0.40-0.200.00

0 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

4 mg/L - 23°C, pH 6 - 0.5%, 1%

0.50% 1%

Chris Keung E-13




y = -2.04E-05x - 1.14E-02

y = -2.49E-05x - 2.00E-02

y = -2.34E-05x - 1.03E-01 -0.20-0.18-0.16-0.14-0.12-0.10-0.08-0.06-0.04-0.020.00

0 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

4 mg/L - 4°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -5.61E-05x - 5.06E-01

y = -1.15E-04x - 1.16E+00 -1.80-1.60-1.40-1.20-1.00-0.80-0.60-0.40-0.200.00

0 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

4 mg/L - 4°C, pH 8 - 0.5%, 1%

0.50% 1%

Chris Keung E-14




y = -4.52E-05x - 2.76E-02

y = -3.96E-05x - 6.53E-02

y = -5.32E-05x - 1.56E-01 -0.35

-0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.000 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

4 mg/L - 23°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -1.35E-04x - 5.66E-01

y = -3.55E-04x - 2.13E+00 -3.50

-3.00

-2.50

-2.00

-1.50

-1.00

-0.50

0.000 500 1000 1500 2000 2500 3000

Ln (C

/Co)

)

Time (min)

4 mg/L - 23°C, pH 8 - 0.5%, 1%

0.50% 1%

Chris Keung E-15


E.2 CHLORAMINES DECAY CHARTS

Figure E- 27: Chloramines decay plot – 0.5 mg/L, 4°C, pH 6


y = -3.44E-05x + 6.85E-04

y = -3.61E-05x + 5.20E-02

y = -3.81E-05x + 7.59E-04

y = -1.09E-04x - 2.62E-02

y = -2.03E-04x - 4.48E-02 -0.50

-0.40

-0.30

-0.20

-0.10

0.00

0.10

0.20

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

)

Time (min)

0.5 mg/L - 4°C, pH 6

0% 0.01% 0.10% 0.50% 1%

y = -1.84E-05x - 2.51E-02

y = -5.04E-05x + 7.29E-02

y = -9.10E-05x - 1.14E-01

y = -2.49E-04x - 9.47E-02 -0.60

-0.50

-0.40

-0.30

-0.20

-0.10

0.00

0.10

0.20

0.30

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

)

Time (min)

0.5 mg/L - 23°C, pH 6

0.01% 0.10% 0.50% 1%

Chris Keung E-16




y = -4.28E-05x + 2.06E-02

y = -6.89E-05x + 2.48E-02

y = -9.10E-05x - 1.14E-01

y = -2.49E-04x - 9.47E-02

-0.60

-0.50

-0.40

-0.30

-0.20

-0.10

0.00

0.10

0.20

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

)

Time (min)

0.5 mg/L - 4°C, pH 8

0% 0.10% 0.50% 1%

y = -6.41E-05x + 1.28E-03

y = -3.00E-05x - 4.02E-02

y = -6.76E-05x - 4.24E-02

y = -8.72E-05x - 6.58E-02

-0.25

-0.20

-0.15

-0.10

-0.05

0.00

0.05

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

)

Time (min)

0.5 mg/L - 23°C, pH 8

0% 0.01% 0.50% 1%

Chris Keung E-17


Figure E- 31: Chloramines decay plot – 1 mg/L, 4°C, pH 6


y = -3.71E-05x + 7.39E-04

y = -5.65E-05x - 2.43E-02

y = -5.75E-05x - 2.54E-02

y = -1.09E-04x - 6.07E-02

-0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.00

0.05

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

)

Time (min)

1 mg/L - 4°C, pH 6

0.01% 0.10% 0.50% 1%

y = -4.46E-05x + 1.31E-02 y = -1.88E-05x + 3.74E-04

y = -6.89E-05x + 2.48E-02 y = -5.45E-05x + 5.45E-04

y = -1.02E-04x - 1.01E-01 -0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.00

0.05

0.10

0.15

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

)

Time (min)

1 mg/L - 23°C, pH 6

0% 0.01% 0.10% 0.50% 1%

Chris Keung E-18




y = -4.46E-05x + 1.31E-02

y = -1.88E-05x + 3.74E-04

y = -5.26E-05x + 1.58E-03

y = -5.45E-05x + 5.45E-04

y = -1.02E-04x - 1.01E-01 -0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.00

0.05

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

)

Time (min)

1 mg/L - 4°C, pH 8

0% 0.01% 0.10% 0.50% 1%

y = -2.95E-05x - 4.06E-02

y = -5.37E-05x + 1.15E-02

y = -4.86E-05x + 2.34E-02 y = -3.33E-05x + 3.33E-04

y = -6.92E-05x - 4.34E-02

-0.20

-0.15

-0.10

-0.05

0.00

0.05

0.10

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

)

Time (min)

1 mg/L - 23°C, pH 8

0% 0.01% 0.10% 0.50% 1%

Chris Keung E-19




y = -1.55E-05x - 6.84E-03

y = -2.10E-05x + 4.19E-04

y = -1.57E-05x - 2.14E-02

y = -1.02E-05x - 2.85E-02

y = -5.46E-05x - 1.37E-02

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.00

0.02

0.04

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

)

Time (min)

1.75 mg/L - 4°C, pH 6

0% 0.01% 0.10% 0.50% 1%

y = -3.76E-05x - 3.56E-02

y = -3.74E-05x - 2.13E-02

y = -5.46E-05x - 2.35E-02

-0.16

-0.14

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

)

Time (min)

1.75 mg/L - 23°C, pH 6

0.10% 0.50% 1%

Chris Keung E-20


Figure E- : Chloramines decay plot – 1.75 mg/L, 4°C, pH 8


y = -1.35E-07x - 1.31E-02

y = -9.59E-06x - 1.30E-02

y = -4.22E-05x - 5.57E-03

-0.09

-0.08

-0.07

-0.06

-0.05

-0.04

-0.03

-0.02

-0.01

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

)

Time (min)

1.75 mg/L - 4°C, pH 8

0.01% 0.50% 1%

y = -1.85E-05x - 1.25E-02

y = -4.34E-05x - 3.17E-02

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

)

Time (min)

1.75 mg/L - 23°C, pH 8

0.10% 1%

Chris Keung E-21




y = -9.05E-06x + 4.44E-03

y = -2.39E-05x - 7.82E-03

y = -5.05E-05x - 3.29E-02

y = -2.59E-05x - 2.61E-02

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.00

0.02

0.04

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

)

Time (min)

3 mg/L - 4°C, pH 6

0.01% 0.10% 0.50% 1%

y = -2.61E-05x + 5.20E-04

y = -1.20E-05x + 8.75E-03

y = -3.74E-05x + 7.45E-04

y = -5.75E-05x - 1.61E-02

-0.14

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.00

0.02

0.04

0.06

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

)

Time (min)

3 mg/L - 23°C, pH 6

0.01% 0.10% 0.50% 1%

Chris Keung E-22




y = -8.13E-06x - 1.12E-02

y = -2.78E-06x - 3.78E-03

y = -8.27E-06x - 1.16E-02

y = -1.12E-05x - 7.53E-03

y = -1.40E-05x - 1.14E-02

-0.05

-0.04

-0.03

-0.02

-0.01

0.00

0.01

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

)

Time (min)

3 mg/L - 4°C, pH 8

0% 0.01% 0.10% 0.50% 1%

y = -4.74E-05x - 2.32E-02

y = -4.21E-05x - 2.58E-02

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

)

Time (min)

3 mg/L - 23°C, pH 8

0.50% 1%

Chris Keung E-23


E.3 CHLORINE DIOXIDE DECAY CHART

Figure E- 42: Chlorine dioxide decay plot – 0.05 mg/L, 4°C, pH 6


y = -2.52E-05x - 1.96E-02

y = -8.03E-05x - 6.19E-03

y = -3.65E-05x - 7.75E-02 -0.16

-0.14

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.05 mg/L - 4°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -2.67E-04x - 2.90E-02

y = -4.62E-04x - 1.58E-01

-0.45

-0.40

-0.35

-0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.05 mg/L - 4°C, pH 6 - 0.5%, 1%

0.5% 1%

Chris Keung E-24




y = -1.42E-04x - 2.44E-02

y = -2.47E-04x - 5.57E-02

y = -1.66E-04x - 9.91E-02 -0.60

-0.50

-0.40

-0.30

-0.20

-0.10

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.05 mg/L - 23°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -5.78E-04x - 1.15E-01

y = -1.54E-03x - 2.28E-01

-3.00

-2.50

-2.00

-1.50

-1.00

-0.50

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.05 mg/L - 23°C, pH 6 - 0.5%, 1%

0.5% 1%

Chris Keung E-25




y = -2.52E-05x - 7.22E-02

y = -6.69E-05x - 6.07E-02

y = -8.39E-05x - 1.91E-02 -0.20

-0.18

-0.16

-0.14

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.05 mg/L - 4°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -2.14E-04x - 7.96E-02

y = -4.52E-04x - 2.05E-01

-1.00

-0.90

-0.80

-0.70

-0.60

-0.50

-0.40

-0.30

-0.20

-0.10

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.05 mg/L - 4°C, pH 8 - 0.5%, 1%

0.5% 1%

Chris Keung E-26




y = -9.34E-05x - 2.05E-01

y = -2.37E-04x - 2.18E-01

y = -1.46E-04x - 4.66E-01 -0.80

-0.70

-0.60

-0.50

-0.40

-0.30

-0.20

-0.10

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.05 mg/L - 23°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -5.68E-04x - 5.02E-01

-1.60

-1.40

-1.20

-1.00

-0.80

-0.60

-0.40

-0.20

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.05 mg/L - 23°C, pH 8 - 0.5%, 1%

0.5% 1%

Chris Keung E-27




y = -2.38E-07x - 3.67E-02

y = 1.84E-06x - 5.52E-03

y = -3.12E-05x - 1.96E-02

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.00

0.02

0.04

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.2 mg/L - 4°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -7.89E-05x - 1.11E-01

y = -1.61E-04x - 2.37E-01

-0.50

-0.45

-0.40

-0.35

-0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

0.2 mg/L - 4°C, pH 6 - 0.5%, 1%

0.5% 1%

Chris Keung E-28




y = -1.29E-04x + 1.43E-02

y = -1.16E-04x - 9.57E-02

y = -1.83E-04x - 2.39E-02 -0.40

-0.35

-0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.00

0.05

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.2 mg/L - 23°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -3.08E-04x - 1.39E-01

y = -6.41E-04x - 1.92E-01

-1.40

-1.20

-1.00

-0.80

-0.60

-0.40

-0.20

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.2 mg/L - 23°C, pH 6 - 0.5%, 1%

0.5% 1%

Chris Keung E-29




y = -4.64E-05x - 1.95E-02

y = -3.30E-05x - 8.50E-03

y = -6.28E-05x - 5.03E-02 -0.18

-0.16

-0.14

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.2 mg/L - 4°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -2.30E-04x - 9.13E-02

y = -4.52E-04x - 1.78E-01

-1.00

-0.90

-0.80

-0.70

-0.60

-0.50

-0.40

-0.30

-0.20

-0.10

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.2 mg/L - 4°C, pH 8 - 0.5%, 1%

0.5% 1%

Chris Keung E-30




y = -5.37E-05x - 3.10E-02

y = -8.03E-05x - 6.69E-02

y = -2.35E-04x - 7.30E-02

-0.60

-0.50

-0.40

-0.30

-0.20

-0.10

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.2 mg/L - 23°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -3.96E-04x - 2.74E-01

y = -1.15E-03x - 2.01E-01

-2.50

-2.00

-1.50

-1.00

-0.50

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.2 mg/L - 23°C, pH 8 - 0.5%, 1%

0.5% 1%

Chris Keung E-31




y = 6.51E-06x - 4.35E-02

y = -5.11E-06x - 2.77E-02

y = -5.29E-06x - 8.58E-02

-0.14

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.4 mg/L - 4°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -6.92E-05x - 7.57E-02

y = -1.28E-04x - 2.20E-01

-0.50

-0.40

-0.30

-0.20

-0.10

0.00

0.10

0.20

0.30

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.4 mg/L - 4°C, pH 6 - 0.5%, 1%

0.5% 1%

Chris Keung E-32




y = -1.21E-04x + 4.15E-03

y = -1.15E-04x + 2.39E-03

y = -1.13E-04x - 4.74E-02

-0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.00

0.05

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.4 mg/L - 23°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -3.56E-04x - 6.33E-02

y = -5.34E-04x - 2.17E-01

-1.20

-1.00

-0.80

-0.60

-0.40

-0.20

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.4 mg/L - 23°C, pH 6 - 0.5%, 1%

0.5% 1%

Chris Keung E-33




y = -5.25E-05x - 5.23E-02

y = -7.82E-05x - 3.75E-02

y = -1.29E-04x - 6.70E-02 -0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.4 mg/L - 4°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -1.34E-04x - 1.77E-01

y = -2.44E-04x - 1.80E-01 -0.60

-0.50

-0.40

-0.30

-0.20

-0.10

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

)

Time (min)

0.4 mg/L - 4°C, pH 8 - 0.5%, 1%

0.5% 1%

Chris Keung E-34




y = -8.78E-05x - 5.31E-02

y = -8.48E-05x - 1.16E-01

y = -2.23E-04x - 1.45E-01

-0.70

-0.60

-0.50

-0.40

-0.30

-0.20

-0.10

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.4 mg/L - 23°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -5.22E-04x - 1.21E-01

y = -8.11E-04x - 1.88E-01

-1.60

-1.40

-1.20

-1.00

-0.80

-0.60

-0.40

-0.20

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.4 mg/L - 23°C, pH 8 - 0.5%, 1%

0.5% 1%

Chris Keung E-35




y = -2.93E-05x - 1.83E-02

y = -3.44E-05x - 2.51E-02

y = -4.63E-05x - 4.63E-02

-0.16

-0.14

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.8 mg/L - 4°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -5.42E-05x - 7.15E-02

y = -6.36E-05x - 1.34E-01

-0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.8 mg/L - 4°C, pH 6 - 0.5%, 1%

0.5% 1%

Chris Keung E-36




y = -3.63E-05x - 2.75E-02

y = -7.12E-05x - 5.40E-02

y = -8.19E-05x - 7.14E-02

-0.25

-0.20

-0.15

-0.10

-0.05

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.8 mg/L - 23°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -1.66E-04x - 5.94E-02

y = -2.93E-04x - 1.46E-01

-0.70

-0.60

-0.50

-0.40

-0.30

-0.20

-0.10

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.8 mg/L - 23°C, pH 6 - 0.5%, 1%

0.5% 1%

Chris Keung E-37




y = -7.27E-06x - 5.91E-03

y = -2.09E-05x - 6.77E-03

y = -3.87E-05x - 3.59E-03

-0.07

-0.06

-0.05

-0.04

-0.03

-0.02

-0.01

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.8 mg/L - 4°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -8.41E-05x - 3.14E-02

y = -1.17E-04x - 7.75E-02

-0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.8 mg/L - 4°C, pH 8 - 0.5%, 1%

0.5% 1%

Chris Keung E-38




y = -9.34E-05x - 2.05E-01

y = -2.37E-04x - 2.18E-01

y = -1.46E-04x - 4.66E-01 -0.80

-0.70

-0.60

-0.50

-0.40

-0.30

-0.20

-0.10

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.8 mg/L - 23°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -5.68E-04x - 5.02E-01

-1.60

-1.40

-1.20

-1.00

-0.80

-0.60

-0.40

-0.20

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

0.8 mg/L - 23°C, pH 8 - 0.5%, 1%

0.5% 1%

Chris Keung E-39


E.4 HYDROGEN PEROXIDE DECAY CHARTS

Figure E- 74: Hydrogen peroxide decay plot – 1 mg/L, 4°C, pH 6


y = -1.97E-05x + 7.46E-03

y = 2.78E-07x - 8.13E-03

y = -2.13E-05x + 2.44E-04

-0.08

-0.06

-0.04

-0.02

0.00

0.02

0.04

0.06

0.08

0 200 400 600 800 1000 1200 1400 1600Ln (C

/Co)

Time (min)

1 mg/L - 4°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -1.20E-04x - 1.08E-01

y = -2.69E-04x - 1.39E-01

-0.60

-0.50

-0.40

-0.30

-0.20

-0.10

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

1 mg/L - 4°C, pH 6 - 0.5%, 1%

0.5% 1%

Chris Keung E-40




y = -1.79E-05x - 8.00E-03

y = -1.36E-05x - 5.21E-03

y = -5.03E-05x - 9.56E-03 -0.10

-0.08

-0.06

-0.04

-0.02

0.00

0.02

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

1 mg/L - 23°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -3.59E-04x + 2.23E-02

y = -7.10E-04x + 3.34E-02

-1.20

-1.00

-0.80

-0.60

-0.40

-0.20

0.00

0.20

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

1 mg/L - 23°C, pH 6 - 0.5%, 1%

0.5% 1%

Chris Keung E-41




y = -1.11E-05x - 7.36E-03

y = -9.33E-06x - 1.31E-03

y = -1.42E-05x + 8.46E-03

-0.03

-0.03

-0.02

-0.02

-0.01

-0.01

0.00

0.01

0.01

0.02

0.02

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

1 mg/L - 4°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -1.22E-04x - 2.52E-02

y = -2.49E-04x - 1.53E-02

-0.40

-0.35

-0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

1 mg/L - 4°C, pH 8 - 0.5%, 1%

0.5% 1%

Chris Keung E-42




y = 2.14E-06x - 5.11E-02

y = -1.03E-05x - 4.37E-02

y = -5.93E-05x - 4.43E-02

-0.14

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

1 mg/L - 23°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -3.33E-04x - 6.06E-02

y = -6.95E-04x - 6.80E-02

-1.20

-1.00

-0.80

-0.60

-0.40

-0.20

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

1 mg/L - 23°C, pH 8 - 0.5%, 1%

0.5% 1%

Chris Keung E-43




y = -7.45E-06x - 4.13E-04

y = -1.77E-06x - 5.90E-03

y = -9.54E-06x - 4.61E-04 -0.03

-0.02

-0.02

-0.01

-0.01

0.00

0.01

0.01

0.02

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

6 mg/L - 4°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -5.90E-05x + 3.23E-03

y = -1.01E-04x - 2.05E-02

-0.20

-0.15

-0.10

-0.05

0.00

0.05

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

6 mg/L - 4°C, pH 6 - 0.5%, 1%

0.5% 1%

Chris Keung E-44




y = 8.80E-08x - 3.18E-03

y = -1.83E-06x - 1.97E-02

y = -1.47E-05x - 1.05E-02 -0.04

-0.04

-0.03

-0.03

-0.02

-0.02

-0.01

-0.01

0.00

0.01

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

6 mg/L - 23°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -5.35E-05x - 5.60E-02

y = -1.21E-04x - 3.13E-02

-0.25

-0.20

-0.15

-0.10

-0.05

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

6 mg/L - 23°C, pH 6 - 0.5%, 1%

0.5% 1%

Chris Keung E-45




y = -6.04E-06x - 1.07E-02

y = -9.59E-06x - 1.13E-02

y = -1.69E-05x - 3.18E-03

-0.04

-0.04

-0.03

-0.03

-0.02

-0.02

-0.01

-0.01

0.00

0.01

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

6 mg/L - 4°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -4.67E-05x - 3.44E-02

y = -8.67E-05x - 4.12E-02

-0.18

-0.16

-0.14

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

6 mg/L - 4°C, pH 8 - 0.5%, 1%

0.5% 1%

Chris Keung E-46




y = 6.49E-07x - 6.32E-03

y = 2.99E-06x - 1.17E-02

y = -2.11E-05x - 5.02E-03 -0.04

-0.03

-0.02

-0.01

0.00

0.01

0.02

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

6 mg/L - 23°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -9.36E-05x - 3.47E-02

y = -2.00E-04x - 5.18E-02

-0.40

-0.35

-0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

6 mg/L - 23°C, pH 8 - 0.5%, 1%

0.5% 1%

Chris Keung E-47


Figure E- 90: Hydrogen peroxide decay plot –15 mg/L, 4°C, pH 6


y = 4.88E-06x - 2.71E-03

y = 7.61E-07x - 4.29E-03

y = -5.67E-06x - 5.90E-03

-0.03

-0.02

-0.02

-0.01

-0.01

0.00

0.01

0.01

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

15 mg/L - 4°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -3.48E-05x - 4.86E-03

y = -8.34E-05x - 2.00E-02

-0.16

-0.14

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

15 mg/L - 4°C, pH 6 - 0.5%, 1%

0.5% 1%

Chris Keung E-48




y = -3.66E-06x + 2.12E-03

y = -3.25E-07x - 5.95E-03

y = -7.07E-06x - 7.70E-03

-0.02

-0.01

-0.01

-0.01

-0.01

-0.01

0.00

0.00

0.00

0.00

0.00

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

15 mg/L - 23°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -1.50E-05x - 2.17E-02

y = -3.88E-05x - 6.19E-03

-0.07

-0.06

-0.05

-0.04

-0.03

-0.02

-0.01

0.00

0.01

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

15 mg/L - 23°C, pH 6 - 0.5%, 1%

0.5% 1%

Chris Keung E-49




y = -3.72E-06x - 2.00E-03

y = -9.92E-06x - 1.16E-02

y = -3.09E-06x - 3.85E-02

-0.07

-0.06

-0.05

-0.04

-0.03

-0.02

-0.01

0.00

0.01

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

15 mg/L - 4°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -3.71E-05x - 1.58E-02

y = -6.24E-05x - 3.78E-02

-0.16

-0.14

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.00

0.02

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

15 mg/L - 4°C, pH 8 - 0.5%, 1%

0.5% 1%

Chris Keung E-50




y = -6.71E-07x - 8.75E-03

y = -5.64E-06x - 1.42E-03

y = -1.76E-05x - 5.62E-03 -0.04

-0.03

-0.03

-0.02

-0.02

-0.01

-0.01

0.00

0.01

0.01

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

15 mg/L - 23°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -2.84E-05x - 2.71E-02

y = -6.32E-05x - 2.48E-02

-0.14

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

15 mg/L - 23°C, pH 8 - 0.5%, 1%

0.5% 1%

Chris Keung E-51




y = -1.49E-06x - 3.47E-03

y = 4.50E-06x - 9.32E-03

y = -2.30E-06x - 4.09E-03

-0.01

-0.01

-0.01

-0.01

-0.01

0.00

0.00

0.00

0.00

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

30 mg/L - 23°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -1.52E-05x - 1.35E-02

y = -2.99E-05x - 1.57E-02

-0.07

-0.06

-0.05

-0.04

-0.03

-0.02

-0.01

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

30 mg/L - 23°C, pH 6 - 0.5%, 1%

0.5% 1%

Chris Keung E-52




y = 7.95E-07x - 1.18E-03

y = 3.04E-06x - 1.12E-02

y = -8.84E-06x - 4.54E-03 -0.02

-0.02

-0.01

-0.01

0.00

0.01

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

30 mg/L - 4°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -1.81E-05x - 7.65E-03

y = -2.68E-05x - 2.91E-02

-0.08

-0.07

-0.06

-0.05

-0.04

-0.03

-0.02

-0.01

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

30 mg/L - 4°C, pH 6 - 0.5%, 1%

0.5% 1%

Chris Keung E-53




y = 5.06E-07x - 6.25E-03

y = -2.01E-06x - 6.12E-03

y = -2.86E-06x - 8.82E-03 -0.02

-0.02

-0.01

-0.01

0.00

0.01

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

30 mg/L - 23°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -1.75E-05x - 1.47E-02

y = -4.40E-05x - 3.08E-02

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

30 mg/L - 23°C, pH 8 - 0.5%, 1%

0.5% 1%

Chris Keung E-54




y = -3.81E-06x - 8.06E-04

y = -5.84E-06x - 4.17E-04

y = -8.57E-06x + 8.28E-04

-0.01

-0.01

-0.01

-0.01

-0.01

0.00

0.00

0.00

0.00

0.00

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

30 mg/L - 4°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -2.25E-05x - 2.88E-02

y = -4.12E-05x - 1.67E-02 -0.09

-0.08

-0.07

-0.06

-0.05

-0.04

-0.03

-0.02

-0.01

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

30 mg/L - 4°C, pH 8 - 0.5%, 1%

0.5% 1%

Chris Keung E-55


E.5 HUWASAN PEROXIDE DECAY CHARTS

Figure E- 106: HuwaSan peroxide decay plot –1 mg/L, 23°C, pH 6


y = -5.94E-05x - 6.57E-02

y = -7.10E-05x - 5.61E-02

y = -1.08E-04x - 1.34E-01

-0.25

-0.20

-0.15

-0.10

-0.05

0.00

0.05

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

1mg/L -4°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -2.21E-04x - 3.29E-02

y = -3.75E-04x - 1.70E-01

-0.80

-0.70

-0.60

-0.50

-0.40

-0.30

-0.20

-0.10

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

1mg/L -4°C, pH 6 - 0.5%, 1%

0.50% 1%

Chris Keung E-56




y = -3.52E-05x - 6.80E-02 y = -9.19E-06x - 1.06E-01

y = -3.99E-05x - 6.74E-02

-0.18

-0.16

-0.14

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

1mg/L -23°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -2.04E-04x - 2.01E-01

y = -4.60E-04x - 1.95E-01

-1.00

-0.90

-0.80

-0.70

-0.60

-0.50

-0.40

-0.30

-0.20

-0.10

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

1mg/L -23°C, pH 6 - 0.5%, 1%

0.50% 1%

Chris Keung E-57




y = -3.44E-05x - 1.14E-02

y = -4.03E-06x - 6.24E-02

y = -2.76E-05x - 7.27E-02 -0.14

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.00

0.02

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

1mg/L -4°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -2.90E-04x - 5.33E-02

y = -6.16E-04x - 8.78E-02

-1.20

-1.00

-0.80

-0.60

-0.40

-0.20

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

1mg/L -4°C, pH 8 - 0.5%, 1%

0.50% 1%

Chris Keung E-58




y = -8.27E-06x + 8.82E-03

y = -2.59E-05x + 1.17E-02

y = -9.98E-05x + 1.16E-02

-0.20

-0.15

-0.10

-0.05

0.00

0.05

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

1mg/L -23°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -5.36E-04x - 6.99E-03

y = -1.23E-03x - 1.32E-02

-2.00

-1.80

-1.60

-1.40

-1.20

-1.00

-0.80

-0.60

-0.40

-0.20

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

1mg/L -23°C, pH 8 - 0.5%, 1%

0.50% 1%

Chris Keung E-59




y = -1.58E-05x - 2.09E-02

y = -1.48E-05x - 1.73E-02

y = -2.13E-05x - 6.46E-02

-0.14

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

6mg/L -4°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -8.01E-05x - 3.95E-02

y = -1.41E-04x - 5.26E-02

-0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.00

0.05

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

6mg/L -4°C, pH 6 - 0.5%, 1%

0.50% 1%

Chris Keung E-60




y = -8.37E-06x - 2.96E-03

y = 2.91E-07x - 6.25E-03

y = -1.74E-05x - 7.12E-03 -0.04

-0.04

-0.03

-0.03

-0.02

-0.02

-0.01

-0.01

0.00

0.01

0.01

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

6mg/L -23°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -4.61E-05x - 4.07E-02

y = -1.46E-04x - 5.33E-02

-0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

6mg/L -23°C, pH 6 - 0.5%, 1%

0.50% 1%

Chris Keung E-61




y = -1.95E-05x - 2.46E-02

y = -1.55E-05x - 1.83E-02

y = -3.42E-05x - 4.18E-02

-0.07

-0.06

-0.05

-0.04

-0.03

-0.02

-0.01

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

6mg/L -4°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -1.94E-04x - 6.65E-02

y = -3.59E-04x - 1.59E-01

-0.80

-0.70

-0.60

-0.50

-0.40

-0.30

-0.20

-0.10

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

6mg/L -4°C, pH 8 - 0.5%, 1%

0.50% 1%

Chris Keung E-62




y = -2.83E-05x + 7.53E-04

y = -3.48E-05x - 1.13E-03

y = -7.64E-05x - 2.98E-02 -0.16

-0.14

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.00

0.02

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

6mg/L -23°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -2.03E-04x - 4.87E-02

y = -3.29E-04x - 8.19E-02

-0.60

-0.50

-0.40

-0.30

-0.20

-0.10

0.00

0.10

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

6mg/L -23°C, pH 8 - 0.5%, 1%

0.50% 1%

Chris Keung E-63




y = -4.61E-06x - 7.71E-03

y = -1.26E-05x - 7.03E-03

y = -2.61E-05x - 1.51E-02 -0.06

-0.05

-0.04

-0.03

-0.02

-0.01

0.00

0.01

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

15mg/L -4°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -4.98E-05x - 1.95E-02

y = -1.08E-04x - 6.13E-02

-0.25

-0.20

-0.15

-0.10

-0.05

0.00

0.05

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

15mg/L -4°C, pH 6 - 0.5%, 1%

0.50% 1%

Chris Keung E-64




y = -8.83E-06x - 4.57E-03

y = -1.16E-05x - 2.79E-03

y = -1.34E-05x - 8.76E-03 -0.03

-0.03

-0.02

-0.02

-0.01

-0.01

0.00

0.01

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

15mg/L -23°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -8.31E-05x - 1.56E-02

y = -1.10E-04x - 5.85E-02

-0.25

-0.20

-0.15

-0.10

-0.05

0.00

0.05

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

15mg/L -23°C, pH 6 - 0.5%, 1%

0.50% 1%

Chris Keung E-65




y = -2.21E-05x - 1.69E-02

y = -3.20E-05x - 2.61E-02

y = -3.40E-05x - 3.17E-02 -0.09

-0.08

-0.07

-0.06

-0.05

-0.04

-0.03

-0.02

-0.01

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

15mg/L -4°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -7.14E-05x - 6.45E-02

y = -8.98E-05x - 1.20E-01

-0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

15mg/L -4°C, pH 8 - 0.5%, 1%

0.50% 1%

Chris Keung E-66




y = -2.71E-05x + 2.25E-03

y = -2.17E-05x - 3.20E-02

y = -4.23E-05x - 3.40E-03 -0.08

-0.07

-0.06

-0.05

-0.04

-0.03

-0.02

-0.01

0.00

0.01

0.02

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

15mg/L -23°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -1.13E-04x + 6.72E-03

y = -1.96E-04x - 4.21E-02 -0.40

-0.35

-0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.00

0.05

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

15mg/L -23°C, pH 8 - 0.5%, 1%

0.50% 1%

Chris Keung E-67




y = -6.18E-06x - 1.17E-03 y = -6.35E-06x - 8.73E-03

y = -4.43E-06x - 3.89E-02

-0.10

-0.09

-0.08

-0.07

-0.06

-0.05

-0.04

-0.03

-0.02

-0.01

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

30mg/L -4°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -2.32E-05x - 4.79E-02

y = -5.67E-05x - 4.64E-02

-0.14

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

30mg/L -4°C, pH 6 - 0.5%, 1%

0.50% 1%

Chris Keung E-68




y = -1.50E-05x - 9.59E-03

y = -1.81E-05x - 8.33E-03

y = -6.20E-06x - 1.84E-02 -0.04-0.04-0.03-0.03-0.02-0.02-0.01-0.010.000.010.010.02

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

30mg/L -23°C, pH 6 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -3.85E-05x - 5.47E-02

y = -9.99E-05x - 3.10E-02

-0.20

-0.18

-0.16

-0.14

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

30mg/L -23°C, pH 6 - 0.5%, 1%

0.50% 1%

Chris Keung E-69




y = -9.06E-06x - 9.21E-03

y = -2.24E-05x - 5.46E-04

y = -2.30E-05x - 1.89E-02 -0.06

-0.05

-0.04

-0.03

-0.02

-0.01

0.00

0.01

0.02

0 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

30mg/L -4°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -2.68E-05x - 3.84E-02

y = -6.13E-05x - 5.90E-02

-0.16

-0.14

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

30mg/L -4°C, pH 8 - 0.5%, 1%

0.50% 1%

Chris Keung E-70




y = -5.02E-06x - 3.85E-02

y = -1.99E-05x - 3.12E-02

y = -4.08E-05x - 1.71E-02 -0.09

-0.08

-0.07

-0.06

-0.05

-0.04

-0.03

-0.02

-0.01

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

30mg/L -23°C, pH 8 - 0%, 0.01%, 0.1%

0% 0.01% 0.10%

y = -7.22E-05x - 5.41E-02

y = -1.22E-04x - 3.02E-02

-0.25

-0.20

-0.15

-0.10

-0.05

0.000 200 400 600 800 1000 1200 1400 1600

Ln (C

/Co)

Time (min)

30mg/L -23°C, pH 8 - 0.5%, 1%

0.50% 1%

Chris Keung F-1


F. EPANET-MSX CODE

Chris Keung F-2


F.1 EPANET HYDRAULIC MODEL CODE (.INP FILE)

[TITLE] EPANET – Hydraulic Model (Example Network 2) [JUNCTIONS] ;ID Elev Demand Pattern 1 50 -694.4 2 ; 2 100 8 ; 3 60 15 ; 4 60 8 ; 5 100 8 ; 6 125 5 ; 7 160 5 ; 8 110 9 ; 9 180 14 ; 10 130 5 ; 11 185 35 ; 12 210 16 ; 13 210 2 ; 14 200 2 ; 15 190 2 ; 16 150 20 ; 17 180 20 ; 18 100 20 ; 19 150 5 ; 20 170 19 ; 21 150 16 ; 22 200 10 ; 23 230 8 ; 24 190 11 ; 25 230 6 ; 27 130 8 ; 28 110 0 ; 29 110 7 ; 30 130 3 ; 31 190 17 ; 32 110 17 ; 33 180 1.5 ; 34 190 1.5 ; 35 110 0 ; 36 110 1 ; [RESERVOIRS] ;ID Head Pattern [TANKS] ;ID Elevation InitLevel MinLevel MaxLevel Diameter MinVol VolCurve 26 210 56.7 50 70 50 0 ;

Chris Keung F-3


[PIPES] ;ID Node1 Node2 Length Diameter Roughness MinorLoss Status 1 1 2 2400 12 100 0 Open ; 2 2 5 800 12 100 0 Open ; 3 2 3 1300 8 100 0 Open ; 4 3 4 1200 8 100 0 Open ; 5 4 5 1000 12 100 0 Open ; 6 5 6 1200 12 100 0 Open ; 7 6 7 2700 12 100 0 Open ; 8 7 8 1200 12 140 0 Open ; 9 7 9 400 12 100 0 Open ;

10 8 10 1000 8 140 0 Open ; 11 9 11 700 12 100 0 Open ; 12 11 12 1900 12 100 0 Open ; 13 12 13 600 12 100 0 Open ; 14 13 14 400 12 100 0 Open ; 15 14 15 300 12 100 0 Open ; 16 13 16 1500 8 100 0 Open ; 17 15 17 1500 8 100 0 Open ; 18 16 17 600 8 100 0 Open ; 19 17 18 700 12 100 0 Open ; 20 18 32 350 12 100 0 Open ; 21 16 19 1400 8 100 0 Open ; 22 14 20 1100 12 100 0 Open ; 23 20 21 1300 8 100 0 Open ; 24 21 22 1300 8 100 0 Open ; 25 20 22 1300 8 100 0 Open ; 26 24 23 600 12 100 0 Open ; 27 15 24 250 12 100 0 Open ; 28 23 25 300 12 100 0 Open ; 29 25 26 200 12 100 0 Open ; 30 25 31 600 12 100 0 Open ; 31 31 27 400 8 100 0 Open ; 32 27 29 400 8 100 0 Open ; 34 29 28 700 8 100 0 Open ; 35 22 33 1000 8 100 0 Open ; 36 33 34 400 8 100 0 Open ; 37 32 19 500 8 100 0 Open ; 38 29 35 500 8 100 0 Open ; 39 35 30 1000 8 100 0 Open ; 40 28 35 700 8 100 0 Open ; 41 28 36 300 8 100 0 Open ; [PUMPS] ;ID Node1 Node2 Parameters [VALVES] ;ID Node1 Node2 Diameter Type Setting MinorLoss [TAGS]

Chris Keung F-4


[DEMANDS] ;Junction Demand Pattern Category [STATUS] ;ID Status/Setting [PATTERNS] ;ID Multipliers ;Demand Pattern 1 .46 .46 .46 .46 .46 .46 1 .27 .27 .27 .27 .27 .27 1 .31 .31 .31 .31 .31 .31 1 .33 .33 .33 .33 .33 .33 1 .39 .39 .39 .39 .39 .39 1 .83 .83 .83 .83 .83 .83 1 1.38 1.38 1.38 1.38 1.38 1.38 1 1.58 1.58 1.58 1.58 1.58 1.58 1 1.67 1.67 1.67 1.67 1.67 1.67 1 1.51 1.51 1.51 1.51 1.51 1.51 1 1.46 1.46 1.46 1.46 1.46 1.46 1 1.3 1.3 1.3 1.3 1.3 1.3 1 1.17 1.17 1.17 1.17 1.17 1.17 1 1.14 1.14 1.14 1.14 1.14 1.14 1 1.1 1.1 1.1 1.1 1.1 1.1 1 1.11 1.11 1.11 1.11 1.11 1.11 1 1.25 1.25 1.25 1.25 1.25 1.25 1 1.37 1.37 1.37 1.37 1.37 1.37 1 1.29 1.29 1.29 1.29 1.29 1.29 1 1.27 1.27 1.27 1.27 1.27 1.27 1 1.19 1.19 1.19 1.19 1.19 1.19 1 .98 .98 .98 .98 .98 .98 1 .67 .67 .67 .67 .67 .67 1 .5 .5 .5 .5 .5 .5 1 .46 .46 .46 .46 .46 .46 1 .27 .27 .27 .27 .27 .27 1 .31 .31 .31 .31 .31 .31 1 .33 .33 .33 .33 .33 .33 1 .39 .39 .39 .39 .39 .39 1 .83 .83 .83 .83 .83 .83 1 1.38 1.38 1.38 1.38 1.38 1.38 1 1.58 1.58 1.58 1.58 1.58 1.58 1 1.67 1.67 1.67 1.67 1.67 1.67 1 1.51 1.51 1.51 1.51 1.51 1.51 1 1.46 1.46 1.46 1.46 1.46 1.46 1 1.3 1.3 1.3 1.3 1.3 1.3 1 1.17 1.17 1.17 1.17 1.17 1.17 1 1.14 1.14 1.14 1.14 1.14 1.14 1 1.1 1.1 1.1 1.1 1.1 1.1 1 1.11 1.11 1.11 1.11 1.11 1.11 1 1.25 1.25 1.25 1.25 1.25 1.25 1 1.37 1.37 1.37 1.37 1.37 1.37 1 1.29 1.29 1.29 1.29 1.29 1.29 1 1.27 1.27 1.27 1.27 1.27 1.27

Chris Keung F-5


1 1.19 1.19 1.19 1.19 1.19 1.19 1 .98 .98 .98 .98 .98 .98 1 .67 .67 .67 .67 .67 .67 1 .5 .5 .5 .5 .5 .5 ;Pump Station Outflow Pattern 2 .96 .96 .96 .96 .96 .96 2 .96 .96 .96 .96 .96 .96 2 .96 .96 .96 .96 .96 .96 2 .96 .96 .96 .96 .96 .96 2 .96 .96 .96 .96 .96 .96 2 .96 .96 .96 .96 .96 .96 2 .62 .62 .62 .62 .62 .62 2 0 0 0 0 0 0 2 0 0 0 0 0 0 2 0 0 0 0 0 0 2 0 0 0 0 0 0 2 0 0 0 0 0 0 2 .8 .8 .8 .8 .8 .8 2 1 1 1 1 1 1 2 1 1 1 1 1 1 2 1 1 1 1 1 1 2 1 1 1 1 1 1 2 .15 .15 .15 .15 .15 .15 2 0 0 0 0 0 0 2 0 0 0 0 0 0 2 0 0 0 0 0 0 2 0 0 0 0 0 0 2 0 0 0 0 0 0 2 0 0 0 0 0 0 2 .96 .96 .96 .96 .96 .96 2 .96 .96 .96 .96 .96 .96 2 .96 .96 .96 .96 .96 .96 2 .96 .96 .96 .96 .96 .96 2 .96 .96 .96 .96 .96 .96 2 .96 .96 .96 .96 .96 .96 2 .62 .62 .62 .62 .62 .62 2 0 0 0 0 0 0 2 0 0 0 0 0 0 2 0 0 0 0 0 0 2 0 0 0 0 0 0 2 0 0 0 0 0 0 2 .8 .8 .8 .8 .8 .8 2 1 1 1 1 1 1 2 1 1 1 1 1 1 2 1 1 1 1 1 1 2 1 1 1 1 1 1 2 .15 .15 .15 .15 .15 .15 2 0 0 0 0 0 0 2 0 0 0 0 0 0 2 0 0 0 0 0 0 2 0 0 0 0 0 0 2 0 0 0 0 0 0 2 0 0 0 0 0 0

Chris Keung F-6


[CURVES] ;ID X-Value Y-Value [CONTROLS] [RULES] [ENERGY] Global Efficiency 75 Global Price 0.0 Demand Charge 0.0 [EMITTERS] ;Junction Coefficient [QUALITY] ;Node InitQual [SOURCES] ;Node Type Quality Pattern [REACTIONS] ;Type Pipe/Tank Coefficient [REACTIONS] Order Bulk 0 Order Tank 0 Order Wall 0 Global Bulk 0 Global Wall 0.0 Limiting Potential 0.0 Roughness Correlation 0.0 [MIXING] ;Tank Model [TIMES] Duration 192 HOURS Hydraulic Timestep 10 MINUTES Quality Timestep 30 SECONDS Pattern Timestep 10 MINUTES Pattern Start 0:00 Report Timestep 0:10 Report Start 148 Start ClockTime 12 am Statistic NONE [REPORT] Status No Summary No Page 0 [OPTIONS] Units GPM

Chris Keung F-7


Headloss H-W Specific Gravity 1.0 Viscosity 1.0 Trials 40 Accuracy 0.001 CHECKFREQ 2 MAXCHECK 10 DAMPLIMIT 0 Unbalanced Continue 10 Pattern 1 Demand Multiplier 1.0 Emitter Exponent 0.5 Quality AGE Diffusivity 1.0 Tolerance 0.01 [COORDINATES] ;Node X-Coord Y-Coord 1 21.00 4.00 2 19.00 20.00 3 11.00 21.00 4 14.00 28.00 5 19.00 25.00 6 28.00 23.00 7 36.00 39.00 8 38.00 30.00 9 36.00 42.00 10 37.00 23.00 11 37.00 49.00 12 39.00 60.00 13 38.00 64.00 14 38.00 66.00 15 37.00 69.00 16 27.00 65.00 17 27.00 69.00 18 23.00 68.00 19 21.00 59.00 20 45.00 68.00 21 51.00 62.00 22 54.00 69.00 23 35.00 74.00 24 37.00 71.00 25 35.00 76.00 27 39.00 87.00 28 49.00 85.00 29 42.00 86.00 30 47.00 80.00 31 37.00 80.00 32 23.00 64.00 33 56.00 73.00 34 56.00 77.00 35 43.00 81.00 36 53.00 87.00 26 33.00 76.00

Chris Keung F-8


[VERTICES] ;Link X-Coord Y-Coord [LABELS] ;X-Coord Y-Coord Label & Anchor Node 24.00 7.00 "Pump Station" 26.76 77.42 "Tank" [BACKDROP] DIMENSIONS 8.75 -0.15 58.25 91.15 UNITS None FILE OFFSET 0.00 0.00 [REPORT] STATUS NO NODES ALL PRESSURE YES DEMAND YES PRESSURE PRECISION 1 QUALITY YES [END]

Chris Keung F-9


F.2 MSX CODE SHORT DURATION, HIGH CONCENTRATION

[TITLE] EPANET-MSX FILE (SHORT DURATION INTRUSION, HIGH CONCENTRATION W/ TANK BOOSTER) [OPTIONS] AREA_UNITS M2 ; SURFACE CONCENTRATION IS MASS/M2 RATE_UNITS HR ; REACTION RATES ARE CONCENTRATION/HOUR SOLVER RK5 ; 5-TH ORDER RUNGE-KUTTA INTEGRATOR TIMESTEP 300 ; 300 SECOND (5 MIN) SOLUTION TIME STEP RTOL 0.001 ; RELATIVE CONCENTRATION TOLERANCE ATOL 0.0001 ; ABSOLUTE CONCENTRATION TOLERANCE [SPECIES] BULK ECOLI1 # ; ECOLI (CL2) BULK ECOLI2 # ; ECOLI (CHLORAMINE) BULK ECOLI3 # ; ECOLI (CLO2) BULK ECOLI4 # ; ECOLI (H202) BULK ECOLI5 # ; ECOLI (HSP) BULK GIARDIA1 # ; GIARDIA (CL2) BULK GIARDIA2 # ; GIARDIA (CHLORAMINE) BULK GIARDIA3 # ; GIARDIA (CLO2) BULK GIARDIA4 # ; GIARDIA (H202) BULK GIARDIA5 # ; GIARDIA (HSP) BULK CL2 MG ; CL2 RESIDUAL (mg/L) BULK TOTCL MG ; CHLORAMINE RESIDUAL (mg/L) BULK CLO2 MG ; CLO2 RESIDUAL (mg/L) BULK HP MG ; H202 RESIDUAL (mg/L) BULK HSP MG ; HSP RESIDUAL (mg/L) [COEFFICIENTS] CONSTANT Kd1 -0.0216 ; Cl2 DECAY COEFFICIENT (1/hour) CONSTANT Kd2 -0.0029 ; CHLORAMINE DECAY COEFFICIENT (1/hour) CONSTANT Kd3 -0.0120 ; CLO2 DECAY COEFFICIENT (1/hour) CONSTANT Kd4 -0.0012 ; H202 DECAY COEFFICIENT (1/hour) CONSTANT Kd5 -0.0046 ; HSP DECAY COEFFICIENT (1/hour) CONSTANT Kpl1 -660 ; ECOLI (low) - CL2 INACT. CONSTANT (L/mg hour) CONSTANT Kpl2 -2.64 ; ECOLI (low) - CHLORAMINE INACT CONSTANT (L/mg hour) CONSTANT Kpl3 -988.62 ; ECOLI (low) - CLO2 INACT CONSTANT (L/mg hour) CONSTANT Kpl4 -35.58 ; ECOLI (low) - H202 INACT CONSTANT (L/mg hour) CONSTANT Kpl5 -645 ; ECOLI (low) - INACT CONSTANT (L/mg hour) CONSTANT Kph1 -8.019 ; GIARDIA (high)- CL2 INACT CONSTANT (L/mg hour) CONSTANT Kph2 -0.376 ; GIARDIA (high)- CHLORAMINE INACT CONSTANT (L/mg hour) CONSTANT Kph3 -27.454 ; GIARDIA (high)- CLO2 INACT CONSTANT (L/mg hour) CONSTANT Kph4 -0.432 ; GIARDIA (high)- H202 INACT CONSTANT (L/mg hour) CONSTANT Kph5 -7.837 ; GIARDIA (high)- HSP INACT CONSTANT (L/mg hour) [TERMS]

Chris Keung F-10


[PIPES] ;TYPE SPECIESID EXPRESSION RATE CL2 Kd1*CL2 ; BULK CL2 DECAY RATE TOTCL Kd2*TOTCL ; BULK CHLORAMINE DECAY RATE CLO2 Kd3*CLO2 ; BULK CLO2 DECAY RATE HP Kd4*HP ; BULK H2O2 DECAY RATE HSP Kd5*HSP ; BULK HSP DECAY RATE ECOLI1 Kpl1*CL2*ECOLI1 ; ECOLI, Inactivation (CL2) RATE ECOLI2 Kpl2*TOTCL*ECOLI2 ; ECOLI, Inactivation (CHLORAMINE) RATE ECOLI3 Kpl3*CLO2*ECOLI3 ; ECOLI, Inactivation (CLO2) RATE ECOLI4 Kpl4*HP*ECOLI4 ; ECOLI, Inactivation (H2O2) RATE ECOLI5 Kpl5*HSP*ECOLI5 ; ECOLI, Inactivation (HSP) RATE GIARDIA1 Kph1*CL2*GIARDIA1 ; GIARDIA, Inactivation (CL2) RATE GIARDIA2 Kph2*TOTCL*GIARDIA2 ; GIARDIA, Inactivation (CHLORAMINE) RATE GIARDIA3 Kph3*CLO2*GIARDIA3 ; GIARDIA, Inactivation (CLO2) RATE GIARDIA4 Kph4*HP*GIARDIA4 ; GIARDIA, Inactivation (H2O2) RATE GIARDIA5 Kph5*HSP*GIARDIA5 ; GIARDIA, Inactivation (HSP) [TANKS] [SOURCES] ;sourceType nodeID speciesID strength (patternID) ;INTRUSION - # PATHOGENS INTRUDING (5210 organisms/L) AT NODE 12 FLOWPACED 12 ECOLI1 5210 3 FLOWPACED 12 ECOLI2 5210 3 FLOWPACED 12 ECOLI3 5210 3 FLOWPACED 12 ECOLI4 5210 3 FLOWPACED 12 ECOLI5 5210 3 FLOWPACED 12 GIARDIA1 5210 3 FLOWPACED 12 GIARDIA2 5210 3 FLOWPACED 12 GIARDIA3 5210 3 FLOWPACED 12 GIARDIA4 5210 3 FLOWPACED 12 GIARDIA5 5210 3 ; INITIAL DOSING DISINFECTANT RESIDUAL AT NODE 1 (mg/L) SETPOINT 1 CL2 4 SETPOINT 1 TOTCL 3 SETPOINT 1 CLO2 0.8 SETPOINT 1 HP 6 SETPOINT 1 HSP 6 ; DISINFECTANT ADDED AT TANK (NODE 26) FLOWPACED 26 CL2 2 FLOWPACED 26 TOTCL 0.6 FLOWPACED 26 CLO2 0.15 FLOWPACED 26 HP 1.1 FLOWPACED 26 HSP 1.8

Chris Keung F-11


INITIAL DEMAND CAUSED BY INTRUSION AT NODE 12 (negative pattern) (mg/L) FLOWPACED 12 CL2 0.26 5 FLOWPACED 12 TOTCL 0 5 FLOWPACED 12 CLO2 0.03 5 FLOWPACED 12 HP 0.03 5 FLOWPACED 12 HSP 0 5 [QUALITY] [PATTERNS] ;ID Multipliers ;SHORT DURATION PATHOGEN INJECTION AT NODE 12 (10 minute intrusion every 48 hours) 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 1 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0

Chris Keung F-12


3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 ;SHORT DURATION INITIAL DEMAND AT NODE 12 (10 minute intrusion every 48 hours) 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 -1 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0

Chris Keung F-13


5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 [REPORT] NODES ALL SPECIES ECOLI1 YES SPECIES ECOLI2 YES SPECIES ECOLI3 YES SPECIES ECOLI4 YES SPECIES ECOLI5 YES SPECIES GIARDIA1 YES SPECIES GIARDIA2 YES SPECIES GIARDIA3 YES SPECIES GIARDIA4 YES SPECIES GIARDIA5 YES SPECIES CL2 YES SPECIES TOTCL YES SPECIES CLO2 YES SPECIES HP YES SPECIES HSP YES [END]

Chris Keung F-14


F.3 MSX CODE SHORT DURATION, LOW CONCENTRATION

[TITLE] EPANET-MSX FILE (SHORT DURATION INTRUSION - LOW CONCENTRATION - TANK BOOSTER) [OPTIONS] AREA_UNITS M2 ; SURFACE CONCENTRATION IS MASS/M2 RATE_UNITS HR ; REACTION RATES ARE CONCENTRATION/HOUR SOLVER RK5 ; 5-TH ORDER RUNGE-KUTTA INTEGRATOR TIMESTEP 300 ; 300 SECOND (5 MIN) SOLUTION TIME STEP RTOL 0.001 ; RELATIVE CONCENTRATION TOLERANCE ATOL 0.0001 ; ABSOLUTE CONCENTRATION TOLERANCE [SPECIES] BULK ECOLI1 # ; ECOLI (CL2) BULK ECOLI2 # ; ECOLI (CHLORAMINE) BULK ECOLI3 # ; ECOLI (CLO2) BULK ECOLI4 # ; ECOLI (H202) BULK ECOLI5 # ; ECOLI (HSP) BULK GIARDIA1 # ; GIARDIA (CL2) BULK GIARDIA2 # ; GIARDIA (CHLORAMINE) BULK GIARDIA3 # ; GIARDIA (CLO2) BULK GIARDIA4 # ; GIARDIA (H202) BULK GIARDIA5 # ; GIARDIA (HSP) BULK CL2 MG ; CL2 RESIDUAL (mg/L) BULK TOTCL MG ; CHLORAMINE RESIDUAL (mg/L) BULK CLO2 MG ; CLO2 RESIDUAL (mg/L) BULK HP MG ; H202 RESIDUAL (mg/L) BULK HSP MG ; HSP RESIDUAL (mg/L) [COEFFICIENTS] CONSTANT Kd1 -0.0216 ; Cl2 DECAY COEFFICIENT (1/hour) CONSTANT Kd2 -0.0029 ; CHLORAMINE DECAY COEFFICIENT (1/hour) CONSTANT Kd3 -0.0120 ; CLO2 DECAY COEFFICIENT (1/hour) CONSTANT Kd4 -0.0012 ; H202 DECAY COEFFICIENT (1/hour) CONSTANT Kd5 -0.0046 ; HSP DECAY COEFFICIENT (1/hour) CONSTANT Kpl1 -660 ; ECOLI (low) - CL2 INACT. CONSTANT (L/mg hour) CONSTANT Kpl2 -2.64 ; ECOLI (low) - CHLORAMINE INACT CONSTANT (L/mg hour) CONSTANT Kpl3 -988.62 ; ECOLI (low) - CLO2 INACT CONSTANT (L/mg hour) CONSTANT Kpl4 -35.58 ; ECOLI (low) - H202 INACT CONSTANT (L/mg hour) CONSTANT Kpl5 -645 ; ECOLI (low) - INACT CONSTANT (L/mg hour) CONSTANT Kph1 -8.019 ; GIARDIA (high)- CL2 INACT CONSTANT (L/mg hour) CONSTANT Kph2 -0.376 ; GIARDIA (high)- CHLORAMINE INACT CONSTANT (L/mg hour) CONSTANT Kph3 -27.454 ; GIARDIA (high)- CLO2 INACT CONSTANT (L/mg hour) CONSTANT Kph4 -0.432 ; GIARDIA (high)- H202 INACT CONSTANT (L/mg hour) CONSTANT Kph5 -7.837 ; GIARDIA (high)- HSP INACT CONSTANT (L/mg hour) [TERMS] [PIPES]

Chris Keung F-15


;TYPE SPECIESID EXPRESSION RATE CL2 Kd1*CL2 ; BULK CL2 DECAY RATE TOTCL Kd2*TOTCL ; BULK CHLORAMINE DECAY RATE CLO2 Kd3*CLO2 ; BULK CLO2 DECAY RATE HP Kd4*HP ; BULK H2O2 DECAY RATE HSP Kd5*HSP ; BULK HSP DECAY RATE ECOLI1 Kpl1*CL2*ECOLI1 ; ECOLI, Inactivation (CL2) RATE ECOLI2 Kpl2*TOTCL*ECOLI2 ; ECOLI, Inactivation (CHLORAMINE) RATE ECOLI3 Kpl3*CLO2*ECOLI3 ; ECOLI, Inactivation (CLO2) RATE ECOLI4 Kpl4*HP*ECOLI4 ; ECOLI, Inactivation (H2O2) RATE ECOLI5 Kpl5*HSP*ECOLI5 ; ECOLI, Inactivation (HSP) RATE GIARDIA1 Kph1*CL2*GIARDIA1 ; GIARDIA, Inactivation (CL2) RATE GIARDIA2 Kph2*TOTCL*GIARDIA2 ; GIARDIA, Inactivation (CHLORAMINE) RATE GIARDIA3 Kph3*CLO2*GIARDIA3 ; GIARDIA, Inactivation (CLO2) RATE GIARDIA4 Kph4*HP*GIARDIA4 ; GIARDIA, Inactivation (H2O2) RATE GIARDIA5 Kph5*HSP*GIARDIA5 ; GIARDIA, Inactivation (HSP) [TANKS] [SOURCES] ;sourceType nodeID speciesID strength (patternID) ;INTRUSION - # PATHOGENS INTRUDING (5210 organisms/L) AT NODE 12 FLOWPACED 12 ECOLI1 5210 3 FLOWPACED 12 ECOLI2 5210 3 FLOWPACED 12 ECOLI3 5210 3 FLOWPACED 12 ECOLI4 5210 3 FLOWPACED 12 ECOLI5 5210 3 FLOWPACED 12 GIARDIA1 5210 3 FLOWPACED 12 GIARDIA2 5210 3 FLOWPACED 12 GIARDIA3 5210 3 FLOWPACED 12 GIARDIA4 5210 3 FLOWPACED 12 GIARDIA5 5210 3 ; INITIAL DOSING DISINFECTANT RESIDUAL AT NODE 1 (mg/L) SETPOINT 1 CL2 1 SETPOINT 1 TOTCL 1 SETPOINT 1 CLO2 0.2 SETPOINT 1 HP 1 SETPOINT 1 HSP 1 ; DISINFECTANT ADDED AT TANK (NODE 26) FLOWPACED 26 CL2 0.5 FLOWPACED 26 TOTCL 0.3 FLOWPACED 26 CLO2 0.13 FLOWPACED 26 HP 0.3 FLOWPACED 26 HSP 0.2 INITIAL DEMAND CAUSED BY INTRUSION AT NODE 12 (negative pattern) (mg/L) FLOWPACED 12 CL2 0.26 5 FLOWPACED 12 TOTCL 0 5 FLOWPACED 12 CLO2 0.03 5

Chris Keung F-16


FLOWPACED 12 HP 0.03 5 FLOWPACED 12 HSP 0 5 [QUALITY] [PATTERNS] ;ID Multipliers ;SHORT DURATION PATHOGEN INJECTION AT NODE 12 (10 minute intrusion every 48 hours) 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 1 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0

Chris Keung F-17


3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 ;SHORT DURATION INITIAL DEMAND AT NODE 12 (10 minute intrusion every 48 hours) 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 -1 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0

Chris Keung F-18


[REPORT] NODES ALL SPECIES ECOLI1 YES SPECIES ECOLI2 YES SPECIES ECOLI3 YES SPECIES ECOLI4 YES SPECIES ECOLI5 YES SPECIES GIARDIA1 YES SPECIES GIARDIA2 YES SPECIES GIARDIA3 YES SPECIES GIARDIA4 YES SPECIES GIARDIA5 YES SPECIES CL2 YES SPECIES TOTCL YES SPECIES CLO2 YES SPECIES HP YES SPECIES HSP YES [END]

Chris Keung F-19


F.4 MSX CODE LONG DURATION, HIGH CONCENTRATION

[TITLE] EPANET-MSX FILE (LONG DURATION INTRUSION - HIGH CONCENTRATION- TANK BOOSTER) [OPTIONS] AREA_UNITS M2 ; SURFACE CONCENTRATION IS MASS/M2 RATE_UNITS HR ; REACTION RATES ARE CONCENTRATION/HOUR SOLVER RK5 ; 5-TH ORDER RUNGE-KUTTA INTEGRATOR TIMESTEP 300 ; 300 SECOND (5 MIN) SOLUTION TIME STEP RTOL 0.001 ; RELATIVE CONCENTRATION TOLERANCE ATOL 0.0001 ; ABSOLUTE CONCENTRATION TOLERANCE [SPECIES] BULK ECOLI1 # ; ECOLI (CL2) BULK ECOLI2 # ; ECOLI (CHLORAMINE) BULK ECOLI3 # ; ECOLI (CLO2) BULK ECOLI4 # ; ECOLI (H202) BULK ECOLI5 # ; ECOLI (HSP) BULK GIARDIA1 # ; GIARDIA (CL2) BULK GIARDIA2 # ; GIARDIA (CHLORAMINE) BULK GIARDIA3 # ; GIARDIA (CLO2) BULK GIARDIA4 # ; GIARDIA (H202) BULK GIARDIA5 # ; GIARDIA (HSP) BULK CL2 MG ; CL2 RESIDUAL (mg/L) BULK TOTCL MG ; CHLORAMINE RESIDUAL (mg/L) BULK CLO2 MG ; CLO2 RESIDUAL (mg/L) BULK HP MG ; H202 RESIDUAL (mg/L) BULK HSP MG ; HSP RESIDUAL (mg/L) [COEFFICIENTS] CONSTANT Kd1 -0.0216 ; Cl2 DECAY COEFFICIENT (1/hour) CONSTANT Kd2 -0.0029 ; CHLORAMINE DECAY COEFFICIENT (1/hour) CONSTANT Kd3 -0.0120 ; CLO2 DECAY COEFFICIENT (1/hour) CONSTANT Kd4 -0.0012 ; H202 DECAY COEFFICIENT (1/hour) CONSTANT Kd5 -0.0046 ; HSP DECAY COEFFICIENT (1/hour) CONSTANT Kpl1 -660 ; ECOLI (low) - CL2 INACT. CONSTANT (L/mg hour) CONSTANT Kpl2 -2.64 ; ECOLI (low) - CHLORAMINE INACT CONSTANT (L/mg hour) CONSTANT Kpl3 -988.62 ; ECOLI (low) - CLO2 INACT CONSTANT (L/mg hour) CONSTANT Kpl4 -35.58 ; ECOLI (low) - H202 INACT CONSTANT (L/mg hour) CONSTANT Kpl5 -645 ; ECOLI (low) - INACT CONSTANT (L/mg hour) CONSTANT Kph1 -8.019 ; GIARDIA (high)- CL2 INACT CONSTANT (L/mg hour) CONSTANT Kph2 -0.376 ; GIARDIA (high)- CHLORAMINE INACT CONSTANT (L/mg hour) CONSTANT Kph3 -27.454 ; GIARDIA (high)- CLO2 INACT CONSTANT (L/mg hour) CONSTANT Kph4 -0.432 ; GIARDIA (high)- H202 INACT CONSTANT (L/mg hour) CONSTANT Kph5 -7.837 ; GIARDIA (high)- HSP INACT CONSTANT (L/mg hour) [TERMS] [PIPES]

Chris Keung F-20


;TYPE SPECIESID EXPRESSION RATE CL2 Kd1*CL2 ; BULK CL2 DECAY RATE TOTCL Kd2*TOTCL ; BULK CHLORAMINE DECAY RATE CLO2 Kd3*CLO2 ; BULK CLO2 DECAY RATE HP Kd4*HP ; BULK H2O2 DECAY RATE HSP Kd5*HSP ; BULK HSP DECAY RATE ECOLI1 Kpl1*CL2*ECOLI1 ; ECOLI, Inactivation (CL2) RATE ECOLI2 Kpl2*TOTCL*ECOLI2 ; ECOLI, Inactivation (CHLORAMINE) RATE ECOLI3 Kpl3*CLO2*ECOLI3 ; ECOLI, Inactivation (CLO2) RATE ECOLI4 Kpl4*HP*ECOLI4 ; ECOLI, Inactivation (H2O2) RATE ECOLI5 Kpl5*HSP*ECOLI5 ; ECOLI, Inactivation (HSP) RATE GIARDIA1 Kph1*CL2*GIARDIA1 ; GIARDIA, Inactivation (CL2) RATE GIARDIA2 Kph2*TOTCL*GIARDIA2 ; GIARDIA, Inactivation (CHLORAMINE) RATE GIARDIA3 Kph3*CLO2*GIARDIA3 ; GIARDIA, Inactivation (CLO2) RATE GIARDIA4 Kph4*HP*GIARDIA4 ; GIARDIA, Inactivation (H2O2) RATE GIARDIA5 Kph5*HSP*GIARDIA5 ; GIARDIA, Inactivation (HSP) [TANKS] [SOURCES] ;sourceType nodeID speciesID strength (patternID) ;INTRUSION - # PATHOGENS INTRUDING (5210 organisms/L) AT NODE 12 FLOWPACED 12 ECOLI1 5210 3 FLOWPACED 12 ECOLI2 5210 3 FLOWPACED 12 ECOLI3 5210 3 FLOWPACED 12 ECOLI4 5210 3 FLOWPACED 12 ECOLI5 5210 3 FLOWPACED 12 GIARDIA1 5210 3 FLOWPACED 12 GIARDIA2 5210 3 FLOWPACED 12 GIARDIA3 5210 3 FLOWPACED 12 GIARDIA4 5210 3 FLOWPACED 12 GIARDIA5 5210 3 ; INITIAL DOSING DISINFECTANT RESIDUAL AT NODE 1 (mg/L) SETPOINT 1 CL2 4 SETPOINT 1 TOTCL 3 SETPOINT 1 CLO2 0.8 SETPOINT 1 HP 6 SETPOINT 1 HSP 6 ; DISINFECTANT ADDED AT TANK (NODE 26) FLOWPACED 26 CL2 2 FLOWPACED 26 TOTCL 0.6 FLOWPACED 26 CLO2 0.15 FLOWPACED 26 HP 1.1 FLOWPACED 26 HSP 1.8 INITIAL DEMAND CAUSED BY INTRUSION AT NODE 12 (negative pattern) (mg/L) FLOWPACED 12 CL2 0.26 5 FLOWPACED 12 TOTCL 0 5 FLOWPACED 12 CLO2 0.03 5 FLOWPACED 12 HP 0.03 5

Chris Keung F-21


FLOWPACED 12 HSP 0 5 [QUALITY] [PATTERNS] ;ID Multipliers ;LONG DURATION PATHOGEN INJECTION AT NODE 12 (1 hour intrusion every 48 hours) 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 1 1 1 1 1 1 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0

Chris Keung F-22


3 0 0 0 0 0 0 3 0 0 0 0 0 0 ;LONG DURATION INITIAL DEMAND AT NODE 12 (1 hour intrusion every 48 hours) 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 -1 -1 -1 -1 -1 -1 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 [REPORT]

Chris Keung F-23


NODES ALL SPECIES ECOLI1 YES SPECIES ECOLI2 YES SPECIES ECOLI3 YES SPECIES ECOLI4 YES SPECIES ECOLI5 YES SPECIES GIARDIA1 YES SPECIES GIARDIA2 YES SPECIES GIARDIA3 YES SPECIES GIARDIA4 YES SPECIES GIARDIA5 YES SPECIES CL2 YES SPECIES TOTCL YES SPECIES CLO2 YES SPECIES HP YES SPECIES HSP YES [END]

Chris Keung F-24


F.5 MSX CODE LONG DURATION, LOW CONCENTRATION

[TITLE] EPANET-MSX FILE (LONG DURATION INTRUSION - LOW CONCENTRATION - TANK BOOSTER) [OPTIONS] AREA_UNITS M2 ; SURFACE CONCENTRATION IS MASS/M2 RATE_UNITS HR ; REACTION RATES ARE CONCENTRATION/HOUR SOLVER RK5 ; 5-TH ORDER RUNGE-KUTTA INTEGRATOR TIMESTEP 300 ; 300 SECOND (5 MIN) SOLUTION TIME STEP RTOL 0.001 ; RELATIVE CONCENTRATION TOLERANCE ATOL 0.0001 ; ABSOLUTE CONCENTRATION TOLERANCE [SPECIES] BULK ECOLI1 # ; ECOLI (CL2) BULK ECOLI2 # ; ECOLI (CHLORAMINE) BULK ECOLI3 # ; ECOLI (CLO2) BULK ECOLI4 # ; ECOLI (H202) BULK ECOLI5 # ; ECOLI (HSP) BULK GIARDIA1 # ; GIARDIA (CL2) BULK GIARDIA2 # ; GIARDIA (CHLORAMINE) BULK GIARDIA3 # ; GIARDIA (CLO2) BULK GIARDIA4 # ; GIARDIA (H202) BULK GIARDIA5 # ; GIARDIA (HSP) BULK CL2 MG ; CL2 RESIDUAL (mg/L) BULK TOTCL MG ; CHLORAMINE RESIDUAL (mg/L) BULK CLO2 MG ; CLO2 RESIDUAL (mg/L) BULK HP MG ; H202 RESIDUAL (mg/L) BULK HSP MG ; HSP RESIDUAL (mg/L) [COEFFICIENTS] CONSTANT Kd1 -0.0216 ; Cl2 DECAY COEFFICIENT (1/hour) CONSTANT Kd2 -0.0029 ; CHLORAMINE DECAY COEFFICIENT (1/hour) CONSTANT Kd3 -0.0120 ; CLO2 DECAY COEFFICIENT (1/hour) CONSTANT Kd4 -0.0012 ; H202 DECAY COEFFICIENT (1/hour) CONSTANT Kd5 -0.0046 ; HSP DECAY COEFFICIENT (1/hour) CONSTANT Kpl1 -660 ; ECOLI (low) - CL2 INACT. CONSTANT (L/mg hour) CONSTANT Kpl2 -2.64 ; ECOLI (low) - CHLORAMINE INACT CONSTANT (L/mg hour) CONSTANT Kpl3 -988.62 ; ECOLI (low) - CLO2 INACT CONSTANT (L/mg hour) CONSTANT Kpl4 -35.58 ; ECOLI (low) - H202 INACT CONSTANT (L/mg hour) CONSTANT Kpl5 -645 ; ECOLI (low) - INACT CONSTANT (L/mg hour) CONSTANT Kph1 -8.019 ; GIARDIA (high)- CL2 INACT CONSTANT (L/mg hour) CONSTANT Kph2 -0.376 ; GIARDIA (high)- CHLORAMINE INACT CONSTANT (L/mg hour) CONSTANT Kph3 -27.454 ; GIARDIA (high)- CLO2 INACT CONSTANT (L/mg hour) CONSTANT Kph4 -0.432 ; GIARDIA (high)- H202 INACT CONSTANT (L/mg hour) CONSTANT Kph5 -7.837 ; GIARDIA (high)- HSP INACT CONSTANT (L/mg hour) [TERMS] [PIPES] ;TYPE SPECIESID EXPRESSION

Chris Keung F-25


RATE CL2 Kd1*CL2 ; BULK CL2 DECAY RATE TOTCL Kd2*TOTCL ; BULK CHLORAMINE DECAY RATE CLO2 Kd3*CLO2 ; BULK CLO2 DECAY RATE HP Kd4*HP ; BULK H2O2 DECAY RATE HSP Kd5*HSP ; BULK HSP DECAY RATE ECOLI1 Kpl1*CL2*ECOLI1 ; ECOLI, Inactivation (CL2) RATE ECOLI2 Kpl2*TOTCL*ECOLI2 ; ECOLI, Inactivation (CHLORAMINE) RATE ECOLI3 Kpl3*CLO2*ECOLI3 ; ECOLI, Inactivation (CLO2) RATE ECOLI4 Kpl4*HP*ECOLI4 ; ECOLI, Inactivation (H2O2) RATE ECOLI5 Kpl5*HSP*ECOLI5 ; ECOLI, Inactivation (HSP) RATE GIARDIA1 Kph1*CL2*GIARDIA1 ; GIARDIA, Inactivation (CL2) RATE GIARDIA2 Kph2*TOTCL*GIARDIA2 ; GIARDIA, Inactivation (CHLORAMINE) RATE GIARDIA3 Kph3*CLO2*GIARDIA3 ; GIARDIA, Inactivation (CLO2) RATE GIARDIA4 Kph4*HP*GIARDIA4 ; GIARDIA, Inactivation (H2O2) RATE GIARDIA5 Kph5*HSP*GIARDIA5 ; GIARDIA, Inactivation (HSP) [TANKS] [SOURCES] ;sourceType nodeID speciesID strength (patternID) ;INTRUSION - # PATHOGENS INTRUDING (5210 organisms/L) AT NODE 12 FLOWPACED 12 ECOLI1 5210 3 FLOWPACED 12 ECOLI2 5210 3 FLOWPACED 12 ECOLI3 5210 3 FLOWPACED 12 ECOLI4 5210 3 FLOWPACED 12 ECOLI5 5210 3 FLOWPACED 12 GIARDIA1 5210 3 FLOWPACED 12 GIARDIA2 5210 3 FLOWPACED 12 GIARDIA3 5210 3 FLOWPACED 12 GIARDIA4 5210 3 FLOWPACED 12 GIARDIA5 5210 3 ; INITIAL DOSING DISINFECTANT RESIDUAL AT NODE 1 (mg/L) SETPOINT 1 CL2 1 SETPOINT 1 TOTCL 1 SETPOINT 1 CLO2 0.2 SETPOINT 1 HP 1 SETPOINT 1 HSP 1 ; DISINFECTANT ADDED AT TANK (NODE 26) FLOWPACED 26 CL2 0.5 FLOWPACED 26 TOTCL 0.3 FLOWPACED 26 CLO2 0.13 FLOWPACED 26 HP 0.3 FLOWPACED 26 HSP 0.2 INITIAL DEMAND CAUSED BY INTRUSION AT NODE 12 (negative pattern) (mg/L) FLOWPACED 12 CL2 0.26 5 FLOWPACED 12 TOTCL 0 5 FLOWPACED 12 CLO2 0.03 5 FLOWPACED 12 HP 0.03 5 FLOWPACED 12 HSP 0 5

Chris Keung F-26


[QUALITY] [PATTERNS] ;ID Multipliers ;LONG DURATION PATHOGEN INJECTION AT NODE 12 (1 hour intrusion every 48 hours) 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 1 1 1 1 1 1 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0 3 0 0 0 0 0 0

Chris Keung F-27


;LONG DURATION INITIAL DEMAND AT NODE 12 (1 hour intrusion every 48 hours) 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 -1 -1 -1 -1 -1 -1 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 0 5 0 0 0 0 0 [REPORT] NODES ALL SPECIES ECOLI1 YES

Chris Keung F-28


SPECIES ECOLI2 YES SPECIES ECOLI3 YES SPECIES ECOLI4 YES SPECIES ECOLI5 YES SPECIES GIARDIA1 YES SPECIES GIARDIA2 YES SPECIES GIARDIA3 YES SPECIES GIARDIA4 YES SPECIES GIARDIA5 YES SPECIES CL2 YES SPECIES TOTCL YES SPECIES CLO2 YES SPECIES HP YES SPECIES HSP YES [END]

re-evaluating secondary disinfectants as sentinels … · 2015. 11. 29. · table 5-1: estimation...

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